Transcriptomic Heterogeneity of Expansile Cribriform and Other Gleason Pattern 4 Prostate Cancer Subtypes

BACKGROUND

Prostate cancers featuring an expansile cribriform (EC) pattern are associated with worse clinical outcomes following radical prostatectomy (RP). However, studies of the genomic characteristics of Gleason pattern 4 subtypes are limited.

OBJECTIVE

To explore transcriptomic characteristics and heterogeneity within Gleason pattern 4 subtypes (fused/poorly formed, glomeruloid, small cribriform, EC/intraductal carcinoma [IDC]) and the association with biochemical recurrence (BCR)-free survival.

DESIGN, SETTING, AND PARTICIPANTS

This was a retrospective cohort study including 165 men with grade group 2-4 prostate cancer who underwent RP at a single academic institution (2016-2020) and Decipher testing of the RP specimen. Patients with Gleason pattern 5 were excluded. IDC and EC patterns were grouped. Median follow-up was 2.5 yr after RP for patients without BCR.

OUTCOMES MEASUREMENTS AND STATISTICAL ANALYSIS

Prompted by heterogeneity within pattern 4 subtypes identified via exploratory analyses, we investigated transcriptomic consensus clusters using partitioning around medoids and hallmark gene set scores. The primary clinical outcome was BCR, defined as two consecutive prostate-specific antigen measurements >0.2 ng/ml at least 8 wk after RP, or any additional treatment. Multivariable Cox proportional-hazards models were used to determine factors associated with BCR-free survival.

RESULTS AND LIMITATIONS

In this cohort, 99/165 patients (60%) had EC and 67 experienced BCR. Exploratory analyses and clustering demonstrated transcriptomic heterogeneity within each Gleason pattern 4 subtype. In the multivariable model controlled for pattern 4 subtype, margin status, Cancer of the Prostate Risk Assessment Post-Surgical score, and Decipher score, a newly identified steroid hormone-driven cluster (hazard ratio 2.35 95% confidence interval 1.01-5.47) was associated with worse BCR-free survival. The study is limited by intermediate follow-up, no validation cohort, and lack of accounting for intratumoral and intraprostatic heterogeneity.

CONCLUSIONS

Transcriptomic heterogeneity was present within and across each Gleason pattern 4 subtype, demonstrating there is additional biologic diversity not captured by histologic subtypes. This heterogeneity can be used to develop novel signatures and to classify transcriptomic subtypes, which may help in refining risk stratification following RP to further guide decision-making on adjuvant and salvage treatments.

PATIENT SUMMARY

We studied prostatectomy specimens and found that tumors with similar microscopic appearance can have genetic differences that may help to predict outcomes after prostatectomy for prostate cancer. Our results demonstrate that further gene expression analysis of prostate cancer subtypes may improve risk stratification after prostatectomy. Future studies are needed to develop novel gene expression signatures and validate these findings in independent sets of patients.

Single cell-transcriptomic analysis informs the lncRNA landscape in metastatic castration resistant prostate cancer

Metastatic castration-resistant prostate cancer (mCRPC) is a lethal form of prostate cancer. Although long-noncoding RNAs (lncRNAs) have been implicated in mCRPC, past studies have relied on bulk sequencing methods with low depth and lack of single-cell resolution. Hence, we performed a lncRNA-focused analysis of single-cell RNA-sequencing data (n = 14) from mCRPC biopsies followed by integration with bulk multi-omic datasets. This yielded 389 cell-enriched lncRNAs in prostate cancer cells and the tumor microenvironment (TME). These lncRNAs demonstrated enrichment with regulatory elements and exhibited alterations during prostate cancer progression. Prostate-lncRNAs were correlated with AR mutational status and response to treatment with enzalutamide, while TME-lncRNAs were associated with RB1 deletions and poor prognosis. Finally, lncRNAs identified between prostate adenocarcinomas and neuroendocrine tumors exhibited distinct expression and methylation profiles. Our findings demonstrate the ability of single-cell analysis to refine our understanding of lncRNAs in mCRPC and serve as a resource for future mechanistic studies.

Fragmentomic analysis of circulating tumor DNA-targeted cancer panels

BACKGROUND

The isolation of cell-free DNA (cfDNA) from the bloodstream can be used to detect and analyze somatic alterations in circulating tumor DNA (ctDNA), and multiple cfDNA-targeted sequencing panels are now commercially available for Food and Drug Administration (FDA)-approved biomarker indications to guide treatment. More recently, cfDNA fragmentation patterns have emerged as a tool to infer epigenomic and transcriptomic information. However, most of these analyses used whole-genome sequencing, which is insufficient to identify FDA-approved biomarker indications in a cost-effective manner.

PATIENTS AND METHODS

We used machine learning models of fragmentation patterns at the first coding exon in standard targeted cancer gene cfDNA sequencing panels to distinguish between cancer and non-cancer patients, as well as the specific tumor type and subtype. We assessed this approach in two independent cohorts: a published cohort from GRAIL (breast, lung, and prostate cancers, non-cancer, n = 198) and an institutional cohort from the University of Wisconsin (UW; breast, lung, prostate, bladder cancers, n = 320). Each cohort was split 70%/30% into training and validation sets.

RESULTS

In the UW cohort, training cross-validated accuracy was 82.1%, and accuracy in the independent validation cohort was 86.6% despite a median ctDNA fraction of only 0.06. In the GRAIL cohort, to assess how this approach performs in very low ctDNA fractions, training and independent validation were split based on ctDNA fraction. Training cross-validated accuracy was 80.6%, and accuracy in the independent validation cohort was 76.3%. In the validation cohort where the ctDNA fractions were all <0.05 and as low as 0.0003, the cancer versus non-cancer area under the curve was 0.99.

CONCLUSIONS

To our knowledge, this is the first study to demonstrate that sequencing from targeted cfDNA panels can be utilized to analyze fragmentation patterns to classify cancer types, dramatically expanding the potential capabilities of existing clinically used panels at minimal additional cost.

The Genomic and Epigenomic Landscape of Double-Negative Metastatic Prostate Cancer

Systemic targeted therapy in prostate cancer is primarily focused on ablating androgen signaling. Androgen deprivation therapy and second-generation androgen receptor (AR)-targeted therapy selectively favor the development of treatment-resistant subtypes of metastatic castration-resistant prostate cancer (mCRPC), defined by AR and neuroendocrine (NE) markers. Molecular drivers of double-negative (AR-/NE-) mCRPC are poorly defined. In this study, we comprehensively characterized treatment-emergent mCRPC by integrating matched RNA sequencing, whole-genome sequencing, and whole-genome bisulfite sequencing from 210 tumors. AR-/NE- tumors were clinically and molecularly distinct from other mCRPC subtypes, with the shortest survival, amplification of the chromatin remodeler CHD7, and PTEN loss. Methylation changes in CHD7 candidate enhancers were linked to elevated CHD7 expression in AR-/NE+ tumors. Genome-wide methylation analysis nominated Krüppel-like factor 5 (KLF5) as a driver of the AR-/NE- phenotype, and KLF5 activity was linked to RB1 loss. These observations reveal the aggressiveness of AR-/NE- mCRPC and could facilitate the identification of therapeutic targets in this highly aggressive disease.

SIGNIFICANCE

Comprehensive characterization of the five subtypes of metastatic castration-resistant prostate cancer identified transcription factors that drive each subtype and showed that the double-negative subtype has the worst prognosis.

AARDVARK: an automated reversion detector for variants affecting resistance kinetics

SUMMARY

Resistance to two classes of FDA-approved therapies that target DNA repair-deficient tumors is caused by mutations that restore the tumor cell's DNA repair function. Identifying these "reversion" mutations currently requires manual annotation of patient tumor sequence data. Here we present AARDVARK, an R package that automatically identifies reversion mutations from DNA sequence data.

AVAILABILITY AND IMPLEMENTATION

AARDVARK is implemented in R (≥3.5). It is available on GitHub at https://github.com/davidquigley/aardvark. It is licensed under the MIT license.

Reversible epigenetic alterations mediate PSMA expression heterogeneity in advanced metastatic prostate cancer

Prostate-specific membrane antigen (PSMA) is an important cell surface target in prostate cancer. There are limited data on the heterogeneity of PSMA tissue expression in metastatic castration-resistant prostate cancer (mCRPC). Furthermore, the mechanisms regulating PSMA expression (encoded by the FOLH1 gene) are not well understood. Here, we demonstrate that PSMA expression is heterogeneous across different metastatic sites and molecular subtypes of mCRPC. In a rapid autopsy cohort in which multiple metastatic sites per patient were sampled, we found that 13 of 52 (25%) cases had no detectable PSMA and 23 of 52 (44%) cases showed heterogeneous PSMA expression across individual metastases, with 33 (63%) cases harboring at least 1 PSMA-negative site. PSMA-negative tumors displayed distinct transcriptional profiles with expression of druggable targets such as MUC1. Loss of PSMA was associated with epigenetic changes of the FOLH1 locus, including gain of CpG methylation and loss of histone 3 lysine 27 (H3K27) acetylation. Treatment with histone deacetylase (HDAC) inhibitors reversed this epigenetic repression and restored PSMA expression in vitro and in vivo. Collectively, these data provide insights into the expression patterns and regulation of PSMA in mCRPC and suggest that epigenetic therapies - in particular, HDAC inhibitors - can be used to augment PSMA levels.

