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Shah OS, Nasrazadani A, Foldi J, Atkinson JM, Kleer CG, McAuliffe PF, Johnston TJ, Stallaert W, da Silva EM, Selenica P, Dopeso H, Pareja F, Mandelker D, Weigelt B, Reis-Filho JS, Bhargava R, Lucas PC, Lee AV, Oesterreich S. Spatial molecular profiling of mixed invasive ductal and lobular breast cancers reveals heterogeneity in intrinsic molecular subtypes, oncogenic signatures, and mutations. Proc Natl Acad Sci U S A 2024; 121:e2322068121. [PMID: 39042692 PMCID: PMC11295029 DOI: 10.1073/pnas.2322068121] [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: 12/28/2023] [Accepted: 06/13/2024] [Indexed: 07/25/2024] Open
Abstract
Mixed invasive ductal and lobular carcinoma (MDLC) is a rare histologic subtype of breast cancer displaying both E-cadherin positive ductal and E-cadherin negative lobular morphologies within the same tumor, posing challenges with regard to anticipated clinical management. It remains unclear whether these distinct morphologies also have distinct biology and risk of recurrence. Our spatially resolved transcriptomic, genomic, and single-cell profiling revealed clinically significant differences between ductal and lobular tumor regions including distinct intrinsic subtype heterogeneity - e.g., MDLC with triple-negative breast cancer (TNBC) or basal ductal and estrogen receptor positive (ER+) luminal lobular regions, distinct enrichment of cell cycle arrest/senescence and oncogenic (ER and MYC) signatures, genetic and epigenetic CDH1 inactivation in lobular but not ductal regions, and single-cell ductal and lobular subpopulations with unique oncogenic signatures further highlighting intraregional heterogeneity. Altogether, we demonstrated that the intratumoral morphological/histological heterogeneity within MDLC is underpinned by intrinsic subtype and oncogenic heterogeneity which may result in prognostic uncertainty and therapeutic dilemma.
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MESH Headings
- Humans
- Female
- Carcinoma, Lobular/genetics
- Carcinoma, Lobular/pathology
- Carcinoma, Lobular/metabolism
- Carcinoma, Ductal, Breast/genetics
- Carcinoma, Ductal, Breast/pathology
- Carcinoma, Ductal, Breast/metabolism
- Mutation
- Breast Neoplasms/genetics
- Breast Neoplasms/pathology
- Breast Neoplasms/metabolism
- Breast Neoplasms/classification
- Cadherins/genetics
- Cadherins/metabolism
- Gene Expression Regulation, Neoplastic
- Biomarkers, Tumor/genetics
- Biomarkers, Tumor/metabolism
- Triple Negative Breast Neoplasms/genetics
- Triple Negative Breast Neoplasms/pathology
- Triple Negative Breast Neoplasms/metabolism
- Transcriptome
- Gene Expression Profiling/methods
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Affiliation(s)
- Osama Shiraz Shah
- Womens Cancer Research Center at University of Pittsburgh Medical Center (UPMC) Hillman Cancer Center and Magee Women’s Research Institute, Pittsburgh, PA15213
- Integrative Systems Biology Program, University of Pittsburgh School of Medicine, PittsburghPA15260
| | - Azadeh Nasrazadani
- Womens Cancer Research Center at University of Pittsburgh Medical Center (UPMC) Hillman Cancer Center and Magee Women’s Research Institute, Pittsburgh, PA15213
- Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, PA15213
| | - Julia Foldi
- Division of Hematology-Oncology, Department of Medicine, University of Pittsburgh, Pittsburgh, PA15260
| | - Jennifer M. Atkinson
- Womens Cancer Research Center at University of Pittsburgh Medical Center (UPMC) Hillman Cancer Center and Magee Women’s Research Institute, Pittsburgh, PA15213
- Department of Pharmacology & Chemical Biology, University of Pittsburgh, Pittsburgh, PA15260
| | - Celina G. Kleer
- Department of Pathology and Rogel Cancer Center, University of Michigan, Ann Arbor, MI48109
| | - Priscilla F. McAuliffe
- Womens Cancer Research Center at University of Pittsburgh Medical Center (UPMC) Hillman Cancer Center and Magee Women’s Research Institute, Pittsburgh, PA15213
- Division of Surgical Oncology, Department of Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA15232
| | - Tyler J. Johnston
- Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA15213
| | - Wayne Stallaert
- Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA15213
| | - Edaise M. da Silva
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY10065
| | - Pier Selenica
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY10065
| | - Higinio Dopeso
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY10065
| | - Fresia Pareja
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY10065
| | - Diana Mandelker
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY10065
| | - Britta Weigelt
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY10065
| | - Jorge S. Reis-Filho
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY10065
| | - Rohit Bhargava
- Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, PA15213
| | - Peter C. Lucas
- Department of Laboratory Medicine and Pathology, Mayo Clinic College of Medicine and Science, Rochester, MN55902
