1
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Wu P, Li D, Zhang C, Dai B, Tang X, Liu J, Wu Y, Wang X, Shen A, Zhao J, Zi X, Li R, Sun N, He J. A unique circulating microRNA pairs signature serves as a superior tool for early diagnosis of pan-cancer. Cancer Lett 2024; 588:216655. [PMID: 38460724 DOI: 10.1016/j.canlet.2024.216655] [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: 09/16/2023] [Revised: 11/18/2023] [Accepted: 01/16/2024] [Indexed: 03/11/2024]
Abstract
Cancer remains a major burden globally and the critical role of early diagnosis is self-evident. Although various miRNA-based signatures have been developed in past decades, clinical utilization is limited due to a lack of precise cutoff value. Here, we innovatively developed a signature based on pairwise expression of miRNAs (miRPs) for pan-cancer diagnosis using machine learning approach. We analyzed miRNA spectrum of 15832 patients, who were divided into training, validation, test, and external test sets, with 13 different cancers from 10 cohorts. Five different machine-learning (ML) algorithms (XGBoost, SVM, RandomForest, LASSO, and Logistic) were adopted for signature construction. The best ML algorithm and the optimal number of miRPs included were identified using area under the curve (AUC) and youden index in validation set. The AUC of the best model was compared to previously published 25 signatures. Overall, Random Forest approach including 31 miRPs (31-miRP) was developed, proving highly efficient in cancer diagnosis across different datasets and cancer types (AUC range: 0.980-1.000). Regarding diagnosis of cancers at early stage, 31-miRP also exhibited high capacities, with AUC ranging from 0.961 to 0.998. Moreover, 31-miRP exhibited advantages in differentiating cancers from normal tissues (AUC range: 0.976-0.998) as well as differentiating cancers from corresponding benign lesions. Encouragingly, comparing to previously published 25 different signatures, 31-miRP also demonstrated clear advantages. In conclusion, 31-miRP acts as a powerful model for cancer diagnosis, characterized by high specificity and sensitivity as well as a clear cutoff value, thereby holding potential as a reliable tool for cancer diagnosis at early stage.
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Affiliation(s)
- Peng Wu
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Dongyu Li
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China; 4+4 Medical Doctor Program, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Chaoqi Zhang
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Bing Dai
- School of Software, Tsinghua University, Beijing, 100084, China
| | - Xiaoya Tang
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Jingjing Liu
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Yue Wu
- Department of Clinical Laboratory, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Xingwu Wang
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Ao Shen
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Jiapeng Zhao
- 4+4 Medical Doctor Program, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Xiaohui Zi
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Ruirui Li
- Department of Pathology, National Cancer Center/ National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Nan Sun
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
| | - Jie He
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
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Bin Masroni MS, Ling Eng GW, Jeon AJ, Gao Y, Cheng H, Leong SM, Cheong JK, Hue SSS, Tan SY. MicroRNA expression signature as a biomarker in the diagnosis of nodal T-cell lymphomas. Cancer Cell Int 2024; 24:48. [PMID: 38291429 PMCID: PMC10826179 DOI: 10.1186/s12935-024-03226-3] [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: 10/27/2023] [Accepted: 01/12/2024] [Indexed: 02/01/2024] Open
Abstract
BACKGROUND The diagnosis of T-cell lymphomas is typically established through a multiparameter approach that combines clinical, morphologic, immunophenotypic, and genetic features, utilizing a variety of histopathologic and molecular techniques. However, accurate diagnosis of such lymphomas and distinguishing them from reactive lymph nodes remains challenging due to their low prevalence and heterogeneous features, hence limiting the confidence of pathologists. We investigated the use of microRNA (miRNA) expression signatures as an adjunctive tool in the diagnosis and classification of T-cell lymphomas that involve lymph nodes. This study seeks to distinguish reactive lymph nodes (RLN) from two types of frequently occurring nodal T-cell lymphomas: nodal T-follicular helper (TFH) cell lymphomas (nTFHL) and peripheral T-cell lymphomas, not otherwise specified (nPTCL). METHODS From the formalin-fixed paraffin-embedded (FFPE) samples from a cohort of 88 subjects, 246 miRNAs were quantified and analyzed by differential expression. Two-class logistic regression and random forest plot models were built to distinguish RLN from the nodal T-cell lymphomas. Gene set enrichment analysis was performed on the target genes of the miRNA to identify pathways and transcription factors that may be regulated by the differentially expressed miRNAs in each subtype. RESULTS Using logistic regression analysis, we identified miRNA signatures that can distinguish RLN from nodal T-cell lymphomas (AUC of 0.92 ± 0.05), from nTFHL (AUC of 0.94 ± 0.05) and from nPTCL (AUC of 0.94 ± 0.08). Random forest plot modelling was also capable of distinguishing between RLN and nodal T-cell lymphomas, but performed worse than logistic regression. However, the miRNA signatures are not able to discriminate between nTFHL and nPTCL, owing to large similarity in miRNA expression patterns. Bioinformatic analysis of the gene targets of unique miRNA expression revealed the enrichment of both known and potentially understudied signalling pathways and genes in such lymphomas. CONCLUSION This study suggests that miRNA biomarkers may serve as a promising, cost-effective tool to aid the diagnosis of nodal T-cell lymphomas, which can be challenging. Bioinformatic analysis of differentially expressed miRNAs revealed both relevant or understudied signalling pathways that may contribute to the progression and development of each T-cell lymphoma entity. This may help us gain further insight into the biology of T-cell lymphomagenesis.
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Affiliation(s)
- Muhammad Sufyan Bin Masroni
- Department of Pathology, Yong Loo Lin School of Medicine, National University of Singapore (NUS), Singapore, 117596, Singapore
| | | | - Ah-Jung Jeon
- MiRXES Lab Pte Ltd, Singapore, 138667, Singapore
| | - Yuan Gao
- MiRXES Lab Pte Ltd, Singapore, 138667, Singapore
| | - He Cheng
- MiRXES Lab Pte Ltd, Singapore, 138667, Singapore
| | - Sai Mun Leong
- Department of Pathology, Yong Loo Lin School of Medicine, National University of Singapore (NUS), Singapore, 117596, Singapore
- NUS Centre for Cancer Research, Singapore, 117599, Singapore
| | - Jit Kong Cheong
- NUS Centre for Cancer Research, Singapore, 117599, Singapore
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore (NUS), Singapore, 117596, Singapore
| | - Susan Swee-Shan Hue
- Department of Pathology, National University Hospital, Singapore, 119077, Singapore.
