Comprehensive Determination of Prostate Tumor ETS Gene Status in Clinical Samples Using the CLIA Decipher Assay

Predicting Prostate Cancer Molecular Subtype With Deep Learning on Histopathologic Images

Microscopic examination of prostate cancer has failed to reveal a reproducible association between molecular and morphologic features. However, deep-learning algorithms trained on hematoxylin and eosin (H&E)-stained whole slide images (WSI) may outperform the human eye and help to screen for clinically-relevant genomic alterations. We created deep-learning algorithms to identify prostate tumors with underlying ETS-related gene (ERG) fusions or PTEN deletions using the following 4 stages: (1) automated tumor identification, (2) feature representation learning, (3) classification, and (4) explainability map generation. A novel transformer-based hierarchical architecture was trained on a single representative WSI of the dominant tumor nodule from a radical prostatectomy (RP) cohort with known ERG/PTEN status (n = 224 and n = 205, respectively). Two distinct vision transformer-based networks were used for feature extraction, and a distinct transformer-based model was used for classification. The ERG algorithm performance was validated across 3 RP cohorts, including 64 WSI from the pretraining cohort (AUC, 0.91) and 248 and 375 WSI from 2 independent RP cohorts (AUC, 0.86 and 0.89, respectively). In addition, we tested the ERG algorithm performance in 2 needle biopsy cohorts comprised of 179 and 148 WSI (AUC, 0.78 and 0.80, respectively). Focusing on cases with homogeneous (clonal) PTEN status, PTEN algorithm performance was assessed using 50 WSI reserved from the pretraining cohort (AUC, 0.81), 201 and 337 WSI from 2 independent RP cohorts (AUC, 0.72 and 0.80, respectively), and 151 WSI from a needle biopsy cohort (AUC, 0.75). For explainability, the PTEN algorithm was also applied to 19 WSI with heterogeneous (subclonal) PTEN loss, where the percentage tumor area with predicted PTEN loss correlated with that based on immunohistochemistry (r = 0.58, P = .0097). These deep-learning algorithms to predict ERG/PTEN status prove that H&E images can be used to screen for underlying genomic alterations in prostate cancer.

Clinical testing of transcriptome-wide expression profiles in high-risk localized and metastatic prostate cancer starting androgen deprivation therapy: an ancillary study of the STAMPEDE abiraterone Phase 3 trial

Metastatic and high-risk localized prostate cancer respond to hormone therapy but outcomes vary. Following a pre-specified statistical plan, we used Cox models adjusted for clinical variables to test associations with survival of multi-gene expression-based classifiers from 781 patients randomized to androgen deprivation with or without abiraterone in the STAMPEDE trial. Decipher score was strongly prognostic (p<2×10-5) and identified clinically-relevant differences in absolute benefit, especially for localized cancers. In metastatic disease, classifiers of proliferation, PTEN or TP53 loss and treatment-persistent cells were prognostic. In localized disease, androgen receptor activity was protective whilst interferon signaling (that strongly associated with tumor lymphocyte infiltration) was detrimental. Post-Operative Radiation-Therapy Outcomes Score was prognostic in localized but not metastatic disease (interaction p=0.0001) suggesting the impact of tumor biology on clinical outcome is context-dependent on metastatic state. Transcriptome-wide testing has clinical utility for advanced prostate cancer and identified worse outcomes for localized cancers with tumor-promoting inflammation.