| | - Adrian V. Lee
- Womens Cancer Research Center at University of Pittsburgh Medical Center (UPMC) Hillman Cancer Center and Magee Women’s Research Institute, Pittsburgh, PA15213
- Department of Pharmacology & Chemical Biology, University of Pittsburgh, Pittsburgh, PA15260
| | - Steffi Oesterreich
- Womens Cancer Research Center at University of Pittsburgh Medical Center (UPMC) Hillman Cancer Center and Magee Women’s Research Institute, Pittsburgh, PA15213
- Department of Pharmacology & Chemical Biology, University of Pittsburgh, Pittsburgh, PA15260
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Shah OS, Nasrazadani A, Foldi J, Atkinson JM, Kleer CG, McAuliffe PF, Johnston TJ, Stallaert W, da Silva EM, Selenica P, Dopeso H, Pareja F, Mandelker D, Weigelt B, Reis-Filho JS, Bhargava R, Lucas PC, Lee AV, Oesterreich S. Spatial molecular profiling of mixed invasive ductal-lobular breast cancers reveals heterogeneity in intrinsic molecular subtypes, oncogenic signatures, and mutations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.09.09.557013. [PMID: 38915645 PMCID: PMC11195088 DOI: 10.1101/2023.09.09.557013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
Mixed invasive ductal and lobular carcinoma (MDLC) is a rare histologic subtype of breast cancer displaying both E-cadherin positive ductal and E-cadherin negative lobular morphologies within the same tumor, posing challenges with regard to anticipated clinical management. It remains unclear whether these distinct morphologies also have distinct biology and risk of recurrence. Our spatially-resolved transcriptomic, genomic, and single-cell profiling revealed clinically significant differences between ductal and lobular tumor regions including distinct intrinsic subtype heterogeneity (e.g., MDLC with TNBC/basal ductal and ER+/luminal lobular regions), distinct enrichment of senescence/dormancy and oncogenic (ER and MYC) signatures, genetic and epigenetic CDH1 inactivation in lobular, but not ductal regions, and single-cell ductal and lobular sub-populations with unique oncogenic signatures further highlighting intra-regional heterogeneity. Altogether, we demonstrated that the intra-tumoral morphological/histological heterogeneity within MDLC is underpinned by intrinsic subtype and oncogenic heterogeneity which may result in prognostic uncertainty and therapeutic dilemma. Significance MDLC displays both ductal and lobular tumor regions. Our multi-omic profiling approach revealed that these morphologically distinct tumor regions harbor distinct intrinsic subtypes and oncogenic features that may cause prognostic uncertainty and therapeutic dilemma. Thus histopathological/molecular profiling of individual tumor regions may guide clinical decision making and benefit patients with MDLC, particularly in the advanced setting where there is increased reliance on next generation sequencing.
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Wu Y, Ma Q, Fan L, Wu S, Wang J. An Automated Breast Volume Scanner-Based Intra- and Peritumoral Radiomics Nomogram for the Preoperative Prediction of Expression of Ki-67 in Breast Malignancy. Acad Radiol 2024; 31:93-103. [PMID: 37544789 DOI: 10.1016/j.acra.2023.07.004] [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: 05/02/2023] [Revised: 07/04/2023] [Accepted: 07/05/2023] [Indexed: 08/08/2023]
Abstract
RATIONALE AND OBJECTIVES This study aimed to create and verify a nomogram for preoperative prediction of Ki-67 expression in breast malignancy to assist in the development of personalized treatment strategies. MATERIALS AND METHODS This retrospective study received approval from the institutional review board and included a cohort of 197 patients with breast malignancy who were admitted to our hospital. Ki-67 expression was divided into two groups based on a 14% threshold: low and high. A radiomics signature was built utilizing 1702 radiomics features based on an intra- and peritumoral (10 mm) regions of interest. Using multivariate logistic regression, radiomics signature, and ultrasound (US) characteristics, the nomogram was developed. To evaluate the model's calibration, clinical application, and predictive ability, decision curve analysis (DCA), the calibration curve, and the receiver operating characteristic curve were used, respectively. RESULTS The final nomogram included three independent predictors: tumor size (P = .037), radiomics signature (P < .001), and US-reported lymph node status (P = .018). The nomogram exhibited satisfactory performance in the training cohort, demonstrating a specificity of 0.944, a sensitivity of 0.745, and an area under the curve (AUC) of 0.905. The validation cohort recorded a specificity of 0.909, a sensitivity of 0.727, and an AUC of 0.882. The DCA showed the nomogram's clinical utility, and the calibration curve revealed a high consistency among the expected and detected values. CONCLUSION The nomogram used in this investigation can accurately predict Ki-67 expression in people with malignant breast tumors, helping to develop personalized treatment approaches.
