Evidence map›Paper›PMID 36389763›Full record

ArticleFrontiers in immunology2022

Identification and validation of immunotherapy for four novel clusters of colorectal cancer based on the tumor microenvironment.

Xiaoyong Zheng, Yajie Ma, Yan Bai, Tao Huang, Xuefeng Lv, Jinhai Deng, Zhongquan Wang, Wenping Lian, Yalin Tong, Xinyu Zhang and 4 more

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 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed
5.5field-weighted citation impact, top 3% 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

45 citing papers in PubMed, 56 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

14 authors at 5 institutions in 2 countries.

Xiaoyong ZhengDepartment of Digestion, Henan Provincial Third People's Hospital, Zhengzhou, China.
Yajie MaDepartment of Medical Affair, Henan Provincial Third People's Hospital, Zhengzhou, China.
Yan BaiDepartment of Digestion, Zhengzhou First People's Hospital, Zhengzhou, China.
Tao HuangMedical School, Huanghe Science and Technology University, Zhengzhou, China.
Xuefeng LvDepartment of Clinical Laboratory, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Jinhai DengRichard Dimbleby Department of Cancer Research, Comprehensive Cancer Centre, Kings College London, London, United Kingdom.
Zhongquan WangDepartment of Clinical Laboratory, Henan Provincial Third People's Hospital, Zhengzhou, China.
Wenping LianDepartment of Clinical Laboratory, Henan Provincial Third People's Hospital, Zhengzhou, China.
Yalin TongDepartment of Digestion, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Xinyu ZhangDepartment of Medical Affair, Henan Provincial Third People's Hospital, Zhengzhou, China.
Miaomiao YueDepartment of Digestion, Henan Provincial Third People's Hospital, Zhengzhou, China.
Yan ZhangDepartment of Digestion, Henan Provincial Third People's Hospital, Zhengzhou, China.
Lifeng LiMedical School, Huanghe Science and Technology University, Zhengzhou, China.
Mengle PengDepartment of Clinical Laboratory, Henan Provincial Third People's Hospital, Zhengzhou, China.
Henan Provincial People's Hospital · CNFirst Affiliated Hospital of Zhengzhou University · CNHuanghe Science and Technology College · CNKing's College London · GBZhengzhou People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The incidence and mortality of colorectal cancer (CRC) are increasing year by year. The accurate classification of CRC can realize the purpose of personalized and precise treatment for patients. The tumor microenvironment (TME) plays an important role in the malignant progression and immunotherapy of CRC. An in-depth understanding of the clusters based on the TME is of great significance for the discovery of new therapeutic targets for CRC. We extracted data on CRC, including gene expression profile, DNA methylation array, somatic mutations, clinicopathological information, and copy number variation (CNV), from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) (four datasets-GSE14333, GSE17538, GSE38832, and GSE39582), cBioPortal, and FireBrowse. The MCPcounter was utilized to quantify the abundance of 10 TME cells for CRC samples. Cluster repetitive analysis was based on the Hcluster function of the Pheatmap package in R. The ESTIMATE package was applied to compute immune and stromal scores for CRC patients. PCA analysis was used to remove batch effects among different datasets and transform genome-wide DNA methylation profiling into methylation of tumor-infiltrating lymphocyte (MeTIL). We evaluated the mutation differences of the clusters using MOVICS, DeconstructSigs, and GISTIC packages. As for therapy, TIDE and SubMap analyses were carried out to forecast the immunotherapy response of the clusters, and chemotherapeutic sensibility was estimated based on the pRRophetic package. All results were verified in the TCGA and GEO data. Four immune clusters (ImmClust-CS1, ImmClust-CS2, ImmClust-CS3, and ImmClust-CS4) were identified for CRC. The four ImmClusts exhibited distinct TME compositions, cancer-associated fibroblasts (CAFs), functional orientation, and immune checkpoints. The highest immune, stromal, and MeTIL scores were observed in CS2, in contrast to the lowest scores in CS4. CS1 may respond to immunotherapy, while CS2 may respond to immunotherapy after anti-CAFs. Among the four ImmClusts, the top 15 markers with the highest mutation frequency were acquired, and CS1 had significantly lower CNA on the focal level than other subtypes. In addition, CS1 and CS2 patients had more stable chromosomes than CS3 and CS4. The most sensitive chemotherapeutic agents in these four ImmClusts were also found. IHC results revealed that CD29 stained significantly darker in the cancer samples, indicating that their CD29 was highly expressed in colon cancer. This work revealed the novel clusters based on TME for CRC, which would guide in predicting the prognosis, biological features, and appropriate treatment for patients with CRC.

Indexed as

Colorectal NeoplasmsTumor MicroenvironmentDNA Copy Number VariationsHumansImmunotherapyPrognosisbioinformaticsclusterscolorectal cancerimmunotherapytumor microenvironment

Identifiers

PMID36389763
PMCPMC9650243
OpenAlexW4307511576

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.