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Zhou J, Liu C, Shi Z, Li X, Chang C, Zhi W, Zhou S. Application of ultrasound-based radiomics models of breast masses to predict invasive components of encapsulated papillary carcinoma. Quant Imaging Med Surg 2023; 13:6887-6898. [PMID: 37869304 PMCID: PMC10585530 DOI: 10.21037/qims-22-1069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 09/01/2023] [Indexed: 10/24/2023]
Abstract
Background Axillary lymph node (ALN) metastasis is seen in encapsulated papillary carcinoma (EPC), mostly with an invasive component (INV). Radiomics can offer more information beyond subjective grayscale and color Doppler ultrasound (US) image interpretation. This study aimed to develop radiomics models for predicting an INV of EPC in the breast based on US images. Methods This study retrospectively enrolled 105 patients (107 masses) with a pathological diagnosis of EPC from January 2016 to April 2021, and all masses had preoperative US images. Of the 107 masses, 64 were randomized to a training set and 43 to a test set. US and clinical features were analyzed to identify features associated with INVs. Then, based on the manually segmented US images to obtain radiomics features, the models to predict INVs were built with 5 ensemble machine learning classifiers. We estimated the performance of the predictive models using accuracy, the area under the receiver operating characteristic (ROC) curve (AUC), sensitivity, and specificity. Results The mean age was 63.71 years (range, 31 to 85 years); the mean size of tumors was 23.40 mm (range, 9 to 120 mm). Among all clinical and US features, only shape was statistically different between EPC with INVs and those without (P<0.05). In this study, the models based on Random Under Sampling (RUS) Boost, Random Forest, XGBoost, AdaBoost, and Easy Ensemble methods had good performance, among which RUS Boost had the best performance with an AUC of 0.875 [95% confidence interval (CI): 0.750-0.974] in the test set. Conclusions Radiomics prediction models were effective in predicting the INV of EPC, whereas clinical and US features demonstrated relatively decreased predictive utility.
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Affiliation(s)
- Jin Zhou
- Department of Ultrasound, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Chaoxu Liu
- Department of Ultrasound, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhaoting Shi
- Department of Ultrasound, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Xiaokang Li
- Department of Electronic Engineering, Fudan University, Shanghai, China
| | - Cai Chang
- Department of Ultrasound, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Wenxiang Zhi
- Department of Ultrasound, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Shichong Zhou
- Department of Ultrasound, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
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202
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Sewanywa L, Hale M, Michelow P, Mayne E, Wiggill T. Validation of the Xpert Breast Cancer STRAT 4 Assay on the GeneXpert instrument to Assess Hormone Receptor, Ki67, and HER2 Gene Expression Status in Breast Cancer Tissue Samples. Appl Immunohistochem Mol Morphol 2023; 31:613-620. [PMID: 37800656 DOI: 10.1097/pai.0000000000001149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Accepted: 07/19/2023] [Indexed: 10/07/2023]
Abstract
Breast cancer is the commonest cause of cancer-related mortality in African females where patients often present later and with advanced disease. Causes for delayed diagnosis include restricted diagnostic access and international controversy on interpretation of ancillary tests like immunohistochemistry (IHC). Fine needle aspirates (FNAC) are an attractive alternative although may have reduced sensitivity. The Xpert Breast Cancer STRAT4 (STRAT4) (CE-IVD*) assay (Cepheid, Sunnyvale) is a semi-quantitative reverse-transcription polymerase chain reaction assay which detects messenger RNA (mRNA) expression in breast samples for estrogen receptor ( ESR1 ), progesterone receptor ( PGR1 ), human epidermal growth factor receptor/Erb-B2 receptor tyrosine kinase 2 (HER2/ ERBB2 ) and the proliferation marker, MKi67 . We assessed the performance of this assay on both formalin-fixed paraffin-embedded (FFPE, n=31) and matched FNAC (n=20) samples from patients presenting with breast cancer to the Johannesburg academic hospitals. IHC and Fluorescent in situ hybridization analysis (performed on HER2-indeterminate samples) was compared with the mRNA expression of the corresponding target genes in FFPE samples, and mRNA expression on FNAC samples was compared with the FFPE results for both mRNA expression and IHC. Concordance between IHC/FISH and Xpert Breast Cancer STRAT4 in FFPE and FNAC samples using the Quick lysis (Q) method (a research-use-only modification of the validated FFPE-lysis method), showed an overall percentage agreement for ESR1 expression of 90.3% and 81.3%, and for PGR1 expression at 86.7% and 81.3% respectively in FFPE and FNAC samples. Concordance was lowest for Ki67 expression, using a binary IHC cutoff for Ki67 positivity at ≥20% staining) at 83.9% and 62.5%, for FFPE and FNAC samples, respectively. This suggests that the STRAT4 assay may be a useful ancillary test in determining HR and Ki67 status in FFPE samples and that use on FNAC samples may be feasible. Future studies should expand the sample numbers and establish locally relevant cutoffs.
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Affiliation(s)
- Lina Sewanywa
- Departments of Molecular Medicine and Haematology
- National Health Laboratory Service, Johannesburg
| | - Martin Hale
- Anatomical Pathology, School of Pathology, Faculty of Health Sciences, University of Witwatersrand
| | - Pamela Michelow
- Anatomical Pathology, School of Pathology, Faculty of Health Sciences, University of Witwatersrand
- National Health Laboratory Service, Johannesburg
| | - Elizabeth Mayne
- National Health Laboratory Service, Johannesburg
- Department of Pathology, Division of Immunology, Faculty of Health Sciences, University of Cape Town, Cape Town
| | - Tracey Wiggill
- National Health Laboratory Service, Johannesburg
- Division of Immunology and Medical Microbiology, Faculty of Medicine and Health Sciences, University of Stellenbosch, Stellenbosch, South Africa
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203
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Pop CF, Nziki LD, El Helou E, Moreau M, Radermecker M, Larsimont D, Veys I, De Neubourg F. Axillary Surgical Attitude Changing with Retrospective Application of ACOSOG Z0011 Eligible Criteria: An Institutional Evaluation. Eur J Breast Health 2023; 19:318-324. [PMID: 37795004 PMCID: PMC10546802 DOI: 10.4274/ejbh.galenos.2023.2023-6-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Accepted: 09/14/2023] [Indexed: 10/06/2023]
Abstract
Objective Sentinel lymph node biopsy (SLNB) represents the gold standard for axillary surgical staging. The aim of this study was to assess the proportion of axillary lymph node dissection (ALND) that could be avoided after retrospective application of the ACOSOG Z0011 criteria and to evaluate the shortterm complications associated with axillary surgery. Materials and Methods We reviewed breast cancer (BC) patients treated by primary breast-conserving surgery from 2012 to 2015. The percentage of SLNB vs ALND performed before and after the application of the ACOSOG Z0011 criteria was calculated. Complications were analyzed using crosstabs, with p<0.05 considered significant. Results Two hundred fifty one patients with a median age of 59.3 years were included. BC tumors had a median size of 13 mm and were mostly unifocal (83.9%). There were 30.3% with 1-2 metastatic lymph nodes (MLN). ALND was performed in 44.2%. The patients with 1-2 MLN, had only SLNB in 14.5% of cases. By applying the ACOSOG Z0011 criteria, ALND would have been avoided in 40.2% of patients. At least one postoperative complication was reported after SLNB or ALND for 45.7% and 74.7% of patients respectively. Seroma was the most frequent complication, and occurred in 29.3% of cases after SLNB and in 59.5% after ALND. Conclusion SNLB is the most commonly used axillary surgical staging procedure in this series (55.8%). With a retrospective application of the ACOSOG Z0011 criteria in our population, ALND could have been avoided for 40.2% patients. Post-operative complications rate was higher after ALND, with a seroma rate at 59.5%.
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Affiliation(s)
- C. Florin Pop
- Department of Surgical Oncology, Institut Jules Bordet, Université Libre de Bruxelles (ULB), Brussels, Belgium
| | - Lea Datin Nziki
- Department of Surgical Oncology, Institut Jules Bordet, Université Libre de Bruxelles (ULB), Brussels, Belgium
| | - Etienne El Helou
- Department of Surgical Oncology, Institut Jules Bordet, Université Libre de Bruxelles (ULB), Brussels, Belgium
| | - Michel Moreau
- Data Centre and Statistics, Institut Jules Bordet, ULB, Brussels, Belgium
| | | | - Denis Larsimont
- Department of Pathology, Institut Jules Bordet, ULB, Brussels, Belgium
| | - Isabelle Veys
- Department of Surgical Oncology, Institut Jules Bordet, Université Libre de Bruxelles (ULB), Brussels, Belgium
| | - Filip De Neubourg
- Department of Surgical Oncology, Institut Jules Bordet, Université Libre de Bruxelles (ULB), Brussels, Belgium
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Larsen M, Olstad CF, Koch HW, Martiniussen MA, Hoff SR, Lund-Hanssen H, Solli HS, Mikalsen KØ, Auensen S, Nygård J, Lång K, Chen Y, Hofvind S. AI Risk Score on Screening Mammograms Preceding Breast Cancer Diagnosis. Radiology 2023; 309:e230989. [PMID: 37847135 DOI: 10.1148/radiol.230989] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2023]
Abstract
Background Few studies have evaluated the role of artificial intelligence (AI) in prior screening mammography. Purpose To examine AI risk scores assigned to screening mammography in women who were later diagnosed with breast cancer. Materials and Methods Image data and screening information of examinations performed from January 2004 to December 2019 as part of BreastScreen Norway were used in this retrospective study. Prior screening examinations from women who were later diagnosed with cancer were assigned an AI risk score by a commercially available AI system (scores of 1-7, low risk of malignancy; 8-9, intermediate risk; and 10, high risk of malignancy). Mammographic features of the cancers based on the AI score were also assessed. The association between AI score and mammographic features was tested with a bivariate test. Results A total of 2787 prior screening examinations from 1602 women (mean age, 59 years ± 5.1 [SD]) with screen-detected (n = 1016) or interval (n = 586) cancers showed an AI risk score of 10 for 389 (38.3%) and 231 (39.4%) cancers, respectively, on the mammograms in the screening round prior to diagnosis. Among the screen-detected cancers with AI scores available two screening rounds (4 years) before diagnosis, 23.0% (122 of 531) had a score of 10. Mammographic features were associated with AI score for invasive screen-detected cancers (P < .001). Density with calcifications was registered for 13.6% (43 of 317) of screen-detected cases with a score of 10 and 4.6% (15 of 322) for those with a score of 1-7. Conclusion More than one in three cases of screen-detected and interval cancers had the highest AI risk score at prior screening, suggesting that the use of AI in mammography screening may lead to earlier detection of breast cancers. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Mehta in this issue.
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Affiliation(s)
- Marthe Larsen
- From the Section for Breast Cancer Screening (M.L., C.F.O., S.H.) and Department of Register Informatics (S.A., J.N.), Cancer Registry of Norway, P.O. Box 5313, 0304 Oslo, Norway; Department of Radiology, Stavanger University Hospital, Stavanger, Norway (H.W.K.); Faculty of Health Sciences, University of Stavanger, Stavanger, Norway (H.W.K.); Department of Radiology, Østfold Hospital Trust, Kalnes, Norway (M.A.M.); Institute of Clinical Medicine, University of Oslo, Oslo, Norway (M.A.M.); Department of Radiology, Ålesund Hospital, Møre og Romsdal Hospital Trust, Ålesund, Norway (S.R.H.); Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, National University for Science and Technology, Trondheim, Norway (S.R.H.); Department of Radiology and Nuclear Medicine, St Olavs University Hospital, Trondheim, Norway (H.L.H.); Department of Radiology, Hospital of Southern Norway, Kristiansand, Norway (H.S.S.); SPKI-The Norwegian Centre for Clinical Artificial Intelligence, University Hospital of North Norway, Tromsø, Norway (K.Ø.M.); Department of Clinical Medicine (K.Ø.M.) and Health and Care Sciences (S.H.), Faculty of Health Sciences, UiT-The Arctic University of Norway, Tromsø, Norway; Department of Translational Medicine, Diagnostic Radiology, Lund University, Lund, Sweden (K.L.); Unilabs Mammography Unit, Skåne University Hospital, Malmø, Sweden (K.L.); School of Medicine, University of Nottingham, Clinical Science Building, Nottingham City Hospital, Nottingham, United Kingdom (Y.C.)
| | - Camilla F Olstad
- From the Section for Breast Cancer Screening (M.L., C.F.O., S.H.) and Department of Register Informatics (S.A., J.N.), Cancer Registry of Norway, P.O. Box 5313, 0304 Oslo, Norway; Department of Radiology, Stavanger University Hospital, Stavanger, Norway (H.W.K.); Faculty of Health Sciences, University of Stavanger, Stavanger, Norway (H.W.K.); Department of Radiology, Østfold Hospital Trust, Kalnes, Norway (M.A.M.); Institute of Clinical Medicine, University of Oslo, Oslo, Norway (M.A.M.); Department of Radiology, Ålesund Hospital, Møre og Romsdal Hospital Trust, Ålesund, Norway (S.R.H.); Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, National University for Science and Technology, Trondheim, Norway (S.R.H.); Department of Radiology and Nuclear Medicine, St Olavs University Hospital, Trondheim, Norway (H.L.H.); Department of Radiology, Hospital of Southern Norway, Kristiansand, Norway (H.S.S.); SPKI-The Norwegian Centre for Clinical Artificial Intelligence, University Hospital of North Norway, Tromsø, Norway (K.Ø.M.); Department of Clinical Medicine (K.Ø.M.) and Health and Care Sciences (S.H.), Faculty of Health Sciences, UiT-The Arctic University of Norway, Tromsø, Norway; Department of Translational Medicine, Diagnostic Radiology, Lund University, Lund, Sweden (K.L.); Unilabs Mammography Unit, Skåne University Hospital, Malmø, Sweden (K.L.); School of Medicine, University of Nottingham, Clinical Science Building, Nottingham City Hospital, Nottingham, United Kingdom (Y.C.)
| | - Henrik W Koch
- From the Section for Breast Cancer Screening (M.L., C.F.O., S.H.) and Department of Register Informatics (S.A., J.N.), Cancer Registry of Norway, P.O. Box 5313, 0304 Oslo, Norway; Department of Radiology, Stavanger University Hospital, Stavanger, Norway (H.W.K.); Faculty of Health Sciences, University of Stavanger, Stavanger, Norway (H.W.K.); Department of Radiology, Østfold Hospital Trust, Kalnes, Norway (M.A.M.); Institute of Clinical Medicine, University of Oslo, Oslo, Norway (M.A.M.); Department of Radiology, Ålesund Hospital, Møre og Romsdal Hospital Trust, Ålesund, Norway (S.R.H.); Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, National University for Science and Technology, Trondheim, Norway (S.R.H.); Department of Radiology and Nuclear Medicine, St Olavs University Hospital, Trondheim, Norway (H.L.H.); Department of Radiology, Hospital of Southern Norway, Kristiansand, Norway (H.S.S.); SPKI-The Norwegian Centre for Clinical Artificial Intelligence, University Hospital of North Norway, Tromsø, Norway (K.Ø.M.); Department of Clinical Medicine (K.Ø.M.) and Health and Care Sciences (S.H.), Faculty of Health Sciences, UiT-The Arctic University of Norway, Tromsø, Norway; Department of Translational Medicine, Diagnostic Radiology, Lund University, Lund, Sweden (K.L.); Unilabs Mammography Unit, Skåne University Hospital, Malmø, Sweden (K.L.); School of Medicine, University of Nottingham, Clinical Science Building, Nottingham City Hospital, Nottingham, United Kingdom (Y.C.)
| | - Marit A Martiniussen
- From the Section for Breast Cancer Screening (M.L., C.F.O., S.H.) and Department of Register Informatics (S.A., J.N.), Cancer Registry of Norway, P.O. Box 5313, 0304 Oslo, Norway; Department of Radiology, Stavanger University Hospital, Stavanger, Norway (H.W.K.); Faculty of Health Sciences, University of Stavanger, Stavanger, Norway (H.W.K.); Department of Radiology, Østfold Hospital Trust, Kalnes, Norway (M.A.M.); Institute of Clinical Medicine, University of Oslo, Oslo, Norway (M.A.M.); Department of Radiology, Ålesund Hospital, Møre og Romsdal Hospital Trust, Ålesund, Norway (S.R.H.); Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, National University for Science and Technology, Trondheim, Norway (S.R.H.); Department of Radiology and Nuclear Medicine, St Olavs University Hospital, Trondheim, Norway (H.L.H.); Department of Radiology, Hospital of Southern Norway, Kristiansand, Norway (H.S.S.); SPKI-The Norwegian Centre for Clinical Artificial Intelligence, University Hospital of North Norway, Tromsø, Norway (K.Ø.M.); Department of Clinical Medicine (K.Ø.M.) and Health and Care Sciences (S.H.), Faculty of Health Sciences, UiT-The Arctic University of Norway, Tromsø, Norway; Department of Translational Medicine, Diagnostic Radiology, Lund University, Lund, Sweden (K.L.); Unilabs Mammography Unit, Skåne University Hospital, Malmø, Sweden (K.L.); School of Medicine, University of Nottingham, Clinical Science Building, Nottingham City Hospital, Nottingham, United Kingdom (Y.C.)
| | - Solveig R Hoff
- From the Section for Breast Cancer Screening (M.L., C.F.O., S.H.) and Department of Register Informatics (S.A., J.N.), Cancer Registry of Norway, P.O. Box 5313, 0304 Oslo, Norway; Department of Radiology, Stavanger University Hospital, Stavanger, Norway (H.W.K.); Faculty of Health Sciences, University of Stavanger, Stavanger, Norway (H.W.K.); Department of Radiology, Østfold Hospital Trust, Kalnes, Norway (M.A.M.); Institute of Clinical Medicine, University of Oslo, Oslo, Norway (M.A.M.); Department of Radiology, Ålesund Hospital, Møre og Romsdal Hospital Trust, Ålesund, Norway (S.R.H.); Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, National University for Science and Technology, Trondheim, Norway (S.R.H.); Department of Radiology and Nuclear Medicine, St Olavs University Hospital, Trondheim, Norway (H.L.H.); Department of Radiology, Hospital of Southern Norway, Kristiansand, Norway (H.S.S.); SPKI-The Norwegian Centre for Clinical Artificial Intelligence, University Hospital of North Norway, Tromsø, Norway (K.Ø.M.); Department of Clinical Medicine (K.Ø.M.) and Health and Care Sciences (S.H.), Faculty of Health Sciences, UiT-The Arctic University of Norway, Tromsø, Norway; Department of Translational Medicine, Diagnostic Radiology, Lund University, Lund, Sweden (K.L.); Unilabs Mammography Unit, Skåne University Hospital, Malmø, Sweden (K.L.); School of Medicine, University of Nottingham, Clinical Science Building, Nottingham City Hospital, Nottingham, United Kingdom (Y.C.)
| | - Håkon Lund-Hanssen
- From the Section for Breast Cancer Screening (M.L., C.F.O., S.H.) and Department of Register Informatics (S.A., J.N.), Cancer Registry of Norway, P.O. Box 5313, 0304 Oslo, Norway; Department of Radiology, Stavanger University Hospital, Stavanger, Norway (H.W.K.); Faculty of Health Sciences, University of Stavanger, Stavanger, Norway (H.W.K.); Department of Radiology, Østfold Hospital Trust, Kalnes, Norway (M.A.M.); Institute of Clinical Medicine, University of Oslo, Oslo, Norway (M.A.M.); Department of Radiology, Ålesund Hospital, Møre og Romsdal Hospital Trust, Ålesund, Norway (S.R.H.); Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, National University for Science and Technology, Trondheim, Norway (S.R.H.); Department of Radiology and Nuclear Medicine, St Olavs University Hospital, Trondheim, Norway (H.L.H.); Department of Radiology, Hospital of Southern Norway, Kristiansand, Norway (H.S.S.); SPKI-The Norwegian Centre for Clinical Artificial Intelligence, University Hospital of North Norway, Tromsø, Norway (K.Ø.M.); Department of Clinical Medicine (K.Ø.M.) and Health and Care Sciences (S.H.), Faculty of Health Sciences, UiT-The Arctic University of Norway, Tromsø, Norway; Department of Translational Medicine, Diagnostic Radiology, Lund University, Lund, Sweden (K.L.); Unilabs Mammography Unit, Skåne University Hospital, Malmø, Sweden (K.L.); School of Medicine, University of Nottingham, Clinical Science Building, Nottingham City Hospital, Nottingham, United Kingdom (Y.C.)
| | - Helene S Solli
- From the Section for Breast Cancer Screening (M.L., C.F.O., S.H.) and Department of Register Informatics (S.A., J.N.), Cancer Registry of Norway, P.O. Box 5313, 0304 Oslo, Norway; Department of Radiology, Stavanger University Hospital, Stavanger, Norway (H.W.K.); Faculty of Health Sciences, University of Stavanger, Stavanger, Norway (H.W.K.); Department of Radiology, Østfold Hospital Trust, Kalnes, Norway (M.A.M.); Institute of Clinical Medicine, University of Oslo, Oslo, Norway (M.A.M.); Department of Radiology, Ålesund Hospital, Møre og Romsdal Hospital Trust, Ålesund, Norway (S.R.H.); Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, National University for Science and Technology, Trondheim, Norway (S.R.H.); Department of Radiology and Nuclear Medicine, St Olavs University Hospital, Trondheim, Norway (H.L.H.); Department of Radiology, Hospital of Southern Norway, Kristiansand, Norway (H.S.S.); SPKI-The Norwegian Centre for Clinical Artificial Intelligence, University Hospital of North Norway, Tromsø, Norway (K.Ø.M.); Department of Clinical Medicine (K.Ø.M.) and Health and Care Sciences (S.H.), Faculty of Health Sciences, UiT-The Arctic University of Norway, Tromsø, Norway; Department of Translational Medicine, Diagnostic Radiology, Lund University, Lund, Sweden (K.L.); Unilabs Mammography Unit, Skåne University Hospital, Malmø, Sweden (K.L.); School of Medicine, University of Nottingham, Clinical Science Building, Nottingham City Hospital, Nottingham, United Kingdom (Y.C.)
| | - Karl Øyvind Mikalsen
- From the Section for Breast Cancer Screening (M.L., C.F.O., S.H.) and Department of Register Informatics (S.A., J.N.), Cancer Registry of Norway, P.O. Box 5313, 0304 Oslo, Norway; Department of Radiology, Stavanger University Hospital, Stavanger, Norway (H.W.K.); Faculty of Health Sciences, University of Stavanger, Stavanger, Norway (H.W.K.); Department of Radiology, Østfold Hospital Trust, Kalnes, Norway (M.A.M.); Institute of Clinical Medicine, University of Oslo, Oslo, Norway (M.A.M.); Department of Radiology, Ålesund Hospital, Møre og Romsdal Hospital Trust, Ålesund, Norway (S.R.H.); Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, National University for Science and Technology, Trondheim, Norway (S.R.H.); Department of Radiology and Nuclear Medicine, St Olavs University Hospital, Trondheim, Norway (H.L.H.); Department of Radiology, Hospital of Southern Norway, Kristiansand, Norway (H.S.S.); SPKI-The Norwegian Centre for Clinical Artificial Intelligence, University Hospital of North Norway, Tromsø, Norway (K.Ø.M.); Department of Clinical Medicine (K.Ø.M.) and Health and Care Sciences (S.H.), Faculty of Health Sciences, UiT-The Arctic University of Norway, Tromsø, Norway; Department of Translational Medicine, Diagnostic Radiology, Lund University, Lund, Sweden (K.L.); Unilabs Mammography Unit, Skåne University Hospital, Malmø, Sweden (K.L.); School of Medicine, University of Nottingham, Clinical Science Building, Nottingham City Hospital, Nottingham, United Kingdom (Y.C.)
