ExSurv: A Web Resource for Prognostic Analyses of Exons Across Human Cancers Using Clinical Transcriptomes

Survival analysis in biomedical sciences is generally performed by correlating the levels of cellular components with patients’ clinical features as a common practice in prognostic biomarker discovery. While the common and primary focus of such analysis in cancer genomics so far has been to identify the potential prognostic genes, alternative splicing – a posttranscriptional regulatory mechanism that affects the functional form of a protein due to inclusion or exclusion of individual exons giving rise to alternative protein products, has increasingly gained attention due to the prevalence of splicing aberrations in cancer transcriptomes. Hence, uncovering the potential prognostic exons can not only help in rationally designing exon-specific therapeutics but also increase specificity toward more personalized treatment options. To address this gap and to provide a platform for rational identification of prognostic exons from cancer transcriptomes, we developed ExSurv (https://exsurv.soic.iupui.edu), a web-based platform for predicting the survival contribution of all annotated exons in the human genome using RNA sequencing-based expression profiles for cancer samples from four cancer types available from The Cancer Genome Atlas. ExSurv enables users to search for a gene of interest and shows survival probabilities for all the exons associated with a gene and found to be significant at the chosen threshold. ExSurv also includes raw expression values across the cancer cohort as well as the survival plots for prognostic exons. Our analysis of the resulting prognostic exons across four cancer types revealed that most of the survival-associated exons are unique to a cancer type with few processes such as cell adhesion, carboxylic, fatty acid metabolism, and regulation of T-cell signaling common across cancer types, possibly suggesting significant differences in the posttranscriptional regulatory pathways contributing to prognosis.

Coding and noncoding expression patterns associated with rare obesity-related disorders: Prader-Willi and Alström syndromes

Obesity is accompanied by hyperphagia in several classical genetic obesity-related syndromes that are rare, including Prader-Willi syndrome (PWS) and Alström syndrome (ALMS). We compared coding and noncoding gene expression in adult males with PWS, ALMS, and nonsyndromic obesity relative to nonobese males using readily available lymphoblastoid cells to identify disease-specific molecular patterns and disturbed mechanisms in obesity. We found 231 genes upregulated in ALMS compared with nonobese males, but no genes were found to be upregulated in obese or PWS males and 124 genes were downregulated in ALMS. The metallothionein gene (MT1X) was significantly downregulated in ALMS, in common with obese males. Only the complex SNRPN locus was disturbed (downregulated) in PWS along with several downregulated small nucleolar RNAs (snoRNAs) in the 15q11-q13 region (SNORD116, SNORD109B, SNORD109A, SNORD107). Eleven upregulated and ten downregulated snoRNAs targeting multiple genes impacting rRNA processing, developmental pathways, and associated diseases were found in ALMS. Fifty-two miRNAs associated with multiple, overlapping gene expression disturbances were upregulated in ALMS, and four were shared with obese males but not PWS males. For example, seven passenger strand microRNAs (miRNAs) (miR-93*, miR-373*, miR-29b-2*, miR-30c-1*, miR27a*, miR27b*, and miR-149*) were disturbed in association with six separate downregulated target genes (CD68, FAM102A, MXI1, MYO1D, TP53INP1, and ZRANB1). Cell cycle (eg, PPP3CA), transcription (eg, POLE2), and development may be impacted by upregulated genes in ALMS, while downregulated genes were found to be involved with metabolic processes (eg, FABP3), immune responses (eg, IL32), and cell signaling (eg, IL1B). The high number of gene and noncoding RNA disturbances in ALMS contrast with observations in PWS and males with nonsyndromic obesity and may reflect the progressing multiorgan pathology of the ALMS disease process.