Evidence map›Paper›PMID 32964043›Full record

ArticleBioMed research international2020

MicroRNA-Related Prognosis Biomarkers from High-Throughput Sequencing Data of Colorectal Cancer.

Xiao-Liang Xing, Zhi-Yong Yao, Ti Zhang, Ning Zhu, Yuan-Wu Liu, Jing Peng

Open access · hybridAbstract read
In one paragraph

Article in BioMed research international, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.4field-weighted citation impact, top 46% 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

6 citing papers in PubMed, 7 citations in OpenAlex.

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  6. Alterations in the CaExploration of targeted anti-tumor therapy · 2021
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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

6 authors at 3 institutions in 1 country.

Xiao-Liang XingXiangya Hospital, Central South University, Changsha, 410078 Hunan, China.
Zhi-Yong YaoHunan Provincial Key Laboratory for Synthetic Biology of Traditional Chinese Medicine, School of Public Health and Laboratory Medicine, Hunan University of Medicine, Huaihua, 418000 Hunan, China.ORCID https://orcid.org/0000-0002-5553-5171
Ti ZhangHunan Provincial Key Laboratory for Synthetic Biology of Traditional Chinese Medicine, School of Public Health and Laboratory Medicine, Hunan University of Medicine, Huaihua, 418000 Hunan, China.
Ning ZhuHunan Provincial Key Laboratory for Synthetic Biology of Traditional Chinese Medicine, School of Public Health and Laboratory Medicine, Hunan University of Medicine, Huaihua, 418000 Hunan, China.
Yuan-Wu LiuBeijing Advanced Innovation Center for Food Nutrition and Human Health, China Agricultural University, 100193 Beijing, China.ORCID https://orcid.org/0000-0001-5132-6252
Jing PengXiangya Hospital, Central South University, Changsha, 410078 Hunan, China.ORCID https://orcid.org/0000-0002-7804-0622
Hunan University of Traditional Chinese Medicine · CNCentral South University · CNChina Agricultural University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundColorectal cancer (CRC) is the third most common cancer in the world, and most of them are adenocarcinomas. CRC could be classified as colon adenocarcinoma (COAD) and rectum adenocarcinoma (READ) according to the original tumorigenesis position. Increasing evidences indicated that microRNAs (miRNAs) play an important role in the occurrence of multiple tumors.

methodsIn this study, we firstly downloaded miRNA (COAD, 8 controls vs. 455 tumors; READ, 3 controls vs. 161 tumors) and mRNA (COAD, 41 controls vs. 478 tumors; READ, 10 controls vs. 166 tumors) data from The Cancer Genome Atlas (TCGA) database and then used DESeq2, RegParallel, miRDB, TargetScanHuman 7.2, DAVID 6.8, STRING, and Cytoscape software to identify the potential prognosis biomarkers.

resultsWe identified 175 differential expression miRNAs (DEMs) and 3747 differential expression genes (DEGs) in COAD and 184 DEMs and 3928 DEGs in READ. And then, we obtained 21 (13 in COAD and 8 in READ) DEMs associated with the survival rates, which correlated with 440 (217 in COAD and 223 in READ) overlapping DEGs. Through survival analysis for those overlapping DEGs, we found 11 (8 in COAD and 3 in READ) overlapping DGEs associated with survival rates of patients, which were correlated with 9 (7 in COAD and 2 in READ) DEMs significantly.

conclusionIn this study, we found several candidate prognostic biomarkers which have been identified in various cancers and also found several new prognosis biomarkers of COAD and READ. In conclusion, this analysis based on theoretical knowledge and clinical outcomes we have done needs further confirmation by more researches.

Indexed as

AdenocarcinomaBiomarkers, TumorColorectal NeoplasmsGene Expression ProfilingGene Expression Regulation, NeoplasticGene Regulatory NetworksHigh-Throughput Nucleotide SequencingHumansMicroRNAsPrognosisRNA, MessengerSurvival AnalysisSurvival RateBiomarkers, TumorMicroRNAsRNA, Messenger

Identifiers

PMID32964043
PMCPMC7501550
OpenAlexW3083869100

What OpenQuestion holds

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LicenceCC BY
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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.