A whole-exome case-control association study to characterize the contribution of rare coding variation to pancreatic cancer risk.

Pancreatic cancer is a deadly disease that accounts for approximately 5% of cancer deaths worldwide, with a dismal 5-year survival rate of 10%. Known genetic risk factors explain only a modest proportion of the heritable risk of pancreatic cancer. We conducted a whole-exome case-control sequencing study in 1,591 pancreatic cancer cases and 2,134 cancer-free controls of European ancestry.

Chromosomal imbalances detected via RNA-sequencing in 28 cancers.

Motivation: RNA-sequencing (RNA-seq) of tumor tissue is typically only used to measure gene expression. Here, we present a statistical approach that leverages existing RNA-seq data to also detect somatic copy number alterations (SCNAs), a pervasive phenomenon in human cancers, without a need to sequence the corresponding DNA.

Results: We present an analysis of 4942 participant samples from 28 cancers in The Cancer Genome Atlas (TCGA), demonstrating robust detection of SCNAs from RNA-seq.

Pan cancer patterns of allelic imbalance from chromosomal alterations in 33 tumor types.

Somatic copy number alterations (SCNAs) serve as hallmarks of tumorigenesis and often result in deviations from one-to-one allelic ratios at heterozygous loci, leading to allelic imbalance (AI). The Cancer Genome Atlas (TCGA) reports SCNAs identified using a circular binary segmentation algorithm, providing segment mean copy number estimates from single-nucleotide polymorphism DNA microarray total intensities (log R ratio), but not allele-specific intensities ("B allele" frequencies) that inform of AI. Our approach provides more sensitive identification of SCNAs by modeling the "B allele" frequencies jointly, thereby bolstering the catalog of chromosomal alterations in this widely utilized resource.

Genomic landscape of allelic imbalance in premalignant atypical adenomatous hyperplasias of the lung.

Background: Genomic investigation of atypical adenomatous hyperplasia (AAH), the only known precursor lesion to lung adenocarcinomas (LUAD), presents challenges due to the low mutant cell fractions. This necessitates sensitive methods for detection of chromosomal aberrations to better study the role of critical alterations in early lung cancer pathogenesis and the progression from AAH to LUAD.

Methods: We applied a sensitive haplotype-based statistical technique to detect chromosomal alterations leading to allelic imbalance (AI) from genotype array profiling of 48 matched normal lung parenchyma, AAH and tumor tissues from 16 stage-I LUAD patients.

Driver Mutations in Normal Airway Epithelium Elucidate Spatiotemporal Resolution of Lung Cancer.

Uninvolved normal-appearing airway epithelium has been shown to exhibit specific mutations characteristic of nearby non-small cell lung cancers (NSCLCs). Yet, its somatic mutational landscape in patients with early-stage NSCLC is unknown. To comprehensively survey the somatic mutational architecture of the normal airway epithelium in patients with early-stage NSCLC.

System for Quality-Assured Data Analysis: Flexible, reproducible scientific workflows.

The reproducibility of scientific processes is one of the paramount problems of bioinformatics, an engineering problem that must be addressed to perform good research. The System for Quality-Assured Data Analysis (SyQADA), described here, seeks to address reproducibility by managing many of the details of procedural bookkeeping in bioinformatics in as simple and transparent a manner as possible. SyQADA has been used by persons with backgrounds ranging from expert programmer to Unix novice, to perform and repeat dozens of diverse bioinformatics workflows on tens of thousands of samples, consuming over 80 CPU-months of computing on over 300,000 individual tasks of scores of projects on laptops, computer servers, and computing clusters.

Assessing inter-component heterogeneity of biphasic uterine carcinosarcomas.

Objective: Uterine carcinosarcoma (UCS) is a rare and aggressive form of uterine cancer. It is bi-phasic, exhibiting histological features of both malignant epithelial (carcinoma) and mesenchymal (sarcoma) elements, reflected in ambiguity in accepted treatment guidelines. We sought to study the genomic and transcriptomic profiles of these elements individually to gain further insights into the development of these tumors.

Oral microbiota reveals signs of acculturation in Mexican American women.

The oral microbiome has been linked to a number of chronic inflammatory conditions, including obesity, diabetes, periodontitis, and cancers of the stomach and liver. These conditions disproportionately affect Mexican American women, yet few studies have examined the oral microbiota in this at-risk group. We characterized the 16S rDNA oral microbiome in 369 non-smoking women enrolled in the MD Anderson Mano a Mano Mexican American Cohort Study.

Integrated case-control and somatic-germline interaction analyses of melanoma susceptibility genes.

While a number of genes have been implicated in melanoma susceptibility, the role of protein-coding variation in melanoma development and progression remains underexplored. To better characterize the role of germline coding variation in melanoma, we conducted a whole-exome case-control and somatic-germline interaction study involving 322 skin cutaneous melanoma cases from The Cancer Genome Atlas and 3607 controls of European ancestry. We controlled for cross-platform technological stratification using XPAT and conducted gene-based association tests using VAAST 2.

