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Prostate cancer is one of the most heritable cancers. Hundreds of germline polymorphisms have been linked to prostate cancer diagnosis and prognosis. Polygenic risk scores can predict genetic risk of a prostate cancer diagnosis. Although these scores inform the probability of developing a tumor, it remains unknown how germline risk influences the tumor molecular evolution. We cultivated a cohort of 1250 localized European-descent patients with germline and somatic DNA profiling. Men of European descent with higher genetic risk were diagnosed earlier and had less genomic instability and fewer driver genes mutated. Higher genetic risk was associated with better outcome. These data imply a polygenic "two-hit" model where germline risk reduces the number of somatic alterations required for tumorigenesis. These findings support further clinical studies of polygenic risk scores as inexpensive and minimally invasive adjuncts to standard risk stratification. Further studies are required to interrogate generalizability to more ancestrally and clinically diverse populations.

Abstract Background Prostate cancer (PrCa) displays resistance to radiotherapy (RT) and requires radiotherapy dose escalation which is associated with greater toxicity. This highlights a need to develop radiation sensitizers to improve the efficacy of RT in PrCa. Ionizing radiation (IR) stimulates pathways of IR-resistance and survival mediated by the protein kinase Akt but it also activates the metabolic energy sensor and tumor suppressor AMP-Activated Protein Kinase (AMPK). Here, we examined the effects of the polyphenol resveratrol (RSV) on the IR-induced inhibition of cell survival, modulation of cell cycle and molecular responses in PrCa cells. Methods Androgen-insensitive (PC3), sensitive (22RV1) PrCa and PNT1A normal prostate epithelial cells were treated with RSV alone (2.5-10 μM) or in combination with IR (2-8 Gy). Clonogenic assays, cell cycle analysis, microscopy and immunoblotting were performed to assess survival, cell cycle progression and molecular responses. Results RSV (2.5-5 μM) inhibited clonogenic survival of PC3 and 22RV1 cells but not of normal prostate PNT1A cells. RSV specifically sensitized PrCa cells to IR, induced cell cycle arrest at G1-S phase and enhanced IR-induced nuclear aberrations and apoptosis. RSV enhanced IR-induced expression of DNA damage (γH2Ax) and apoptosis (cleaved-caspase 3) markers as well as of the cell cycle regulators p53, p21cip1 and p27kip1. RSV enhanced IR-activation of ATM and AMPK but inhibited basal and IR-induced phosphorylation of Akt. Conclusions Our results suggest that RSV arrests cell cycle, promotes apoptosis and sensitizes PrCa cells to IR likely through a desirable dual action to activate the ATM-AMPK-p53-p21cip1/p27kip1 and inhibit the Akt signalling pathways.

Abstract Background Chemicals from occupational exposure and components of cigarette smoke can cause DNA damage in bladder urothelium. Failure to repair DNA damage by DNA repair proteins may result in mutations leading to genetic instability and the development of bladder cancer. Immunohistochemistry studies have shown DNA damage signal activation in precancerous bladder lesions which is lost on progression, suggesting that the damage signalling mechanism acts as a brake to further tumorigenesis. Single nucleotide polymorphisms (SNPs) in DSB signalling genes may alter protein function. We hypothesized that SNPs in DSB signalling genes may modulate predisposition to bladder cancer and influence the effects of environmental exposures. Methods We recruited 771 cases and 800 controls (573 hospital-based and 227 population-based from a previous case-control study) and interviewed them regarding their smoking habits and occupational history. DNA was extracted from a peripheral blood sample and genotyping of 24 SNPs in MRE11, NBS1, RAD50, H2AX and ATM was undertaken using an allelic discrimination method (Taqman). Results Smoking and occupational dye exposure were strongly associated with bladder cancer risk. Using logistic regression adjusting for age, sex, smoking and occupational dye exposure, there was a marginal increase in risk of bladder cancer for an MRE11 3'UTR SNP (rs2155209, adjusted odds ratio 1.54 95% CI (1.13–2.08, p = 0.01) for individuals homozygous for the rare allele compared to those carrying the common homozygous or heterozygous genotype). However, in the hospital-based controls, the genotype distribution for this SNP deviated from Hardy-Weinberg equilibrium. None of the other SNPs showed an association with bladder cancer and we did not find any significant interaction between any of these polymorphisms and exposure to smoking or dye exposure. Conclusion Apart from a possible effect for one MRE11 3'UTR SNP, our study does not support the hypothesis that SNPs in DSB signaling genes modulate predisposition to bladder cancer.

