Commercial Gene Expression Tests for Prostate Cancer Prognosis Provide Paradoxical Estimates of Race-Specific Risk

A reliable transcriptomic risk-score applicable to formalin-fixed paraffin-embedded biopsies improves outcome prediction in localized prostate cancer

BACKGROUND

Clinical manifestation of prostate cancer (PCa) is highly variable. Aggressive tumors require radical treatment while clinically non-significant ones may be suitable for active surveillance. We previously developed the prognostic ProstaTrend RNA signature based on transcriptome-wide microarray and RNA-sequencing (RNA-Seq) analyses, primarily of prostatectomy specimens. An RNA-Seq study of formalin-fixed paraffin-embedded (FFPE) tumor biopsies has now allowed us to use this test as a basis for the development of a novel test that is applicable to FFPE biopsies as a tool for early routine PCa diagnostics.

METHODS

All patients of the FFPE biopsy cohort were treated by radical prostatectomy and median follow-up for biochemical recurrence (BCR) was 9 years. Based on the transcriptome data of 176 FFPE biopsies, we filtered ProstaTrend for genes susceptible to FFPE-associated degradation via regression analysis. ProstaTrend was additionally restricted to genes with concordant prognostic effects in the RNA-Seq TCGA prostate adenocarcinoma (PRAD) cohort to ensure robust and broad applicability. The prognostic relevance of the refined Transcriptomic Risk Score (TRS) was analyzed by Kaplan-Meier curves and Cox-regression models in our FFPE-biopsy cohort and 9 other public datasets from PCa patients with BCR as primary endpoint. In addition, we developed a prostate single-cell atlas of 41 PCa patients from 5 publicly available studies to analyze gene expression of ProstaTrend genes in different cell compartments.

RESULTS

Validation of the TRS using the original ProstaTrend signature in the cohort of FFPE biopsies revealed a relevant impact of FFPE-associated degradation on gene expression and consequently no significant association with prognosis (Cox-regression, p-value > 0.05) in FFPE tissue. However, the TRS based on the new version of the ProstaTrend-ffpe signature, which included 204 genes (of originally 1396 genes), was significantly associated with BCR in the FFPE biopsy cohort (Cox-regression p-value < 0.001) and retained prognostic relevance when adjusted for Gleason Grade Groups. We confirmed a significant association with BCR in 9 independent cohorts including 1109 patients. Comparison of the prognostic performance of the TRS with 17 other prognostically relevant PCa panels revealed that ProstaTrend-ffpe was among the best-ranked panels. We generated a PCa cell atlas to associate ProstaTrend genes with cell lineages or cell types. Tumor-specific luminal cells have a significantly higher TRS than normal luminal cells in all analyzed datasets. In addition, TRS of epithelial and luminal cells was correlated with increased Gleason score in 3 studies.

CONCLUSIONS

We developed a prognostic gene-expression signature for PCa that can be applied to FFPE biopsies and may be suitable to support clinical decision-making.

A harmonized resource of integrated prostate cancer clinical, -omic, and signature features

Genomic and transcriptomic data have been generated across a wide range of prostate cancer (PCa) study cohorts. These data can be used to better characterize the molecular features associated with clinical outcomes and to test hypotheses across multiple, independent patient cohorts. In addition, derived features, such as estimates of cell composition, risk scores, and androgen receptor (AR) scores, can be used to develop novel hypotheses leveraging existing multi-omic datasets. The full potential of such data is yet to be realized as independent datasets exist in different repositories, have been processed using different pipelines, and derived and clinical features are often not provided or  not standardized. Here, we present the curatedPCaData R package, a harmonized data resource representing >2900 primary tumor, >200 normal tissue, and >500 metastatic PCa samples across 19 datasets processed using standardized pipelines with updated gene annotations. We show that meta-analysis across harmonized studies has great potential for robust and clinically meaningful insights. curatedPCaData is an open and accessible community resource with code made available for reproducibility.