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Affiliation(s)
- Yimin Wu
- Department of Ultrasound, WuHu Hospital, East China Normal University (The Second People's Hospital, WuHu), Wuhu, Anhui, PR China (Y.W., J.W.)
| | - Qianqing Ma
- Department of Ultrasound, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, PR China (Q.M.)
| | - Lifang Fan
- Department of Medical Imaging, Wannan Medical College, Wuhu, Anhui, PR China (L.F.)
| | - Shujian Wu
- Yijishan Hospital Affiliated to Wannan Medical College, Wuhu, Anhui, PR China (S.W.)
| | - Junli Wang
- Department of Ultrasound, WuHu Hospital, East China Normal University (The Second People's Hospital, WuHu), Wuhu, Anhui, PR China (Y.W., J.W.).
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Wang J, Gao W, Lu M, Yao X, Yang D. Development of an interpretable machine learning model for Ki-67 prediction in breast cancer using intratumoral and peritumoral ultrasound radiomics features. Front Oncol 2023; 13:1290313. [PMID: 38044998 PMCID: PMC10691503 DOI: 10.3389/fonc.2023.1290313] [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: 09/07/2023] [Accepted: 11/02/2023] [Indexed: 12/05/2023] Open
Abstract
Background Traditional immunohistochemistry assessment of Ki-67 in breast cancer (BC) via core needle biopsy is invasive, inaccurate, and nonrepeatable. While machine learning (ML) provides a promising alternative, its effectiveness depends on extensive data. Although the current mainstream MRI-centered radiomics offers sufficient data, its unsuitability for repeated examinations, along with limited accessibility and an intratumoral focus, constrain the application of predictive models in evaluating Ki-67 levels. Objective This study aims to explore ultrasound (US) image-based radiomics, incorporating both intra- and peritumoral features, to develop an interpretable ML model for predicting Ki-67 expression in BC patients. Methods A retrospective analysis was conducted on 263 BC patients, divided into training and external validation cohorts. From intratumoral and peritumoral regions of interest (ROIs) in US images, 849 distinctive radiomics features per ROI were derived. These features underwent systematic selection to analyze Ki-67 expression relationships. Four ML models-logistic regression, random forests, support vector machine (SVM), and extreme gradient boosting-were formulated and internally validated to identify the optimal predictive model. External validation was executed to ascertain the robustness of the optimal model, followed by employing Shapley Additive Explanations (SHAP) to reveal the significant features of the model. Results Among 231 selected BC patients, 67.5% exhibited high Ki-67 expression, with consistency observed across both training and validation cohorts as well as other clinical characteristics. Of the 1698 radiomics features identified, 15 were significantly correlated with Ki-67 expression. The SVM model, utilizing combined ROI, demonstrated the highest accuracy [area under the receiver operating characteristic curve (AUROC): 0.88], making it the most suitable for predicting Ki-67 expression. External validation sustained an AUROC of 0.82, affirming the model's robustness above a 40% threshold. SHAP analysis identified five influential features from intra- and peritumoral ROIs, offering insight into individual prediction. Conclusion This study emphasized the potential of SVM model using radiomics features from both intra- and peritumoral US images, for predicting elevated Ki-67 levels in BC patients. The model exhibited strong performance in validations, indicating its promise as a noninvasive tool to enable personalized decision-making in BC care.
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Hashemi M, Paskeh MDA, Orouei S, Abbasi P, Khorrami R, Dehghanpour A, Esmaeili N, Ghahremanzade A, Zandieh MA, Peymani M, Salimimoghadam S, Rashidi M, Taheriazam A, Entezari M, Hushmandi K. Towards dual function of autophagy in breast cancer: A potent regulator of tumor progression and therapy response. Biomed Pharmacother 2023; 161:114546. [PMID: 36958191 DOI: 10.1016/j.biopha.2023.114546] [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: 12/14/2022] [Revised: 03/11/2023] [Accepted: 03/14/2023] [Indexed: 03/25/2023] Open
Abstract
As a devastating disease, breast cancer has been responsible for decrease in life expectancy of females and its morbidity and mortality are high. Breast cancer is the most common tumor in females and its treatment has been based on employment of surgical resection, chemotherapy and radiotherapy. The changes in biological behavior of breast tumor relies on genomic and epigenetic mutations and depletions as well as dysregulation of molecular mechanisms that autophagy is among them. Autophagy function can be oncogenic in increasing tumorigenesis, and when it has pro-death function, it causes reduction in viability of tumor cells. The carcinogenic function of autophagy in breast tumor is an impediment towards effective therapy of patients, as it can cause drug resistance and radio-resistance. The important hallmarks of breast tumor such as glucose metabolism, proliferation, apoptosis and metastasis can be regulated by autophagy. Oncogenic autophagy can inhibit apoptosis, while it promotes stemness of breast tumor. Moreover, autophagy demonstrates interaction with tumor microenvironment components such as macrophages and its level can be regulated by anti-tumor compounds in breast tumor therapy. The reasons of considering autophagy in breast cancer therapy is its pleiotropic function, dual role (pro-survival and pro-death) and crosstalk with important molecular mechanisms such as apoptosis. Moreover, current review provides a pre-clinical and clinical evaluation of autophagy in breast tumor.
