Dataset Information

Splice Expression Variation Analysis (SEVA) for inter-tumor heterogeneity of gene isoform usage in cancer.

ABSTRACT: Motivation:Current bioinformatics methods to detect changes in gene isoform usage in distinct phenotypes compare the relative expected isoform usage in phenotypes. These statistics model differences in isoform usage in normal tissues, which have stable regulation of gene splicing. Pathological conditions, such as cancer, can have broken regulation of splicing that increases the heterogeneity of the expression of splice variants. Inferring events with such differential heterogeneity in gene isoform usage requires new statistical approaches. Results:We introduce Splice Expression Variability Analysis (SEVA) to model increased heterogeneity of splice variant usage between conditions (e.g. tumor and normal samples). SEVA uses a rank-based multivariate statistic that compares the variability of junction expression profiles within one condition to the variability within another. Simulated data show that SEVA is unique in modeling heterogeneity of gene isoform usage, and benchmark SEVA's performance against EBSeq, DiffSplice and rMATS that model differential isoform usage instead of heterogeneity. We confirm the accuracy of SEVA in identifying known splice variants in head and neck cancer and perform cross-study validation of novel splice variants. A novel comparison of splice variant heterogeneity between subtypes of head and neck cancer demonstrated unanticipated similarity between the heterogeneity of gene isoform usage in HPV-positive and HPV-negative subtypes and anticipated increased heterogeneity among HPV-negative samples with mutations in genes that regulate the splice variant machinery. These results show that SEVA accurately models differential heterogeneity of gene isoform usage from RNA-seq data. Availability and implementation:SEVA is implemented in the R/Bioconductor package GSReg. Contact:bahman@jhu.edu or favorov@sensi.org or ejfertig@jhmi.edu. Supplementary information:Supplementary data are available at Bioinformatics online.

SUBMITTER: Afsari B

PROVIDER: S-EPMC5972655 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Splice Expression Variation Analysis (SEVA) for inter-tumor heterogeneity of gene isoform usage in cancer.

Afsari Bahman B Guo Theresa T Considine Michael M Florea Liliana L Kagohara Luciane T LT Stein-O'Brien Genevieve L GL Kelley Dylan D Flam Emily E Zambo Kristina D KD Ha Patrick K PK Geman Donald D Ochs Michael F MF Califano Joseph A JA Gaykalova Daria A DA Favorov Alexander V AV Fertig Elana J EJ

Bioinformatics (Oxford, England) 20180601 11

<h4>Motivation</h4>Current bioinformatics methods to detect changes in gene isoform usage in distinct phenotypes compare the relative expected isoform usage in phenotypes. These statistics model differences in isoform usage in normal tissues, which have stable regulation of gene splicing. Pathological conditions, such as cancer, can have broken regulation of splicing that increases the heterogeneity of the expression of splice variants. Inferring events with such differential heterogeneity in ge ...[more]

PMID: 29342249

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Project description:BACKGROUND: Alternative splicing and isoform level expression profiling is an emerging field of interest within genomics. Splicing sensitive microarrays, with probes targeted to individual exons or exon-junctions, are becoming increasingly popular as a tool capable of both expression profiling and finer scale isoform detection. Despite their intuitive appeal, relatively little is known about the performance of such tools, particularly in comparison with more traditional 3' targeted microarrays. Here, we use the well studied Microarray Quality Control (MAQC) dataset to benchmark the Affymetrix Exon Array, and compare it to two other popular platforms: Illumina, and Affymetrix U133. RESULTS: We show that at the gene expression level, the Exon Array performs comparably with the two 3' targeted platforms. However, the interplatform correlation of the results is slightly lower than between the two 3' arrays. We show that some of the discrepancies stem from the RNA amplification protocols, e.g. the Exon Array is able to detect expression of non-polyadenylated transcripts. More importantly, we show that many other differences result from the ability of the Exon Array to monitor more detailed isoform-level changes; several examples illustrate that changes detected by the 3' platforms are actually isoform variations, and that the nature of these variations can be resolved using Exon Array data. Finally, we show how the Exon Array can be used to detect alternative isoform differences, such as alternative splicing, transcript termination, and alternative promoter usage. We discuss the possible pitfalls and false positives resulting from isoform-level analysis. CONCLUSION: The Exon Array is a valuable tool that can be used to profile gene expression while providing important additional information regarding the types of gene isoforms that are expressed and variable. However, analysis of alternative splicing requires much more hands on effort and visualization of results in order to correctly interpret the data, and generally results in considerably higher false positive rates than expression analysis. One of the main sources of error in the MAQC dataset is variation in amplification efficiency across transcripts, most likely caused by joint effects of elevated GC content in the 5' ends of genes and reduced likelihood of random-primed first strand synthesis in the 3' ends of genes. These effects are currently not adequately corrected using existing statistical methods. We outline approaches to reduce such errors by filtering out potentially problematic data.