Intrinsic Molecular Subtypes of Metastatic Castration-Resistant Prostate Cancer

PURPOSE

Although numerous biology-driven subtypes have been described previously in metastatic castration-resistant prostate cancer (mCRPC), unsupervised molecular subtyping based on gene expression has been less studied, especially using large cohorts. Thus, we sought to identify the intrinsic molecular subtypes of mCRPC and assess molecular and clinical correlates in the largest combined cohort of mCRPC samples with gene expression data available to date.

EXPERIMENTAL DESIGN

We combined and batch-effect corrected gene expression data from four mCRPC cohorts from the Fred Hutchinson Cancer Research Center (N = 157), a small-cell neuroendocrine (NE) prostate cancer (SCNC)-enriched cohort from Weill Cornell Medicine (N = 49), and cohorts from the Stand Up 2 Cancer/Prostate Cancer Foundation East Coast Dream Team (N = 266) and the West Coast Dream Team (N = 162).

RESULTS

Hierarchical clustering of RNA-sequencing data from these 634 mCRPC samples identified two distinct adenocarcinoma subtypes, one of which (adeno-immune) was characterized by higher gene expression of immune pathways, higher CIBERSORTx immune scores, diminished ASI benefit, and non-lymph node metastasis tropism compared with an adeno-classic subtype. We also identified two distinct subtypes with enrichment for an NE phenotype, including an NE-liver subgroup characterized by liver metastasis tropism, PTEN loss, and APC and SPOP mutations compared with an NE-classic subgroup.

CONCLUSIONS

Our results emphasize the heterogeneity of mCRPC beyond currently accepted molecular phenotypes, and suggest that future studies should consider incorporating transcriptome-wide profiling to better understand how these differences impact treatment responses and outcomes.

The 5-Hydroxymethylcytosine Landscape of Prostate Cancer

Analysis of DNA methylation is a valuable tool to understand disease progression and is increasingly being used to create diagnostic and prognostic clinical biomarkers. While conversion of cytosine to 5-methylcytosine (5mC) commonly results in transcriptional repression, further conversion to 5-hydroxymethylcytosine (5hmC) is associated with transcriptional activation. Here we perform the first study integrating whole-genome 5hmC with DNA, 5mC, and transcriptome sequencing in clinical samples of benign, localized, and advanced prostate cancer. 5hmC is shown to mark activation of cancer drivers and downstream targets. Furthermore, 5hmC sequencing revealed profoundly altered cell states throughout the disease course, characterized by increased proliferation, oncogenic signaling, dedifferentiation, and lineage plasticity to neuroendocrine and gastrointestinal lineages. Finally, 5hmC sequencing of cell-free DNA from patients with metastatic disease proved useful as a prognostic biomarker able to identify an aggressive subtype of prostate cancer using the genes TOP2A and EZH2, previously only detectable by transcriptomic analysis of solid tumor biopsies. Overall, these findings reveal that 5hmC marks epigenomic activation in prostate cancer and identify hallmarks of prostate cancer progression with potential as biomarkers of aggressive disease.

SIGNIFICANCE

In prostate cancer, 5-hydroxymethylcytosine delineates oncogene activation and stage-specific cell states and can be analyzed in liquid biopsies to detect cancer phenotypes. See related article by Wu and Attard, p. 3880.

Resistance to ATR Inhibitors Is Mediated by Loss of the Nonsense-Mediated Decay Factor UPF2

Significance:

Loss of NMD proteins promotes resistance to ATR inhibitors in gastric cancer cells, which may provide a combination of therapeutic targets and biomarkers to improve the clinical utility of these drugs.

Transcriptional profiling of matched patient biopsies clarifies molecular determinants of enzalutamide-induced lineage plasticity

The androgen receptor (AR) signaling inhibitor enzalutamide (enza) is one of the principal treatments for metastatic castration-resistant prostate cancer (CRPC). Several emergent enza clinical resistance mechanisms have been described, including lineage plasticity in which the tumors manifest reduced dependency on the AR. To improve our understanding of enza resistance, herein we analyze the transcriptomes of matched biopsies from men with metastatic CRPC obtained prior to treatment and at progression (n = 21). RNA-sequencing analysis demonstrates that enza does not induce marked, sustained changes in the tumor transcriptome in most patients. However, three patients' progression biopsies show evidence of lineage plasticity. The transcription factor E2F1 and pathways linked to tumor stemness are highly activated in baseline biopsies from patients whose tumors undergo lineage plasticity. We find a gene signature enriched in these baseline biopsies that is strongly associated with poor survival in independent patient cohorts and with risk of castration-induced lineage plasticity in patient-derived xenograft models, suggesting that tumors harboring this gene expression program may be at particular risk for resistance mediated by lineage plasticity and poor outcomes.

Why ARNT Prostate Tumors Responding to Enzalutamide?

SUMMARY

Prostate tumors can develop resistance to androgen receptor (AR)-targeted therapies through treatment-induced changes in transcription factor activity that promote transcriptional and morphologic features of a neuroendocrine lineage. This study identifies an unexpected role for the circadian protein ARNTL in resistance to enzalutamide, a second-generation AR-targeted therapy. See related article by Linder et al., p. 2074 (4).

Deep whole-genome ctDNA chronology of treatment-resistant prostate cancer

Circulating tumour DNA (ctDNA) in blood plasma is an emerging tool for clinical cancer genotyping and longitudinal disease monitoring¹. However, owing to past emphasis on targeted and low-resolution profiling approaches, our understanding of the distinct populations that comprise bulk ctDNA is incomplete^2-12. Here we perform deep whole-genome sequencing of serial plasma and synchronous metastases in patients with aggressive prostate cancer. We comprehensively assess all classes of genomic alterations and show that ctDNA contains multiple dominant populations, the evolutionary histories of which frequently indicate whole-genome doubling and shifts in mutational processes. Although tissue and ctDNA showed concordant clonally expanded cancer driver alterations, most individual metastases contributed only a minor share of total ctDNA. By comparing serial ctDNA before and after clinical progression on potent inhibitors of the androgen receptor (AR) pathway, we reveal population restructuring converging solely on AR augmentation as the dominant genomic driver of acquired treatment resistance. Finally, we leverage nucleosome footprints in ctDNA to infer mRNA expression in synchronously biopsied metastases, including treatment-induced changes in AR transcription factor signalling activity. Our results provide insights into cancer biology and show that liquid biopsy can be used as a tool for comprehensive multi-omic discovery.

Abstract 3625: Clonal architecture and evolution of treatment-resistant prostate cancer via deep whole-genome ctDNA sequencing

Background: Circulating tumor DNA (ctDNA) in blood plasma is an emerging tool for clinical cancer genotyping and longitudinal disease monitoring. However, integration of ctDNA tests into clinical management is critically impeded by the poor understanding of the distinct somatic populations comprising bulk ctDNA—including their relationship to synchronous metastatic tissue, and their temporal dynamics during standard-of-care treatment. Prior approaches relying on targeted and/or low-resolution techniques (e.g. targeted exon sequencing, low-pass (shallow) whole-genome sequencing; WGS) do not permit comprehensive dissection of clonal architecture and unbiased analysis of putative resistance mechanisms.

Methods: We performed deep WGS on serial plasma ctDNA (median depth: 185×) and synchronous metastatic tissue biopsies with high tumor purity from 35 patients with metastatic castration-resistant prostate cancer. We developed a subclonal reconstruction algorithm optimized for our data enabling resolution of per-patient evolutionary histories and ctDNA clonal composition. ctDNA nucleosome footprinting was used to infer mRNA abundance in synchronously biopsied metastases and androgen receptor (AR) transcription factor activity at 3224 AR binding sites (ARBS).

Results: We comprehensively assess all classes of genomic alterations and demonstrate that ctDNA harbors greater populational heterogeneity than metastatic tissue (p&lt;0.001). The evolutionary histories of ctDNA populations indicate frequent whole-genome doubling and attenuation of C&gt;T aging-associated mutation signature during subclonal differentiation. Although driver alterations were largely concordant between tissue and ctDNA, each individual metastasis contributed only a minor share of total ctDNA (average ctDNA contribution: 17%). By comparing serial ctDNA before and after clinical progression on potent AR pathway inhibitors, we reveal population restructuring converging solely on AR copy augmentation as the dominant genomic driver of acquired treatment-resistance. Nucleosome depletion at transcription start-sites is highly correlated with same-patient metastatic tissue mRNA abundance, indicating that ctDNA fragmentomics can recapitulate transcriptomic patterns in metastatic lesions. Most ctDNA samples exhibited strong ARBS nucleosome depletion which correlated with AR gene copy number (R=0.36, p=0.003). Finally, serial ctDNA nucleosome profiling at ARBS revealed adaptive transcriptomic resistance to AR pathway inhibitors, including lineage switch to a neuroendocrine-like (AR-low) state.

Conclusions: We show that the populations comprising ctDNA are typically complex and more heterogeneous than those found in bulk WGS of a synchronous metastasis. Our work advocates for liquid biopsy as a comprehensive multi-omic discovery tool for cancers with high ctDNA fractions.