Transcriptomes of Prostate Cancer with TMPRSS2:ERG and Other ETS Fusions

The most common somatic event in primary prostate cancer is a fusion between the androgen-related TMPRSS2 gene and the ERG oncogene. Tumors with these fusions, which occur early in carcinogenesis, have a distinctive etiology. A smaller subset of other tumors harbor fusions between TMPRSS2 and members of the ETS transcription factor family other than ERG. To assess the genomic similarity of tumors with non-ERG ETS fusions and those with fusions involving ERG, this study derived a transcriptomic signature of non-ERG ETS fusions and assessed this signature and ERG-related gene expression in 1,050 men with primary prostate cancer from three independent population-based and hospital-based studies. Although non-ERG ETS fusions involving ETV1, ETV4, ETV5, or FLI1 were individually rare, they jointly accounted for one in seven prostate tumors. Genes differentially regulated between non-ERG ETS tumors and tumors without ETS fusions showed similar differential expression when ERG tumors and tumors without ETS fusions were compared (differences explained: R2 = 69-77%), including ETS-related androgen receptor (AR) target genes. Differences appeared to result from similarities among ETS tumors rather than similarities among non-ETS tumors. Gene sets associated with ERG fusions were consistent with gene sets associated with non-ERG ETS fusions, including fatty acid and amino acid metabolism, an observation that was robust across cohorts.

IMPLICATIONS

Considering ETS fusions jointly may be useful for etiologic studies on prostate cancer, given that the transcriptome is profoundly impacted by ERG and non-ERG ETS fusions in a largely similar fashion, most notably genes regulating metabolic pathways.

Association of B7-H3 expression with racial ancestry, immune cell density, and androgen receptor activation in prostate cancer

Background

B7 homolog 3 (B7‐H3) is an immunomodulatory molecule that is highly expressed in prostate cancer (PCa) and belongs to the B7 superfamily, which includes PD‐L1. Immunotherapies (antibodies, antibody‐drug conjugates, and chimeric antigen receptor T cells) targeting B7‐H3 are currently in clinical trials; therefore, elucidating the molecular and immune microenvironment correlates of B7‐H3 expression may help to guide trial design and interpretation. The authors tested the interconnected hypotheses that B7‐H3 expression is associated with genetic racial ancestry, immune cell composition, and androgen receptor signaling in PCa.

Methods

An automated, clinical‐grade immunohistochemistry assay was developed by to digitally quantify B7‐H3 protein expression across 2 racially diverse cohorts of primary PCa (1 with previously reported transcriptomic data) and pretreatment and posttreatment PCa tissues from a trial of intensive neoadjuvant hormonal therapy.

Results

B7‐H3 protein expression was significantly lower in self‐identified Black patients and was inversely correlated with the percentage African ancestry. This association with race was independent of the significant association of B7‐H3 protein expression with ERG/ETS and PTEN status. B7‐H3 messenger RNA expression, but not B7‐H3 protein expression, was significantly correlated with regulatory (FOXP3‐positive) T‐cell density. Finally, androgen receptor activity scores were significantly correlated with B7‐H3 messenger RNA expression, and neoadjuvant intensive hormonal therapy was associated with a significant decrease in B7‐H3 protein expression.

Conclusions

The current data underscore the importance of studying racially and molecularly diverse PCa cohorts in the immunotherapy era. This study is among the first to use genetic ancestry markers to add to the emerging evidence that PCa in men of African ancestry may have a distinct biology associated with B7‐H3 expression.

Lay Summary

B7‐H3 is an immunomodulatory molecule that is highly expressed in prostate cancer and is under investigation in clinical trials.

The authors determined that B7‐H3 protein expression is inversely correlated with an individual's proportion of African ancestry.

The results demonstrate that B7‐H3 messenger RNA expression is correlated with the density of tumor T‐regulatory cells.

Finally, in the first paired analysis of B7‐H3 protein expression before and after neoadjuvant intensive hormone therapy, the authors determined that hormone therapy is associated with a decrease in B7‐H3 protein levels, suggesting that androgen signaling may positively regulate B7‐H3 expression.

These results may help to guide the design of future clinical trials and to develop biomarkers of response in such trials.

B7‐H3 protein expression was significantly lower in self‐identified Black patients and was inversely correlated with the percentage African ancestry. Androgen receptor activity scores were significantly correlated with B7‐H3 messenger RNA expression, and neoadjuvant intensive hormonal therapy was associated with a significant decrease in B7‐H3 protein expression, consistent with a presumed androgen receptor binding site upstream of the B7‐H3 promoter.

Biomarker discovery studies for patient stratification using machine learning analysis of omics data: a scoping review

OBJECTIVE

To review biomarker discovery studies using omics data for patient stratification which led to clinically validated FDA-cleared tests or laboratory developed tests, in order to identify common characteristics and derive recommendations for future biomarker projects.