| | - Steinar Auensen
- From the Section for Breast Cancer Screening (M.L., C.F.O., S.H.) and Department of Register Informatics (S.A., J.N.), Cancer Registry of Norway, P.O. Box 5313, 0304 Oslo, Norway; Department of Radiology, Stavanger University Hospital, Stavanger, Norway (H.W.K.); Faculty of Health Sciences, University of Stavanger, Stavanger, Norway (H.W.K.); Department of Radiology, Østfold Hospital Trust, Kalnes, Norway (M.A.M.); Institute of Clinical Medicine, University of Oslo, Oslo, Norway (M.A.M.); Department of Radiology, Ålesund Hospital, Møre og Romsdal Hospital Trust, Ålesund, Norway (S.R.H.); Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, National University for Science and Technology, Trondheim, Norway (S.R.H.); Department of Radiology and Nuclear Medicine, St Olavs University Hospital, Trondheim, Norway (H.L.H.); Department of Radiology, Hospital of Southern Norway, Kristiansand, Norway (H.S.S.); SPKI-The Norwegian Centre for Clinical Artificial Intelligence, University Hospital of North Norway, Tromsø, Norway (K.Ø.M.); Department of Clinical Medicine (K.Ø.M.) and Health and Care Sciences (S.H.), Faculty of Health Sciences, UiT-The Arctic University of Norway, Tromsø, Norway; Department of Translational Medicine, Diagnostic Radiology, Lund University, Lund, Sweden (K.L.); Unilabs Mammography Unit, Skåne University Hospital, Malmø, Sweden (K.L.); School of Medicine, University of Nottingham, Clinical Science Building, Nottingham City Hospital, Nottingham, United Kingdom (Y.C.)
| | - Jan Nygård
- From the Section for Breast Cancer Screening (M.L., C.F.O., S.H.) and Department of Register Informatics (S.A., J.N.), Cancer Registry of Norway, P.O. Box 5313, 0304 Oslo, Norway; Department of Radiology, Stavanger University Hospital, Stavanger, Norway (H.W.K.); Faculty of Health Sciences, University of Stavanger, Stavanger, Norway (H.W.K.); Department of Radiology, Østfold Hospital Trust, Kalnes, Norway (M.A.M.); Institute of Clinical Medicine, University of Oslo, Oslo, Norway (M.A.M.); Department of Radiology, Ålesund Hospital, Møre og Romsdal Hospital Trust, Ålesund, Norway (S.R.H.); Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, National University for Science and Technology, Trondheim, Norway (S.R.H.); Department of Radiology and Nuclear Medicine, St Olavs University Hospital, Trondheim, Norway (H.L.H.); Department of Radiology, Hospital of Southern Norway, Kristiansand, Norway (H.S.S.); SPKI-The Norwegian Centre for Clinical Artificial Intelligence, University Hospital of North Norway, Tromsø, Norway (K.Ø.M.); Department of Clinical Medicine (K.Ø.M.) and Health and Care Sciences (S.H.), Faculty of Health Sciences, UiT-The Arctic University of Norway, Tromsø, Norway; Department of Translational Medicine, Diagnostic Radiology, Lund University, Lund, Sweden (K.L.); Unilabs Mammography Unit, Skåne University Hospital, Malmø, Sweden (K.L.); School of Medicine, University of Nottingham, Clinical Science Building, Nottingham City Hospital, Nottingham, United Kingdom (Y.C.)
| | - Kristina Lång
- From the Section for Breast Cancer Screening (M.L., C.F.O., S.H.) and Department of Register Informatics (S.A., J.N.), Cancer Registry of Norway, P.O. Box 5313, 0304 Oslo, Norway; Department of Radiology, Stavanger University Hospital, Stavanger, Norway (H.W.K.); Faculty of Health Sciences, University of Stavanger, Stavanger, Norway (H.W.K.); Department of Radiology, Østfold Hospital Trust, Kalnes, Norway (M.A.M.); Institute of Clinical Medicine, University of Oslo, Oslo, Norway (M.A.M.); Department of Radiology, Ålesund Hospital, Møre og Romsdal Hospital Trust, Ålesund, Norway (S.R.H.); Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, National University for Science and Technology, Trondheim, Norway (S.R.H.); Department of Radiology and Nuclear Medicine, St Olavs University Hospital, Trondheim, Norway (H.L.H.); Department of Radiology, Hospital of Southern Norway, Kristiansand, Norway (H.S.S.); SPKI-The Norwegian Centre for Clinical Artificial Intelligence, University Hospital of North Norway, Tromsø, Norway (K.Ø.M.); Department of Clinical Medicine (K.Ø.M.) and Health and Care Sciences (S.H.), Faculty of Health Sciences, UiT-The Arctic University of Norway, Tromsø, Norway; Department of Translational Medicine, Diagnostic Radiology, Lund University, Lund, Sweden (K.L.); Unilabs Mammography Unit, Skåne University Hospital, Malmø, Sweden (K.L.); School of Medicine, University of Nottingham, Clinical Science Building, Nottingham City Hospital, Nottingham, United Kingdom (Y.C.)
| | - Yan Chen
- From the Section for Breast Cancer Screening (M.L., C.F.O., S.H.) and Department of Register Informatics (S.A., J.N.), Cancer Registry of Norway, P.O. Box 5313, 0304 Oslo, Norway; Department of Radiology, Stavanger University Hospital, Stavanger, Norway (H.W.K.); Faculty of Health Sciences, University of Stavanger, Stavanger, Norway (H.W.K.); Department of Radiology, Østfold Hospital Trust, Kalnes, Norway (M.A.M.); Institute of Clinical Medicine, University of Oslo, Oslo, Norway (M.A.M.); Department of Radiology, Ålesund Hospital, Møre og Romsdal Hospital Trust, Ålesund, Norway (S.R.H.); Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, National University for Science and Technology, Trondheim, Norway (S.R.H.); Department of Radiology and Nuclear Medicine, St Olavs University Hospital, Trondheim, Norway (H.L.H.); Department of Radiology, Hospital of Southern Norway, Kristiansand, Norway (H.S.S.); SPKI-The Norwegian Centre for Clinical Artificial Intelligence, University Hospital of North Norway, Tromsø, Norway (K.Ø.M.); Department of Clinical Medicine (K.Ø.M.) and Health and Care Sciences (S.H.), Faculty of Health Sciences, UiT-The Arctic University of Norway, Tromsø, Norway; Department of Translational Medicine, Diagnostic Radiology, Lund University, Lund, Sweden (K.L.); Unilabs Mammography Unit, Skåne University Hospital, Malmø, Sweden (K.L.); School of Medicine, University of Nottingham, Clinical Science Building, Nottingham City Hospital, Nottingham, United Kingdom (Y.C.)
| | - Solveig Hofvind
- From the Section for Breast Cancer Screening (M.L., C.F.O., S.H.) and Department of Register Informatics (S.A., J.N.), Cancer Registry of Norway, P.O. Box 5313, 0304 Oslo, Norway; Department of Radiology, Stavanger University Hospital, Stavanger, Norway (H.W.K.); Faculty of Health Sciences, University of Stavanger, Stavanger, Norway (H.W.K.); Department of Radiology, Østfold Hospital Trust, Kalnes, Norway (M.A.M.); Institute of Clinical Medicine, University of Oslo, Oslo, Norway (M.A.M.); Department of Radiology, Ålesund Hospital, Møre og Romsdal Hospital Trust, Ålesund, Norway (S.R.H.); Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, National University for Science and Technology, Trondheim, Norway (S.R.H.); Department of Radiology and Nuclear Medicine, St Olavs University Hospital, Trondheim, Norway (H.L.H.); Department of Radiology, Hospital of Southern Norway, Kristiansand, Norway (H.S.S.); SPKI-The Norwegian Centre for Clinical Artificial Intelligence, University Hospital of North Norway, Tromsø, Norway (K.Ø.M.); Department of Clinical Medicine (K.Ø.M.) and Health and Care Sciences (S.H.), Faculty of Health Sciences, UiT-The Arctic University of Norway, Tromsø, Norway; Department of Translational Medicine, Diagnostic Radiology, Lund University, Lund, Sweden (K.L.); Unilabs Mammography Unit, Skåne University Hospital, Malmø, Sweden (K.L.); School of Medicine, University of Nottingham, Clinical Science Building, Nottingham City Hospital, Nottingham, United Kingdom (Y.C.)
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López-Mejía JA, Mantilla-Ollarves JC, Rocha-Zavaleta L. Modulation of JAK-STAT Signaling by LNK: A Forgotten Oncogenic Pathway in Hormone Receptor-Positive Breast Cancer. Int J Mol Sci 2023; 24:14777. [PMID: 37834225 PMCID: PMC10573125 DOI: 10.3390/ijms241914777] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2023] [Revised: 09/25/2023] [Accepted: 09/28/2023] [Indexed: 10/15/2023] Open
Abstract
Breast cancer remains the most frequently diagnosed cancer in women worldwide. Tumors that express hormone receptors account for 75% of all cases. Understanding alternative signaling cascades is important for finding new therapeutic targets for hormone receptor-positive breast cancer patients. JAK-STAT signaling is commonly activated in hormone receptor-positive breast tumors, inducing inflammation, proliferation, migration, and treatment resistance in cancer cells. In hormone receptor-positive breast cancer, the JAK-STAT cascade is stimulated by hormones and cytokines, such as prolactin and IL-6. In normal cells, JAK-STAT is inhibited by the action of the adaptor protein, LNK. However, the role of LNK in breast tumors is not fully understood. This review compiles published reports on the expression and activation of the JAK-STAT pathway by IL-6 and prolactin and potential inhibition of the cascade by LNK in hormone receptor-positive breast cancer. Additionally, it includes analyses of available datasets to determine the level of expression of LNK and various members of the JAK-STAT family for the purpose of establishing associations between expression and clinical outcomes. Together, experimental evidence and in silico studies provide a better understanding of the potential implications of the JAK-STAT-LNK loop in hormone receptor-positive breast cancer progression.
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Affiliation(s)
- José A. López-Mejía
- Departamento de Biología Molecular y Biotecnología, Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México, Mexico City 03100, Mexico; (J.A.L.-M.); (J.C.M.-O.)
| | - Jessica C. Mantilla-Ollarves
- Departamento de Biología Molecular y Biotecnología, Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México, Mexico City 03100, Mexico; (J.A.L.-M.); (J.C.M.-O.)
| | - Leticia Rocha-Zavaleta
- Departamento de Biología Molecular y Biotecnología, Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México, Mexico City 03100, Mexico; (J.A.L.-M.); (J.C.M.-O.)
- Programa Institucional de Cáncer de Mama, Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México, Mexico City 03100, Mexico
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206
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Rodríguez M, González DM, El-Sharkawy F, Castaño M, Madrid J. Complete pathological response in patients with HER2 positive breast cancer treated with neoadjuvant therapy in Colombia. BIOMEDICA : REVISTA DEL INSTITUTO NACIONAL DE SALUD 2023; 43:396-405. [PMID: 37871573 PMCID: PMC10637353 DOI: 10.7705/biomedica.6665] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 08/16/2023] [Indexed: 10/25/2023]
Abstract
Introduction Breast cancer is the most common type of cancer and the leading cause of death by cancer in women in Colombia. Approximately 15 to 20% of breast cancers overexpress HER2. Objective To analyze the relationship between multiple clinical and histological variables and pathological complete response in patients with HER2-positive breast cancer undergoing neoadjuvant therapy in a specialized cancer center in Colombia. Materials and methods We performed a retrospective analysis of non-metastatic HER2-positive breast cancer patients who received neoadjuvant therapy between 2007 and 2020 at the Instituto de Cancerología Las Americas Auna (Medellín, Colombia). Assessed parameters were tumor grade, proliferation index, estrogen receptor, progesterone receptor, HER2 status, type of neoadjuvant therapy, pathologic complete response rates, and overall survival. Results Variables associated with low pathologic complete response rates were tumor grades 1-2 (OR = 0.55; 95% CI = 0.37-0.81; p = 0.03), estrogen receptor positivity (OR =0.65; 95%; CI = 0.43-0.97; p=0.04), and progesterone receptor positivity (OR = 0.44; 95% CI = 0.29-0.65; p = 0.0001). HER2 strong positivity (score 3+) was associated with high pathological complete response rates (OR = 3.3; 95% CI = 1.3-8.35; p=0.013). Five-year overall survival was 91.5% (95% CI = 82.6-95.9) in patients with pathological complete response and 73.6% (95% CI = 66.4-79.6) in patients who did not achieve pathological complete response (p = 0.001). Additionally, the pathological complete response rate was three times higher in patients receiving combined neoadjuvant chemotherapy with anti-HER2 therapy than in those with chemotherapy alone (48% versus 16%). Conclusions In patients with HER2-positive breast cancer, tumor grade 3, estrogen receptor negativity, progesterone receptor negativity, strong HER2 positivity (score 3+), and the use of the neoadjuvant trastuzumab are associated with higher pathological complete response rates.
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Affiliation(s)
- Mauricio Rodríguez
- Departamento de Cirugía Oncológica, Universidad de Antioquia, Medellín, Colombia.
| | - Diego M González
- Departamento de Cirugía Oncológica, Universidad de Antioquia, Medellín, Colombia; Instituto de Cancerología Las Américas Auna, Medellín, Colombia.
| | - Farah El-Sharkawy
- Department of Pathology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States of America.
| | - Mileny Castaño
- Instituto de Cancerología Las Américas Auna, Medellín, Colombia.
| | - Jorge Madrid
- Departamento de Cirugía Oncológica, Universidad de Antioquia, Medellín, Colombia.
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207
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Geršak K, Geršak BM, Gazić B, Klevišar Ivančič A, Drev P, Ružić Gorenjec N, Grašič Kuhar C. The Possible Role of Anti- and Protumor-Infiltrating Lymphocytes in Pathologic Complete Response in Early Breast Cancer Patients Treated with Neoadjuvant Systemic Therapy. Cancers (Basel) 2023; 15:4794. [PMID: 37835488 PMCID: PMC10571934 DOI: 10.3390/cancers15194794] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Revised: 09/20/2023] [Accepted: 09/27/2023] [Indexed: 10/15/2023] Open
Abstract
The tumor microenvironment, composed of pro- and antitumor immune cells, affects cancer cell behavior. We aimed to evaluate whether tumor-infiltrating lymphocyte (TIL) density and TIL subtypes in core biopsies at the diagnosis of breast cancer patients could predict a pathologic complete response (pCR; ypT0/is ypN0) from neoadjuvant systemic therapy (NST). The TIL subtypes were determined based on the proportions of presumably antitumor (CD8+, CXCL13+) and protumor (PD-1+, FOXP3+) immune cells. A prospective, noninterventional study, including 171 participants undergoing NST, was performed. The median TIL density for the entire cohort was 10% (IQR: 3.5-23.8), and 59 (35%) patients achieved pCR. TIL density was positively associated with pCR (univariately and multivariably). In the multivariable logistic regression model, TIL density was an independent predictor of pCR (p = 0.012, OR 1.27; 95% CI 1.05-1.54) when controlled for age (p = 0.232), Ki-67 (p = 0.001), node-negative status (p = 0.024), and HER2+/triple negative vs. luminal B-like subtype (p < 0.001). In our sample, higher proportions of PD-1+ TILs and FOXP3+ TILs were associated with a higher probability of pCR but the association was not statistically significant and we could not make any conclusions on the direction of associations in the model with all four biomarkers. In the exploratory multivariable analysis, we showed that only higher CD8+ TILs were associated with pCR. In conclusion, TIL density and its subtypes are associated with pCR.
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Affiliation(s)
- Klara Geršak
- Faculty of Medicine, University of Ljubljana, Vrazov Trg 2, 1000 Ljubljana, Slovenia (B.G.); (A.K.I.); (C.G.K.)
- Division of Medical Oncology, Institute of Oncology Ljubljana, Zaloška Cesta 2, 1000 Ljubljana, Slovenia
| | - Blaž Matija Geršak
- Faculty of Medicine, University of Ljubljana, Vrazov Trg 2, 1000 Ljubljana, Slovenia (B.G.); (A.K.I.); (C.G.K.)
| | - Barbara Gazić
- Faculty of Medicine, University of Ljubljana, Vrazov Trg 2, 1000 Ljubljana, Slovenia (B.G.); (A.K.I.); (C.G.K.)
- Department of Pathology, Institute of Oncology Ljubljana, Zaloška Cesta 2, 1000 Ljubljana, Slovenia;
| | - Andreja Klevišar Ivančič
- Faculty of Medicine, University of Ljubljana, Vrazov Trg 2, 1000 Ljubljana, Slovenia (B.G.); (A.K.I.); (C.G.K.)
- Department of Pathology, Institute of Oncology Ljubljana, Zaloška Cesta 2, 1000 Ljubljana, Slovenia;
| | - Primož Drev
- Department of Pathology, Institute of Oncology Ljubljana, Zaloška Cesta 2, 1000 Ljubljana, Slovenia;
| | - Nina Ružić Gorenjec
- Institute for Biostatistics and Medical Informatics, Faculty of Medicine, University of Ljubljana, Vrazov Trg 2, 1000 Ljubljana, Slovenia;
| | - Cvetka Grašič Kuhar
- Faculty of Medicine, University of Ljubljana, Vrazov Trg 2, 1000 Ljubljana, Slovenia (B.G.); (A.K.I.); (C.G.K.)
- Division of Medical Oncology, Institute of Oncology Ljubljana, Zaloška Cesta 2, 1000 Ljubljana, Slovenia
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Wolf CL, Pruett C, Lighter D, Jorcyk CL. The clinical relevance of OSM in inflammatory diseases: a comprehensive review. Front Immunol 2023; 14:1239732. [PMID: 37841259 PMCID: PMC10570509 DOI: 10.3389/fimmu.2023.1239732] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Accepted: 08/30/2023] [Indexed: 10/17/2023] Open
Abstract
Oncostatin M (OSM) is a pleiotropic cytokine involved in a variety of inflammatory responses such as wound healing, liver regeneration, and bone remodeling. As a member of the interleukin-6 (IL-6) family of cytokines, OSM binds the shared receptor gp130, recruits either OSMRβ or LIFRβ, and activates a variety of signaling pathways including the JAK/STAT, MAPK, JNK, and PI3K/AKT pathways. Since its discovery in 1986, OSM has been identified as a significant contributor to a multitude of inflammatory diseases, including arthritis, inflammatory bowel disease, lung and skin disease, cardiovascular disease, and most recently, COVID-19. Additionally, OSM has also been extensively studied in the context of several cancer types including breast, cervical, ovarian, testicular, colon and gastrointestinal, brain,lung, skin, as well as other cancers. While OSM has been recognized as a significant contributor for each of these diseases, and studies have shown OSM inhibition is effective at treating or reducing symptoms, very few therapeutics have succeeded into clinical trials, and none have yet been approved by the FDA for treatment. In this review, we outline the role OSM plays in a variety of inflammatory diseases, including cancer, and outline the previous and current strategies for developing an inhibitor for OSM signaling.
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Affiliation(s)
- Cody L. Wolf
- Department of Biomolecular Sciences, Boise State University, Boise, ID, United States
| | - Clyde Pruett
- Department of Biological Sciences, Boise State University, Boise, ID, United States
| | - Darren Lighter
- Department of Biological Sciences, Boise State University, Boise, ID, United States
| | - Cheryl L. Jorcyk
- Department of Biomolecular Sciences, Boise State University, Boise, ID, United States
- Department of Biological Sciences, Boise State University, Boise, ID, United States
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209
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Gygi JP, Konstorum A, Pawar S, Aron E, Kleinstein SH, Guan L. A supervised Bayesian factor model for the identification of multi-omics signatures. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.25.525545. [PMID: 36747790 PMCID: PMC9900835 DOI: 10.1101/2023.01.25.525545] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
MOTIVATION Predictive biological signatures provide utility as biomarkers for disease diagnosis and prognosis, as well as prediction of responses to vaccination or therapy. These signatures are iden-tified from high-throughput profiling assays through a combination of dimensionality reduction and machine learning techniques. The genes, proteins, metabolites, and other biological analytes that compose signatures also generate hypotheses on the underlying mechanisms driving biological responses, thus improving biological understanding. Dimensionality reduction is a critical step in signature discovery to address the large number of analytes in omics datasets, especially for multi-omics profiling studies with tens of thousands of measurements. Latent factor models, which can account for the structural heterogeneity across diverse assays, effectively integrate multi-omics data and reduce dimensionality to a small number of factors that capture correlations and associations among measurements. These factors provide biologically interpretable features for predictive model-ing. However, multi-omics integration and predictive modeling are generally performed independent-ly in sequential steps, leading to suboptimal factor construction. Combining these steps can yield better multi-omics signatures that are more predictive while still being biologically meaningful. RESULTS We developed a supervised variational Bayesian factor model that extracts multi-omics signatures from high-throughput profiling datasets that can span multiple data types. Signature-based multiPle-omics intEgration via lAtent factoRs (SPEAR) adaptively determines factor rank, emphasis on factor structure, data relevance and feature sparsity. The method improves the recon-struction of underlying factors in synthetic examples and prediction accuracy of COVID-19 severity and breast cancer tumor subtypes. AVAILABILITY SPEAR is a publicly available R-package hosted at https://bitbucket.org/kleinstein/SPEAR.
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210
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Xie S, Ju S, Zhang X, Qi C, Zhang J, Mao M, Chen C, Chen Y, Ji F, Zhou J, Wang L. A retrospective comparative study on the diagnostic efficacy and the complications: between CassiII rotational core biopsy and core needle biopsy. Front Oncol 2023; 13:1067246. [PMID: 37823052 PMCID: PMC10562690 DOI: 10.3389/fonc.2023.1067246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 08/03/2023] [Indexed: 10/13/2023] Open
Abstract
Accurate pathologic diagnosis and molecular classification of breast mass biopsy tissue is important for determining individualized therapy for (neo)adjuvant systemic therapies for invasive breast cancer. The CassiII rotational core biopsy system is a novel biopsy technique with a guide needle and a "stick-freeze" technology. The comprehensive assessments including the concordance rates of diagnosis and biomarker status between CassiII and core needle biopsy were evaluated in this study. Estrogen receptor (ER), progesterone receptor (PgR), human epidermal growth factor receptor 2 (HER2), and Ki67 were analyzed through immunohistochemistry. In total, 655 patients with breast cancer who underwent surgery after biopsy at Sir Run Run Shaw Hospital between January 2019 to December 2021 were evaluated. The concordance rates (CRs) of malignant surgical specimens with CassiII needle biopsy was significantly high compared with core needle biopsy. Moreover, CassiII needle biopsy had about 20% improvement in sensitivity and about 5% improvement in positive predictive value compared to Core needle biopsy. The characteristics including age and tumor size were identified the risk factors for pathological inconsistencies with core needle biopsies. However, CassiII needle biopsy was associated with tumor diameter only. The CRs of ER, PgR, HER2, and Ki67 using Cassi needle were 98.08% (kappa, 0.941; p<.001), 90.77% (kappa, 0.812; p<.001), 69.62% (kappa, 0.482; p<.001), and 86.92% (kappa, 0.552; p<.001), respectively. Post-biopsy complications with CassiII needle biopsy were also collected. The complications of CassiII needle biopsy including chest stuffiness, pain and subcutaneous ecchymosis are not rare. The underlying mechanism of subcutaneous congestion or hematoma after CassiII needle biopsy might be the larger needle diameter and the effect of temperature on coagulation function. In summary, CassiII needle biopsy is age-independent and has a better accuracy than CNB for distinguishing carcinoma in situ and invasive carcinoma.