Citation Format: Cameron Herberts, Matti Annala, Joonatan Sipola, Sarah W. Ng, Xinyi E. Chen, Anssi Nurminen, Olga Korhonen, Aslı D. Munzur, Kevin Beja, Elena Schönlau, Cecily Q. Bernales, Elie Ritch, Jack V. Bacon, Nathan A. Lack, Matti Nykter, Rahul Aggarwal, Eric J. Small, Martin E. Gleave, David A. Quigley, Felix Y. Feng, Kim N. Chi, Alexander W. Wyatt. Clonal architecture and evolution of treatment-resistant prostate cancer via deep whole-genome ctDNA sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3625.

Clinical and molecular features of low prostate-specific membrane antigen (PSMA) expression in patients (pts) with metastatic castration resistant prostate cancer (mCRPC)

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Background: Low PSMA uptake on positron-emission tomography is seen in up to 30% of mCRPC pts and represents a clinically distinct subgroup with adverse outcomes. We assessed transcriptional and clinical features associated with low PSMA ( FOLH1) gene expression in mCRPC. Methods: A retrospective analysis of mCRPC biopsy samples with RNA-seq data was undertaken. Normalized FOLH1 expression was compared across histologic subtypes and sites of disease. We assessed the association between FOLH1 expression, selected androgen receptor (AR) target genes, master regulators of neuroendocrine differentiation, and previously validated AR activity and treatment-associated small cell neuroendocrine carcinoma (t-SCNC) transcriptional signature scores using Pearson correlations. Associations between FOLH1 and both PSA50 response to subsequent AR-targeted therapy and overall survival (OS) were examined by logistic regression and Cox proportional hazard models, respectively. Results: Samples from 97 pts were identified, of which 18% harbored t-SCNC histology. 45% of pts had visceral metastases at the time of biopsy, and 41% received subsequent AR-targeted therapy. Median FOLH1 expression was lower in pts with visceral metastases vs no visceral metastases (14.7 vs 15.6, p = 0.02) but was not significantly different across t-SCNC vs adenocarcinoma biopsies (14.3 vs 15.4, p = 0.13). FOLH1 expression was positively correlated with AR transcriptional activity and AR target genes, and negatively correlated with master regulators of neuroendocrine differentiation and t-SCNC transcriptional signature scores (Table). Low FOLH1 expression did not predict PSA50 response to subsequent AR-targeted therapy (OR 0.97, p = 0.8), but was associated with shorter OS on univariate analysis (HR 1.09, 95% CI 1.02-1.16, p=0.01). A post-hoc analysis revealed a trend towards decreased median OS in pts with FOLH1 expression <12 (7.5 vs 17.1 months, log-rank p = 0.06). Conclusions: In this retrospective analysis of mCRPC pts, low FOLH1 expression was associated with transcriptional features of t-SCNC, decreased AR activity, and shorter OS. These findings are hypothesis-generating and prospective validation is needed.[Table: see text]

Prognosis Associated With Luminal and Basal Subtypes of Metastatic Prostate Cancer

Importance

Luminal and basal subtypes of primary prostate cancer have been shown to be molecularly distinct and clinically important in predicting response to therapy. These subtypes have not been described in metastatic prostate cancer.

Objectives

To identify clinical and molecular correlates of luminal and basal subtypes in metastatic castration-resistant prostate cancer (mCRPC) and investigate differences in survival, particularly after treatment with androgen-signaling inhibitors (ASIs).

Design, Setting, and Participants

In this cohort study, a retrospective analysis was conducted of 4 cohorts with mCRPC (N = 634) across multiple academic centers. Treatment was at the physicians' discretion. Details of the study cohorts have been published elsewhere between 2016 and 2019. Data were analyzed from March 2018 to February 2021.

Main Outcomes and Measures

The primary clinical end point was overall survival from the date of tissue biopsy/molecular profiling. Luminal and basal subtypes were also stratified by postbiopsy ASI treatment. The primary molecular analyses included associations with small cell/neuroendocrine prostate cancer (SCNC), molecular pathways, and DNA alterations.

Results

In the 634 patients, 288 (45%) had tumors classified as luminal, and 346 (55%) had tumors classified as basal. However, 53 of 59 (90%) SCNC tumors were basal (P < .001). Similar to primary prostate cancer, luminal tumors exhibited overexpression of AR pathway genes. In basal tumors, a significantly higher rate of RB1 loss (23% basal vs 4% luminal; P < .001), FOXA1 alterations (36% basal vs 27% luminal; P = .03) and MYC alterations (73% basal vs 56% luminal; P < .001) were identified. Patients with basal tumors had worse overall survival compared with those with luminal tumors only in patients treated with an ASI postbiopsy (East Coast Dream Team: hazard ratio [HR], 0.39; 95% CI, 0.20-0.74; P = .004; West Coast Dream Team: HR, 0.57; 95% CI, 0.33-0.97; P = .04). Among patients with luminal tumors, those treated with an ASI had significantly better survival (HR, 0.27; 95% CI, 0.14-0.53; P < .001), whereas patients with basal tumors did not (HR, 0.62; 95% CI, 0.36-1.04, P = .07). The interaction term between subtype and ASI treatment was statistically significant (HR, 0.42; 95% CI, 0.20-0.89; P = .02).

Conclusions and Relevance

These findings represent the largest integrated clinical, transcriptomic, and genomic analysis of mCRPC samples to date, and suggest that mCRPC can be classified as luminal and basal tumors. Analogous to primary prostate cancer, these data suggest that the benefit of ASI treatment is more pronounced in luminal tumors and support the use of ASIs in this population. In the basal tumors, a chemotherapeutic approach could be considered in some patients given the similarity to SCNC and the diminished benefit of ASI therapy. Further validation in prospective clinical trials is warranted.

Predicting cancer drug TARGETS - TreAtment Response Generalized Elastic-neT Signatures

We are now in an era of molecular medicine, where specific DNA alterations can be used to identify patients who will respond to specific drugs. However, there are only a handful of clinically used predictive biomarkers in oncology. Herein, we describe an approach utilizing in vitro DNA and RNA sequencing and drug response data to create TreAtment Response Generalized Elastic-neT Signatures (TARGETS). We trained TARGETS drug response models using Elastic-Net regression in the publicly available Genomics of Drug Sensitivity in Cancer (GDSC) database. Models were then validated on additional in-vitro data from the Cancer Cell Line Encyclopedia (CCLE), and on clinical samples from The Cancer Genome Atlas (TCGA) and Stand Up to Cancer/Prostate Cancer Foundation West Coast Prostate Cancer Dream Team (WCDT). First, we demonstrated that all TARGETS models successfully predicted treatment response in the separate in-vitro CCLE treatment response dataset. Next, we evaluated all FDA-approved biomarker-based cancer drug indications in TCGA and demonstrated that TARGETS predictions were concordant with established clinical indications. Finally, we performed independent clinical validation in the WCDT and found that the TARGETS AR signaling inhibitors (ARSI) signature successfully predicted clinical treatment response in metastatic castration-resistant prostate cancer with a statistically significant interaction between the TARGETS score and PSA response (p = 0.0252). TARGETS represents a pan-cancer, platform-independent approach to predict response to oncologic therapies and could be used as a tool to better select patients for existing therapies as well as identify new indications for testing in prospective clinical trials.

Circadian PERformance in breast cancer: a germline and somatic genetic study of PER3VNTR polymorphisms and gene co-expression

Polymorphisms in the PER3 gene have been associated with several human disease phenotypes, including sleep disorders and cancer. In particular, the long allele of a variable number of tandem repeat (VNTR) polymorphism has been previously linked to an increased risk of breast cancer. Here we carried out a combined germline and somatic genetic analysis of the role of the PER3^VNRT polymorphism in breast cancer. The combined data from 8284 individuals showed a non-significant trend towards increased breast cancer risk in the 5-repeat allele homozygous carriers (OR = 1.17, 95% CI: 0.97–1.42). We observed allelic imbalance at the PER3 locus in matched blood and tumor DNA samples, showing a significant retention of the long variant (risk) allele in tumor samples, and a preferential loss of the short repetition allele (p = 0.0005). Gene co-expression analysis in healthy and tumoral breast tissue samples uncovered significant associations between PER3 expression levels with those from genes which belong to several cancer-associated pathways. Finally, relapse-free survival (RFS) analysis showed that low expression levels of PER3 were linked to a significant lower RSF in luminal A (p = 3 × 10⁻¹²) but not in the rest of breast cancer subtypes.

An integrated functional and clinical genomics approach reveals genes driving aggressive metastatic prostate cancer

Genomic sequencing of thousands of tumors has revealed many genes associated with specific types of cancer. Similarly, large scale CRISPR functional genomics efforts have mapped genes required for cancer cell proliferation or survival in hundreds of cell lines. Despite this, for specific disease subtypes, such as metastatic prostate cancer, there are likely a number of undiscovered tumor specific driver genes that may represent potential drug targets. To identify such genetic dependencies, we performed genome-scale CRISPRi screens in metastatic prostate cancer models. We then created a pipeline in which we integrated pan-cancer functional genomics data with our metastatic prostate cancer functional and clinical genomics data to identify genes that can drive aggressive prostate cancer phenotypes. Our integrative analysis of these data reveals known prostate cancer specific driver genes, such as AR and HOXB13, as well as a number of top hits that are poorly characterized. In this study we highlight the strength of an integrated clinical and functional genomics pipeline and focus on two top hit genes, KIF4A and WDR62. We demonstrate that both KIF4A and WDR62 drive aggressive prostate cancer phenotypes in vitro and in vivo in multiple models, irrespective of AR-status, and are also associated with poor patient outcome.