Algorithmic fairness in artificial intelligence for medicine and healthcare

In healthcare, the development and deployment of insufficiently fair systems of artificial intelligence (AI) can undermine the delivery of equitable care. Assessments of AI models stratified across subpopulations have revealed inequalities in how patients are diagnosed, treated and billed. In this Perspective, we outline fairness in machine learning through the lens of healthcare, and discuss how algorithmic biases (in data acquisition, genetic variation and intra-observer labelling variability, in particular) arise in clinical workflows and the resulting healthcare disparities. We also review emerging technology for mitigating biases via disentanglement, federated learning and model explainability, and their role in the development of AI-based software as a medical device.

curatedPCaData: Integration of clinical, genomic, and signature features in a curated and harmonized prostate cancer data resource

Genomic and transcriptomic data have been generated across a wide range of prostate cancer (PCa) study cohorts. These data can be used to better characterize the molecular features associated with clinical outcomes and to test hypotheses across multiple, independent patient cohorts. In addition, derived features, such as estimates of cell composition, risk scores, and androgen receptor (AR) scores, can be used to develop novel hypotheses leveraging existing multi-omic datasets. The full potential of such data is yet to be realized as independent datasets exist in different repositories, have been processed using different pipelines, and derived and clinical features are often not provided or unstandardized. Here, we present the curatedPCaData R package, a harmonized data resource representing >2900 primary tumor, >200 normal tissue, and >500 metastatic PCa samples across 19 datasets processed using standardized pipelines with updated gene annotations. We show that meta-analysis across harmonized studies has great potential for robust and clinically meaningful insights. curatedPCaData is an open and accessible community resource with code made available for reproducibility.

Molecular Testing for Diagnostics, Prognostication, and Treatment Stratification in Cancers

ABSTRACT

Precision cancer care, for essentially all cancer types, now requires molecular diagnostics to assess mutations, chromosomal alterations, and gene expression to personalize treatments for individual patients. Advances in the diagnostics and treatment options have moved the field forward from fundamental discoveries beginning in the 1960s to the development of many targeted therapies that can be as specific as targeting a single-base-pair mutation. Herein is a brief historical perspective on cancer precision medicine with current diagnostic, prognostic, and treatment stratification guidance for early- and late-stage cancers.

Racial disparities in prostate cancer among black men: epidemiology and outcomes

Prostate cancer has the widest racial disparities of any cancer, and these disparities appear at every stage of the cancer continuum. This review focuses on the disparities in prostate cancer between Black and White men, spanning from prevention and screening to clinical outcomes. We conduct an expansive review of the literature on racial disparities in prostate cancer, interpret the findings, and discuss areas of unmet need in research. We provide an overview of epidemiologic concepts necessary to understanding the current state of prostate cancer disparities, discuss the complexities of studying race, and review potential drivers of disparities in incidence and mortality. We argue that the cause of this disparity is multifactorial and due to a combination of social and environmental factors. The path forward needs to focus on enrolling and retaining Black men in prostate cancer clinical trials and observational studies and identifying potential interventions to improve prevention and clinical outcomes in Black men.

Characterizing molecular subtypes of high-risk non-muscle-invasive bladder cancer in African American patients

BACKGROUND

We sought to determine whether differences in subtype distribution and differentially expressed genes exist between African Americans (AAs) and European Americans (EAs) in patients with high-risk nonmuscle-invasive bladder cancer (NMIBC).

METHODS

We performed a retrospective cohort study including 26 patients (14 AAs and 12 EAs) from the University of Texas Medical Branch and the Durham Veterans Affair Health Care System from 2010 to 2020 among treatment naïve, high-risk NMIBC. Profiled gene expressions were performed using the UROMOL classification system.

RESULTS

UROMOL racial subtype distributions were similar with class 2a being most common with 10 genes commonly upregulated in AAs compared to EAs including EFEMP1, S100A16, and MCL1 which are associated with progression to muscle-invasive bladder cancer, mitomycin C resistance, and bacillus Calmette-Guérin durability, respectively. We used single nuclei analysis to map the malignant cell heterogeneity in urothelial cancer which 5 distinct malignant epithelial subtypes whose presence has been associated with different therapeutic response prediction abilities. We mapped the expression of the 10 genes commonly upregulated by race as a function of the 5 malignant subtypes. This showed borderline (P = 0.056) difference among the subtypes suggesting AAs and EAs may be expected to have different therapeutic responses to treatments for bladder cancer. AAs were enriched with immune-related, inflammatory, and cellular regulation pathways compared to EAs, yet appeared to have reduced levels of the aggressive C3/CDH12 bladder tumor cell population.