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Affiliation(s)
- Mehrdad Hashemi
- Farhikhtegan Medical Convergence Sciences Research Center, Farhikhtegan Hospital Tehran Medical Sciences, Islamic Azad University, Tehran, Iran; Department of Genetics, Faculty of Advanced Science and Technology, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
| | - Mahshid Deldar Abad Paskeh
- Farhikhtegan Medical Convergence Sciences Research Center, Farhikhtegan Hospital Tehran Medical Sciences, Islamic Azad University, Tehran, Iran; Department of Genetics, Faculty of Advanced Science and Technology, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
| | - Sima Orouei
- Department of Biology, Science and Research Branch, Islamic Azad University, Tehran, Iran
| | - Pegah Abbasi
- Farhikhtegan Medical Convergence Sciences Research Center, Farhikhtegan Hospital Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
| | - Ramin Khorrami
- Department of Food Hygiene and Quality Control, Faculty of Veterinary Medicine, University of Tehran, Tehran, Iran
| | - Amir Dehghanpour
- Farhikhtegan Medical Convergence Sciences Research Center, Farhikhtegan Hospital Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
| | - Negin Esmaeili
- Farhikhtegan Medical Convergence Sciences Research Center, Farhikhtegan Hospital Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
| | - Azin Ghahremanzade
- Farhikhtegan Medical Convergence Sciences Research Center, Farhikhtegan Hospital Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
| | - Mohammad Arad Zandieh
- Department of Food Hygiene and Quality Control, Division of Epidemiology, Faculty of Veterinary Medicine, University of Tehran, Tehran, Iran
| | - Maryam Peymani
- Department of Biology, Faculty of Basic Sciences, Shahrekord Branch, Islamic Azad University, Shahrekord, Iran
| | - Shokooh Salimimoghadam
- Department of Biochemistry and Molecular Biology, Faculty of Veterinary Medicine, Shahid Chamran University of Ahvaz, Ahvaz, Iran
| | - Mohsen Rashidi
- Department Pharmacology, Faculty of Medicine, Mazandaran University of Medical Sciences, Sari 4815733971, Iran; The Health of Plant and Livestock Products Research Center, Mazandaran University of Medical Sciences, Sari 4815733971, Iran.
| | - Afshin Taheriazam
- Farhikhtegan Medical Convergence Sciences Research Center, Farhikhtegan Hospital Tehran Medical Sciences, Islamic Azad University, Tehran, Iran; Department of Orthopedics, Faculty of medicine, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran.
| | - Maliheh Entezari
- Farhikhtegan Medical Convergence Sciences Research Center, Farhikhtegan Hospital Tehran Medical Sciences, Islamic Azad University, Tehran, Iran; Department of Genetics, Faculty of Advanced Science and Technology, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran.
| | - Kiavash Hushmandi
- Department of Food Hygiene and Quality Control, Division of Epidemiology, Faculty of Veterinary Medicine, University of Tehran, Tehran, Iran.
