Evidence map›Paper›PMID 34790389›Full record

ArticleJournal of gastrointestinal oncology2021

TCGA database analysis of the tumor mutation burden and its clinical significance in colon cancer.

Junjie Chen, Anwaier Apizi, Lin Wang, Guanting Wu, Zheng Zhu, Huihui Yao, Guoliang Chen, Xinyu Shi, Bo Shi, Qingliang Tai and 4 more

Abstract read
In one paragraph

Article in Journal of gastrointestinal oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
–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

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

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  8. Review
  9. Inhibition of colon cancer K-RasFrontiers in pharmacology · 2022
    Article
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.

Junjie Chen *Department of General Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China.
Anwaier Apizi *Department of Gastrointestinal Tumors, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
Lin Wang *Department of Gastrointestinal Tumors, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
Guanting WuDepartment of General Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China.
Zheng ZhuDepartment of General Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China.
Huihui YaoDepartment of General Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China.
Guoliang ChenDepartment of General Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China.
Xinyu ShiDepartment of General Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China.
Bo ShiDepartment of General Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China.
Qingliang TaiDepartment of General Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China.
Chenglong ShenDepartment of Gastrointestinal Surgery, Changshu No. 2 Hospital, Changshu, China.
Guoqiang ZhouDepartment of Gastrointestinal Surgery, Changshu No. 2 Hospital, Changshu, China.
Lingzhi WuDepartment of Oncology, The First Affiliated Hospital of Soochow University, Suzhou, China.
Songbing HeDepartment of General Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundColon cancer is one of the most common malignant tumors, with high rates of incidence and death. The tumor mutational burden (TMB), which is characterized by microsatellite instability, has been becoming a powerful predictor which can show tumor behavior and response to immunotherapy.

methodsIn this study, we analyzed 437 mutation data of colon cancer samples obtained from The Cancer Genome Atlas (TCGA) and divided patients into low- and high-TMB groups according to the TMB value. Then we identified differentially-expressed genes (DEGs), conducted immune cell infiltration and survival analyses between groups.

resultsThe higher TMB of the patients with colon cancer predicts a poorer prognosis. Functional analysis was performed to assess the prognostic value of the top 30 core genes. The CIBER-SORT algorithm was used to investigate the correlation between the immune cells and TMB subtypes. An immune prognosis model was constructed to screen out immune genes related to prognosis, and the tumor immunity assessment resource (TIMER) was then used to determine the correlation between gene expression and the abundance of tumor-infiltrating immune cell subsets in colon cancer. We observed that APC, TP53, TTN, KRAS, MUC16, SYNE1, PIK3CA have higher somatic mutations. DEGs enrichment analysis showed that they are involved in the regulation of neuroactive ligand-receptor interaction, the Cyclic adenosine monophosphate (cAMP) signaling pathway, the calcium signaling pathway, and pantothenate and Coenzyme A (CoA) biosynthesis. The difference in the abundance of various white blood cell subtypes showed that Cluster of Differentiation 8 (CD8) T cells (P=0.008), activated CD4 memory T cells (P=0.019), M1 macrophages (P=0.002), follicular helper T cells (P=0.034), activated Natural killer (NK cell) cells (P=0.017) increased remarkably, while M0 macrophages significantly reduced (P=0.025). The two immune model genes showed that secretin (SCT) was negatively correlated with survival, while Guanylate cyclase activator 2A (GUCA2A) was positively correlated.

conclusionsThis study conducted a systematically comprehensive analysis of the prediction and clinical significance of TMB in colon cancer in identification, monitoring, and prognosis of colon cancer, and providing reference information for immunotherapy.

Indexed as

colon cancerprognosisTCGATumor mutation burden (TMB)

Identifiers

PMID34790389
PMCPMC8576223

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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.