CONCLUSIONS

While premature, gene expression differed between AAs and EAs, supporting potential race-based etiologies for muscle-invasion, response to treatments, and transcriptome pathway regulations.

Variation in Molecularly Defined Prostate Tumor Subtypes by Self-identified Race

Background

Socioeconomic and health care utilization factors are major drivers of prostate cancer (PC) mortality disparities in the USA; however, tumor molecular heterogeneity may also contribute to the higher mortality among Black men.

Objective

To compare differences in PC subtype frequency and genomic aggressiveness by self-identified race.

Design setting and participants

Five molecular subtype classifiers were applied for 426 Black and 762 White PC patients in the Decipher Genomics Resource Information Database (GRID).

Outcome measurements and statistical analysis

Differences in subtype frequency and tumor genomic risk (Decipher score >0.6) by race were evaluated using χ² tests and multivariable-adjusted logistic regression models.

Results and limitations

Subtype frequencies differed by race for four classifiers. Subtypes characterized by the presence of SPOP mutations, SPINK1 overexpression, and neuroendocrine differentiation were more common among Black men. ERG and ETS fusion-positive subtypes were more frequent among White men, with no clear differences for subtypes reflecting luminal versus basal lineage. The hypothesized low-risk Kamoun S2 subtype was associated with a lower Decipher score among White men only (p = 0.01 for heterogeneity), while the aggressive You PCS1 subtype was associated with a higher Decipher score among White men only (p = 0.001 for heterogeneity). The Tomlins ERG⁺ subtype was associated with a higher Decipher score relative to all other subtypes among Black men, with no association among White men (p = 0.007 for heterogeneity).

Conclusions

The frequency of PC molecular subtypes differed by self-identified race. Additional studies are required to evaluate whether our observations suggest differences in the tumor genomic risk of progression by self-identified race.

Patient summary

We studied five classifiers that identify subtypes of prostate tumors and found that subtypes differed in frequency between Black and White patients. Further research is warranted to evaluate how differences in tumor subtypes may contribute to disparities in prostate cancer mortality.

Experimental challenges to modeling prostate cancer heterogeneity

Tumor heterogeneity plays a key role in prostate cancer prognosis, therapy selection, relapse, and acquisition of treatment resistance. Prostate cancer presents a heterogeneous diversity at inter- and intra-tumor and inter-patient levels which are influenced by multiple intrinsic and/or extrinsic factors. Recent studies have started to characterize the complexity of prostate tumors and these different tiers of heterogeneity. In this review, we discuss the most common factors that contribute to tumoral diversity. Moreover, we focus on the description of the in vitro and in vivo approaches, as well as high-throughput technologies, that help to model intra-tumoral diversity. Further understanding tumor heterogeneities and the challenges they present will guide enhanced patient risk stratification, aid the design of more precise therapies, and ultimately help beat this chameleon-like disease.

NCCN Risk Reclassification in Black Men with Low and Intermediate Risk Prostate Cancer After Genomic Testing

OBJECTIVES

To assess the utility of genomic testing in risk-stratifying Black patients with low and intermediate risk prostate cancer.

METHODS

We retrospectively identified 63 Black men deemed eligible for active surveillance based on National Comprehensive Cancer Network (NCCN) guidelines, who underwent OncotypeDx Genomic Prostate Score testing between April 2016 and July 2020. Nonparametric statistical testing was used to compare relevant features between patients reclassified to a higher NCCN risk after genomic testing and those who were not reclassified.