- Department of Pathology, Yong Loo Lin School of Medicine, National University of Singapore (NUS), Singapore, 117596, Singapore.
- NUS Centre for Cancer Research, Singapore, 117599, Singapore.
| | - Soo Yong Tan
- Department of Pathology, National University Hospital, Singapore, 119077, Singapore.
- Department of Pathology, Yong Loo Lin School of Medicine, National University of Singapore (NUS), Singapore, 117596, Singapore.
- Advanced Molecular Pathology Laboratory, Institute of Molecular and Cell Biology, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore, 138673, Singapore.
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3
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Zhang S, Wu SQY, Hum M, Perumal J, Tan EY, Lee ASG, Teng J, Dinish US, Olivo M. Complete characterization of RNA biomarker fingerprints using a multi-modal ATR-FTIR and SERS approach for label-free early breast cancer diagnosis. RSC Adv 2024; 14:3599-3610. [PMID: 38264270 PMCID: PMC10804230 DOI: 10.1039/d3ra05723b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 11/17/2023] [Indexed: 01/25/2024] Open
Abstract
Breast cancer is a prevalent form of cancer worldwide, and the current standard screening method, mammography, often requires invasive biopsy procedures for further assessment. Recent research has explored microRNAs (miRNAs) in circulating blood as potential biomarkers for early breast cancer diagnosis. In this study, we employed a multi-modal spectroscopy approach, combining attenuated total reflection Fourier transform infrared (ATR-FTIR) and surface-enhanced Raman scattering (SERS) to comprehensively characterize the full-spectrum fingerprints of RNA biomarkers in the blood serum of breast cancer patients. The sensitivity of conventional FTIR and Raman spectroscopy was enhanced by ATR-FTIR and SERS through the utilization of a diamond ATR crystal and silver-coated silicon nanopillars, respectively. Moreover, a wider measurement wavelength range was achieved with the multi-modal approach than with a single spectroscopic method alone. We have shown the results on 91 clinical samples, which comprised 44 malignant and 47 benign cases. Principal component analysis (PCA) was performed on the ATR-FTIR, SERS, and multi-modal data. From the peak analysis, we gained insights into biomolecular absorption and scattering-related features, which aid in the differentiation of malignant and benign samples. Applying 32 machine learning algorithms to the PCA results, we identified key molecular fingerprints and demonstrated that the multi-modal approach outperforms individual techniques, achieving higher average validation accuracy (95.1%), blind test accuracy (91.6%), specificity (94.7%), sensitivity (95.5%), and F-score (94.8%). The support vector machine (SVM) model showed the best area under the curve (AUC) characterization value of 0.9979, indicating excellent performance. These findings highlight the potential of the multi-modal spectroscopy approach as an accurate, reliable, and rapid method for distinguishing between malignant and benign breast tumors in women. Such a label-free approach holds promise for improving early breast cancer diagnosis and patient outcomes.
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Affiliation(s)
- Shuyan Zhang
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR) 2 Fusionopolis Way, Innovis #08-03 Singapore 138634 Republic of Singapore
| | - Steve Qing Yang Wu
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR) 2 Fusionopolis Way, Innovis #08-03 Singapore 138634 Republic of Singapore
| | - Melissa Hum
- Division of Cellular and Molecular Research, Humphrey Oei Institute of Cancer Research, National Cancer Centre Singapore (NCCS) 30 Hospital Boulevard Singapore 168583 Republic of Singapore
| | - Jayakumar Perumal
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR) 2 Fusionopolis Way, Innovis #08-03 Singapore 138634 Republic of Singapore
| | - Ern Yu Tan
- Breast & Endocrine Surgery, Tan Tock Seng Hospital (TTSH) 11 Jln Tan Tock Seng Singapore 308433 Republic of Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University 50 Nanyang Avenue Singapore 639798 Republic of Singapore
| | - Ann Siew Gek Lee
- Division of Cellular and Molecular Research, Humphrey Oei Institute of Cancer Research, National Cancer Centre Singapore (NCCS) 30 Hospital Boulevard Singapore 168583 Republic of Singapore
- SingHealth Duke-NUS Oncology Academic Clinical Programme (ONCO ACP), Duke-NUS Medical School Singapore 169857 Republic of Singapore
- Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore Singapore 117593 Republic of Singapore
| | - Jinghua Teng
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR) 2 Fusionopolis Way, Innovis #08-03 Singapore 138634 Republic of Singapore
| | - U S Dinish
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR) 2 Fusionopolis Way, Innovis #08-03 Singapore 138634 Republic of Singapore
| | - Malini Olivo
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR) 2 Fusionopolis Way, Innovis #08-03 Singapore 138634 Republic of Singapore
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Tariq M, Richard V, Kerin MJ. MicroRNAs as Molecular Biomarkers for the Characterization of Basal-like Breast Tumor Subtype. Biomedicines 2023; 11:3007. [PMID: 38002007 PMCID: PMC10669494 DOI: 10.3390/biomedicines11113007] [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: 10/11/2023] [Revised: 11/03/2023] [Accepted: 11/07/2023] [Indexed: 11/26/2023] Open
Abstract
Breast cancer is a heterogeneous disease highlighted by the presence of multiple tumor variants and the basal-like breast cancer (BLBC) is considered to be the most aggressive variant with limited therapeutics and a poor prognosis. Though the absence of detectable protein and hormonal receptors as biomarkers hinders early detection, the integration of genomic and transcriptomic profiling led to the identification of additional variants in BLBC. The high-throughput analysis of tissue-specific micro-ribonucleic acids (microRNAs/miRNAs) that are deemed to have a significant role in the development of breast cancer also displayed distinct expression profiles in each subtype of breast cancer and thus emerged to be a robust approach for the precise characterization of the BLBC subtypes. The classification schematic of breast cancer is still a fluid entity that continues to evolve alongside technological advancement, and the transcriptomic profiling of tissue-specific microRNAs is projected to aid in the substratification and diagnosis of the BLBC tumor subtype. In this review, we summarize the current knowledge on breast tumor classification, aim to collect comprehensive evidence based on the microRNA expression profiles, and explore their potential as prospective biomarkers of BLBC.