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Affiliation(s)
- Shuduo Xie
- Department of Surgical Oncology, Affiliated Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, Hangzhou, Zhejiang, China
| | - Siwei Ju
- Department of Surgical Oncology, Affiliated Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, Hangzhou, Zhejiang, China
| | - Xun Zhang
- Department of Surgical Oncology, Affiliated Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, Hangzhou, Zhejiang, China
| | - Chao Qi
- Department of Clinical Laboratory, Affiliated Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Jiahang Zhang
- Department of Surgical Oncology, Affiliated Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, Hangzhou, Zhejiang, China
| | - Misha Mao
- Department of Surgical Oncology, Affiliated Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, Hangzhou, Zhejiang, China
| | - Cong Chen
- Department of Breast Surgery, Affiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Yongxia Chen
- Department of Surgical Oncology, Affiliated Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, Hangzhou, Zhejiang, China
| | - Feiyang Ji
- Department of Surgical Oncology, Affiliated Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, Hangzhou, Zhejiang, China
| | - Jichun Zhou
- Department of Surgical Oncology, Affiliated Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, Hangzhou, Zhejiang, China
| | - Linbo Wang
- Department of Surgical Oncology, Affiliated Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, Hangzhou, Zhejiang, China
- Zhejiang Provincial Clinical Research Center for CANCER, Hangzhou, Zhejiang, China
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Miziak P, Baran M, Błaszczak E, Przybyszewska-Podstawka A, Kałafut J, Smok-Kalwat J, Dmoszyńska-Graniczka M, Kiełbus M, Stepulak A. Estrogen Receptor Signaling in Breast Cancer. Cancers (Basel) 2023; 15:4689. [PMID: 37835383 PMCID: PMC10572081 DOI: 10.3390/cancers15194689] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2023] [Revised: 09/19/2023] [Accepted: 09/20/2023] [Indexed: 10/15/2023] Open
Abstract
Estrogen receptor (ER) signaling is a critical regulator of cell proliferation, differentiation, and survival in breast cancer (BC) and other hormone-sensitive cancers. In this review, we explore the mechanism of ER-dependent downstream signaling in BC and the role of estrogens as growth factors necessary for cancer invasion and dissemination. The significance of the clinical implications of ER signaling in BC, including the potential of endocrine therapies that target estrogens' synthesis and ER-dependent signal transmission, such as aromatase inhibitors or selective estrogen receptor modulators, is discussed. As a consequence, the challenges associated with the resistance to these therapies resulting from acquired ER mutations and potential strategies to overcome them are the critical point for the new treatment strategies' development.
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Affiliation(s)
- Paulina Miziak
- Department of Biochemistry and Molecular Biology, Medical University of Lublin, 1 Chodzki Street, 20-093 Lublin, Poland; (M.B.); (E.B.); (A.P.-P.); (J.K.); (M.D.-G.)
| | - Marzena Baran
- Department of Biochemistry and Molecular Biology, Medical University of Lublin, 1 Chodzki Street, 20-093 Lublin, Poland; (M.B.); (E.B.); (A.P.-P.); (J.K.); (M.D.-G.)
| | - Ewa Błaszczak
- Department of Biochemistry and Molecular Biology, Medical University of Lublin, 1 Chodzki Street, 20-093 Lublin, Poland; (M.B.); (E.B.); (A.P.-P.); (J.K.); (M.D.-G.)
| | - Alicja Przybyszewska-Podstawka
- Department of Biochemistry and Molecular Biology, Medical University of Lublin, 1 Chodzki Street, 20-093 Lublin, Poland; (M.B.); (E.B.); (A.P.-P.); (J.K.); (M.D.-G.)
| | - Joanna Kałafut
- Department of Biochemistry and Molecular Biology, Medical University of Lublin, 1 Chodzki Street, 20-093 Lublin, Poland; (M.B.); (E.B.); (A.P.-P.); (J.K.); (M.D.-G.)
| | - Jolanta Smok-Kalwat
- Department of Clinical Oncology, Holy Cross Cancer Centre, 3 Artwinskiego Street, 25-734 Kielce, Poland;
| | - Magdalena Dmoszyńska-Graniczka
- Department of Biochemistry and Molecular Biology, Medical University of Lublin, 1 Chodzki Street, 20-093 Lublin, Poland; (M.B.); (E.B.); (A.P.-P.); (J.K.); (M.D.-G.)
| | - Michał Kiełbus
- Department of Biochemistry and Molecular Biology, Medical University of Lublin, 1 Chodzki Street, 20-093 Lublin, Poland; (M.B.); (E.B.); (A.P.-P.); (J.K.); (M.D.-G.)
| | - Andrzej Stepulak
- Department of Biochemistry and Molecular Biology, Medical University of Lublin, 1 Chodzki Street, 20-093 Lublin, Poland; (M.B.); (E.B.); (A.P.-P.); (J.K.); (M.D.-G.)
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Choi JH, Yu J, Jung M, Jekal J, Kim KS, Jung SU. Prognostic significance of TP53 and PIK3CA mutations analyzed by next-generation sequencing in breast cancer. Medicine (Baltimore) 2023; 102:e35267. [PMID: 37747019 PMCID: PMC10519541 DOI: 10.1097/md.0000000000035267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Revised: 08/02/2023] [Accepted: 08/25/2023] [Indexed: 09/26/2023] Open
Abstract
Breast cancer is one of the most prevalent malignant tumors affecting women globally. It is a heterogeneous disease characterized by mutations in several genes. Several gene panels have been applied to assess the risk of breast cancer and determine the appropriate treatment. As a powerful tool, Next-generation sequencing (NGS) has been widely utilized in cancer research due to its advantages, including high speed, high throughput, and high accuracy. In this study, we aim to analyze the correlation between somatic mutations in breast cancer, analyzed using NGS, and the prognosis of patients. Between May 2018 and May 2019, a total of 313 patients with breast cancer underwent surgical treatment, which included total mastectomy and breast-conserving surgery. Among these patients, 265 were diagnosed with invasive ductal carcinoma. In this study, we analyzed the NGS results, clinicopathological characteristics, and their correlation with prognosis. Using a gene panel, we examined 143 somatic mutations in solid cancers. Notably, the study population included patients who had received neoadjuvant chemotherapy. The mean age of the patients was 53.1 (±10.28) years, and the median follow-up time was 48 months (range, 8-54). Among the 265 patients, 68 had received prior systemic therapy. Of these, 203 underwent breast-conserving surgery, and 62 underwent a mastectomy. Various somatic mutations were observed in NGS, with the most frequent mutation being PIK3CA mutations, which accounted for 44% of all mutations. TP53 mutations were the second most frequent, and ERBB2 mutations were the third most frequent. TP53 mutations were associated with poor disease-free survival (P = .027), while PIK3CA mutations were associated with better disease-free survival (P = .035) than PIK3CA wild-type. In our study, we identified various somatic mutations in breast cancer. Particularly, we found that TP53 and PIK3CA mutations are potentially associated with the prognosis of breast cancer. These findings suggest that the presence of specific mutations may have implications for predicting the prognosis of breast cancer. Further research and validation are needed to gain a deeper understanding of the role of these mutations and their mechanisms in prognosis prediction.
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Affiliation(s)
- Jin Hyuk Choi
- Division of Breast Surgery, Department of Surgery, Kosin University Gospel Hospital, Busan, Korea
- Kosin University College of Medicine, Busan, Korea
| | - Jesang Yu
- Kosin University College of Medicine, Busan, Korea
- Department of Radiation Oncology, Kosin University Gospel Hospital, Busan, Korea
| | - Minjung Jung
- Kosin University College of Medicine, Busan, Korea
- Department of Pathology, Kosin University Gospel Hospital, Busan, Korea
| | - Junyong Jekal
- Division of Breast Surgery, Department of Surgery, Kosin University Gospel Hospital, Busan, Korea
| | - Ku Sang Kim
- Division of Breast Surgery, Department of Surgery, Kosin University Gospel Hospital, Busan, Korea
| | - Sung Ui Jung
- Division of Breast Surgery, Department of Surgery, Kosin University Gospel Hospital, Busan, Korea
- Kosin University College of Medicine, Busan, Korea
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Park H, Son H, Cha H, Song K, Bang S, Jee S, Kim H, Myung J, Shin SJ, Cha C, Chung MS, Paik S. ASAP1 Expression in Invasive Breast Cancer and Its Prognostic Role. Int J Mol Sci 2023; 24:14355. [PMID: 37762658 PMCID: PMC10532164 DOI: 10.3390/ijms241814355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 09/14/2023] [Accepted: 09/19/2023] [Indexed: 09/29/2023] Open
Abstract
Breast cancer is a major global health burden with high morbidity and mortality rates. Previous studies have reported that increased expression of ASAP1 is associated with poor prognosis in various types of cancer. This study was conducted on 452 breast cancer patients who underwent surgery at Hanyang University Hospital, Seoul, South Korea. Data on clinicopathological characteristics including molecular pathologic markers were collected. Immunohistochemical staining of ASAP1 expression level were used to classify patients into high and low groups. In total, 452 cases low ASAP1 expression group was associated with significantly worse recurrence-free survival (p = 0.029). In ER-positive cases (n = 280), the low ASAP1 expression group was associated with significantly worse overall survival (p = 0.039) and recurrence-free survival (p = 0.029). In multivariate cox analysis, low ASAP1 expression was an independent significant predictor of poor recurrence-free survival in the overall patient group (hazard ratio = 2.566, p = 0.002) and ER-positive cases (hazard ratio = 4.046, p = 0.002). In the analysis of the TCGA dataset, the low-expression group of ASAP1 protein demonstrated a significantly poorer progression-free survival (p = 0.005). This study reports that low ASAP1 expression was associated with worse recurrence-free survival in invasive breast cancer.
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Affiliation(s)
- Hosub Park
- Department of Pathology, Hanyang University Hospital, Hanyang University College of Medicine, Seoul 04763, Republic of Korea
| | - Hwangkyu Son
- Department of Pathology, Hanyang University Hospital, Hanyang University College of Medicine, Seoul 04763, Republic of Korea
| | - Hyebin Cha
- Department of Pathology, Hanyang University Hospital, Hanyang University College of Medicine, Seoul 04763, Republic of Korea
| | - Kihyuk Song
- Department of Pathology, Hanyang University Hospital, Hanyang University College of Medicine, Seoul 04763, Republic of Korea
| | - Seongsik Bang
- Department of Pathology, Hanyang University Hospital, Hanyang University College of Medicine, Seoul 04763, Republic of Korea
| | - Seungyun Jee
- Department of Pathology, Asan Medical Center, University of Ulsan College of Medicine, Seoul 06273, Republic of Korea
| | - Hyunsung Kim
- Department of Pathology, Hanyang University Hospital, Hanyang University College of Medicine, Seoul 04763, Republic of Korea
| | - Jaekyung Myung
- Department of Pathology, Hanyang University Hospital, Hanyang University College of Medicine, Seoul 04763, Republic of Korea
| | - Su-Jin Shin
- Department of Pathology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul 06273, Republic of Korea
| | - Chihwan Cha
- Department of Surgery, Hanyang University Hospital, Hanyang University College of Medicine, Seoul 04763, Republic of Korea
| | - Min Sung Chung
- Department of Surgery, Hanyang University Hospital, Hanyang University College of Medicine, Seoul 04763, Republic of Korea
| | - Seungsam Paik
- Department of Pathology, Hanyang University Hospital, Hanyang University College of Medicine, Seoul 04763, Republic of Korea
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214
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Setyawan IGB, Kurnia D, Setiaji K, Anwar SL, Purwanto DJ, Azhar Y, Budijitno S, Suprabawati DGA, Priyono SH, Siregar BA, Indriawan R, Tripriadi ES, Umar M, Pieter JSLA, Yarso KY, Hermansyah D, Wibisana IGNG, Harahap WA, Gautama W, Achmad D. Sociodemographic disparities associated with advanced stages and distant metastatic breast cancers at diagnosis in Indonesia: a cross-sectional study. Ann Med Surg (Lond) 2023; 85:4211-4217. [PMID: 37663742 PMCID: PMC10473298 DOI: 10.1097/ms9.0000000000001030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 06/20/2023] [Indexed: 09/05/2023] Open
Abstract
Background The global health burden of breast cancer is increasing with 5-year survival rates being much shorter in low-income and middle-income countries. Sociodemographic and clinical disparities in early cancer detection affect long-term outcome. Methods The authors compared social, demographic, and pathological characteristics associated with metastatic and late stages of breast cancer diagnosis using data collected from a special registry developed by Perhimpunan Bedah Onkologi Indonesia (PERABOI) in 2015. Results Of 4959 patients recruited in this study, 995 women (20.1%) were diagnosed with metastatic breast cancer. Lower education status and living in rural areas were significantly associated with Stage IV at diagnosis [odds ratio (OR)=1.256, 95% CI=1.093-1.445, P=0.001; and OR=1.197, 95% CI=1.042-1.377, P=0.012; respectively). Main complaints other than lump (ulceration, breast pain, and discharge) and occupation as a housewife were also associated with the presentation of metastatic diseases (OR=2.598, 95% CI=2.538-3.448, P<0.001 and OR=1.264, 95% CI=1.056-1.567, P=0.030, respectively). Having lower education and living outside Java and Bali islands were associated with the diagnosis of late-stage breast cancers (OR=1.908, 95% CI=1.629-2.232, P<0.001 and OR=3.039, 95% CI=2.238-4.126, P<0.001; respectively). A higher proportion of breast cancer patients were relatively younger with bigger tumour size, positive axillary nodal involvement, and more frequent Human epidermal growth factor receptor 2 overexpression. Conclusion The authors identified sociodemographic disparities in the metastatic and late-stage diagnosis of breast cancers among Indonesian women. The subsequent action is required to reduce disparities faced by women with lower social and educational levels for early diagnosis and better healthcare access.
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Affiliation(s)
- IG Budhi Setyawan
- Perhimpunan Bedah Onkologi Indonesia (PERABOI)/Indonesian Association of Surgical Oncology (ISSO)
- Division of Surgical Oncology, RSUP Dr IGNG Ngoerah/Udayana University, Denpasar, Bali
| | - Dian Kurnia
- Perhimpunan Bedah Onkologi Indonesia (PERABOI)/Indonesian Association of Surgical Oncology (ISSO)
- Division of Surgical Oncology, RSUD Dr M. Yunus Bengkulu, Kota Bengkulu, Bengkulu
| | - Kunta Setiaji
- Perhimpunan Bedah Onkologi Indonesia (PERABOI)/Indonesian Association of Surgical Oncology (ISSO)
- Division of Surgical Oncology, RSUP Dr Sardjito / Universitas Gadjah Mada, Yogyakarta
| | - Sumadi Lukman Anwar
- Perhimpunan Bedah Onkologi Indonesia (PERABOI)/Indonesian Association of Surgical Oncology (ISSO)
- Division of Surgical Oncology, RSUP Dr Sardjito / Universitas Gadjah Mada, Yogyakarta
| | - Deni J. Purwanto
- Perhimpunan Bedah Onkologi Indonesia (PERABOI)/Indonesian Association of Surgical Oncology (ISSO)
- Division of Surgical Oncology, RSK Dharmais, Jakarta 11420, DKI Jakarta
| | - Yohana Azhar
- Perhimpunan Bedah Onkologi Indonesia (PERABOI)/Indonesian Association of Surgical Oncology (ISSO)
- Division of Surgical Oncology, RSUP Dr Hasan Sadikin / Universitas Padjadjaran, Bandung, Jawa Barat
| | - Selamat Budijitno
- Perhimpunan Bedah Onkologi Indonesia (PERABOI)/Indonesian Association of Surgical Oncology (ISSO)
- Division of Surgical Oncology, RSUP Dr Kariadi / Universitas Diponegoro, Semarang, Jawa Tengah
| | - Desak Gede Agung Suprabawati
- Perhimpunan Bedah Onkologi Indonesia (PERABOI)/Indonesian Association of Surgical Oncology (ISSO)
- Division of Surgical Oncology, RSUD Dr Soetomo / Universitas Airlangga, Surabaya, Jawa Timur
| | - Sasongko Hadi Priyono
- Perhimpunan Bedah Onkologi Indonesia (PERABOI)/Indonesian Association of Surgical Oncology (ISSO)
- Division of Surgical Oncology, Universitas Lambung Mangkurat, Banjarmasin, Kalimantan Selatan
| | - Bintang Abadi Siregar
- Perhimpunan Bedah Onkologi Indonesia (PERABOI)/Indonesian Association of Surgical Oncology (ISSO)
- Division of Surgical Oncology, RSUD Dr H Abdul Moeloek / Universitas Lampung, Bandar Lampung, Lampung
| | - Ramses Indriawan
- Perhimpunan Bedah Onkologi Indonesia (PERABOI)/Indonesian Association of Surgical Oncology (ISSO)
- Division of Surgical Oncology, RSUD Propinsi NTB / Universitas Mataram, Kota Mataram, Nusa Tenggara Barat
| | - Effif Syofra Tripriadi
- Perhimpunan Bedah Onkologi Indonesia (PERABOI)/Indonesian Association of Surgical Oncology (ISSO)
- Division of Surgical Oncology, RSUD Dr Arifin Achmad / Universitas Riau, Pekanbaru, Riau
| | - Mulawan Umar
- Perhimpunan Bedah Onkologi Indonesia (PERABOI)/Indonesian Association of Surgical Oncology (ISSO)
- Division of Surgical Oncology, RSUP Dr Moh Hoesain / Universitas Sriwijaya, Palembang, Sumatra Selatan
| | - John SLA Pieter
- Perhimpunan Bedah Onkologi Indonesia (PERABOI)/Indonesian Association of Surgical Oncology (ISSO)
- Division of Surgical Oncology, RSUP Dr Wahidin Sudirohusodo / Universitas Hasanuddin, Makassar, Sulawesi Selatan
| | - Kristanto Yuli Yarso
- Perhimpunan Bedah Onkologi Indonesia (PERABOI)/Indonesian Association of Surgical Oncology (ISSO)
- Division of Surgical Oncology, RSUD Dr Moewardi / Universitas Sebelas Maret, Surakarta, Jawa Tengah
| | - Dedy Hermansyah
- Perhimpunan Bedah Onkologi Indonesia (PERABOI)/Indonesian Association of Surgical Oncology (ISSO)
- Division of Surgical Oncology, RSUP Dr H Adam Malik / Universitas Sumatra Utara, Medan, Sumatra Utara
| | - IGN Gunawan Wibisana
- Perhimpunan Bedah Onkologi Indonesia (PERABOI)/Indonesian Association of Surgical Oncology (ISSO)
- Division of Surgical Oncology, RSUP Dr Cipto Mangunkusumo / Universitas Indonesia, Padang, Sumatra Barat
| | - Wirsma Arif Harahap
- Perhimpunan Bedah Onkologi Indonesia (PERABOI)/Indonesian Association of Surgical Oncology (ISSO)
- Division of Surgical Oncology, RSUP Dr M Djamil / Universitas Andalas, Jakarta, DKI Jakarta, Indonesia
| | - Walta Gautama
- Perhimpunan Bedah Onkologi Indonesia (PERABOI)/Indonesian Association of Surgical Oncology (ISSO)
- Division of Surgical Oncology, RSK Dharmais, Jakarta 11420, DKI Jakarta
| | - Dimyati Achmad
- Perhimpunan Bedah Onkologi Indonesia (PERABOI)/Indonesian Association of Surgical Oncology (ISSO)
- Division of Surgical Oncology, RSUP Dr Hasan Sadikin / Universitas Padjadjaran, Bandung, Jawa Barat
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Li L, Wu N, Zhuang G, Geng L, Zeng Y, Wang X, Wang S, Ruan X, Zheng X, Liu J, Gao M. Heterogeneity and potential therapeutic insights for triple-negative breast cancer based on metabolic-associated molecular subtypes and genomic mutations. Front Pharmacol 2023; 14:1224828. [PMID: 37719859 PMCID: PMC10502304 DOI: 10.3389/fphar.2023.1224828] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 08/21/2023] [Indexed: 09/19/2023] Open
Abstract
Objective: Due to a lack of effective therapy, triple-negative breast cancer (TNBC) is extremely poor prognosis. Metabolic reprogramming is an important hallmark in tumorigenesis, cancer diagnosis, prognosis, and treatment. Categorizing metabolic patterns in TNBC is critical to combat heterogeneity and targeted therapeutics. Methods: 115 TNBC patients from TCGA were combined into a virtual cohort and verified by other verification sets, discovering differentially expressed genes (DEGs). To identify reliable metabolic features, we applied the same procedures to five independent datasets to verify the identified TNBC subtypes, which differed in terms of prognosis, metabolic characteristics, immune infiltration, clinical features, somatic mutation, and drug sensitivity. Results: In general, TNBC could be classified into two metabolically distinct subtypes. C1 had high immune checkpoint genes expression and immune and stromal scores, demonstrating sensitivity to the treatment of PD-1 inhibitors. On the other hand, C2 displayed a high variation in metabolism pathways involved in carbohydrate, lipid, and amino acid metabolism. More importantly, C2 was a lack of immune signatures, with late pathological stage, low immune infiltration and poor prognosis. Interestingly, C2 had a high mutation frequency in PIK3CA, KMT2D, and KMT2C and displayed significant activation of the PI3K and angiogenesis pathways. As a final output, we created a 100-gene classifier to reliably differentiate the TNBC subtypes and AKR1B10 was a potential biomarker for C2 subtypes. Conclusion: In conclusion, we identified two subtypes with distinct metabolic phenotypes, provided novel insights into TNBC heterogeneity, and provided a theoretical foundation for therapeutic strategies.
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Affiliation(s)
- Lijuan Li
- Department of Cancer Prevention Center, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Nan Wu
- Department of Cancer Prevention Center, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Gaojian Zhuang
- The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People’s Hospital, Qingyuan, China
| | - Lin Geng
- Department of Thyroid and Neck Tumor, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Yu Zeng
- Department of Thyroid and Neck Tumor, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Xuan Wang
- Department of Phase I Clinical Trial, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Shuang Wang
- Department of Cancer Prevention Center, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Xianhui Ruan
- Department of Thyroid and Neck Tumor, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Xiangqian Zheng
- Department of Thyroid and Neck Tumor, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Juntian Liu
- Department of Cancer Prevention Center, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Ming Gao
- Department of Thyroid and Neck Tumor, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
- Department of Thyroid and Breast Surgery, Tianjin Union Medical Center, Tianjin Key Laboratory of General Surgery in construction, Tianjin Union Medical Center, Tianjin, China
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Huang JX, Shi J, Ding SS, Zhang HL, Wang XY, Lin SY, Xu YF, Wei MJ, Liu LZ, Pei XQ. Deep Learning Model Based on Dual-Modal Ultrasound and Molecular Data for Predicting Response to Neoadjuvant Chemotherapy in Breast Cancer. Acad Radiol 2023; 30 Suppl 2:S50-S61. [PMID: 37270368 DOI: 10.1016/j.acra.2023.03.036] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 03/24/2023] [Accepted: 03/25/2023] [Indexed: 06/05/2023]
Abstract
RATIONALE AND OBJECTIVES To carry out radiomics analysis/deep convolutional neural network (CNN) based on B-mode ultrasound (BUS) and shear wave elastography (SWE) to predict response to neoadjuvant chemotherapy (NAC) in breast cancer patients. MATERIALS AND METHODS In this prospective study, 255 breast cancer patients who received NAC between September 2016 and December 2021 were included. Radiomics models were designed using a support vector machine classifier based on US images obtained before treatment, including BUS and SWE. And CNN models also were developed using ResNet architecture. The final predictive model was developed by combining the dual-modal US and independently associated clinicopathologic characteristics. The predictive performances of the models were assessed with five-fold cross-validation. RESULTS Pretreatment SWE performed better than BUS in predicting the response to NAC for breast cancer for both the CNN and radiomics models (P < 0.001). The predictive results of the CNN models were significantly better than the radiomics models, with AUCs of 0.72 versus 0.69 for BUS and 0.80 versus 0.77 for SWE, respectively (P = 0.003). The CNN model based on the dual-modal US and molecular data exhibited outstanding performance in predicting NAC response, with an accuracy of 83.60% ± 2.63%, a sensitivity of 87.76% ± 6.44%, and a specificity of 77.45% ± 4.38%. CONCLUSION The pretreatment CNN model based on the dual-modal US and molecular data achieved excellent performance for predicting the response to chemotherapy in breast cancer. Therefore, this model has the potential to serve as a non-invasive objective biomarker to predict NAC response and aid clinicians with individual treatments.