Strategies for identification of somatic variants using the Ion Torrent deep targeted sequencing platform.

Background: 'Next-generation' (NGS) sequencing has wide application in medical genetics, including the detection of somatic variation in cancer. The Ion Torrent-based (IONT) platform is among NGS technologies employed in clinical, research and diagnostic settings. However, identifying mutations from IONT deep sequencing with high confidence has remained a challenge.

XPAT: a toolkit to conduct cross-platform association studies with heterogeneous sequencing datasets.

High-throughput sequencing data are increasingly being made available to the research community for secondary analyses, providing new opportunities for large-scale association studies. However, heterogeneity in target capture and sequencing technologies often introduce strong technological stratification biases that overwhelm subtle signals of association in studies of complex traits. Here, we introduce the Cross-Platform Association Toolkit, XPAT, which provides a suite of tools designed to support and conduct large-scale association studies with heterogeneous sequencing datasets.

Genomic Landscape of Atypical Adenomatous Hyperplasia Reveals Divergent Modes to Lung Adenocarcinoma.

There is a dearth of knowledge about the pathogenesis of premalignant lung lesions, especially for atypical adenomatous hyperplasia (AAH), the only known precursor for the major lung cancer subtype adenocarcinoma (LUAD). In this study, we performed deep DNA and RNA sequencing analyses of a set of AAH, LUAD, and normal tissues. Somatic variants were found in AAHs from 5 of 22 (23%) patients, 4 of 5 of whom had matched LUAD with driver mutations.

Development of Kras mutant lung adenocarcinoma in mice with knockout of the airway lineage-specific gene Gprc5a.

Despite the urgency for prevention and treatment of lung adenocarcinoma (LUAD), we still do not know drivers in pathogenesis of the disease. Earlier work revealed that mice with knockout of the G-protein coupled receptor Gprc5a develop late onset lung tumors including LUADs. Here, we sought to further probe the impact of Gprc5a expression on LUAD pathogenesis.

Mutational Heterogeneity in and Arises at the Crypt Level and Leads to Polyclonality in Early Colorectal Tumorigenesis.

The majority of genomic alterations causing intratumoral heterogeneity (ITH) in colorectal cancer are thought to arise during early stages of carcinogenesis as a burst but only after truncal mutations in have expanded a single founder clone. We have investigated if the initial source of ITH is consequent to multiple independent lineages derived from different crypts harboring distinct truncal and driver mutations, thus challenging the prevailing monoclonal monocryptal model. High-depth next-generation sequencing and SNP arrays were performed in whole-lesion extracts of 37 familial adenomatous polyposis colorectal adenomas.

Rapid and powerful detection of subtle allelic imbalance from exome sequencing data with hapLOHseq.

Motivation: The detection of subtle genomic allelic imbalance events has many potential applications. For example, identifying cancer-associated allelic imbalanced regions in low tumor-cellularity samples or in low-proportion tumor subclones can be used for early cancer detection, prognostic assessment and therapeutic selection in cancer patients. We developed hapLOHseq for the detection of subtle allelic imbalance events from next-generation sequencing data.

Genomic Landscape of Colorectal Mucosa and Adenomas.

The molecular basis of the adenoma-to-carcinoma transition has been deduced using comparative analysis of genetic alterations observed through the sequential steps of intestinal carcinogenesis. However, comprehensive genomic analyses of adenomas and at-risk mucosa are still lacking. Therefore, our aim was to characterize the genomic landscape of colonic at-risk mucosa and adenomas.

Genomic Landscape Established by Allelic Imbalance in the Cancerization Field of a Normal Appearing Airway.

Visually normal cells adjacent to, and extending from, tumors of the lung may carry molecular alterations characteristics of the tumor itself, an effect referred to as airway field of cancerization. This airway field has been postulated as a model for early events in lung cancer pathogenesis. Yet the genomic landscape of somatically acquired molecular alterations in airway epithelia of lung cancer patients has remained unknown.

Cancer in silico drug discovery: a systems biology tool for identifying candidate drugs to target specific molecular tumor subtypes.

Large-scale cancer datasets such as The Cancer Genome Atlas (TCGA) allow researchers to profile tumors based on a wide range of clinical and molecular characteristics. Subsequently, TCGA-derived gene expression profiles can be analyzed with the Connectivity Map (CMap) to find candidate drugs to target tumors with specific clinical phenotypes or molecular characteristics. This represents a powerful computational approach for candidate drug identification, but due to the complexity of TCGA and technology differences between CMap and TCGA experiments, such analyses are challenging to conduct and reproduce.

The genome of the sea urchin Strongylocentrotus purpuratus.

We report the sequence and analysis of the 814-megabase genome of the sea urchin Strongylocentrotus purpuratus, a model for developmental and systems biology. The sequencing strategy combined whole-genome shotgun and bacterial artificial chromosome (BAC) sequences. This use of BAC clones, aided by a pooling strategy, overcame difficulties associated with high heterozygosity of the genome.