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Adetunji A, Venishetty N, Gombakomba N, Jeune KR, Smith M, Winer A. Genomics in active surveillance and post-prostatectomy patients: A review of when and how to use effectively. Curr Urol Rep 2024; 25:253-260. [PMID: 38869692 DOI: 10.1007/s11934-024-01219-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/05/2024] [Indexed: 06/14/2024]
Abstract
PURPOSE OF REVIEW Prostate cancer (PCa) represents a significant health burden globally, ranking as the most diagnosed cancer among men and a leading cause of cancer-related mortality. Conventional treatment methods such as radiation therapy or radical prostatectomy have significant side effects which often impact quality of life. As our understanding of the natural history and progression of PCa has evolved, so has the evolution of management options. RECENT FINDINGS Active surveillance (AS) has become an increasingly favored approach to the management of very low, low, and properly selected favorable intermediate risk PCa. AS permits ongoing observation and postpones intervention until definitive treatment is required. There are, however, challenges with selecting patients for AS, which further emphasizes the need for more precise tools to better risk stratify patients and choose candidates more accurately. Tissue-based biomarkers, such as ProMark, Prolaris, GPS (formerly Oncotype DX), and Decipher, are valuable because they improve the accuracy of patient selection for AS and offer important information on the prognosis and severity of disease. By enabling patients to be categorized according to their risk profiles, these biomarkers help physicians and patients make better informed treatment choices and lower the possibility of overtreatment. Even with their potential, further standardization and validation of these biomarkers is required to guarantee their broad clinical utility. Active surveillance has emerged as a preferred strategy for managing low-risk prostate cancer, and tissue-based biomarkers play a crucial role in refining patient selection and risk stratification. Standardization and validation of these biomarkers are essential to ensure their widespread clinical use and optimize patient outcomes.
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Affiliation(s)
- Adedayo Adetunji
- Department of Urology, SUNY Downstate Health Sciences University, Brooklyn, NY, USA.
| | - Nikit Venishetty
- Paul L. Foster School of Medicine, Texas Tech Health Sciences Center, El Paso, TX, USA
| | - Nita Gombakomba
- Department of Urology, SUNY Downstate Health Sciences University, Brooklyn, NY, USA
| | - Karl-Ray Jeune
- Department of Urology, SUNY Downstate Health Sciences University, Brooklyn, NY, USA
| | - Matthew Smith
- Department of Urology, SUNY Downstate Health Sciences University, Brooklyn, NY, USA
| | - Andrew Winer
- Department of Urology, SUNY Downstate Health Sciences University, Brooklyn, NY, USA
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Mukand NH, Chirikova E, Lichtensztajn D, Negoita S, Aboushwareb T, Bennett J, Brooks JD, Leppert JT, Chung BI, Li C, Schwartz SM, Gershman ST, Insaf T, Morawski BM, Stroup A, Wu XC, Doherty JA, Petkov VI, Zambon JP, Gomez SL, Cheng I. Assessing sociodemographic and regional disparities in Oncotype DX Genomic Prostate Score uptake. Cancer 2024. [PMID: 39158464 DOI: 10.1002/cncr.35511] [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: 11/29/2023] [Revised: 04/08/2024] [Accepted: 06/21/2024] [Indexed: 08/20/2024]
Abstract
BACKGROUND The Oncotype DX Genomic Prostate Score (ODX-GPS) is a gene expression assay that predicts disease aggressiveness. The objective of this study was to identify sociodemographic and regional factors associated with ODX-GPS uptake. METHODS Data from Surveillance Epidemiology and End Results registries on men with localized prostate cancer with a Gleason score of 3 + 3 or 3 + 4, PSA ≤20 ng/mL, and stage T1c to T2c disease from 2013 through 2017 were linked with ODX-GPS data. Census-tract level neighborhood socioeconomic status (nSES) quintiles were constructed using a composite socioeconomic score. Multivariable logistic regression was used to estimate the associations of ODX-GPS uptake with age at diagnosis, race and ethnicity, nSES, geographic region, insurance type, and marital status, accounting for National Comprehensive Cancer Network risk group, year of diagnosis, and clustering by census tract. RESULTS Among 111,434 eligible men, 5.5% had ODX-GPS test uptake. Of these, 78.3% were non-Hispanic White, 9.6% were Black, 6.7% were Hispanic, and 3.6% were Asian American. Black men had the lowest odds of ODX-GPS uptake (odds ratio, 0.70; 95% confidence interval [CI], 0.63-0.76). Those in the highest versus lowest quintile of nSES were 1.64 times more likely (95% CI, 1.38-2.94) to have ODX-GPS uptake. The odds of ODX-GPS uptake were statistically significantly higher among men residing in the Northeast, West, and Midwest compared to the South. CONCLUSIONS Disparities in ODX-GPS uptake by race, ethnicity, nSES, and geographical region were identified. Concerted efforts should be made to ensure that this clinical test is equitably available.