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Affiliation(s)
- Jia-Xin Huang
- Department of Medical Ultrasound, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510000, China (J.-X.H., X.-Y.W., Y.-F.X., M.-J.W., L.-Z.L., X.-Q.P.)
| | - Jun Shi
- School of Communication and Information Engineering, Shanghai University, Shanghai 200444, China (J.S., S.-S.D., H.-L.Z.)
| | - Sai-Sai Ding
- School of Communication and Information Engineering, Shanghai University, Shanghai 200444, China (J.S., S.-S.D., H.-L.Z.)
| | - Hui-Li Zhang
- School of Communication and Information Engineering, Shanghai University, Shanghai 200444, China (J.S., S.-S.D., H.-L.Z.)
| | - Xue-Yan Wang
- Department of Medical Ultrasound, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510000, China (J.-X.H., X.-Y.W., Y.-F.X., M.-J.W., L.-Z.L., X.-Q.P.)
| | - Shi-Yang Lin
- Department of Medical Ultrasound, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou 510000, China (S.-Y.L.)
| | - Yan-Fen Xu
- Department of Medical Ultrasound, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510000, China (J.-X.H., X.-Y.W., Y.-F.X., M.-J.W., L.-Z.L., X.-Q.P.)
| | - Ming-Jie Wei
- Department of Medical Ultrasound, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510000, China (J.-X.H., X.-Y.W., Y.-F.X., M.-J.W., L.-Z.L., X.-Q.P.)
| | - Long-Zhong Liu
- Department of Medical Ultrasound, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510000, China (J.-X.H., X.-Y.W., Y.-F.X., M.-J.W., L.-Z.L., X.-Q.P.)
| | - Xiao-Qing Pei
- Department of Medical Ultrasound, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510000, China (J.-X.H., X.-Y.W., Y.-F.X., M.-J.W., L.-Z.L., X.-Q.P.).
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Sassi F, Rekaya MB, Belarbi A, Chilla D, Mansouri N, Achouri L, Saied E, Kassa R, Kacem LB, Ouezani M, Debabeche N, Rebhi F, Rammeh S. Pathologically confirmed women's breast cancer: A descriptive study of Tunisian and Algerian series. Cancer Rep (Hoboken) 2023; 6 Suppl 1:e1818. [PMID: 37092543 PMCID: PMC10440841 DOI: 10.1002/cnr2.1818] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2022] [Revised: 03/22/2023] [Accepted: 03/27/2023] [Indexed: 04/25/2023] Open
Abstract
BACKGROUND Breast cancer (BC) is the most frequent malignancy among women in Tunisia and Algeria. Clinical and pathological characteristics of this cancer among these populations are not widely reported. The aim of the study was to report clinical and pathological characteristics of women's BC in a Tunisian and Algerian series. METHODS Pathologically confirmed 1089 BCs were gathered in the pathology departments of three Northern Tunisian hospitals: Tunis military, Charles Nicolle and Jendouba and in the pathology department of Alger Douera hospital between January 2015 and December 2020. Clinical and pathological findings of the two series: age, tumor size, histological type, grading according to Scarff-Bloom Richardson grading system, lymph node status at the time of diagnosis in axillary lymphadenectomy specimens and the immunohistochemical expression of estrogen and progesterone receptors (ER/PR), HER2 and Ki-67, were collected from the pathological reports. RESULTS The median age at diagnosis was 50 and 48 years in Tunisian and Algerian series, respectively (p = 0.016). The diagnosis of BC was made on surgical specimens (lumpectomy or mastectomy) in 373/491 (76%) cases of the Tunisian series and in 225/598 (37.6%) cases of the Algerian one. Median tumor size was 2.8 cm and 2.5 cm in Algerian and Tunisian series, respectively (p = 0.252). Invasive BCs not otherwise specified was observed in 440/481 (91.5%) BCs in Tunisian series and in 519/586 (88.6%) BCs in Algerian series. Axillary lymph node positive tumors were observed in 64.6% and 58.8% of Tunisian and Algerian women, respectively (p = 0.926). BCs were ER positive in 311/385 (80.8%) and 486/571 (85.1%) cases and HER2 positive in 86/283 (30.4%) and 60/385 (15.6%) cases of Tunisian and Algerian series, respectively. CONCLUSIONS In Tunisia and Algeria, BC has poor prognostic factors with large tumor sizes and high rates of lymph nodes involvement at diagnosis.
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Affiliation(s)
- Farah Sassi
- Department of Pathology, Charles Nicolle Hospital Tunis, UR17ES15, Faculté de Médecine de TunisUniversité de Tunis El ManarTunisTunisia
| | - Meriem Ben Rekaya
- Department of Pathology, Charles Nicolle Hospital Tunis, UR17ES15, Faculté de Médecine de TunisUniversité de Tunis El ManarTunisTunisia
| | - Ayed Belarbi
- Department of Pathology, Douéra Hospital, Laboratoire de Recherche polymorphisme génétique No. 18Université d'Alger 1Alger CentreAlgeria
| | - Dalia Chilla
- Department of Pathology, Douéra Hospital, Laboratoire de Recherche polymorphisme génétique No. 18Université d'Alger 1Alger CentreAlgeria
| | - Nada Mansouri
- Department of PathologyMilitary HospitalTunisTunisia
| | - Leila Achouri
- Department of Surgical OncologyRegional Hospital of JendoubaJendoubaTunisia
| | - Essia Saied
- Department of Pathology, Charles Nicolle Hospital Tunis, UR17ES15, Faculté de Médecine de TunisUniversité de Tunis El ManarTunisTunisia
| | - Reda Kassa
- Department of Pathology, Douéra Hospital, Laboratoire de Recherche polymorphisme génétique No. 18Université d'Alger 1Alger CentreAlgeria
| | - Linda Belhaj Kacem
- Department of Pathology, Charles Nicolle Hospital Tunis, UR17ES15, Faculté de Médecine de TunisUniversité de Tunis El ManarTunisTunisia
| | - Manel Ouezani
- Department of Pathology, Douéra Hospital, Laboratoire de Recherche polymorphisme génétique No. 18Université d'Alger 1Alger CentreAlgeria
| | - Nadjiba Debabeche
- Department of Pathology, Douéra Hospital, Laboratoire de Recherche polymorphisme génétique No. 18Université d'Alger 1Alger CentreAlgeria
| | - Fatima Rebhi
- Department of Pathology, Douéra Hospital, Laboratoire de Recherche polymorphisme génétique No. 18Université d'Alger 1Alger CentreAlgeria
| | - Soumaya Rammeh
- Department of Pathology, Charles Nicolle Hospital Tunis, UR17ES15, Faculté de Médecine de TunisUniversité de Tunis El ManarTunisTunisia
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Hurvitz SA, Bardia A, Quiroga V, Park YH, Blancas I, Alonso-Romero JL, Vasiliev A, Adamchuk H, Salgado M, Yardley DA, Berzoy O, Zamora-Auñón P, Chan D, Spera G, Xue C, Ferreira E, Badovinac Crnjevic T, Pérez-Moreno PD, López-Valverde V, Steinseifer J, Fernando TM, Moore HM, Fasching PA. Neoadjuvant palbociclib plus either giredestrant or anastrozole in oestrogen receptor-positive, HER2-negative, early breast cancer (coopERA Breast Cancer): an open-label, randomised, controlled, phase 2 study. Lancet Oncol 2023; 24:1029-1041. [PMID: 37657462 DOI: 10.1016/s1470-2045(23)00268-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 05/10/2023] [Accepted: 05/24/2023] [Indexed: 09/03/2023]
Abstract
BACKGROUND The development of more potent selective oestrogen receptor antagonists and degraders (SERDs) that can be orally administered could help to address the limitations of current endocrine therapies. We report the primary and final analyses of the coopERA Breast Cancer study, designed to test whether giredestrant, a highly potent, non-steroidal, oral SERD, would show a stronger anti-proliferative effect than anastrozole after 2 weeks for oestrogen receptor-positive, HER2-negative, untreated early breast cancer. METHODS In this open-label, randomised, controlled, phase 2 study, postmenopausal women were eligible if they were aged 18 years or older; had clinical T stage (cT)1c to cT4a-c (≥1·5 cm within cT1c) oestrogen receptor-positive, HER2-negative, untreated early breast cancer; an Eastern Cooperative Oncology Group performance status of 0-1; and baseline Ki67 score of at least 5%. The study was conducted at 59 hospital or clinic sites in 11 countries globally. Participants were randomly assigned (1:1) to giredestrant 30 mg oral daily or anastrozole 1 mg oral daily on days 1-14 (window-of-opportunity phase) via an interactive web-based system with permuted-block randomisation with block size of four. Randomisation was stratified by cT stage, baseline Ki67 score, and progesterone receptor status. A 16-week neoadjuvant phase comprised the same regimen plus palbociclib 125 mg oral daily on days 1-21 of a 28-day cycle, for four cycles. The primary endpoint was geometric mean relative Ki67 score change from baseline to week 2 in patients with complete central Ki67 scores at baseline and week 2 (window-of-opportunity phase). Safety was assessed in all patients who received at least one dose of study drug. The study is registered with ClinicalTrials.gov (NCT04436744) and is complete. FINDINGS Between Sept 4, 2020, and June 22, 2021, 221 patients were enrolled and randomly assigned to the giredestrant plus palbociclib group (n=112; median age 62·0 years [IQR 57·0-68·5]) or anastrozole plus palbociclib group (n=109; median age 62·0 [57·0-67·0] years). 15 (7%) of 221 patients were Asian, three (1%) were Black or African American, 194 (88%) were White, and nine (4%) were unknown races. At data cutoff for the primary analysis (July 19, 2021), the geometric mean relative reduction of Ki67 from baseline to week 2 was -75% (95% CI -80 to -70) with giredestrant and -67% (-73 to -59) with anastrozole (p=0·043), meeting the primary endpoint. At the final analysis (data cutoff Nov 24, 2021), the most common grade 3-4 adverse events were neutropenia (29 [26%] of 112 in the giredestrant plus palbociclib group vs 29 [27%] of 109 in the anastrozole plus palbociclib group) and decreased neutrophil count (17 [15%] vs 16 [15%]). Serious adverse events occurred in five (4%) patients in the giredestrant plus palbociclib group and in two (2%) patients in the anastrozole plus palbociclib group. There were no treatment-related deaths. One patient died due to an adverse event in the giredestrant plus palbociclib group (myocardial infarction). INTERPRETATION Giredestrant offers encouraging anti-proliferative and anti-tumour activity and was well tolerated, both as a single agent and in combination with palbociclib. Results justify further investigation in ongoing trials. FUNDING F Hoffmann-La Roche.
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Affiliation(s)
- Sara A Hurvitz
- Breast Cancer Clinical Trials Program, Division of Hematology-Oncology, David Geffen School of Medicine, Clinical Research Unit, UCLA Jonsson Comprehensive Cancer Center, Los Angeles, CA, USA; Fred Hutchinson Cancer Center, Seattle, WA, USA.
| | - Aditya Bardia
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Vanesa Quiroga
- GEICAM Spanish Breast Cancer Group, San Sebastián de los Reyes, Madrid, Spain; Catalan Institute of Oncology Badalona, Barcelona, Spain
| | | | - Isabel Blancas
- GEICAM Spanish Breast Cancer Group, San Sebastián de los Reyes, Madrid, Spain; Hospital Universitario San Cecilio, Instituto de Investigación Biosanitaria de Granada, Granada, Spain; Medicine Department, Granada University, Granada, Spain
| | - José Luis Alonso-Romero
- GEICAM Spanish Breast Cancer Group, San Sebastián de los Reyes, Madrid, Spain; Hospital Clínico Universitario Virgen de la Arrixaca, IMIB-Arrixaca, Murcia, Spain
| | - Aleksandr Vasiliev
- NSHI Road Clinical Hospital of JSC Russian Railways, Saint Petersburg, Russia
| | - Hryhoriy Adamchuk
- Communal Enterprise Kryvyi Rih Oncology Dispensary, Kryvyi Rih, Ukraine
| | | | - Denise A Yardley
- Sarah Cannon Research Institute and Tennessee Oncology, Nashville, TN, USA
| | - Oleksandr Berzoy
- Communal Non-profit Enterprise Odesa Regional Clinical Hospital of Odesa Regional Council, Odesa, Ukraine
| | - Pilar Zamora-Auñón
- GEICAM Spanish Breast Cancer Group, San Sebastián de los Reyes, Madrid, Spain; Hospital Universitario La Paz, Madrid, Spain
| | - David Chan
- Torrance Memorial Hunt Cancer Center, Torrance, CA, USA
| | - Gonzalo Spera
- Translational Research in Oncology (TRIO), Montevideo, Uruguay
| | - Cloris Xue
- F Hoffmann-La Roche, Toronto, ON, Canada
| | | | | | | | | | | | | | | | - Peter A Fasching
- University Hospital Erlangen, Comprehensive Cancer Center Erlangen-EMN, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
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Tabár L, Dean PB, Tucker FL, Yen AMF, Chen SLS, Lin ATY, Hsu CY, Munpolsri P, Wu WYY, Smith RA, Duffy SW, Chen THH, Tarján M, Vörös A. Imaging biomarkers are underutilised but highly predictive prognostic factors for the more fatal breast cancer subtypes. Eur J Radiol 2023; 166:111021. [PMID: 37542814 DOI: 10.1016/j.ejrad.2023.111021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2023] [Revised: 07/25/2023] [Accepted: 07/30/2023] [Indexed: 08/07/2023]
Abstract
PURPOSE The development and refinement of breast imaging modalities offer a wealth of diagnostic information such as imaging biomarkers, which are primarily the mammographic appearance of the various breast cancer subtypes. These are readily available preoperatively at the time of diagnosis and can enhance the prognostic value of currently used molecular biomarkers. In this study, we investigated the relative utility of the molecular and imaging biomarkers, both jointly and independently, when predicting long-term patient outcome according to the site of tumour origin. METHODS We evaluated the association of imaging biomarkers and conventional molecular biomarkers, (ER, PR, HER-2, Ki67), separately and combined, with long-term patient outcome in all breast cancer cases having complete data on both imaging and molecular biomarkers (n = 2236) diagnosed in our Institute during the period 2008-2019. Large format histopathology technique was used to document intra- and intertumoural heterogeneity and select the appropriate foci for evaluating molecular biomarkers. RESULTS The breast cancer imaging biomarkers were strongly predictive of long-term patient outcome. The molecular biomarkers were predictive of outcome only for unifocal acinar adenocarcinoma of the breast (AAB), but less reliable in the multifocal AAB cases due to variability of molecular biomarkers in the individual tumour foci. In breast cancer of mesenchymal origin (BCMO), conventionally termed classic invasive lobular carcinoma, and in cancers originating from the major lactiferous ducts (ductal adenocarcinoma of the breast, DAB), the molecular biomarkers misleadingly indicated favourable prognosis, whereas the imaging biomarkers in BCMO and DAB reliably indicated the high risk of breast cancer death. Among the 2236 breast cancer cases, BCMO and DAB comprised 21% of the breast cancer cases, but accounted for 45% of the breast cancer deaths. CONCLUSIONS Integration of imaging biomarkers into the diagnostic workup of breast cancer yields a more precise, comprehensive and prognostically accurate diagnostic report. This is particularly necessary in multifocal AAB cases having intertumoural heterogeneity, in diffuse carcinomas (DAB and BCMO), and in cases with combined DAB and AAB. In such cases, the imaging biomarkers should be prioritised over molecular biomarkers in planning treatment because the latter fail to predict the severity of the disease. In combination with the use of the large section histopathology technique, imaging biomarkers help alleviate some of the current problems in breast cancer management, such as over- and under-assessment of disease extent, which carry the risk of overtreatment and undertreatment.
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Affiliation(s)
- László Tabár
- Falun Central Hospital, Lasarettsvägen 10, 791 82 Falun, Sweden.
| | - Peter B Dean
- University of Turku, FI-20014 Turun Yliopisto, Finland
| | | | - Amy Ming-Fang Yen
- School of Oral Hygiene, College of Oral Medicine, Taipei Medical University, 250 Wuxing Street, Taipei 110, Taiwan
| | - Sam Li-Sheng Chen
- School of Oral Hygiene, College of Oral Medicine, Taipei Medical University, 250 Wuxing Street, Taipei 110, Taiwan
| | - Abbie Ting-Yu Lin
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, 17 Hsuchow Road, Taipei 100, Taiwan
| | - Chen-Yang Hsu
- Daichung Hospital, No. 304, Guangfu Rd, Zhunan Township, Miaoli 350, Taiwan
| | - Pattaranan Munpolsri
- School of Oral Hygiene, College of Oral Medicine, Taipei Medical University, 250 Wuxing Street, Taipei 110, Taiwan
| | - Wendy Yi-Ying Wu
- Department of Radiation Sciences, Oncology, Umeå University, Sweden
| | - Robert A Smith
- Early Cancer Detection Science, American Cancer Society, Atlanta, GA 30303, USA
| | - Stephen W Duffy
- Centre for Prevention, Detection and Diagnosis, Wolfson Institute of Population Health, Queen Mary University of London, Charterhouse Square London EC1M 6BQ, UK
| | - Tony Hsiu-Hsi Chen
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, 17 Hsuchow Road, Taipei 100, Taiwan
| | - Miklós Tarján
- Falun Central Hospital, Lasarettsvägen 10, 791 82 Falun, Sweden
| | - András Vörös
- Department of Pathology, University of Szeged, Állomás street 1, H-6720 Szeged, Hungary
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Liu C, Huang X, Chen X, Shi Z, Liu C, Liang Y, Huang X, Chen M, Chen X, Liang C, Liu Z. Use of Pretreatment Multiparametric MRI to Predict Tumor Regression Pattern to Neoadjuvant Chemotherapy in Breast Cancer. Acad Radiol 2023; 30 Suppl 2:S62-S70. [PMID: 37019697 DOI: 10.1016/j.acra.2023.02.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 02/19/2023] [Accepted: 02/20/2023] [Indexed: 04/07/2023]
Abstract
RATIONALE AND OBJECTIVES To develop an easy-to-use model by combining pretreatment MRI and clinicopathologic features for early prediction of tumor regression pattern to neoadjuvant chemotherapy (NAC) in breast cancer. MATERIALS AND METHODS We retrospectively analyzed 420 patients who received NAC and underwent definitive surgery in our hospital from February 2012 to August 2020. Pathologic findings of surgical specimens were used as the gold standard to classify tumor regression patterns into concentric and non-concentric shrinkage. Morphologic and kinetic MRI features were both analyzed. Univariable and multivariable analyses were performed to select the key clinicopathologic and MRI features for pretreatment prediction of regression pattern. Logistic regression and six machine learning methods were used to construct prediction models, and their performance were evaluated with receiver operating characteristic curve. RESULTS Two clinicopathologic variables and three MRI features were selected as independent predictors to construct prediction models. The apparent area under the curve (AUC) of seven prediction models were in the range of 0.669-0.740. The logistic regression model yielded an AUC of 0.708 (95% confidence interval [CI]: 0.658-0.759), and the decision tree model achieved the highest AUC of 0.740 (95% CI: 0.691-0.787). For internal validation, the optimism-corrected AUCs of seven models were in the range of 0.592-0.684. There was no significant difference between the AUCs of the logistic regression model and that of each machine learning model. CONCLUSION Prediction models combining pretreatment MRI and clinicopathologic features are useful for predicting tumor regression pattern in breast cancer, which can assist to select patients who can benefit from NAC for de-escalation of breast surgery and modify treatment strategy.
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Affiliation(s)
- Chen Liu
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China; Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, No.106 Zhongshan Er Road, Guangzhou, 510080, China; Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, China
| | - Xiaomei Huang
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China; Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, No.106 Zhongshan Er Road, Guangzhou, 510080, China; Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, China
| | - Xiaobo Chen
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China; Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, No.106 Zhongshan Er Road, Guangzhou, 510080, China; Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, China
| | - Zhenwei Shi
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, No.106 Zhongshan Er Road, Guangzhou, 510080, China; Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, China; Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Chunling Liu
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, No.106 Zhongshan Er Road, Guangzhou, 510080, China; Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, China
| | - Yanting Liang
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, No.106 Zhongshan Er Road, Guangzhou, 510080, China; Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, China; Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Xin Huang
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, No.106 Zhongshan Er Road, Guangzhou, 510080, China; Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, China; Shantou University Medical College, Shantou, China
| | - Minglei Chen
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, No.106 Zhongshan Er Road, Guangzhou, 510080, China; Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, China
| | - Xin Chen
- Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China
| | - Changhong Liang
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, No.106 Zhongshan Er Road, Guangzhou, 510080, China; Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, China
| | - Zaiyi Liu
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China; Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, No.106 Zhongshan Er Road, Guangzhou, 510080, China; Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, China.
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Chang H, Wang D, Li Y, Xiang S, Yang YX, Kong P, Fang C, Ming L, Wang X, Zhang C, Jia W, Yan Q, Liu X, Zeng Q. Evaluation of breast cancer malignancy, prognostic factors and molecular subtypes using a continuous-time random-walk MR diffusion model. Eur J Radiol 2023; 166:111003. [PMID: 37506477 DOI: 10.1016/j.ejrad.2023.111003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 07/06/2023] [Accepted: 07/20/2023] [Indexed: 07/30/2023]
Abstract
PURPOSE To assess the continuous-time random-walk (CTRW) model's diagnostic value in breast lesions and to explore the associations between the CTRW parameters and breast cancer pathologic factors. METHOD This retrospective study included 85 patients (70 malignant and 18 benign lesions) who underwent 3.0T MRI examinations. Diffusion-weighted images (DWI) were acquired with 16b-values to fit the CTRW model. Three parameters (Dm, α, and β) derived from CTRW and apparent diffusion coefficient (ADC) from DWI were compared among the benign/malignant lesions, molecular prognostic factors, and molecular subtypes by Mann-Whitney U test. Spearman correlation was used to evaluate the associations between the parameters and prognostic factors. The diagnostic performance was assessed by the area under the receiver operating characteristic curve (AUC) based on the diffusion parameters. RESULTS All parameters, ADC, Dm, α, and β were significantly lower in the malignant than benign lesions (P < 0.05). The combination of all the CTRW parameters (Dm, α, and β) provided the highest AUC (0.833) and the best sensitivity (94.3%) in differentiating malignant status. And the positive status of estrogen receptor (ER) and progesterone receptor (PR) showed significantly lower β compared with the negative counterparts (P < 0.05). The high Ki-67 expression produced significantly lower Dm and ADC values (P < 0.05). Additionally, combining multiple CTRW parameters improved the performance of diagnosing molecular subtypes of breast cancer. Moreover, Spearman correlations analysis showed that β produced significant correlations with ER, PR and Ki-67 expression (P < 0.05). CONCLUSIONS The CTRW parameters could be used as non-invasive quantitative imaging markers to evaluate breast lesions.
