CaArray_carpt-00469: Copy Number and Targeted Mutational Analysis Reveals Novel Somatic Events in Metastatic Prostate Tumors
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE68597 | GEO | 2015/05/07
SECONDARY ACCESSION(S): PRJNA283186
REPOSITORIES: GEO
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Project description:Advanced prostate cancer can progress to systemic metastatic tumors, which are generally androgen insensitive and ultimately lethal. Here, we report a comprehensive genomic survey for somatic events in systemic metastatic prostate tumors using both high-resolution copy number analysis and targeted mutational survey of 3508 exons from 577 cancer-related genes using next generation sequencing. Focal homozygous deletions were detected at 8p22, 10q23.31, 13q13.1, 13q14.11, and 13q14.12. Key genes mapping within these deleted regions include PTEN, BRCA2, C13ORF15, and SIAH3. Focal high-level amplifications were detected at 5p13.2-p12, 14q21.1, 7q22.1, and Xq12. Key amplified genes mapping within these regions include SKP2, FOXA1, and AR. Furthermore, targeted mutational analysis of normal-tumor pairs has identified somatic mutations in genes known to be associated with prostate cancer including AR and TP53, but has also revealed novel somatic point mutations in genes including MTOR, BRCA2, ARHGEF12, and CHD5. Finally, in one patient where multiple independent metastatic tumors were available, we show common and divergent somatic alterations that occur at both the copy number and point mutation level, supporting a model for a common clonal progenitor with metastatic tumor-specific divergence. Our study represents a deep genomic analysis of advanced metastatic prostate tumors and has revealed candidate somatic alterations, possibly contributing to lethal prostate cancer.
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Project description:Many studies have shown that primary prostate cancers are multifocal1-3, and are composed of multiple genetically distinct cancer cell clones4-6. Whether or not multiclonal primary prostate cancers typically give rise to multiclonal or monoclonal prostate cancer metastases is largely unknown, although studies at single chromosomal loci are consistent with the latter. Here we show through a high-resolution genome-wide SNP and copy number survey that most if not all metastatic prostate cancers have monoclonal origins and maintain a unique signature copy number pattern of the parent cancer cell while also accumulating a variable number of separate subclonally sustained changes. We find no relationship between anatomic site of metastasis and genomic copy number change pattern. Taken together with past animal and cytogenetic studies of metastasis7, and recent single-locus genetic data in prostate and other metastatic cancers8-10, it appears that despite common genomic heterogeneity in primary cancers, most metastatic cancers arise from a single precursor cancer cell. Methodologically, this study establishes that genomic archeology of multiple anatomically separate metastatic cancers in individuals can be used to define the salient genomic features of a parent cancer clone of proven lethal metastatic phenotype.
2009-04-12 | GSE14996 | GEO
Project description:Detecting genomic alterations that result in more aggressive prostate cancer may improve clinical treatment and our understanding of the biology underlying this common but complex disease. To this end, we undertook a genome-wide copy number alterations (CNAs) study of clinicopathological characteristics of 62 prostate tumors using the Illumina 1M single nucleotide polymorphism array. The highest overall frequencies of CNAs were on chromosomes 8q (gains), 8p (loss and copy-neutral), and 6q (copy-loss). Combined loss and copy-neutral events were associated with increasing disease grade (P = 0.03), stage (P = 0.01), and diagnostic prostate specific antigen (PSA) (P = 0.01). Further evaluation of CNAs using gene ontology identified pathways involved with disease aggressiveness. The "regulation of apoptosis" pathway was associated with stage of disease (P = 0.004), while the "reproductive cellular process" pathway was associated with diagnostic PSA (P = 0.00038). Specific genes within these pathways exhibited strong associations with clinical characteristics; for example, in the apoptosis pathway BNIP3L was associated with increasing prostate tumor stage (P = 0.007). These findings confirm known regions of CNAs in prostate cancer and localize additional regions and possible genes (e.g., BNIP3L, WWOX, and GATM) that may help to clarify the genetic basis of prostate cancer aggressiveness.
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Project description:MotivationWhole exome and gene panel sequencing are increasingly used for oncological diagnostics. To investigate the accuracy of SCNA detection algorithms on simulated and clinical tumor samples, the precision and sensitivity of four SCNA callers were measured using 50 simulated whole exome and 50 simulated targeted gene panel datasets, and using 119 TCGA tumor samples for which SNP array data were available.ResultsOn synthetic exome and panel data, VarScan2 mostly called false positives, whereas Control-FREEC was precise (>90% correct calls) at the cost of low sensitivity (<40% detected). ONCOCNV was slightly less precise on gene panel data, with similarly low sensitivity. This could be explained by low sensitivity for amplifications and high precision for deletions. Surprisingly, these results were not strongly affected by moderate tumor impurities; only contaminations with more than 60% non-cancerous cells resulted in strongly declining precision and sensitivity. On the 119 clinical samples, both Control-FREEC and CNVkit called 71.8% and 94%, respectively, of the SCNAs found by the SNP arrays, but with a considerable amount of false positives (precision 29% and 4.9%).DiscussionWhole exome and targeted gene panel methods by design limit the precision of SCNA callers, making them prone to false positives. SCNA calls cannot easily be integrated in clinical pipelines that use data from targeted capture-based sequencing. If used at all, they need to be cross-validated using orthogonal methods.Availability and implementationScripts are provided as supplementary information.Contactgunther.jansen@molecularhealth.com.Supplementary informationSupplementary data are available at Bioinformatics online.