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Affiliation(s)
| | - Vinitha Richard
- Discipline of Surgery, Lambe Institute for Translational Research, H91 TK33 Galway, Ireland;
| | - Michael J. Kerin
- Discipline of Surgery, Lambe Institute for Translational Research, H91 TK33 Galway, Ireland;
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5
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Chan SF, Cheng H, Goh KKR, Zou R. Preanalytic Methodological Considerations and Sample Quality Control of Circulating miRNAs. J Mol Diagn 2023; 25:438-453. [PMID: 37030398 DOI: 10.1016/j.jmoldx.2023.03.005] [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: 12/29/2022] [Revised: 02/24/2023] [Accepted: 03/22/2023] [Indexed: 04/10/2023] Open
Abstract
As miRNAs emerge as potential circulating biomarkers for the diagnosis or prognosis of a wide variety of diseases, the quantification of miRNA necessitates careful preanalytic considerations and sample quality control becomes crucial. This study comprehensively analyzed the profiles of 356 miRNAs by quantitative RT-PCR in various blood sample types, with various processing protocols. The comprehensive analysis investigated the correlations of individual miRNAs with certain confounding factors. On the basis of these profiles, a panel of 7 miRNAs was established for the quality control of samples corresponding to hemolysis and platelet contamination. The panel was used to investigate the confounding impacts based on the size of the blood collection tube, the centrifugation protocol, post-freeze-thaw spinning, and whole blood storage. A standard dual-spin workflow for the processing of blood had been established for optimal sample quality. The real-time stability of 356 miRNAs was also investigated with demonstration of the temperature and time-induced miRNA degradation profile. Stability-related miRNAs were identified from real-time stability study and further incorporated into the quality control panel. This quality control panel enables the assessment of sample quality for more robust and reliable detection of circulating miRNAs.
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Affiliation(s)
- Suit-Fong Chan
- Research and Development Lab, MiRXES Lab Pte. Ltd., Singapore.
| | - He Cheng
- Research and Development Lab, MiRXES Lab Pte. Ltd., Singapore
| | | | - Ruiyang Zou
- Research and Development Lab, MiRXES Lab Pte. Ltd., Singapore
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6
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Hue SSS, Jin Y, Cheng H, Bin Masroni MS, Tang LWT, Ho YH, Ong DBL, Leong SM, Tan SY. Tissue-Specific microRNA Expression Profiling to Derive Novel Biomarkers for the Diagnosis and Subtyping of Small B-Cell Lymphomas. Cancers (Basel) 2023; 15:cancers15020453. [PMID: 36672402 PMCID: PMC9856483 DOI: 10.3390/cancers15020453] [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: 11/11/2022] [Revised: 12/23/2022] [Accepted: 12/30/2022] [Indexed: 01/13/2023] Open
Abstract
Accurate diagnosis of the most common histological subtypes of small B-cell lymphomas is challenging due to overlapping morphological features and limitations of ancillary testing, which involves a large number of immunostains and molecular investigations. In addition, a common diagnostic challenge is to distinguish reactive lymphoid hyperplasia that do not require additional stains from such lymphomas that need ancillary investigations. We investigated if tissue-specific microRNA (miRNA) expression may provide potential biomarkers to improve the pathology diagnostic workflow. This study seeks to distinguish reactive lymphoid proliferation (RL) from small B-cell lymphomas, and to further distinguish the four main subtypes of small B-cell lymphomas. Two datasets were included: a discovery cohort (n = 100) to screen for differentially expressed miRNAs and a validation cohort (n = 282) to develop classification models. The models were evaluated for accuracy in subtype prediction. MiRNA gene set enrichment was also performed to identify differentially regulated pathways. 306 miRNAs were detected and quantified, resulting in 90-miRNA classification models from which smaller panels of miRNAs biomarkers with good accuracy were derived. Bioinformatic analysis revealed the upregulation of known and other potentially relevant signaling pathways in such lymphomas. In conclusion, this study suggests that miRNA expression profiling may serve as a promising tool to aid the diagnosis of common lymphoid lesions.
