A Pan-Cancer Analysis of Alternative Splicing Events Reveals Novel Tumor-Associated Splice Variants of Matriptase

Dargahi, Daryanaz; Swayze, Richard D.; Yee, Leanna; Bergqvist, Peter; Hedberg, Bradley J.; Heravi-Moussavi, Alireza; Dullaghan, Edie; Dercho, Ryan A.; An, Jianghong; Babcook, John S.; Jones, Steven J.M.

doi:10.4137/cin.s19435

Cited by 9 publications

(5 citation statements)

References 40 publications

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“…By contrast, despite the importance of mRNA isoform variation and alternative splicing, there have been limited efforts in transcriptome-wide survival analysis of alternative splicing in cancer patients. Most RNA-seq studies of alternative splicing in cancer transcriptomes focus on identifying ‘cancer-specific' alternative splicing events by comparing cancer tissues with normal controls (see refs 18 , 19 , 20 , 21 , 22 , 23 for examples). A recent analysis of TCGA RNA-seq data identified 163 recurrent differential alternative splicing events between cancer and normal tissues of three cancer types, among which five were found to have suggestive survival signals for breast cancer at a nominal P -value cutoff of 0.05 (ref.…”

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confidence: 99%

SURVIV for survival analysis of mRNA isoform variation

Shen

Wang

et al. 2016

Nat Commun

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The rapid accumulation of clinical RNA-seq data sets has provided the opportunity to associate mRNA isoform variations to clinical outcomes. Here we report a statistical method SURVIV (Survival analysis of mRNA Isoform Variation), designed for identifying mRNA isoform variation associated with patient survival time. A unique feature and major strength of SURVIV is that it models the measurement uncertainty of mRNA isoform ratio in RNA-seq data. Simulation studies suggest that SURVIV outperforms the conventional Cox regression survival analysis, especially for data sets with modest sequencing depth. We applied SURVIV to TCGA RNA-seq data of invasive ductal carcinoma as well as five additional cancer types. Alternative splicing-based survival predictors consistently outperform gene expression-based survival predictors, and the integration of clinical, gene expression and alternative splicing profiles leads to the best survival prediction. We anticipate that SURVIV will have broad utilities for analysing diverse types of mRNA isoform variation in large-scale clinical RNA-seq projects.

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mentioning

confidence: 99%

SURVIV for survival analysis of mRNA isoform variation

Shen

Wang

et al. 2016

Nat Commun

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“…Alternative splicing is one of the most important regulation mechanisms of the diversity of transcriptome and proteome. Some cancers can use AS to produce proteins that are conducive to the proliferation and invasion of cancer cells (Dargahi et al, 2014). Some AS events have been proven to be targets of prognosis and treatment (Pajares et al, 2007;Venables et al, 2008;Griffith et al, 2013).…”

Section: Discussionmentioning

confidence: 99%

“…Due to functional importance and high frequency of occurrence, changes in AS often affect the homeostasis of cells, which may be related to cancers. Some cancers can use AS to produce proteins that are conducive to the proliferation and invasion of cancer cells (Dargahi et al, 2014). Emerging studies suggest that abnormal AS events are closely related to the development of cancers (Oltean and Bates, 2014;Climente-Gonzalez et al, 2017;Singh and Eyras, 2017;Zong et al, 2018;Yang et al, 2019) and some AS events are targets of prognosis and treatment (Pajares et al, 2007;Venables et al, 2008;Griffith et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Comprehensive Analysis of Prognostic Alternative Splicing Signatures in Endometrial Cancer

Chen

et al. 2020

Front. Genet.

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Background: Alternative splicing (AS) is one of the critical post-transcriptional regulatory mechanisms of various cancers and also plays a crucial role in the development of cancers, including endometrial cancer (EC). Methods: The splicing data and gene expression profiles of EC were obtained from The Cancer Genome Atlas. The corresponding clinical data were extracted from TCGA-CDR. With univariate Cox regression analysis, least absolute shrinkage and selection operator model, and multivariate Cox regression analysis, the survival-related AS events were selected. Functional enrichment analysis was also performed to investigate the functions of these AS events. Splicing factors and AS regulation network were constructed to understand the correlation among these AS events. Result: A total of 1826 AS events were identified as survival-related events. Functional enrichment analysis showed that these AS events were associated with several immune system-related processes. Then, the prognostic signatures were developed based on these survival-related events and acted as an independent prognostic factor for EC. Splicing factors and AS regulation network were also constructed to understand the regulatory mechanisms of AS events in EC. Conclusion: This study systematically analyzed the role of AS events in EC and developed the prognostic model for EC.

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“…Large-scale expression analyses in multiple tumor types have produced a catalogue of splicing isoforms related to malignant transformation (Dorman et al 2014; Brooks et al 2014, Tsai et al 2015; DiFeo et al 2009, Dargahi et al 2014). Similarly, splicing regulators displaying mutations or differential expression in cancer cells have been identified.…”

Section: Alternative Splicing Events In Glioblastoma Developmentmentioning

confidence: 99%

RNA processing as an alternative route to attack glioblastoma

et al. 2017

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Genomic analyses have become an important tool to identify new avenues for therapy. This is especially true for cancer types with extremely poor outcomes, since our lack of effective therapies offers no tangible clinical starting point to build upon. The highly malignant brain tumor glioblastoma (GBM) exemplifies such a refractory cancer, with only 15 month average patient survival. Analyses of several hundred GBM samples compiled by the TCGA (The Cancer Genome Atlas) have produced an extensive transcriptomic map, identified prevalent chromosomal alterations, and defined important driver mutations. Unfortunately, clinical trials based on these results have not yet delivered an improvement on outcome. It is, therefore, necessary to characterize other regulatory routes known for playing a role in tumor relapse and response to treatment. Alternative splicing affects more than 90% of the human coding genes and it is an important source for transcript variation and gene regulation. Mutations and alterations in splicing factors are highly prevalent in multiple cancers, demonstrating the potential for splicing to act as a tumor driver. As a result, numerous genes are expressed as cancer-specific splicing isoforms that are functionally distinct from the canonical isoforms found in normal tissue. These include genes that regulate cancer-critical pathways such as apoptosis, DNA repair, cell proliferation, and migration. Splicing defects can even induce genomic instability, a common characteristic of cancer, and a driver of tumor evolution. Importantly, components of the splicing machinery are targetable; multiple drugs can inhibit splicing factors or promote changes in splicing which could be exploited to begin improving clinical outcomes. Here, we review the current literature and present a case for exploring RNA processing as therapeutic route for the treatment of GBM.

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A Pan-Cancer Analysis of Alternative Splicing Events Reveals Novel Tumor-Associated Splice Variants of Matriptase

Cited by 9 publications

References 40 publications

SURVIV for survival analysis of mRNA isoform variation

SURVIV for survival analysis of mRNA isoform variation

Comprehensive Analysis of Prognostic Alternative Splicing Signatures in Endometrial Cancer

RNA processing as an alternative route to attack glioblastoma

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