Evidence map›Paper›PMID 31644551›Full record

ArticlePloS one2019

SpliceHetero: An information theoretic approach for measuring spliceomic intratumor heterogeneity from bulk tumor RNA-seq.

Minsu Kim, Sangseon Lee, Sangsoo Lim, Sun Kim

Abstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Minsu KimInterdisciplinary Program in Bioinformatics, Seoul National University, Seoul, 08826, Korea.
Sangseon LeeInterdisciplinary Program in Bioinformatics, Seoul National University, Seoul, 08826, Korea.
Sangsoo LimDepartment of Computer Science and Engineering, Seoul National University, Seoul, 08826, Korea.
Sun KimDepartment of Computer Science and Engineering, Seoul National University, Seoul, 08826, Korea.ORCID 0000-0001-5385-9546

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

motivationIntratumor heterogeneity (ITH) represents the diversity of cell populations that make up cancer tissue. The level of ITH in a tumor is usually measured by a genomic variation profile, such as copy number variation and somatic mutation. However, a recent study has identified ITH at the transcriptome level and suggested that ITH at gene expression levels is useful for predicting prognosis. Measuring ITH levels at the spliceome level is a natural extension. There are serious technical challenges in measuring spliceomic ITH (sITH) from bulk tumor RNA sequencing (RNA-seq) due to the complex splicing patterns.

resultsWe propose an information-theoretic method to measure the sITH of bulk tumors to overcome the above challenges. This method has been extensively tested in experiments using synthetic data, xenograft tumor data, and TCGA pan-cancer data. As a result, we showed that sITH is closely related to cancer progression and clonal heterogeneity, along with clinically significant features such as cancer stage, survival outcome and PAM50 subtype. As far as we know, it is the first study to define ITH at the spliceome level. This method can greatly improve the understanding of cancer spliceome and has great potential as a diagnostic and prognostic tool.

Indexed as

Biomarkers, TumorGenetic HeterogeneityRNA SplicingAlgorithmsComputational BiologyDNA Copy Number VariationsHigh-Throughput Nucleotide SequencingHumansNeoplasmsReproducibility of ResultsSequence Analysis, RNASpliceosomesBiomarkers, Tumor

Identifiers

PMID31644551
PMCPMC6808416

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.