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Affiliation(s)
- Nita H Mukand
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California, USA
| | - Ekaterina Chirikova
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California, USA
| | - Daphne Lichtensztajn
- Greater Bay Area Cancer Registry, University of California San Francisco, San Francisco, California, USA
| | - Serban Negoita
- Surveillance Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, Rockville, Maryland, USA
| | | | | | - James D Brooks
- Department of Urology, Stanford Medicine, Palo Alto, California, USA
| | - John T Leppert
- Department of Urology, Stanford Medicine, Palo Alto, California, USA
| | - Benjamin I Chung
- Department of Urology, Stanford Medicine, Palo Alto, California, USA
| | - Christopher Li
- Cancer Surveillance System, Fred Hutchinson Cancer Center, Seattle, Washington, USA
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
| | - Stephen M Schwartz
- Cancer Surveillance System, Fred Hutchinson Cancer Center, Seattle, Washington, USA
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
| | - Susan T Gershman
- Massachusetts Department of Public Health, Boston, Massachusetts, USA
| | - Tabassum Insaf
- Bureau of Cancer Epidemiology, New York State Health Department, Albany, New York, USA
- School of Public Health, Epidemiology and Biostatistics, University of Albany, Albany, New York, USA
| | | | - Antionette Stroup
- New Jersey Cancer Registry, Rutgers Cancer Institute of New Jersey, New Brunswick, New Jersey, USA
- Department of Biostatistics and Epidemiology, Rutgers School of Public Health, New Brunswick, New Jersey, USA
| | - Xiao-Cheng Wu
- Louisiana Tumor Registry, School of Public Health, Louisiana State University Health Sciences Center, New Orleans, Louisiana, USA
| | - Jennifer A Doherty
- Utah Cancer Registry, University of Utah, Salt Lake City, Utah, USA
- Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah, USA
- Department of Population Health Sciences, University of Utah, Salt Lake City, Utah, USA
| | - Valentina I Petkov
- Surveillance Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, Rockville, Maryland, USA
| | | | - Scarlett Lin Gomez
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California, USA
- Greater Bay Area Cancer Registry, University of California San Francisco, San Francisco, California, USA
- Cancer Surveillance System, Fred Hutchinson Cancer Center, Seattle, Washington, USA
- Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, California, USA
| | - Iona Cheng
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California, USA
- Greater Bay Area Cancer Registry, University of California San Francisco, San Francisco, California, USA
- Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, California, USA
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Nguyen AM, Carter GC, Wilson LAM, Canfield S. Real-world utilization, patient characteristics, and treatment patterns among men with localized prostate cancer tested with the 17-gene genomic prostate score® (GPS TM) assay. Prostate 2024; 84:922-931. [PMID: 38666513 DOI: 10.1002/pros.24709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 03/22/2024] [Accepted: 04/03/2024] [Indexed: 06/04/2024]
Abstract
