Evidence map›Paper›PMID 31927530›Full record

ArticleAging2020

Low-abundance mutations in colorectal cancer patients and healthy adults.

Yanfei Li, Zhengsheng Dai, Gang Huang, Yueling Jin, Zhongping Ning, Junwei Shen

Open access · greenAbstract read
In one paragraph

Article in Aging, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.1field-weighted citation impact, top 55% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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

6 authors at 2 institutions in 1 country.

Yanfei LiShanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Shanghai, China.
Zhengsheng DaiShanghai Pudong Hospital Affiliated to Fudan University, Shanghai, China.
Gang HuangShanghai University of Medicine and Health Sciences, Shanghai, China.
Yueling JinShanghai University of Medicine and Health Sciences, Shanghai, China.
Zhongping NingShanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Shanghai, China.
Junwei ShenShanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Shanghai, China.
Shanghai University of Medicine and Health Sciences · CNPudong Medical Center · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Detecting low-abundance mutations is very important for cancer diagnosis and treatment. Here we describe an improved targeted sequencing analysis that dramatically increases sequencing depth. Seven colorectal cancer (CRC) patients and seven healthy adults were enrolled in this study. We examined genetic mutations in tissue samples from the central and peripheral regions of tumors from the CRC patients and in blood cells from the healthy adults. We observed that each CRC carried larger numbers of mutations more than previously estimated. These included numerous deletion mutations in the tumor tissue. While the cellular morphology in the surrounding normal colonic tissues was healthy, these cells also carried many mutations. Similarly, the blood cells from the healthy donors carried numerous mutations. These findings shed new light on the processes of tumorigenesis and aging, and also present a potentially effective method for detecting low-abundance mutations for cancer diagnosis and targeted treatments.

Indexed as

Biomarkers, TumorGenetic Predisposition to DiseaseMutationCase-Control StudiesColorectal NeoplasmsDNA Mutational AnalysisGene ExpressionGenetic Association StudiesHumansImmunohistochemistryBiomarkers, Tumorcolorectal cancerhealthlow-abundancemutation

Identifiers

PMID31927530
PMCPMC6977685
OpenAlexW2998802018

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.