1
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Zhong Q, Sun R, Aref AT, Noor Z, Anees A, Zhu Y, Lucas N, Poulos RC, Lyu M, Zhu T, Chen GB, Wang Y, Ding X, Rutishauser D, Rupp NJ, Rueschoff JH, Poyet C, Hermanns T, Fankhauser C, Rodríguez Martínez M, Shao W, Buljan M, Neumann JF, Beyer A, Hains PG, Reddel RR, Robinson PJ, Aebersold R, Guo T, Wild PJ. Proteomic-based stratification of intermediate-risk prostate cancer patients. Life Sci Alliance 2024; 7:e202302146. [PMID: 38052461 PMCID: PMC10698198 DOI: 10.26508/lsa.202302146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 11/22/2023] [Accepted: 11/23/2023] [Indexed: 12/07/2023] Open
Abstract
Gleason grading is an important prognostic indicator for prostate adenocarcinoma and is crucial for patient treatment decisions. However, intermediate-risk patients diagnosed in the Gleason grade group (GG) 2 and GG3 can harbour either aggressive or non-aggressive disease, resulting in under- or overtreatment of a significant number of patients. Here, we performed proteomic, differential expression, machine learning, and survival analyses for 1,348 matched tumour and benign sample runs from 278 patients. Three proteins (F5, TMEM126B, and EARS2) were identified as candidate biomarkers in patients with biochemical recurrence. Multivariate Cox regression yielded 18 proteins, from which a risk score was constructed to dichotomize prostate cancer patients into low- and high-risk groups. This 18-protein signature is prognostic for the risk of biochemical recurrence and completely independent of the intermediate GG. Our results suggest that markers generated by computational proteomic profiling have the potential for clinical applications including integration into prostate cancer management.
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Affiliation(s)
- Qing Zhong
- https://ror.org/01bsaey45 ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
| | - Rui Sun
- https://ror.org/05hfa4n20 iMarker Lab, Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
| | - Adel T Aref
- https://ror.org/01bsaey45 ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
| | - Zainab Noor
- https://ror.org/01bsaey45 ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
| | - Asim Anees
- https://ror.org/01bsaey45 ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
| | - Yi Zhu
- https://ror.org/05hfa4n20 iMarker Lab, Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
| | - Natasha Lucas
- https://ror.org/01bsaey45 ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
| | - Rebecca C Poulos
- https://ror.org/01bsaey45 ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
| | - Mengge Lyu
- https://ror.org/05hfa4n20 iMarker Lab, Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
| | - Tiansheng Zhu
- https://ror.org/05hfa4n20 iMarker Lab, Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
| | - Guo-Bo Chen
- Urology & Nephrology Center, Department of Urology, Clinical Research Institute, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, China
| | - Yingrui Wang
- https://ror.org/05hfa4n20 iMarker Lab, Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
| | - Xuan Ding
- https://ror.org/05hfa4n20 iMarker Lab, Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
| | - Dorothea Rutishauser
- Department of Pathology and Molecular Pathology, University Hospital Zürich, Zürich, Switzerland
| | - Niels J Rupp
- Department of Pathology and Molecular Pathology, University Hospital Zürich, Zürich, Switzerland
| | - Jan H Rueschoff
- Department of Pathology and Molecular Pathology, University Hospital Zürich, Zürich, Switzerland
| | - Cédric Poyet
- Department of Urology, University Hospital Zürich, Zürich, Switzerland
| | - Thomas Hermanns
- Department of Urology, University Hospital Zürich, Zürich, Switzerland
| | - Christian Fankhauser
- Department of Urology, University Hospital Zürich, Zürich, Switzerland
- Department of Urology, Cantonal Hospital Lucerne, Lucerne, Switzerland
| | | | - Wenguang Shao
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic and Developmental Sciences, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China
| | - Marija Buljan