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Affiliation(s)
- Susan Swee-Shan Hue
- Department of Pathology, National University Hospital, Level 3 NUH Main Building, 21 Lower Kent Ridge Road, Singapore 119077, Singapore
- Department of Pathology, Yong Loo Lin School of Medicine, National University of Singapore, Level 3 NUH Main Building, 21 Lower Kent Ridge Road, Singapore 119077, Singapore
| | - Yu Jin
- MiRXES Pte Ltd., 2 Tukang Innovation Grove, JTC MedTech Hub, #08-01, Singapore 618305, Singapore
| | - He Cheng
- MiRXES Pte Ltd., 2 Tukang Innovation Grove, JTC MedTech Hub, #08-01, Singapore 618305, Singapore
| | - Muhammad Sufyan Bin Masroni
- Department of Pathology, Yong Loo Lin School of Medicine, National University of Singapore, Level 3 NUH Main Building, 21 Lower Kent Ridge Road, Singapore 119077, Singapore
| | - Lloyd Wei Tat Tang
- Department of Pharmacy, Faculty of Science, National University of Singapore, Block S4A, Level 3, 18 Science Drive 4, Singapore 117543, Singapore
| | - Yong Howe Ho
- Department of Pathology, Tan Tock Seng Hospital, Level 2 Podium Block, 11 Jalan Tan Tock Seng, Singapore 308433, Singapore
| | - Diana Bee-Lan Ong
- Department of Pathology, University of Malaya, Lembah Pantai, Kuala Lumpur 50603, Malaysia
| | - Sai Mun Leong
- Department of Pathology, Yong Loo Lin School of Medicine, National University of Singapore, Level 3 NUH Main Building, 21 Lower Kent Ridge Road, Singapore 119077, Singapore
| | - Soo Yong Tan
- Department of Pathology, Yong Loo Lin School of Medicine, National University of Singapore, Level 3 NUH Main Building, 21 Lower Kent Ridge Road, Singapore 119077, Singapore
- Advanced Molecular Pathology Laboratory, Institute of Molecular and Cell Biology, Agency for Science, Technology and Research (A*STAR), 61 Biopolis Drive, Proteos, Singapore 138673, Singapore
- Correspondence:
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7
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Suzuki K, Yamaguchi T, Kohda M, Tanaka M, Takemura H, Wakita M, Tabe Y, Kato S, Nasu M, Hashimoto T, Mine S, Serizawa N, Tomishima K, Nagahara A, Matsuda T, Yamaji T, Tsugane S, Saito Y, Daiko H, Yoshikawa T, Kato K, Okusaka T, Ochiya T, Yamamoto Y, Yotsui S, Yamamoto T, Yamasaki T, Miyata H, Yasui M, Omori T, Ohkawa K, Ikezawa K, Nakabori T, Sugimoto N, Kudo T, Yoshida K, Ohue M, Nishizawa T. Establishment of preanalytical conditions for microRNA profile analysis of clinical plasma samples. PLoS One 2022; 17:e0278927. [PMID: 36516194 PMCID: PMC9750036 DOI: 10.1371/journal.pone.0278927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 11/23/2022] [Indexed: 12/15/2022] Open
Abstract
The relationship between the expression of microRNAs (miRNAs) in blood and a variety of diseases has been investigated. MiRNA-based liquid biopsy has attracted much attention, and cancer-specific miRNAs have been reported. However, the results of analyses of the expression of these miRNAs vary among studies. The reproduction of results regarding miRNA expression levels could be difficult if there are differences in the data acquisition process. Previous studies have shown that the anticoagulant type used during plasma preparation and sample storage conditions could contribute to differences in measured miRNA levels. Thus, the impact of these preanalytical conditions on comprehensive miRNA expression profiles was examined. First, the miRNA expression profiles of samples obtained from healthy volunteers were analyzed using next-generation sequencing. Based on an analysis of the library concentration, human genome identification rate, ratio of unique sequences and expression profiles, the optimal preanalytical conditions for obtaining highly reproducible miRNA expression profiles were established. The optimal preanalytical conditions were as follows: ethylenediaminetetraacetic acid (EDTA) as the anticoagulant, whole-blood storage at room temperature within 6 hours, and plasma storage at 4°C or -20°C within 30 days. Next, plasma samples were collected from 60 cancer patients (3 facilities × 20 patients/facility), and miRNA expression profiles were analyzed. There were no significant differences in measurements except in the expression of erythrocyte-derived hsa-miR-451a. However, the variation in hsa-miR-451a levels was smaller among facilities than among individuals. This finding suggests that samples obtained from the same facility could show significantly different degrees of hemolysis across individuals. We found that the standardization of anticoagulant use and storage conditions contributed to reducing the variation in sample quality across facilities. The findings from this study could be useful in developing protocols for collecting samples from multiple facilities for cancer screening tests.
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Affiliation(s)
- Kuno Suzuki
- Healthcare Business Department, PFDeNA, Inc., Tokyo, Japan
- * E-mail:
| | | | - Masakazu Kohda
- Healthcare Business Department, PFDeNA, Inc., Tokyo, Japan
| | - Masami Tanaka
- Healthcare Business Department, PFDeNA, Inc., Tokyo, Japan
| | - Hiroyuki Takemura
- Department of Clinical Laboratory, Juntendo University Hospital, Tokyo, Japan
| | - Mitsuru Wakita
- Department of Clinical Laboratory, Juntendo University Hospital, Tokyo, Japan
| | - Yoko Tabe
- Department of Clinical Laboratory, Juntendo University Hospital, Tokyo, Japan
| | - Shunsuke Kato
- Department of Clinical Oncology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Motomi Nasu
- Department of Esophageal and Gastroenterological Surgery, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Takashi Hashimoto
- Department of Esophageal and Gastroenterological Surgery, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Shinji Mine
- Department of Esophageal and Gastroenterological Surgery, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Nobuko Serizawa
- Department of Gastroenterology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Ko Tomishima
- Department of Gastroenterology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Akihito Nagahara
- Department of Gastroenterology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Takahisa Matsuda
- Cancer Screening Center, National Cancer Center Hospital, Tokyo, Japan
| | - Taiki Yamaji
- Division of Epidemiology, National Cancer Center Institute for Cancer Control, Tokyo, Japan
| | - Shoichiro Tsugane
- Division of Cohort Research, National Cancer Center Institute for Cancer Control, Tokyo, Japan
| | - Yutaka Saito
- Department of Endoscopy, National Cancer Center Hospital, Tokyo, Japan
| | - Hiroyuki Daiko
- Department of Esophageal Surgery, National Cancer Center Hospital, Tokyo, Japan
| | - Takaki Yoshikawa
- Department of Gastric Surgery, National Cancer Center Hospital, Tokyo, Japan
| | - Ken Kato
- Department of Head and Neck, Esophageal Medical Oncology / Department of Gastrointestinal Medical Oncology, National Cancer Center Hospital, Tokyo, Japan
| | - Takuji Okusaka
- Department of Hepatobiliary and Pancreatic Oncology, National Cancer Center Hospital, Tokyo, Japan
| | - Takahiro Ochiya
- Laboratory of Integrative Oncology, National Cancer Center Research Institute, Tokyo, Japan
| | - Yusuke Yamamoto
- Laboratory of Integrative Oncology, National Cancer Center Research Institute, Tokyo, Japan
| | - Shoji Yotsui
- Clinical Laboratory, Osaka International Cancer Institute, Osaka, Japan
| | - Takashi Yamamoto
