Evidence map›Paper›PMID 36358609›Full record

ArticleCancers2022

Molecular Classification of Colorectal Cancer by microRNA Profiling: Correlation with the Consensus Molecular Subtypes (CMS) and Validation of miR-30b Targets.

Mateo Paz-Cabezas, Tania Calvo-López, Alejandro Romera-Lopez, Daniel Tabas-Madrid, Jesus Ogando, María-Jesús Fernández-Aceñero, Javier Sastre, Alberto Pascual-Montano, Santos Mañes, Eduardo Díaz-Rubio and 1 more

Open access · goldAbstract read
In one paragraph

Article in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.9field-weighted citation impact, top 30% 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

8 citing papers in PubMed, 10 citations in OpenAlex.

  1. A laminin α4-CD8Oncoimmunology · 2025
    Article
  2. Review
  3. Article
  4. Review
  5. Article
  6. Review
  7. Review
  8. Review
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

11 authors at 2 institutions in 1 country.

Mateo Paz-CabezasGenomics and Microarrays Laboratory, Medical Oncology Department, Instituto de Investigación Sanitaria San Carlos (IdiSSC), Hospital Clinico San Carlos, 28040 Madrid, Spain.
Tania Calvo-LópezGenomics and Microarrays Laboratory, Medical Oncology Department, Instituto de Investigación Sanitaria San Carlos (IdiSSC), Hospital Clinico San Carlos, 28040 Madrid, Spain.
Alejandro Romera-LopezGenomics and Microarrays Laboratory, Medical Oncology Department, Instituto de Investigación Sanitaria San Carlos (IdiSSC), Hospital Clinico San Carlos, 28040 Madrid, Spain.
Daniel Tabas-MadridImmunology and Oncology Department, Centro Nacional de Biotecnología (CSIC), 28049 Madrid, Spain.
Jesus OgandoImmunology and Oncology Department, Centro Nacional de Biotecnología (CSIC), 28049 Madrid, Spain.
María-Jesús Fernández-AceñeroSurgical Pathology, Instituto de Investigación Sanitaria San Carlos (IdiSSC), Hospital Clinico San Carlos, 28040 Madrid, Spain.ORCID 0000-0002-2439-3553
Javier SastreGenomics and Microarrays Laboratory, Medical Oncology Department, Instituto de Investigación Sanitaria San Carlos (IdiSSC), Hospital Clinico San Carlos, 28040 Madrid, Spain.
Alberto Pascual-MontanoImmunology and Oncology Department, Centro Nacional de Biotecnología (CSIC), 28049 Madrid, Spain.
Santos MañesImmunology and Oncology Department, Centro Nacional de Biotecnología (CSIC), 28049 Madrid, Spain.ORCID 0000-0001-8023-957X
Eduardo Díaz-RubioGenomics and Microarrays Laboratory, Medical Oncology Department, Instituto de Investigación Sanitaria San Carlos (IdiSSC), Hospital Clinico San Carlos, 28040 Madrid, Spain.ORCID 0000-0003-2792-5348
Beatriz Perez-VillamilGenomics and Microarrays Laboratory, Medical Oncology Department, Instituto de Investigación Sanitaria San Carlos (IdiSSC), Hospital Clinico San Carlos, 28040 Madrid, Spain.ORCID 0000-0002-6881-7442
Instituto de Investigación Sanitaria del Hospital Clínico San Carlos · ESCentro Nacional de Biotecnología · ES

Funding

Bayer Healthcare BPV.M01BAYComunidad de Madrid S2017/BMD-3733Fundacion 2000 Merck-Serono F01MSER13Fundación Mutua Madrileña AP151962014Fundacion Rodriguez-Pascual EDRFERP.2013MCIN PID2020-116303RB-I00/MCIN/AEI/10.13039/501100011033
6 · The paper itself

Abstract

Colorectal cancer consensus molecular subtypes (CMSs) are widely accepted and constitutes the basis for patient stratification to improve clinical practice. We aimed to find whether miRNAs could reproduce molecular subtypes, and to identify miRNA targets associated to the High-stroma/CMS4 subtype. The expression of 939 miRNAs was analyzed in tumors classified in CMS. TALASSO was used to find gene-miRNA interactions. A miR-mRNA regulatory network was constructed using Cytoscape. Candidate gene-miR interactions were validated in 293T cells. Hierarchical-Clustering identified three miRNA tumor subtypes (miR-LS; miR-MI; and miR-HS) which were significantly associated (p < 0.001) to the reported mRNA subtypes. miR-LS correlated with the low-stroma/CMS2; miR-MI with the mucinous-MSI/CMS1 and miR-HS with high-stroma/CMS4. MicroRNA tumor subtypes and association to CMSs were validated with TCGA datasets. TALASSO identified 1462 interactions (p < 0.05) out of 21,615 found between 176 miRs and 788 genes. Based on the regulatory network, 88 miR-mRNA interactions were selected as candidates. This network was functionally validated for the pair miR-30b/SLC6A6. We found that miR-30b overexpression silenced 3′-UTR-SLC6A6-driven luciferase expression in 293T-cells; mutation of the target sequence in the 3′-UTR-SLC6A6 prevented the miR-30b inhibitory effect. In conclusion CRC subtype classification using a miR-signature might facilitate a real-time analysis of the disease course and treatment response.

Indexed as

colorectal cancermicroarray gene-expression profilingmicroRNAsmolecular classificationprognostic factors

Identifiers

PMID36358609
PMCPMC9656292
OpenAlexW4307371186

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.