Copy number alteration burden predicts prostate cancer relapse

Breast and prostate cancers harbor common somatic copy number alterations that consistently differ by race and are associated with survival

Background

Pan-cancer studies of somatic copy number alterations (SCNAs) have demonstrated common SCNA patterns across cancer types, but despite demonstrable differences in aggressiveness of some cancers by race, pan-cancer SCNA variation by race has not been explored. This study investigated a) racial differences in SCNAs in both breast and prostate cancer, b) the degree to which they are shared across cancers, and c) the impact of these shared, race-differentiated SCNAs on cancer survival.

Methods

Utilizing data from The Cancer Genome Atlas (TCGA), SCNAs were identified using GISTIC 2.0, and in each tumor type, differences in SCNA magnitude between African Americans (AA) and European Americans (EA) were tested using linear regression. Unsupervised hierarchical clustering of the copy number of genes residing in race-differentiated SCNAs shared between tumor types was used to identify SCNA-defined patient groups, and Cox proportional hazards regression was used to test for association between those groups and overall/progression-free survival (PFS).

Results

We identified SCNAs that differed by race in breast (n = 58 SCNAs; permutation p < 10^− 4) and prostate tumors (n = 78 SCNAs; permutation p = 0.006). Six race-differentiated SCNAs common to breast and prostate found at chromosomes 5q11.2-q14.1, 5q15-q21.1, 8q21.11-q21.13, 8q21.3-q24.3, 11q22.3, and 13q12.3-q21.3 had consistent differences by race across both tumor types, and all six were of higher magnitude in AAs, with the chromosome 8q regions being the only amplifications. Higher magnitude copy number differences in AAs were also identified at two of these race-differentiated SCNAs in two additional hormonally-driven tumor types: endometrial (8q21.3-q24.3 and 13q12.3-q21.3) and ovarian (13q12.3-q21.3) cancers. Race differentiated SCNA-defined patient groups were significantly associated with survival differences in both cancer types, and these groups also differentiated within triple negative breast cancers based on PFS. While the frequency of the SCNA-defined patient groups differed by race, their effects on survival did not.

Conclusions

This study identified race-differentiated SCNAs shared by two related cancers. The association of SCNA-defined patient groups with survival demonstrates the clinical significance of combinations of these race-differentiated genomic aberrations, and the higher frequency of these alterations in AA relative to EA patients may explain racial disparities in risk of aggressive breast and prostate cancer.

Morphology-Predicted Large-Scale Transition Number in Circulating Tumor Cells Identifies a Chromosomal Instability Biomarker Associated with Poor Outcome in Castration-Resistant Prostate Cancer

Chromosomal instability (CIN) increases a tumor cell's ability to acquire chromosomal alterations, a mechanism by which tumor cells evolve, adapt, and resist therapeutics. We sought to develop a biomarker of CIN in circulating tumor cells (CTC) that are more likely to reflect the genetic diversity of patient's disease than a single-site biopsy and be assessed rapidly so as to inform treatment management decisions in real time. Large-scale transitions (LST) are genomic alterations defined as chromosomal breakages that generate chromosomal gains or losses of greater than or equal to10 Mb. Here we studied the relationship between the number of LST in an individual CTC determined by direct sequencing and morphologic features of the cells. This relationship was then used to develop a computer vision algorithm that utilizes CTC image features to predict the presence of a high (9 or more) versus low (8 or fewer) LST number in a single cell. As LSTs are a primary functional component of homologous recombination deficient cellular phenotypes, the image-based algorithm was studied prospectively on 10,240 CTCs in 367 blood samples obtained from 294 patients with progressing metastatic castration-resistant prostate cancer taken prior to starting a standard-of-care approved therapy. The resultant computer vision-based biomarker of CIN in CTCs in a pretreatment sample strongly associated with poor overall survival times in patients treated with androgen receptor signaling inhibitors and taxanes. SIGNIFICANCE: A rapidly assessable biomarker of chromosomal instability in CTC is associated with poor outcomes when detected in men with progressing mCRPC.

Triple Aberrant Prostate Cancer (TAPC) - Aggregate role of aberrations in TP53, PTEN and RB1 on ETS gene fusions and prognosis in metastatic castrate resistant prostate cancer

BACKGROUND

Aberrations in TP53, PTEN and RB1 are key drivers of therapy resistance in prostate cancer. Up to 50% of prostate cancers harbor ETS gene rearrangements, a potentially compounding aggressive biological event. Little is known about the impact of aggregate aberrations and gene fusion events in prostate cancer.

METHODS

Using cBioportal for Cancer Genomics, an open-access resource for exploration of multidimensional cancer genomics data, we integrate whole-exome sequencing, gene expression, and histopathology with longitudinal clinical outcomes. Subsets of prostate tumors with aberrations in all three genes TP53, PTEN and RB1 were identified and correlated with prevalence of gene fusions. Prostate tumors with aberrations in TP53, PTEN, and RB1 were termed "triple aberrant prostate cancer" (TAPC).

RESULTS

Of 479 metastatic prostate tumors, 195 (40.7%) were TAPC, versus 21 of 594 (3.5%) of primary prostate tumors. Patients with metastatic TAPC showed a trend toward poorer overall survival than patients harboring 0, 1 or 2 of these aberrations. Twenty-five distinct fusions were identified, all involving ETS transcription factors. Both primary and metastatic prostate cancers with ETS fusions were significantly more likely to be TAPC than those without ETS fusions.

CONCLUSIONS

This study identified a unique molecular signature consisting of combined aberrations in TP53, PTEN and RB1 that is associated with poorer overall survival, as well as increasing prevalence of ETS gene fusions and differential gene expression patterns favoring aggressive disease and tumor progression. Identification of this subset of patients could inform prognostic decisions and provide a rationale for more aggressive or unique therapeutic approaches.

Genetic alterations in the 3q26.31-32 locus confer an aggressive prostate cancer phenotype

Large-scale genetic aberrations that underpin prostate cancer development and progression, such as copy-number alterations (CNAs), have been described but the consequences of specific changes in many identified loci is limited. Germline SNPs in the 3q26.31 locus are associated with aggressive prostate cancer, and is the location of NAALADL2, a gene overexpressed in aggressive disease. The closest gene to NAALADL2 is TBL1XR1, which is implicated in tumour development and progression. Using publicly-available cancer genomic data we report that NAALADL2 and TBL1XR1 gains/amplifications are more prevalent in aggressive sub-types of prostate cancer when compared to primary cohorts. In primary disease, gains/amplifications occurred in 15.99% (95% CI: 13.02–18.95) and 14.96% (95% CI: 12.08–17.84%) for NAALADL2 and TBL1XR1 respectively, increasing in frequency in higher Gleason grade and stage tumours. Gains/amplifications result in transcriptional changes and the development of a pro-proliferative and aggressive phenotype. These results support a pivotal role for copy-number gains in this genetic region.

Benjamin Simpson et al. use publicly available cancer genomic data to investigate copy number changes at the 3q26.31–32 locus, which has been associated with aggressive prostate cancer based on single-nucleotide polymorphisms. They find that gains of NAALADL2 and TBL1XR1 in this locus are associated with more aggressive subtypes of prostate cancer and the transcription of pro-proliferative signalling processes.