- Clinical Laboratory, Osaka International Cancer Institute, Osaka, Japan
| | - Tomoyuki Yamasaki
- Clinical Laboratory, Osaka International Cancer Institute, Osaka, Japan
| | - Hiroshi Miyata
- Department of Gastroenterological Surgery, Osaka International Cancer Institute, Osaka, Japan
| | - Masayoshi Yasui
- Department of Gastroenterological Surgery, Osaka International Cancer Institute, Osaka, Japan
| | - Takeshi Omori
- Department of Gastroenterological Surgery, Osaka International Cancer Institute, Osaka, Japan
| | - Kazuyoshi Ohkawa
- Department of Hepatobiliary and Pancreatic Oncology, Osaka International Cancer Institute, Osaka, Japan
| | - Kenji Ikezawa
- Department of Hepatobiliary and Pancreatic Oncology, Osaka International Cancer Institute, Osaka, Japan
| | - Tasuku Nakabori
- Department of Hepatobiliary and Pancreatic Oncology, Osaka International Cancer Institute, Osaka, Japan
| | - Naotoshi Sugimoto
- Department of Medical Oncology, Osaka International Cancer Institute, Osaka, Japan
| | - Toshihiro Kudo
- Department of Medical Oncology, Osaka International Cancer Institute, Osaka, Japan
| | - Keiichi Yoshida
- Next-generation Precision Medicine Research Center, Osaka International Cancer Institute, Osaka, Japan
| | - Masayuki Ohue
- Next-generation Precision Medicine Research Center, Osaka International Cancer Institute, Osaka, Japan
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Addressing the Clinical Feasibility of Adopting Circulating miRNA for Breast Cancer Detection, Monitoring and Management with Artificial Intelligence and Machine Learning Platforms. Int J Mol Sci 2022; 23:ijms232315382. [PMID: 36499713 PMCID: PMC9736108 DOI: 10.3390/ijms232315382] [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: 10/28/2022] [Revised: 11/24/2022] [Accepted: 11/28/2022] [Indexed: 12/12/2022] Open
Abstract
Detecting breast cancer (BC) at the initial stages of progression has always been regarded as a lifesaving intervention. With modern technology, extensive studies have unraveled the complexity of BC, but the current standard practice of early breast cancer screening and clinical management of cancer progression is still heavily dependent on tissue biopsies, which are invasive and limited in capturing definitive cancer signatures for more comprehensive applications to improve outcomes in BC care and treatments. In recent years, reviews and studies have shown that liquid biopsies in the form of blood, containing free circulating and exosomal microRNAs (miRNAs), have become increasingly evident as a potential minimally invasive alternative to tissue biopsy or as a complement to biomarkers in assessing and classifying BC. As such, in this review, the potential of miRNAs as the key BC signatures in liquid biopsy are addressed, including the role of artificial intelligence (AI) and machine learning platforms (ML), in capitalizing on the big data of miRNA for a more comprehensive assessment of the cancer, leading to practical clinical utility in BC management.
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9
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Zhang C, Sun C, Zhao Y, Wang Q, Guo J, Ye B, Yu G. Overview of MicroRNAs as Diagnostic and Prognostic Biomarkers for High-Incidence Cancers in 2021. Int J Mol Sci 2022; 23:ijms231911389. [PMID: 36232692 PMCID: PMC9570028 DOI: 10.3390/ijms231911389] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2022] [Revised: 09/20/2022] [Accepted: 09/21/2022] [Indexed: 12/24/2022] Open
Abstract
MicroRNAs (miRNAs) are small non-coding RNAs (ncRNAs) about 22 nucleotides in size, which play an important role in gene regulation and are involved in almost all major cellular physiological processes. In recent years, the abnormal expression of miRNAs has been shown to be associated with human diseases including cancer. In the past ten years, the link between miRNAs and various cancers has been extensively studied, and the abnormal expression of miRNAs has been reported in various malignant tumors, such as lung cancer, gastric cancer, colorectal cancer, liver cancer, breast cancer, and prostate cancer. Due to the high malignancy grade of these cancers, it is more necessary to develop the related diagnostic and prognostic methods. According to the study of miRNAs, many potential cancer biomarkers have been proposed for the diagnosis and prognosis of diseases, especially cancer, thus providing a new theoretical basis and perspective for cancer screening. The use of miRNAs as biomarkers for diagnosis or prognosis of cancer has the advantages of being less invasive to patients, with better accuracy and lower price. In view of the important clinical significance of miRNAs in human cancer research, this article reviewed the research status of miRNAs in the above-mentioned cancers in 2021, especially in terms of diagnosis and prognosis, and provided some new perspectives and theoretical basis for the diagnosis and treatment of cancers.
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Affiliation(s)
- Chunyan Zhang
- State Key Laboratory Cell Differentiation and Regulation, Henan Normal University, Xinxiang 453007, China
- Henan International Joint Laboratory of Pulmonary Fibrosis, Henan Normal University, Xinxiang 453007, China
- Henan Center for Outstanding Overseas Scientists of Pulmonary Fibrosis, Henan Normal University, Xinxiang 453007, China
- College of Life Science, Henan Normal University, Xinxiang 453007, China
- Institute of Biomedical Science, Henan Normal University, Xinxiang 453007, China
| | - Caifang Sun
- State Key Laboratory Cell Differentiation and Regulation, Henan Normal University, Xinxiang 453007, China
- College of Life Science, Henan Normal University, Xinxiang 453007, China
| | - Yabin Zhao
- State Key Laboratory Cell Differentiation and Regulation, Henan Normal University, Xinxiang 453007, China
- College of Life Science, Henan Normal University, Xinxiang 453007, China
| | - Qiwen Wang
- State Key Laboratory Cell Differentiation and Regulation, Henan Normal University, Xinxiang 453007, China
- Henan International Joint Laboratory of Pulmonary Fibrosis, Henan Normal University, Xinxiang 453007, China
- Henan Center for Outstanding Overseas Scientists of Pulmonary Fibrosis, Henan Normal University, Xinxiang 453007, China
- College of Life Science, Henan Normal University, Xinxiang 453007, China
- Institute of Biomedical Science, Henan Normal University, Xinxiang 453007, China
| | - Jianlin Guo
- State Key Laboratory Cell Differentiation and Regulation, Henan Normal University, Xinxiang 453007, China
- Henan International Joint Laboratory of Pulmonary Fibrosis, Henan Normal University, Xinxiang 453007, China
- Henan Center for Outstanding Overseas Scientists of Pulmonary Fibrosis, Henan Normal University, Xinxiang 453007, China
- College of Life Science, Henan Normal University, Xinxiang 453007, China
- Institute of Biomedical Science, Henan Normal University, Xinxiang 453007, China
| | - Bingyu Ye
- State Key Laboratory Cell Differentiation and Regulation, Henan Normal University, Xinxiang 453007, China
- Henan International Joint Laboratory of Pulmonary Fibrosis, Henan Normal University, Xinxiang 453007, China
- Henan Center for Outstanding Overseas Scientists of Pulmonary Fibrosis, Henan Normal University, Xinxiang 453007, China
- College of Life Science, Henan Normal University, Xinxiang 453007, China
- Institute of Biomedical Science, Henan Normal University, Xinxiang 453007, China
- Correspondence: (B.Y.); (G.Y.)