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Affiliation(s)
- Huan Chang
- Department of Radiology, Shandong Provincial Qianfoshan Hospital, Shandong University, Jinan, Shandong, China
| | - Dawei Wang
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, Shandong, China
| | - Yuting Li
- Department of Radiology, The First College of Clinical Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
| | - Shaoxin Xiang
- MR Collaboration, United Imaging Research Institute of Intelligent Imaging, Beijing, China
| | - Yu Xin Yang
- MR Collaboration, United Imaging Research Institute of Intelligent Imaging, Beijing, China
| | - Peng Kong
- Department of Breast Surgery, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, Shandong, China
| | - Caiyun Fang
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Lei Ming
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, Shandong, China
| | - Xiangqing Wang
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, Shandong, China
| | - Chuanyi Zhang
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, Shandong, China
| | - Wenjing Jia
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Qingqing Yan
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Xinhui Liu
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Qingshi Zeng
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, Shandong, China.
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Chen X, Ding J, Hu G, Shu X, Liu Y, Du J, Wen Z, Liu J, Huang H, Tang G, Liu W. Estrogen-Induced LncRNA, LINC02568, Promotes Estrogen Receptor-Positive Breast Cancer Development and Drug Resistance Through Both In Trans and In Cis Mechanisms. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2206663. [PMID: 37404090 PMCID: PMC10477896 DOI: 10.1002/advs.202206663] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Revised: 06/12/2023] [Indexed: 07/06/2023]
Abstract
Endocrine therapy is the frontline treatment for estrogen receptor (ER) positive breast cancer patients. However, the primary and acquired resistance to endocrine therapy drugs remain as a major challenge in the clinic. Here, this work identifies an estrogen-induced lncRNA, LINC02568, which is highly expressed in ER-positive breast cancer and functional important in cell growth in vitro and tumorigenesis in vivo as well as endocrine therapy drug resistance. Mechanically, this work demonstrates that LINC02568 regulates estrogen/ERα-induced gene transcriptional activation in trans by stabilizing ESR1 mRNA through sponging miR-1233-5p in the cytoplasm. Meanwhile, LINC02568 contributes to tumor-specific pH homeostasis by regulating carbonic anhydrase CA12 in cis in the nucleus. The dual functions of LINC02568 together contribute to breast cancer cell growth and tumorigenesis as well as endocrine therapy drug resistance. Antisense oligonucleotides (ASO) targeting LINC02568 significantly inhibits ER-positive breast cancer cell growth in vitro and tumorigenesis in vivo. Furthermore, combination treatment with ASO targeting LINC02568 and endocrine therapy drugs or CA12 inhibitor U-104 exhibits synergistic effects on tumor growth. Taken together, the findings reveal the dual mechanisms of LINC02568 in regulating ERα signaling and pH homeostasis in ER-positive breast cancer, and indicated that targeting LINC02568 might represent a potential therapeutic avenue in the clinic.
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Affiliation(s)
- Xue Chen
- State Key Laboratory of Cellular Stress BiologySchool of Pharmaceutical SciencesXiamen UniversityXiang'an South RoadXiamen361102FujianChina
- Fujian Provincial Key Laboratory of Innovative Drug Target ResearchSchool of Pharmaceutical SciencesXiamen UniversityXiang'an South RoadXiamen361102FujianChina
- Xiang An Biomedicine LaboratorySchool of Pharmaceutical SciencesXiamen UniversityXiang'an South RoadXiamen361102FujianChina
| | - Jian‐cheng Ding
- State Key Laboratory of Cellular Stress BiologySchool of Pharmaceutical SciencesXiamen UniversityXiang'an South RoadXiamen361102FujianChina
- Fujian Provincial Key Laboratory of Innovative Drug Target ResearchSchool of Pharmaceutical SciencesXiamen UniversityXiang'an South RoadXiamen361102FujianChina
- Xiang An Biomedicine LaboratorySchool of Pharmaceutical SciencesXiamen UniversityXiang'an South RoadXiamen361102FujianChina
| | - Guo‐sheng Hu
- State Key Laboratory of Cellular Stress BiologySchool of Pharmaceutical SciencesXiamen UniversityXiang'an South RoadXiamen361102FujianChina
- Fujian Provincial Key Laboratory of Innovative Drug Target ResearchSchool of Pharmaceutical SciencesXiamen UniversityXiang'an South RoadXiamen361102FujianChina
- Xiang An Biomedicine LaboratorySchool of Pharmaceutical SciencesXiamen UniversityXiang'an South RoadXiamen361102FujianChina
| | - Xing‐yi Shu
- State Key Laboratory of Cellular Stress BiologySchool of Pharmaceutical SciencesXiamen UniversityXiang'an South RoadXiamen361102FujianChina
- Fujian Provincial Key Laboratory of Innovative Drug Target ResearchSchool of Pharmaceutical SciencesXiamen UniversityXiang'an South RoadXiamen361102FujianChina
- Xiang An Biomedicine LaboratorySchool of Pharmaceutical SciencesXiamen UniversityXiang'an South RoadXiamen361102FujianChina
| | - Yan Liu
- Department of Anus and BowelsAffiliated Nanhua HospitalUniversity of South ChinaDongfeng South RoadHengyang421002HunanChina
| | - Jun Du
- State Key Laboratory of Cellular Stress BiologySchool of Pharmaceutical SciencesXiamen UniversityXiang'an South RoadXiamen361102FujianChina
- Fujian Provincial Key Laboratory of Innovative Drug Target ResearchSchool of Pharmaceutical SciencesXiamen UniversityXiang'an South RoadXiamen361102FujianChina
- Xiang An Biomedicine LaboratorySchool of Pharmaceutical SciencesXiamen UniversityXiang'an South RoadXiamen361102FujianChina
| | - Zi‐jing Wen
- State Key Laboratory of Cellular Stress BiologySchool of Pharmaceutical SciencesXiamen UniversityXiang'an South RoadXiamen361102FujianChina
- Fujian Provincial Key Laboratory of Innovative Drug Target ResearchSchool of Pharmaceutical SciencesXiamen UniversityXiang'an South RoadXiamen361102FujianChina
- Xiang An Biomedicine LaboratorySchool of Pharmaceutical SciencesXiamen UniversityXiang'an South RoadXiamen361102FujianChina
| | - Jun‐yi Liu
- State Key Laboratory of Molecular Vaccinology and Molecular DiagnosticsNational Institute of Diagnostics and Vaccine Development in Infectious DiseasesXiamen UniversityXiang'an South RoadXiamen361102FujianChina
| | - Hai‐hua Huang
- Department of PathologyThe Second Affiliated HospitalShantou University Medical CollegeDongxia North RoadShantou515041GuangdongChina
| | - Guo‐hui Tang
- Department of Anus and BowelsAffiliated Nanhua HospitalUniversity of South ChinaDongfeng South RoadHengyang421002HunanChina
| | - Wen Liu
- State Key Laboratory of Cellular Stress BiologySchool of Pharmaceutical SciencesXiamen UniversityXiang'an South RoadXiamen361102FujianChina
- Fujian Provincial Key Laboratory of Innovative Drug Target ResearchSchool of Pharmaceutical SciencesXiamen UniversityXiang'an South RoadXiamen361102FujianChina
- Xiang An Biomedicine LaboratorySchool of Pharmaceutical SciencesXiamen UniversityXiang'an South RoadXiamen361102FujianChina
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Chung C, Yeung VTY, Wong KCW. Prognostic and predictive biomarkers with therapeutic targets in breast cancer: A 2022 update on current developments, evidence, and recommendations. J Oncol Pharm Pract 2023; 29:1343-1360. [PMID: 35971313 DOI: 10.1177/10781552221119797] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
OBJECTIVE To evaluate and validate the recent and emerging data for prognostic and predictive biomarkers with therapeutic targets in breast cancer. DATA SOURCES A literature search from January 2015 to March 2022 was performed using the key terms breast cancer, clinical practice guidelines, gene mutations, genomic assay, immune cancer therapy, predictive and/or prognostic biomarkers, and targeted therapies. STUDY SELECTION AND DATA EXTRACTION Relevant clinical trials, meta-analyses, seminal articles, and published evidence- and consensus-based clinical practice guidelines in the English language were identified, reviewed and evaluated. DATA SYNTHESIS Breast cancer is a biologically heterogeneous disease, leading to wide variability in treatment responses and survival outcomes. Biomarkers for breast cancer are evolving from traditional biomarkers in immunohistochemistry (IHC) such as estrogen receptor (ER), progesterone receptor (PR) and epidermal growth factor receptor type 2 (HER2) to genetic biomarkers with therapeutic implications (e.g. breast cancer susceptibility gene 1/2 [BRCA1/2], estrogen receptor α [ESR1] gene mutation, HER2 gene mutation, microsatellite instability [MSI], phosphatidylinositol 3-kinase catalytic subunit 3Cα [PIK3CA] gene mutation, neurotrophic tyrosine receptor kinase [NTRK] gene mutation). In addition, current data are most robust for biomarkers in immunotherapy (e.g. programmed cell death receptor ligand-1 [PD-L1], microsatellite instability-high [MSI-H] or deficient mismatch repair [dMMR]). Oncotype DX assay remains the best validated gene expression assay that is both predictive and prognostic whereas MammaPrint is prognostic for genomic risk. CONCLUSIONS Biomarker-driven therapies have the potential to confer greater therapeutic advantages than standard-of-care therapies. The purported survival benefits associated with biomarker-driven therapies should be weighed against their potential harms.
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Affiliation(s)
- Clement Chung
- Department of Pharmacy, Houston Methodist West Hospital, Houston, TX, USA
| | - Vanessa T Y Yeung
- State Key Laboratory of Translational Oncology, Sir YK Pao Centre for Cancer, Department of Clinical Oncology, Hong Kong Cancer Institute, The Chinese University of Hong Kong, Hong Kong SAR
| | - Kenneth C W Wong
- State Key Laboratory of Translational Oncology, Sir YK Pao Centre for Cancer, Department of Clinical Oncology, Hong Kong Cancer Institute, The Chinese University of Hong Kong, Hong Kong SAR
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Champendal M, Marmy L, Malamateniou C, Sá Dos Reis C. Artificial intelligence to support person-centred care in breast imaging - A scoping review. J Med Imaging Radiat Sci 2023; 54:511-544. [PMID: 37183076 DOI: 10.1016/j.jmir.2023.04.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 04/05/2023] [Accepted: 04/11/2023] [Indexed: 05/16/2023]
Abstract
AIM To overview Artificial Intelligence (AI) developments and applications in breast imaging (BI) focused on providing person-centred care in diagnosis and treatment for breast pathologies. METHODS The scoping review was conducted in accordance with the Joanna Briggs Institute methodology. The search was conducted on MEDLINE, Embase, CINAHL, Web of science, IEEE explore and arxiv during July 2022 and included only studies published after 2016, in French and English. Combination of keywords and Medical Subject Headings terms (MeSH) related to breast imaging and AI were used. No keywords or MeSH terms related to patients, or the person-centred care (PCC) concept were included. Three independent reviewers screened all abstracts and titles, and all eligible full-text publications during a second stage. RESULTS 3417 results were identified by the search and 106 studies were included for meeting all criteria. Six themes relating to the AI-enabled PCC in BI were identified: individualised risk prediction/growth and prediction/false negative reduction (44.3%), treatment assessment (32.1%), tumour type prediction (11.3%), unnecessary biopsies reduction (5.7%), patients' preferences (2.8%) and other issues (3.8%). The main BI modalities explored in the included studies were magnetic resonance imaging (MRI) (31.1%), mammography (27.4%) and ultrasound (23.6%). The studies were predominantly retrospective, and some variations (age range, data source, race, medical imaging) were present in the datasets used. CONCLUSIONS The AI tools for person-centred care are mainly designed for risk and cancer prediction and disease management to identify the most suitable treatment. However, further studies are needed for image acquisition optimisation for different patient groups, improvement and customisation of patient experience and for communicating to patients the options and pathways of disease management.
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Affiliation(s)
- Mélanie Champendal
- School of Health Sciences HESAV, HES-SO; University of Applied Sciences Western Switzerland: Lausanne, CH.
| | - Laurent Marmy
- School of Health Sciences HESAV, HES-SO; University of Applied Sciences Western Switzerland: Lausanne, CH.
| | - Christina Malamateniou
- School of Health Sciences HESAV, HES-SO; University of Applied Sciences Western Switzerland: Lausanne, CH; Department of Radiography, Division of Midwifery and Radiography, School of Health Sciences, University of London, London, UK.
| | - Cláudia Sá Dos Reis
- School of Health Sciences HESAV, HES-SO; University of Applied Sciences Western Switzerland: Lausanne, CH.
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225
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Laouris P, Rodrigues MES, Costa SCV, Rala de Paula BH. Neoadjuvant immunotherapy in early-stage triple negative breast cancer. ANNALS OF TRANSLATIONAL MEDICINE 2023; 11:338. [PMID: 37675326 PMCID: PMC10477652 DOI: 10.21037/atm-23-1550] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 05/30/2023] [Indexed: 09/08/2023]
Affiliation(s)
- Panayiotis Laouris
- Early Phase Trials Unit, Division of Oncology, University of Cambridge, Cambridge, UK
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Schmidt G, Findeklee S, del Sol Martinez G, Georgescu MT, Gerlinger C, Nemat S, Klamminger GG, Nigdelis MP, Solomayer EF, Hamoud BH. Accuracy of Breast Ultrasonography and Mammography in Comparison with Postoperative Histopathology in Breast Cancer Patients after Neoadjuvant Chemotherapy. Diagnostics (Basel) 2023; 13:2811. [PMID: 37685349 PMCID: PMC10486727 DOI: 10.3390/diagnostics13172811] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Revised: 08/14/2023] [Accepted: 08/28/2023] [Indexed: 09/10/2023] Open
Abstract
INTRODUCTION Nowadays chemotherapy in breast cancer patients is optionally applied neoadjuvant, which allows for testing of tumor response to the chemotherapeutical treatment in vivo, as well as allowing a greater number of patients to benefit from a subsequent breast-conserving surgery. MATERIAL AND METHODS We compared breast ultrasonography, mammography, and clinical examination (palpation) results with postoperative histopathological findings after neoadjuvant chemotherapy, aiming to determine the most accurate prediction of complete remission and tumor-free resection margins. To this end, clinical and imaging data of 184 patients (193 tumors) with confirmed diagnosis of breast cancer and neoadjuvant therapy were analyzed. RESULTS After chemotherapy, tumors could be assessed by palpation in 91.7%, by sonography in 99.5%, and by mammography in 84.5% (chi-square p < 0.0001) of cases. Although mammography proved more accurate in estimating the exact neoadjuvant tumor size than breast sonography in total numbers (136/163 (83.44%) vs. 142/192 (73.96%), n.s.), 29 tumors could be assessed solely by means of breast sonography. A sonographic measurement was feasible in 192 cases (99.48%) post-chemotherapy and in all cases prior to chemotherapy. CONCLUSIONS We determined a superiority of mammography and breast sonography over clinical palpation in predicting neoadjuvant tumor size. However, neither examination method can predict either pCR or tumor margins with high confidence.
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Affiliation(s)
- Gilda Schmidt
- Department for Gynecology, Obstetrics and Reproductive Medicine, Saarland University Hospital, 66421 Homburg, Germany; (G.S.); (B.H.H.)
| | - Sebastian Findeklee
- Department for Gynecology, Obstetrics and Reproductive Medicine, Saarland University Hospital, 66421 Homburg, Germany; (G.S.); (B.H.H.)
| | - Gerda del Sol Martinez
- Department for Gynecology, Obstetrics and Reproductive Medicine, Saarland University Hospital, 66421 Homburg, Germany; (G.S.); (B.H.H.)
| | - Mihai-Teodor Georgescu
- “Prof. Dr. Al. Trestioreanu” Oncology Discipline, “Carol Davila” University of Medicine and Pharmacy, 020021 Bucharest, Romania
- “Prof. Dr. Al. Trestioreanu” Oncology Institute, 022328 Bucharest, Romania
| | - Christoph Gerlinger
- Department for Gynecology, Obstetrics and Reproductive Medicine, Saarland University Hospital, 66421 Homburg, Germany; (G.S.); (B.H.H.)
| | - Sogand Nemat
- Clinic for Diagnostic and Interventional Radiology, Medical Faculty, Saarland University, 66421 Homburg, Germany
| | - Gilbert Georg Klamminger
- Department for Gynecology, Obstetrics and Reproductive Medicine, Saarland University Hospital, 66421 Homburg, Germany; (G.S.); (B.H.H.)
| | - Meletios P. Nigdelis
- Department for Gynecology, Obstetrics and Reproductive Medicine, Saarland University Hospital, 66421 Homburg, Germany; (G.S.); (B.H.H.)
- Unit of Reproductive Endocrinology, 1st Department of Obstetrics and Gynecology, Papageorgiou General Hospital, Aristotle University of Thessaloniki, 564 03 Thessaloniki, Greece
| | - Erich-Franz Solomayer
- Department for Gynecology, Obstetrics and Reproductive Medicine, Saarland University Hospital, 66421 Homburg, Germany; (G.S.); (B.H.H.)
| | - Bashar Haj Hamoud
- Department for Gynecology, Obstetrics and Reproductive Medicine, Saarland University Hospital, 66421 Homburg, Germany; (G.S.); (B.H.H.)
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227
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Zhu S, Wu Y, Song B, Yi M, Yan Y, Mei Q, Wu K. Recent advances in targeted strategies for triple-negative breast cancer. J Hematol Oncol 2023; 16:100. [PMID: 37641116 PMCID: PMC10464091 DOI: 10.1186/s13045-023-01497-3] [Citation(s) in RCA: 21] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Accepted: 08/21/2023] [Indexed: 08/31/2023] Open
Abstract
Triple-negative breast cancer (TNBC), a highly aggressive subtype of breast cancer, negatively expresses estrogen receptor, progesterone receptor, and the human epidermal growth factor receptor 2 (HER2). Although chemotherapy is the main form of treatment for patients with TNBC, the effectiveness of chemotherapy for TNBC is still limited. The search for more effective therapies is urgent. Multiple targeted therapeutic strategies have emerged according to the specific molecules and signaling pathways expressed in TNBC. These include PI3K/AKT/mTOR inhibitors, epidermal growth factor receptor inhibitors, Notch inhibitors, poly ADP-ribose polymerase inhibitors, and antibody-drug conjugates. Moreover, immune checkpoint inhibitors, for example, pembrolizumab, atezolizumab, and durvalumab, are widely explored in the clinic. We summarize recent advances in targeted therapy and immunotherapy in TNBC, with the aim of serving as a reference for the development of individualized treatment of patients with TNBC in the future.
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Affiliation(s)
- Shuangli Zhu
- Department of Oncology, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Yuze Wu
- Department of Oncology, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Bin Song
- Cancer Center, Shanxi Bethune Hospital, Shanxi Academy of Medical Science, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, 030032, China
| | - Ming Yi
- Department of Breast Surgery, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310000, China
| | - Yuheng Yan
- Department of Oncology, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Qi Mei
- Cancer Center, Shanxi Bethune Hospital, Shanxi Academy of Medical Science, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, 030032, China.
- Cancer Center, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
| | - Kongming Wu
- Cancer Center, Shanxi Bethune Hospital, Shanxi Academy of Medical Science, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, 030032, China.
- Cancer Center, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
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228
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Dank M, Mühl D, Pölhös A, Csanda R, Herold M, Kovacs AK, Madaras L, Kulka J, Palhazy T, Tokes AM, Toth M, Ujhelyi M, Szasz AM, Herold Z. The Prediction Analysis of Microarray 50 (PAM50) Gene Expression Classifier Utilized in Indeterminate-Risk Breast Cancer Patients in Hungary: A Consecutive 5-Year Experience. Genes (Basel) 2023; 14:1708. [PMID: 37761848 PMCID: PMC10530528 DOI: 10.3390/genes14091708] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 08/24/2023] [Accepted: 08/26/2023] [Indexed: 09/29/2023] Open
Abstract
BACKGROUND Breast cancer has been categorized into molecular subtypes using immunohistochemical staining (IHC) and fluorescence in situ hybridization (FISH) since the early 2000s. However, recent research suggests that gene expression testing, specifically Prosigna® Prediction Analysis of Microarray 50 (PAM50), provides more accurate classification methods. In this retrospective study, we compared the results of IHC/FISH and PAM50 testing. We also examined the impact of various PAM50 parameters on overall survival (OS) and progression-free survival (PFS). RESULTS We analyzed 42 unilateral breast cancer samples, with 18 classified as luminal A, 10 as luminal B, 8 as Human epidermal growth factor receptor 2 (HER2)-positive, and 6 as basal-like using PAM50. Interestingly, 17 out of the 42 samples (40.47%) showed discordant results between histopathological assessment and the PAM50 classifier. While routine IHC/FISH resulted in classification differences for a quarter to a third of samples within each subtype, all basal-like tumors were misclassified. Hormone receptor-positive tumors (hazard rate: 8.7803; p = 0.0085) and patients who had higher 10-year recurrence risk scores (hazard rate: 1.0539; p = 0.0201) had shorter OS and PFS. CONCLUSIONS Our study supports the existing understanding of molecular subtypes in breast cancer and emphasizes the overlap between clinical characteristics and molecular subtyping. These findings underscore the value of gene expression profiling, such as PAM50, in improving treatment decisions for breast cancer patients.