Design and Development of a Fully Synthetic Multiplex Ligation-Dependent Probe Amplification-Based Probe Mix for Detection of Copy Number Alterations in Prostate Cancer Formalin-Fixed, Paraffin-Embedded Tissue Samples

DNA copy number alterations (CNAs) are promising biomarkers to predict prostate cancer (PCa) outcome. However, fluorescence in situ hybridization (FISH) cannot assess complex CNA signatures because of low multiplexing capabilities. Multiplex ligation-dependent probe amplification (MLPA) can detect multiple CNAs in a single PCR assay, but PCa-specific probe mixes available commercially are lacking. Synthetic MLPA probes were designed to target 10 CNAs relevant to PCa: 5q15-21.1 (CHD1), 6q15 (MAP3K7), 8p21.2 (NKX3-1), 8q24.21 (MYC), 10q23.31 (PTEN), 12p13.1 (CDKN1B), 13q14.2 (RB1), 16p13.3 (PDPK1), 16q23.1 (GABARAPL2), and 17p13.1 (TP53), with 9 control probes. In cell lines, CNAs were detected when the cancer genome was as low as 30%. Compared with FISH in radical prostatectomy formalin-fixed, paraffin-embedded samples (n = 18: 15 cancers and 3 matched benign), the MLPA assay showed median sensitivity and specificity of 80% and 93%, respectively, across all CNAs assessed. In the validation set (n = 40: 20 tumors sampled in two areas), the respective sensitivity and specificity of MLPA compared advantageously with FISH and TaqMan droplet digital PCR (ddPCR) when assessing PTEN deletion (FISH: 85% and 100%; ddPCR: 100% and 83%) and PDPK1 gain (FISH: 100% and 92%; ddPCR: 93% and 100%). This new PCa probe mix accurately identifies CNAs by MLPA across multiple genes using low quality and quantities (50 ng) of DNA extracted from clinical formalin-fixed, paraffin-embedded samples.

Current Challenges and Implications of Proteogenomic Approaches in Prostate Cancer

In the recent past, next-generation sequencing (NGS) approaches have heralded the omics era. With NGS data burgeoning, there arose a need to disseminate the omic data better. Proteogenomics has been vividly used for characterising the functions of candidate genes and is applied in ascertaining various diseased phenotypes, including cancers. However, not much is known about the role and application of proteogenomics, especially Prostate Cancer (PCa). In this review, we outline the need for proteogenomic approaches, their applications and their role in PCa.

Decoding the evolutionary response to prostate cancer therapy by plasma genome sequencing

BACKGROUND

Investigating genome evolution in response to therapy is difficult in human tissue samples. To address this challenge, we develop an unbiased whole-genome plasma DNA sequencing approach that concurrently measures genomic copy number and exome mutations from archival cryostored plasma samples. This approach is applied to study longitudinal blood plasma samples from prostate cancer patients, where longitudinal tissue biopsies from the bone and other metastatic sites have been challenging to collect.

RESULTS

A molecular characterization of archival plasma DNA from 233 patients and genomic profiling of 101 patients identifies clinical correlations of aneuploid plasma DNA profiles with poor survival, increased plasma DNA concentrations, and lower plasma DNA size distributions. Deep-exome sequencing and genomic copy number profiling are performed on 23 patients, including 9 patients with matched metastatic tissues and 12 patients with serial plasma samples. These data show a high concordance in genomic alterations between the plasma DNA and metastatic tissue samples, suggesting the plasma DNA is highly representative of the tissue alterations. Longitudinal sequencing of 12 patients with 2-5 serial plasma samples reveals clonal dynamics and genome evolution in response to hormonal and chemotherapy. By performing an integrated evolutionary analysis, minor subclones are identified in 9 patients that expanded in response to therapy and harbored mutations associated with resistance.

CONCLUSIONS

This study provides an unbiased evolutionary approach to non-invasively delineate clonal dynamics and identify clones with mutations associated with resistance in prostate cancer.

Exploration of gene expression profiles and immune microenvironment between high and low tumor mutation burden groups in prostate cancer

BACKGROUND

Tumor mutation burden (TMB) has been established as a biomarker for response to immune therapy and prognosis in various cancers. However, the association between TMB and prognosis of prostate cancer (PCa) remains unclear. This study aimed to investigate the impact of TMB in biochemical recurrence (BCR) and the immune microenvironment in high and low TMB groups.

METHODS

Mutation data, gene expression, clinicopathological information were downloaded from The Cancer Genome Atlas (TCGA). Mutation types and TMB values were identified. All samples were divided into high and low TMB groups with median TMB value as the cutoff point. The BCR-free survival rates, Differentially expressed genes (DEGs) and immune cells infiltrations in different TMB groups were identified.

RESULTS

The most common variant type and SNV were single nucleotide polymorphism and C > T. respectively. High TMB level was significantly associated with older age, positive lymph node, higher International Society of Urological Pathology (ISUP) grade, advanced stage and poor BCR-free survival. 132 DEGs were identified and involved in receptor ligand activity and hormone activity. High expression of six core genes UBE2C, PLK1, CDC20, BUB1, CDK1 and HJURP were associated with worse BCR-free survival. The analysis of immune cells infiltration revealed that the amount of activated CD4⁺ memory T cells was significantly different in high and low TMB groups.

CONCLUSIONS

The current study comprehensively described the summary of mutation and TMB related DEGs in PCa. TMB was associated with BCR-free survival and the infiltration of activated CD4⁺ memory T cells in the immune microenvironment.

DEFOR: depth- and frequency-based somatic copy number alteration detector

MOTIVATION

Detection of somatic copy number alterations (SCNAs) using high-throughput sequencing has become popular because of rapid developments in sequencing technology. Existing methods do not perform well in calling SCNAs for the unstable tumor genomes.

RESULTS

We developed a new method, DEFOR, to detect SCNAs in tumor samples from exome-sequencing data. The evaluation showed that DEFOR has a higher accuracy for SCNA detection from exome sequencing compared with the five existing tools. This advantage is especially apparent in unstable tumor genomes with a large proportion of SCNAs.

AVAILABILITY AND IMPLEMENTATION

DEFOR is available at https://github.com/drzh/defor.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Chromosome Abnormalities: New Insights into Their Clinical Significance in Cancer

Chromosomal abnormalities, consisting of numerical and structural chromosome abnormalities, are a common characteristic of cancer. Numerical chromosome abnormalities, mainly including aneuploidy and chromosome instability, are caused by chromosome segregation errors in mitosis, whereas structural chromosome abnormalities are a consequence of DNA damage and comprise focal/arm-level chromosome gain or loss. Recent advances have started to unveil the mechanisms by which chromosomal abnormalities can facilitate tumorigenesis and change the cellular fitness and the expression or function of RNAs and proteins. Accumulating evidence suggests that chromosome abnormalities represent a genomic signature that is linked to cancer prognosis and reaction to chemotherapy and immunotherapy. In this review, we discuss the most recent findings on the role of chromosome abnormalities in tumorigenesis and cancer progression, with a particular emphasis on how aneuploidy and chromosome instability influence cancer therapy and prognosis. We also highlight the distribution and clinical application of the structural chromosome abnormalities in various cancer types. A better understanding of the role of chromosome abnormalities will be beneficial to the development of precision oncology and suggest future directions for the field.

Somatic Tissue Engineering in Mouse Models Reveals an Actionable Role for WNT Pathway Alterations in Prostate Cancer Metastasis

To study genetic factors influencing the progression and therapeutic responses of advanced prostate cancer, we developed a fast and flexible system that introduces genetic alterations relevant to human disease directly into the prostate glands of mice using tissue electroporation. These electroporation-based genetically engineered mouse models (EPO-GEMM) recapitulate features of traditional germline models and, by modeling genetic factors linked to late-stage human disease, can produce tumors that are metastatic and castration-resistant. A subset of tumors with Trp53 alterations acquired spontaneous WNT pathway alterations, which are also associated with metastatic prostate cancer in humans. Using the EPO-GEMM approach and an orthogonal organoid-based model, we show that WNT pathway activation drives metastatic disease that is sensitive to pharmacologic WNT pathway inhibition. Thus, by leveraging EPO-GEMMs, we reveal a functional role for WNT signaling in driving prostate cancer metastasis and validate the WNT pathway as therapeutic target in metastatic prostate cancer. SIGNIFICANCE: Our understanding of the factors driving metastatic prostate cancer is limited by the paucity of models of late-stage disease. Here, we develop EPO-GEMMs of prostate cancer and use them to identify and validate the WNT pathway as an actionable driver of aggressive metastatic disease.This article is highlighted in the In This Issue feature, p. 890.