- Empa - Swiss Federal Laboratories for Materials Science and Technology, St. Gallen, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | | | | | - Peter G Hains
- https://ror.org/01bsaey45 ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
| | - Roger R Reddel
- https://ror.org/01bsaey45 ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
| | - Phillip J Robinson
- https://ror.org/01bsaey45 ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia
| | - Ruedi Aebersold
- Department of Biology, Institute of Molecular Systems Biology, ETH Zürich, Zürich, Switzerland
- Faculty of Science, University of Zürich, Zürich, Switzerland
| | - Tiannan Guo
- https://ror.org/05hfa4n20 iMarker Lab, Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
| | - Peter J Wild
- Goethe University Frankfurt, Dr. Senckenberg Institute of Pathology, University Hospital Frankfurt, Frankfurt am Main, Germany
- Frankfurt Institute for Advanced Studies, Frankfurt am Main, Germany
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2
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Lim MH, Shin S, Park K, Park J, Kim SW, Basurrah MA, Lee S, Kim DH. Deep Learning Model for Predicting Airway Organoid Differentiation. Tissue Eng Regen Med 2023; 20:1109-1117. [PMID: 37594633 PMCID: PMC10645934 DOI: 10.1007/s13770-023-00563-8] [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: 11/21/2022] [Revised: 06/06/2023] [Accepted: 06/12/2023] [Indexed: 08/19/2023] Open
Abstract
BACKGROUND Organoids are self-organized three-dimensional culture systems and have the advantages of both in vitro and in vivo experiments. However, each organoid has a different degree of self-organization, and methods such as immunofluorescence staining are required for confirmation. Therefore, we established a system to select organoids with high tissue-specific similarity using deep learning without relying on staining by acquiring bright-field images in a non-destructive manner. METHODS We identified four biomarkers in RNA extracted from airway organoids. We also predicted biomarker expression by image-based analysis of organoids by convolution neural network, a deep learning method. RESULTS We predicted airway organoid-specific marker expression from bright-field images of organoids. Organoid differentiation was verified by immunofluorescence staining of the same organoid after predicting biomarker expression in bright-field images. CONCLUSION Our study demonstrates the potential of imaging and deep learning to distinguish organoids with high human tissue similarity in disease research and drug screening.
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Affiliation(s)
- Mi Hyun Lim
- Department of Otolaryngology-Head and Neck Surgery, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Banpo-daero 222, Seocho-gu, Seoul, 06591, Republic of Korea
| | - Seungmin Shin
- Department of Mechanical Engineering, Pohang University of Science and Technology (POSTECH), 223, 5th Engineering Building 77 Cheongam-Ro, Nam-Gu, Pohang, Gyeongbuk, 37673, Republic of Korea
| | - Keonhyeok Park
- Department of Mechanical Engineering, Pohang University of Science and Technology (POSTECH), 223, 5th Engineering Building 77 Cheongam-Ro, Nam-Gu, Pohang, Gyeongbuk, 37673, Republic of Korea
| | - Jaejung Park
- Department of Mechanical Engineering, Pohang University of Science and Technology (POSTECH), 223, 5th Engineering Building 77 Cheongam-Ro, Nam-Gu, Pohang, Gyeongbuk, 37673, Republic of Korea
| | - Sung Won Kim
- Department of Otolaryngology-Head and Neck Surgery, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Banpo-daero 222, Seocho-gu, Seoul, 06591, Republic of Korea
| | | | - Seungchul Lee
- Department of Mechanical Engineering, Pohang University of Science and Technology (POSTECH), 223, 5th Engineering Building 77 Cheongam-Ro, Nam-Gu, Pohang, Gyeongbuk, 37673, Republic of Korea.
- Graduate School of Artificial Intelligence, Pohang University of Science and Technology (POSTECH), Pohang, Republic of Korea.
| | - Do Hyun Kim
- Department of Otolaryngology-Head and Neck Surgery, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Banpo-daero 222, Seocho-gu, Seoul, 06591, Republic of Korea.