Replicative immortality is a hallmark of cancer, and can be achieved through telomere lengthening and maintenance. Although the role of telomere length in cancer has been well studied, its association to genomic features is less well known. Here, we report the telomere lengths of 392 localized prostate cancer tumours and characterize their relationship to genomic, transcriptomic and proteomic features. Shorter tumour telomere lengths are associated with elevated genomic instability, including single-nucleotide variants, indels and structural variants. Genes involved in cell proliferation and signaling are correlated with tumour telomere length at all levels of the central dogma. Telomere length is also associated with multiple clinical features of a tumour. Longer telomere lengths in non-tumour samples are associated with a lower rate of biochemical relapse. In summary, we describe the multi-level integration of telomere length, genomics, transcriptomics and proteomics in localized prostate cancer.

Driver gene mutations that are more prevalent in metastatic, castration-resistant prostate cancer (mCRPC) than localized disease represent candidate prognostic biomarkers. We analyze 1,844 localized (1,289) or mCRPC (555) tumors and quantify the prevalence of 113 somatic driver single nucleotide variants (SNVs), copy number aberrations (CNAs), and structural variants (SVs) in each state. One-third are significantly more prevalent in mCRPC than expected while a quarter are less prevalent. Mutations in AR and its enhancer are more prevalent in mCRPC, as are those in TP53, MYC, ZNRF3 and PRKDC. ZNRF3 loss is associated with decreased ZNRF3 mRNA abundance, WNT, cell cycle & PRC1/2 activity, and genomic instability. ZNRF3 loss, RNA downregulation and hypermethylation are prognostic of metastasis and overall survival, independent of clinical and pathologic indices. These data demonstrate a strategy for identifying biomarkers of localized cancer aggression, with ZNRF3 loss as a predictor of metastasis in prostate cancer.

BackgroundThe development of noninvasive tests for the early detection of aggressive prostate tumors is a major unmet clinical need. miRNAs are promising noninvasive biomarkers: they play essential roles in tumorigenesis, are stable under diverse analytical conditions, and can be detected in body fluids.MethodsWe measured the longitudinal stability of 673 miRNAs by collecting serial urine samples from 10 patients with localized prostate cancer. We then measured temporally stable miRNAs in an independent training cohort (n = 99) and created a biomarker predictive of Gleason grade using machine-learning techniques. Finally, we validated this biomarker in an independent validation cohort (n = 40).ResultsWe found that each individual has a specific urine miRNA fingerprint. These fingerprints are temporally stable and associated with specific biological functions. We identified seven miRNAs that were stable over time within individual patients and integrated them with machine-learning techniques to create a novel biomarker for prostate cancer that overcomes interindividual variability. Our urine biomarker robustly identified high-risk patients and achieved similar accuracy as tissue-based prognostic markers (area under the receiver operating characteristic = 0.72, 95% confidence interval = 0.69 to 0.76 in the training cohort, and area under the receiver operating characteristic curve = 0.74, 95% confidence interval = 0.55 to 0.92 in the validation cohort).ConclusionsThese data highlight the importance of quantifying intra- and intertumoral heterogeneity in biomarker development. This noninvasive biomarker may usefully supplement invasive or expensive radiologic- and tissue-based assays.