Molecular and Clinical Relevance of ZBTB38 Expression Levels in Prostate Cancer

Prostate cancer is one of the most commonly diagnosed cancers in men. A number of genomic and clinical studies have led to a better understanding of prostate cancer biology. Still, the care of patients as well as the prediction of disease aggressiveness, recurrence and outcome remain challenging. Here, we showed that expression of the gene ZBTB38 is associated with poor prognosis in localised prostate cancer and could help discriminate aggressive localised prostate tumours from those who can benefit only from observation. Analysis of different prostate cancer cohorts indicates that low expression levels of ZBTB38 associate with increased levels of chromosomal abnormalities and more aggressive pathological features, including higher rate of biochemical recurrence of the disease. Importantly, gene expression profiling of these tumours, complemented with cellular assays on prostate cancer cell lines, unveiled that tumours with low levels of ZBTB38 expression might be targeted by doxorubicin, a compound generating reactive oxygen species. Our study shows that ZBTB38 is involved in prostate cancer pathogenesis and may represent a useful marker to identify high risk and highly rearranged localised prostate cancer susceptible to doxorubicin.

Intron retention is a hallmark and spliceosome represents a therapeutic vulnerability in aggressive prostate cancer

The role of dysregulation of mRNA alternative splicing (AS) in the development and progression of solid tumors remains to be defined. Here we describe the first comprehensive AS landscape in the spectrum of human prostate cancer (PCa) evolution. We find that the severity of splicing dysregulation correlates with disease progression and establish intron retention as a hallmark of PCa stemness and aggressiveness. Systematic interrogation of 274 splicing-regulatory genes (SRGs) uncovers prevalent genomic copy number variations (CNVs), leading to mis-expression of ~68% of SRGs during PCa development and progression. Consequently, many SRGs are prognostic. Surprisingly, androgen receptor controls a splicing program distinct from its transcriptional regulation. The spliceosome modulator, E7107, reverses cancer aggressiveness and inhibits castration-resistant PCa (CRPC) in xenograft and autochthonous PCa models. Altogether, our studies establish aberrant AS landscape caused by dysregulated SRGs as a hallmark of PCa aggressiveness and the spliceosome as a therapeutic vulnerability for CRPC.

A genomic and epigenomic atlas of prostate cancer in Asian populations

Prostate cancer is the second most common cancer in men worldwide¹. Over the past decade, large-scale integrative genomics efforts have enhanced our understanding of this disease by characterizing its genetic and epigenetic landscape in thousands of patients^2,3. However, most tumours profiled in these studies were obtained from patients from Western populations. Here we produced and analysed whole-genome, whole-transcriptome and DNA methylation data for 208 pairs of tumour tissue samples and matched healthy control tissue from Chinese patients with primary prostate cancer. Systematic comparison with published data from 2,554 prostate tumours revealed that the genomic alteration signatures in Chinese patients were markedly distinct from those of Western cohorts: specifically, 41% of tumours contained mutations in FOXA1 and 18% each had deletions in ZNF292 and CHD1. Alterations of the genome and epigenome were correlated and were predictive of disease phenotype and progression. Coding and noncoding mutations, as well as epimutations, converged on pathways that are important for prostate cancer, providing insights into this devastating disease. These discoveries underscore the importance of including population context in constructing comprehensive genomic maps for disease.

Intratumoral heterogeneity and genetic characteristics of prostate cancer

Prostate cancer is a heterogeneous disease and optimum gene targeting treatment is often impermissible. We aim to determine the intratumoral genomic heterogeneity of prostate cancer and explore candidate genes for targeted therapy. Exome sequencing was performed on 37 samples from 16 patients with prostate cancer. Somatic variant analysis, copy number variant (CNV) analysis, clonal evolution analysis and variant spectrum analysis were used to study the intratumoral genomic heterogeneity and genetic characteristics of metastatic prostate cancer. Our study confirmed the high intratumoral genetic heterogeneity of prostate cancer in many aspects, including number of shared variants, tumor mutation burden (TMB), variant genes, CNV burden, weighted genome instability index (wGII), CNV profiles, clonal evolutionary process, variant spectrum and mutational signatures. Moreover, we identified several common genetic characteristics of prostate cancer. Alterations of DNA damage repair genes, RTK/RAS pathway associated gene RASGRF1 and autophagy gene EPG5 may be involved in tumorigenesis in prostate cancer. CNV burden and DNA damage repair (DDR) genes may be associated with metastasis of prostate cancer.

Overall tumor genomic instability: an important predictor of recurrence-free survival in patients with localized clear cell renal cell carcinoma

Measurement of a tumor's overall genomic instability has gathered recent interest over the identification of specific genomic imbalances, as it may provide a more robust measure of tumor aggressiveness. Here we demonstrate the association of tumor genomic instability in the prediction of disease recurrence in patients with clinically localized clear cell renal cell carcinoma (ccRCC). Genomic copy number analysis was performed using SNP-based microarrays on tumors from 103 ccRCC patients. The number of copy number alterations (CNAs) for each tumor was calculated, and a genomic imbalance threshold (GIT) associated with high stage and high-grade disease was determined. Cox proportional hazards regression analyzes were performed to assess the effect of GIT on recurrence-free survival adjusting for known confounders. In the cohort, copy number losses in chromosome arms 3p, 14q, 6q, 9p, and 1p and gains of 5q and 7p/q were common. CNA burden significantly increased with increasing stage (p < .001) and grade (p < .001). The median CNA burden associated with patients presenting with advanced stage (IV) and high-grade (III/IV) tumors was ≥9, defining the GIT. On regression analysis, GIT was a superior predictor of recurrence (Hazard Ratio 4.44 [CI 1.36-14.48], p = .01) independent of stage, with similar results adjusting for grade. These findings were confirmed using an alternative measure of genomic instability, weighted Genomic Integrity Index. Our data support a key role for genomic instability in ccRCC progression. More importantly, we have identified a GIT (≥ 9 CNAs) that is a superior and independent predictor of disease recurrence in high-risk ccRCC patients.

Therapeutic potential of ReACp53 targeting mutant p53 protein in CRPC

BACKGROUNDS

p53 is a tumor suppressor that prevents cancer onset and progression, and mutations in the p53 gene cause loss of the tumor suppressor function of the protein. The mutant p53 protein in tumor cells can form aggregates which contribute to the dominant-negative effect over the wild-type p53 protein, causing loss of p53 tumor suppression or gain of novel oncogenic functions. Mutations in p53 have been implicated in the pathogenesis of primary prostate cancer (PCa), and are often detected in recurrent and metastatic disease. Thus, targeting mutant p53 may constitute an alternative therapeutic strategy for advanced PCa for which there are no other viable options.

METHODS

In this study, we used immunoprecipitation, immunofluorescence, clonogenic survival, and cell proliferation assays, flow cytometric analysis and in vivo xenograft to investigate the biological effects of ReACp53, a cell-permeable peptide inhibitor of p53 aggregation, on mutant p53-carrying PCa cells.

RESULTS

Our results show that ReACp53 targets amyloid aggregates of mutant p53 protein and restores the p53 nuclear function as transcriptional factor, induces mitochondrial cell death and reduces DNA synthesis of mutant p53-carrying PCa cells; ReACp53 also inhibits xenograft tumor growth in vivo.

CONCLUSIONS

The data presented here suggest a therapeutic potential of targeting mutant p53 protein in advanced PCa setting, which has a clinical impact for aggressive PCa with transforming how such tumors are managed.

Protein tyrosine kinase 6 signaling in prostate cancer

More than 25 years have passed since the discovery of protein tyrosine kinase 6 (PTK6), a non-receptor tyrosine kinase distantly related to SRC family kinases. Since then, a variety of data suggest that PTK6 promotes oncogenic signaling and tumorigenesis, generally dependent on its kinase activity. Increased PTK6 expression, activation at the plasma membrane and altered intracellular localization have been discovered in prostate cancers. While PTK6 is localized to nuclei of epithelial cells in normal prostate, it is relocalized and activated at the plasma membrane in prostate tumors. Active PTK6 interacts with and directly phosphorylates AKT, FAK and BCAR1 to promote oncogenic signaling. Furthermore, PTK6 can enhance the epithelial mesenchymal transition by inhibiting E-cadherin expression and inducing expression of the mesenchymal markers vimentin, SLUG and ZEB1. Several lines of evidence suggest that PTK6 plays a role in Pten null prostate tumors. PTEN targets activating phosphorylation of PTK6 and loss of PTEN subsequently leads to PTK6 activation. Different studies provide compelling evidence as to why PTK6 is a potential therapeutic target in prostate cancer. Here, we briefly review the advances and significance of PTK6 in prostate cancer.