RESULTS

The median age was 66 years and median pre-biopsy PSA was 7.3. Initial risk classifications were: very low risk: 7 (11.1%), low risk: 24(38.1%), favorable intermediate risk: 31(49.2%), and unfavorable intermediate risk: 1 (1.6%). Overall, NCCN risk classifications after Genomic Prostate Score testing were significantly higher than initial classifications (P=.003, Wilcoxon signed-rank). Among patients with discordant risk designations, 28(28/40, 70%) were reclassified to a higher NCCN risk after genomic testing. A pre-biopsy prostate specific antigen of greater than 10 did not have significantly higher odds of HBR (OR:2.16 [95% CI: 0.64,7.59, P=.2). Of favorable intermediate risk patients, 20(64.5%) were reclassified to a higher NCCN risk. Ultimately, 18 patients underwent definitive treatment.

CONCLUSIONS

Incorporation of genomic testing in risk stratifying Black men with low and intermediate-risk prostate cancer resulted in overall higher NCCN risk classifications. Our findings suggest a role for increased utilization of genomic testing in refining risk-stratification within this patient population. These tests may better inform treatment decisions on an individualized basis.

Prostate Cancer Racial Disparities: A Systematic Review by the Prostate Cancer Foundation Panel

CONTEXT

Prostate cancer (PCa) is a complex disease that disproportionately impacts Black men in the USA. The structural factors that drive heterogeneous outcomes for patients of differing backgrounds are probably the same ones that result in population-level disparities. The relative contribution of drivers along the PCa disease continuum is an active area of investigation and debate.

OBJECTIVE

To critically synthesize the available evidence on PCa disparities from a population-level perspective in comparison to data from "equal access and equal care settings" and to provide a consensus summary of the state of PCa disparities.

EVIDENCE ACQUISITION

A plenary panel on PCa disparities presented at the Prostate Cancer Foundation meeting on October 24, 2019 and ensuing discussions are reported here. We used a systematic literature review approach and the Preferred Reporting Items for Systematic Reviews and Meta-analyses to select the most relevant publications. A total of 3333 publications between 2011 and 2021 were retrieved, of which 52 were included in the review; an additional 13 articles on screening guidelines, seminal clinical trials, and statistical methodology were used in the evidence synthesis.

EVIDENCE SYNTHESIS

Race disparities in PCa are a result of a complex interaction between socioeconomic factors impacting access to care and ancestral/genetic factors that may influence tumor biology. Black men in the USA continue to have a nearly 1.8 times higher population-level mortality rate than White men. Failure to account for the race-specific incidence burden would continue to lead to residual disparity even after achieving relatively similar outcomes after primary treatment, resulting in a higher long-term mortality burden. Selection bias remains possible in PCa studies, which often rely on highly specific cohorts of Black men with higher use of health care resources that may not represent the average Black patient in the USA. Novel methods including mediation analysis and genetic ancestry rather than self-identified race can optimize analytical models investigating racial disparities and may lead to a better understanding of PCa genomic diversity and behavior.

CONCLUSIONS

Our findings emphasize the importance of racially diverse studies, including precision -omics, prevention, and targeted therapy initiatives, to elucidate mechanisms underlying racial differences in outcomes and response to therapy. We propose novel approaches for studying and addressing PCa disparities. Contemporary methods, particularly in the domain of mediation analysis, can promote scientific rigor in understanding these disparities.

PATIENT SUMMARY

Inaccurate data interpretation or lack of data altogether for Black men can impact policy and ultimately affect millions of individuals of African origin worldwide. Our review identifies a need to develop and prioritize a strategy for including Black and other men with prostate cancer in intervention studies and randomized clinical trials to halt the widening prostate cancer disparities.