| | - Guoying Yu
- State Key Laboratory Cell Differentiation and Regulation, Henan Normal University, Xinxiang 453007, China
- Henan International Joint Laboratory of Pulmonary Fibrosis, Henan Normal University, Xinxiang 453007, China
- Henan Center for Outstanding Overseas Scientists of Pulmonary Fibrosis, Henan Normal University, Xinxiang 453007, China
- College of Life Science, Henan Normal University, Xinxiang 453007, China
- Institute of Biomedical Science, Henan Normal University, Xinxiang 453007, China
- Correspondence: (B.Y.); (G.Y.)
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Connected-SegNets: A Deep Learning Model for Breast Tumor Segmentation from X-ray Images. Cancers (Basel) 2022; 14:cancers14164030. [PMID: 36011022 PMCID: PMC9406420 DOI: 10.3390/cancers14164030] [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: 07/18/2022] [Revised: 08/17/2022] [Accepted: 08/18/2022] [Indexed: 11/17/2022] Open
Abstract
Inspired by Connected-UNets, this study proposes a deep learning model, called Connected-SegNets, for breast tumor segmentation from X-ray images. In the proposed model, two SegNet architectures are connected with skip connections between their layers. Moreover, the cross-entropy loss function of the original SegNet has been replaced by the intersection over union (IoU) loss function in order to make the proposed model more robust against noise during the training process. As part of data preprocessing, a histogram equalization technique, called contrast limit adapt histogram equalization (CLAHE), is applied to all datasets to enhance the compressed regions and smooth the distribution of the pixels. Additionally, two image augmentation methods, namely rotation and flipping, are used to increase the amount of training data and to prevent overfitting. The proposed model has been evaluated on two publicly available datasets, specifically INbreast and the curated breast imaging subset of digital database for screening mammography (CBIS-DDSM). The proposed model has also been evaluated using a private dataset obtained from Cheng Hsin General Hospital in Taiwan. The experimental results show that the proposed Connected-SegNets model outperforms the state-of-the-art methods in terms of Dice score and IoU score. The proposed Connected-SegNets produces a maximum Dice score of 96.34% on the INbreast dataset, 92.86% on the CBIS-DDSM dataset, and 92.25% on the private dataset. Furthermore, the experimental results show that the proposed model achieves the highest IoU score of 91.21%, 87.34%, and 83.71% on INbreast, CBIS-DDSM, and the private dataset, respectively.
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11
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Liu X, Papukashvili D, Wang Z, Liu Y, Chen X, Li J, Li Z, Hu L, Li Z, Rcheulishvili N, Lu X, Ma J. Potential utility of miRNAs for liquid biopsy in breast cancer. Front Oncol 2022; 12:940314. [PMID: 35992785 PMCID: PMC9386533 DOI: 10.3389/fonc.2022.940314] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Accepted: 07/04/2022] [Indexed: 12/18/2022] Open
Abstract
Breast cancer (BC) remains the most prevalent malignancy due to its incidence rate, recurrence, and metastasis in women. Conventional strategies of cancer detection– mammography and tissue biopsy lack the capacity to detect the complete cancer genomic landscape. Besides, they often give false- positive or negative results. The presence of this and other disadvantages such as invasiveness, high-cost, and side effects necessitates developing new strategies to overcome the BC burden. Liquid biopsy (LB) has been brought to the fore owing to its early detection, screening, prognosis, simplicity of the technique, and efficient monitoring. Remarkably, microRNAs (miRNAs)– gene expression regulators seem to play a major role as biomarkers detected in the samples of LB. Particularly, miR-21 and miR-155 among other possible candidates seem to serve as favorable biomarkers in the diagnosis and prognosis of BC. Hence, this review will assess the potential utility of miRNAs as biomarkers and will highlight certain promising candidates for the LB approach in the diagnosis and management of BC that may optimize the patient outcome.
