Evidence map›Paper›PMID 38430268›Full record

ArticleCancer immunology, immunotherapy : CII2024

Construction of an immune predictive model and identification of TRIP6 as a prognostic marker and therapeutic target of CRC by integration of single-cell and bulk RNA-seq data.

Wenjun Liu, Xitu Luo, Zilang Zhang, Yepeng Chen, Yongliang Dai, Jianzhong Deng, Chengyu Yang, Hao Liu

Abstract read
In one paragraph

Article in Cancer immunology, immunotherapy : CII, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
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

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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

9 citing papers in PubMed.

  1. Article
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  4. Prognosis of intensive care unit patients with colorectal cancer.World journal of gastrointestinal oncology · 2025
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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

8 authors.

Wenjun Liu *The First Department of General Surgery, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510150, Guangdong, China.
Xitu Luo *The First Department of General Surgery, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510150, Guangdong, China.
Zilang Zhang *Department of Anorectal Surgery, The First People's Hospital of Foshan, Guangdong, 528010, China.
Yepeng ChenThe First Department of General Surgery, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510150, Guangdong, China.
Yongliang DaiThe First Department of General Surgery, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510150, Guangdong, China.
Jianzhong DengDepartment of Anorectal Surgery, The First People's Hospital of Foshan, Guangdong, 528010, China.
Chengyu YangThe First Department of General Surgery, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510150, Guangdong, China.
Hao LiuDivision of Vascular and Interventional Radiology, Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, 510000, Guangdong, China. droctorliu24@163.com.

Funding

Foshan Municipal Health Commission 2019C020Guangzhou Municipal Health Commission 2023C-TS45
6 · The paper itself

Abstract

backgroundInvestigations elucidating the complex immunological mechanisms involved in colorectal cancer (CRC) and accurately predicting patient outcomes via bulk RNA-Seq analysis have been notably limited. This study aimed to identify the immune status of CRC patients, construct a prognostic model, and identify prognostic signatures via bulk RNA sequencing (RNA-seq) and single-cell RNA-seq (scRNA-seq).

methodsThe scRNA-seq data of CRC were downloaded from Gene Expression Omnibus (GEO). The UCSC Xena database was used to obtain bulk RNA-seq data. Differentially expressed gene (DEG), functional enrichment, and random forest analyses were conducted in order to identify core genes associated with colorectal cancer (CRC) that were relevant to prognosis. A molecular immune prediction model was developed using logistic regression after screening features using the least absolute shrinkage and selection operator (LASSO). The differences in immune cell infiltration, mutation, chemotherapeutic drug sensitivity, cellular senescence, and communication between patients who were at high and low risk of CRC according to the predictive model were investigated. The prognostic genes that were closely associated with CRC were identified by random survival forest (RSF) analysis. The expression levels and clinical significance of the hub genes were analyzed in vitro. The LoVo cell line was employed to ascertain the biological role of thyroid hormone receptor-interacting protein 6 (TRIP6).

resultsA total of seven main cell subtypes were identified by scRNA-seq analysis. A molecular immune predictive model was constructed based on the risk scores. The risk score was significantly associated with OS, stage, mutation burden, immune cell infiltration, response to immunotherapy, key pathways, and cell-cell communication. The functions of the six hub genes were determined and further utilized to establish a regulatory network. Our findings unequivocally confirmed that TRIP6 upregulation was verified in the CRC samples. After knocking down TRIP6, cell proliferation, migration, and invasion of LoVo cells were inhibited, and apoptosis was promoted.

conclusionsThe molecular predictive model reliably distinguished the immune status of CRC patients. We further revealed that TRIP6 may act as an oncogene in CRC, making it a promising candidate for targeted therapy and as a prognostic marker for CRC.

Indexed as

Colorectal NeoplasmsImmunotherapyAdaptor Proteins, Signal TransducingHumansLIM Domain ProteinsPrognosisRNA-SeqSequence Analysis, RNATranscription FactorsAdaptor Proteins, Signal TransducingLIM Domain ProteinsTranscription FactorsTRIP6 protein, humanColorectal cancerImmune landscapePrognosisSingle-cell RNA sequencingTRIP6

Identifiers

PMID38430268
PMCPMC10908634

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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.