Project description:Background:The Dako PD-L1 immunohistochemistry (IHC) 22C3 pharmDx and the Dako 28-8 IHC pharmDx assays were approved by the US Food and Drug Administration, as a companion diagnostic test for pembrolizumab (Keytruda, Merk, Kenilworth, NJ, USA) and a complementary diagnostic test for nivolumab (Opdivo, Bristol Meyer Squibb, New York, NY, USA) in non-small cell lung cancer (NSCLC), respectively. Increased PD-L1 expression levels can be associated with greater therapeutic efficacy of pembrolizumab relative to other anti-PD-1 agents. However, in treatment decision making, little is known about which tissue (primary or metastatic lesion) should be stained by 22C3 antibody. We investigated the relationship between PD-L1 expression in primary tumors and paired metastatic lymph nodes using the 22C3 assay, and evaluated the concordance between the 22C3 and 28-8 assays. Methods:PD-L1 expression was evaluated in cells from primary tumors and paired metastatic lymph nodes using the 22C3 and 28-8 IHC assays. Total 35 patients with primary tumor and paired metastatic lymph node were enrolled into this study, and all samples were surgically resected, formalin-fixed, and paraffin-embedded NSCLC tissues. Tumor cells exhibiting complete or partial membrane staining, were considered as PD-L1 positive. On the basis of tumor proportion score (TPS), all samples were classified as no expression (TPS: <1%), low expression (TPS: 1-49%), or high expression (TPS: ?50%). Results:TPS distribution was markedly different between primary tumors and paired metastatic lymph nodes. In 22C3 IHC assay, TPS similar to that of metastatic lymph nodes was demonstrated in 10 primary tumors, and concordance rate between them was 28.6%. Concurrently, in 28-8 IHC assay, 11 primary tumors had TPS similar to that of metastatic lymph nodes, with a concordance rate of 31.4%. Conclusions:TPS concordance rates (for both 22C3 and 28-8 antibodies) between primary tumors and paired lymph nodes were low. Inter-tumor heterogeneity of PD-L1 expression is an important issue for clinical oncologists during treatment planning.

Project description:BackgroundThe long-term effects of cocaine on behavior are accompanied by structural changes in excitatory glutamatergic synapses onto the medium spiny neurons of the striatum. The Kalrn gene encodes several functionally distinct isoforms; these multidomain guanine nucleotide exchange factors (GEFs) contain additional domains known to interact with phosphatidylinositides as well as with a number of different proteins. Through their activation of Rho proteins and their interactions with other proteins, the different Kalirin isoforms affect cytoskeletal organization. Chronic exposure of adult male rodents to cocaine increases levels of Kalirin 7 in the striatum. When exposed chronically to cocaine, mice lacking Kalirin 7, the major adult isoform, fail to show an increase in dendritic spine density in the nucleus accumbens, show diminished place preference for cocaine, and exhibit increased locomotor activity in response to cocaine.ResultsThe use of alternate promoters and 3'-terminal exons of the mouse Kalrn gene were investigated using real-time quantitative polymerase chain reaction. While the two most distal full-length Kalrn promoters are used equally in the prefrontal cortex, the more proximal of these promoters accounts for most of the transcripts expressed in the nucleus accumbens. The 3'-terminal exon unique to the Kalirin 7 isoform accounts for a greater percentage of the Kalrn transcripts in prefrontal cortex than in nucleus accumbens. Western blot analyses confirmed these differences. Chronic cocaine treatment increases usage of the promoter encoding the Δ-Kalirin isoforms but does not alter full-length Kalirin promoter usage. Usage of the 3'-terminal exon unique to Kalirin 7 increases following chronic cocaine exposure.ConclusionsKalrn promoter and 3'-terminal exon utilization are region-specific. In the nucleus accumbens, cocaine-mediated alterations in promoter usage and 3'-terminal exon usage favor expression of Kalirin 7 and Δ-Kalirin 7. The Δ-isoform, which lacks a Sec14p domain and four of the nine spectrin-like repeats found in full-length Kalirin isoforms, increases spine headsize without increasing dendritic spine numbers. Thus cocaine-mediated changes in alternative splicing of the Kalrn gene may contribute importantly to the behavioral, morphological and biochemical responses observed.

Dataset Information

Splice Expression Variation Analysis (SEVA) for inter-tumor heterogeneity of gene isoform usage in cancer.

Publications

Splice Expression Variation Analysis (SEVA) for inter-tumor heterogeneity of gene isoform usage in cancer.

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