Evidence map›Paper›PMID 37359923›Full record

ArticleIndian journal of surgical oncology2023

Multi-omics Analysis Classifies Colorectal Cancer into Distinct Methylated Immunogenic and Angiogenic Subtypes Based on Anatomical Laterality.

Anu R I, Aastha Vatsyayan, Dileep Damodaran, Ambily Sivadas, Kurt Van der Speeten

Open access · greenAbstract read
In one paragraph

Article in Indian journal of surgical oncology, 2023. 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, top 76% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

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

5 authors at 4 institutions in 2 countries.

Anu R IDepartment of Cancer Biology and Therapeutics, MVR Cancer Center and Research Institute, Calicut, Kerala India.ORCID 0000-0001-7647-9976
Aastha VatsyayanCSIR Institute of Genomics and Integrative Biology (CSIR-IGIB), New Delhi, India.
Dileep DamodaranDepartment of Surgical Oncology, MVR Cancer Center and Research Institute, Calicut, Kerala India.
Ambily SivadasDivision of Nutrition, St. John's Research Institute, Bangalore, India.
Kurt Van der SpeetenDepartment of Surgical Oncology, Ziekenhuis Oost-Limburg, Genk, Belgium.
University of Calicut · INInstitute of Genomics and Integrative Biology · INSt. John's National Academy of Health Sciences · INZiekenhuis Oost-Limburg · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We employed supervised machine learning algorithms to a cohort of colorectal cancer patients from the NCI to differentiate and classify the heterogenous disease based on anatomical laterality and multi-omics stratification, in a first of its kind. Multi-omics integrative analysis shows distinct clustering of left and right colorectal cancer with disentangled representation of methylome and delineation of transcriptome and genome. We present novel multi-omics findings consistent with augmented hypermethylation of genes in right CRC, epigenomic biomarkers on the right in conjunction with immune-mediated pathway signatures, and lymphocytic invasion which unlocks unique therapeutic avenues. Contrarily, left CRC multi-omics signature is found to be marked by angiogenesis, cadherins, and epithelial-mesenchymal transition (EMT). An integrated multi-omics molecular signature of Supplementary Information: The online version contains supplementary material available at 10.1007/s13193-023-01760-6.

Indexed as

Cancer biomarkersColorectal cancerComputational oncologyMolecular signatureMulti-omics

Identifiers

PMID37359923
PMCPMC10284779
OpenAlexW4376875852

What OpenQuestion holds

Textmetadata
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.