Evidence map›Paper›PMID 36293319›Full record

ArticleInternational journal of molecular sciences2022

Identification of Prognostic Gene Signatures by Developing a scRNA-Seq-Based Integration Approach to Predict Recurrence and Chemotherapy Benefit in Stage II-III Colorectal Cancer.

Zixuan Wang, Kaiyuan Xing, Bo Zhang, Yanru Zhang, Tengyue Chai, Jingkai Geng, Xuexue Qin, Xinxin Zhang, Chaohan Xu

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of molecular sciences, 2022. 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
0.3field-weighted citation impact, top 40% 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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Article
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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

9 authors at 1 institution in 1 country.

Zixuan WangCollege of Bioinformatics Science and Technology, Harbin Medical University, No. 194, Xue-Fu Road, Nangang Region, Harbin 150081, China.
Kaiyuan XingCollege of Bioinformatics Science and Technology, Harbin Medical University, No. 194, Xue-Fu Road, Nangang Region, Harbin 150081, China.
Bo ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, No. 194, Xue-Fu Road, Nangang Region, Harbin 150081, China.
Yanru ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, No. 194, Xue-Fu Road, Nangang Region, Harbin 150081, China.
Tengyue ChaiCollege of Bioinformatics Science and Technology, Harbin Medical University, No. 194, Xue-Fu Road, Nangang Region, Harbin 150081, China.
Jingkai GengCollege of Bioinformatics Science and Technology, Harbin Medical University, No. 194, Xue-Fu Road, Nangang Region, Harbin 150081, China.
Xuexue QinCollege of Bioinformatics Science and Technology, Harbin Medical University, No. 194, Xue-Fu Road, Nangang Region, Harbin 150081, China.
Xinxin ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, No. 194, Xue-Fu Road, Nangang Region, Harbin 150081, China.
Chaohan XuCollege of Bioinformatics Science and Technology, Harbin Medical University, No. 194, Xue-Fu Road, Nangang Region, Harbin 150081, China.
Harbin Medical University · CN

Funding

Department of Heilongjiang Province Grant No. 12541415Heilongjiang Natural Science Fund Project Grant No. LH2019C087HMU Marshal Initiative Funding Grant Nos. HMUMIF-21008Innovative Scientific Research Fund of Harbin Medical University Grant number 2021-KYYWF-0279National Science Foundation of Heilongjiang Province Grant Nos. YQ2019C012Postdoctoral project of Heilongjiang Province Grant No. LBH-Z14130
6 · The paper itself

Abstract

Prospective identification of robust biomarkers related to prognosis and adjuvant chemotherapy has become a necessary and critical step to predict the benefits of adjuvant therapy for patients with stage II-III colorectal cancer (CRC) before clinical treatment. We proposed a single-cell-based prognostic biomarker recognition approach to identify and construct CRC up- and down-regulated prognostic signatures (CUPsig and CDPsig) by integrating scRNA-seq and bulk datasets. We found that most genes in CUPsig and CDPsig were known disease genes, and they had good prognostic abilities in CRC validation datasets. Multivariate analysis confirmed that they were two independent prognostic factors of disease-free survival (DFS). Significantly, CUPsig and CDPsig could effectively predict adjuvant chemotherapy benefits in drug-treated validation datasets. Additionally, they also performed well in patients with CMS4 subtype. Subsequent analysis of drug sensitivity showed that expressions of these two signatures were significantly associated with the sensitivities of CRC cell lines to multiple drugs. In summary, we proposed a novel prognostic biomarker identification approach, which could be used to identify novel prognostic markers for stage II-III CRC patients who will undergo adjuvant chemotherapy and facilitate their further personalized treatments.

Indexed as

Biomarkers, TumorColorectal NeoplasmsChemotherapy, AdjuvantGene Expression ProfilingHumansNeoplasm StagingPrognosisProspective StudiesSingle-Cell AnalysisBiomarkers, Tumorbulk dataCRCprognostic signaturescRNA-seq

Identifiers

PMID36293319
PMCPMC9604003
OpenAlexW4306742442

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.