Many primary tumours have low levels of molecular oxygen (hypoxia), and hypoxic tumours respond poorly to therapy. Pan-cancer molecular hallmarks of tumour hypoxia remain poorly understood, with limited comprehension of its associations with specific mutational processes, non-coding driver genes and evolutionary features. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumour types, we quantify hypoxia in 1188 tumours spanning 27 cancer types. Elevated hypoxia associates with increased mutational load across cancer types, irrespective of underlying mutational class. The proportion of mutations attributed to several mutational signatures of unknown aetiology directly associates with the level of hypoxia, suggesting underlying mutational processes for these signatures. At the gene level, driver mutations in TP53, MYC and PTEN are enriched in hypoxic tumours, and mutations in PTEN interact with hypoxia to direct tumour evolutionary trajectories. Overall, hypoxia plays a critical role in shaping the genomic and evolutionary landscapes of cancer.

Prostate cancer is the second most commonly diagnosed malignancy among men worldwide. Recurrently mutated in primary and metastatic prostate tumors, FOXA1 encodes a pioneer transcription factor involved in disease onset and progression through both androgen receptor-dependent and androgen receptor-independent mechanisms. Despite its oncogenic properties however, the regulation of FOXA1 expression remains unknown. Here, we identify a set of six cis-regulatory elements in the FOXA1 regulatory plexus harboring somatic single-nucleotide variants in primary prostate tumors. We find that deletion and repression of these cis-regulatory elements significantly decreases FOXA1 expression and prostate cancer cell growth. Six of the ten single-nucleotide variants mapping to FOXA1 regulatory plexus significantly alter the transactivation potential of cis-regulatory elements by modulating the binding of transcription factors. Collectively, our results identify cis-regulatory elements within the FOXA1 plexus mutated in primary prostate tumors as potential targets for therapeutic intervention.

Oncogenesis is driven by germline, environmental and stochastic factors. It is unknown how these interact to produce the molecular phenotypes of tumors. We therefore quantified the influence of germline polymorphisms on the somatic epigenome of 589 localized prostate tumors. Predisposition risk loci influence a tumor's epigenome, uncovering a mechanism for cancer susceptibility. We identified and validated 1,178 loci associated with altered methylation in tumoral but not nonmalignant tissue. These tumor methylation quantitative trait loci influence chromatin structure, as well as RNA and protein abundance. One prominent tumor methylation quantitative trait locus is associated with AKT1 expression and is predictive of relapse after definitive local therapy in both discovery and validation cohorts. These data reveal intricate crosstalk between the germ line and the epigenome of primary tumors, which may help identify germline biomarkers of aggressive disease to aid patient triage and optimize the use of more invasive or expensive diagnostic assays.

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.

Neuroendocrine prostate cancer (NEPC), a lethal form of the disease, is characterized by loss of androgen receptor (AR) signaling during neuroendocrine transdifferentiation, which results in resistance to AR-targeted therapy. Clinically, genomically and epigenetically, NEPC resembles other types of poorly differentiated neuroendocrine tumors (NETs). Through pan-NET analyses, we identified ONECUT2 as a candidate master transcriptional regulator of poorly differentiated NETs. ONECUT2 ectopic expression in prostate adenocarcinoma synergizes with hypoxia to suppress androgen signaling and induce neuroendocrine plasticity. ONEUCT2 drives tumor aggressiveness in NEPC, partially through regulating hypoxia signaling and tumor hypoxia. Specifically, ONECUT2 activates SMAD3, which regulates hypoxia signaling through modulating HIF1α chromatin-binding, leading NEPC to exhibit higher degrees of hypoxia compared to prostate adenocarcinomas. Treatment with hypoxia-activated prodrug TH-302 potently reduces NEPC tumor growth. Collectively, these results highlight the synergy between ONECUT2 and hypoxia in driving NEPC, and emphasize the potential of hypoxia-directed therapy for NEPC patients.