Suppressing fatty acid uptake has therapeutic effects in preclinical models of prostate cancer

Metabolism alterations are hallmarks of cancer, but the involvement of lipid metabolism in disease progression is unclear. We investigated the role of lipid metabolism in prostate cancer using tissue from patients with prostate cancer and patient-derived xenograft mouse models. We showed that fatty acid uptake was increased in human prostate cancer and that these fatty acids were directed toward biomass production. These changes were mediated, at least partly, by the fatty acid transporter CD36, which was associated with aggressive disease. Deleting Cd36 in the prostate of cancer-susceptible Pten^-/- mice reduced fatty acid uptake and the abundance of oncogenic signaling lipids and slowed cancer progression. Moreover, CD36 antibody therapy reduced cancer severity in patient-derived xenografts. We further demonstrated cross-talk between fatty acid uptake and de novo lipogenesis and found that dual targeting of these pathways more potently inhibited proliferation of human cancer-derived organoids compared to the single treatments. These findings identify a critical role for CD36-mediated fatty acid uptake in prostate cancer and suggest that targeting fatty acid uptake might be an effective strategy for treating prostate cancer.

Copy number alterations are associated with metastatic-lethal progression in prostate cancer

BACKGROUNDS

Aside from Gleason score few factors accurately identify the subset of prostate cancer (PCa) patients at high risk for metastatic progression. We hypothesized that copy number alterations (CNAs), assessed using CpG methylation probes on Illumina Infinium® Human Methylation450 (HM450K) BeadChip arrays, could identify primary prostate tumors with potential to develop metastatic progression.

METHODS

Epigenome-wide DNA methylation profiling was performed in surgically resected primary tumor tissues from two cohorts of PCa patients with clinically localized disease who underwent radical prostatectomy (RP) as primary therapy and were followed prospectively for at least 5 years: (1) a Fred Hutchinson (FH) Cancer Research Center-based cohort (n = 323 patients); and (2) an Eastern Virginia (EV) Medical School-based cohort (n = 78 patients). CNAs were identified using the R package ChAMP. Metastasis was confirmed by positive bone scan, MRI, CT or biopsy, and death certificates confirmed cause of death.

RESULTS

We detected 15 recurrent CNAs were associated with metastasis in the FH cohort and replicated in the EV cohort (p < 0.05) without adjusting for Gleason score in the model. Eleven of the recurrent CNAs were associated with metastatic progression in the FH cohort and validated in the EV cohort (p < 0.05) when adjusting for Gleason score.

CONCLUSIONS

This study shows that CNAs can be reliably detected from HM450K-based DNA methylation data. There are 11 recurrent CNAs showing association with metastatic-lethal events following RP and improving prediction over Gleason score. Genes affected by these CNAs may functionally relate to tumor aggressiveness and metastatic progression.

CDKN1B Deletions are Associated with Metastasis in African American Men with Clinically Localized, Surgically Treated Prostate Cancer

PURPOSE

The potential biological determinants of aggressive prostate cancer in African American (AA) men are unknown. Here we characterize prostate cancer genomic alterations in the largest cohort to date of AA men with clinical follow-up for metastasis, with the aim to elucidate the key molecular drivers associated with poor prognosis in this population.

EXPERIMENTAL DESIGN

Targeted sequencing was retrospectively performed on 205 prostate tumors from AA men treated with radical prostatectomy (RP) to examine somatic genomic alterations and percent of the genome with copy-number alterations (PGA). Cox proportional hazards analyses assessed the association of genomic alterations with risk of metastasis.

RESULTS

At RP, 71% (145/205) of patients had grade group ≥3 disease, and 49% (99/202) were non-organ confined. The median PGA was 3.7% (IQR = 0.9%-9.4%) and differed by pathologic grade (P < 0.001) and stage (P = 0.02). Median follow-up was 5 years. AA men with the highest quartile of PGA had increased risks of metastasis (multivariable: HR = 13.45; 95% CI, 2.55-70.86; P = 0.002). The most common somatic mutations were SPOP (11.2%), FOXA1 (8.3%), and TP53 (3.9%). The most common loci altered at the copy number level were CDKN1B (6.3%), CHD1 (4.4%), and PTEN (3.4%). TP53 mutations and deep deletions in CDKN1B were associated with increased risks of metastasis on multivariable analyses (TP53: HR = 9.5; 95% CI, 2.2-40.6; P = 0.002; CDKN1B: HR = 6.7; 95% CI, 1.3-35.2; P = 0.026).

CONCLUSIONS

Overall, PGA, somatic TP53 mutations, and a novel finding of deep deletions in CDKN1B were associated with poor prognosis in AA men. These findings require confirmation in additional AA cohorts.

Circulating cell-free DNA: Translating prostate cancer genomics into clinical care

Only in the past decade tremendous advances have been made in understanding prostate cancer genomics and consequently in applying new treatment strategies. As options regarding treatments are increasing so are the challenges in selecting the right treatment option for each patient and not the least, understanding the optimal time-point and sequence of applying available treatments. Critically, without reliable methods that enable sequential monitoring of evolving genotypes in individual patients, we will never reach effective personalised driven treatment approaches. This review focuses on the clinical implications of prostate cancer genomics and the potential of cfDNA in facilitating treatment management.

A systematic evaluation of copy number alterations detection methods on real SNP array and deep sequencing data

BACKGROUND

The Copy Number Alterations (CNAs) are discovered to be tightly associated with cancers, so accurately detecting them is one of the most important tasks in the cancer genomics. A series of CNAs detection methods have been proposed and new ones are still being developed. Due to the complexity of CNAs in cancers, no CNAs detection method has been accepted as the gold standard caller. Several evaluation works have made attempts to reveal typical CNAs detection methods' performance. Limited by the scale of evaluation data, these different comparison works don't reach a consensus and the researchers are still confused on how to choose one proper CNAs caller for their analysis. Therefore, it needs a more comprehensive evaluation of typical CNAs detection methods' performance.

RESULTS

In this work, we use a large-scale real dataset from CAGEKID consortium to evaluate total 12 typical CNAs detection methods. These methods are most widely used in cancer researches and always used as benchmark for the newly proposed CNAs detection methods. This large-scale dataset comprises of SNP array data on 94 samples and the whole genome sequencing data on 10 samples. Evaluations are comprehensively implemented in current scenarios of CNAs detection, which include that detect CNAs on SNP array data, on sequencing data with tumor and normal matched samples and on sequencing data with single tumor sample. Three SNP based methods are firstly ranked. Subsequently, the best SNP based method's results are used as benchmark to compare six matched samples based methods and three single tumor sample based methods in terms of the preprocessing, recall rate, Jaccard index and segmentation characteristics.

CONCLUSIONS

Our survey thoroughly reveals 12 typical methods' superiority and inferiority. We explain why methods show specific characteristics from a methodological standpoint. Finally, we present the guiding principle for choosing one proper CNAs detection method under specific conditions. Some unsolved problems and expectations are also addressed for upcoming CNAs detection methods.

Molecular Biomarkers in Localized Prostate Cancer: ASCO Guideline

PURPOSE

This guideline provides recommendations for available tissue-based prostate cancer biomarkers geared toward patient selection for active surveillance, identification of clinically significant disease, choice of postprostatectomy adjuvant versus salvage radiotherapy, and to address emerging questions such as the relative value of tissue biomarkers compared with magnetic resonance imaging.

METHODS

An ASCO multidisciplinary Expert Panel, with representatives from the European Association of Urology, American Urological Association, and the College of American Pathologists, conducted a systematic literature review of localized prostate cancer biomarker studies between January 2013 and January 2019. Numerous tissue-based molecular biomarkers were evaluated for their prognostic capabilities and potential for improving management decisions. Here, the Panel makes recommendations regarding the clinical use and indications of these biomarkers.

RESULTS

Of 555 studies identified, 77 were selected for inclusion plus 32 additional references selected by the Expert Panel. Few biomarkers had rigorous testing involving multiple cohorts and only 5 of these tests are commercially available currently: Oncotype Dx Prostate, Prolaris, Decipher, Decipher PORTOS, and ProMark. With various degrees of value and validation, multiple biomarkers have been shown to refine risk stratification and can be considered for select men to improve management decisions. There is a paucity of prospective studies assessing short- and long-term outcomes of patients when these markers are integrated into clinical decision making.