OBJECTIVES Descriptive study focusing on real-world utilization and characteristics of men with prostate cancer tested with the 17-gene Genomic Prostate Score® (GPS™) assay by linking administrative claims and electronic health record (EHR) data with GPS results. METHODS This retrospective, observational cohort study (January 1, 2013 to December 31, 2020) included men aged 40-80 years with localized prostate cancer claims, continuous enrollment in Optum's Integrated Claims data set, ≥1 day of EHR clinical activity, and a GPS result. Men were classified as undergoing definitive therapy (DT) (prostatectomy, radiation, or focal therapy) or active surveillance (AS). AS and DT distribution were analyzed across GPS results, National Comprehensive Cancer Network® (NCCN®) risk, and race. Costs were assessed 6 months after the first GPS result (index); clinical outcomes and AS persistence were assessed during the variable follow-up. All variables were analyzed descriptively. RESULTS Of 834 men, 650 (77.9%) underwent AS and 184 (22.1%) DT. Most men had Quan-Charlson comorbidity scores of 1-2 and a tumor stage of T1c (index). The most common Gleason patterns were 3 + 3 (79.6%) (AS cohort) and 3 + 4 (55.9%) (DT cohort). The mean (standard deviation) GPS results at index were 23.2 (11.3) (AS) and 30.9 (12.9) (DT). AS decreased with increasing GPS result and NCCN risk. Differences between races were minimal. Total costs were substantially higher in the DT cohort. CONCLUSIONS Most men with GPS-tested localized prostate cancer underwent AS, indicating the GPS result can inform clinical management. Decreasing AS with increasing GPS result and NCCN risk suggests the GPS complements NCCN risk stratification.
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Cui F, Tang X, Man C, Fan Y. Prognostic value of 17-Gene genomic prostate score in patients with clinically localized prostate cancer: a meta-analysis. BMC Cancer 2024; 24:628. [PMID: 38783246 PMCID: PMC11112896 DOI: 10.1186/s12885-024-12389-1] [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: 03/15/2024] [Accepted: 05/15/2024] [Indexed: 05/25/2024] Open
Abstract
BACKGROUND The 17-gene Genomic Prostate Score (GPS) test has been clinically employed to predict adverse prognosis in prostate cancer. In this meta-analysis, we aimed to evaluate the prognostic value of the 17-gene GPS in patients with prostate cancer. METHODS Potentially relevant studies were obtained by searching PubMed, Web of Science, Embase databases from their inception to December 1, 2023. Studies were considered eligible if they evaluated the association of the 17-gene GPS with distant metastases, biochemical recurrence, or prostate cancer-specific mortality (PCSM) in prostate cancer patients. To estimate the prognostic value, we pooled the adjusted hazard ratio (HR) with 95% confidence intervals (CI) for the high versus low GPS group or per 20-unit increase in GPS. RESULTS Seven cohort studies that reported on 8 articles comprising 1,962 patients satisfied the eligibility criteria. Meta-analysis showed that per 20-unit increase in GPS was significantly associated with distant metastases (HR 2.99; 95% CI 1.97-4.53), biochemical recurrence (HR 2.18; 95% CI 1.64-2.89), and PCSM (HR 3.14; 95% CI 1.86-5.30). Moreover, patients with high GPS (> 40 points) had an increased risk of distant metastases (HR 5.22; 95% CI 3.72-7.31), biochemical recurrence (HR 4.41; 95% CI 2.29-8.49), and PCSM (HR 3.81; 95% CI 1.74-8.33) than those with low GPS (≤ 40 points). CONCLUSIONS A higher 17-gene GPS significantly predicts distant metastases, biochemical recurrence, and PCSM in men with clinically localized prostate cancer. However, large-scale multicenter prospective studies are necessary to further validate these findings.