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Affiliation(s)
- Magdolna Dank
- Division of Oncology, Department of Internal Medicine and Oncology, Semmelweis University, H-1083 Budapest, Hungary
| | - Dorottya Mühl
- Division of Oncology, Department of Internal Medicine and Oncology, Semmelweis University, H-1083 Budapest, Hungary
| | - Annamária Pölhös
- Division of Oncology, Department of Internal Medicine and Oncology, Semmelweis University, H-1083 Budapest, Hungary
| | - Renata Csanda
- Division of Oncology, Department of Internal Medicine and Oncology, Semmelweis University, H-1083 Budapest, Hungary
| | - Magdolna Herold
- Division of Oncology, Department of Internal Medicine and Oncology, Semmelweis University, H-1083 Budapest, Hungary
- Department of Internal Medicine and Hematology, Semmelweis University, H-1088 Budapest, Hungary
| | - Attila Kristof Kovacs
- Department of Pathology, Forensic and Insurance Medicine, Semmelweis University, H-1091 Budapest, Hungary
| | - Lilla Madaras
- Department of Pathology, Forensic and Insurance Medicine, Semmelweis University, H-1091 Budapest, Hungary
| | - Janina Kulka
- Department of Pathology, Forensic and Insurance Medicine, Semmelweis University, H-1091 Budapest, Hungary
| | - Timea Palhazy
- Department of Surgery, Transplantation and Gastroenterology, Semmelweis University, H-1082 Budapest, Hungary
| | - Anna-Maria Tokes
- Department of Pathology, Forensic and Insurance Medicine, Semmelweis University, H-1091 Budapest, Hungary
| | - Monika Toth
- Department of Radiology, Semmelweis University, H-1082 Budapest, Hungary
| | | | - Attila Marcell Szasz
- Division of Oncology, Department of Internal Medicine and Oncology, Semmelweis University, H-1083 Budapest, Hungary
| | - Zoltan Herold
- Division of Oncology, Department of Internal Medicine and Oncology, Semmelweis University, H-1083 Budapest, Hungary
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Mitsueda R, Toda H, Shinden Y, Fukuda K, Yasudome R, Kato M, Kikkawa N, Ohtsuka T, Nakajo A, Seki N. Oncogenic Targets Regulated by Tumor-Suppressive miR-30c-1-3p and miR-30c-2-3p: TRIP13 Facilitates Cancer Cell Aggressiveness in Breast Cancer. Cancers (Basel) 2023; 15:4189. [PMID: 37627217 PMCID: PMC10453418 DOI: 10.3390/cancers15164189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Revised: 07/26/2023] [Accepted: 08/17/2023] [Indexed: 08/27/2023] Open
Abstract
Accumulating evidence suggests that the miR-30 family act as critical players (tumor-suppressor or oncogenic) in a wide range of human cancers. Analysis of microRNA (miRNA) expression signatures and The Cancer Genome Atlas (TCGA) database revealed that that two passenger strand miRNAs, miR-30c-1-3p and miR-30c-2-3p, were downregulated in cancer tissues, and their low expression was closely associated with worse prognosis in patients with BrCa. Functional assays showed that miR-30c-1-3p and miR-30c-2-3p overexpression significantly inhibited cancer cell aggressiveness, suggesting these two miRNAs acted as tumor-suppressors in BrCa cells. Notably, involvement of passenger strands of miRNAs is a new concept of cancer research. Further analyses showed that seven genes (TRIP13, CCNB1, RAD51, PSPH, CENPN, KPNA2, and MXRA5) were putative targets of miR-30c-1-3p and miR-30c-2-3p in BrCa cells. Expression of seven genes were upregulated in BrCa tissues and predicted a worse prognosis of the patients. Among these genes, we focused on TRIP13 and investigated the functional significance of this gene in BrCa cells. Luciferase reporter assays showed that TRIP13 was directly regulated by these two miRNAs. TRIP13 knockdown using siRNA attenuated BrCa cell aggressiveness. Inactivation of TRIP13 using a specific inhibitor prevented the malignant transformation of BrCa cells. Exploring the molecular networks controlled by miRNAs, including passenger strands, will facilitate the identification of diagnostic markers and therapeutic target molecules in BrCa.
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Affiliation(s)
- Reiko Mitsueda
- Department of Digestive Surgery, Breast and Thyroid Surgery, Graduate School of Medical and Dental Sciences, Kagoshima University, Kagoshima 890-8520, Japan; (R.M.); (H.T.); (Y.S.); (K.F.); (R.Y.); (T.O.); (A.N.)
| | - Hiroko Toda
- Department of Digestive Surgery, Breast and Thyroid Surgery, Graduate School of Medical and Dental Sciences, Kagoshima University, Kagoshima 890-8520, Japan; (R.M.); (H.T.); (Y.S.); (K.F.); (R.Y.); (T.O.); (A.N.)
| | - Yoshiaki Shinden
- Department of Digestive Surgery, Breast and Thyroid Surgery, Graduate School of Medical and Dental Sciences, Kagoshima University, Kagoshima 890-8520, Japan; (R.M.); (H.T.); (Y.S.); (K.F.); (R.Y.); (T.O.); (A.N.)
| | - Kosuke Fukuda
- Department of Digestive Surgery, Breast and Thyroid Surgery, Graduate School of Medical and Dental Sciences, Kagoshima University, Kagoshima 890-8520, Japan; (R.M.); (H.T.); (Y.S.); (K.F.); (R.Y.); (T.O.); (A.N.)
| | - Ryutaro Yasudome
- Department of Digestive Surgery, Breast and Thyroid Surgery, Graduate School of Medical and Dental Sciences, Kagoshima University, Kagoshima 890-8520, Japan; (R.M.); (H.T.); (Y.S.); (K.F.); (R.Y.); (T.O.); (A.N.)
| | - Mayuko Kato
- Department of Functional Genomics, Graduate School of Medicine, Chiba University, Chiba 260-8670, Japan; (M.K.); (N.K.)
| | - Naoko Kikkawa
- Department of Functional Genomics, Graduate School of Medicine, Chiba University, Chiba 260-8670, Japan; (M.K.); (N.K.)
| | - Takao Ohtsuka
- Department of Digestive Surgery, Breast and Thyroid Surgery, Graduate School of Medical and Dental Sciences, Kagoshima University, Kagoshima 890-8520, Japan; (R.M.); (H.T.); (Y.S.); (K.F.); (R.Y.); (T.O.); (A.N.)
| | - Akihiro Nakajo
- Department of Digestive Surgery, Breast and Thyroid Surgery, Graduate School of Medical and Dental Sciences, Kagoshima University, Kagoshima 890-8520, Japan; (R.M.); (H.T.); (Y.S.); (K.F.); (R.Y.); (T.O.); (A.N.)
| | - Naohiko Seki
- Department of Functional Genomics, Graduate School of Medicine, Chiba University, Chiba 260-8670, Japan; (M.K.); (N.K.)
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Tinterri C, Di Maria Grimaldi S, Sagona A, Barbieri E, Darwish S, Bottini A, Canavese G, Gentile D. Comparison of Long-Term Oncological Results in Young Women with Breast Cancer between BRCA-Mutation Carriers Versus Non-Carriers: How Tumor and Genetic Risk Factors Influence the Clinical Prognosis. Cancers (Basel) 2023; 15:4177. [PMID: 37627205 PMCID: PMC10452863 DOI: 10.3390/cancers15164177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 08/17/2023] [Accepted: 08/18/2023] [Indexed: 08/27/2023] Open
Abstract
BACKGROUND Breast cancer (BC) is very uncommon in young women (YW) and it is unclear whether a BRCA mutation has prognostic implications. Our aim was to evaluate the characteristics of YW with BC by comparing the long-term oncological results between BRCA-mutation carriers and non-carriers. METHODS We retrospectively reviewed all the consecutive YW (aged 18-40 years) diagnosed with BC. Endpoints were disease-free survival (DFS), distant disease-free survival (DDFS), and overall survival (OS). RESULTS 63 YW with a BRCA mutation were compared with 339 YW without BRCA mutation. BRCA-mutation carriers were younger (60.3% versus 34.8% if age ≤ 35 years, p = 0.001) and presented with more aggressive tumors (66.7% versus 40.7% if G3, p = 0.001; 57.2% versus 12.4% if biological subtype triple-negative, p = 0.001; 73.0% versus 39.2% if Ki67 ≥ 25%, p = 0.001). Non-carriers presented significantly better DFS, DDFS, and OS compared with BRCA-mutation carriers. Neoadjuvant chemotherapy was found to be an independent protective factor for OS in BRCA-mutation carriers. CONCLUSIONS BC is more likely to present at a younger age (≤ 35 years) and with more aggressive characteristics (G3, triple-negative, Ki67 ≥ 25%) in YW with BRCA mutation compared with their non-mutated counterparts. Young BRCA-mutation carriers showed a poorer prognosis in terms of recurrence and survival compared with non-carriers. The implementation of neoadjuvant chemotherapy may improve survival in YW with BC and BRCA mutation.
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Affiliation(s)
- Corrado Tinterri
- Breast Unit, IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089 Rozzano, Milan, Italy; (C.T.); (S.D.M.G.); (A.S.); (E.B.); (S.D.); (A.B.); (G.C.)
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, 20090 Pieve Emanuele, Milan, Italy
| | - Simone Di Maria Grimaldi
- Breast Unit, IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089 Rozzano, Milan, Italy; (C.T.); (S.D.M.G.); (A.S.); (E.B.); (S.D.); (A.B.); (G.C.)
| | - Andrea Sagona
- Breast Unit, IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089 Rozzano, Milan, Italy; (C.T.); (S.D.M.G.); (A.S.); (E.B.); (S.D.); (A.B.); (G.C.)
| | - Erika Barbieri
- Breast Unit, IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089 Rozzano, Milan, Italy; (C.T.); (S.D.M.G.); (A.S.); (E.B.); (S.D.); (A.B.); (G.C.)
| | - Shadya Darwish
- Breast Unit, IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089 Rozzano, Milan, Italy; (C.T.); (S.D.M.G.); (A.S.); (E.B.); (S.D.); (A.B.); (G.C.)
| | - Alberto Bottini
- Breast Unit, IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089 Rozzano, Milan, Italy; (C.T.); (S.D.M.G.); (A.S.); (E.B.); (S.D.); (A.B.); (G.C.)
| | - Giuseppe Canavese
- Breast Unit, IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089 Rozzano, Milan, Italy; (C.T.); (S.D.M.G.); (A.S.); (E.B.); (S.D.); (A.B.); (G.C.)
| | - Damiano Gentile
- Breast Unit, IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089 Rozzano, Milan, Italy; (C.T.); (S.D.M.G.); (A.S.); (E.B.); (S.D.); (A.B.); (G.C.)
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, 20090 Pieve Emanuele, Milan, Italy
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Chamandi G, El-Hajjar L, El Kurdi A, Le Bras M, Nasr R, Lehmann-Che J. ER Negative Breast Cancer and miRNA: There Is More to Decipher Than What the Pathologist Can See! Biomedicines 2023; 11:2300. [PMID: 37626796 PMCID: PMC10452617 DOI: 10.3390/biomedicines11082300] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2023] [Revised: 08/03/2023] [Accepted: 08/08/2023] [Indexed: 08/27/2023] Open
Abstract
Breast cancer (BC), the most prevalent cancer in women, is a heterogenous disease. Despite advancements in BC diagnosis, prognosis, and therapeutics, survival rates have drastically decreased in the metastatic setting. Therefore, BC still remains a medical challenge. The evolution of high-throughput technology has highlighted gaps in the classification system of BCs. Of particular interest is the notorious triple negative BC, which was recounted as being heterogenous itself and it overlaps with distinct subtypes, namely molecular apocrine (MA) and luminal androgen (LAR) BCs. These subtypes are, even today, still misdiagnosed and poorly treated. As such, researchers and clinicians have been looking for ways through which to refine BC classification in order to properly understand the initiation, development, progression, and the responses to the treatment of BCs. One tool is biomarkers and, specifically, microRNA (miRNA), which are highly reported as associated with BC carcinogenesis. In this review, the diverse roles of miRNA in estrogen receptor negative (ER-) and androgen receptor positive (AR+) BC are depicted. While highlighting their oncogenic and tumor suppressor functions in tumor progression, we will discuss their diagnostic, prognostic, and predictive biomarker potentials, as well as their drug sensitivity/resistance activity. The association of several miRNAs in the KEGG-reported pathways that are related to ER-BC carcinogenesis is presented. The identification and verification of accurate miRNA panels is a cornerstone for tackling BC classification setbacks, as is also the deciphering of the carcinogenesis regulators of ER - AR + BC.
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Affiliation(s)
- Ghada Chamandi
- Department of Anatomy, Cell Biology and Physiological Sciences, Faculty of Medicine, American University of Beirut, 11-0236 Beirut, Lebanon; (G.C.); (L.E.-H.)
- Pathophysiology of Breast Cancer Team, INSERM U976, Immunologie Humaine, Pathophysiologie, Immunothérapie (HIPI), Université Paris Cité, 75010 Paris, France;
| | - Layal El-Hajjar
- Department of Anatomy, Cell Biology and Physiological Sciences, Faculty of Medicine, American University of Beirut, 11-0236 Beirut, Lebanon; (G.C.); (L.E.-H.)
- Office of Basic/Translational Research and Graduate Studies, Faculty of Medicine, American University of Beirut, 11-0236 Beirut, Lebanon
| | - Abdallah El Kurdi
- Department of Biochemistry and Molecular Genetics, Faculty of Medicine, American University of Beirut, 11-0236 Beirut, Lebanon;
| | - Morgane Le Bras
- Pathophysiology of Breast Cancer Team, INSERM U976, Immunologie Humaine, Pathophysiologie, Immunothérapie (HIPI), Université Paris Cité, 75010 Paris, France;
| | - Rihab Nasr
- Department of Anatomy, Cell Biology and Physiological Sciences, Faculty of Medicine, American University of Beirut, 11-0236 Beirut, Lebanon; (G.C.); (L.E.-H.)
| | - Jacqueline Lehmann-Che
- Pathophysiology of Breast Cancer Team, INSERM U976, Immunologie Humaine, Pathophysiologie, Immunothérapie (HIPI), Université Paris Cité, 75010 Paris, France;
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Xulu KR, Nweke EE, Augustine TN. Delineating intra-tumoral heterogeneity and tumor evolution in breast cancer using precision-based approaches. Front Genet 2023; 14:1087432. [PMID: 37662839 PMCID: PMC10469897 DOI: 10.3389/fgene.2023.1087432] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 08/08/2023] [Indexed: 09/05/2023] Open
Abstract
The burden of breast cancer continues to increase worldwide as it remains the most diagnosed tumor in females and the second leading cause of cancer-related deaths. Breast cancer is a heterogeneous disease characterized by different subtypes which are driven by aberrations in key genes such as BRCA1 and BRCA2, and hormone receptors. However, even within each subtype, heterogeneity that is driven by underlying evolutionary mechanisms is suggested to underlie poor response to therapy, variance in disease progression, recurrence, and relapse. Intratumoral heterogeneity highlights that the evolvability of tumor cells depends on interactions with cells of the tumor microenvironment. The complexity of the tumor microenvironment is being unraveled by recent advances in screening technologies such as high throughput sequencing; however, there remain challenges that impede the practical use of these approaches, considering the underlying biology of the tumor microenvironment and the impact of selective pressures on the evolvability of tumor cells. In this review, we will highlight the advances made thus far in defining the molecular heterogeneity in breast cancer and the implications thereof in diagnosis, the design and application of targeted therapies for improved clinical outcomes. We describe the different precision-based approaches to diagnosis and treatment and their prospects. We further propose that effective cancer diagnosis and treatment are dependent on unpacking the tumor microenvironment and its role in driving intratumoral heterogeneity. Underwriting such heterogeneity are Darwinian concepts of natural selection that we suggest need to be taken into account to ensure evolutionarily informed therapeutic decisions.
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Affiliation(s)
- Kutlwano Rekgopetswe Xulu
- School of Anatomical Sciences, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Ekene Emmanuel Nweke
- Department of Surgery, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Tanya Nadine Augustine
- School of Anatomical Sciences, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
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233
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Shi J, Zhang L, Geng C. HER-2 ultra-low breast cancer: exploring the clinicopathological features and prognosis in a retrospective study. Front Oncol 2023; 13:1210314. [PMID: 37664018 PMCID: PMC10472273 DOI: 10.3389/fonc.2023.1210314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2023] [Accepted: 07/28/2023] [Indexed: 09/05/2023] Open
Abstract
Objective To explore the clinicopathological features of patients with ultra-low expression of human epidermal growth factor 2 (HER-2) in breast cancer and its impact on prognosis. Methods Data from 1024 patients with primary breast cancer having HER-2 ultra-low expression from January 01, 2018, to December 31, 2018, were collected and analyzed retrospectively. The clinicopathological features and prognosis were compared using a chi-squared test or Fisher exact probability method. COX regression analysis and log-rank test were used to explore the factors related to the postoperative 5-year survival rate. All analytical data were defined as statistically significant (P < 0.05). Results Overall survival (OS) was higher in the HER-2 ultra-low group compared to the low expression group (P = 0.022). The tumor diameter, lymph node metastasis (LNM), and Ki67 expression were factors affecting DFS in the HER-2 ultra-low expression group (P < 0.05). The tumor diameter and LNM were risk factors affecting the OS (P < 0.05) in the HER-2 ultra-low expression group. LNM and Ki67 expression were risk factors affecting DFS (P < 0.05) in the HER-2 low expression group. LNM was considered an independent risk factor affecting OS (P < 0.05). Conclusion Breast cancer with HER-2 ultra-low expression has differences in the clinicopathological features. Breast cancer with HER-2 low expression is more aggressive and has a worse prognosis. This study provides a reference to consider in the treatment of HER-2-low and -ultra-low expression breast cancer.
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Affiliation(s)
| | | | - Cuizhi Geng
- Department of Breast Oncology, Fourth Hospital of Hebei Medical University, Shijiazhuang, China
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234
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Zhuang Y, Zhang F, Xu Y, He L, Huang W, Hong C, Cui Y. Evaluating the expression of heat shock protein 27 and topoisomerase II α in a retrospective cohort of patients diagnosed with locally advanced breast cancer and treated with neoadjuvant anthracycline-based chemotherapies. Front Oncol 2023; 13:1067179. [PMID: 37675221 PMCID: PMC10478710 DOI: 10.3389/fonc.2023.1067179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Accepted: 07/21/2023] [Indexed: 09/08/2023] Open
Abstract
Background Neoadjuvant anthracycline-based chemotherapy (NAC) is a major regimen for the treatment of local advanced breast cancer (LABC), while resistance to NAC remains a paramount clinical obstacle. To investigate the role of heat shock protein 27 (Hsp27) and/or topoisomerase IIα (TopoIIα) in LABC patients treated with NAC, we performed this retrospective study. Methods Associations of Hsp27 transcripts with clinic-pathological characteristics, survival and drug response were investigated in public databases. Hsp27-related genes were identified, followed by functional enrichment analyses. Besides, two protein-protein interaction networks were built. Then, tumors from 103 patients who were diagnosed with LABC and received NAC were collected, and Hsp27 and TopoIIα were examined by Immunohistochemistry (IHC). Chi-square or Fisher's exact tests were performed, as well as survival analyses. Results Either at the transcriptional level in public databases or at the protein level tested by IHC, a high level of Hsp27 was associated with aggressive tumor characteristics such as lymph node invasion and chemotherapy resistance. Hsp27-related genes mostly involved in the metabolic pathway and the gamete generation biological process. An elevated Hsp27 indicated a poor prognosis in patients with breast cancer (log-rank test P = 0.002 and 0.004 for disease-free survival [DFS] and overall survival [OS], respectively), while it might not be an independent predictor. Of note, tumors with high TopoIIα expression (TopoIIα+) was less likely to express Hsp27 (Hsp27+), in contrast to those with TopoIIα negativity (31.1% vs. 86.2%, P<0.001), and survival analyses revealed that patients with Hsp27+ and TopoIIα- tumors had a significantly lower DFS and OS (log-rank test P < 0.001 and 0.001, respectively), in contrast to the other three groups. Conclusions Hsp27 was associated with aggressive breast cancers and more predictable for the prognosis of LABC patients treated with NAC when concomitantly considering TopoIIα expression.
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Affiliation(s)
- Yixuan Zhuang
- Guangdong Provincial Key Laboratory for Breast Cancer Diagnosis and Treatment, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, China
- Department of Pathology, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, China
| | - Fan Zhang
- Oncology Research Laboratory, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, China
| | - Yue Xu
- Guangdong Provincial Key Laboratory for Breast Cancer Diagnosis and Treatment, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, China
| | - Lifang He
- Breast Center, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, China
| | - Wenhe Huang
- Department of Breast and Thyroid Surgery, Xiang’an Hospital of Xiamen University, Xiamen, Fujian, China
| | - Chaoqun Hong
- Oncology Research Laboratory, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, China
| | - Yukun Cui
- Guangdong Provincial Key Laboratory for Breast Cancer Diagnosis and Treatment, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, China
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Park GE, Kang BJ, Kim SH, Jung NY. The Role of Diffusion-Weighted Imaging Based on Maximum-Intensity Projection in Young Patients with Marked Background Parenchymal Enhancement on Contrast-Enhanced Breast MRI. Life (Basel) 2023; 13:1744. [PMID: 37629601 PMCID: PMC10455098 DOI: 10.3390/life13081744] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 08/03/2023] [Accepted: 08/11/2023] [Indexed: 08/27/2023] Open
Abstract
Diffusion-weighted imaging (DWI) utilizing maximum-intensity projection (MIP) was suggested as a cost-effective alternative tool without the risk of gadolinium-based contrast agents. The purpose of this study was to investigate whether DWI MIPs played a supportive role in young (≤60) patients with marked background parenchymal enhancement (BPE) on contrast-enhanced MRI (CE-MRI). The research included 1303 patients with varying degrees of BPE, and correlations between BPE on CE-MRI, the background diffusion signal (BDS) on DWI, and clinical parameters were analyzed. Lesion detection scores were compared between CE-MRI and DWI, with DWI showing higher scores. Among the 186 lesions in 181 patients with marked BPE on CE-MRI, the main lesion on MIPs of CE-MRI was partially or completely seen in 88.7% of cases, while it was not seen in 11.3% of cases. On the other hand, the main lesion on MIPs of DWI was seen in 91.4% of cases, with only 8.6% of cases showing no visibility. DWI achieved higher scores for lesion detection compared to CE-MRI. The presence of a marked BDS was significantly associated with a lower likelihood of a higher DWI score (p < 0.001), and non-mass lesions were associated with a decreased likelihood of a higher DWI score compared with mass lesions (p = 0.196). In conclusion, the inclusion of MIPs of DWI in the preoperative evaluation of breast cancer patients, particularly young women with marked BPE, proved highly beneficial in improving the overall diagnostic process.
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Affiliation(s)
- Ga-Eun Park
- Department of Radiology, Seoul Saint Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea; (G.-E.P.); (B.-J.K.); (S.-h.K.)
| | - Bong-Joo Kang
- Department of Radiology, Seoul Saint Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea; (G.-E.P.); (B.-J.K.); (S.-h.K.)
| | - Sung-hun Kim
- Department of Radiology, Seoul Saint Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea; (G.-E.P.); (B.-J.K.); (S.-h.K.)
| | - Na-Young Jung
- Department of Radiology, Uijeongbu Eulji Medical Center, College of Medicine, Eulji University, Uijeongbu 11759, Republic of Korea
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Tinterri C, Canavese G, Gatzemeier W, Barbieri E, Bottini A, Sagona A, Caraceni G, Testori A, Di Maria Grimaldi S, Dani C, Boni L, Bruzzi P, Fernandes B, Scorsetti M, Zambelli A, Gentile D. Sentinel lymph node biopsy versus axillary lymph node dissection in breast cancer patients undergoing mastectomy with one to two metastatic sentinel lymph nodes: sub-analysis of the SINODAR-ONE multicentre randomized clinical trial and reopening of enrolment. Br J Surg 2023; 110:1143-1152. [PMID: 37471574 PMCID: PMC10492188 DOI: 10.1093/bjs/znad215] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 05/15/2023] [Accepted: 06/13/2023] [Indexed: 07/22/2023]
Abstract
BACKGROUND The initial results of the SINODAR-ONE randomized clinical trial reported that patients with T1-2 breast cancer and one to two macrometastatic sentinel lymph nodes treated with breast-conserving surgery, sentinel lymph node biopsy only, and adjuvant therapy did not present worse 3-year survival, regional recurrence, or distant recurrence rates compared with those treated with axillary lymph node dissection. To extend the recommendation of axillary lymph node dissection omission even in patients treated with mastectomy, a sub-analysis of the SINODAR-ONE trial is presented here. METHODS Patients with T1-2 breast cancer and no more than two metastatic sentinel lymph nodes undergoing mastectomy were analysed. After sentinel lymph node biopsy, patients were randomly assigned to receive either axillary lymph node dissection followed by adjuvant treatment (standard arm) or adjuvant treatment alone (experimental arm). The primary endpoint was overall survival. The secondary endpoint was recurrence-free survival. RESULTS A total of 218 patients were treated with mastectomy; 111 were randomly assigned to the axillary lymph node dissection group and 107 to the sentinel lymph node biopsy-only group. At a median follow-up of 33.0 months, there were three deaths (two deaths in the axillary lymph node dissection group and one death in the sentinel lymph node biopsy-only group). There were five recurrences in each treatment arm. No axillary lymph node recurrence was observed. The 5-year overall survival rates were 97.8 and 98.7 per cent in the axillary lymph node dissection treatment arm and the sentinel lymph node biopsy-only treatment arm, respectively (P = 0.597). The 5-year recurrence-free survival rates were 95.7 and 94.1 per cent in the axillary lymph node dissection treatment arm and the sentinel lymph node biopsy treatment arm, respectively (P = 0.821). CONCLUSION In patients with T1-2 breast cancer and one to two macrometastatic sentinel lymph nodes treated with mastectomy, the overall survival and recurrence-free survival rates of patients treated with sentinel lymph node biopsy only were not inferior to those treated with axillary lymph node dissection. To strengthen the conclusion of the trial, the enrolment of patients treated with mastectomy was reopened as a single-arm experimental study. REGISTRATION NUMBER NCT05160324 (http://www.clinicaltrials.gov).