RECOMMENDATIONS

Tissue-based molecular biomarkers (evaluating the sample with the highest volume of the highest Gleason pattern) may improve risk stratification when added to standard clinical parameters, but the Expert Panel endorses their use only in situations in which the assay results, when considered as a whole with routine clinical factors, are likely to affect a clinical decision. These assays are not recommended for routine use as they have not been prospectively tested or shown to improve long-term outcomes-for example, quality of life, need for treatment, or survival. Additional information is available at www.asco.org/genitourinary-cancer-guidelines.

Significance of BRCA2 and RB1 Co-loss in Aggressive Prostate Cancer Progression

PURPOSE

Previous sequencing studies revealed that alterations of genes associated with DNA damage response (DDR) are enriched in men with metastatic castration-resistant prostate cancer (mCRPC). BRCA2, a DDR and cancer susceptibility gene, is frequently deleted (homozygous and heterozygous) in men with aggressive prostate cancer. Here we show that patients with prostate cancer who have lost a copy of BRCA2 frequently lose a copy of tumor suppressor gene RB1; importantly, for the first time, we demonstrate that co-loss of both genes in early prostate cancer is sufficient to induce a distinct biology that is likely associated with worse prognosis.

EXPERIMENTAL DESIGN

We prospectively investigated underlying molecular mechanisms and genomic consequences of co-loss of BRCA2 and RB1 in prostate cancer. We used CRISPR-Cas9 and RNAi-based methods to eliminate these two genes in prostate cancer cell lines and subjected them to in vitro studies and transcriptomic analyses. We developed a 3-color FISH assay to detect genomic deletions of BRCA2 and RB1 in prostate cancer cells and patient-derived mCRPC organoids.

RESULTS

In human prostate cancer cell lines (LNCaP and LAPC4), loss of BRCA2 leads to the castration-resistant phenotype. Co-loss of BRCA2-RB1 in human prostate cancer cells induces an epithelial-to-mesenchymal transition, which is associated with invasiveness and a more aggressive disease phenotype. Importantly, PARP inhibitors attenuate cell growth in human mCRPC-derived organoids and human CRPC cells harboring single-copy loss of both genes.

CONCLUSIONS

Our findings suggest that early identification of this aggressive form of prostate cancer offers potential for improved outcomes with early introduction of PARP inhibitor-based therapy.See related commentary by Mandigo and Knudsen, p. 1784.

Characterization of HMGB1/2 Interactome in Prostate Cancer by Yeast Two Hybrid Approach: Potential Pathobiological Implications

High mobility group box B (HMGB) proteins are pivotal in the development of cancer. Although the proteomics of prostate cancer (PCa) cells has been reported, the involvement of HMGB proteins and their interactome in PCa is an unexplored field of considerable interest. We describe herein the results of the first HMGB1/HMGB2 interactome approach to PCa. Libraries constructed from the PCa cell line, PC-3, and from patients’ PCa primary tumor have been screened by the yeast 2-hybrid approach (Y2H) using HMGB1 and HMGB2 baits. Functional significance of this PCa HMGB interactome has been validated through expression and prognosis data available on public databases. Copy number alterations (CNA) affecting these newly described HMGB interactome components are more frequent in the most aggressive forms of PCa: those of neuroendocrine origin or castration-resistant PCa. Concordantly, adenocarcinoma PCa samples showing CNA in these genes are also associated with the worse prognosis. These findings open the way to their potential use as discriminatory biomarkers between high and low risk patients. Gene expression of a selected set of these interactome components has been analyzed by qPCR after HMGB1 and HMGB2 silencing. The data show that HMGB1 and HMGB2 control the expression of several of their interactome partners, which might contribute to the orchestrated action of these proteins in PCa

Sex Differences in Cancer Driver Genes and Biomarkers

Cancer differs significantly between men and women; even after adjusting for known epidemiologic risk factors, the sexes differ in incidence, outcome, and response to therapy. These differences occur in many but not all tumor types, and their origins remain largely unknown. Here, we compare somatic mutation profiles between tumors arising in men and in women. We discovered large differences in mutation density and sex biases in the frequency of mutation of specific genes; these differences may be associated with sex biases in DNA mismatch repair genes or microsatellite instability. Sex-biased genes include well-known drivers of cancer such as β-catenin and BAP1 Sex influenced biomarkers of patient outcome, where different genes were associated with tumor aggression in each sex. These data call for increased study and consideration of the molecular role of sex in cancer etiology, progression, treatment, and personalized therapy.Significance: This study provides a comprehensive catalog of sex differences in somatic alterations, including in cancer driver genes, which influence prognostic biomarkers that predict patient outcome after definitive local therapy. Cancer Res; 78(19); 5527-37. ©2018 AACR.

Combination of TMB and CNA Stratifies Prognostic and Predictive Responses to Immunotherapy Across Metastatic Cancer

PURPOSE

Although tumor mutation burden (TMB) has been well known to predict the response to immune checkpoint inhibitors (ICI), lack of randomized clinical trial data has restricted its clinical application. This study aimed to explore the significance and feasibility of biomarker combination based on TMB and copy-number alteration (CNA) for the prognosis of each tumor and prediction for ICI therapy in metastatic pan-cancer milieu.

EXPERIMENTAL DESIGN

Non-ICI-treated MSK pan-cancer cohort was used for prognosis analysis. Three independent immunotherapy cohorts, including non-small cell lung cancer (n = 240), skin cutaneous melanoma (n = 174), and mixed cancer (Dana-Farber, n = 98) patients from previous studies, were analyzed for efficacy of ICI therapy.

RESULTS

TMB and CNA showed optimized combination for the prognosis of most metastatic cancer types, and patients with TMB^lowCNA^low showed better survival. In the predictive analysis, both TMB and CNA were independent predictive factors for ICI therapy. Remarkably, when TMB and CNA were jointly analyzed, those with TMB^highCNA^low showed favorable responses to ICI therapy. Meanwhile, TMB^highCNA^low as a new biomarker showed better prediction for ICI efficacy compared with either TMB-high or CNA-low alone. Furthermore, analysis of the non-ICI-treated MSK pan-cancer cohort supported that the joint stratification of TMB and CNA can be used to categorize tumors into distinct sensitivity to ICI therapy across pan-tumors.

CONCLUSIONS

The combination of TMB and CNA can jointly stratify multiple metastatic tumors into groups with different prognosis and heterogeneous clinical responses to ICI treatment. Patients with TMB^highCNA^low cancer can be an optimal subgroup for ICI therapy.

Integration of Cancer Genomics Data for Tree-based Dimensionality Reduction and Cancer Outcome Prediction

Accurate outcome prediction is crucial for precision medicine and personalized treatment of cancer. Researchers have found that multi-dimensional cancer omics studies outperform each data type (mRNA, microRNA, methylation or somatic copy number alteration) study in human disease research. Existing methods leveraging multiple level of molecular data often suffer from various limitations, e. g., heterogeneity, poor robustness or loss of generality. To overcome these limitations, we presented the tree-based dimensionality reduction approach for the identification of smooth tree graph and developed accurate predictive model for clinical outcome prediction. We demonstrated that 1) Discriminative Dimensionality Reduction via learning a Tree (DDRTree) achieved reduced dimension space tree with statistical significance; 2) Tree based support vector machine (SVM) classifier improved prediction performance of cancer recurrence as compared to t-test based SVM classifier; 3) Tree based SVM classifier was robust with regard to the different number of multi-markers; 4) Combining multiple omics data improved prediction performance of cancer recurrence as compared to a single-omics data; and 5) Tree based SVM classifier achieved similar or better prediction performance when compared to the features from state-of-the-art feature selection methods. Our results demonstrated great potential of the tree-based dimensionality reduction approach based clinical outcome prediction.