CRISPRi screens reveal a DNA methylation-mediated 3D genome dependent causal mechanism in prostate cancer

Prostate cancer (PCa) risk-associated SNPs are enriched in noncoding cis-regulatory elements (rCREs), yet their modi operandi and clinical impact remain elusive. Here, we perform CRISPRi screens of 260 rCREs in PCa cell lines. We find that rCREs harboring high risk SNPs are more essential for cell proliferation and H3K27ac occupancy is a strong indicator of essentiality. We also show that cell-line-specific essential rCREs are enriched in the 8q24.21 region, with the rs11986220-containing rCRE regulating MYC and PVT1 expression, cell proliferation and tumorigenesis in a cell-line-specific manner, depending on DNA methylation-orchestrated occupancy of a CTCF binding site in between this rCRE and the MYC promoter. We demonstrate that CTCF deposition at this site as measured by DNA methylation level is highly variable in prostate specimens, and observe the MYC eQTL in the 8q24.21 locus in individuals with low CTCF binding. Together our findings highlight a causal mechanism synergistically driven by a risk SNP and DNA methylation-mediated 3D genome architecture, advocating for the integration of genetics and epigenetics in assessing risks conferred by genetic predispositions.

5-hydroxymethylcytosine as a liquid biopsy biomarker in mCRPC

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Background: 5-hydroxymethylcytosine (5hmC) is an epigenetic modification which regulates gene expression and is associated with active transcription. The optimization of 5hmC sequencing in cell-free DNA (cfDNA) could therefore enable assessment of gene activity through a liquid biopsy. We aimed to investigate the 5hmC landscape of metastatic castration-resistant prostate cancer (mCRPC) and to evaluate the potential of 5hmC modifications in cfDNA as biomarkers of outcome in mCRPC patients. Methods: Genome-wide 5hmC modifications were analyzed with a low-input whole-genome 5hmC sequencing method based on selective chemical labeling in DNA from 93 mCRPC tissue biopsies previously profiled with whole-genome sequencing (WGS), RNA-sequencing and whole-genome bisulfite sequencing (WGBS). In addition, we analyzed 64 cell-free DNA (cfDNA) samples, from men with mCRPC before first-line abiraterone or enzalutamide, with both 5hmC sequencing and a conventional targeted ctDNA panel assessing common genomic alterations. Results: In mCRPC tissue samples, 5hmC enrichment was more strongly associated with gene expression than promoter methylation or copy number. Among cancer hallmark pathways, the androgen response genes had the strongest association between 5hmC and gene expression, suggesting a disease specific marking of gene activation. 5hmC patterns in cfDNA could be used to estimate the circulating tumor DNA fraction (ct-fraction), which was prognostic for overall survival (tertiles of ct-fraction, HR = 1.6 95%CI 1.1-2.3, p = 0.007). Further, 5hmC levels were indicative of gain of oncogene activity (such as AR, MYC, and PIK3CA) and loss of tumor suppressor gene activity (such as RB1, TP53 and BRCA2). The number of alterations, by 5hmC levels, of common drivers of mCRPC was prognostic for overall survival, also after adjusting for ct-fraction (adjusted p = 0.00001), and the prognostic value of common alterations detected by 5hmC sequencing versus conventional targeted ctDNA sequencing was similar. Finally, 5hmC levels in cfDNA of genes not significantly altered by copy number gain or loss (and thus not routinely included in targeted ctDNA sequencing assays), such as TOP2A and EZH2, identified a high-risk subgroup of mCRPC, which was highly prognostic for overall survival independent of ct-fraction (adjusted HR = 1.8 95%CI 1.2-2.8, p = 0.007). Conclusions: 5hmC in mCRPC tissue demonstrated an association with gene expression that was highest for prostate cancer driver genes, highlighting the ability to track disease-specific biology. 5hmC in cfDNA from men with mCRPC can be used to estimate the ct-fraction of the sample, infer activity gain and loss of common drivers of mCRPC, and identify high-risk groups of mCRPC based on alterations not commonly detected with conventional ctDNA sequencing, showing its potential as a liquid biomarker. Further studies are aimed at optimizing and validating 5hmC-based biomarkers in larger cohorts.

Autoantibody Landscape in Patients with Advanced Prostate Cancer

PURPOSE

Autoantibody responses in cancer are of great interest, as they may be concordant with T-cell responses to cancer antigens or predictive of response to cancer immunotherapies. Thus, we sought to characterize the antibody landscape of metastatic castration-resistant prostate cancer (mCRPC).

EXPERIMENTAL DESIGN

Serum antibody epitope repertoire analysis (SERA) was performed on patient serum to identify tumor-specific neoepitopes. Somatic mutation-specific neoepitopes were investigated by associating serum epitope enrichment scores with whole-genome sequencing results from paired solid tumor metastasis biopsies and germline blood samples. A protein-based immunome-wide association study (PIWAS) was performed to identify significantly enriched epitopes, and candidate serum antibodies enriched in select patients were validated by ELISA profiling. A distinct cohort of patients with melanoma was evaluated to validate the top cancer-specific epitopes.

RESULTS

SERA was performed on 1,229 serum samples obtained from 72 men with mCRPC and 1,157 healthy control patients. Twenty-nine of 6,636 somatic mutations (0.44%) were associated with an antibody response specific to the mutated peptide. PIWAS analyses identified motifs in 11 proteins, including NY-ESO-1 and HERVK-113, as immunogenic in mCRPC, and ELISA confirmed serum antibody enrichment in candidate patients. Confirmatory PIWAS, Identifying Motifs Using Next-generation sequencing Experiments (IMUNE), and ELISA analyses performed on serum samples from 106 patients with melanoma similarly revealed enriched cancer-specific antibody responses to NY-ESO-1.

CONCLUSIONS

We present the first large-scale profiling of autoantibodies in advanced prostate cancer, utilizing a new antibody profiling approach to reveal novel cancer-specific antigens and epitopes. Our study recovers antigens of known importance and identifies novel tumor-specific epitopes of translational interest.

SV-HotSpot: detection and visualization of hotspots targeted by structural variants associated with gene expression

Whole genome sequencing (WGS) has enabled the discovery of genomic structural variants (SVs), including those targeting intergenic and intronic non-coding regions that eluded previous exome focused strategies. However, the field currently lacks an automated tool that analyzes SV candidates to identify recurrent SVs and their targeted sites (hotspot regions), visualizes these genomic events within the context of various functional elements, and evaluates their potential effect on gene expression. To address this, we developed SV-HotSpot, an automated tool that integrates SV candidates, copy number alterations, gene expression, and genome annotations (e.g. gene and regulatory elements) to discover, annotate, and visualize recurrent SVs and their targeted hotspot regions that may affect gene expression. We applied SV-HotSpot to WGS and matched transcriptome data from metastatic castration resistant prostate cancer patients and rediscovered recurrent SVs targeting coding and non-coding functional elements known to promote prostate cancer progression and metastasis. SV-HotSpot provides a valuable resource to integrate SVs, gene expression, and genome annotations for discovering biologically relevant SVs altering coding and non-coding genome. SV-HotSpot is available at https://github.com/ChrisMaherLab/SV-HotSpot .

Copy Number Loss of 17q22 Is Associated with Enzalutamide Resistance and Poor Prognosis in Metastatic Castration-Resistant Prostate Cancer

PURPOSE

The purpose of this study was to measure genomic changes that emerge with enzalutamide treatment using analyses of whole-genome sequencing and RNA sequencing.

EXPERIMENTAL DESIGN

One hundred and one tumors from men with metastatic castration-resistant prostate cancer (mCRPC) who had not been treated with enzalutamide (n = 64) or who had enzalutamide-resistant mCRPC (n = 37) underwent whole genome sequencing. Ninety-nine of these tumors also underwent RNA sequencing. We analyzed the genomes and transcriptomes of these mCRPC tumors.

RESULTS

Copy number loss was more common than gain in enzalutamide-resistant tumors. Specially, we identified 124 protein-coding genes that were more commonly lost in enzalutamide-resistant samples. These 124 genes included eight putative tumor suppressors located at nine distinct genomic regions. We demonstrated that focal deletion of the 17q22 locus that includes RNF43 and SRSF1 was not present in any patient with enzalutamide-naïve mCRPC but was present in 16% (6/37) of patients with enzalutamide-resistant mCRPC. 17q22 loss was associated with lower RNF43 and SRSF1 expression and poor overall survival from time of biopsy [median overall survival of 19.3 months in 17q22 intact vs. 8.9 months in 17q22 loss, HR, 3.44 95% confidence interval (CI), 1.338-8.867, log-rank P = 0.006]. Finally, 17q22 loss was linked with activation of several targetable factors, including CDK1/2, Akt, and PLK1, demonstrating the potential therapeutic relevance of 17q22 loss in mCRPC.

CONCLUSIONS

Copy number loss is common in enzalutamide-resistant tumors. Focal deletion of chromosome 17q22 defines a previously unappreciated molecular subset of enzalutamide-resistant mCRPC associated with poor clinical outcome.