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Zhu Y, Dou Y, Qin L, Wang H, Wen Z. Prediction of Ki-67 of Invasive Ductal Breast Cancer Based on Ultrasound Radiomics Nomogram. JOURNAL OF ULTRASOUND IN MEDICINE : OFFICIAL JOURNAL OF THE AMERICAN INSTITUTE OF ULTRASOUND IN MEDICINE 2023; 42:649-664. [PMID: 35851691 DOI: 10.1002/jum.16061] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 06/27/2022] [Accepted: 06/29/2022] [Indexed: 06/15/2023]
Abstract
PURPOSE The objective of this research was to develop and validate an ultrasound-based radiomics nomogram for the pre-operative assessment of Ki-67 in breast cancer (BC). MATERIALS AND METHODS From December 2016 to December 2018, 515 patients with invasive ductal breast cancer who received two-dimensional (2D) ultrasound and Ki-67 examination were studied and analyzed retrospectively. The dataset was distributed at random into a training cohort (n = 360) and a test cohort (n = 155) in the ratio of 7:3. Each tumor region of interest was defined based on 2D ultrasound images and radiomics features were extracted. ANOVA, maximum correlation minimum redundancy (mRMR) algorithm, and minimum absolute shrinkage and selection operator (LASSO) were performed to pick features, and independent clinical predictors were integrated with radscore to construct the nomogram for predicting Ki-67 index by univariate and multivariate logistic regression analysis. The performance and utility of the models were evaluated by plotting receiver operating characteristic (ROC) curves, decision curve analysis (DCA), and calibration curves. RESULTS In the testing cohort, the area under the receiver characteristic curve (AUC) of the nomogram was 0.770 (95% confidence interval, 0.690-0.860). In both cohorts, the nomogram outperformed both the clinical model and the radiomics model (P < .05 according to the DeLong test). The analysis of DCA proved that the model has clinical utility. CONCLUSIONS The nomogram based on 2D ultrasound images offered an approach for predicting Ki-67 in BC.
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Affiliation(s)
- Yunpei Zhu
- Ultrasound Department, First Affiliated Hospital of Dalian Medical University, Dalian City, Liaoning Province, China
| | - Yanping Dou
- Ultrasound Department, First Affiliated Hospital of Dalian Medical University, Dalian City, Liaoning Province, China
| | - Ling Qin
- Ultrasound Department, First Affiliated Hospital of Dalian Medical University, Dalian City, Liaoning Province, China
| | - Hui Wang
- Ultrasound Department, First Affiliated Hospital of Dalian Medical University, Dalian City, Liaoning Province, China
| | - Zhihong Wen
- Radiology Department, Dalian Fifth People's Hospital, Dalian City, Liaoning Province, China
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van den Bosch T, Vermeulen L, Miedema DM. Quantitative models for the inference of intratumor heterogeneity. COMPUTATIONAL AND SYSTEMS ONCOLOGY 2022. [DOI: 10.1002/cso2.1034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Affiliation(s)
- Tom van den Bosch
- Laboratory for Experimental Oncology and Radiobiology Center for Experimental and Molecular Medicine Cancer Center Amsterdam and Amsterdam Gastroenterology and Metabolism Amsterdam University Medical Centers Amsterdam The Netherlands
- Oncode Institute Amsterdam The Netherlands
| | - Louis Vermeulen
- Laboratory for Experimental Oncology and Radiobiology Center for Experimental and Molecular Medicine Cancer Center Amsterdam and Amsterdam Gastroenterology and Metabolism Amsterdam University Medical Centers Amsterdam The Netherlands
- Oncode Institute Amsterdam The Netherlands
| | - Daniël M. Miedema
- Laboratory for Experimental Oncology and Radiobiology Center for Experimental and Molecular Medicine Cancer Center Amsterdam and Amsterdam Gastroenterology and Metabolism Amsterdam University Medical Centers Amsterdam The Netherlands
- Oncode Institute Amsterdam The Netherlands
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Kayadibi Y, Kocak B, Ucar N, Akan YN, Akbas P, Bektas S. Radioproteomics in Breast Cancer: Prediction of Ki-67 Expression With MRI-based Radiomic Models. Acad Radiol 2022; 29 Suppl 1:S116-S125. [PMID: 33744071 DOI: 10.1016/j.acra.2021.02.001] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Revised: 01/28/2021] [Accepted: 02/02/2021] [Indexed: 12/12/2022]
Abstract
RATIONALE AND OBJECTIVES We aimed to investigate the value of magnetic resonance image (MRI)-based radiomics in predicting Ki-67 expression of breast cancer. METHODS In this retrospective study, 159 lesions from 154 patients were included. Radiomic features were extracted from contrast-enhanced T1-weighted MRI (C+MRI) and apparent diffusion coefficient (ADC) maps, with open-source software. Dimension reduction was done with reliability analysis, collinearity analysis, and feature selection. Two different Ki-67 expression cut-off values (14% vs 20%) were studied as reference standard for the classifications. Input for the models were radiomic features from individual MRI sequences or their combination. Classifications were performed using a generalized linear model. RESULTS Considering Ki-67 cut-off value of 14%, training and testing AUC values were 0.785 (standard deviation [SD], 0.193) and 0.849 for ADC; 0.696 (SD, 0.150) and 0.695 for C+MRI; 0.755 (SD, 0.171) and 0.635 for the combination of both sequences, respectively. Regarding Ki-67 cut-off value of 20%, training and testing AUC values were 0.744 (SD, 0.197) and 0.617 for ADC; 0.629 (SD, 0.251) and 0.741 for C+MRI; 0.761 (SD, 0.207) and 0.618 for the combination of both sequences, respectively. CONCLUSION ADC map-based selected radiomic features coupled with generalized linear modeling might be a promising non-invasive method to determine the Ki-67 expression level of breast cancer.