Analysis of Tumor Genomic Pathway Alterations Using Broad-Panel Next-Generation Sequencing in Surgically Resected Lung Adenocarcinoma

PURPOSE

The majority of broad-panel tumor genomic profiling has used a gene-centric approach, although much of that data is unused in clinical decision making. We hypothesized that a pathway-centric approach using next-generation sequencing (NGS), combined with conventional clinicopathologic features, may better predict disease-free survival (DFS) in early stage lung adenocarcinoma.

EXPERIMENTAL DESIGN

Utilizing our prospectively maintained database, we analyzed 492 patients with primary, untreated, completely surgically resected lung adenocarcinoma. Ten canonical pathways were analyzed using broad-panel NGS. The correlations of DFS and number (and type) of pathway (NPA) were analyzed using the Kaplan-Meier method and log-rank test. Associations between altered pathways and clinicopathologic variables, as well as identification of actionable therapeutic strategies were explored.

RESULTS

Median NPA for the cohort was two (range, 0-5). Smoking status, solid morphologic appearance on preoperative CT, maximal standardized uptake value, pathologic tumor size, aggressive histologic subtype, lymphovascular invasion, visceral pleural invasion, and positive lymph nodes were significantly associated with NPA (P < 0.05). Of 543 actionable genetic alterations identified, 455 (84%) were within the RTK/RAS pathway. A total of 86 tumors had actionable therapeutic genomic alterations in >1 pathway. On multivariable analysis, higher NPA was significantly associated with worse DFS (HR, 1.31; P = 0.014).

CONCLUSIONS

NPA and specific pathway alterations are associated with clinicopathologic features in patients with surgically resected lung adenocarcinoma. Cell cycle, Hippo, TGFβ, and p53 pathway alterations are associated with poor DFS. Finally, NPA is an independent risk factor for poor DFS in our cohort.See related commentary by Blakely, p. 7269.

Chromosomal Instability in Tumor Initiation and Development

Chromosomal instability (CIN) is one of the major forms of genomic instability in various human cancers and is recognized as a common hallmark of tumorigenesis and heterogeneity. However, some malignant tumors show a paucity of chromosomal alterations, suggesting that tumor progression and evolution can occur in the absence of CIN. It is unclear whether CIN is stable between precursor lesions, primary tumor, and metastases or if it evolves during these steps. In this review, we describe the influence of CIN on the various steps in tumor initiation and development. Given the recognized significant effects of CIN in cancer, CIN-targeted therapeutics could have a major impact on improving clinical outcomes.

Identification of hyper-rewired genomic stress non-oncogene addiction genes across 15 cancer types

Non-oncogene addiction (NOA) genes are essential for supporting the stress-burdened phenotype of tumours and thus vital for their survival. Although NOA genes are acknowledged to be potential drug targets, there has been no large-scale attempt to identify and characterise them as a group across cancer types. Here we provide the first method for the identification of conditional NOA genes and their rewired neighbours using a systems approach. Using copy number data and expression profiles from The Cancer Genome Atlas (TCGA) we performed comparative analyses between high and low genomic stress tumours for 15 cancer types. We identified 101 condition-specific differential coexpression modules, mapped to a high-confidence human interactome, comprising 133 candidate NOA rewiring hub genes. We observe that most modules lose coexpression in the high-stress state and that activated stress modules and hubs take part in homoeostasis maintenance processes such as chromosome segregation, oxireductase activity, mitotic checkpoint (PLK1 signalling), DNA replication initiation and synaptic signalling. We furthermore show that candidate NOA rewiring hubs are unique for each cancer type, but that their respective rewired neighbour genes largely are shared across cancer types.

Cellular and Molecular Mechanisms Underlying Prostate Cancer Development: Therapeutic Implications

Prostate cancer is the most frequent nonskin cancer and second most common cause of cancer-related deaths in man. Prostate cancer is a clinically heterogeneous disease with many patients exhibiting an aggressive disease with progression, metastasis, and other patients showing an indolent disease with low tendency to progression. Three stages of development of human prostate tumors have been identified: intraepithelial neoplasia, adenocarcinoma androgen-dependent, and adenocarcinoma androgen-independent or castration-resistant. Advances in molecular technologies have provided a very rapid progress in our understanding of the genomic events responsible for the initial development and progression of prostate cancer. These studies have shown that prostate cancer genome displays a relatively low mutation rate compared with other cancers and few chromosomal loss or gains. The ensemble of these molecular studies has led to suggest the existence of two main molecular groups of prostate cancers: one characterized by the presence of ERG rearrangements (~50% of prostate cancers harbor recurrent gene fusions involving ETS transcription factors, fusing the 5' untranslated region of the androgen-regulated gene TMPRSS2 to nearly the coding sequence of the ETS family transcription factor ERG) and features of chemoplexy (complex gene rearrangements developing from a coordinated and simultaneous molecular event), and a second one characterized by the absence of ERG rearrangements and by the frequent mutations in the E3 ubiquitin ligase adapter SPOP and/or deletion of CDH1, a chromatin remodeling factor, and interchromosomal rearrangements and SPOP mutations are early events during prostate cancer development. During disease progression, genomic and epigenomic abnormalities accrued and converged on prostate cancer pathways, leading to a highly heterogeneous transcriptomic landscape, characterized by a hyperactive androgen receptor signaling axis.

Molecular Underpinnings Governing Genetic Complexity of ETS-Fusion-Negative Prostate Cancer

Inter- and intra-patient molecular heterogeneity of primary and metastatic prostate cancer (PCa) confers variable clinical outcome and poses a formidable challenge in disease management. High-throughput integrative genomics and functional approaches have untangled the complexity involved in this disease and revealed a spectrum of diverse aberrations prevalent in various molecular subtypes, including ETS fusion negative. Emerging evidence indicates that SPINK1 upregulation, mutations in epigenetic regulators or chromatin modifiers, and SPOP are associated with the ETS-fusion negative subtype. Additionally, patients with defects in a DNA-repair pathway respond to poly-(ADP-ribose)-polymerase (PARP) inhibition therapies. Furthermore, a new class of immunogenic subtype defined by CDK12 biallelic loss has also been identified in ETS-fusion-negative cases. This review focuses on the emerging molecular underpinnings driving key oncogenic aberrations and advancements in therapeutic strategies of this disease.

A Novel Mechanism Driving Poor-Prognosis Prostate Cancer: Overexpression of the DNA Repair Gene, Ribonucleotide Reductase Small Subunit M2 (RRM2)

PURPOSE

Defects in genes in the DNA repair pathways significantly contribute to prostate cancer progression. We hypothesize that overexpression of DNA repair genes may also drive poorer outcomes in prostate cancer. The ribonucleotide reductase small subunit M2 (RRM2) is essential for DNA synthesis and DNA repair by producing dNTPs. It is frequently overexpressed in cancers, but very little is known about its function in prostate cancer.

EXPERIMENTAL DESIGN

The oncogenic activity of RRM2 in prostate cancer cells was assessed by inhibiting or overexpressing RRM2. The molecular mechanisms of RRM2 function were determined. The clinical significance of RRM2 overexpression was evaluated in 11 prostate cancer clinical cohorts. The efficacy of an RRM2 inhibitor (COH29) was assessed in vitro and in vivo. Finally, the mechanism underlying the transcriptional activation of RRM2 in prostate cancer tissue and cells was determined.

RESULTS

Knockdown of RRM2 inhibited its oncogenic function, whereas overexpression of RRM2 promoted epithelial mesenchymal transition in prostate cancer cells. The prognostic value of RRM2 RNA levels in prostate cancer was confirmed in 11 clinical cohorts. Integrating the transcriptomic and phosphoproteomic changes induced by RRM2 unraveled multiple oncogenic pathways downstream of RRM2. Targeting RRM2 with COH29 showed excellent efficacy. Thirteen putative RRM2-targeting transcription factors were bioinformatically identified, and FOXM1 was validated to transcriptionally activate RRM2 in prostate cancer.

CONCLUSIONS

We propose that increased expression of RRM2 is a mechanism driving poor patient outcomes in prostate cancer and that its inhibition may be of significant therapeutic value.

Circulating Tumor Cells as a Predictor of Treatment Response in Clinically Localized Prostate Cancer

PURPOSE

Using nonenrichment-based, potentially more sensitive Epic Sciences circulating tumor cell (CTC) platform, we sought to detect and characterize CTCs in untreated, high-risk localized prostate cancer and to evaluate their clinical implication.