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Affiliation(s)
- Corrado Tinterri
- Breast Unit, IRCCS Humanitas Research Hospital, Milan, Italy
- Department of Biomedical Sciences, Humanitas University, Milan, Italy
| | | | | | - Erika Barbieri
- Breast Unit, IRCCS Humanitas Research Hospital, Milan, Italy
| | - Alberto Bottini
- Breast Unit, IRCCS Humanitas Research Hospital, Milan, Italy
| | - Andrea Sagona
- Breast Unit, IRCCS Humanitas Research Hospital, Milan, Italy
| | - Giulia Caraceni
- Breast Unit, IRCCS Humanitas Research Hospital, Milan, Italy
| | - Alberto Testori
- Breast Unit, IRCCS Humanitas Research Hospital, Milan, Italy
| | | | - Carla Dani
- Department of Epidemiology, Biostatistics and Clinical Trials, IRCCS S. Martino, IST, Genoa, Italy
| | - Luca Boni
- Department of Epidemiology, Biostatistics and Clinical Trials, IRCCS S. Martino, IST, Genoa, Italy
| | - Paolo Bruzzi
- Department of Epidemiology, Biostatistics and Clinical Trials, IRCCS S. Martino, IST, Genoa, Italy
| | - Bethania Fernandes
- Department of Pathology, IRCCS Humanitas Research Hospital, Milan, Italy
| | - Marta Scorsetti
- Department of Biomedical Sciences, Humanitas University, Milan, Italy
- Department of Radiotherapy and Radiosurgery, IRCCS Humanitas Research Hospital, Milan, Italy
| | - Alberto Zambelli
- Department of Biomedical Sciences, Humanitas University, Milan, Italy
- Medical Oncology and Haematology Unit, IRCCS Humanitas Research Hospital, Milan, Italy
| | - Damiano Gentile
- Breast Unit, IRCCS Humanitas Research Hospital, Milan, Italy
- Department of Biomedical Sciences, Humanitas University, Milan, Italy
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Abbas Syed R, Davey MG, Richard V, Miller N, Kerin MJ. Biological Implications of MicroRNAs as Regulators and Biomarkers of Therapeutic Toxicities in Breast Cancer. Int J Mol Sci 2023; 24:12694. [PMID: 37628874 PMCID: PMC10454054 DOI: 10.3390/ijms241612694] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2023] [Revised: 07/29/2023] [Accepted: 08/07/2023] [Indexed: 08/27/2023] Open
Abstract
Contemporary breast cancer management includes surgical resection combined with a multimodal approach, including chemotherapy, radiotherapy, endocrine therapy, and targeted therapies. Breast cancer treatment is now personalised in accordance with disease and host factors, which has translated to enhanced outcomes for the vast majority of patients. Unfortunately, the treatment of the disease involves patients developing treatment-induced toxicities, with cardiovascular and metabolic side effects having negative implications for long-term quality-of-life metrics. MicroRNAs (miRNAs) are a class of small non-coding ribonucleic acids that are 17 to 25 nucleotides in length, which have utility in modifying genetic expression by working at a post-transcriptional cellular level. miRNAs have involvement in modulating breast cancer development, which is well described, with these biomarkers acting as important regulators of disease, as well as potential diagnostic and therapeutic biomarkers. This review focuses on highlighting the role of miRNAs as regulators and biomarkers of disease, particularly in breast cancer management, with a specific mention of the potential value of miRNAs in predicting treatment-related cardiovascular toxicity.
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Affiliation(s)
- Raza Abbas Syed
- Discipline of Surgery, Lambe Institute for Translational Research, University of Galway, H91 YR71 Galway, Ireland; (M.G.D.)
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Bai Q, Lv H, Bao L, Yang Y, Zhang X, Chang H, Xue T, Ren M, Zhu X, Zhou X, Yang W. Invasive Breast Cancer with HER2 ≥4.0 and <6.0: Risk Classification and Molecular Typing by a 21-Gene Expression Assay and MammaPrint Plus BluePrint Testing. BREAST CANCER (DOVE MEDICAL PRESS) 2023; 15:563-575. [PMID: 37554155 PMCID: PMC10406110 DOI: 10.2147/bctt.s420738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Accepted: 07/26/2023] [Indexed: 08/10/2023]
Abstract
PURPOSE To investigate the HER2 status and clinicopathological features in invasive breast cancer with HER2 ≥4.0 and <6.0, which has always been controversial. METHODS Forty breast cancer cases with HER2 ≥4.0 and <6.0 by fluorescence in situ hybridization (FISH) were collected and classified into two groups based on the HRE2/CEP17 ratio (Group A: ≥2.0, n=22; Group B: <2.0, n=18). Clinicopathological characteristics, HER2 status, risk classification, and molecular typing were further analyzed and compared by 21-Gene expression assay and MammaPrint plus BluePrint test. RESULTS The majority of cases in both groups were invasive carcinoma (NOS), with histological grade II, HR+, Ki-67 ≥20%, HER2 2+, and a high risk of recurrence, although younger patients and lymph node metastases were more common in Group A. Surprisingly, all HR+ breast cancers in both groups were classified as luminal-type, HR- cases were all basal-type or unknown, and the index of HER2 in all cases was <0.000 using the BluePrint test, which indicated that HER2 status should be negative. Furthermore, the level of HER2 mRNA expression in all cases of both groups was <10.7, which was defined as HER2 negative by the 21-Gene expression assay. In addition, 10 patients of Group A received anti-HER2 neoadjuvant therapy; only one patient with HR- achieved Grade 5 based on the Miller-Payne system, whereas none of the patients achieved pathological complete response (pCR) based on the Residual Cancer Burden system. CONCLUSION Group A breast cancer, which has always been unquestionably diagnosed as HER2 amplification, was more likely to be HER2 negative and derived less benefit from anti-HER2 neoadjuvant chemotherapy. Group A breast cancer should be distinguished from classical HER2-positive breast cancers when assessing HER2 FISH, and a larger cohort of Group A patients should be included in further studies.
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Affiliation(s)
- Qianming Bai
- Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, 200032, People’s Republic of China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, People’s Republic of China
- Institute of Pathology, Fudan University, Shanghai, 200032, People’s Republic of China
| | - Hong Lv
- Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, 200032, People’s Republic of China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, People’s Republic of China
- Institute of Pathology, Fudan University, Shanghai, 200032, People’s Republic of China
| | - Longlong Bao
- Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, 200032, People’s Republic of China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, People’s Republic of China
- Institute of Pathology, Fudan University, Shanghai, 200032, People’s Republic of China
| | - Yu Yang
- Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, 200032, People’s Republic of China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, People’s Republic of China
- Institute of Pathology, Fudan University, Shanghai, 200032, People’s Republic of China
| | - Xin Zhang
- Department of Pathology, Fudan University Zhongshan Hospital, Shanghai, 200032, People’s Republic of China
| | - Heng Chang
- Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, 200032, People’s Republic of China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, People’s Republic of China
- Institute of Pathology, Fudan University, Shanghai, 200032, People’s Republic of China
| | - Tian Xue
- Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, 200032, People’s Republic of China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, People’s Republic of China
- Institute of Pathology, Fudan University, Shanghai, 200032, People’s Republic of China
| | - Min Ren
- Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, 200032, People’s Republic of China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, People’s Republic of China
- Institute of Pathology, Fudan University, Shanghai, 200032, People’s Republic of China
| | - Xiaoli Zhu
- Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, 200032, People’s Republic of China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, People’s Republic of China
- Institute of Pathology, Fudan University, Shanghai, 200032, People’s Republic of China
| | - Xiaoyan Zhou
- Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, 200032, People’s Republic of China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, People’s Republic of China
- Institute of Pathology, Fudan University, Shanghai, 200032, People’s Republic of China
| | - Wentao Yang
- Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, 200032, People’s Republic of China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, People’s Republic of China
- Institute of Pathology, Fudan University, Shanghai, 200032, People’s Republic of China
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Cakir Pekoz B, Dilek O, Koseci T, Tas ZA, Irkorucu O, Gulek B. Can peritumoral edema evaluated by Magnetic Resonance Imaging before neoadjuvant chemotherapy predict complete pathological response in breast cancer? Scott Med J 2023; 68:121-128. [PMID: 37161314 DOI: 10.1177/00369330231174230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
BACKGROUND AND AIMS The complete pathological response (pCR) following neoadjuvant chemotherapy (NAC) in breast cancer is essential for the accurate prediction of prognosis. We aimed to evaluate the efficacy of the presence and type of peritumoral edema detected by magnetic resonance imaging (MRI) in predicting pCR to NAC in breast cancer patients. METHODS AND RESULTS One hundred five patients with the diagnosis of invasive carcinoma were evaluated by MRI before NAC. Edema was evaluated in fat-suppressed T2-weighted images. The patients were categorized into three groups: patients with no peritumoral edema, patients with peritumoral edema, and patients demonstrating subcutaneous edema. The cases were categorized as being pCR and non-pCR. Molecular subtypes, lymphovascular invasion (LVI), tumor size, and apparent diffusion coefficient (ADC) were evaluated. A positive relationship was found between the presence of edema and tumor size. Subcutaneous edema was found to be statistically higher in non-pCR patients. While the number of pCR patients with subcutaneous edema was 17 (30.4%), the number of non-pCR patients with subcutaneous edema was 26 (53.1%) (p = 0.018). LVI was found to be statistically higher in patients with edema. The number of edema-negative and LVI (+) patients was 4 (15.4%), while the number of edema-positive and LVI (+) patients was 28 (35.4%) (p = 0.042). Intratumoral and peritumoral ADC values were significantly higher in tumors with edema. CONCLUSION The presence of subcutaneous edema and LVI may be utilized for the prediction of pCR outcomes in breast cancer patients scheduled for NAC treatment.
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Affiliation(s)
- Burcak Cakir Pekoz
- Department of Radiology, University of Health Sciences-Adana Health Practice and Research Center, Adana, Turkey
| | - Okan Dilek
- Department of Radiology, University of Health Sciences-Adana Health Practice and Research Center, Adana, Turkey
| | - Tolga Koseci
- Department of Medical Oncology and Internal Medicine, Cukurova University Faculty of Medicine, Adana, Turkey
| | - Zeynel Abidin Tas
- Department of Pathology, University of Health Sciences-Adana Health Practice and Research Center, Adana, Turkey
| | - Oktay Irkorucu
- Department of Clinical Sciences, University of Sharjah, College of Medicine, Sharjah, United Arab Emirates
| | - Bozkurt Gulek
- Department of Radiology, University of Health Sciences-Adana Health Practice and Research Center, Adana, Turkey
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Schreiber J, Ignatov A, Burger E, Meinecke AM, Eggemann H. Breast cancer therapy in women under 35 years and between 50 and 69 years: influence of the observation period. J Cancer Res Clin Oncol 2023; 149:5665-5676. [PMID: 36538146 DOI: 10.1007/s00432-022-04520-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Accepted: 12/03/2022] [Indexed: 12/24/2022]
Abstract
PURPOSE In recent years, therapeutic strategies based on tumour biology have increased significantly. We aimed to provide an overview of the recent changes in patient characteristics, treatment procedures and survival factors for two groups of patients: women younger than 35 years and women between 50 and 69 years. METHODS We used data from the population-based Cancer Registry Magdeburg. Subjects included women with non-metastatic breast cancer treated between 2000 and 2015. We compared between two observation periods: 2000-2007 and 2008-2015. RESULTS There was an increase in patient survival from the first to the second observation period. Tumour characteristics and treatment modalities changed, especially in the group of older patients. The proportion of prognostically more favourable tumour subtypes, such as Luminal A, increased significantly. Between 2008 and 2015, there were more hormone receptor-positive, lymph-node-negative, human epidermal growth factor receptor-2 (HER2)-negative and well-differentiated tumours. Surgical methods were associated with significantly reduced radicality, while the rate of neoadjuvant therapy increased in both groups. There was a decrease in cyclophosphamide, methotrexate and 5-fluoruracil (CMF) and anthracycline therapies, but taxane-containing chemotherapy increased. While tamoxifen was used more frequently in younger patients in the later observation period, its use was reduced in older patients, superseded by aromatase inhibitors. Furthermore, the use of immune therapy increased. CONCLUSION In both age groups, but primarily in older patients, there were significant changes in tumour biology and treatment options between the two observation periods. These changes have led to a continuous improvement in patient outcomes.
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Affiliation(s)
- J Schreiber
- Department of Obstetrics and Gynecology, Klinikum Magdeburg, Birkenallee 34, 39130, Magdeburg, Germany
| | - A Ignatov
- Department of Obstetrics and Gynecology, Otto-von-Guericke University, Gerhard-Hauptmann-Str. 35, 39108, Magdeburg, Germany
| | - E Burger
- Cancer Registry Magdeburg, Magdeburg, Germany
| | - A-M Meinecke
- Department of Obstetrics and Gynecology, Otto-von-Guericke University, Gerhard-Hauptmann-Str. 35, 39108, Magdeburg, Germany
| | - H Eggemann
- Department of Obstetrics and Gynecology, Klinikum Magdeburg, Birkenallee 34, 39130, Magdeburg, Germany.
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Crocetti E, Ravaioli A, Giuliani O, Bucchi L, Vattiato R, Mancini S, Zamagni F, Vitali B, Balducci C, Baldacchini F, Falcini F. Female breast cancer subtypes in the Romagna Unit of the Emilia-Romagna cancer registry, and estimated incident cases by subtypes and age in Italy in 2020. J Cancer Res Clin Oncol 2023; 149:7299-7304. [PMID: 36922443 PMCID: PMC10374783 DOI: 10.1007/s00432-023-04593-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 01/18/2023] [Indexed: 03/17/2023]
Abstract
PURPOSE The aim of this study was to estimate the Italian burden of incident breast cancer (BC) by subtypes, according to the distribution of hormonal receptor (HR) status and expression of human epidermal growth factor 2 (HER2). METHODS Female breast cancers incidence in the Romagna Unit of the Emilia-Romagna registry (n. 10,711) were grouped into: HR+ /HER2-, HR+ /HER2+ , HR-/HER2+ , HR-/HER2- and missing, and by age: < 50, 50-69 and 70+ years. Data were compared with other published Italian population-bases series before using them for national estimates. We used national and regional numbers of expected breast cancers published by the Italian network of cancer registries considering the age- and geographic-specific variation of the Italian population. RESULTS Overall, 70.7% of incident BC cases are expected to be HR+ /HER2-, 8.5% HR+ /HER2+ , 7.5% HR-/HER2-, 4.1% HR-/HER2+ and 9.3% missing. The global ranking is similar across age-groups but with age-specific differences. The proportion of missing was around 3-times lower than in the other Italian published population-based series and similar to the SEER one. In Italy, are estimated 38,841 HR+ /HER2- breast cancer cases, 4665 HR+ /HER2+ , 4098 HR-/HER2-, 2281 HR-/HER2+ , and 5092 not specified. Numbers by age-group were provided. CONCLUSIONS The present estimates relied on high-quality population-based data and provide a clinically relevant information on the burden of breast cancer subtypes. These data will support the planning of therapy needs for oncologists, decision-makers, and all other stakeholders.
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Affiliation(s)
- Emanuele Crocetti
- Romagna Unit of the Emilia-Romagna Cancer Registry, Romagna Cancer Institute, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) Dino Amadori, Forlì, Meldola, Italy.
| | - Alessandra Ravaioli
- Romagna Unit of the Emilia-Romagna Cancer Registry, Romagna Cancer Institute, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) Dino Amadori, Forlì, Meldola, Italy.
| | - Orietta Giuliani
- Romagna Unit of the Emilia-Romagna Cancer Registry, Romagna Cancer Institute, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) Dino Amadori, Forlì, Meldola, Italy
| | - Lauro Bucchi
- Romagna Unit of the Emilia-Romagna Cancer Registry, Romagna Cancer Institute, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) Dino Amadori, Forlì, Meldola, Italy
| | - Rosa Vattiato
- Romagna Unit of the Emilia-Romagna Cancer Registry, Romagna Cancer Institute, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) Dino Amadori, Forlì, Meldola, Italy
| | - Silvia Mancini
- Romagna Unit of the Emilia-Romagna Cancer Registry, Romagna Cancer Institute, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) Dino Amadori, Forlì, Meldola, Italy
| | - Federica Zamagni
- Romagna Unit of the Emilia-Romagna Cancer Registry, Romagna Cancer Institute, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) Dino Amadori, Forlì, Meldola, Italy
| | - Benedetta Vitali
- Romagna Unit of the Emilia-Romagna Cancer Registry, Romagna Cancer Institute, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) Dino Amadori, Forlì, Meldola, Italy
| | - Chiara Balducci
- Romagna Unit of the Emilia-Romagna Cancer Registry, Romagna Cancer Institute, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) Dino Amadori, Forlì, Meldola, Italy
| | - Flavia Baldacchini
- Romagna Unit of the Emilia-Romagna Cancer Registry, Romagna Cancer Institute, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) Dino Amadori, Forlì, Meldola, Italy
| | - Fabio Falcini
- Romagna Unit of the Emilia-Romagna Cancer Registry, Romagna Cancer Institute, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) Dino Amadori, Forlì, Meldola, Italy
- Local Health Authority, Cancer Prevention Unit, Forlì, Italy
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Li W, Lu N, Chen C, Lu X. Identifying the optimal cutoff point of Ki-67 in breast cancer: a single-center experience. J Int Med Res 2023; 51:3000605231195468. [PMID: 37652458 PMCID: PMC10478558 DOI: 10.1177/03000605231195468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Accepted: 08/01/2023] [Indexed: 09/02/2023] Open
Abstract
OBJECTIVE Ki-67 is associated with breast cancer subtypes, but the optimal cutoff point of Ki-67 has not been established in our center. We evaluated the cutoff point of Ki-67 in breast cancer and analyzed the associations among Ki-67, clinicopathological features, and prognosis. METHODS The clinicopathological data and prognostic information of patients with breast cancer treated in our center were retrospectively collected, and the optimal cutoff point of Ki-67 was determined by univariate and multivariate survival risk analyses. The cutoff point was used to group the patients, and the differences in the clinicopathological features and prognosis were analyzed between the two groups. RESULTS In total, 609 patients with estrogen receptor-positive and human epidermal growth factor receptor 2-negative primary breast cancer were enrolled. The mean Ki-67 value was 22.3% ± 15.4%, the median was 20%, and a cutoff point of 30% was an independent factor influencing recurrence-free survival. When 30% was used as the cutoff point, patients with a Ki-67 value of ≤30% had a better prognosis and lower tumor malignancy. CONCLUSION The optimal cutoff point of Ki-67 in breast cancer in our center is 30%.
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Affiliation(s)
- Wang Li
- School of Graduate, Bengbu Medical College, Bengbu, China
- Department of Breast Surgery, Affiliated Hospital of Jiaxing University (the First Hospital of Jiaxing), Jiaxing, China
| | - Ning Lu
- Department of Pathology, Affiliated Hospital of Jiaxing University (the First Hospital of Jiaxing), Jiaxing, China
| | - Caiping Chen
- Department of Breast Surgery, Affiliated Hospital of Jiaxing University (the First Hospital of Jiaxing), Jiaxing, China
| | - Xiang Lu
- School of Graduate, Bengbu Medical College, Bengbu, China
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243
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Zhong Z, Ling L, Tao J, Xu W, Liu X, Qian C, Wang S, Deng J, Wang S, Zhou W, Pan H. Percutaneous microwave ablation combined with endocrine therapy versus standard therapy for elderly patients with HR-positive and HER2-negative invasive breast cancer: a propensity score-matched analysis of a multi-center, prospective cohort study. Gland Surg 2023; 12:940-951. [PMID: 37727345 PMCID: PMC10506117 DOI: 10.21037/gs-23-33] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Accepted: 06/15/2023] [Indexed: 09/21/2023]
Abstract
Background There is a growing trend to apply minimally invasive local treatments for elderly patients with early-stage breast cancer. As a minimally invasive thermal therapy, microwave ablation (MWA) has been attempted to treat breast cancer of small lesions, but its long-term local efficacy on elderly patients has seldom been reported. In this study, we aimed to compare outcomes of MWA combined with endocrine therapy to standard surgery combined with adjuvant therapy in the treatment of hormone receptor (HR)-positive and human epidermal growth factor receptor 2 (HER2)-negative invasive breast cancer for elderly patients. Methods This prospective multi-center cohort study enrolled patients over 70 years old diagnosed with HR-positive and HER2-negative early-stage invasive breast cancer between January 2016 and July 2021. Patients chose either non-randomized to undergo MWA combined with endocrine therapy (MWA group) or standard surgery combined with adjuvant therapy (surgery group). Endpoints for the comparisons were disease-free survival (DFS), overall survival (OS) and length of hospital stay (LOS) after adjusting for previously reported risk factors using propensity score matching (1:3). Results Of the enrolled 132 patients, 33 were in the MWA group and 99 were in the surgery group. MWA was successfully performed in all cases, and technical effectiveness was achieved in all cases. With a median follow-up of 31 months, only one case had local recurrence 23 months after MWA. MWA combined with endocrine therapy and standard surgery combined adjuvant therapy for elderly patients with breast cancer achieved similar DFS [hazard ratio, 0.536; 95% confidence interval (CI): 0.128-2.249] and OS (hazard ratio, 0.537; 95% CI: 0.089-3.235). Besides, MWA had much shorter LOS than standard surgery (7.1 versus 13.0 days, P<0.001). Conclusions MWA combined with endocrine therapy and standard surgery combined with adjuvant therapy for elderly breast cancer patients achieved similar outcomes. MWA combined with endocrine may be a feasible treatment strategy for elderly patients with HR-positive and HER2-negative invasive breast cancer.