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Affiliation(s)
- Xiangrong Liu
- Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, China
| | - Dimitri Papukashvili
- Department of Pharmacology, School of Medicine, Southern University of Science and Technology, Shenzhen, China
| | - Zhixiang Wang
- Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, China
| | - Yan Liu
- Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, China
| | - Xiaoxia Chen
- Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, China
| | - Jianrong Li
- Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, China
| | - Zhiyuan Li
- Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, China
| | - Linjie Hu
- Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, China
| | - Zheng Li
- Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, China
| | - Nino Rcheulishvili
- Department of Pharmacology, School of Medicine, Southern University of Science and Technology, Shenzhen, China
| | - Xiaoqing Lu
- Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, China
- *Correspondence: Xiaoqing Lu, ; Jinfeng Ma,
| | - Jinfeng Ma
- Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, China
- *Correspondence: Xiaoqing Lu, ; Jinfeng Ma,
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Carvalho TM, Brasil GO, Jucoski TS, Adamoski D, de Lima RS, Spautz CC, Anselmi KF, Ozawa PMM, Cavalli IJ, Carvalho de Oliveira J, Gradia DF, Ribeiro EMDSF. MicroRNAs miR-142-5p, miR-150-5p, miR-320a-3p, and miR-4433b-5p in Serum and Tissue: Potential Biomarkers in Sporadic Breast Cancer. Front Genet 2022; 13:865472. [PMID: 35846122 PMCID: PMC9280295 DOI: 10.3389/fgene.2022.865472] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2022] [Accepted: 05/16/2022] [Indexed: 12/18/2022] Open
Abstract
Breast cancer (BC) is a heterogeneous disease, and establishing biomarkers is essential to patient management. We previously described that extracellular vesicle–derived miRNAs (EV-miRNAs) miR-142-5p, miR-150-5p, miR-320a, and miR-4433b-5p in serum discriminated BC from control samples, either alone or combined in a panel. Using these previously described markers, we intend to evaluate whether the same markers identified in EVs are also potential biomarkers in tissue and serum. Expression analysis using RT-qPCR was performed using serum of 67 breast cancer patients (BC-S), 19 serum controls (CT), 83 fresh tumor tissues (BC-T), and 29 adjacent nontumor tissue samples (NT). In addition, analysis from The Cancer Genome Atlas (TCGA) data (832 BC-T and 136 NT) was performed. In all comparisons, we found concordant high expression levels of miR-320a and miR-4433b-5p in BC-S compared to CT in both EVs and cell-free miRNAs (cf-miRNAs). Although miR-150-5p and miR-142-5p were not found to be differentially expressed in serum, panels including these miRNAs improved sensitivity and specificity, supporting our previous findings in EVs. Fresh tissue and data from the TCGA database had, in most comparisons, an opposite behavior when compared to serum and EVs: lower levels of all miRNAs in BC-T than those in NT samples. TCGA analyses revealed reduced expression levels of miR-150-5p and miR-320a-3p in BC-T than those in NT samples and the overexpression of miR-142-5p in BC-T, unlike our RT-qPCR results from tissue in the Brazilian cohort. The fresh tissue analysis showed that all miRNAs individually could discriminate between BC-T and NT in the Brazilian cohort, with high sensitivity and sensibility. Furthermore, combining panels showed higher AUC values and improved sensitivity and specificity. In addition, lower levels of miR-320a-3p in serum were associated with poor overall survival in BC Brazilian patients. In summary, we observed that miR-320a and miR-4433b-5p distinguished BC from controls with high specificity and sensibility, regardless of the sample source. In addition, lower levels of miR-150-5p and higher levels of miR-142-5p were statistically significant biomarkers in tissue, according to TCGA. When combined in panels, all combinations could distinguish BC patients from controls. These results highlight a potential application of these miRNAs as BC biomarkers.
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Affiliation(s)
- Tamyres Mingorance Carvalho
- Laboratory of Human Cytogenetics and Oncogenetics, Postgraduate Program in Genetics, Department of Genetics, Federal University of Paraná (UFPR), Curitiba, Brazil
| | - Guillermo Ortiz Brasil
- Laboratory of Human Cytogenetics and Oncogenetics, Postgraduate Program in Genetics, Department of Genetics, Federal University of Paraná (UFPR), Curitiba, Brazil
| | - Tayana Schultz Jucoski
- Laboratory of Human Cytogenetics and Oncogenetics, Postgraduate Program in Genetics, Department of Genetics, Federal University of Paraná (UFPR), Curitiba, Brazil
| | - Douglas Adamoski
- Laboratory of Human Cytogenetics and Oncogenetics, Postgraduate Program in Genetics, Department of Genetics, Federal University of Paraná (UFPR), Curitiba, Brazil
- Brazilian Biosciences National Laboratory (LNBio), Brazilian Center for Research in Energy and Materials (CNPEM), Sao Paulo, Brazil
| | | | | | | | - Patricia Midori Murobushi Ozawa
- Laboratory of Human Cytogenetics and Oncogenetics, Postgraduate Program in Genetics, Department of Genetics, Federal University of Paraná (UFPR), Curitiba, Brazil
- Department of Cell and Developmental Biology, Vanderbilt University School of Medicine, Nashville, TN, United States
| | - Iglenir João Cavalli
- Laboratory of Human Cytogenetics and Oncogenetics, Postgraduate Program in Genetics, Department of Genetics, Federal University of Paraná (UFPR), Curitiba, Brazil
| | - Jaqueline Carvalho de Oliveira
- Laboratory of Human Cytogenetics and Oncogenetics, Postgraduate Program in Genetics, Department of Genetics, Federal University of Paraná (UFPR), Curitiba, Brazil
| | - Daniela Fiori Gradia
- Laboratory of Human Cytogenetics and Oncogenetics, Postgraduate Program in Genetics, Department of Genetics, Federal University of Paraná (UFPR), Curitiba, Brazil
| | - Enilze Maria de Souza Fonseca Ribeiro
- Laboratory of Human Cytogenetics and Oncogenetics, Postgraduate Program in Genetics, Department of Genetics, Federal University of Paraná (UFPR), Curitiba, Brazil
- *Correspondence: Enilze Maria de Souza Fonseca Ribeiro,
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Sehovic E, Urru S, Chiorino G, Doebler P. Meta-analysis of diagnostic cell-free circulating microRNAs for breast cancer detection. BMC Cancer 2022; 22:634. [PMID: 35681127 PMCID: PMC9178880 DOI: 10.1186/s12885-022-09698-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Accepted: 05/24/2022] [Indexed: 01/17/2023] Open
Abstract
Background Breast cancer (BC) is the most frequently diagnosed cancer among women. Numerous studies explored cell-free circulating microRNAs as diagnostic biomarkers of BC. As inconsistent and rarely intersecting microRNA panels have been reported thus far, we aim to evaluate the overall diagnostic performance as well as the sources of heterogeneity between studies. Methods Based on the search of three online search engines performed up to March 21st 2022, 56 eligible publications that investigated diagnostic circulating microRNAs by utilizing Real-Time Quantitative Reverse Transcription PCR (qRT-PCR) were obtained. Primary studies’ potential for bias was evaluated with the revised tool for the quality assessment of diagnostic accuracy studies (QUADAS-2). A bivariate generalized linear mixed-effects model was applied to obtain pooled sensitivity and specificity. A novel methodology was utilized in which the sample and study models’ characteristics were analysed to determine the potential preference of studies for sensitivity or specificity. Results Pooled sensitivity and specificity of 0.85 [0.81—0.88] and 0.83 [0.79—0.87] were obtained, respectively. Subgroup analysis showed a significantly better performance of multiple (sensitivity: 0.90 [0.86—0.93]; specificity: 0.86 [0.80—0.90]) vs single (sensitivity: 0.82 [0.77—0.86], specificity: 0.83 [0.78—0.87]) microRNA panels and a comparable pooled diagnostic performance between studies using serum (sensitivity: 0.87 [0.81—0.91]; specificity: 0.83 [0.78—0.87]) and plasma (sensitivity: 0.83 [0.77—0.87]; specificity: 0.85 [0.78—0.91]) as specimen type. In addition, based on bivariate and univariate analyses, miRNA(s) based on endogenous normalizers tend to have a higher diagnostic performance than miRNA(s) based on exogenous ones. Moreover, a slight tendency of studies to prefer specificity over sensitivity was observed. Conclusions In this study the diagnostic ability of circulating microRNAs to diagnose BC was reaffirmed. Nonetheless, some subgroup analyses showed between-study heterogeneity. Finally, lack of standardization and of result reproducibility remain the biggest issues regarding the diagnostic application of circulating cell-free microRNAs. Supplementary Information The online version contains supplementary material available at 10.1186/s12885-022-09698-8.