METHODS

Between 2012 and 2015, blood samples were prospectively collected from patients with National Comprehensive Cancer Network high-risk localized prostate cancer undergoing either radiotherapy (XRT) plus androgen deprivation therapy or radical prostatectomy (RP) with curative intent. Samples were analyzed with the Epic Sciences platform with 4^J,6-diamidino-2-phenylindole, CD45, cytokeratin (CK), and androgen receptor (AR) N-terminal staining. CTC counts were correlated with biochemical recurrence (BCR).

RESULTS

A diversity of CTC subtypes, including CK-positive, CK-negative, AR-positive, and CTC clusters, were observed in 73.3% (33 of 45) of patients with evaluable data. The median follow-up was 14.2 months (range, 0.5 to 43.7 months). BCR occurred more frequently in the RP group than XRT (15 of 26 v one of 19), with most patients in the XRT group continuing to receive androgen deprivation therapy. A higher proportion of metastatic events were observed in the RP group (five of 26 v one of 19). In the RP group, BCR and development of metastases were associated with a higher total number of CTCs, AR-positive CTCs, and CTC phenotypic heterogeneity. One patient who developed BCR and metastases quickly after RP had diverse phenotypical CTC subtypes, and single-cell genomic analyses of all detectable CTCs confirmed common prostate cancer copy number alterations and PTEN loss.

CONCLUSION

CTCs can be identified in most patients with high-risk localized prostate cancer before definitive therapy using the Epic Sciences platform. If confirmed in a larger cohort with longer follow-up, phenotypic and genomic characterization of CTCs pretherapy may provide an additional means of risk stratifying patients with newly diagnosed high-risk disease and potentially help identify patients who could require multimodal therapy.

Aneuploidy drives lethal progression in prostate cancer

Aneuploidy, defined as chromosome gains and losses, is a hallmark of cancer. However, compared with other tumor types, extensive aneuploidy is relatively rare in prostate cancer. Thus, whether numerical chromosome aberrations dictate disease progression in prostate cancer patients is not known. Here, we report the development of a method based on whole-transcriptome profiling that allowed us to identify chromosome-arm gains and losses in 333 primary prostate tumors. In two independent cohorts (n = 404) followed prospectively for metastases and prostate cancer-specific death for a median of 15 years, increasing extent of tumor aneuploidy as predicted from the tumor transcriptome was strongly associated with higher risk of lethal disease. The 23% of patients whose tumors had five or more predicted chromosome-arm alterations had 5.3 times higher odds of lethal cancer (95% confidence interval, 2.2 to 13.1) than those with the same Gleason score and no predicted aneuploidy. Aneuploidy was associated with lethality even among men with high-risk Gleason score 8-to-10 tumors. These results point to a key role of aneuploidy in driving aggressive disease in primary prostate cancer.

Sex Disparity and Copy Number Alterations in Esophageal Squamous Cell Carcinoma

Although sex differences in the incidence of esophageal cancer are well-established, the independent prognostic value of sex remains unclear. Recently, several groups have performed comprehensive molecular analyses of esophageal tumors,¹ providing the opportunity to elucidate the underlying genomic bases for epidemiologic observations. We therefore sought to evaluate the effect of sex on esophageal cancer prognosis and to compare genomic data from tumors in men versus women.

Molecular Pathology of High-Grade Prostatic Intraepithelial Neoplasia: Challenges and Opportunities

A better understanding of the early stages of prostate cancer initiation, potentially arising from precursor lesions, may fuel development of powerful approaches for prostate cancer prevention or interception. The best-known candidate for such a precursor lesion has been referred to as high-grade prostatic intraepithelial neoplasia (HGPIN). Although there is significant evidence supporting the notion that such HGPIN lesions can give rise to invasive adenocarcinomas of the prostate, there are also numerous complicating considerations and evidence that cloud the picture in many instances. Notably, recent evidence has suggested that some fraction of such lesions that are morphologically consistent with HGPIN may actually be invasive carcinomas masquerading as HGPIN-a state that we term "postinvasive intraepithelial carcinoma" (PIC). Although the prevalence of such PIC lesions is not fully understood, this and other factors can confound the potential of identifying prostate precursors that can be targeted for disease prevention, interception, or treatment. Here, we review our current understanding of the morphological and molecular pathological features of prostate cancer precursor lesions.

A novel DNA-binding motif in prostate tumor overexpressed-1 (PTOV1) required for the expression of ALDH1A1 and CCNG2 in cancer cells

PTOV1 is a transcription and translation regulator and a promoter of cancer progression. Its overexpression in prostate cancer induces transcription of drug resistance and self-renewal genes, and docetaxel resistance. Here we studied PTOV1 ability to directly activate the transcription of ALDH1A1 and CCNG2 by binding to specific promoter sequences. Chromatin immunoprecipitation and electrophoretic mobility shift assays identified a DNA-binding motif inside the PTOV-A domain with similarities to known AT-hooks that specifically interacts with ALDH1A1 and CCNG2 promoters. Mutation of this AT-hook-like sequence significantly decreased the expression of ALDH1A1 and CCNG2 promoted by PTOV1. Immunohistochemistry revealed the association of PTOV1 with mitotic chromosomes in high grade prostate, colon, bladder, and breast carcinomas. Overexpression of PTOV1, ALDH1A1, and CCNG2 significantly correlated with poor prognosis in prostate carcinomas and with shorter relapse-free survival in colon carcinoma. The previously described interaction with translation complexes and its direct binding to ALDH1A1 and CCNG2 promoters found here reveal the PTOV1 capacity to modulate the expression of critical genes at multiple levels in aggressive cancers. Remarkably, the AT-hook motifs in PTOV1 open possibilities for selective targeting its nuclear and/or cytoplasmic activities.

Identification of gene-phenotype connectivity associated with flavanone naringenin by functional network analysis

Naringenin, extracted from grapefruits and citrus fruits, is a bioactive flavonoid with antioxidative, anti-inflammatory, antifibrogenic, and anticancer properties. In the past two decades, the growth of publications of naringenin in PubMed suggests that naringenin is quickly gaining interest. However, systematically regarding its biological functions connected to its direct and indirect target proteins remains difficult but necessary. Herein, we employed a set of bioinformatic platforms to integrate and dissect available published data of naringenin. Analysis based on DrugBank and the Search Tool for the Retrieval of Interacting Genes/Proteins revealed seven direct protein targets and 102 indirect protein targets. The protein-protein interaction (PPI) network of total 109 naringenin-mediated proteins was next visualized using Cytoscape. What's more, all naringenin-mediated proteins were subject to Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis by the Database for Annotation, Visualization and Integrated Discovery, which resulted in three ESR1-related signaling pathways and prostate cancer pathway. Refined analysis of PPI network and KEGG pathway identified four genes (ESR1, PIK3CA, AKT1, and MAPK1). Further genomic analysis of four genes using cBioPortal indicated that naringenin might exert biological effects via ESR1 signaling axis. In general, this work scrutinized naringenin-relevant knowledge and provided an insight into the regulation and mediation of naringenin on prostate cancer.

The Proteogenomic Landscape of Curable Prostate Cancer

DNA sequencing has identified recurrent mutations that drive the aggressiveness of prostate cancers. Surprisingly, the influence of genomic, epigenomic, and transcriptomic dysregulation on the tumor proteome remains poorly understood. We profiled the genomes, epigenomes, transcriptomes, and proteomes of 76 localized, intermediate-risk prostate cancers. We discovered that the genomic subtypes of prostate cancer converge on five proteomic subtypes, with distinct clinical trajectories. ETS fusions, the most common alteration in prostate tumors, affect different genes and pathways in the proteome and transcriptome. Globally, mRNA abundance changes explain only ∼10% of protein abundance variability. As a result, prognostic biomarkers combining genomic or epigenomic features with proteomic ones significantly outperform biomarkers comprised of a single data type.