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3
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Röbeck P, Xu L, Ahmed D, Dragomir A, Dahlman P, Häggman M, Ladjevardi S. P-score in preoperative biopsies accurately predicts P-score in final pathology at radical prostatectomy in patients with localized prostate cancer. Prostate 2023; 83:831-839. [PMID: 36938873 DOI: 10.1002/pros.24523] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 02/13/2023] [Accepted: 03/03/2023] [Indexed: 03/21/2023]
Abstract
BACKGROUND Prostate cancer (PCa) is a highly heterogeneous, multifocal disease, and identification of clinically significant lesions is challenging, which complicates the choice of adequate treatment. The Prostatype® score (P-score) is intended to guide treatment decisions for newly diagnosed PCa patients based on a three-gene signature (IGFBP3, F3, and VGLL3) and clinicopathological information obtained at diagnosis. This study evaluated association of the P-score measured in preoperative magnetic resonance imaging/transrectal ultrasound fusion-guided core needle biopsies (CNBs) and the P-score measured in radical prostatectomy (RP) specimens of PCa patients. We also evaluated the P-score association with the pathology of RP specimens. Furthermore, concordance of the P-score in paired CNB and RP specimens, as well as in index versus concomitant nonindex tumor foci from the same RP was investigated. METHODS The study included 100 patients with localized PCa. All patients were diagnosed by CNB and underwent RP between 2015 and 2018. Gene expression was assessed with the Prostatype® real-time quantitative polymerase chain reaction kit and the P-score was calculated. Patients were categorized into three P-score risk groups according to previously defined cutoffs. RESULTS For 71 patients, sufficient CNB tumor material was available for comparison with the RP specimens. The CNB-based P-score was associated with the pathological T-stage in RP specimens (p = 0.02). Moreover, the CNB-based P-score groups were in substantial agreement with the RP-based P-score groups (weighted κ score: 0.76 [95% confidence interval, 95% CI: 0.60-0.92]; Spearman's rank correlation coefficient r = 0.83 [95% CI: 0.74-0.89]; p < 0.0001). Similarly, the P-score groups based on paired index tumor and concomitant nonindex tumor foci (n = 64) were also in substantial agreement (weighted κ score: 0.74 [95% CI: 0.57-0.91]; r = 0.83 [95% CI: 0.73-0.89], p < 0.0001). CONCLUSIONS Our findings suggest that the P-score based on preoperative CNB accurately reflects the pathology of the whole tumor, highlighting its value as a decision support tool for newly diagnosed PCa patients.
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Affiliation(s)
- Pontus Röbeck
- Department of Urology, Uppsala University Hospital, Uppsala, Sweden
| | - Lidi Xu
- Prostatype Genomics AB, Stockholm, Sweden
| | | | - Anca Dragomir
- Department of Pathology, Uppsala University Hospital, Uppsala, Sweden
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Pär Dahlman
- Department of Surgical Sciences, Radiology, Uppsala University Hospital, Uppsala, Sweden
| | - Michael Häggman
- Department of Urology, Uppsala University Hospital, Uppsala, Sweden
| | - Sam Ladjevardi
- Department of Urology, Uppsala University Hospital, Uppsala, Sweden
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4
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Söderdahl F, Xu LD, Bring J, Häggman M. A Novel Risk Score (P-score) Based on a Three-Gene Signature, for Estimating the Risk of Prostate Cancer-Specific Mortality. Res Rep Urol 2022; 14:203-217. [PMID: 35586706 PMCID: PMC9109804 DOI: 10.2147/rru.s358169] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Accepted: 04/30/2022] [Indexed: 11/23/2022] Open
Abstract
