Evidence map›Paper›PMID 36451813›Full record

ArticleFrontiers in immunology2022

Construction of a novel choline metabolism-related signature to predict prognosis, immune landscape, and chemotherapy response in colon adenocarcinoma.

Cong Liu, Dingwei Liu, Fangfei Wang, Yang Liu, Jun Xie, Jinliang Xie, Yong Xie

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
4.4field-weighted citation impact, top 4% 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

21 citing papers in PubMed, 40 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

7 authors at 3 institutions in 1 country.

Cong LiuDepartment of Gastroenterology, Digestive Disease Hospital, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.
Dingwei LiuDepartment of Gastroenterology, Digestive Disease Hospital, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.
Fangfei WangDepartment of Gastroenterology, Digestive Disease Hospital, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.
Yang LiuDepartment of Gastroenterology, Digestive Disease Hospital, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.
Jun XieDepartment of Gastroenterology, Digestive Disease Hospital, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.
Jinliang XieDepartment of Gastroenterology, Digestive Disease Hospital, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.
Yong XieDepartment of Gastroenterology, Digestive Disease Hospital, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.
Nanchang University · CNJiangxi Chest Hospital · CNFirst Affiliated Hospital of Nanchang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Colon adenocarcinoma (COAD) is a common digestive system malignancy with high mortality and poor prognosis. Accumulating evidence indicates that choline metabolism is closely related to tumorigenesis and development. However, the efficacy of choline metabolism-related signature in predicting patient prognosis, immune microenvironment and chemotherapy response has not been fully clarified. Methods: Choline metabolism-related differentially expressed genes (DEGs) between normal and COAD tissues were screened using datasets from The Cancer Genome Atlas (TCGA), Kyoto Encyclopedia of Genes and Genomes (KEGG), AmiGO2 and Reactome Pathway databases. Two choline metabolism-related genes (CHKB and PEMT) were identified by univariate and multivariate Cox regression analyses. TCGA-COAD was the training cohort, and GSE17536 was the validation cohort. Patients in the high- and low-risk groups were distinguished according to the optimal cutoff value of the risk score. A nomogram was used to assess the prognostic accuracy of the choline metabolism-related signature. Calibration curves, decision curve analysis (DCA), and clinical impact curve (CIC) were used to improve the clinical applicability of the prognostic signature. Gene Ontology (GO) and KEGG pathway enrichment analyses of DEGs in the high- and low-risk groups were performed. KEGG cluster analysis was conducted by the KOBAS-i database. The distribution and expression of CHKB and PEMT in various types of immune cells were analyzed based on single-cell RNA sequencing (scRNA-seq). The CIBERSORT and ESTIMATE algorithms evaluated tumor immune cell infiltration in the high- and low-risk groups. Evaluation of the half maximal inhibitory concentration (IC Results: We constructed and validated a choline metabolism-related signature containing two genes (CHKB and PEMT). The overall survival (OS) of patients in the high-risk group was significantly worse than that of patients in the low-risk group. The nomogram could effectively and accurately predict the OS of COAD patients at 1, 3, and 5 years. The DCA curve and CIC demonstrate the clinical utility of the nomogram. scRNA-seq showed that CHKB was mainly distributed in endothelial cells, while PEMT was mainly distributed in CD4 Conclusion: In conclusion, we constructed a choline metabolism-related signature in COAD and revealed its potential application value in predicting the prognosis, immune microenvironment, and chemotherapy response of patients, which may lay an important theoretical basis for future personalized precision therapy.

Indexed as

AdenocarcinomaColonic NeoplasmsAnimalsCD8-Positive T-LymphocytesCholineEndothelial CellsHumansMiceMolecular Docking SimulationPhosphatidylethanolamine N-MethyltransferasePrognosisTumor MicroenvironmentCholinePEMT protein, mousePhosphatidylethanolamine N-Methyltransferasechemotherapy responsecholine metabolismcolon adenocarcinomaimmuneprognostic

Identifiers

PMID36451813
PMCPMC9701742
OpenAlexW4309043385

What OpenQuestion holds

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Registered trials

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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.