Evidence map›Paper›PMID 38826219›Full record

ArticleResearch square2024

Single-cell transcriptomics reveals stage- and side-specificity of gene modules in colorectal cancer.

Sara Rahiminejad, Kavitha Mukund, Mano Ram Maurya, Shankar Subramaniam

Abstract readPreprint
In one paragraph

Article in Research square, 2024. 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

4 authors.

Sara RahiminejadUniversity of California, San Diego.
Kavitha MukundUniversity of California, San Diego.
Mano Ram MauryaUniversity of California, San Diego.
Shankar SubramaniamUniversity of California, San Diego.

Funding

Systems Biology Analyses for Hemodynamic Regulation of Vascular HomeostasisR01HL108735 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI CHIEN, SHU, SHYY, JOHN YJ · 2012 to 2024
$13.4M
Biomedical Data Commons Workbench (BDCW)OT2OD030544 · OD · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SUBRAMANIAM, SHANKAR · 2020 to 2024
$3.2M
Reconstruction and Modeling of Dynamical Molecular NetworksR01LM012595 · NLM · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SUBRAMANIAM, SHANKAR · 2018 to 2021
$1.3M
NHLBI NIH HHS R01 HL108735NIH HHS OT2 OD030544NLM NIH HHS R01 LM012595Wellcome Trust
6 · The paper itself

Abstract

backgroundAn understanding of mechanisms underlying colorectal cancer (CRC) development and progression is yet to be fully elucidated. This study aims to employ network theoretic approaches to analyse single cell transcriptomic data from CRC to better characterize its progression and sided-ness.

methodsWe utilized a recently published single-cell RNA sequencing data (GEO-GSE178341) and parsed the cell X gene data by stage and side (right and left colon). Using Weighted Gene Co-expression Network Analysis (WGCNA), we identified gene modules with varying preservation levels (weak or strong) of network topology between early (pT1) and late stages (pT234), and between right and left colons. Spearman's rank correlation (

resultsEqualizing cell counts across different stages, we detected 13 modules for the early stage, two of which were non-preserved in late stages. Both non-preserved modules displayed distinct gene connectivity patterns between the early and late stages, characterized by low

conclusionsWe identified modules with topological and functional differences specific to cell types between the early and late stages, and between the right and left colons. This study enhances the understanding of roles played by different cell types at different stages and sides, providing valuable insights for future studies focused on the diagnosis and treatment of CRC.

Indexed as

early tumor stagefunctional enrichmentlate tumor stageleft colonmodularityright colonscRNA-seqWGCNA

Identifiers

PMID38826219
PMCPMC11142301

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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.