Purpose To develop and validate a risk score (P-score) algorithm which includes previously described three-gene signature and clinicopathological parameters to predict the risk of death from prostate cancer (PCa) in a retrospective cohort. Patients and Methods A total of 591 PCa patients diagnosed between 2003 and 2008 in Stockholm, Sweden, with a median clinical follow-up time of 7.6 years (1–11 years) were included in this study. Expression of a three-gene signature (IGFBP3, F3, VGLL3) was measured in formalin-fixed paraffin-embedded material from diagnostic core needle biopsies (CNB) of these patients. A point-based scoring system based on a Fine-Gray competing risk model was used to establish the P-score based on the three-gene signature combined with PSA value, Gleason score and tumor stage at diagnosis. The endpoint was PCa-specific mortality, while other causes of death were treated as a competing risk. Out of the 591 patients, 315 patients (estimation cohort) were selected to develop the P-score. The P-score was subsequently validated in an independent validation cohort of 276 patients. Results The P-score was established ranging from the integers 0 to 15. Each one-unit increase was associated with a hazard ratio of 1.39 (95% confidence interval: 1.27–1.51, p < 0.001). The P-score was validated and performed better in predicting PCa-specific mortality than both D’Amico (0.76 vs 0.70) and NCCN (0.76 vs 0.71) by using the concordance index for competing risk. Similar improvement patterns are shown by time-dependent area under the curve. As demonstrated by cumulative incidence function, both P-score and gene signature stratified PCa patients into significantly different risk groups. Conclusion We developed the P-score, a risk stratification system for newly diagnosed PCa patients by integrating a three-gene signature measured in CNB tissue. The P-score could provide valuable decision support to distinguish PCa patients with favorable and unfavorable outcomes and hence improve treatment decisions.
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Affiliation(s)
| | - Li-Di Xu
- Prostatype Genomics AB, Stockholm, Sweden
| | | | - Michael Häggman
- Department of Urology, Uppsala University Hospital, Uppsala, Sweden
- Correspondence: Michael Häggman, Department of Urology, Uppsala University Hospital, SE-751 85 Uppsala University Hospital, Uppsala, Sweden, Tel +46 70 520 42 87, Email
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5
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Pramana S, Hardiyanta IKY, Hidayat FY, Mariyah S. A comparative assessment on gene expression classification methods of RNA-seq data generated using next-generation sequencing (NGS). NARRA J 2022; 2:e60. [PMID: 38450388 PMCID: PMC10914053 DOI: 10.52225/narra.v2i1.60] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/13/2021] [Accepted: 03/22/2022] [Indexed: 03/08/2024]
Abstract
Next-generation sequencing or massively parallel sequencing have revolutionized genomic research. RNA sequencing (RNA-Seq) can profile the gene-expression used for molecular diagnosis, disease classification and providing potential markers of diseases. For classification of gene expressions, several methods that have been proposed are based on microarray data which is a continuous scale or require a normal distribution assumption. As the RNA-Seq data do not meet those requirements, these methods cannot be applied directly. In this study, we compare several classifiers including Logistic Regression, Support Vector Machine, Classification and Regression Trees and Random Forest. A simulation study with different parameters such as over dispersion, differential expression rate is conducted and the results are compared with two mRNA experimental datasets. To measure predictive accuracy six performance indicators are used: Percentage Correctly Classified, Area Under Receiver Operating Characteristic (ROC) Curve, Kolmogorov Smirnov Statistics, Partial Gini Index, H-measure and Brier Score. The result shows that Random Forest outperforms the other classification algorithms.