Many primary tumours have low levels of molecular oxygen (hypoxia). Hypoxic tumours are more likely to metastasize to distant sites and respond poorly to multiple therapies. Surprisingly, then, the pan-cancer molecular hallmarks of tumour hypoxia remain poorly understood, with limited understanding of its associations with specific mutational processes, non-coding driver genes and evolutionary features. To fill this gap, we quantified hypoxia in 1,188 tumours spanning 27 cancer types. We show that elevated hypoxia is associated with increased mutational load across cancers, irrespective of the underlying mutational class. The proportion of mutations attributed to several mutational signatures of unknown aetiology are directly associated with the level of hypoxia, suggesting underlying mutational processes for these signatures. At the gene level, driver mutations in TP53, MYC and PTEN are enriched in tumours with high hypoxia, and mutations in PTEN interact with hypoxia to direct the evolutionary trajectory of tumours. Overall, this work demonstrates that hypoxia plays a critical role in shaping the genomic landscape of cancer.

Identifying the earliest somatic changes in prostate cancer can give important insights into tumor evolution and aids in stratifying high- from low-risk disease. We integrated whole genome, transcriptome and methylome analysis of early-onset prostate cancers (diagnosis ≤55 years). Characterization across 292 prostate cancer genomes revealed age-related genomic alterations and a clock-like enzymatic-driven mutational process contributing to the earliest mutations in prostate cancer patients. Our integrative analysis identified four molecular subgroups, including a particularly aggressive subgroup with recurrent duplications associated with increased expression of ESRP1, which we validate in 12,000 tissue microarray tumors. Finally, we combined the patterns of molecular co-occurrence and risk-based subgroup information to deconvolve the molecular and clinical trajectories of prostate cancer from single patient samples.

BackgroundInvasive cribriform and intraductal carcinoma (CR/IDC) is associated with adverse outcome of prostate cancer patients. The aim of this study was to determine the molecular aberrations associated with CR/IDC in primary prostate cancer, focusing on genomic instability and somatic copy number alterations (CNA).MethodsWhole-slide images of The Cancer Genome Atlas Project (TCGA, N = 260) and the Canadian Prostate Cancer Genome Network (CPC-GENE, N = 199) radical prostatectomy datasets were reviewed for Gleason score (GS) and presence of CR/IDC. Genomic instability was assessed by calculating the percentage of genome altered (PGA). Somatic copy number alterations (CNA) were determined using Fisher-Boschloo tests and logistic regression. Primary analysis were performed on TCGA (N = 260) as discovery and CPC-GENE (N = 199) as validation set.ResultsCR/IDC growth was present in 80/260 (31%) TCGA and 76/199 (38%) CPC-GENE cases. Patients with CR/IDC and ≥ GS 7 had significantly higher PGA than men without this pattern in both TCGA (2.2 fold; p = 0.0003) and CPC-GENE (1.7 fold; p = 0.004) cohorts. CR/IDC growth was associated with deletions of 8p, 16q, 10q23, 13q22, 17p13, 21q22, and amplification of 8q24. CNAs comprised a total of 1299 gene deletions and 369 amplifications in the TCGA dataset, of which 474 and 328 events were independently validated, respectively. Several of the affected genes were known to be associated with aggressive prostate cancer such as loss of PTEN, CDH1, BCAR1 and gain of MYC. Point mutations in TP53, SPOP and FOXA1were also associated with CR/IDC, but occurred less frequently than CNAs.ConclusionsCR/IDC growth is associated with increased genomic instability clustering to genetic regions involved in aggressive prostate cancer. Therefore, CR/IDC is a pathologic substrate for progressive molecular tumour derangement.