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Project description:Somatic copy number alterations (SCNAs) in tumors are clinically significant diagnostic, prognostic, and predictive biomarkers. SCNA detection from targeted next-generation sequencing panels is increasingly common in clinical practice; however, detailed descriptions of optimization and validation of SCNA pipelines for small targeted panels are limited. This study describes the validation and implementation of a tumor-only SCNA pipeline using CNVkit, augmented with custom modules and optimized for clinical implementation by testing reference materials and clinical tumor samples with different classes of copy number variation (CNV; amplification, single copy loss, and biallelic loss). Using wet-bench and in silico methods, various parameters impacting CNV calling, including assay-intrinsic variables (establishment of normal reference and sequencing coverage), sample-intrinsic variables (tumor purity and sample quality), and CNV algorithm-intrinsic variables (bin size), were optimized. The pipeline was trained and tested on an optimization cohort and validated using an independent cohort with a sensitivity and specificity of 100% and 93%, respectively. Using custom modules, intragenic CNVs with breakpoints within tumor suppressor genes were uncovered. Using the validated pipeline, re-analysis of 28 pediatric solid tumors that had been previously profiled for mutations identified SCNAs in 86% (24/28) samples, with 46% (13/28) samples harboring findings of potential clinical relevance. Our report highlights the importance of rigorous establishment of performance characteristics of SCNA pipelines and presents a detailed validation framework for optimal SCNA detection in targeted sequencing panels.
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Project description:To identify clinically important molecular subtypes of prostate cancer (PCa), we characterized the somatic landscape of aggressive tumors via deep, whole-genome sequencing. In our discovery set of ten tumor/normal subject pairs with Gleason scores of 8-10 at diagnosis, coordinated analysis of germline and somatic variants, including single-nucleotide variants, indels, and structural variants, revealed biallelic BRCA2 disruptions in a subset of samples. Compared to the other samples, the PCa BRCA2-deficient tumors exhibited a complex and highly specific mutation signature, featuring a 2.88-fold increased somatic mutation rate, depletion of context-specific C>T substitutions, and an enrichment for deletions, especially those longer than 10 bp. We next performed a BRCA2 deficiency-targeted reanalysis of 150 metastatic PCa tumors, and each of the 18 BRCA2-mutated samples recapitulated the BRCA2 deficiency-associated mutation signature, underscoring the potent influence of these lesions on somatic mutagenesis and tumor evolution. Among all 21 individuals with BRCA2-deficient tumors, only about half carried deleterious germline alleles. Importantly, the somatic mutation signature in tumors with one germline and one somatic risk allele was indistinguishable from those with purely somatic mutations. Our observations clearly demonstrate that BRCA2-disrupted tumors represent a unique and clinically relevant molecular subtype of aggressive PCa, highlighting both the promise and utility of this mutation signature as a prognostic and treatment-selection biomarker. Further, any test designed to leverage BRCA2 status as a biomarker for PCa must consider both germline and somatic mutations and all types of deleterious mutations.
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Project description:Many studies have shown that primary prostate cancers are multifocal and are composed of multiple genetically distinct cancer cell clones. Whether or not multiclonal primary prostate cancers typically give rise to multiclonal or monoclonal prostate cancer metastases is largely unknown, although studies at single chromosomal loci are consistent with the latter case. Here we show through a high-resolution genome-wide single nucleotide polymorphism and copy number survey that most, if not all, metastatic prostate cancers have monoclonal origins and maintain a unique signature copy number pattern of the parent cancer cell while also accumulating a variable number of separate subclonally sustained changes. We find no relationship between anatomic site of metastasis and genomic copy number change pattern. Taken together with past animal and cytogenetic studies of metastasis and recent single-locus genetic data in prostate and other metastatic cancers, these data indicate that despite common genomic heterogeneity in primary cancers, most metastatic cancers arise from a single precursor cancer cell. This study establishes that genomic archeology of multiple anatomically separate metastatic cancers in individuals can be used to define the salient genomic features of a parent cancer clone of proven lethal metastatic phenotype.
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Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
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Project description:Small intestine neuroendocrine tumors (SI-NETs) represent the most common histotype among small intestine neoplasms, and metastatic disease is usually present at diagnosis. A retrospective series of 52 sporadic primary surgically resected SI-NETs, which were metastatic at diagnosis, was analyzed by high-coverage target sequencing (HCTS) for the mutational status of 57 genes and copy number status of 40 genes selected from recently published genome sequencing data. Seven genes were found to be recurrently mutated: CDKN1B (9.6%), APC and CDKN2C (each 7.7%), BRAF, KRAS, PIK3CA, and TP53 (each 3.8%). Copy number analysis showed frequent allelic loss of 4 genes located on chromosome 18 (BCL2, CDH19, DCC, and SMAD4) in 23/52 (44.2%) and losses on chromosomes 11 (38%) and 16 (15%). Other recurrent copy number variations were gains for genes located on chromosomes 4 (31%), 5 (27%), 14 (36%), and 20 (20%). Univariate survival analysis showed that SRC gene copy number gains were associated with a poorer prognosis (p = 0.047). Recurrent copy number variations are important events in SI-NET and SRC may represent a novel prognostic biomarker for this tumor type.
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