Immune DNA signature of T-cell infiltration in breast tumor exomes.

Tumor infiltrating lymphocytes (TILs) have been associated with favorable prognosis in multiple tumor types. The Cancer Genome Atlas (TCGA) represents the largest collection of cancer molecular data, but lacks detailed information about the immune environment. Here, we show that exome reads mapping to the complementarity-determining-region 3 (CDR3) of mature T-cell receptor beta (TCRB) can be used as an immune DNA (iDNA) signature. Specifically, we propose a method to identify CDR3 reads in a breast tumor exome and validate it using deep TCRB sequencing. In 1,078 TCGA breast cancer exomes, the fraction of CDR3 reads was associated with TILs fraction, tumor purity, adaptive immunity gene expression signatures and improved survival in Her2+ patients. Only 2/839 TCRB clonotypes were shared between patients and none associated with a specific HLA allele or somatic driver mutations. The iDNA biomarker enriches the comprehensive dataset collected through TCGA, revealing associations with other molecular features and clinical outcomes

Biological data sciences in genome research

The last 20 years have been a remarkable era for biology and medicine. One of the most significant achievements has been the sequencing of the first human genomes, which has laid the foundation for profound insights into human genetics, the intricacies of regulation and development, and the forces of evolution. Incredibly, as we look into the future over the next 20 years, we see the very real potential for sequencing more than 1 billion genomes, bringing even deeper insight into human genetics as well as the genetics of millions of other species on the planet. Realizing this great potential for medicine and biology, though, will only be achieved through the integration and development of highly scalable computational and quantitative approaches that can keep pace with the rapid improvements to biotechnology. In this perspective, I aim to chart out these future technologies, anticipate the major themes of research, and call out the challenges ahead. One of the largest shifts will be in the training used to prepare the class of 2035 for their highly interdisciplinary world

Prognostic microRNA signatures derived from The Cancer Genome Atlas for head and neck squamous cell carcinomas

Identification of novel prognostic biomarkers typically requires a large dataset which provides sufficient statistical power for discovery research. To this end, we took advantage of the high‐throughput data from The Cancer Genome Atlas (TCGA) to identify a set of prognostic biomarkers in head and neck squamous cell carcinomas (HNSCC) including oropharyngeal squamous cell carcinoma (OPSCC) and other subtypes. In this study, we analyzed miRNA‐seq data obtained from TCGA patients to identify prognostic biomarkers for OPSCC. The identified miRNAs were further tested with an independent cohort. miRNA‐seq data from TCGA was also analyzed to identify prognostic miRNAs in oral cavity squamous cell carcinoma (OSCC) and laryngeal squamous cell carcinoma (LSCC). Our study identified that miR‐193b‐3p and miR‐455‐5p were positively associated with survival, and miR‐92a‐3p and miR‐497‐5p were negatively associated with survival in OPSCC. A combined expression signature of these four miRNAs was prognostic of overall survival in OPSCC, and more importantly, this signature was validated in an independent OPSCC cohort. Furthermore, we identified four miRNAs each in OSCC and LSCC that were prognostic of survival, and combined signatures were specific for subtypes of HNSCC. A robust 4‐miRNA prognostic signature in OPSCC, as well as prognostic signatures in other subtypes of HNSCC, was developed using sequencing data from TCGA as the primary source. This demonstrates the power of using TCGA as a potential resource to develop prognostic tools for improving individualized patient care

Functional Mutations Form at CTCF-Cohesin Binding Sites in Melanoma Due to Uneven Nucleotide Excision Repair across the Motif

© 2016 The Author(s) CTCF binding sites are frequently mutated in cancer, but how these mutations accumulate and whether they broadly perturb CTCF binding are not well understood. Here, we report that skin cancers exhibit a highly specific asymmetric mutation pattern within CTCF motifs attributable to ultraviolet irradiation and differential nucleotide excision repair (NER). CTCF binding site mutations form independently of replication timing and are enriched at sites of CTCF/cohesin complex binding, suggesting a role for cohesin in stabilizing CTCF-DNA binding and impairing NER. Performing CTCF ChIP-seq in a melanoma cell line, we show CTCF binding site mutations to be functional by demonstrating allele-specific reduction of CTCF binding to mutant alleles. While topologically associating domains with mutated CTCF anchors in melanoma contain differentially expressed cancer-associated genes, CTCF motif mutations appear generally under neutral selection. However, the frequency and potential functional impact of such mutations in melanoma highlights the need to consider their impact on cellular phenotype in individual genomes.Link_to_subscribed_fulltex

Distribution-based measures of tumor heterogeneity are sensitive to mutation calling and lack strong clinical predictive power.

Mutant allele frequency distributions in cancer samples have been used to estimate intratumoral heterogeneity and its implications for patient survival. However, mutation calls are sensitive to the calling algorithm. It remains unknown whether the relationship of heterogeneity and clinical outcome is robust to these variations. To resolve this question, we studied the robustness of allele frequency distributions to the mutation callers MuTect, SomaticSniper, and VarScan in 4722 cancer samples from The Cancer Genome Atlas. We observed discrepancies among the results, particularly a pronounced difference between allele frequency distributions called by VarScan and SomaticSniper. Survival analysis showed little robust predictive power for heterogeneity as measured by Mutant-Allele Tumor Heterogeneity (MATH) score, with the exception of uterine corpus endometrial carcinoma. However, we found that variations in mutant allele frequencies were mediated by variations in copy number. Our results indicate that the clinical predictions associated with MATH score are primarily caused by copy number aberrations that alter mutant allele frequencies. Finally, we present a mathematical model of linear tumor evolution demonstrating why MATH score is insufficient for distinguishing different scenarios of tumor growth. Our findings elucidate the importance of allele frequency distributions as a measure for tumor heterogeneity and their prognostic role

Loss of Wave1 gene defines a subtype of lethal prostate cancer

Genetic alterations involving TMPRSS2-ERG alterations and deletion of key tumor suppressor genes are associated with development and progression of prostate cancer (PCa). However, less defined are early events that may contribute to the development of high-risk metastatic prostate cancer. Bioinformatic analysis of existing tumor genomic data from PCa patients revealed that WAVE complex gene alterations are associated with a greater likelihood of prostate cancer recurrence. Further analysis of primary vs. castration resistant prostate cancer indicate that disruption of WAVE complex gene expression, and particularly WAVE1 gene (WASF1) loss, is also associated with castration resistance, where WASF1 is frequently co-deleted with PTEN and resists androgen deprivation therapy (ADT). Hence, we propose that WASF1 status defines a subtype of ADT-resistant patients. Better understanding of the effects of WAVE pathway disruption will lead to development of better diagnostic and treatment modalities

Germline MC1R status influences somatic mutation burden in melanoma

The major genetic determinants of cutaneous melanoma risk in the general population are disruptive variants (R alleles) in the melanocortin 1 receptor (MC1R) gene. These alleles are also linked to red hair, freckling, and sun sensitivity, all of which are known melanoma phenotypic risk factors. Here we report that in melanomas and for somatic C>T mutations, a signature linked to sun exposure, the expected single-nucleotide variant count associated with the presence of an R allele is estimated to be 42% (95% CI, 15-76%) higher than that among persons without an R allele. This figure is comparable to the expected mutational burden associated with an additional 21 years of age. We also find significant and similar enrichment of non-C>T mutation classes supporting a role for additional mutagenic processes in melanoma development in individuals carrying R alleles