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Affiliation(s)
- Feilun Cui
- Department of Urology, Affiliated Taizhou Second People's Hospital of Yangzhou University, Taizhou, 225500, China
- Department of Urology, The Fourth Affiliated Hospital of Jiangsu University, Zhenjiang, 212001, China
| | - Xuan Tang
- Cancer Institute, The Affiliated People's Hospital, Jiangsu University, No. 8 Dianli Road, Zhenjiang, Zhenjiang, 212002, China
| | - Changfeng Man
- Cancer Institute, The Affiliated People's Hospital, Jiangsu University, No. 8 Dianli Road, Zhenjiang, Zhenjiang, 212002, China.
| | - Yu Fan
- Cancer Institute, The Affiliated People's Hospital, Jiangsu University, No. 8 Dianli Road, Zhenjiang, Zhenjiang, 212002, China.
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5
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Hamid AA, Sweeney CJ, Hovens C, Corcoran N, Azad AA. Precision medicine for prostate cancer: An international perspective. Urol Oncol 2024:S1078-1439(24)00334-X. [PMID: 38614920 DOI: 10.1016/j.urolonc.2024.02.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 02/07/2024] [Accepted: 02/14/2024] [Indexed: 04/15/2024]
Abstract
Greater personalization of cancer medicine continues to shape therapy development and patient selection accordingly. The treatment of prostate cancer has evolved considerably since the discovery of androgen deprivation therapy. The comprehensive profiling of the prostate cancer genome has mapped the targetable molecular landscape of the disease and identified opportunities for the implementation of novel and combination therapies. In this review, we provide an overview of the molecular biology of prostate cancer and tools developed to aid prognostication and prediction of therapy benefit. Modern treatment of advanced prostate cancer is reviewed as a paradigm of increasing precision-informed approach to patient care, and must be considered on a global scale with respect to the state of science and care delivery.
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Affiliation(s)
- Anis A Hamid
- Genitourinary Oncology Service, Memorial Sloan Kettering Cancer Center, New York, NY; Department of Surgery, University of Melbourne, Melbourne, Australia.
| | | | | | - Niall Corcoran
- Department of Surgery, University of Melbourne, Melbourne, Australia
| | - Arun A Azad
- Department of Medical Oncology, Peter MacCallum Cancer Centre, Melbourne, Australia; Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Australia
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Boyer MJ, Carpenter DJ, Gingrich JR, Raman SR, Sirohi D, Tabriz AA, Rompre-Broduer A, Lunyera J, Basher F, Bitting RL, Kosinski A, Cantrell S, Gordon AM, Ear B, Gierisch JM, Jacobs M, Goldstein KM. Genomic classifiers and prognosis of localized prostate cancer: a systematic review. Prostate Cancer Prostatic Dis 2024:10.1038/s41391-023-00766-z. [PMID: 38200096 DOI: 10.1038/s41391-023-00766-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Revised: 10/26/2023] [Accepted: 11/20/2023] [Indexed: 01/12/2024]
Abstract
BACKGROUND Refinement of the risk classification for localized prostate cancer is warranted to aid in clinical decision making. A systematic analysis was undertaken to evaluate the prognostic ability of three genomic classifiers, Decipher, GPS, and Prolaris, for biochemical recurrence, development of metastases and prostate cancer-specific mortality in patients with localized prostate cancer. METHODS Data sources: MEDLINE, Embase, and Web of Science were queried for reports published from January 2010 to April 2022. STUDY SELECTION prospective or retrospective studies reporting prognosis for patients with localized prostate cancer. DATA EXTRACTION relevant data were extracted into a customized database by one researcher with a second overreading. Risk of bias was assessed using a validated tool for prognostic studies, Quality in Prognosis Studies (QUIPS). Disagreements were resolved by consensus or by input from a third reviewer. We assessed the certainty of evidence by GRADE incorporating adaptation for prognostic studies. RESULTS Data synthesis: a total of 39 studies (37 retrospective) involving over 10,000 patients were identified. Twenty-two assessed Decipher, 5 GPS, and 14 Prolaris. Thirty-four studies included patients who underwent prostatectomy. Based on very low to low certainty of evidence, each of the three genomic classifiers modestly improved upon the prognostic ability for biochemical recurrence, development of metastases, and prostate cancer-specific mortality compared to standard clinical risk-classification schemes. LIMITATIONS downgrading of confidence in the evidence stemmed largely from bias due to the retrospective nature of the studies, heterogeneity in treatment received, and era in which patients were treated (i.e., prior to the 2000s). CONCLUSIONS Genomic classifiers provide a small but consistent improvement upon the prognostic ability of clinical classification schemes, which may be helpful when treatment decisions are uncertain. However, evidence from current management-era data and of the predictive ability of these tests is needed.