DESIGN

Scoping review.

METHODS

We searched PubMed, EMBASE and Web of Science to obtain a comprehensive list of articles from the biomedical literature published between January 2000 and July 2021, describing clinically validated biomarker signatures for patient stratification, derived using statistical learning approaches. All documents were screened to retain only peer-reviewed research articles, review articles or opinion articles, covering supervised and unsupervised machine learning applications for omics-based patient stratification. Two reviewers independently confirmed the eligibility. Disagreements were solved by consensus. We focused the final analysis on omics-based biomarkers which achieved the highest level of validation, that is, clinical approval of the developed molecular signature as a laboratory developed test or FDA approved tests.

RESULTS

Overall, 352 articles fulfilled the eligibility criteria. The analysis of validated biomarker signatures identified multiple common methodological and practical features that may explain the successful test development and guide future biomarker projects. These include study design choices to ensure sufficient statistical power for model building and external testing, suitable combinations of non-targeted and targeted measurement technologies, the integration of prior biological knowledge, strict filtering and inclusion/exclusion criteria, and the adequacy of statistical and machine learning methods for discovery and validation.

CONCLUSIONS

While most clinically validated biomarker models derived from omics data have been developed for personalised oncology, first applications for non-cancer diseases show the potential of multivariate omics biomarker design for other complex disorders. Distinctive characteristics of prior success stories, such as early filtering and robust discovery approaches, continuous improvements in assay design and experimental measurement technology, and rigorous multicohort validation approaches, enable the derivation of specific recommendations for future studies.

E26 transformation-specific variant 4 as a tumor promotor in human cancers through specific molecular mechanisms

E26 transformation-specific (ETS) variant 4 (ETV4) is an important transcription factor that belongs to the ETS transcription factor family and is essential for much cellular physiology. Recent evidence has revealed that ETV4 is aberrantly expressed in many types of tumors, and its overexpression is related to poor prognosis of cancer patients. Additionally, increasing studies have identified that ETV4 promotes cancer growth, invasion, metastasis, and drug resistance. Mechanistically, the level of ETV4 is regulated by some post-translation modulations in a broad spectrum of cancers. However, little progress has been made to comprehensively summarize the critical roles of ETV4 in different human cancers. Hence, this review mainly focuses on the physiological functions of ETV4 in various human tumors. In addition, the molecular mechanisms of ETV4-mediated cancer progression were elucidated, including how ETV4 modulates its downstream signaling pathways and how ETV4 is regulated by some factors. On this basis, the present review may provide a valuable therapeutics strategy for future cancer treatment by targeting ETV4-related pathways.

Gene Regulatory Network of ETS Domain Transcription Factors in Different Stages of Glioma

The ETS domain family of transcription factors is involved in a number of biological processes, and is commonly misregulated in various forms of cancer. Using microarray datasets from patients with different grades of glioma, we have analyzed the expression profiles of various ETS genes, and have identified ETV1, ELK3, ETV4, ELF4, and ETV6 as novel biomarkers for the identification of different glioma grades. We have further analyzed the gene regulatory networks of ETS transcription factors and compared them to previous microarray studies, where Elk-1-VP16 or PEA3-VP16 were overexpressed in neuroblastoma cell lines, and we identify unique and common regulatory networks for these ETS proteins.

Plasma cells are enriched in localized prostate cancer in Black men and are associated with improved outcomes

Black men die more often of prostate cancer yet, interestingly, may derive greater survival benefits from immune-based treatment with sipuleucel-T. Since no signatures of immune-responsiveness exist for prostate cancer, we explored race-based immune-profiles to identify vulnerabilities. Here we show in multiple independent cohorts comprised of over 1,300 patient samples annotated with either self-identified race or genetic ancestry, prostate tumors from Black men or men of African ancestry have increases in plasma cell infiltrate and augmented markers of NK cell activity and IgG expression. These findings are associated with improved recurrence-free survival following surgery and nominate plasma cells as drivers of prostate cancer immune-responsiveness.

