Gastric cancer is a leading cause of cancer deaths, but analysis of its molecular and clinical characteristics has been complicated by histological and aetiological heterogeneity. Here we describe a comprehensive molecular evaluation of 295 primary gastric adenocarcinomas as part of The Cancer Genome Atlas (TCGA) project. We propose a molecular classification dividing gastric cancer into four subtypes: tumours positive for Epstein–Barr virus, which display recurrent PIK3CA mutations, extreme DNA hypermethylation, and amplification of JAK2, CD274 (also known as PD-L1) and PDCD1LG2 (also knownasPD-L2); microsatellite unstable tumours, which show elevated mutation rates, including mutations of genes encoding targetable oncogenic signalling proteins; genomically stable tumours, which are enriched for the diffuse histological variant and mutations of RHOA or fusions involving RHO-family GTPase-activating proteins; and tumours with chromosomal instability, which show marked aneuploidy and focal amplification of receptor tyrosine kinases. Identification of these subtypes provides a roadmap for patient stratification and trials of targeted therapies.
Thymic epithelial tumors (TETs) are one of the rarest adult malignancies. Among TETs, thymoma is the most predominant, characterized by a unique association with autoimmune diseases, followed by thymic carcinoma, which is less common but more clinically aggressive. Using multi-platform omics analyses on 117 TETs, we define four subtypes of these tumors defined by genomic hallmarks and an association with survival and World Health Organization histological subtype. We further demonstrate a marked prevalence of a thymoma-specific mutated oncogene, GTF2I, and explore its biological effects on multi-platform analysis. We further observe enrichment of mutations in HRAS, NRAS, and TP53. Last, we identify a molecular link between thymoma and the autoimmune disease myasthenia gravis, characterized by tumoral overexpression of muscle autoantigens, and increased aneuploidy.
Paired-end sequencing is a common approach for identifying structural variation (SV) in genomes. Discrepancies between the observed and expected alignments indicate potential SVs. Most SV detection algorithms use only one of the possible signals and ignore reads with multiple alignments. This results in reduced sensitivity to detect SVs, especially in repetitive regions. We introduce GASVPro, an algorithm combining both paired read and read depth signals into a probabilistic model that can analyze multiple alignments of reads. GASVPro outperforms existing methods with a 50 to 90% improvement in specificity on deletions and a 50% improvement on inversions. GASVPro is available at http://compbio.cs.brown.edu/software.
Serous epithelial ovarian cancer (EOC) patients often succumb to aggressive metastatic disease, yet little is known about the behavior and genetics of ovarian cancer metastasis. Here, we aim to understand how omental metastases differ from primary tumors and how these differences may influence chemotherapy. We analyzed the miRNA expression profiles of primary EOC tumors and their respective omental metastases from 9 patients using miRNA Taqman qPCR arrays. We find 17 miRNAs with differential expression in omental lesions compared to primary tumors. miR-21, miR-150, and miR-146a have low expression in most primary tumors with significantly increased expression in omental lesions, with concomitant decreased expression of predicted mRNA targets based on mRNA expression. We find that miR-150 and miR-146a mediate spheroid size. Both miR-146a and miR-150 increase the number of residual surviving cells by 2–4 fold when challenged with lethal cisplatin concentrations. These observations suggest that at least two of the miRNAs, miR-146a and miR-150, up-regulated in omental lesions, stimulate survival and increase drug tolerance. Our observations suggest that cancer cells in omental tumors express key miRNAs differently than primary tumors, and that at least some of these microRNAs may be critical regulators of the emergence of drug resistant disease.
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