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Affiliation(s)
| | | | | | - Siti Mariyah
- Politeknik Statistika STIS, Jakarta, Indonesia
- School of Computer Science and Engineering, University of New South Wales, Sydney, Australia
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6
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Tosoian JJ, Loeb S, Epstein JI, Turkbey B, Choyke PL, Schaeffer EM. Active Surveillance of Prostate Cancer: Use, Outcomes, Imaging, and Diagnostic Tools. AMERICAN SOCIETY OF CLINICAL ONCOLOGY EDUCATIONAL BOOK. AMERICAN SOCIETY OF CLINICAL ONCOLOGY. ANNUAL MEETING 2017. [PMID: 27249729 DOI: 10.14694/edbk_159244] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Active surveillance (AS) has emerged as a standard management option for men with very low-risk and low-risk prostate cancer, and contemporary data indicate that use of AS is increasing in the United States and abroad. In the favorable-risk population, reports from multiple prospective cohorts indicate a less than 1% likelihood of metastatic disease and prostate cancer-specific mortality over intermediate-term follow-up (median 5-6 years). Higher-risk men participating in AS appear to be at increased risk of adverse outcomes, but these populations have not been adequately studied to this point. Although monitoring on AS largely relies on serial prostate biopsy, a procedure associated with considerable morbidity, there is a need for improved diagnostic tools for patient selection and monitoring. Revisions from the 2014 International Society of Urologic Pathology consensus conference have yielded a more intuitive reporting system and detailed reporting of low-intermediate grade tumors, which should facilitate the practice of AS. Meanwhile, emerging modalities such as multiparametric magnetic resonance imaging and tissue-based molecular testing have shown prognostic value in some populations. At this time, however, these instruments have not been sufficiently studied to consider their routine, standardized use in the AS setting. Future studies should seek to identify those platforms most informative in the AS population and propose a strategy by which promising diagnostic tools can be safely and efficiently incorporated into clinical practice.
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Affiliation(s)
- Jeffrey J Tosoian
- From the Brady Urological Institute, Departments of Urology and Pathology, Johns Hopkins University School of Medicine, Baltimore, MD; Department of Urology and Population Health, New York University, New York, NY; Molecular Imaging Program, National Cancer Institute, Bethesda, MD; Department of Urology, Northwestern University, Chicago, IL
| | - Stacy Loeb
- From the Brady Urological Institute, Departments of Urology and Pathology, Johns Hopkins University School of Medicine, Baltimore, MD; Department of Urology and Population Health, New York University, New York, NY; Molecular Imaging Program, National Cancer Institute, Bethesda, MD; Department of Urology, Northwestern University, Chicago, IL
| | - Jonathan I Epstein
- From the Brady Urological Institute, Departments of Urology and Pathology, Johns Hopkins University School of Medicine, Baltimore, MD; Department of Urology and Population Health, New York University, New York, NY; Molecular Imaging Program, National Cancer Institute, Bethesda, MD; Department of Urology, Northwestern University, Chicago, IL
| | - Baris Turkbey
- From the Brady Urological Institute, Departments of Urology and Pathology, Johns Hopkins University School of Medicine, Baltimore, MD; Department of Urology and Population Health, New York University, New York, NY; Molecular Imaging Program, National Cancer Institute, Bethesda, MD; Department of Urology, Northwestern University, Chicago, IL
| | - Peter L Choyke
- From the Brady Urological Institute, Departments of Urology and Pathology, Johns Hopkins University School of Medicine, Baltimore, MD; Department of Urology and Population Health, New York University, New York, NY; Molecular Imaging Program, National Cancer Institute, Bethesda, MD; Department of Urology, Northwestern University, Chicago, IL
| | - Edward M Schaeffer
- From the Brady Urological Institute, Departments of Urology and Pathology, Johns Hopkins University School of Medicine, Baltimore, MD; Department of Urology and Population Health, New York University, New York, NY; Molecular Imaging Program, National Cancer Institute, Bethesda, MD; Department of Urology, Northwestern University, Chicago, IL
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7
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Lee H, Lee S, Bae H, Kang HS, Kim SJ. Genome-wide identification of target genes for miR-204 and miR-211 identifies their proliferation stimulatory role in breast cancer cells. Sci Rep 2016; 6:25287. [PMID: 27121770 PMCID: PMC4848534 DOI: 10.1038/srep25287] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2015] [Accepted: 04/14/2016] [Indexed: 12/15/2022] Open
Abstract
MiR-204 and miR-211 (miR-204/211) share the same seed site sequence, targeting many of the same genes. Their role in cancer development remains controversial, as both cell proliferative and suppressive effects have been identified. This study aimed to address the relationship between the two structurally similar microRNAs (miRs) by examining their target genes in depth as well as to reveal their contribution in breast cancer cells. Genome-wide pathway analysis with the dysregulated genes after overexpression of either of the two miRs in MCF-7 breast cancer cell identified the “Cancer”- and “Cell signaling”-related pathway as the top pathway for miR-204 and miR-211, respectively. The majority of the target genes for both miRs notably comprised ones that have been characterized to drive cells anti-tumorigenic. Accordingly, the miRs induced the proliferation of MCF-7 and MDA-MB-231 cells, judged by cell proliferation as well as colony forming assay. Tumor suppressors, MX1 and TXNIP, were proven to be direct targets of the miRs. In addition, a high association was observed between miR-204 and miR-211 expression in breast cancer tissue. Our results indicate that miR-204/211 serve to increase cell proliferation at least in MCF-7 and MDA-MB-231 breast cancer cells by downregulating tumor suppressor genes.