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Affiliation(s)
- Matthew J Boyer
- Durham VA Health Care System, Durham, NC, USA.
- Department of Radiation Oncology, Duke University School of Medicine, Durham, NC, USA.
| | | | - Jeffrey R Gingrich
- Durham VA Health Care System, Durham, NC, USA
- Department of Urology, Duke University School of Medicine, Durham, NC, USA
| | - Sudha R Raman
- Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, USA
| | - Deepika Sirohi
- Department of Pathology, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Amir Alishahi Tabriz
- Department of Health Outcomes and Behavior, Moffitt Cancer Center, Tampa, FL, USA
| | | | - Joseph Lunyera
- Division of General Internal Medicine, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Fahmin Basher
- Division of Medical Oncology, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Rhonda L Bitting
- Durham VA Health Care System, Durham, NC, USA
- Division of Medical Oncology, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Andrzej Kosinski
- Department of Biostatistics & Bioinformatics, Duke University School of Medicine, Durham, NC, USA
| | - Sarah Cantrell
- Duke University Medical Center Library & Archives, Duke University School of Medicine, Durham, NC, USA
| | | | - Belinda Ear
- Durham VA Health Care System, Durham, NC, USA
| | - Jennifer M Gierisch
- Durham VA Health Care System, Durham, NC, USA
- Division of General Internal Medicine, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
- Department of Population Health, Duke University School of Medicine, Durham, NC, USA
| | | | - Karen M Goldstein
- Durham VA Health Care System, Durham, NC, USA
- Division of General Internal Medicine, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
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7
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San Francisco IF, Rojas PA, Bravo JC, Díaz J, Ebel L, Urrutia S, Prieto B, Cerda-Infante J. Can We Predict Prostate Cancer Metastasis Based on Biomarkers? Where Are We Now? Int J Mol Sci 2023; 24:12508. [PMID: 37569883 PMCID: PMC10420177 DOI: 10.3390/ijms241512508] [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: 07/13/2023] [Revised: 07/26/2023] [Accepted: 07/27/2023] [Indexed: 08/13/2023] Open
Abstract
The incidence of prostate cancer (PC) has risen annually. PC mortality is explained by the metastatic disease (mPC). There is an intermediate scenario in which patients have non-mPC but have initiated a metastatic cascade through epithelial-mesenchymal transition. There is indeed a need for more and better tools to predict which patients will progress in the future to non-localized clinical disease or already have micrometastatic disease and, therefore, will clinically progress after primary treatment. Biomarkers for the prediction of mPC are still under development; there are few studies and not much evidence of their usefulness. This review is focused on tissue-based genomic biomarkers (TBGB) for the prediction of metastatic disease. We develop four main research questions that we attempt to answer according to the current evidence. Why is it important to predict metastatic disease? Which tests are available to predict metastatic disease? What impact should there be on clinical guidelines and clinical practice in predicting metastatic disease? What are the current prostate cancer treatments? The importance of predicting metastasis is fundamental given that, once metastasis is diagnosed, quality of life (QoL) and survival drop dramatically. There is still a need and space for more cost-effective TBGB tests that predict mPC disease.