BackgroundPlatform-specific error profiles necessitate confirmatory studies where predictions made on data generated using one technology are additionally verified by processing the same samples on an orthogonal technology. However, verifying all predictions can be costly and redundant, and testing a subset of findings is often used to estimate the true error profile.ResultsTo determine how to create subsets of predictions for validation that maximize accuracy of global error profile inference, we developed Valection, a software program that implements multiple strategies for the selection of verification candidates. We evaluated these selection strategies on one simulated and two experimental datasets.ConclusionsValection is implemented in multiple programming languages, available at: http://labs.oicr.on.ca/boutros-lab/software/valection.

BackgroundHypoxia is associated with a poor prognosis in prostate cancer. This work aimed to derive and validate a hypoxia-related mRNA signature for localized prostate cancer.MethodHypoxia genes were identified in vitro via RNA-sequencing and combined with in vivo gene co-expression analysis to generate a signature. The signature was independently validated in eleven prostate cancer cohorts and a bladder cancer phase III randomized trial of radiotherapy alone or with carbogen and nicotinamide (CON).ResultsA 28-gene signature was derived. Patients with high signature scores had poorer biochemical recurrence free survivals in six of eight independent cohorts of prostatectomy-treated patients (Log rank test P

Prostate cancer represents a substantial clinical challenge because it is difficult to predict outcome and advanced disease is often fatal. We sequenced the whole genomes of 112 primary and metastatic prostate cancer samples. From joint analysis of these cancers with those from previous studies (930 cancers in total), we found evidence for 22 previously unidentified putative driver genes harboring coding mutations, as well as evidence for NEAT1 and FOXA1 acting as drivers through noncoding mutations. Through the temporal dissection of aberrations, we identified driver mutations specifically associated with steps in the progression of prostate cancer, establishing, for example, loss of CHD1 and BRCA2 as early events in cancer development of ETS fusion-negative cancers. Computational chemogenomic (canSAR) analysis of prostate cancer mutations identified 11 targets of approved drugs, 7 targets of investigational drugs, and 62 targets of compounds that may be active and should be considered candidates for future clinical trials.

Summary:The NanoString System is a well-established technology for measuring RNA and DNA abundance. Although it can estimate copy number variation, relatively few tools support analysis of these data. To address this gap, we created NanoStringNormCNV, an R package for pre-processing and copy number variant calling from NanoString data. This package implements algorithms for pre-processing, quality-control, normalization and copy number variation detection. A series of reporting and data visualization methods support exploratory analyses. To demonstrate its utility, we apply it to a new dataset of 96 genes profiled on 41 prostate tumour and 24 matched normal samples. Availability and implementation:NanoStringNormCNV is implemented in R and is freely available at http://labs.oicr.on.ca/boutros-lab/software/nanostringnormcnv. Contact:paul.boutros@oicr.on.ca. Supplementary information:Supplementary data are available at Bioinformatics online.

Nuclear mutations are well known to drive tumor incidence, aggression and response to therapy. By contrast, the frequency and roles of mutations in the maternally inherited mitochondrial genome are poorly understood. Here we sequence the mitochondrial genomes of 384 localized prostate cancer patients, and identify a median of one mitochondrial single-nucleotide variant (mtSNV) per patient. Some of these mtSNVs occur in recurrent mutational hotspots and associate with aggressive disease. Younger patients have fewer mtSNVs than those who diagnosed at an older age. We demonstrate strong links between mitochondrial and nuclear mutational profiles, with co-occurrence between specific mutations. For example, certain control region mtSNVs co-occur with gain of the MYC oncogene, and these mutations are jointly associated with patient survival. These data demonstrate frequent mitochondrial mutation in prostate cancer, and suggest interplay between nuclear and mitochondrial mutational profiles in prostate cancer.In prostate cancer, the role of mutations in the maternally-inherited mitochondrial genome are not well known. Here, the authors demonstrate frequent, age-dependent mitochondrial mutation in prostate cancer. Strong links between mitochondrial and nuclear mutational profiles are associated with clinical aggressivity.

