Evidence map›Paper›PMID 37355491›Full record

ArticleFunctional & integrative genomics2023

Integration of bulk RNA sequencing data and single-cell RNA sequencing analysis on the heterogeneity in patients with colorectal cancer.

Jiawei Zhang, Yangsheng Wu, Zhong Shen

Abstract read
In one paragraph

Article in Functional & integrative genomics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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

1 citing paper in PubMed.

  1. 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

3 authors.

Jiawei Zhang *The Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, 310053, China.
Yangsheng Wu *College of Life Science, Zhejiang Chinese Medical University, Hangzhou, 310053, China.
Zhong ShenDepartment of Coloproctology, The Hangzhou Third People's Hospital, the No.38 Westlake Avenue, Hangzhou City, 310009, Zhejiang Province, China. shenzhong114@sina.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) pathway has emerged as a critical innate immune pathway that could virtually impact nearly all aspects of tumorigenesis including colorectal cancer. This work aimed to develop and validate molecular subtypes related to cGAS-STING pathways for colorectal cancer using Bulk RNA-seq and single-cell RNA-seq (scRNA-seq) data. Bulk RNA-seq data were acquired from The Cancer Genome Atlas dataset (training dataset) and Gene Expression Omnibus dataset (validation dataset). Univariate COX survival analysis was utilized to identify prognostic differentially expressed genes (DEGs) from 6 immune pathways related to cGAS-STING. ConsensusClusterPlus package was used to classify different subtypes based on DEGs. scRNA-seq data were used to validate differences in immune status between different subtypes. Two clusters with distinct prognosis were identified based on 27 DEGs. The six cGAS-STING-related pathways had different levels of significance between the two clusters. Clust1 had most number of amplified CNVs and clust2 had the most number of loss CNVs. TP53 was the top mutated gene of which missense mutations contributed the most of single-nucleotide variants. Immune score of clust1 was higher than that in clust2, as reflected in macrophages, T cells, and natural killer cells. Three unfavorable genes and 31 protection factors were screened between the two clusters in three datasets. ScRNA-seq data analysis demonstrated that macrophages were more enriched in clust1, and tumor cells and immune cells had close interaction. We classified two distinct subtypes with different prognosis, mutation landscape, and immune characteristics.

Indexed as

CarcinogenesisColorectal NeoplasmsBase SequenceHumansNucleotidyltransferasesRNA-SeqNucleotidyltransferasesColorectal cancerImmuneMolecular subtypesPrognosisscRNA-seq

Identifiers

PMID37355491
PMCPMC10290593

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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.