Identifying molecular cancer drivers is critical for precision oncology. Multiple advanced algorithms to identify drivers now exist, but systematic attempts to combine and optimize them on large datasets are few. We report a PanCancer and PanSoftware analysis spanning 9,423 tumor exomes (comprising all 33 of The Cancer Genome Atlas projects) and using 26 computational tools to catalog driver genes and mutations. We identify 299 driver genes with implications regarding their anatomical sites and cancer/cell types. Sequence- and structure-based analyses identified >3,400 putative missense driver mutations supported by multiple lines of evidence. Experimental validation confirmed 60%-85% of predicted mutations as likely drivers. We found that >300 MSI tumors are associated with high PD-1/PD-L1, and 57% of tumors analyzed harbor putative clinically actionable events. Our study represents the most comprehensive discovery of cancer genes and mutations to date and will serve as a blueprint for future biological and clinical endeavors.

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Highlights d Integrated proteogenomic characterization in 103 ccRCC cases d Delineation of chromosomal translocation events leading to chromosome 3p loss d Tumor-specific proteomic/phosphoproteomic alterations unrevealed by mRNA analysis d Immune-based subtypes of ccRCC defined by mRNA, proteome, and phosphoproteome

We reviewed the literature to determine the effectiveness of HIV-related interventions in reducing HIV/AIDS stigma. Studies selected had randomized controlled trial (RCT), pretest–posttest with a non-randomized control group, or pretest–posttest one group study designs in which HIV-related interventions were being evaluated, and in which HIV/AIDS stigma was one of the outcomes being measured. A checklist was used to extract data from accepted studies, assess their internal validity, and overall quality. Data were extracted from 19 studies, and 14 of these studies demonstrated effectiveness in reducing HIV/ AIDS stigma. Only 2 of these 14 effective studies were considered good studies, based on quality, the extent to which the intervention focused on reducing HIV/AIDS stigma, and the statistics reported to demonstrate effectiveness. Future studies to reduce HIV/AIDS stigma could improve by designing interventions that pay greater attention to internal validity, use validated HIV/AIDS stigma instruments, and achieve both statistical and public health significance.

In the originally published version of this article, Daniel Geiszler's last name was misspelled. This error has now been corrected in the article online.

The functional impact of the vast majority of cancer somatic mutations remains unknown, representing a critical knowledge gap for implementing precision oncology. Here, we report the development of a moderate-throughput functional genomic platform consisting of efficient mutant generation, sensitive viability assays using two growth factor-dependent cell models, and functional proteomic profiling of signaling effects for select aberrations. We apply the platform to annotate >1,000 genomic aberrations, including gene amplifications, point mutations, indels, and gene fusions, potentially doubling the number of driver mutations characterized in clinically actionable genes. Further, the platform is sufficiently sensitive to identify weak drivers. Our data are accessible through a user-friendly, public data portal. Our study will facilitate biomarker discovery, prediction algorithm improvement, and drug development.

Summaryobjective To develop scales to measure tuberculosis and HIV ⁄ AIDS stigma in a developing world context.methods Cross-sectional study of tuberculosis patients in southern Thailand, who were asked to rate their agreement with items measuring TB and HIV ⁄ AIDS stigma. Developing the scales involved exploratory and confirmatory factor analyses, internal consistency, construct validity, test-retest reliability and standardized summary scores.results Factor analyses identified two sub-scales associated with both tuberculosis and HIV ⁄ AIDS stigma: community and patient perspectives. Goodness-of-fit was good (TLI = 94, LFI = 0.88 and RMSEA = 0.11), internal consistency was excellent (Cronbach's alphas 0.82-0.91), test-retest reliability was moderate, and construct validity showed an inverse correlation with social support.

SUMMARYFor the past decade, cancer genomic studies have focused on mutations leading to splice-site disruption, overlooking those having splice-creating potential. Here, we applied a bioinformatic tool, MiSplice, for the large-scale discovery of splice-site-creating mutations (SCMs) across 8,656 TCGA tumors. We report 1,964 originally mis-annotated mutations having clear evidence of creating alternative splice junctions. TP53 and GATA3 have 26 and 18 SCMs, respectively, and ATRX has 5 from lower-grade gliomas. Mutations in 11 genes, including PARP1, BRCA1, and BAP1, were experimentally validated for splice-site-creating function. Notably, we found that neoantigens induced by SCMs are likely several folds more immunogenic compared to missense mutations, exemplified by the recurrent GATA3 SCM. Further, high expression of PD-1 and PD-L1 was observed in tumors with SCMs, suggesting candidates for immune blockade therapy. Our work highlights the importance of integrating DNA and RNA data for understanding the functional and the clinical implications of mutations in human diseases.