Evidence map›Paper›PMID 31949492›Full record

ArticleJournal of Cancer2020

An Exon Signature to Estimate the Tumor Mutational Burden of Right-sided Colon Cancer Patients.

Wenbing Guo, Yelin Fu, Liangliang Jin, Kai Song, Ruihan Yu, Tianhao Li, Lishuang Qi, Yunyan Gu, Wenyuan Zhao, Zheng Guo

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of Cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Wenbing GuoCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China;
Yelin FuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China;
Liangliang JinCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China;
Kai SongCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China;
Ruihan YuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China;
Tianhao LiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China;
Lishuang QiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China;
Yunyan GuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China;
Wenyuan ZhaoCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China;
Zheng GuoCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China;

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The clinical applicability of the whole-exome sequencing (WES) in estimating tumor mutational burden (TMB) is currently limited by high cost, time-consuming and tissue availability. And given to the differences in the mutational landscapes among different types of cancer, we aimed to develop a cancer-specific signature to estimate TMB for right-sided colon cancer patients (RCC). Using WES data of 315 RCC patients, we identified the exons in which the number of mutational sites of the coding DNA sequences associated with TMB through linear regression analysis. Then, among these exons, we extracted a signature composed by 102 exons (~0.13 Mbp) through a heuristic selection procedure. The TMB estimated by the signature was highly correlated with those calculated by WES in the discovery dataset (R

Indexed as

a cancer-specific signaturethe coding DNA sequencesthe right-sided colon cancertumor mutational burden

Identifiers

PMID31949492
PMCPMC6959028

What OpenQuestion holds

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Registered trials

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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.