Radioresistance remains a significant obstacle in the treatment of Prostate Cancer (PCa). To simulate the clinical scenario of irradiation resistance (IRR), we created DU145-IRR PCa cell lines by treatment with 2 Gy daily IR for 59 fractions. DU145-IRR cells acquired an aggressive phenotype as evidenced by increased clonogenic survival, tumorigenic potential and invasiveness. We performed transcriptome profiling to discover dysregulated genes in DU145-IRR cells and identified the long non-coding RNA (lncRNA), Urothelial carcinoma-associated 1 (UCA1). We first investigated the role of UCA1 in radiation response and found that UCA1 abundance was significantly higher in DU145-IRR cells compared to control cells. UCA1 siRNA-knockdown reversed the aggressive phenotype and significantly increased sensitivity to IR. UCA1 depletion inhibited growth, induced cell cycle arrest at the G2/M transition and decreased activation of the pro-survival Akt pathway. We then studied the clinical significance of UCA1 expression in two independent cohorts of PCa patients: MSKCC (130 patients) and CPC-GENE (209 patients). UCA1 over-expression was associated with decreased 5-year disease-free survival in MSKCC patients (HR = 2.9; p = 0.007) and a trend toward lower biochemical recurrence-free survival in CPC-GENE patients (HR = 2.7; p = 0.05). We showed for the first time that UCA1 depletion induces radiosensitivity, decreases proliferative capacity and disrupts cell cycle progression, which may occur through altered Akt signaling and induced cell cycle arrest at the G2/M transition. Our results indicate that UCA1 might have prognostic value in PCa and be a potential therapeutic target.

Germline mutations in the BRCA2 tumour suppressor are associated with both an increased lifetime risk of developing prostate cancer (PCa) and increased risk of aggressive disease. To understand this aggression, here we profile the genomes and methylomes of localized PCa from 14 carriers of deleterious germline BRCA2 mutations (BRCA2-mutant PCa). We show that BRCA2-mutant PCa harbour increased genomic instability and a mutational profile that more closely resembles metastastic than localized disease. BRCA2-mutant PCa shows genomic and epigenomic dysregulation of the MED12L/MED12 axis, which is frequently dysregulated in metastatic castration-resistant prostate cancer (mCRPC). This dysregulation is enriched in BRCA2-mutant PCa harbouring intraductal carcinoma (IDC). Microdissection and sequencing of IDC and juxtaposed adjacent non-IDC invasive carcinoma in 10 patients demonstrates a common ancestor to both histopathologies. Overall we show that localized castration-sensitive BRCA2-mutant tumours are uniquely aggressive, due to de novo aberration in genes usually associated with metastatic disease, justifying aggressive initial treatment.

Radioresistance remains a significant obstacle in the treatment of Prostate Cancer (PCa). To simulate the clinical scenario of irradiation resistance (IRR), we created DU145-IRR PCa cell lines by treatment with 2 Gy daily IR for 59 fractions. DU145-IRR cells acquired an aggressive phenotype as evidenced by increased clonogenic survival, tumorigenic potential and invasiveness. We performed transcriptome profiling to discover dysregulated genes in DU145-IRR cells and identified the long non-coding RNA (lncRNA), Urothelial carcinoma-associated 1 (UCA1). We first investigated the role of UCA1 in radiation response and found that UCA1 abundance was significantly higher in DU145-IRR cells compared to control cells. UCA1 siRNA-knockdown reversed the aggressive phenotype and significantly increased sensitivity to IR. UCA1 depletion inhibited growth, induced cell cycle arrest at the G2/M transition and decreased activation of the pro-survival Akt pathway. We then studied the clinical significance of UCA1 expression in two independent cohorts of PCa patients: MSKCC (130 patients) and CPC-GENE (209 patients). UCA1 over-expression was associated with decreased 5-year disease-free survival in MSKCC patients (HR = 2.9; p = 0.007) and a trend toward lower biochemical recurrence-free survival in CPC-GENE patients (HR = 2.7; p = 0.05). We showed for the first time that UCA1 depletion induces radiosensitivity, decreases proliferative capacity and disrupts cell cycle progression, which may occur through altered Akt signaling and induced cell cycle arrest at the G2/M transition. Our results indicate that UCA1 might have prognostic value in PCa and be a potential therapeutic target.

