Evidence map›Paper›PMID 35861108›Full record

ArticleCancer medicine2023

Cancer carrier screening in the general population using whole-genome sequencing.

Ya-Sian Chang, Dy-San Chao, Chin-Chun Chung, Yu-Pao Chou, Chieh-Min Chang, Chia-Li Lin, Hou-Wei Chu, Hon-Da Chen, Ting-Yuan Liu, Yu-Hsuan Juan and 2 more

Abstract read
In one paragraph

Article in Cancer medicine, 2023. 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

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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.

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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.

Ya-Sian ChangCenter for Precision Medicine, China Medical University Hospital, Taichung, Taiwan.
Dy-San ChaoCenter for Precision Medicine, China Medical University Hospital, Taichung, Taiwan.
Chin-Chun ChungCenter for Precision Medicine, China Medical University Hospital, Taichung, Taiwan.
Yu-Pao ChouCenter for Precision Medicine, China Medical University Hospital, Taichung, Taiwan.
Chieh-Min ChangCenter for Precision Medicine, China Medical University Hospital, Taichung, Taiwan.
Chia-Li LinCenter for Precision Medicine, China Medical University Hospital, Taichung, Taiwan.
Hou-Wei ChuInstitute of Biomedical Sciences|, Academia Sinica, Taipei, Taiwan.
Hon-Da ChenCenter for Precision Medicine, China Medical University Hospital, Taichung, Taiwan.
Ting-Yuan LiuCenter for Precision Medicine, China Medical University Hospital, Taichung, Taiwan.
Yu-Hsuan JuanCenter for Precision Medicine, China Medical University Hospital, Taichung, Taiwan.
Shun-Jen ChangDepartment of Kinesiology, Health and Leisure Studies, National University of Kaohsiung, Kaohsiung, Taiwan.
Jan-Gowth ChangCenter for Precision Medicine, China Medical University Hospital, Taichung, Taiwan.ORCID 0000-0003-0375-1427

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCancer is a major cause of death, and its early identification and intervention have potential for clinical actionability and benefits for human health. The studies using whole-genome sequencing (WGS) and large samples analysis of cancer-related genes have been rarely done.

methodsWe performed WGS to explore germline mutations in coding and non-coding areas of cancer-related genes and non-coding driver genes and regulatory areas. Structural variants (SVs) was also analyzed. We used several tools and a subgrouping method to analyze the variants in 1491 healthy participants. Moreover, 275 cancer-related genes sequencing was carried out in 125 cancer patients.

resultsThe incidence of familial cancer in the Taiwanese general population is 8.79% (131/1491). Cancer carrier rate of cancer-related genes is about 7.04% (105/1491) for pathogenic/likely pathogenic variants (P/LP) on ClinVar database only, and 28.24% (421/1491) for P/LP and loss of function variants. The carrier frequencies of cancer-related genes P/LP on ClinVar database were as follows: 8.40% (11/131), 7.11% (28/394), and 6.83% (66/966) in FC, 1MC, and nMC, respectively. The SVs and non-coding driver gene variants are uncommon. There are 1.54% (23/1491) of actionable cancer genes in American College of Medical Genetics and Genomics (ACMG), and the germline mutation rate of 275 cancer-related genes is 7.2% (9/125) in cancer patients including 4.0% (5/125) of actionable cancer genes in ACMG. After analyzing the frequencies of P/LP variants on GJB2 and SLC25A13 genes, we suggest that these two genes may not be cancer-related genes and need be re-evaluated.

conclusionsWGS analysis can completely detect germline mutations in cancer carriers. This study use subgrouping approach for samples provides a strategy to study whether a gene or variant is a cancer-related gene or variant in the future studies.

Indexed as

Genetic Predisposition to DiseaseNeoplasmsEarly Detection of CancerHumansMitochondrial Membrane Transport ProteinsOncogenesWhole Genome SequencingMitochondrial Membrane Transport ProteinsSLC25A13 protein, humanGJB2SLC25A13variant analysiswhole-genome sequencing

Identifiers

PMID35861108
PMCPMC9883534

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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.