Evidence map›Paper›PMID 34306573›Full record

ArticleComputational and structural biotechnology journal2021

Using bioinformatics approaches to investigate driver genes and identify BCL7A as a prognostic gene in colorectal cancer.

Jeffrey Yung-Chuan Chao, Hsin-Chuan Chang, Jeng-Kai Jiang, Chih-Yung Yang, Fang-Hsin Chen, Yo-Liang Lai, Wen-Jen Lin, Chia-Yang Li, Shu-Chi Wang, Muh-Hwa Yang and 2 more

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PubMed Full text at PMC Publisher
In one paragraph

Article in Computational and structural biotechnology journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.8field-weighted citation impact, top 30% of its field
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

5 citing papers in PubMed, 7 citations in OpenAlex.

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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

12 authors at 7 institutions in 1 country.

Jeffrey Yung-Chuan ChaoInstitute of Clinical Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.
Hsin-Chuan ChangInstitute of Microbiology and Immunology, National Yang Ming Chiao Tung University, Taipei, Taiwan.
Jeng-Kai JiangDivision of Colon & Rectal Surgery, Department of Surgery, Taipei Veterans General Hospital, Taipei, Taiwan.
Chih-Yung YangDepartment of Teaching and Research, Taipei City Hospital, Taipei, Taiwan.
Fang-Hsin ChenDepartment of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan, Taiwan.
Yo-Liang LaiDepartment of Radiation Oncology, China Medical University Hospital, Taichung, Taiwan.
Wen-Jen LinGraduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan.
Chia-Yang LiDepartment of Medical Laboratory Science and Biotechnology, College of Health Sciences, Kaohsiung Medical University, Kaohsiung 80708, Taiwan.
Shu-Chi WangDivision of Medical Oncology, Taipei Veterans General Hospital, Taipei 112, Taiwan.
Muh-Hwa YangInstitute of Clinical Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.
Yu-Feng LinDepartment of Medical Laboratory Science and Biotechnology, College of Medical and Health Science, Asia University, Taichung, Taiwan.
Wei-Chung ChengGraduate Institute of Biomedical Science, China Medical University, Taichung, Taiwan.
National Yang Ming Chiao Tung University · TWChina Medical University · TWKaohsiung Medical University · TWAsia University · TWChang Gung University · TWNational United University · TWTaipei Veterans General Hospital · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Colorectal cancer (CRC) results from the uncontrolled growth of cells in the colon, rectum, or appendix. The 5-year relative survival rate for patients with CRC is 65% and is correlated with the stage at diagnosis (being 91% for stage I at diagnosis versus 12% for stage IV). This study aimed to identify CRC driver genes to assist in the design of a cancer panel to detect gene mutations during clinical early-stage screening and identify genes for use in prognostic assessments and the evaluation of appropriate treatment options. First, we utilized bioinformatics approaches to analyze 354 paired sequencing profiles from The Cancer Genome Atlas (TCGA) to identify CRC driver genes and analyzed the sequencing profiles of 38 patients with >5 years of follow-up data to search for prognostic genes. The results revealed eight driver genes and ten prognostic genes. Next, the presence of the identified gene mutations was verified using tissue and blood samples from Taiwanese CRC patients. The results showed that the set identified gene mutations provide high coverage for driver gene screening, and

Indexed as

Cancer panelColorectal cancerDriver genesNext generation sequencingPrognostic genes

Identifiers

PMID34306573
PMCPMC8280477
OpenAlexW3180151410

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.