BackgroundIt is extremely common to need to select a subset of reads from a BAM file based on their specific properties. Typically, a user unpacks the BAM file to a text stream using SAMtools, parses and filters the lines using AWK, then repacks them using SAMtools. This process is tedious and error-prone. In particular, when working with many columns of data, mix-ups are common and the bit field containing the flags is unintuitive. There are several libraries for reading BAM files, such as Bio-SamTools for Perl and pysam for Python. Both allow access to the BAM's read information and can filter reads, but require substantial boilerplate code; this is high overhead for mostly ad hoc filtering.ResultsWe have created a query language that gathers reads using a collection of predicates and common logical connectives. Queries run faster than equivalents and can be compiled to native code for embedding in larger programs.ConclusionsBAMQL provides a user-friendly, powerful and performant way to extract subsets of BAM files for ad hoc analyses or integration into applications. The query language provides a collection of predicates beyond those in SAMtools, and more flexible connectives.

Genome-wide DNA sequencing was used to decrypt the phylogeny of multiple samples from distinct areas of cancer and morphologically normal tissue taken from the prostates of three men. Mutations were present at high levels in morphologically normal tissue distant from the cancer, reflecting clonal expansions, and the underlying mutational processes at work in morphologically normal tissue were also at work in cancer. Our observations demonstrate the existence of ongoing abnormal mutational processes, consistent with field effects, underlying carcinogenesis. This mechanism gives rise to extensive branching evolution and cancer clone mixing, as exemplified by the coexistence of multiple cancer lineages harboring distinct ERG fusions within a single cancer nodule. Subsets of mutations were shared either by morphologically normal and malignant tissues or between different ERG lineages, indicating earlier or separate clonal cell expansions. Our observations inform on the origin of multifocal disease and have implications for prostate cancer therapy in individual cases.

The high morbidity and mortality of patients with esophageal (E) and gastro-esophageal junction (GEJ) cancers, warrants new pre-clinical models for drug testing. The utility of primary tumor xenografts (PTXGs) as pre-clinical models was assessed. Clinicopathological, immunohistochemical markers (p53, p16, Ki-67, Her-2/neu and EGFR), and global mRNA abundance profiles were evaluated to determine selection biases of samples implanted or engrafted, compared with the underlying population. Nine primary E/GEJ adenocarcinoma xenograft lines were further characterized for the spectrum and stability of gene/protein expression over passages. Seven primary esophageal adenocarcinoma xenograft lines were treated with individual or combination chemotherapy. Tumors that were implanted (n=55) in NOD/SCID mice had features suggestive of more aggressive biology than tumors that were never implanted (n=32). Of those implanted, 21/55 engrafted; engraftment was associated with poorly differentiated tumors (p=0.04) and older patients (p=0.01). Expression of immunohistochemical markers were similar between patient sample and corresponding xenograft. mRNA differences observed between patient tumors and first passage xenografts were largely due to loss of human stroma in xenografts. mRNA patterns of early vs late passage xenografts and of small vs large tumors of the same passage were similar. Complete resistance was present in 2/7 xenografts while the remaining tumors showed varying degrees of sensitivity, that remained constant across passages. Because of their ability to recapitulate primary tumor characteristics during engraftment and across serial passaging, PTXGs can be useful clinical systems for assessment of drug sensitivity of human E/GEJ cancers.