Function and regulation of the PEA3 subfamily of ETS transcription factors in cancer

The PEA3 subfamily is a subgroup of the E26 transformation-specific (ETS) family. Its members, ETV1, ETV4, and ETV5, have been found to be overexpressed in multiple cancers. The deregulation of ETV1, ETV4, and ETV5 induces cell growth, invasion, and migration in various tumor cells, leading to tumor progression, metastasis, and drug resistance. Therefore, exploring drugs or therapeutic targets that target the PEA3 subfamily may contribute to the clinical treatment of tumor patients. In this review, we introduce the structures and functions of the PEA3 subfamily members, systematically review their main roles in various tumor cells, analyze their prognostic and diagnostic value, and, finally, introduce several molecular targets and therapeutic drugs targeting ETV1, ETV4, and ETV5. We conclude that targeting a series of upstream regulators and downstream target genes of the PEA3 subfamily may be an effective strategy for the treatment of ETV1/ETV4/ETV5-overexpressing tumors.

A New Era of Prostate Cancer Precision Medicine

Prostate cancer is the second most common male cancer affecting Western society. Despite substantial advances in the exploration of prostate cancer biomarkers and treatment strategies, men are over diagnosed with inert prostate cancer, while there is also a substantial mortality from the invasive disease. Precision medicine is the management of treatment profiles across different cancers predicting therapies for individual cancer patients. With strategies including individual genomic profiling and targeting specific cancer pathways, precision medicine for prostate cancer has the potential to impose changes in clinical practices. Some of the recent advances in prostate cancer precision medicine comprise targeting gene fusions, genome editing tools, non-coding RNA biomarkers, and the promise of liquid tumor profiling. In this review, we will discuss these recent scientific advances to scale up these approaches and endeavors to overcome clinical barriers for prostate cancer precision medicine.

Transcriptomic Heterogeneity of Androgen Receptor Activity Defines a de novo low AR-Active Subclass in Treatment Naïve Primary Prostate Cancer

PURPOSE

The heterogeneity of androgen receptor (AR)-activity (AR-A) is well-characterized in heavily treated metastatic castration-resistant prostate cancer (mCRPC). However, the diversity and clinical implications of AR-A in treatment-naïve primary prostate cancer is largely unknown. We sought to characterize AR-A in localized prostate cancer and understand its molecular and clinical implications.

EXPERIMENTAL DESIGN

Genome-wide expression profiles from prostatectomy or biopsy samples from 19,470 patients were used, all with independent pathology review. This was comprised of prospective discovery (n = 5,239) and validation (n = 12,728) cohorts, six retrospective institutional cohorts with long-term clinical outcomes data (n = 1,170), and The Cancer Genome Atlas (n = 333).

RESULTS

A low AR-active subclass was identified, which comprised 9%-11% of each cohort, and was characterized by increased immune signaling, neuroendocrine expression, and decreased DNA repair. These tumors were predominantly ERG and basal subtype. Low AR-active tumors had significantly more rapid development of recurrence or metastatic disease across cohorts, which was maintained on multivariable analysis [HR, 2.61; 95% confidence interval (CI), 1.22-5.60; P = 0.014]. Low AR-active tumors were predicted to be more sensitive to PARP inhibition, platinum chemotherapy, and radiotherapy, and less sensitive to docetaxel and androgen-deprivation therapy. This was validated clinically, in that low AR-active tumors were less sensitive to androgen-deprivation therapy (OR, 0.41; 95% CI, 0.21-0.80; P = 0.008).

CONCLUSIONS

Leveraging large-scale transcriptomic data allowed the identification of an aggressive subtype of treatment-naïve primary prostate cancer that harbors molecular features more analogous to mCRPC. This suggests that a preexisting subgroup of patients may have tumors that are predisposed to fail multiple current standard-of-care therapies and warrant dedicated therapeutic investigation.

African American Specific Gene Panel Predictive of Poor Prostate Cancer Outcome

PURPOSE

Most prostate cancer in African American men lacks the ETS (E26 transforming specific) family fusion event (ETS-). We aimed to establish clinically relevant biomarkers in African American men by studying ETS dependent gene expression patterns to identified race specific genes predictive of outcomes.