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Affiliation(s)
- Hyunkyung Lee
- Department of Life Science, Dongguk University-Seoul, Goyang, Republic of Korea
| | - Seungyeon Lee
- Department of Life Science, Dongguk University-Seoul, Goyang, Republic of Korea
| | - Hansol Bae
- Department of Life Science, Dongguk University-Seoul, Goyang, Republic of Korea
| | - Han-Sung Kang
- Research Institute and Hospital, National Cancer Center, Goyang, Republic of Korea
| | - Sun Jung Kim
- Department of Life Science, Dongguk University-Seoul, Goyang, Republic of Korea
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8
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Peng Z, Andersson K, Lindholm J, Dethlefsen O, Pramana S, Pawitan Y, Nistér M, Nilsson S, Li C. Improving the Prediction of Prostate Cancer Overall Survival by Supplementing Readily Available Clinical Data with Gene Expression Levels of IGFBP3 and F3 in Formalin-Fixed Paraffin Embedded Core Needle Biopsy Material. PLoS One 2016; 11:e0145545. [PMID: 26731648 PMCID: PMC4701463 DOI: 10.1371/journal.pone.0145545] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2015] [Accepted: 12/04/2015] [Indexed: 11/28/2022] Open
Abstract
Background A previously reported expression signature of three genes (IGFBP3, F3 and VGLL3) was shown to have potential prognostic value in estimating overall and cancer-specific survivals at diagnosis of prostate cancer in a pilot cohort study using freshly frozen Fine Needle Aspiration (FNA) samples. Methods We carried out a new cohort study with 241 prostate cancer patients diagnosed from 2004–2007 with a follow-up exceeding 6 years in order to verify the prognostic value of gene expression signature in formalin fixed paraffin embedded (FFPE) prostate core needle biopsy tissue samples. The cohort consisted of four patient groups with different survival times and death causes. A four multiplex one-step RT-qPCR test kit, designed and optimized for measuring the expression signature in FFPE core needle biopsy samples, was used. In archive FFPE biopsy samples the expression differences of two genes (IGFBP3 and F3) were measured. The survival time predictions using the current clinical parameters only, such as age at diagnosis, Gleason score, PSA value and tumor stage, and clinical parameters supplemented with the expression levels of IGFBP3 and F3, were compared. Results When combined with currently used clinical parameters, the gene expression levels of IGFBP3 and F3 are improving the prediction of survival time as compared to using clinical parameters alone. Conclusion The assessment of IGFBP3 and F3 gene expression levels in FFPE prostate cancer tissue would provide an improved survival prediction for prostate cancer patients at the time of diagnosis.