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Rossi T, Gallerani G, Martinelli G, Maltoni R, Fabbri F. Circulating Tumor Cells as a Tool to Untangle the Breast Cancer Heterogeneity Issue. Biomedicines 2021; 9:biomedicines9091242. [PMID: 34572427 PMCID: PMC8466266 DOI: 10.3390/biomedicines9091242] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Revised: 09/13/2021] [Accepted: 09/14/2021] [Indexed: 12/28/2022] Open
Abstract
Breast cancer (BC) is a disease characterized by high degrees of heterogeneity at morphologic, genomic, and genetic levels, even within the same tumor mass or among patients. As a consequence, different subpopulations coexist and less represented clones may have a selective advantage, significantly influencing the outcome of BC patients. Circulating tumor cells (CTCs) represent a rare population of cells with a crucial role in metastatic cascade, and in recent years have represented a fascinating alternative to overcome the heterogeneity issue as a “liquid biopsy”. However, besides the raw enumeration of these cells in advanced epithelial tumors, there are no CTC-based assays applied in the clinical practice to improve personalized medicine. In this review, we report the latest findings in the field of CTCs for intra-tumoral heterogeneity unmasking in BC, supporting the need to deepen their analysis to investigate their role in metastatic process and include the molecular characterization in the clinical practice. In the future, CTCs will be helpful in monitoring patients during treatment, as well as to better address therapeutic strategies.
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Affiliation(s)
- Tania Rossi
- Biosciences Laboratory, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) “Dino Amadori”, 47014 Meldola, Italy; (G.G.); (F.F.)
- Correspondence: ; Tel.: +39-0549-73-9982
| | - Giulia Gallerani
- Biosciences Laboratory, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) “Dino Amadori”, 47014 Meldola, Italy; (G.G.); (F.F.)
| | - Giovanni Martinelli
- Scientific Directorate, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) “Dino Amadori”, 47014 Meldola, Italy;
| | - Roberta Maltoni
- Healthcare Administration, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) “Dino Amadori”, 47014 Meldola, Italy;
| | - Francesco Fabbri
- Biosciences Laboratory, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) “Dino Amadori”, 47014 Meldola, Italy; (G.G.); (F.F.)
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Kayadibi Y, Ucar N, Kaya MF, Yildirim E, Bektas S. Characterization of Suspicious Microcalcifications on Mammography Using 2D Shear-Wave Elastography. ULTRASOUND IN MEDICINE & BIOLOGY 2021; 47:2532-2542. [PMID: 34127332 DOI: 10.1016/j.ultrasmedbio.2021.05.008] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Revised: 04/27/2021] [Accepted: 05/06/2021] [Indexed: 06/12/2023]
Abstract
Our aim was to investigate the correlations between the findings of two-dimensional shear-wave elastography (2D-SWE) and the histopathologic results of microcalcifications (MCs) visualized using ultrasonography (USG). Fifty people with suspicious MCs without accompanying mass were evaluated. They underwent USG and 2D-SWE before USG-guided tru-cut biopsy. SWE values and histopathologic features were compared statistically. The variables between groups were analyzed using the Mann-Whitney U test. Receiver operating characteristic analysis was performed and cut-off values determined to discriminate malignancy, invasiveness and high grade. Pathology confirmed 27 malignant lesions (18 invasive ductal carcinomas, one invasive lobular and eight ductal carcinomas in situ) and 23 benign ones. There was a statistically significant difference between the SWE values of malignant and benign MCs (p < 0.001). The diagnostic performance of SWE for malignancy, invasiveness and high grade were as follows, repectively: sensitivity (93%, 83%, 88%), specificity (91%, 88%, 53%), positive predictive value (93%, 94%, 44%), negative predictive value (91%, 70%, 90%) and area under the curve (0.952, 0.885, 0.776). Cut-off values were determined as 57 kPa for malignancy, 124 kPa for invasiveness and 124.5 kPa for high grade. In conclusion, SWE is a useful method in clinical practice for characterizing MCs that can be visualized with USG.