The DNA methylation landscape of advanced prostate cancer

Although DNA methylation is a key regulator of gene expression, the comprehensive methylation landscape of metastatic cancer has never been defined. Through whole-genome bisulfite sequencing paired with deep whole-genome and transcriptome sequencing of 100 castration-resistant prostate metastases, we discovered alterations affecting driver genes only detectable with integrated whole-genome approaches. Notably, we observed that 22% of tumors exhibited a novel epigenomic subtype associated with hyper-methylation and somatic mutations in TET2, DNMT3B, IDH1, and BRAF. We also identified intergenic regions where methylation is associated with RNA expression of the oncogenic driver genes AR, MYC and ERG. Finally, we showed that differential methylation during progression preferentially occurs at somatic mutational hotspots and putative regulatory regions. This study is a large integrated study of whole-genome, whole-methylome and whole-transcriptome sequencing in metastatic cancer and provides a comprehensive overview of the important regulatory role of methylation in metastatic castration-resistant prostate cancer.

The comprehensive methylation landscape of metastatic castration-resistant prostate cancer (mCRPC) identifies new phenotypic subtypes: Results from the West Coast Prostate Cancer Dream Team (WCDT)

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Background: While recent studies have delineated the genomic landscape of mCRPC, its epigenomic landscape has not been as well characterized. The goal of this study was to define the comprehensive methylation landscape of mCRPC. Methods: mCRPC patients (pts) underwent a metastasis biopsy as part of a multi-institutional study (NCT02432001). Deep whole-genome bisulfite sequencing (mean depth 46x) was performed on fresh frozen tissue from 100 mCRPC patients; data was paired with deep whole-genome and transcriptome sequencing from the same samples. Unbiased hierarchical clustering of the mCRPC methylome was undertaken, and the survival of patients in each cluster was calculated using the Kaplan Meier method. Results: Unbiased hierarchical clustering revealed several distinct subtypes. 22% of mCRPC samples exhibited a novel epigenomic subtype associated with hyper-methylation. This hypermethylated (HM) cluster was significantly associated with somatic mutations in genes known to be involved in methylation, eg TET2 and DNMT3B, as well as in genes in which mutations have been associated with hyper-methylation in other cancer types ( IDH1 in glioblastoma and BRAF in colon cancer). mCRPC survival was 56.1 mos in pts with HM cancers compared to 35.6 mos in non-HM (p = .055). Methylome clustering also identified a unique cluster comprised of all patients with treatment-induced small cell/neuroendocrine cancer, a subtype previously associated with poor survival. Conclusions: This integrated study of whole-genome, whole methylome and whole-transcriptome sequencing provides the first comprehensive overview of the important regulatory role of methylation in metastatic castration-resistant prostate cancer, and has identified at least two distinct subtypes. The clinical and therapeutic implications of methylation subtypes should be explored in future studies. Clinical trial information: NCT02432001 .

An integrated molecular profile of endometrioid ovarian cancer

OBJECTIVE

Endometrioid ovarian carcinoma (EOVC) is an uncommon subtype of epithelial ovarian carcinoma and its molecular characteristics have been incompletely described. Prior sequencing investigations have been limited to targeted gene panels. We performed whole-exome sequencing to build an unbiased genetic profile of molecular alterations in endometrioid ovarian tumors with a goal to better understand this disease in the context of epithelial ovarian cancer and endometrioid uterine cancers.

METHODS

Whole-exome sequencing was performed on EOVC samples (n = 26) and matched normals (n = 15). Gene mutations, mutational signatures and copy number variations (CNVs) informed a multi-dimensional regression classifier allowing for comparison to endometrial carcinoma (UCEC) and high grade serous ovarian carcinoma (HGSC).

RESULTS

EOVC has a distinct and heterogeneous genomic profile. Identified significantly mutated genes in EOVC (PTEN, CTNNB1, PIK3CA, KMT2D, KMT2B, PIK3R1, ARID1A and TP53) occurred at similar frequencies in UCEC. Hypermutation, resulting from both mismatch repair deficiency (MMRd) and POLE mutation, was observed in EOVC at a frequency similar to UCEC. Like UCEC, a subset of EOVC cases closely resembled HGSC, harboring TP53 mutations, homologous recombination deficiency (HRd) mutation signatures and widespread CNVs. A machine-learning classifier confirmed the heterogeneous composition of EOVC. Potential therapeutic targets were identified in 62% of EOVC cases. We validated our findings in an orthogonal clinical sequencing registry of EOVC cases.

CONCLUSIONS

We identified that EOVC are a molecularly heterogeneous group of epithelial ovarian cancers with distinct mutational signatures. In an age of precision oncology, there is a pressing need to understand the unique molecular drivers in uncommon histologic subtypes to facilitate genomically driven oncologic treatments.

ADRB2 expression in progressive metastatic castration-resistant prostate cancer

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Background: The net oncogenic effect of the G protein-coupled receptor β2 adrenergic receptor ADRB2, which may induce neuroendocrine differentiation via cyclic AMP and protein kinase A and whose expression is epigenetically regulated by EZH2, is controversial. ADRB2 expression and associated clinical outcomes in metastatic castration-resistant prostate cancer (mCRPC) are unknown. Methods: This was a retrospective analysis of a cohort of men with mCRPC who were prospectively enrolled in the multi-center SU2C/PCF/AACR West Coast Prostate Cancer Dream Team study, in which biopsies of a metastatic site were obtained at disease progression. Specimens underwent laser capture microdissection and RNA-seq. ADRB2 expression was stratified by histology and transcriptional cluster based on prior unsupervised hierarchical transcriptome clustering, and correlated with EZH2 expression. ADRB2 expression (lowest quartile) was correlated with OS from time of biopsy by log rank test and a multivariable Cox proportional hazard model. Results: One-hundred and twenty-seven men with progressive mCRPC underwent metastatic biopsies and had sufficient tumor for RNA-seq. ADRB2 expression was lowest in the small cell-enriched transcriptional cluster (P<0.001), and correlated inversely with EZH2 expression (r=-0.28, P<0.01). Men with low ADRB2 expression had a shorter median OS than those with high (9.5 vs 18.9 mo, P=0.02). In multivariable analysis adjusting for small cell histology, performance status, LDH, and visceral metastases, high ADRB2 expression was associated with a trend towards longer OS (HR=0.65, 95% CI 0.41-1.02, P=0.06). Conclusions: Low ADRB2 expression is associated with worse OS in men with progressive mCRPC, and may be a means by which EZH2 confers resistance to antiandrogen therapy. Indirect ADRB2 stimulation with EZH2 inhibitors may improve outcomes. Validation in independent cohorts is necessary.

Prostate cancer research: The next generation; report from the 2019 Coffey-Holden Prostate Cancer Academy Meeting

INTRODUCTION

The 2019 Coffey-Holden Prostate Cancer Academy (CHPCA) Meeting, "Prostate Cancer Research: The Next Generation," was held 20 to 23 June, 2019, in Los Angeles, California.

METHODS

The CHPCA Meeting is an annual conference held by the Prostate Cancer Foundation, that is uniquely structured to stimulate intense discussion surrounding topics most critical to accelerating prostate cancer research and the discovery of new life-extending treatments for patients. The 7th Annual CHPCA Meeting was attended by 86 investigators and concentrated on many of the most promising new treatment opportunities and next-generation research technologies.

RESULTS

The topics of focus at the meeting included: new treatment strategies and novel agents for targeted therapies and precision medicine, new treatment strategies that may synergize with checkpoint immunotherapy, next-generation technologies that visualize tumor microenvironment (TME) and molecular pathology in situ, multi-omics and tumor heterogeneity using single cells, 3D and TME models, and the role of extracellular vesicles in cancer and their potential as biomarkers.

DISCUSSION

This meeting report provides a comprehensive summary of the talks and discussions held at the 2019 CHPCA Meeting, for the purpose of globally disseminating this knowledge and ultimately accelerating new treatments and diagnostics for patients with prostate cancer.

Diverse AR Gene Rearrangements Mediate Resistance to Androgen Receptor Inhibitors in Metastatic Prostate Cancer

PURPOSE

Prostate cancer is the second leading cause of male cancer deaths. Castration-resistant prostate cancer (CRPC) is a lethal stage of the disease that emerges when endocrine therapies are no longer effective at suppressing activity of the androgen receptor (AR) transcription factor. The purpose of this study was to identify genomic mechanisms that contribute to the development and progression of CRPC.

EXPERIMENTAL DESIGN

We used whole-genome and targeted DNA-sequencing approaches to identify mechanisms underlying CRPC in an aggregate cohort of 272 prostate cancer patients. We analyzed structural rearrangements at the genome-wide level and carried out a detailed structural rearrangement analysis of the AR locus. We used genome engineering to perform experimental modeling of AR gene rearrangements and long-read RNA sequencing to analyze effects on expression of AR and truncated AR variants (AR-V).

RESULTS

AR was among the most frequently rearranged genes in CRPC tumors. AR gene rearrangements promoted expression of diverse AR-V species. AR gene rearrangements occurring in the context of AR amplification correlated with AR overexpression. Cell lines with experimentally derived AR gene rearrangements displayed high expression of tumor-specific AR-Vs and were resistant to endocrine therapies, including the AR antagonist enzalutamide.

CONCLUSIONS

AR gene rearrangements are an important mechanism of resistance to endocrine therapies in CRPC.