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Affiliation(s)
- Zhaoyun Zhong
- Department of Breast Surgery, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Jiangsu Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Lijun Ling
- Department of Breast Surgery, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Jiangsu Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Jing Tao
- Department of Breast Surgery, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China
- Department of General Surgery, The Fourth Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Weiwei Xu
- Department of Breast Surgery, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Jiangsu Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Xiaoan Liu
- Department of Breast Surgery, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Jiangsu Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Chao Qian
- Department of General Surgery, Sir Run Run Hospital, Nanjing Medical University, Nanjing, China
| | - Siqi Wang
- Department of Radiology, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China
| | - Jing Deng
- Department of Ultrasonography, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China
| | - Shui Wang
- Department of Breast Surgery, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Jiangsu Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Wenbin Zhou
- Department of Breast Surgery, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Jiangsu Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Hong Pan
- Department of Breast Surgery, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Jiangsu Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, China
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Parikh P, Babu G, Singh R, Krishna V, Bhatt A, Bansal I, Rajappa S, Sahoo TP, Aggarwal S, Bapna A, Biswas G, Somashekhar SP, Bajpai J, Maniar V, Desai S, Raja T, Rath GK. Consensus guidelines for the management of HR-positive HER2/neu negative early breast cancer in India, SAARC region and other LMIC by DELPHI survey method. BMC Cancer 2023; 23:714. [PMID: 37525142 PMCID: PMC10391857 DOI: 10.1186/s12885-023-11121-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Accepted: 06/28/2023] [Indexed: 08/02/2023] Open
Abstract
BACKGROUND Precise prognostication is the key to optimum and effective treatment planning for early-stage hormone receptor (HR) positive, HER2/neu negative breast cancer patients. Differences in the breast cancer incidence and tumor anatomical features at diagnosis, pharmacogenomics data between Western and Indian women along with the vast diversity in the economic status and differences in insurance policies of these regions; suggest recommendations put forward for Western women might not be applicable to Indian/Asian women. Opinions from oncologists through a voting survey on various prognostic factors/tools to be considered for planning adjuvant therapy are consolidated in this report for the benefit of oncologists of the sub-continent, SAARC and Asia's LMIC (low and middle-income countries). METHODS A three-phase DELPHI survey was conducted to collect opinions on prognostic factors considered for planning adjuvant therapy in early-stage HR+/HER2/neu negative breast cancer patients. A panel of 25 oncologists with expertise in breast cancer participated in the survey conducted in 2021. The experts provided opinions as 'agree' or disagree' or 'not sure' in phases-1 and 2 which were conducted virtually; in the final phase-3, all the panel experts met in person and concluded the survey. RESULTS Opinions on 41 statements related to prognostic factors/tools and their implications in planning adjuvant endocrine/chemotherapy were collected. All the statements were supported by the latest data from the clinical trials (prospective/retrospective). The statements with opinions of consensus less than 66% were disseminated in phase-2, and later in phase-3 with supporting literature. In phase-3, all the opinions from panelists were consolidated and guidelines were framed. CONCLUSIONS This consensus guideline will assist oncologists of India, SAARC and LMIC countries in informed clinical decision-making on adjuvant treatment in early HR+/HER2/neu negative breast cancer patients.
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Affiliation(s)
- Purvish Parikh
- Dept of Clinical Hematology, Mahatma Gandhi Medical College Hospital, Jaipur, 302023, India.
| | - Govind Babu
- HCG Cancer Hospital, Bengaluru, 560027, India
| | - Randeep Singh
- Narayana Super speciality Hospital, Gurugram, 122002, India
| | - Vamshi Krishna
- Asian Institute of Gastroenterology, Hyderabad, 500082, India
| | - Amit Bhatt
- Avinash Cancer Clinic, Pune, 411004, India
| | - Indu Bansal
- Narayana Super speciality Hospital, Gurugram, 122002, India
| | - Senthil Rajappa
- Basavaratakam Indo American Cancer Hospital & Research Institute, Hyderabad, 500034, India
| | | | | | - Ajay Bapna
- Bhagwan Mahaveer Cancer Hospital and Research Centre, Jaipur, 302017, India
| | | | - S P Somashekhar
- Manipal Comprehensive Cancer Center, Manipal Hospital, Bengaluru, 560017, India
| | | | | | - Sharad Desai
- Mahatma Gandhi Cancer Hospital, Miraj, 416410, India
| | - T Raja
- Apollo Speciality Cancer Hospital, Chennai, 600035, India
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Höller A, Nguyen-Sträuli BD, Frauchiger-Heuer H, Ring A. "Diagnostic and Prognostic Biomarkers of Luminal Breast Cancer: Where are We Now?". BREAST CANCER (DOVE MEDICAL PRESS) 2023; 15:525-540. [PMID: 37533589 PMCID: PMC10392911 DOI: 10.2147/bctt.s340741] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/01/2023] [Accepted: 07/12/2023] [Indexed: 08/04/2023]
Abstract
Luminal breast cancers are hormone receptor (estrogen and/or progesterone) positive that are further divided into HER2-negative luminal A and HER2-positive luminal B subtypes. According to currently accepted convention, they represent the most common subtypes of breast cancer, accounting for approximately 70% of cases. Biomarkers play a critical role in the functional characterization, prognostication, and therapeutic prediction, rendering them indispensable for the clinical management of invasive breast cancer. Traditional biomarkers include clinicopathological parameters, which are increasingly extended by genetic and other molecular markers, enabling the comprehensive characterization of patients with luminal breast cancer. Liquid biopsies capturing and analyzing circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA) are emerging technologies that envision personalized management through precision oncology. This article reviews key biomarkers in luminal breast cancer and ongoing developments.
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Affiliation(s)
- Anna Höller
- Department of Gynecology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Bich Doan Nguyen-Sträuli
- Department of Gynecology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Department of Biology, Institute of Molecular Health Sciences, Swiss Federal Institute of Technology (ETH) Zurich, Zurich, Switzerland
| | - Heike Frauchiger-Heuer
- Department of Gynecology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Alexander Ring
- Department of Gynecology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Department of Biology, Institute of Molecular Health Sciences, Swiss Federal Institute of Technology (ETH) Zurich, Zurich, Switzerland
- Department of Medical Oncology and Hematology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
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Chiorino G, Petracci E, Sehovic E, Gregnanin I, Camussi E, Mello-Grand M, Ostano P, Riggi E, Vergini V, Russo A, Berrino E, Ortale A, Garena F, Venesio T, Gallo F, Favettini E, Frigerio A, Matullo G, Segnan N, Giordano L. Plasma microRNA ratios associated with breast cancer detection in a nested case-control study from a mammography screening cohort. Sci Rep 2023; 13:12040. [PMID: 37491482 PMCID: PMC10368693 DOI: 10.1038/s41598-023-38886-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Accepted: 07/17/2023] [Indexed: 07/27/2023] Open
Abstract
Mammographic breast cancer screening is effective in reducing breast cancer mortality. Nevertheless, several limitations are known. Therefore, developing an alternative or complementary non-invasive tool capable of increasing the accuracy of the screening process is highly desirable. The objective of this study was to identify circulating microRNA (miRs) ratios associated with BC in women attending mammography screening. A nested case-control study was conducted within the ANDROMEDA cohort (women of age 46-67 attending BC screening). Pre-diagnostic plasma samples, information on life-styles and common BC risk factors were collected. Small-RNA sequencing was carried out on plasma samples from 65 cases and 66 controls. miR ratios associated with BC were selected by two-sample Wilcoxon test and lasso logistic regression. Subsequent assessment by RT-qPCR of the miRs contained in the selected miR ratios was carried out as a platform validation. To identify the most promising biomarkers, penalised logistic regression was further applied to candidate miR ratios alone, or in combination with non-molecular factors. Small-RNA sequencing yielded 20 candidate miR ratios associated with BC, which were further assessed by RT-qPCR. In the resulting model, penalised logistic regression selected seven miR ratios (miR-199a-3p_let-7a-5p, miR-26b-5p_miR-142-5p, let-7b-5p_miR-19b-3p, miR-101-3p_miR-19b-3p, miR-93-5p_miR-19b-3p, let-7a-5p_miR-22-3p and miR-21-5p_miR-23a-3p), together with body mass index (BMI), menopausal status (MS), the interaction term BMI * MS, life-style score and breast density. The ROC AUC of the model was 0.79 with a sensitivity and specificity of 71.9% and 76.6%, respectively. We identified biomarkers potentially useful for BC screening measured through a widespread and low-cost technique. This is the first study reporting circulating miRs for BC detection in a screening setting. Validation in a wider sample is warranted.Trial registration: The Andromeda prospective cohort study protocol was retrospectively registered on 27-11-2015 (NCT02618538).
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Affiliation(s)
- Giovanna Chiorino
- Cancer Genomics Lab, Fondazione Edo ed Elvo Tempia, Via Malta 3, 13900, Biella, Italy
| | - Elisabetta Petracci
- Unit of Biostatistics and Clinical Trials, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori", Meldola, Italy
| | - Emir Sehovic
- Cancer Genomics Lab, Fondazione Edo ed Elvo Tempia, Via Malta 3, 13900, Biella, Italy.
- Department of Life Sciences and Systems Biology, University of Turin, Turin, Italy.
| | - Ilaria Gregnanin
- Cancer Genomics Lab, Fondazione Edo ed Elvo Tempia, Via Malta 3, 13900, Biella, Italy
| | - Elisa Camussi
- SSD Epidemiologia Screening, CPO-AOU Città della Salute e della Scienza di Torino, Via Camillo Benso Di Cavour 31, 10123, Turin, Italy
| | - Maurizia Mello-Grand
- Cancer Genomics Lab, Fondazione Edo ed Elvo Tempia, Via Malta 3, 13900, Biella, Italy
| | - Paola Ostano
- Cancer Genomics Lab, Fondazione Edo ed Elvo Tempia, Via Malta 3, 13900, Biella, Italy
| | - Emilia Riggi
- SSD Epidemiologia Screening, CPO-AOU Città della Salute e della Scienza di Torino, Via Camillo Benso Di Cavour 31, 10123, Turin, Italy
| | - Viviana Vergini
- SSD Epidemiologia Screening, CPO-AOU Città della Salute e della Scienza di Torino, Via Camillo Benso Di Cavour 31, 10123, Turin, Italy
| | - Alessia Russo
- Department of Medical Sciences, University of Turin, Turin, Italy
| | - Enrico Berrino
- Department of Medical Sciences, University of Turin, Turin, Italy
- Pathology Unit, Candiolo Cancer Institute, FPO IRCCS, Candiolo, Italy
| | - Andrea Ortale
- SSD Epidemiologia Screening, CPO-AOU Città della Salute e della Scienza di Torino, Via Camillo Benso Di Cavour 31, 10123, Turin, Italy
| | - Francesca Garena
- SSD Epidemiologia Screening, CPO-AOU Città della Salute e della Scienza di Torino, Via Camillo Benso Di Cavour 31, 10123, Turin, Italy
| | - Tiziana Venesio
- Pathology Unit, Candiolo Cancer Institute, FPO IRCCS, Candiolo, Italy
| | - Federica Gallo
- Epidemiology Unit, Staff Health Direction, Local Health Authority 1 of Cuneo, Cuneo, Italy
| | | | - Alfonso Frigerio
- SSD Epidemiologia Screening, CPO-AOU Città della Salute e della Scienza di Torino, Via Camillo Benso Di Cavour 31, 10123, Turin, Italy
| | - Giuseppe Matullo
- Department of Medical Sciences, University of Turin, Turin, Italy
| | - Nereo Segnan
- SSD Epidemiologia Screening, CPO-AOU Città della Salute e della Scienza di Torino, Via Camillo Benso Di Cavour 31, 10123, Turin, Italy.
| | - Livia Giordano
- SSD Epidemiologia Screening, CPO-AOU Città della Salute e della Scienza di Torino, Via Camillo Benso Di Cavour 31, 10123, Turin, Italy
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Kovačević L, Štajduhar A, Stemberger K, Korša L, Marušić Z, Prutki M. Breast Cancer Surrogate Subtype Classification Using Pretreatment Multi-Phase Dynamic Contrast-Enhanced Magnetic Resonance Imaging Radiomics: A Retrospective Single-Center Study. J Pers Med 2023; 13:1150. [PMID: 37511763 PMCID: PMC10381456 DOI: 10.3390/jpm13071150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 07/12/2023] [Accepted: 07/13/2023] [Indexed: 07/30/2023] Open
Abstract
This study aimed to explore the potential of multi-phase dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) radiomics for classifying breast cancer surrogate subtypes. This retrospective study analyzed 360 breast cancers from 319 patients who underwent pretreatment DCE-MRI between January 2015 and January 2019. The cohort consisted of 33 triple-negative, 26 human epidermal growth factor receptor 2 (HER2)-positive, 109 luminal A-like, 144 luminal B-like HER2-negative, and 48 luminal B-like HER2-positive lesions. A total of 1781 radiomic features were extracted from manually segmented breast cancers in each DCE-MRI sequence. The model was internally validated and selected using ten times repeated five-fold cross-validation on the primary cohort, with further evaluation using a validation cohort. The most successful models were logistic regression models applied to the third post-contrast subtraction images. These models exhibited the highest area under the curve (AUC) for discriminating between luminal A like vs. others (AUC: 0.78), luminal B-like HER2 negative vs. others (AUC: 0.57), luminal B-like HER2 positive vs. others (AUC: 0.60), HER2 positive vs. others (AUC: 0.81), and triple negative vs. others (AUC: 0.83). In conclusion, the radiomic features extracted from multi-phase DCE-MRI are promising for discriminating between breast cancer subtypes. The best-performing models relied on tissue changes observed during the mid-stage of the imaging process.
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Affiliation(s)
- Lucija Kovačević
- Clinical Department of Diagnostic and Interventional Radiology, University Hospital Centre Zagreb, Kispaticeva 12, 10000 Zagreb, Croatia; (L.K.); (M.P.)
| | - Andrija Štajduhar
- Department for Medical Statistics, Epidemiology and Medical Informatics School of Medicine, University of Zagreb, Salata 12, 10000 Zagreb, Croatia
| | - Karlo Stemberger
- Clinical Department of Diagnostic and Interventional Radiology, University Hospital Centre Zagreb, Kispaticeva 12, 10000 Zagreb, Croatia; (L.K.); (M.P.)
| | - Lea Korša
- Clinical Department of Pathology and Cytology, University Hospital Centre Zagreb, Kispaticeva 12, 10000 Zagreb, Croatia
| | - Zlatko Marušić
- Clinical Department of Pathology and Cytology, University Hospital Centre Zagreb, Kispaticeva 12, 10000 Zagreb, Croatia
| | - Maja Prutki
- Clinical Department of Diagnostic and Interventional Radiology, University Hospital Centre Zagreb, Kispaticeva 12, 10000 Zagreb, Croatia; (L.K.); (M.P.)
- School of Medicine, University of Zagreb, Salata 3, 10000 Zagreb, Croatia
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Schandiz H, Park D, Kaiser YL, Lyngra M, Talleraas IS, Geisler J, Sauer T. Subtypes of high-grade breast ductal carcinoma in situ (DCIS): incidence and potential clinical impact. Breast Cancer Res Treat 2023:10.1007/s10549-023-07016-9. [PMID: 37453021 PMCID: PMC10361903 DOI: 10.1007/s10549-023-07016-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 06/19/2023] [Indexed: 07/18/2023]
Abstract
OBJECTIVE The purpose of this study was to investigate and classify the molecular subtypes of high-grade ductal carcinoma in situ (DCIS) and identify possible high-risk subtypes. The heterogenicity of DCIS with variable clinical and histopathological presentations has been recognized. Nevertheless, only histopathological grading and diameter are currently implemented in clinical decision-making following the diagnosis of DCIS. The molecular subtypes of DCIS and their IHC surrogate markers have not been defined in conventional treatment guidelines and recommendations. We applied the definitions of molecular subtypes according to the IHC surrogate markers defined for IBC and subclassified high-grade DCIS, accordingly. METHODS Histopathological specimens were collected, revised, and regraded from 494 patients diagnosed with DCIS between 1996 and 2018. Other in situ and papillary lesions observed in breast biopsies were excluded from this study. 357 high-grade DCIS cases were submitted to IHC analysis. The markers investigated were ER, PR, HER2, and Ki67. RESULTS 45 cases were classified as grade 1, 19 as grade 2, and 430 as grade 3. Sixty patients with high-grade DCIS had an additional invasive component in the surgical specimen. Thirty-three patients were diagnosed with recurrent DCIS or invasive cancer (minimum one year after their primary DCIS diagnosis). The proportions of luminal A and luminal B HER2-negative subtypes varied depending on whether 2011 or 2013 St. Gallen Consensus Conference guidelines were adopted. Luminal A was the most prevalent subtype, according to both classifications. The luminal B HER2-positive subtype was found in 22.1% of cases, HER2-enriched subtype in 21.8%, and TPN subtype in 5.6%. There were strong indications that HER2-enriched subtype was significantly more frequent among DCIS with invasive component (p = 0.0169). CONCLUSIONS High-grade DCIS exhibits all the molecular subtypes previously identified in IBC, but with a somewhat different distribution in our cohort. HER2-enriched subtype is substantially related to the presence of an invasive component in DCIS; consequently, it is regarded as a high-risk entity.
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Affiliation(s)
- Hossein Schandiz
- Department of Pathology, Akershus University Hospital, Lørenskog, Norway.
| | - Daehoon Park
- Department of Pathology, Oslo University Hospital, Oslo, Norway
| | - Yan Liu Kaiser
- Department of Clinical Molecular Biology (EpiGen), Akershus University Hospital (AHUS), Lørenskog, Norway
| | - Marianne Lyngra
- Department of Pathology, Akershus University Hospital, Lørenskog, Norway
| | | | - Jürgen Geisler
- Department of Oncology, Akershus University Hospital, Lørenskog, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Campus AHUS, Oslo, Norway
| | - Torill Sauer
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Campus AHUS, Oslo, Norway
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Zeng Y, Wang J, Zhong X, Xiang Z, Yang T, Yu S, Dai Z, Xu N, Liu L. The disparities in prognostic prediction and annualized hazard function in different molecular subtypes between young Chinese and White American women with breast cancer. Front Oncol 2023; 13:1199492. [PMID: 37492473 PMCID: PMC10364598 DOI: 10.3389/fonc.2023.1199492] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 06/22/2023] [Indexed: 07/27/2023] Open
Abstract
Background and objectives The prognostic disparities in different molecular subtypes between young Chinese and White American breast cancer patients remain unclear. The goal of this study was to explore the prognostic differences in different molecular subtypes between Chinese and White American patients aged ≤ 40 years. Methods We included Chinese and White female breast cancer patients at or under the age of 40 from the Surveillance, Epidemiology, and End Results database (SEER) and the West China Hospital of Sichuan University. The chi-square test, log-rank test, and Cox proportional hazards model were employed to evaluate the distribution and survival disparities in the two racial/ethnic cohorts and different molecular subtypes. An annualized hazard function was used to calculate the annual failure rate among different molecular subtypes. Results This study included 20,859 female breast cancer patients at or under the age of 40, of whom 18,400 were White women and 2,459 were Chinese women. With a median follow-up time of 47 months, the 5-year breast cancer-specific survival (BCSS) rates for young Chinese and White women were 93.9% and 90.0%, respectively (P< 0.001). Molecular subtype was found to be a significant predictor in both young Chinese and White patients (P< 0.001), but different trends were observed in the two racial/ethnic cohorts when exploring the association between BCSS and molecular subtypes. Among young White patients, the hormone receptor (HoR) (+)/epidermal growth factor receptor 2 (HER2) (+) subtype had the best 5-year BCSS rate, while in young Chinese patients, the HoR (+)/HER2 (+) and HoR (+)/HER2 (-) showed comparable survival curves and both showed superior 5-year BCSS than other subtypes. Stratification by molecular subtypes, young Chinese patients demonstrated a superior 5-year BCSS in HoR (+)/HER2 (-) (96.3% vs 92.9%, P< 0.001) and triple-negative subtypes (88% vs 81.7%, P= 0.006) compared to young White American patients, while no significant differences were found in HoR (+)/HER2 (+) and HER2 enriched tumors. The annual hazard function for BCSS showed that there were significantly different trends in the HoR (+)/HER2 (-) and HoR (+)/HER2 (+) subtypes between young Chinese and White patients. Conclusions There are disparities in prognosis and annualized hazard function between young Chinese and White females with breast cancer in different molecular subtypes.
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Affiliation(s)
- Yuanyuan Zeng
- Division of Head & Neck Tumor Multimodality Treatment, Cancer Center, and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
| | - Jun Wang
- Division of Head & Neck Tumor Multimodality Treatment, Cancer Center, and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
| | - Xiaorong Zhong
- Breast Center, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
| | - Zhongzheng Xiang
- Division of Head & Neck Tumor Multimodality Treatment, Cancer Center, and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
| | - Tian Yang
- Division of Head & Neck Tumor Multimodality Treatment, Cancer Center, and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
| | - Siting Yu
- Division of Head & Neck Tumor Multimodality Treatment, Cancer Center, and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
| | - Zelei Dai
- Division of Head & Neck Tumor Multimodality Treatment, Cancer Center, and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
| | - Ningyue Xu
- Division of Head & Neck Tumor Multimodality Treatment, Cancer Center, and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
| | - Lei Liu
- Division of Head & Neck Tumor Multimodality Treatment, Cancer Center, and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
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Kang YJ, Oh SJ, Bae SY, Kim EK, Lee YJ, Park EH, Jeong J, Park HK, Suh YJ, Kim YS. Predictive biological factors for late survival in patients with HER2-positive breast cancer. Sci Rep 2023; 13:11008. [PMID: 37420033 PMCID: PMC10328940 DOI: 10.1038/s41598-023-38200-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2023] [Accepted: 07/05/2023] [Indexed: 07/09/2023] Open
Abstract
The human epidermal growth factor receptor-2 (HER2) enriched subtype of breast cancer is associated with early recurrence, mostly within 5 years. However, anti-HER2 therapies have improved outcomes and their benefits persist in the long term. This study aimed to determine predictive factors for late survival in patients with HER2-positive breast cancer. We analyzed 20,672 patients with HER2-positive stage I-III breast cancer. The patients were divided into two groups based on a follow-up period of 60 months. The multivariate analysis of factors associated with poor overall survival included old age, advanced pathologic tumor size stage (pT), advanced pathologic regional lymph node stage (pN), high histological grade, presence of lymphatic and vascular invasion, and HR-negative status within 60 months. In the breast cancer-specific survival (BCSS) of the > 60 months follow-up group, the hazard ratios (HRa) based on pN-negative were 3.038, 3.722, and 4.877 in pN1 (p = 0.001), pN2 (p < 0.001), and pN3 (p < 0.001), respectively. Only pT4 level was statistically significant in the pT group (HRa, 4.528; p = 0.007). Age (HRa, 1.045, p < 0.001) and hormone receptor-positive status (HRa, 1.705, p = 0.022) were also associated to worse BCSS. Although lymphatic invasion was not significantly associated with BCSS, there was a tendency toward a relationship (p = 0.079) with worse BCSS. In HER2-positive breast cancer patients, node status had a more significant relationship with long-term prognosis than T stage. Patients with HER2-positive breast cancer who have T4 or node-positive should be considered for clinical observation and education beyond 5 years.
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Affiliation(s)
- Young-Joon Kang
- Department of Surgery, College of Medicine, Incheon St. Mary's Hospital, The Catholic University of Korea, Incheon, Republic of Korea
| | - Se Jeong Oh
- Department of Surgery, College of Medicine, Incheon St. Mary's Hospital, The Catholic University of Korea, Incheon, Republic of Korea
| | - Soo Youn Bae
- Department of Surgery, College of Medicine, Seoul St. Mary's Hospital, The Catholic University of Korea, Seoul, Republic of Korea
| | - Eun-Kyu Kim
- Department of Surgery, Seoul National University College of Medicine, Breast Care Center, Seoul National University Bundang Hospital, Seoul, Republic of Korea
| | - Young-Jin Lee
- Division of Breast Surgery, Department of Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Eun Hwa Park
- Department of Surgery, Dong-A University College of Medicine, Busan, South Korea
| | - Joon Jeong
- Department of Surgery, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Heung Kyu Park
- Department of Surgery Breast Cancer Center, Gil Medical Center of Gachon University, Incheon, Republic of Korea
| | - Young Jin Suh
- Division of Breast and Thyroid Surgical Oncology, Department of Surgery, College of Medicine, St. Vincent's Hospital, The Catholic University of Korea, Suwon, Republic of Korea
| | - Yong-Seok Kim
- Department of Surgery, College of Medicine, Uijeongbu St. Mary's Hospital, The Catholic University of Korea, 271, Cheonbo-ro, Uijeongbu-si, Gyeonggi-do, 11765, Republic of Korea.
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