Evidence map›Paper›PMID 33719152›Full record

ArticleJournal of cellular and molecular medicine2021

Two novel qualitative transcriptional signatures robustly applicable to non-research-oriented colorectal cancer samples with low-quality RNA.

Jun Cheng, Yating Guo, Guoxian Guan, Haiyan Huang, Fengle Jiang, Jun He, Junling Wu, Zheng Guo, Xing Liu, Lu Ao

Open access · goldAbstract read
In one paragraph

Article in Journal of cellular and molecular medicine, 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
0.3field-weighted citation impact, top 45% 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, 4 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

10 authors at 1 institution in 1 country.

Jun ChengAffiliated Foshan Maternity and Child Healthcare Hospital, Southern Medical University (Foshan Maternity & Child Healthcare Hospital), Foshan, China.
Yating GuoDepartment of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China.
Guoxian GuanDepartment of Colorectal Surgery, The Affiliated Union Hospital of Fujian Medical University, Fuzhou, China.
Haiyan HuangDepartment of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China.
Fengle JiangDepartment of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China.
Jun HeDepartment of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China.
Junling WuDepartment of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China.
Zheng GuoDepartment of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China.
Xing LiuDepartment of Colorectal Surgery, The Affiliated Union Hospital of Fujian Medical University, Fuzhou, China.
Lu AoDepartment of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China.ORCID 0000-0001-7378-4967
Fujian Medical University · CN

Funding

Joint research program of health and education in Fujian Province 2019-WJ-32Joint Scientific and Technology Innovation Fund of Fujian Province 2018Y9065National Natural Science Foundation of China 61801118National Natural Science Foundation of China 81602738Natural Science Foundation of Fujian Province 2020J01600
6 · The paper itself

Abstract

Currently, due to the low quality of RNA caused by degradation or low abundance, the accuracy of gene expression measurements by transcriptome sequencing (RNA-seq) is very challenging for non-research-oriented clinical samples, majority of which are preserved in hospitals or tissue banks worldwide with complete pathological information and follow-up data. Molecular signatures consisting of several genes are rarely applied to such samples. To utilize these resources effectively, 45 stage II non-research-oriented samples which were formalin-fixed paraffin-embedded (FFPE) colorectal carcinoma samples (CRC) using RNA-seq have been analysed. Our results showed that although gene expression measurements were significantly affected, most cancer features, based on the relative expression orderings (REOs) of gene pairs, were well preserved. We then developed two REO-based signatures, which consisted of 136 gene pairs for early diagnosis of CRC, and 4500 gene pairs for predicting post-surgery relapse risk of stage II and III CRC. The performance of our signatures, which included hundreds or thousands of gene pairs, was more robust for non-research-oriented clinical samples, compared to that of two published concise REO-based signatures. In conclusion, REO-based signatures with relatively more gene pairs could be robustly applied to non-research-oriented CRC samples.

Indexed as

Gene Expression Regulation, NeoplasticTranscriptomeBase SequenceBiomarkers, TumorColorectal NeoplasmsDatabases, GeneticEarly DiagnosisGene Expression ProfilingHumansProtein Interaction MapsRNATranscription, GeneticBiomarkers, TumorRNAcolorectal cancerlow-quality RNAnon-research-oriented clinical samplesrelative expression orderingstranscriptional signature

Identifiers

PMID33719152
PMCPMC8034468
OpenAlexW3139374379

What OpenQuestion holds

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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.