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Affiliation(s)
- Ignacio F. San Francisco
- Environ Innovation Laboratory, Avenida Providencia 1208 Oficina 207, Providencia, Santiago 7500000, Chile;
| | - Pablo A. Rojas
- Servicio de Urología, Complejo Asistencial Dr. Sotero del Río, Santiago 8150215, Chile;
| | - Juan C. Bravo
- Servicio de Urología, Hospital Regional Libertador Bernardo O’Higgins, Rancagua 2820000, Chile;
| | - Jorge Díaz
- Servicio de Urología, Instituto Oncológico Fundación Arturo López Pérez, Santiago 7500921, Chile;
| | - Luis Ebel
- Servicio de Urología, Hospital Base de Valdivia, Universidad Austral, Valdivia 5090000, Chile;
| | - Sebastián Urrutia
- Servicio de Urología, Hospital Dr. Hernán Henríquez Aravena, Universidad de La Frontera, Temuco 4780000, Chile;
| | - Benjamín Prieto
- Environ Innovation Laboratory, Avenida Providencia 1208 Oficina 207, Providencia, Santiago 7500000, Chile;
| | - Javier Cerda-Infante
- Environ Innovation Laboratory, Avenida Providencia 1208 Oficina 207, Providencia, Santiago 7500000, Chile;
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Tsakiroglou M, Evans A, Pirmohamed M. Leveraging transcriptomics for precision diagnosis: Lessons learned from cancer and sepsis. Front Genet 2023; 14:1100352. [PMID: 36968610 PMCID: PMC10036914 DOI: 10.3389/fgene.2023.1100352] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Accepted: 02/20/2023] [Indexed: 03/12/2023] Open
Abstract
Diagnostics require precision and predictive ability to be clinically useful. Integration of multi-omic with clinical data is crucial to our understanding of disease pathogenesis and diagnosis. However, interpretation of overwhelming amounts of information at the individual level requires sophisticated computational tools for extraction of clinically meaningful outputs. Moreover, evolution of technical and analytical methods often outpaces standardisation strategies. RNA is the most dynamic component of all -omics technologies carrying an abundance of regulatory information that is least harnessed for use in clinical diagnostics. Gene expression-based tests capture genetic and non-genetic heterogeneity and have been implemented in certain diseases. For example patients with early breast cancer are spared toxic unnecessary treatments with scores based on the expression of a set of genes (e.g., Oncotype DX). The ability of transcriptomics to portray the transcriptional status at a moment in time has also been used in diagnosis of dynamic diseases such as sepsis. Gene expression profiles identify endotypes in sepsis patients with prognostic value and a potential to discriminate between viral and bacterial infection. The application of transcriptomics for patient stratification in clinical environments and clinical trials thus holds promise. In this review, we discuss the current clinical application in the fields of cancer and infection. We use these paradigms to highlight the impediments in identifying useful diagnostic and prognostic biomarkers and propose approaches to overcome them and aid efforts towards clinical implementation.
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Affiliation(s)
- Maria Tsakiroglou
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, United Kingdom
- *Correspondence: Maria Tsakiroglou,
| | - Anthony Evans
- Computational Biology Facility, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, United Kingdom
| | - Munir Pirmohamed
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, United Kingdom
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9
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Vujicic I, Rusevski A, Stankov O, Popov Z, Dimovski A, Davalieva K. Potential Role of Seven Proteomics Tissue Biomarkers for Diagnosis and Prognosis of Prostate Cancer in Urine. Diagnostics (Basel) 2022; 12:diagnostics12123184. [PMID: 36553191 PMCID: PMC9777474 DOI: 10.3390/diagnostics12123184] [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: 11/02/2022] [Revised: 12/09/2022] [Accepted: 12/12/2022] [Indexed: 12/23/2022] Open
Abstract
As the currently available tests for the clinical management of prostate cancer (PCa) are still far from providing precise diagnosis and risk stratification, the identification of new molecular marker(s) remains a pertinent clinical need. Candidate PCa biomarkers from the published proteomic comparative studies of prostate tissue (2002-2020) were collected and systematically evaluated. AZGP1, MDH2, FABP5, ENO1, GSTP1, GSTM2, and EZR were chosen for further evaluation in the urine of 85 PCa patients and controls using ELISA. Statistically significant differences in protein levels between PCa and BPH showed FABP5 (p = 0.019) and ENO1 (p = 0.015). A biomarker panel based on the combination of FABP5, ENO1, and PSA provided the highest accuracy (AUC = 0.795) for PCa detection. The combination of FABP5, EZR, AZGP1, and MDH2 showed AUC = 0.889 in PCa prognosis, with 85.29% of the samples correctly classified into low and high Gleason score (GS) groups. The addition of PSA to the panel slightly increased the AUC to 0.914. AZGP1, FABP5, and EZR showed significant correlation with GS, stage, and percentage of positive biopsy cores. Although validation using larger patient cohorts will be necessary to establish the credibility of the proposed biomarker panels in a clinical context, this study opens a way for the further testing of more high-quality proteomics biomarkers, which could ultimately add value to the clinical management of PCa.