Genomic Drivers of Poor Prognosis and Enzalutamide Resistance in Metastatic Castration-resistant Prostate Cancer

BACKGROUND

Metastatic castration-resistant prostate cancer (mCRPC) is the lethal form of the disease. Several recent studies have identified genomic alterations in mCRPC, but the clinical implications of these genomic alterations have not been fully elucidated.

OBJECTIVE

To use whole-genome sequencing (WGS) to assess the association between key driver gene alterations and overall survival (OS), and to use whole-transcriptome RNA sequencing to identify genomic drivers of enzalutamide resistance.

DESIGN, SETTING, AND PARTICIPANTS

We performed survival analyses and gene set enrichment analysis (GSEA) on WGS and RNA sequencing results for a cohort of 101 mCRPC patients.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

OS was the clinical endpoint for all univariate and multivariable survival analyses. Candidate drivers of enzalutamide resistance were identified in an unbiased manner, and mutations of the top candidate were further assessed for enrichment among enzalutamide-resistant patients using Fisher's exact test.

RESULTS AND LIMITATIONS

Harboring two DNA alterations in RB1 was independently predictive of poor OS (median 14.1 vs 42.0mo; p=0.007) for men with mCRPC. GSEA identified the Wnt/β-catenin pathway as the top differentially modulated pathway among enzalutamide-resistant patients. Furthermore, β-catenin mutations were exclusive to enzalutamide-resistant patients (p=0.01) and independently predictive of poor OS (median 13.6 vs 41.7mo; p=0.025).

CONCLUSIONS

The presence of two RB1 DNA alterations identified in our WGS analysis was independently associated with poor OS among men with mCRPC. The Wnt/β-catenin pathway plays an important role in enzalutamide resistance, with differential pathway expression and enrichment of β-catenin mutations in enzalutamide-resistant patients. Moreover, β-catenin mutations were predictive of poor OS in our cohort.

PATIENT SUMMARY

We observed a correlation between genomic findings for biopsy samples from metastases from men with metastatic castration-resistant prostate cancer (mCRPC) and clinical outcomes. This work sheds new light on clinically relevant genomic alterations in mCRPC and provides a roadmap for the development of new personalized treatment regimens in mCRPC.

A single H/ACA small nucleolar RNA mediates tumor suppression downstream of oncogenic RAS

Small nucleolar RNAs (snoRNAs) are a diverse group of non-coding RNAs that direct chemical modifications at specific residues on other RNA molecules, primarily on ribosomal RNA (rRNA). SnoRNAs are altered in several cancers; however, their role in cell homeostasis as well as in cellular transformation remains poorly explored. Here, we show that specific subsets of snoRNAs are differentially regulated during the earliest cellular response to oncogenic RAS^G12V expression. We describe a novel function for one H/ACA snoRNA, SNORA24, which guides two pseudouridine modifications within the small ribosomal subunit, in RAS-induced senescence in vivo. We find that in mouse models, loss of Snora24 cooperates with RAS^G12V to promote the development of liver cancer that closely resembles human steatohepatitic hepatocellular carcinoma (HCC). From a clinical perspective, we further show that human HCCs with low SNORA24 expression display increased lipid content and are associated with poor patient survival. We next asked whether ribosomes lacking SNORA24-guided pseudouridine modifications on 18S rRNA have alterations in their biophysical properties. Single-molecule Fluorescence Resonance Energy Transfer (FRET) analyses revealed that these ribosomes exhibit perturbations in aminoacyl-transfer RNA (aa-tRNA) selection and altered pre-translocation ribosome complex dynamics. Furthermore, we find that HCC cells lacking SNORA24-guided pseudouridine modifications have increased translational miscoding and stop codon readthrough frequencies. These findings highlight a role for specific snoRNAs in safeguarding against oncogenic insult and demonstrate a functional link between H/ACA snoRNAs regulated by RAS and the biophysical properties of ribosomes in cancer.

DNA-Dependent Protein Kinase Drives Prostate Cancer Progression through Transcriptional Regulation of the Wnt Signaling Pathway

PURPOSE

Protein kinases are known to play a prominent role in oncogenic progression across multiple cancer subtypes, yet their role in prostate cancer progression remains underexplored. The purpose of this study was to identify kinases that drive prostate cancer progression.Experimental Design: To discover kinases that drive prostate cancer progression, we investigated the association between gene expression of all known kinases and long-term clinical outcomes in tumor samples from 545 patients with high-risk disease. We evaluated the impact of genetic and pharmacologic inhibition of the most significant kinase associated with metastatic progression in vitro and in vivo.

RESULTS

DNA-dependent protein kinase (DNAPK) was identified as the most significant kinase associated with metastatic progression in high-risk prostate cancer. Inhibition of DNAPK suppressed the growth of both AR-dependent and AR-independent prostate cancer cells. Gene set enrichment analysis nominated Wnt as the top pathway associated with DNAPK. We found that DNAPK interacts with the Wnt transcription factor LEF1 and is critical for LEF1-mediated transcription.

CONCLUSIONS

Our data show that DNAPK drives prostate cancer progression through transcriptional regulation of Wnt signaling and is an attractive therapeutic target in aggressive prostate cancer.

Abstract 733: Characterizing the genetic profile of endometrioid ovarian carcinoma using exome sequencing

Objective: Endometrioid ovarian carcinoma is poorly understood at the genomic level. Prior sequencing investigations have been limited to small gene panels. In order to characterize the etiology of this disease and identify potential therapeutic targets, we sought to build an unbiased genetic profile of coding gene alterations in endometriod ovarian tumors.

Methods: We sequenced the exomes of primary endometrioid ovarian tumors obtained from our institutional gynecologic oncology tissue bank from 1996 - 2011. We analyzed somatic point mutations, copy number alterations, structural variations and mutational signatures and integrated these data to determine genetic drivers. Demographic and clinical data were collected by retrospective chart review.

Results: Seventeen primary endometrioid ovarian tumors were sequenced. Median age at surgical resection was 51 years (range 33-77 years). The majority of patients presented with early stage disease (71%), many had a history of endometriosis (47%) and 19% had a synchronous primary uterine carcinoma. Microsatellite instability (MSI) was present in 18% (3/17) tumors. All three of these tumors with MSI exhibited a high tumor mutational burden with an average of 174 mutations per megabase of DNA, and two of them had confirmed loss or inactivation of mismatch repair proteins. Approximately half of all cases (47%) had inactivation or truncating mutations in PTEN. 59% of cases (10/17) had alterations in WNT pathway genes, including 6/17 (35%) with missense mutations in the regulatory domain of beta catenin (CTNNB1). 2/17 (12%) had TP53 mutations. We identified one case with a mutation in the exonuclease domain of POLE (P286R), which also exhibited a characteristic POLE-mutant mutation signature.

Conclusion: Using whole exome sequencing, we identified that endometrioid ovarian carcinomas are commonly hypermutated and often harbor microsatellite instability. These findings highlight the importance of genetic sequencing to determine which patients may benefit from targeted immunotherapies.

Citation Format: William E. Pierson, Pamela Peters, David A. Quigley, Lee-may Chen, Jocelyn S. Chapman. Characterizing the genetic profile of endometrioid ovarian carcinoma using exome sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 733.

Novel RB1-Loss Transcriptomic Signature Is Associated with Poor Clinical Outcomes across Cancer Types

PURPOSE

Rb-pathway disruption is of great clinical interest, as it has been shown to predict outcomes in multiple cancers. We sought to develop a transcriptomic signature for detecting biallelic RB1 loss (RBS) that could be used to assess the clinical implications of RB1 loss on a pan-cancer scale.

EXPERIMENTAL DESIGN

We utilized data from the Cancer Cell Line Encyclopedia (N = 995) to develop the first pan-cancer transcriptomic signature for predicting biallelic RB1 loss (RBS). Model accuracy was validated using The Cancer Genome Atlas (TCGA) Pan-Cancer dataset (N = 11,007). RBS was then used to assess the clinical relevance of biallelic RB1 loss in TCGA Pan-Cancer and in an additional metastatic castration-resistant prostate cancer (mCRPC) cohort.

RESULTS

RBS outperformed the leading existing signature for detecting RB1 biallelic loss across all cancer types in TCGA Pan-Cancer (AUC, 0.89 vs. 0.66). High RBS (RB1 biallelic loss) was associated with promoter hypermethylation (P = 0.008) and gene body hypomethylation (P = 0.002), suggesting RBS could detect epigenetic gene silencing. TCGA Pan-Cancer clinical analyses revealed that high RBS was associated with short progression-free (P < 0.00001), overall (P = 0.0004), and disease-specific (P < 0.00001) survival. On multivariable analyses, high RBS was predictive of shorter progression-free survival in TCGA Pan-Cancer (P = 0.03) and of shorter overall survival in mCRPC (P = 0.004) independently of the number of DNA alterations in RB1.

CONCLUSIONS

Our study provides the first validated tool to assess RB1 biallelic loss across cancer types based on gene expression. RBS can be useful for analyzing datasets with or without DNA-sequencing results to investigate the emerging prognostic and treatment implications of Rb-pathway disruption.See related commentary by Choudhury and Beltran, p. 4199.