APOBEC Mutagenesis and Copy-Number Alterations Are Drivers of Proteogenomic Tumor Evolution and Heterogeneity in Metastatic Thoracic Tumors

Intratumor mutational heterogeneity has been documented in primary non-small-cell lung cancer. Here, we elucidate mechanisms of tumor evolution and heterogeneity in metastatic thoracic tumors (lung adenocarcinoma and thymic carcinoma) using whole-exome and transcriptome sequencing, SNP array for copy-number alterations (CNAs), and mass-spectrometry-based quantitative proteomics of metastases obtained by rapid autopsy. APOBEC mutagenesis, promoted by increased expression of APOBEC3 region transcripts and associated with a high-risk APOBEC3 germline variant, correlated with mutational tumor heterogeneity. TP53 mutation status was associated with APOBEC hypermutator status. Interferon pathways were enriched in tumors with high APOBEC mutagenesis and IFN-γ-induced expression of APOBEC3B in lung adenocarcinoma cells, suggesting that the immune microenvironment may promote mutational heterogeneity. CNAs occurring late in tumor evolution correlated with downstream transcriptomic and proteomic heterogeneity, although global proteomic heterogeneity was significantly greater than transcriptomic and CNA heterogeneity. These results illustrate key mechanisms underlying multi-dimensional heterogeneity in metastatic thoracic tumors.

The Genomics of Prostate Cancer: A Historic Perspective

The genomics of prostate cancer (PCA) has been difficult to study compared with some other cancer types for a multitude of reasons, despite significant efforts since the early 1980s. Overcoming some of these obstacles has paved the way for greater insight into the genomics of PCA. The advent of high-throughput technologies coming from the initial use of microsatellite and oligonucleotide probes gave rise to techniques like comparative genomic hybridization (CGH). With the introduction of massively parallel genomic sequencing, referred to as next-generation sequencing (NGS), a deeper understanding of cancer genomics in general has occurred. Along with these technologic advances, there has been the development of computational biology and statistical approaches to address novel large data sets characterized by single base resolution. This review will provide a historic perspective of PCA genomics with an emphasis on the cardinal mutations and alterations observed to be consistently seen in PCA for both hormone-naïve localized PCA and castration-resistant prostate cancer (CRPC). There will be a focus on alterations that have the greatest potential to play a role in disease progression and therapy management.

An overview of publicly available patient-centered prostate cancer datasets

Prostate cancer (PCa) is the second most common cancer in men, and the second leading cause of death from cancer in men. Many studies on PCa have been carried out, each taking much time before the data is collected and ready to be analyzed. However, on the internet there is already a wide range of PCa datasets available, which could be used for data mining, predictive modelling or other purposes, reducing the need to setup new studies to collect data. In the current scientific climate, moving more and more to the analysis of "big data" and large, international, multi-site projects using a modern IT infrastructure, these datasets could be proven extremely valuable. This review presents an overview of publicly available patient-centered PCa datasets, divided into three categories (clinical, genomics and imaging) and an "overall" section to enable researchers to select a suitable dataset for analysis, without having to go through days of work to find the right data. To acquire a list of human PCa databases, scientific literature databases and academic social network sites were searched. We also used the information from other reviews. All databases in the combined list were then checked for public availability. Only databases that were either directly publicly available or available after signing a research data agreement or retrieving a free login were selected for inclusion in this review. Data should be available to commercial parties as well. This paper focuses on patient-centered data, so the genomics data section does not include gene-centered databases or pathway-centered databases. We identified 42 publicly available, patient-centered PCa datasets. Some of these consist of different smaller datasets. Some of them contain combinations of datasets from the three data domains: clinical data, imaging data and genomics data. Only one dataset contains information from all three domains. This review presents all datasets and their characteristics: number of subjects, clinical fields, imaging modalities, expression data, mutation data, biomarker measurements, etc. Despite all the attention that has been given to making this overview of publicly available databases as extensive as possible, it is very likely not complete, and will also be outdated soon. However, this review might help many PCa researchers to find suitable datasets to answer the research question with, without the need to start a new data collection project. In the coming era of big data analysis, overviews like this are becoming more and more useful.

The Identification of Potential Biomarkers and Biological Pathways in Prostate Cancer

Purpose: The present study aims to explore the potential mechanisms contributing to prostate cancer (PCa), screen the hub genes, and identify potential biomarkers and correlated pathways of PCa progression.

Methods: The PCa gene expression profile GSE3325 was operated to analyze the differentially expressed genes (DEGs). DAVID was used to evaluate Gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. A protein-protein interaction (PPI) network was constructed to visualize interactions of the hub genes. The prognostic and diagnostic analysis of these hub genes was carried out to evaluate their potential effects on PCa.

Results: A total of 847 DEGs were identified (427 upregulated genes and 420 downregulated genes). Meanwhile, top15 hub genes were showed. GO analysis displayed that the DEGs were mainly enriched in cell cycle, DNA damage response, signal transduction by p53 class mediator resulting in cell cycle arrest and proteinaceous extracellular matrix. KEGG analysis indicated the DEGs were enriched in the p53 signaling pathway and cell cycle pathway. The GO and KEGG enrichment analyses for the DEGs disclosed important biological features of PCa. PPI network showed the interaction of top 15 hub genes. Gene Set Enrichment Analysis (GSEA) revealed that some of the hub genes were associated with biochemical recurrence (BCR) and metastasis of PCa. Some top hub genes were distinctive and new discoveries compared with that of the existing associated researches.

Conclusions: Our analysis revealed that the changes of cell cycle and p53 signaling pathway are two major signatures of PCa. CENPA, KIF20A and CDCA8 might promote the tumorigenesis and progression of PCa, especially in BCR and metastasis, which could be novel therapeutic targets and biomarkers for diagnosis, prognosis of PCa.

Genomic Evaluation of Multiparametric Magnetic Resonance Imaging-visible and -nonvisible Lesions in Clinically Localised Prostate Cancer

BACKGROUND

The prostate cancer (PCa) diagnostic pathway is undergoing a radical change with the introduction of multiparametric magnetic resonance imaging (mpMRI), genomic testing, and different prostate biopsy techniques. It has been proposed that these tests should be used in a sequential manner to optimise risk stratification.

OBJECTIVE

To characterise the genomic, epigenomic, and transcriptomic features of mpMRI-visible and -nonvisible PCa in clinically localised disease.

DESIGN, SETTING, AND PARTICIPANTS

Multicore analysis of fresh prostate tissue sampled immediately after radical prostatectomy was performed for intermediate- to high-risk PCa.

INTERVENTION

Low-pass whole-genome, exome, methylation, and transcriptome profiling of patient tissue cores taken from microscopically benign and cancerous areas in the same prostate. Circulating free and germline DNA was assessed from the blood of five patients.

OUTCOME MEASUREMENT AND STATISTICAL ANALYSIS

Correlations between preoperative mpMRI and genomic characteristics of tumour and benign prostate samples were assessed. Gene profiles for individual tumour cores were correlated with existing genomic classifiers currently used for prognostication.

RESULTS AND LIMITATIONS

A total of 43 prostate cores (22 tumour and 21 benign) were profiled from six whole prostate glands. Of the 22 tumour cores, 16 were tumours visible and six were tumours nonvisible on mpMRI. Intratumour genomic, epigenomic, and transcriptomic heterogeneity was found within mpMRI-visible lesions. This could potentially lead to misclassification of patients using signatures based on copy number or RNA expression. Moreover, three of the six cores obtained from mpMRI-nonvisible tumours harboured one or more genetic alterations commonly observed in metastatic castration-resistant PCa. No circulating free DNA alterations were found. Limitations include the small cohort size and lack of follow-up.

CONCLUSIONS

Our study supports the continued use of systematic prostate sampling in addition to mpMRI, as avoidance of systematic biopsies in patients with negative mpMRI may mean that clinically significant tumours harbouring genetic alterations commonly seen in metastatic PCa are missed. Furthermore, there is inconsistency in individual genomics when genomic classifiers are applied.

PATIENT SUMMARY

Our study shows that tumour heterogeneity within prostate tumours visible on multiparametric magnetic resonance imaging (mpMRI) can lead to misclassification of patients if only one core is used for genomic analysis. In addition, some cancers that were missed by mpMRI had genomic aberrations that are commonly seen in advanced metastatic prostate cancer. Avoiding biopsies in mpMRI-negative cases may mean that such potentially lethal cancers are missed.