Evidence map›Paper›PMID 41913937›Full record

ArticleCancer informatics2026

In Silico Analysis of the Dual Role of Tumor Microenvironment on Colon Cancer Subtypes.

Christianah Kehinde, Michelle Livesey, Yeuko Manganyi, Hocine Bendou

Abstract read
In one paragraph

Article in Cancer informatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Christianah KehindeComputational Biology Division, Faculty of Health Sciences, Integrative Biomedical Sciences, University of Cape Town, South Africa.
Michelle LiveseyDepartment of Pathology, Faculty of Health Sciences, Institute of Infectious Diseases and Molecular Medicine, University of Cape Town, South Africa.ORCID https://orcid.org/0000-0001-9277-6209
Yeuko ManganyiComputational Biology Division, Faculty of Health Sciences, Integrative Biomedical Sciences, University of Cape Town, South Africa.ORCID https://orcid.org/0009-0008-0909-7343
Hocine BendouComputational Biology Division, Faculty of Health Sciences, Integrative Biomedical Sciences, University of Cape Town, South Africa.ORCID https://orcid.org/0000-0001-5371-6107

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Colon cancer is a highly heterogeneous disease, marked by substantial intra- and inter-tumor variability. Investigating transcriptomic profiles can offer deeper insight into this heterogeneity. However, most genome-transcriptome studies on colon cancer have primarily focused on examining primary tumors and matched normal tissues, often neglecting the multi-stage disease progression. Objective: To establish unique molecular colon subtypes based on the progression in transcriptomic profiles. Additionally, to investigate the implicated factors, such as mutations and the tumor microenvironment (TME), that affect colon cancer progression and their implications for therapy. Methods: RNA-sequencing data from The Cancer Genome Atlas Colon Cancer (TCGA-COAD) cohort were obtained from the UCSC Xena database, including 47 early and 39 late-stage tumor samples. Heterogeneity was exposed by tracking cancer progression through the multi-stages of cancer development. Hierarchical clustering revealed colon subtypes with varying progression, and differentially expressed genes (DEGs) were identified between these subtypes. The DEGs were subjected to Recursive Feature Elimination and mutational analyses to reveal driver genes. The TME and biological pathways were analyzed. The study was validated with an independent GEO dataset. Results: Two novel colon subtypes were identified. Significant enrichment pathways and varied mutations in cancer driver genes were found in both subtypes. Interestingly, concurrent downregulation of oncogenes and tumor suppressor genes was observed in one of the subtypes, suggesting a link to the dual functionality of CD4 and CD8 T-cells in the TME. Conclusion: Overall, our study demonstrates a complex relationship between TME and gene expression of driver genes. The presence of immune cell fractions with dual functions suggests a balanced early-to-late-stage progression. The findings provide insights into the disease progression that potentially contribute to the development of targeted therapies.

Indexed as

colon cancerheterogeneitysubtypingtargeted therapytumor microenvironment

Identifiers

PMID41913937
PMCPMC13033067

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.