MATERIALS AND METHODS

Two multicenter cohorts of a total of 1,427 men were used for the discovery and validation (635 and 792 men, respectively) of race specific predictive biomarkers. We used false discovery rate adjusted q values to identify race and ETS dependent genes which were differentially expressed in African American men who experienced biochemical recurrence within 5 years. Principal component modeling along with survival analysis was done to assess the accuracy of the gene panel in predicting recurrence.

RESULTS

We identified 3,047 genes which were differentially expressed based on ETS status. Of these genes 362 were differentially expressed in a race specific manner (false discovery rate 0.025 or less). A total of 81 genes were race specific and over expressed in African American men who experienced biochemical recurrence. The final gene panel included APOD, BCL6, EMP1, MYADM, SRGN and TIMP3. These genes were associated with 5-year biochemical recurrence (HR 1.97, 95% CI 1.27-3.06, p = 0.002) and they improved the predictive accuracy of clinicopathological variables only in African American men (60-month time dependent AUC 0.72).

CONCLUSIONS

In an effort to elucidate biological features associated with prostate cancer aggressiveness in African American men we identified ETS dependent biomarkers predicting early onset biochemical recurrence only in African American men. Thus, these ETS dependent biomarkers representing ideal candidates for biomarkers of aggressive disease in this patient population.

Transcriptomic and Clinical Characterization of Neuropeptide Y Expression in Localized and Metastatic Prostate Cancer: Identification of Novel Prostate Cancer Subtype with Clinical Implications

BACKGROUND

Tumor microenvironment and its interaction with neuroendocrine modulators contribute to prostate carcinogenesis and progression.

OBJECTIVE

We sought to define the transcriptomic and clinical implications of neuropeptide Y (NPY) expression in prostate cancer progression.

DESIGN, SETTING, AND PARTICIPANTS

Genome-wide expression profiling of three localized prostate cancer (total n=18818) and five metastatic castrate-resistant prostate cancer (mCRPC; total n=495) cohorts was used to characterize NPY expression. All men underwent radical prostatectomy (RP) for localized prostate cancer.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Patients were grouped into those with low NPY and high NPY based on NPY expression. Associations between these groups and histological, genomic, and clinical outcomes including progression-free survival (PFS) and metastases-free survival (MFS) were examined. Combining ERG-fusion status with NPY expression, four groups were defined (lowNPY/ERG+, lowNPY/ERG-, highNPY/ERG+, and highNPY/ERG-). Cox proportional hazards modeled the time to distant metastasis after RP. Genomic risk scores for metastasis were calculated for prospective samples, based on a 22-gene signature.

RESULTS AND LIMITATIONS

Across cancers, NPY showed the highest expression in prostate cancer in The Cancer Genome Atlas (TCGA) PAN-Cancer cohort (n=9483, p<0.0001). In 17967 prospective samples, low NPY expression was associated with aggressive grade group 5 disease and a higher genomic risk (p<0.0001). In the retrospective (n=355) and TCGA (n=497) cohorts, low NPY was associated with shorter MFS and PFS, respectively (p=0.001 for both). In mCRPC cohorts, low NPY was associated with neuroendocrine development (p<0.01). NPY was highly correlated to ERG; thus, we defined four groups based on NPY expression and ERG fusion. The lowNPY/ERG+ subtype was associated with the highest genomic risk for metastasis (p<0.0001) and the highest rate of metastasis compared with all other subtypes (hazard ratio [HR]: 2.2 [1.22-4.03], p=0.008), while the highNPY/ERG- subtype was associated with the lowest genomic risk for metastasis (p<0.0001) and the lowest rate of metastasis (HR: 0.53 [0.35-0.81], p=0.003).

CONCLUSIONS

Low NPY expression is associated with adverse genomic features and clinical correlates and outcomes. The lowNPY/ERG+ subtype was associated with the highest risk of developing metastasis. Prognostic subgrouping and tailored treatments by NPY expression and ERG fusion status warrant further study.