Whole-Genome and Transcriptional Analysis of Treatment-Emergent Small-Cell Neuroendocrine Prostate Cancer Demonstrates Intraclass Heterogeneity

Therapeutic resistance in metastatic castration-resistant prostate cancer (mCRPC) can be accompanied by treatment-emergent small-cell neuroendocrine carcinoma (t-SCNC), a morphologically distinct subtype. We performed integrative whole-genome and -transcriptome analysis of mCRPC tumor biopsies including paired biopsies after progression, and multiple samples from the same individual. t-SCNC was significantly less likely to have amplification of AR or an intergenic AR-enhancer locus, and demonstrated lower expression of AR and its downstream transcriptional targets. Genomic and transcriptional hallmarks of t-SCNC included biallelic loss of RB1, elevated expression levels of CDKN2A and E2F1, and loss of expression of the AR and AR-responsive genes including TMPRSS2 and NKX3-1. We identified three tumors that converted from adenocarcinoma to t-SCNC and demonstrate spatial and temporal intrapatient heterogeneity of metastatic tumors harboring adenocarcinoma, t-SCNC, or mixed expression phenotypes, with implications for treatment strategies in which dual targeting of adenocarcinoma and t-SCNC phenotypes may be necessary. IMPLICATIONS: The t-SCNC phenotype is characterized by lack of AR enhancer gain and loss of RB1 function, and demonstrates both interindividual and intraindividual heterogeneity.Visual Overview: http://mcr.aacrjournals.org/content/molcanres/17/6/1235/F1.large.jpg.

Genomic drivers of poor prognosis and enzalutamide resistance in metastatic castration-resistant prostate cancer

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Background: Metastatic castration-resistant prostate cancer (mCRPC) is the lethal form of the disease. Several recent efforts have identified genomic alterations in mCRPC, but the clinical implications of these alterations have not been fully elucidated. We conducted a prospective cohort study (n = 101) using whole genome sequencing (WGS) to analyze the association between key driver gene alterations and overall survival. We also performed whole-transcriptome RNA sequencing (RNA-seq) analyses to identify potential mechanisms of enzalutamide resistance in mCRPC. Methods: Metastasis biopsies were obtained in 101 mCRPC patients as part of the multi-institutional West Coast Prostate Cancer Dream Team project. Samples underwent WGS and RNA-seq. The resulting mutation, copy number, and structural variant calls were integrated to determine functional copy number status of candidate genes for downstream clinical analyses. We performed univariate and multivariable analyses to assess the prognostic significance of candidate genomic events with respect to overall survival. To nominate and investigate genomic pathways associated with enzalutamide resistance, we performed expression-based gene set enrichment analysis followed by cross-sectional enrichment and survival analyses related to the top nominated pathway. Results: RB1 loss was associated with poor overall survival (median 14.1 vs. 42.0 months, p < 0.001). When we compared enzalutamide resistant versus naïve samples using gene set enrichment analysis, we identified the Wnt/beta-catenin pathway as the top differentially expressed pathway in enzalutamide-resistant patients. Furthermore, CTNNB1 (beta-catenin) activating mutations were exclusive to enzalutamide-resistant patients (p = 0.013) and predictive of poor overall survival (median 13.6 vs. 41.7 months, p < 0.001). Conclusions: Impaired survival in mCRPC patients is associated with RB1 loss, identified by integrated genomic analysis of CRPC metastasis biopsies. Among men with mCRPC that was enzalutamide-resistant, the Wnt/beta-catenin pathway is nominated as an important predictive (and potentially therapeutic) pathway.

Genomic Hallmarks and Structural Variation in Metastatic Prostate Cancer

While mutations affecting protein-coding regions have been examined across many cancers, structural variants at the genome-wide level are still poorly defined. Through integrative deep whole-genome and -transcriptome analysis of 101 castration-resistant prostate cancer metastases (109X tumor/38X normal coverage), we identified structural variants altering critical regulators of tumorigenesis and progression not detectable by exome approaches. Notably, we observed amplification of an intergenic enhancer region 624 kb upstream of the androgen receptor (AR) in 81% of patients, correlating with increased AR expression. Tandem duplication hotspots also occur near MYC, in lncRNAs associated with post-translational MYC regulation. Classes of structural variations were linked to distinct DNA repair deficiencies, suggesting their etiology, including associations of CDK12 mutation with tandem duplications, TP53 inactivation with inverted rearrangements and chromothripsis, and BRCA2 inactivation with deletions. Together, these observations provide a comprehensive view of how structural variations affect critical regulators in metastatic prostate cancer.

Antisecretory Factor-Mediated Inhibition of Cell Volume Dynamics Produces Antitumor Activity in Glioblastoma

Interstitial fluid pressure (IFP) presents a barrier to drug uptake in solid tumors, including the aggressive primary brain tumor glioblastoma (GBM). It remains unclear how fluid dynamics impacts tumor progression and can be targeted therapeutically. To address this issue, a novel telemetry-based approach was developed to measure changes in IFP during progression of GBM xenografts. Antisecretory factor (AF) is an endogenous protein that displays antisecretory effects in animals and patients. Here, endogenous induction of AF protein or exogenous administration of AF peptide reduced IFP and increased drug uptake in GBM xenografts. AF inhibited cell volume regulation of GBM cells, an effect that was phenocopied in vitro by the sodium-potassium-chloride cotransporter 1 (SLC12A2/NKCC1) inhibitor bumetanide. As a result, AF induced apoptosis and increased survival in GBM models. In vitro, the ability of AF to reduce GBM cell proliferation was phenocopied by bumetanide and NKCC1 knockdown. Next, AF's ability to sensitize GBM cells to the alkylating agent temozolomide, standard of care in GBM patients, was evaluated. Importantly, combination of AF induction and temozolomide treatment blocked regrowth in GBM xenografts. Thus, AF-mediated inhibition of cell volume regulation represents a novel strategy to increase drug uptake and improve outcome in GBM. Mol Cancer Res; 16(5); 777-90. ©2018 AACR.

Commonly Occurring Cell Subsets in High-Grade Serous Ovarian Tumors Identified by Single-Cell Mass Cytometry

We have performed an in-depth single-cell phenotypic characterization of high-grade serous ovarian cancer (HGSOC) by multiparametric mass cytometry (CyTOF). Using a CyTOF antibody panel to interrogate features of HGSOC biology, combined with unsupervised computational analysis, we identified noteworthy cell types co-occurring across the tumors. In addition to a dominant cell subset, each tumor harbored rarer cell phenotypes. One such group co-expressed E-cadherin and vimentin (EV), suggesting their potential role in epithelial mesenchymal transition, which was substantiated by pairwise correlation analyses. Furthermore, tumors from patients with poorer outcome had an increased frequency of another rare cell type that co-expressed vimentin, HE4, and cMyc. These poorer-outcome tumors also populated more cell phenotypes, as quantified by Simpson's diversity index. Thus, despite the recognized genomic complexity of the disease, the specific cell phenotypes uncovered here offer a focus for therapeutic intervention and disease monitoring.

Age, estrogen, and immune response in breast adenocarcinoma and adjacent normal tissue

Chronic inflammation promotes breast tumor growth and invasion by accelerating angiogenesis and tissue remodeling in the tumor microenvironment. There is a complex relationship between inflammation and estrogen, which drives the growth of 70 percent of breast tumors. While low levels of estrogen exposure stimulate macrophages and other inflammatory cell populations, very high levels are immune suppressive. Breast tumor incidence is increased by obesity and age, which interact to influence inflammatory cell populations in normal breast tissue. To characterize the impact of these factors on tumors and the tumor microenvironment, we measured gene expression in 195 breast adenocarcinomas and matched adjacent normal breast tissue samples collected at Akershus University Hospital (AHUS). Age and Body Mass Index (BMI) were independently associated with inflammation in adjacent normal tissue but not tumors. Estrogen Receptor (ER)-negative tumors had elevated macrophage expression compared with matched normal tissue, but ER-positive tumors showed an unexpected decrease in macrophage expression. We found an inverse relationship between the increase in tumor estrogen pathway expression compared with adjacent normal tissue and tumor macrophage score. We validated this finding in 126 breast tumor-normal pairs from the previously published METABRIC cohort. We developed a novel statistic, the Rewiring Coefficient, to quantify the rewiring of gene co-expression networks at the level of individual genes. Differential correlation analysis demonstrated distinct pathways were rewired during tumorigenesis. Our data support an immune suppressive effect of high doses of estrogen signaling in breast tumor microenvironment, suggesting that this effect contributes to the greater presence of prognostic and therapeutically relevant immune cells in ER-negative tumors.

Panx3 links body mass index and tumorigenesis in a genetically heterogeneous mouse model of carcinogen-induced cancer

Background

Body mass index (BMI) has been implicated as a primary factor influencing cancer development. However, understanding the relationship between these two complex traits has been confounded by both environmental and genetic heterogeneity.

Methods

In order to gain insight into the genetic factors linking BMI and cancer, we performed chemical carcinogenesis on a genetically heterogeneous cohort of interspecific backcross mice ((Mus Spretus × FVB/N) F1 × FVB/N). Using this cohort, we performed quantitative trait loci (QTL) analysis to identify regions linked to BMI. We then performed an integrated analysis incorporating gene expression, sequence comparison between strains, and gene expression network analysis to identify candidate genes influencing both tumor development and BMI.