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Affiliation(s)
- Ivo Vujicic
- University Clinic for Urology, University Clinical Centre “Mother Theresa”, 1000 Skopje, North Macedonia
| | - Aleksandar Rusevski
- Research Centre for Genetic Engineering and Biotechnology “Georgi D Efremov”, Macedonian Academy of Sciences and Arts, 1000 Skopje, North Macedonia
| | - Oliver Stankov
- University Clinic for Urology, University Clinical Centre “Mother Theresa”, 1000 Skopje, North Macedonia
| | - Zivko Popov
- Clinical Hospital “Acibadem Sistina”, 1000 Skopje, North Macedonia
- Medical Faculty, University “St. Cyril and Methodius”, 1000 Skopje, North Macedonia
- Macedonian Academy of Sciences and Arts, 1000 Skopje, North Macedonia
| | - Aleksandar Dimovski
- Research Centre for Genetic Engineering and Biotechnology “Georgi D Efremov”, Macedonian Academy of Sciences and Arts, 1000 Skopje, North Macedonia
- Faculty of Pharmacy, University “St. Cyril and Methodius”, 1000 Skopje, North Macedonia
| | - Katarina Davalieva
- Research Centre for Genetic Engineering and Biotechnology “Georgi D Efremov”, Macedonian Academy of Sciences and Arts, 1000 Skopje, North Macedonia
- Correspondence:
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10
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Chan E, McKenney JK, Hawley S, Corrigan D, Auman H, Newcomb LF, Boyer HD, Carroll PR, Cooperberg MR, Klein E, Fazli L, Gleave ME, Hurtado-Coll A, Simko JP, Nelson PS, Thompson IM, Tretiakova MS, Troyer D, True LD, Vakar-Lopez F, Lin DW, Brooks JD, Feng Z, Nguyen JK. Analysis of separate training and validation radical prostatectomy cohorts identifies 0.25 mm diameter as an optimal definition for "large" cribriform prostatic adenocarcinoma. Mod Pathol 2022; 35:1092-1100. [PMID: 35145197 PMCID: PMC9314256 DOI: 10.1038/s41379-022-01009-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Revised: 01/05/2022] [Accepted: 01/05/2022] [Indexed: 11/09/2022]
Abstract
Cribriform growth pattern is well-established as an adverse pathologic feature in prostate cancer. The literature suggests "large" cribriform glands associate with aggressive behavior; however, published studies use varying definitions for "large". We aimed to identify an outcome-based quantitative cut-off for "large" vs "small" cribriform glands. We conducted an initial training phase using the tissue microarray based Canary retrospective radical prostatectomy cohort. Of 1287 patients analyzed, cribriform growth was observed in 307 (24%). Using Kaplan-Meier estimates of recurrence-free survival curves (RFS) that were stratified by cribriform gland size, we identified 0.25 mm as the optimal cutoff to identify more aggressive disease. In univariable and multivariable Cox proportional hazard analyses, size >0.25 mm was a significant predictor of worse RFS compared to patients with cribriform glands ≤0.25 mm, independent of pre-operative PSA, grade, stage and margin status (p < 0.001). In addition, two different subset analyses of low-intermediate risk cases (cases with Gleason score ≤ 3 + 4 = 7; and cases with Gleason score = 3 + 4 = 7/4 + 3 = 7) likewise demonstrated patients with largest cribriform diameter >0.25 mm had a significantly lower RFS relative to patients with cribriform glands ≤0.25 mm (each subset p = 0.004). Furthermore, there was no significant difference in outcomes between patients with cribriform glands ≤ 0.25 mm and patients without cribriform glands. The >0.25 mm cut-off was validated as statistically significant in a separate 419 patient, completely embedded whole-section radical prostatectomy cohort by biochemical recurrence, metastasis-free survival, and disease specific death, even when cases with admixed Gleason pattern 5 carcinoma were excluded. In summary, our findings support reporting cribriform gland size and identify 0.25 mm as an optimal outcome-based quantitative measure for defining "large" cribriform glands. Moreover, cribriform glands >0.25 mm are associated with potential for metastatic disease independent of Gleason pattern 5 adenocarcinoma.