PATIENT SUMMARY

The low neuropeptide Y prostate cancer subtype appears to be aggressive with a high risk of developing metastasis.

Distinct transcriptional repertoire of the androgen receptor in ETS fusion-negative prostate cancer

Background

Prostate cancer (PCa) tumors harboring translocations of ETS family genes with the androgen responsive TMPRSS2 gene (ETS+ tumors) provide a robust biomarker for detecting PCa in approximately 70% of patients. ETS+ PCa express high levels of the androgen receptor (AR), yet PCa tumors lacking ETS fusions (ETS−) also express AR and demonstrate androgen-regulated growth. In this study, we evaluate the differences in the AR-regulated transcriptomes between ETS+ and ETS− PCa tumors.

Methods

10,608 patient tumors from three independent PCa datasets classified as ETS+ (samples overexpressing ERG or other ETS family members) or ETS− (all other PCa) were analyzed for differential gene expression using false-discovery-rate adjusted methods and gene-set enrichment analysis (GSEA).

Results

Based on the expression of AR-dependent genes and an unsupervised Principal Component Analysis (PCA) model, AR-regulated gene expression alone was able to separate PCa samples into groups based on ETS status in all PCa databases. ETS status distinguished several differentially expressed genes in both TCGA (6.9%) and GRID (6.6%) databases, with 413 genes overlapping in both databases. Importantly, GSEA showed enrichment of distinct androgen-responsive genes in both ETS− and ETS+ tumors, and AR ChIP-seq data identified 131 direct AR-target genes that are regulated in an ETS-specific fashion. Notably, dysregulation of ETS-dependent AR-target genes within the metabolic and non-canonical WNT pathways was associated with clinical outcomes.

Conclusions

ETS status influences the transcriptional repertoire of the AR, and ETS− PCa tumors appear to rely on distinctly different AR-dependent transcriptional programs to drive and sustain tumorigenesis.

ETS2 is a prostate basal cell marker and is highly expressed in prostate cancers aberrantly expressing p63

BACKGROUND

Rare prostate carcinomas aberrantly express p63 and have an immunophenotype intermediate between basal and luminal cells. Here, we performed gene expression profiling on p63-expressing prostatic carcinomas and compared them to usual-type adenocarcinoma. We identify ETS2 as highly expressed in p63-expressing prostatic carcinomas and benign prostate basal cells, with lower expression in luminal cells and primary usual-type adenocarcinomas.

METHODS

A total of 8 p63-expressing prostate carcinomas at radical prostatectomy were compared to 358 usual-type adenocarcinomas by gene expression profiling performed on formalin fixed paraffin embedded tumor tissue using Affymetrix 1.0 ST microarrays. Correlation between differentially expressed genes and TP63 expression was performed in 5239 prostate adenocarcinomas available in the Decipher GRID. For validation, ETS2 in situ hybridization was performed on 19 p63-expressing prostate carcinomas and 30 usual-type adenocarcinomas arrayed on tissue microarrays (TMA).

RESULTS

By gene expression, p63-expressing prostate carcinomas showed low cell cycle activity and low Decipher prognostic scores, but were predicted to have high Gleason grade compared to usual-type adenocarcinomas by gene expression signatures and morphology. Among the genes over-expressed in p63-expressing carcinoma relative to usual-type adenocarcinoma were known p63-regulated genes, along with ETS2, an ETS family member previously implicated as a prostate cancer tumor suppressor gene. Across several cohorts of prostate samples, ETS2 gene expression was correlated with TP63 expression and was significantly higher in benign prostate compared to usual-type adenocarcinoma. By in situ hybridization, ETS2 gene expression was high in benign basal cells, and low to undetectable in benign luminal cells or usual-type adenocarcinoma. In contrast, ETS2 was highly expressed in 95% (18/19) of p63-expressing prostate carcinomas.

CONCLUSIONS

ETS2 is a predominantly basally-expressed gene in the prostate, with low expression in usual-type adenocarcinoma and high expression in p63-expressing carcinomas. Given this pattern, the significance of ETS2 loss by deletion or mutation in usual-type adenocarcinomas is uncertain.