Results

Analysis of QTL linked to tumorigenesis and BMI identified several loci associated with both phenotypes. Exploring these loci in greater detail revealed a novel relationship between the Pannexin 3 gene (Panx3) and both BMI and tumorigenesis. Panx3 is positively associated with BMI and is strongly tied to a lipid metabolism gene expression network. Pre-treatment Panx3 gene expression levels in normal skin are associated with tumor susceptibility and inhibition of Panx function strongly influences inflammation.

Conclusions

These studies have identified several genetic loci that influence both BMI and carcinogenesis and implicate Panx3 as a candidate gene that links these phenotypes through its effects on inflammation and lipid metabolism.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-016-0334-8) contains supplementary material, which is available to authorized users.

Gene Expression Architecture of Mouse Dorsal and Tail Skin Reveals Functional Differences in Inflammation and Cancer

Inherited germline polymorphisms can cause gene expression levels in normal tissues to differ substantially between individuals. We present an analysis of the genetic architecture of normal adult skin from 470 genetically unique mice, demonstrating the effect of germline variants, skin tissue location, and perturbation by exogenous inflammation or tumorigenesis on gene signaling pathways. Gene networks related to specific cell types and signaling pathways, including sonic hedgehog (Shh), Wnt, Lgr family stem cell markers, and keratins, differed at these tissue sites, suggesting mechanisms for the differential susceptibility of dorsal and tail skin to development of skin diseases and tumorigenesis. The Pten tumor suppressor gene network is rewired in premalignant tumors compared to normal tissue, but this response to perturbation is lost during malignant progression. We present a software package for expression quantitative trait loci (eQTL) network analysis and demonstrate how network analysis of whole tissues provides insights into interactions between cell compartments and signaling molecules.

Large-Scale Profiling of Kinase Dependencies in Cancer Cell Lines

One approach to identifying cancer-specific vulnerabilities and therapeutic targets is to profile genetic dependencies in cancer cell lines. Here, we describe data from a series of siRNA screens that identify the kinase genetic dependencies in 117 cancer cell lines from ten cancer types. By integrating the siRNA screen data with molecular profiling data, including exome sequencing data, we show how vulnerabilities/genetic dependencies that are associated with mutations in specific cancer driver genes can be identified. By integrating additional data sets into this analysis, including protein-protein interaction data, we also demonstrate that the genetic dependencies associated with many cancer driver genes form dense connections on functional interaction networks. We demonstrate the utility of this resource by using it to predict the drug sensitivity of genetically or histologically defined subsets of tumor cell lines, including an increased sensitivity of osteosarcoma cell lines to FGFR inhibitors and SMAD4 mutant tumor cells to mitotic inhibitors.

Abstract P6-08-05: Protein tyrosine kinase activity and miRNA expression profiling reveals differences according to progesterone-receptor-status in HER-2 negative breast cancer

Background: Kinases are considered as promising source of biomarkers for diagnostic, prognostic and therapeutic purposes in cancer patients. We assessed tyrosine kinase activity in 39 primary breast cancer samples that were all hormone receptor positive (ER+ and/or PR+) with differential HER-2 status, using microarray technology. Methods: Pamchip® peptide microarrays were used to measure the activity of protein tyrosine kinases in 32 breast cancer samples. The breast cancer cell lines MCF-7, BT474 and ZR75-1, was studied for kinase activity, both untreated and treated with estradiol. Results: Results showed differences in phosphorylation amongst breast cancer samples. A total of 37 peptide kinases were highly phosphorylated in a group of breast cancer samples representing 33 protein tyrosine kinases involved in cancer pathways and immunological responses. In vitro studies with breast cancer cell lines exhibited the same phosphorylation profiles, but increased phosphorylation was only observed in one cell line, ZR75-1. Eliminating HER-2 positive samples, we obtained differences in phosphorylation profiles based on PR-status only. Samples lacking PR-expression exhibited higher kinase activity of downstream kinases compared to PR-positive samples. Similar results were obtained with miRNA expression profiles of 31 breast cancer samples. Five miRNAs were identified to be significantly differentially expressed (p &lt; 0.05) between PR-negative and PR-positive samples. This effect was even stronger when eliminating HER-2 positive samples, with 13 miRNAs exhibiting significant differential expression based on PR-status. Conclusion: Although our data are based on a small dataset, the lack of PR expression seems to have a profound effect on tyrosine kinase activity and miRNA expression in HER-2 negative breast cancers without any effect on gene expression. This indicates that regulatory and functional molecules might exhibit phenotypical features of cancer that cannot be explained by gene expression alone.

Citation Format: Tahiri A, Satheesh SV, de Wijn R, Lders T, Aure MR, Quigley DA, Bukholm IR, Hurtado A, Kristensen VN, Geisler J. Protein tyrosine kinase activity and miRNA expression profiling reveals differences according to progesterone-receptor-status in HER-2 negative breast cancer. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P6-08-05.

Abstract B59: Age and estrogen-dependent inflammation in breast adenocarcinoma and normal breast tissue

Chronic inflammation promotes breast tumor growth and invasion by accelerating angiogenesis and tissue remodeling in the tumor microenvironment. There is a complex relationship between inflammation and estrogen, which drives the growth of 70 percent of breast tumors. Low levels of estrogen exposure stimulate macrophages and other inflammatory cell populations, but very high levels are immune suppressive. Breast tumor incidence is increased by obesity and age, which interact to influence inflammatory cell populations in normal breast tissue. To characterize the impact of these factors on tumors and the tumor microenvironment, we measured gene expression profiles in 195 breast adenocarcinomas and 195 matched adjacent normal breast tissue samples. Age and Body Mass Index (BMI) were independently associated with inflammation in normal tissue but not tumors. We developed a novel statistic, the Rewiring Coefficient, to quantify the rewiring of gene co-expression networks at the level of individual genes. Estrogen Receptor (ER)-negative tumors had elevated macrophage expression compared to matched normal tissue, but ER-positive tumors showed an unexpected decrease in macrophage expression. We found an inverse relationship between the increase in tumor estrogen pathway expression compared to adjacent normal tissue and that tumor's macrophage score and validated this finding in 126 matched breast tumor-normal pairs from the previously published METABRIC cohort. Our data support an immune suppressive effect of high doses of estrogen signaling in breast tumor microenvironment, suggesting that this effect contributes to the greater presence of prognostic and therapeutically relevant immune cells in ER-negative tumors.

Citation Format: David A. Quigley, Andliena Tahiri, Torben Lüders, Margit H. Riis, Allan Balmain, Anne-Lise Børresen-Dale, Ida R. Bukholm, Vessela Kristensen. Age and estrogen-dependent inflammation in breast adenocarcinoma and normal breast tissue. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Breast Cancer Research; Oct 17-20, 2015; Bellevue, WA. Philadelphia (PA): AACR; Mol Cancer Res 2016;14(2_Suppl):Abstract nr B59.

Predicting prognosis and therapeutic response from interactions between lymphocytes and tumor cells

As epithelial tumors grow from single cells to a malignant mass of invasive tissue, they must exploit the innate inflammatory response, while evading the adaptive immune system. Prognosis of solid tumors has historically focused on macroscopic features such as size, grade, and mitotic index. It is now clear that prognosis assessment must also consider the stromal and immune cells that surround and infiltrate the tumor. Tumors promote growth, angiogenesis, and tissue remodeling by subverting the normal functions of macrophages and other cells of the innate immune system that inhabit their microenvironment. Simultaneously, tumor cells escape from and inactivate the adaptive immune system by exploiting the mechanisms preventing damaging auto-immune responses in cytotoxic T cells. The presence of CD8(+) T cells within epithelial tumors is now a well-supported marker of better prognosis in many tumor types. However, this benefit is counterbalanced by immune regulatory cell populations that promote tumor escape from immune surveillance and metastasis. Therapeutic approaches that kill tumor cells selectively by re-activating immune checkpoints are becoming an established therapeutic option, but it is not yet clear how to identify which patients will benefit from this treatment modality. Evidence is accumulating that identifying the presence of T cell-activating neoantigens, produced by mutated proteins in tumors, will play an important role in checkpoint inhibitor prognosis. This review provides an overview of the evidence that lymphocytic infiltration of tumors has prognostic value in many epithelial tumor types and is linked to the success of chemical and immune checkpoint therapeutic strategies.

The genetics of splicing in neuroblastoma

Regulation of mRNA splicing, a critical and tightly regulated cellular function, underlies the majority of proteomic diversity and is frequently disrupted in disease. Using an integrative genomics approach, we combined both genomic data and exon-level transcriptome data in two somatic tissues (cerebella and peripheral ganglia) from a transgenic mouse model of neuroblastoma, a tumor that arises from the peripheral neural crest. Here, we describe splicing quantitative trait loci associated with differential splicing across the genome that we use to identify genes with previously unknown functions within the splicing pathway and to define de novo intronic splicing motifs that influence splicing from hundreds of bases away. Our results show that these splicing motifs represent sites for functional recurrent mutations and highlight novel candidate genes in human cancers, including childhood neuroblastoma.

SIGNIFICANCE

Somatic mutations with predictable downstream effects are largely relegated to coding regions, which comprise less than 2% of the human genome. Using an unbiased in vivo analysis of a mouse model of neuroblastoma, we have identified intronic splicing motifs that translate into sites for recurrent somatic mutations in human cancers.