Tissue- and Liquid-Based Biomarkers in Prostate Cancer Precision Medicine

Worldwide, prostate cancer (PC) is the second-most-frequently diagnosed male cancer and the fifth-most-common cause of all cancer-related deaths. Suspicion of PC in a patient is largely based upon clinical signs and the use of prostate-specific antigen (PSA) levels. Although PSA levels have been criticised for a lack of specificity, leading to PC over-diagnosis, it is still the most commonly used biomarker in PC management. Unfortunately, PC is extremely heterogeneous, and it can be difficult to stratify patients whose tumours are unlikely to progress from those that are aggressive and require treatment intensification. Although PC-specific biomarker research has previously focused on disease diagnosis, there is an unmet clinical need for novel prognostic, predictive and treatment response biomarkers that can be used to provide a precision medicine approach to PC management. In particular, the identification of biomarkers at the time of screening/diagnosis that can provide an indication of disease aggressiveness is perhaps the greatest current unmet clinical need in PC management. Largely through advances in genomic and proteomic techniques, exciting pre-clinical and clinical research is continuing to identify potential tissue, blood and urine-based PC-specific biomarkers that may in the future supplement or replace current standard practices. In this review, we describe how PC-specific biomarker research is progressing, including the evolution of PSA-based tests and those novel assays that have gained clinical approval. We also describe alternative diagnostic biomarkers to PSA, in addition to biomarkers that can predict PC aggressiveness and biomarkers that can predict response to certain therapies. We believe that novel biomarker research has the potential to make significant improvements to the clinical management of this disease in the near future.

Epidemiology and genomics of prostate cancer in Asian men

Prostate cancer is a global health problem, but incidence varies considerably across different continents. Asia is traditionally considered a low-incidence area, but the incidence and mortality of prostate cancer have rapidly increased across the continent. Substantial differences in epidemiological features have been observed among different Asian regions, and incidence, as well as mortality-to-incidence ratio, is associated with the human development index. Prostate cancer mortality decreased in Japan and Israel from 2007 to 2016, but mortality has increased in Thailand, Kyrgyzstan and Uzbekistan over the same period. Genomic analyses have shown a low prevalence of ERG oncoprotein in the East Asian population, alongside a low rate of PTEN loss, high CHD1 enrichments and high FOXA1 alterations. Contributions from single-nucleotide polymorphisms to prostate cancer risk vary with ethnicity, but germline mutation rates of DNA damage repair genes in metastatic prostate cancer are comparable in Chinese and white patients from the USA and UK. Pharmacogenomic features of testosterone metabolism might contribute to disparities seen in the response to androgen deprivation between East Asian men and white American and European men. Overall, considerable diversity in epidemiology and genomics of prostate cancer across Asia defines disease characteristics in these populations, but studies in this area are under-represented in the literature. Taking into account this intracontinental and intercontinental heterogeneity, translational studies are required in order to develop ethnicity-specific treatment strategies.

Gene Regulation Network Analysis on Human Prostate Orthografts Highlights a Potential Role for the JMJD6 Regulon in Clinical Prostate Cancer

Simple Summary

Prostate cancer is a very common malignancy worldwide. Treatment resistant prostate cancer poses a big challenge to clinicians and is the second most common cause of premature death in men with cancer. Gene expression analysis has been performed on clinical tumours but to date none of the gene expression-based biomarkers for prostate cancer have been successfully integrated to into clinical practice to improve patient management and treatment choice. We applied a novel laboratory prostate cancer model to mimic clinical hormone responsive and resistant prostate cancer and tested whether a network of genes similarly regulated by transcription factors (gene products that control the expression of target genes) are associated with patient outcome. We identified regulons (networks of genes similarly regulated) from our preclinical prostate cancer models and further evaluated the top ranked JMJD6 gene related regulated network in three independent clinical patient cohorts.