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Affiliation(s)
- Yasemin Kayadibi
- Department of Radiology, Cerrahpasa Medical Faculty, Istanbul Universitesi-Cerrahpasa, Kocamustafapasa, Istanbul, Turkey.
| | - Nese Ucar
- Department of Radiology, Gaziosmanspasa Education and Research Hospital, Gaziosmanpasa, Istanbul, Turkey
| | - Mehmet Fatih Kaya
- Department of Radiology, Gaziosmanspasa Education and Research Hospital, Gaziosmanpasa, Istanbul, Turkey
| | - Emine Yildirim
- Department of General Surgery, Gaziosmanspasa Education and Research Hospital, Gaziosmanpasa, Istanbul, Turkey
| | - Sibel Bektas
- Department of Pathology, Gaziosmanspasa Education and Research Hospital, Gaziosmanpasa, Istanbul, Turkey
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Rusidzé M, Adlanmérini M, Chantalat E, Raymond-Letron I, Cayre S, Arnal JF, Deugnier MA, Lenfant F. Estrogen receptor-α signaling in post-natal mammary development and breast cancers. Cell Mol Life Sci 2021; 78:5681-5705. [PMID: 34156490 PMCID: PMC8316234 DOI: 10.1007/s00018-021-03860-4] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 05/12/2021] [Accepted: 05/19/2021] [Indexed: 12/16/2022]
Abstract
17β-estradiol controls post-natal mammary gland development and exerts its effects through Estrogen Receptor ERα, a member of the nuclear receptor family. ERα is also critical for breast cancer progression and remains a central therapeutic target for hormone-dependent breast cancers. In this review, we summarize the current understanding of the complex ERα signaling pathways that involve either classical nuclear “genomic” or membrane “non-genomic” actions and regulate in concert with other hormones the different stages of mammary development. We describe the cellular and molecular features of the luminal cell lineage expressing ERα and provide an overview of the transgenic mouse models impacting ERα signaling, highlighting the pivotal role of ERα in mammary gland morphogenesis and function and its implication in the tumorigenic processes. Finally, we describe the main features of the ERα-positive luminal breast cancers and their modeling in mice.
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Affiliation(s)
- Mariam Rusidzé
- INSERM U1297, Institut Des Maladies Métaboliques et Cardiovasculaires, Université de Toulouse - UPS, CHU, Toulouse, France
| | - Marine Adlanmérini
- INSERM U1297, Institut Des Maladies Métaboliques et Cardiovasculaires, Université de Toulouse - UPS, CHU, Toulouse, France
| | - Elodie Chantalat
- INSERM U1297, Institut Des Maladies Métaboliques et Cardiovasculaires, Université de Toulouse - UPS, CHU, Toulouse, France
| | - I Raymond-Letron
- LabHPEC et Institut RESTORE, Université de Toulouse, CNRS U-5070, EFS, ENVT, Inserm U1301, Toulouse, France
| | - Surya Cayre
- Department of Cell Biology and Cancer, Institut Curie, PSL Research University, Sorbonne University, CNRS UMR144, Paris, France
| | - Jean-François Arnal
- INSERM U1297, Institut Des Maladies Métaboliques et Cardiovasculaires, Université de Toulouse - UPS, CHU, Toulouse, France
| | - Marie-Ange Deugnier
- Department of Cell Biology and Cancer, Institut Curie, PSL Research University, Sorbonne University, CNRS UMR144, Paris, France
| | - Françoise Lenfant
- INSERM U1297, Institut Des Maladies Métaboliques et Cardiovasculaires, Université de Toulouse - UPS, CHU, Toulouse, France.
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12
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Eiden C, Ungefroren H. The Ratio of RAC1B to RAC1 Expression in Breast Cancer Cell Lines as a Determinant of Epithelial/Mesenchymal Differentiation and Migratory Potential. Cells 2021; 10:cells10020351. [PMID: 33567745 PMCID: PMC7915250 DOI: 10.3390/cells10020351] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Revised: 01/27/2021] [Accepted: 02/03/2021] [Indexed: 12/13/2022] Open
Abstract
Breast cancer (BC) is a heterogenous disease encompassing tumors with different histomorphological phenotypes and transcriptionally defined subtypes. However, the non-mutational/epigenetic alterations that are associated with or causally involved in phenotype diversity or conversion remain to be elucidated. Data from the pancreatic cancer model have shown that the small GTPase RAC1 and its alternatively spliced isoform, RAC1B, antagonistically control epithelial–mesenchymal transition and cell motility induced by transforming growth factor β. Using a battery of established BC cell lines with either a well-differentiated epithelial or poorly differentiated mesenchymal phenotype, we observed subtype-specific protein expression of RAC1B and RAC1. While epithelial BC lines were RAC1Bhigh and RAC1low, mesenchymal lines exhibited the reverse expression pattern. High RAC1B and/or low RAC1 abundance also correlated closely with a poor invasion potential, and vice versa, as revealed by measuring random cell migration (chemokinesis), the preferred mode of cellular movement in cells that have undergone mesenchymal transdifferentiation. We propose that a high RAC1B:RAC1 ratio in BC cells is predictive of an epithelial phenotype, while low RAC1B along with high RAC1 is a distinguishing feature of the mesenchymal state. The combined quantitative assessment of RAC1B and RAC1 in tumor biopsies of BC patients may represent a novel diagnostic tool for probing molecular subtype and eventually predict malignant potential of breast tumors.