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Affiliation(s)
- Emir Sehovic
- Cancer Genomics Lab, Fondazione Edo ed Elvo Tempia, 13900, Biella, Italy. .,Department of Life Sciences and Systems Biology, University of Turin, 10100, Turin, Italy.
| | - Sara Urru
- Cancer Genomics Lab, Fondazione Edo ed Elvo Tempia, 13900, Biella, Italy.,Unit of Biostatistics, Epidemiology and Public Health, Department of Cardiac, Thoracic, Vascular Sciences, and Public Health, University of Padova, 35121, Padova, Italy
| | - Giovanna Chiorino
- Cancer Genomics Lab, Fondazione Edo ed Elvo Tempia, 13900, Biella, Italy
| | - Philipp Doebler
- Department of Statistics, TU Dortmund University, 44227, Dortmund, Germany
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Cheong JK, Tang YC, Zhou L, Cheng H, Too HP. Advances in quantifying circulatory microRNA for early disease detection. Curr Opin Biotechnol 2022; 74:256-262. [PMID: 34999430 DOI: 10.1016/j.copbio.2021.12.007] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Revised: 12/10/2021] [Accepted: 12/20/2021] [Indexed: 02/08/2023]
Abstract
Precision preventive healthcare aims to improve patient health by integrating preventive measures with early disease detection for timely intervention with precision medicine. Key to the delivery of preventive healthcare is the clinical adoption of novel assays that enable early disease detection. Such assays, typically based on biomarkers such as microRNAs (miRNAs) from liquid biopsy or excreta, are entering clinical practice after years of clinical development and validation. In this review, we discuss the clinical utility and validation of miRNA-based molecular diagnostics for early disease detection through large-cohort studies and key considerations for developing multi-analyte clinical assays. We also highlight recent advances in the ongoing development of integrated PCR-free miRNA detection systems for point-of-care testing.
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Affiliation(s)
- Jit Kong Cheong
- Department of Biochemistry, Yong Loo Lin School of Medicine (YLLSoM), National University of Singapore (NUS), Singapore; Precision Medicine Programme, YLLSoM, NUS, Singapore; NUS Centre for Cancer Research, Singapore.
| | | | | | | | - Heng-Phon Too
- Department of Biochemistry, Yong Loo Lin School of Medicine (YLLSoM), National University of Singapore (NUS), Singapore; NUS Centre for Cancer Research, Singapore.
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Circulating miRNAs as Novel Non-Invasive Biomarkers to Aid the Early Diagnosis of Suspicious Breast Lesions for Which Biopsy Is Recommended. Cancers (Basel) 2021; 13:cancers13164028. [PMID: 34439180 PMCID: PMC8391908 DOI: 10.3390/cancers13164028] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Revised: 08/06/2021] [Accepted: 08/06/2021] [Indexed: 12/13/2022] Open
Abstract
Simple Summary In population-based screens, tissue biopsy remains the standard practice for women with imaging that suggests breast cancer. We examined circulating microRNAs as minimally invasive diagnostic biomarkers to discriminate malignant from benign breast lesions. A retrospective cohort of plasma samples divided into training and testing sets and a prospective cohort of women with suspicious imaging findings who underwent tissue biopsy were investigated through a global microRNA profile by OpenArray. Seven signatures, involving 5 specific miRNAs (miR-625, miR-423-5p, miR-370-3p, miR-181c, and miR-301b), were identified and validated in the testing set. Among the 7 signatures, the discriminatory performances of 5 of them were confirmed in the prospective cohort. Abstract In population-based screens, tissue biopsy remains the standard practice for women with imaging that suggests breast cancer. We examined circulating microRNAs as minimally invasive diagnostic biomarkers to discriminate malignant from benign breast lesions. miRNAs were analyzed by OpenArray in a retrospective cohort of plasma samples including 100 patients with malignant (T), 89 benign disease (B), and 99 healthy donors (HD) divided into training and testing sets and a prospective cohort (BABE) of 289 women with suspicious imaging findings who underwent tissue biopsy. miRNAs associated with disease status were identified by univariate analysis and then combined into signatures by multivariate logistic regression models. By combining 16 miRNAs differentially expressed in the T vs. HD comparison, 26 signatures were also able to significantly discriminate T from B disease. Seven of them, involving 5 specific miRNAs (miR-625, miR-423-5p, miR-370-3p, miR-181c, and miR-301b), were statistically validated in the testing set. Among the 7 signatures, the discriminatory performances of 5 were confirmed in the prospective BABE Cohort. This study identified 5 circulating miRNAs that, properly combined, distinguish malignant from benign breast disease in women with a high likelihood of malignancy.
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