Abstract

Background: Prostate cancer (PCa) is the second most common tumour diagnosed in men. Tumoral heterogeneity in PCa creates a significant challenge to develop robust prognostic markers and novel targets for therapy. An analysis of gene regulatory networks (GRNs) in PCa may provide insight into progressive PCa. Herein, we exploited a graph-based enrichment score to integrate data from GRNs identified in preclinical prostate orthografts and differentially expressed genes in clinical resected PCa. We identified active regulons (transcriptional regulators and their targeted genes) associated with PCa recurrence following radical prostatectomy. Methods: The expression of known transcription factors and co-factors was analysed in a panel of prostate orthografts (n = 18). We searched for genes (as part of individual GRNs) predicted to be regulated by the highest number of transcriptional factors. Using differentially expressed gene analysis (on a per sample basis) coupled with gene graph enrichment analysis, we identified candidate genes and associated GRNs in PCa within the UTA cohort, with the most enriched regulon being JMJD6, which was further validated in two additional cohorts, namely EMC and ICGC cohorts. Cox regression analysis was performed to evaluate the association of the JMJD6 regulon activity with disease-free survival time in the three clinical cohorts as well as compared to three published prognostic gene signatures (TMCC11, BROMO-10 and HYPOXIA-28). Results: 1308 regulons were correlated to transcriptomic data from the three clinical prostatectomy cohorts. The JMJD6 regulon was identified as the top enriched regulon in the UTA cohort and again validated in the EMC cohort as the top-ranking regulon. In both UTA and EMC cohorts, the JMJD6 regulon was significantly associated with cancer recurrence. Active JMJD6 regulon also correlated with disease recurrence in the ICGC cohort. Furthermore, Kaplan–Meier analysis confirmed shorter time to recurrence in patients with active JMJD6 regulon for all three clinical cohorts (UTA, EMC and ICGC), which was not the case for three published prognostic gene signatures (TMCC11, BROMO-10 and HYPOXIA-28). In multivariate analysis, the JMJD6 regulon status significantly predicted disease recurrence in the UTA and EMC, but not ICGC datasets, while none of the three published signatures significantly prognosticate for cancer recurrence. Conclusions: We have characterised gene regulatory networks from preclinical prostate orthografts and applied transcriptomic data from three clinical cohorts to evaluate the prognostic potential of the JMJD6 regulon.

TMPRSS2-ERG fusion impacts anterior tumor location in men with prostate cancer

BACKGROUND

In prostate cancer (PCa), lack of androgen receptor (AR) regulated TMPRSS2-ETS-related gene (ERG) gene fusion (ERG^negative ) status has been associated with African American race; however, the implications of ERG status for the location of dominant tumors within the prostate remains understudied.

METHODS

An African American-enriched multiinstitutional cohort of 726 PCa patients consisting of both African American men (AAM; n = 254) and European American men (EAM; n = 472) was used in the analyses. Methods of categorical analysis were used. Messenger RNA (mRNA) expression differences between anterior and posterior tumor lesions were analyzed using Wilcoxon rank-sum tests with multiple comparison corrections.

RESULTS

Anti-ERG immunohistochemistry staining showed that the association between ERG status and anterior tumors is independent of race and is consistently robust for both AAM (ERG^negative 81.4% vs. ERG^positive 18.6%; p = .005) and EAM (ERG^negative 60.4% vs. ERG^positive 39.6%; p < .001). In a multivariable model, anterior tumors were more likely to be IHC-ERG^negative (odds ratio [OR]: 3.20; 95% confidence interval [CI]: 2.14-4.78; p < .001). IHC-ERG^negative were also more likely to have high-grade tumors (OR: 1.73; 95% CI: 1.06-2.82; p = .02). In the exploratory genomic analysis, mRNA expression of location-dependent genes is highly influenced by ERG status and African American race. However, tumor location did not impact the expression of AR or the major canonical AR-target genes (KLK3, AMACR, and MYC).

CONCLUSIONS

ERG^negative tumor status is the strongest predictor of anterior prostate tumors, regardless of race. Furthermore, AR expression and canonical AR signaling do not impact tumor location.

Biological Aspects of Cancer Health Disparities

Racial and ethnic disparities span the continuum of cancer care and are driven by a complex interplay among social, psychosocial, lifestyle, environmental, health system, and biological determinants of health. Research is needed to identify these determinants of cancer health disparities and to develop interventions to achieve cancer health equity. Herein, we focus on the overall burden of ancestry-related molecular alterations, the functional significance of the alterations in hallmarks of cancer, and the implications of the alterations for precision oncology and immuno-oncology. In conclusion, we reflect on the importance of estimating ancestry, improving diverse racial and ethnic participation in cancer clinical trials, and examining the intersection among determinants of cancer health disparities.

Development of an Actionable Framework to Address Cancer Care Disparities in Medically Underserved Populations in the United States: Expert Roundtable Recommendations

Cancer disparities persist among medically underserved populations despite widespread efforts to address them. We describe the development of a framework for addressing cancer care disparities across the cancer care continuum (CCC), guided by the CCC domains established by the Institute of Medicine/National Academies of Sciences, Engineering, and Medicine (IOM/NAS).