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Affiliation(s)
- Caroline Eiden
- First Department of Medicine, University Hospital Schleswig-Holstein, Campus Lübeck, D-23538 Lübeck, Germany;
| | - Hendrik Ungefroren
- First Department of Medicine, University Hospital Schleswig-Holstein, Campus Lübeck, D-23538 Lübeck, Germany;
- Clinic for General Surgery, Visceral, Thoracic, Transplantation and Pediatric Surgery, University Hospital Schleswig-Holstein, Campus Kiel, D-24105 Kiel, Germany
- Correspondence: ; Tel.: +49-451-3101-7866
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Paran Y, Liron Y, Batsir S, Mabjeesh N, Geiger B, Kam Z. Multi-parametric characterization of drug effects on cells. F1000Res 2021; 9. [PMID: 33363713 PMCID: PMC7737707 DOI: 10.12688/f1000research.26254.2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 01/13/2021] [Indexed: 12/28/2022] Open
Abstract
We present here a novel multi-parametric approach for the characterization of multiple cellular features, using images acquired by high-throughput and high-definition light microscopy. We specifically used this approach for deep and unbiased analysis of the effects of a drug library on five cultured cell lines. The presented method enables the acquisition and analysis of millions of images, of treated and control cells, followed by an automated identification of drugs inducing strong responses, evaluating the median effect concentrations and those cellular properties that are most highly affected by the drug. The tools described here provide standardized quantification of multiple attributes for systems level dissection of complex functions in normal and diseased cells, using multiple perturbations. Such analysis of cells, derived from pathological samples, may help in the diagnosis and follow-up of treatment in patients.
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Affiliation(s)
- Yael Paran
- Department of Molecular Cell Biology, The Weizmann Institute of Science, Rehovot, 76100, Israel.,IDEA Biomedical Ltd., Rehovot, 76705, Israel
| | - Yuvalal Liron
- Department of Molecular Cell Biology, The Weizmann Institute of Science, Rehovot, 76100, Israel
| | - Sarit Batsir
- Department of Molecular Cell Biology, The Weizmann Institute of Science, Rehovot, 76100, Israel
| | - Nicola Mabjeesh
- Department of Urology, Tel Aviv Sourasky Medical Center, Tel Aviv, 64239, Israel
| | - Benjamin Geiger
- Department of Molecular Cell Biology, The Weizmann Institute of Science, Rehovot, 76100, Israel.,Department of Immunology, The Weizmann Institute of Science, Rehovot, 76100, Israel
| | - Zvi Kam
- Department of Molecular Cell Biology, The Weizmann Institute of Science, Rehovot, 76100, Israel
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14
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Santolla MF, Maggiolini M. The FGF/FGFR System in Breast Cancer: Oncogenic Features and Therapeutic Perspectives. Cancers (Basel) 2020; 12:E3029. [PMID: 33081025 PMCID: PMC7603197 DOI: 10.3390/cancers12103029] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Revised: 10/12/2020] [Accepted: 10/16/2020] [Indexed: 12/13/2022] Open
Abstract
One of the major challenges in the treatment of breast cancer is the heterogeneous nature of the disease. With multiple subtypes of breast cancer identified, there is an unmet clinical need for the development of therapies particularly for the less tractable subtypes. Several transduction mechanisms are involved in the progression of breast cancer, therefore making the assessment of the molecular landscape that characterizes each patient intricate. Over the last decade, numerous studies have focused on the development of tyrosine kinase inhibitors (TKIs) to target the main pathways dysregulated in breast cancer, however their effectiveness is often limited either by resistance to treatments or the appearance of adverse effects. In this context, the fibroblast growth factor/fibroblast growth factor receptor (FGF/FGFR) system represents an emerging transduction pathway and therapeutic target to be fully investigated among the diverse anti-cancer settings in breast cancer. Here, we have recapitulated previous studies dealing with FGFR molecular aberrations, such as the gene amplification, point mutations, and chromosomal translocations that occur in breast cancer. Furthermore, alterations in the FGF/FGFR signaling across the different subtypes of breast cancer have been described. Next, we discussed the functional interplay between the FGF/FGFR axis and important components of the breast tumor microenvironment. Lastly, we pointed out the therapeutic usefulness of FGF/FGFR inhibitors, as revealed by preclinical and clinical models of breast cancer.
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Affiliation(s)
| | - Marcello Maggiolini
- Department of Pharmacy, Health and Nutritional Sciences, University of Calabria, 87036 Rende, Italy;
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