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Affiliation(s)
- Emily Chan
- Department of Pathology, University of California San Francisco (UCSF), San Francisco, CA, USA.
| | - Jesse K McKenney
- Robert J. Tomsich Institute of Pathology and Laboratory Medicine, Cleveland Clinic, Cleveland, OH, USA
| | | | - Dillon Corrigan
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | | | - Lisa F Newcomb
- Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- University of Washington Medical Center, Seattle, WA, USA
| | - Hilary D Boyer
- Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Peter R Carroll
- Department of Urology, University of California San Francisco (UCSF), San Francisco, CA, USA
| | - Matthew R Cooperberg
- Department of Urology, University of California San Francisco (UCSF), San Francisco, CA, USA
| | - Eric Klein
- Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Ladan Fazli
- University of British Columbia, Vancouver, BC, Canada
| | | | | | - Jeffry P Simko
- Department of Pathology, University of California San Francisco (UCSF), San Francisco, CA, USA
| | - Peter S Nelson
- Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- University of Washington Medical Center, Seattle, WA, USA
| | | | | | - Dean Troyer
- Eastern Virginia Medical School, Norfolk, VA, USA
- Department of Pathology, UT Health, San Antonio, TX, USA
| | | | | | - Daniel W Lin
- Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- University of Washington Medical Center, Seattle, WA, USA
| | | | - Ziding Feng
- Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Jane K Nguyen
- Robert J. Tomsich Institute of Pathology and Laboratory Medicine, Cleveland Clinic, Cleveland, OH, USA
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Prognostic Genomic Tissue-Based Biomarkers in the Treatment of Localized Prostate Cancer. J Pers Med 2022; 12:jpm12010065. [PMID: 35055380 PMCID: PMC8781984 DOI: 10.3390/jpm12010065] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Revised: 12/15/2021] [Accepted: 12/29/2021] [Indexed: 02/05/2023] Open
Abstract
In localized prostate cancer clinicopathologic variables have been used to develop prognostic nomograms quantifying the probability of locally advanced disease, of pelvic lymph node and distant metastasis at diagnosis or the probability of recurrence after radical treatment of the primary tumor. These tools although essential in daily clinical practice for the management of such a heterogeneous disease, which can be cured with a wide spectrum of treatment strategies (i.e., active surveillance, RP and radiation therapy), do not allow the precise distinction of an indolent instead of an aggressive disease. In recent years, several prognostic biomarkers have been tested, combined with the currently available clinicopathologic prognostic tools, in order to improve the decision-making process. In the following article, we reviewed the literature of the last 10 years and gave an overview report on commercially available tissue-based biomarkers and more specifically on mRNA-based gene expression classifiers. To date, these genomic tests have been widely investigated, demonstrating rigorous quality criteria including reproducibility, linearity, analytical accuracy, precision, and a positive impact in the clinical decision-making process. Albeit data published in literature, the systematic use of these tests in prostate cancer is currently not recommended due to insufficient evidence.
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