BackgroundChromothripsis, a newly discovered type of complex genomic rearrangement, has been implicated in the evolution of several types of cancers. To date, it has been described in bone cancer, SHH-medulloblastoma and acute myeloid leukemia, amongst others, however there are still no formal or automated methods for detecting or annotating it in high throughput sequencing data. As such, findings of chromothripsis are difficult to compare and many cases likely escape detection altogether.ResultsWe introduce ShatterProof, a software tool for detecting and quantifying chromothriptic events. ShatterProof takes structural variation calls (translocations, copy-number variations, short insertions and loss of heterozygosity) produced by any algorithm and using an operational definition of chromothripsis performs robust statistical tests to accurately predict the presence and location of chromothriptic events. Validation of our tool was conducted using clinical data sets including matched normal, prostate cancer samples in addition to the colorectal cancer and SCLC data sets used in the original description of chromothripsis.ConclusionsShatterProof is computationally efficient, having low memory requirements and near linear computation time. This allows it to become a standard component of sequencing analysis pipelines, enabling researchers to routinely and accurately assess samples for chromothripsis. Source code and documentation can be found at http://search.cpan.org/~sgovind/Shatterproof.

Despite the use of clinical prognostic factors (PSA, T-category and Gleason score), 20-60% of localized prostate cancers (PCa) fail primary local treatment. Herein, we determined the prognostic importance of main sensors of the DNA damage response (DDR): MRE11A, RAD50, NBN, ATM, ATR and PRKDC. We studied copy number alterations in DDR genes in localized PCa treated with image-guided radiotherapy (IGRT; n=139) versus radical prostatectomy (RadP; n=154). In both cohorts, NBN gains were the most frequent genomic alteration (14.4 and 11% of cases, respectively), and were associated with overall tumour genomic instability (p

Short tandem repeat (STR) analysis, such as the AmpFlSTR® Identifiler® Plus kit, is a standard, PCR-based human genotyping method used in the field of forensics. Misidentification of cell line and tissue DNA can be costly if not detected early; therefore it is necessary to have quality control measures such as STR profiling in place. A major issue in large-scale research studies involving archival formalin-fixed paraffin embedded (FFPE) tissues is that varying levels of DNA degradation can result in failure to correctly identify samples using STR genotyping. PCR amplification of STRs of several hundred base pairs is not always possible when DNA is degraded. The Sample ID Plus® panel from Sequenom allows for human DNA identification and authentication using SNP genotyping. In comparison to lengthy STR amplicons, this multiplexing PCR assay requires amplification of only 76-139 base pairs, and utilizes 47 SNPs to discriminate between individual samples. In this study, we evaluated both STR and SNP genotyping methods of sample identification, with a focus on paired FFPE tumor/normal DNA samples intended for next-generation sequencing (NGS). The ability to successfully validate the identity of FFPE samples can enable cost savings by reducing rework.

In early 2011, a dialogue was initiated within the Board of Directors (BOD) of the American Society for Radiation Oncology (ASTRO) regarding the future of the basic sciences of the specialty, primarily focused on the current state and potential future direction of basic research within radiation oncology. After consideration of the complexity of the issues involved and the precise nature of the undertaking, in August 2011, the BOD empanelled a Cancer Biology/Radiation Biology Task Force (TF). The TF was charged with developing an accurate snapshot of the current state of basic (preclinical) research in radiation oncology from the perspective of relevance to the modern clinical practice of radiation oncology as well as the education of our trainees and attending physicians in the biological sciences. The TF was further charged with making suggestions as to critical areas of biological basic research investigation that might be most likely to maintain and build further the scientific foundation and vitality of radiation oncology as an independent and vibrant medical specialty. It was not within the scope of service of the TF to consider the quality of ongoing research efforts within the broader radiation oncology space, to presume to consider their future potential, or to discourage in any way the investigators committed to areas of interest other than those targeted. The TF charge specifically precluded consideration of research issues related to technology, physics, or clinical investigations. This document represents an Executive Summary of the Task Force report.