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Affiliation(s)
- Zhuochun Peng
- Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden
- Chundsell Medicals AB, Stockholm, Sweden
| | - Karl Andersson
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
- Ridgeview Instruments AB, Uppsala, Sweden
| | - Johan Lindholm
- Clinical Pathology/Cytology, Karolinska University Hospital, Stockholm, Sweden
| | - Olga Dethlefsen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Setia Pramana
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Yudi Pawitan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Monica Nistér
- Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden
- Clinical Pathology/Cytology, Karolinska University Hospital, Stockholm, Sweden
| | - Sten Nilsson
- Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden
- Clinical Oncology, Karolinska University Hospital, Stockholm, Sweden
| | - Chunde Li
- Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden
- Clinical Oncology, Karolinska University Hospital, Stockholm, Sweden
- Chundsell Medicals AB, Stockholm, Sweden
- * E-mail:
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9
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Tosoian JJ, Loeb S, Epstein JI, Turkbey B, Choyke P, Schaeffer EM. Active Surveillance of Prostate Cancer: Use, Outcomes, Imaging, and Diagnostic Tools. Am Soc Clin Oncol Educ Book 2016; 35:e235-45. [PMID: 27249729 PMCID: PMC4917301 DOI: 10.1200/edbk_159244] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Active surveillance (AS) has emerged as a standard management option for men with very low-risk and low-risk prostate cancer, and contemporary data indicate that use of AS is increasing in the United States and abroad. In the favorable-risk population, reports from multiple prospective cohorts indicate a less than 1% likelihood of metastatic disease and prostate cancer-specific mortality over intermediate-term follow-up (median 5-6 years). Higher-risk men participating in AS appear to be at increased risk of adverse outcomes, but these populations have not been adequately studied to this point. Although monitoring on AS largely relies on serial prostate biopsy, a procedure associated with considerable morbidity, there is a need for improved diagnostic tools for patient selection and monitoring. Revisions from the 2014 International Society of Urologic Pathology consensus conference have yielded a more intuitive reporting system and detailed reporting of low-intermediate grade tumors, which should facilitate the practice of AS. Meanwhile, emerging modalities such as multiparametric magnetic resonance imaging and tissue-based molecular testing have shown prognostic value in some populations. At this time, however, these instruments have not been sufficiently studied to consider their routine, standardized use in the AS setting. Future studies should seek to identify those platforms most informative in the AS population and propose a strategy by which promising diagnostic tools can be safely and efficiently incorporated into clinical practice.
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Affiliation(s)
- Jeffrey J Tosoian
- Brady Urological Institute and Department of Urology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, Phone: 410-955-2139, , Fax: 410-955-0833
| | - Stacy Loeb
- Department of Urology and Population Health, New York University, New York, NY 10016, , Phone: 646-825-6358
| | - Jonathan I Epstein
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA, , Phone: 410-955-5043
| | - Baris Turkbey
- Molecular Imaging Program, National Cancer Institute, Bethesda, MD, USA, , Phone: 301-443-2315
| | - Peter Choyke
- Molecular Imaging Program, National Cancer Institute, Bethesda, MD, USA, , Phone: 301-402-8409
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Reichard CA, Stephenson AJ, Klein EA. Applying precision medicine to the active surveillance of prostate cancer. Cancer 2015; 121:3403-11. [PMID: 26149066 PMCID: PMC4758404 DOI: 10.1002/cncr.29496] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2015] [Revised: 04/29/2015] [Accepted: 05/04/2015] [Indexed: 01/05/2023]
Abstract
The recent introduction of a variety of molecular tests will potentially reshape the care of patients with prostate cancer. These tests may make more accurate management decisions possible for those patients who have been "overdiagnosed" with biologically indolent disease, which represents an exceptionally small mortality risk. There is a wide range of possible applications of these tests to different clinical scenarios in patient populations managed with active surveillance. Cancer 2015;121:3435-43. © 2015 American Cancer Society.
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Affiliation(s)
- Chad A. Reichard
- Glickman Urological and Kidney InstituteCleveland ClinicClevelandOhio
| | | | - Eric A. Klein
- Glickman Urological and Kidney InstituteCleveland ClinicClevelandOhio
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