Evidence map›Paper›PMID 35008299›Full record

ArticleCancers2021

A Gene Signature Derived from the Loss of CDKN1A (p21) Is Associated with CMS4 Colorectal Cancer.

Santiago Bueno-Fortes, Julienne K Muenzner, Alberto Berral-Gonzalez, Chuanpit Hampel, Pablo Lindner, Alexandra Berninger, Kerstin Huebner, Philipp Kunze, Tobias Bäuerle, Katharina Erlenbach-Wuensch and 4 more

Open access · goldAbstract read
In one paragraph

Article in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.6field-weighted citation impact, top 32% 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

6 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. CDKN1A/p21 in Breast Cancer: Part of the Problem, or Part of the Solution?International journal of molecular sciences · 2023
    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

14 authors at 3 institutions in 2 countries.

Santiago Bueno-FortesBioinformatics and Functional Genomics Group, Cancer Research Center (CiC-IMBCC, CSIC/USAL/IBSAL), Consejo Superior de Investigaciones Científicas (CSIC) and University of Salamanca (USAL), 37007 Salamanca, Spain.
Julienne K MuenznerExperimental Tumor Pathology, University Hospital of the Friedrich-Alexander University Erlangen-Nürnberg, 91054 Erlangen, Germany.
Alberto Berral-GonzalezBioinformatics and Functional Genomics Group, Cancer Research Center (CiC-IMBCC, CSIC/USAL/IBSAL), Consejo Superior de Investigaciones Científicas (CSIC) and University of Salamanca (USAL), 37007 Salamanca, Spain.ORCID 0000-0001-8388-6051
Chuanpit HampelExperimental Tumor Pathology, University Hospital of the Friedrich-Alexander University Erlangen-Nürnberg, 91054 Erlangen, Germany.
Pablo LindnerExperimental Tumor Pathology, University Hospital of the Friedrich-Alexander University Erlangen-Nürnberg, 91054 Erlangen, Germany.
Alexandra BerningerExperimental Tumor Pathology, University Hospital of the Friedrich-Alexander University Erlangen-Nürnberg, 91054 Erlangen, Germany.
Kerstin HuebnerExperimental Tumor Pathology, University Hospital of the Friedrich-Alexander University Erlangen-Nürnberg, 91054 Erlangen, Germany.
Philipp KunzeExperimental Tumor Pathology, University Hospital of the Friedrich-Alexander University Erlangen-Nürnberg, 91054 Erlangen, Germany.
Tobias BäuerlePreclinical Imaging Platform Erlangen (PIPE), Institute of Radiology, University Hospital Erlangen-Nuremberg, 91054 Erlangen, Germany.
Katharina Erlenbach-WuenschInstitute of Pathology, University Hospital of the Friedrich-Alexander University Erlangen-Nürnberg, 91054 Erlangen, Germany.
José Manuel Sánchez-SantosBioinformatics and Functional Genomics Group, Cancer Research Center (CiC-IMBCC, CSIC/USAL/IBSAL), Consejo Superior de Investigaciones Científicas (CSIC) and University of Salamanca (USAL), 37007 Salamanca, Spain.ORCID 0000-0002-7434-7598
Arndt HartmannInstitute of Pathology, University Hospital of the Friedrich-Alexander University Erlangen-Nürnberg, 91054 Erlangen, Germany.
Javier De Las RivasBioinformatics and Functional Genomics Group, Cancer Research Center (CiC-IMBCC, CSIC/USAL/IBSAL), Consejo Superior de Investigaciones Científicas (CSIC) and University of Salamanca (USAL), 37007 Salamanca, Spain.ORCID 0000-0002-0984-9946
Regine Schneider-StockExperimental Tumor Pathology, University Hospital of the Friedrich-Alexander University Erlangen-Nürnberg, 91054 Erlangen, Germany.
Friedrich-Alexander-Universität Erlangen-Nürnberg · DEConsejo Superior de Investigaciones Científicas · ESUniversitätsklinikum Erlangen · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The epithelial-mesenchymal transition (EMT) is associated with tumor aggressiveness and increased invasion, migration, metastasis, angiogenesis, and drug resistance. Although the HCT116 p21-/- cell line is well known for its EMT-associated phenotype, with high Vimentin and low E-cadherin protein levels, the gene signature of this rather intermediate EMT-like cell line has not been determined so far. In this work, we present a robust molecular and bioinformatics analysis, to reveal the associated gene expression profile and its correlation with different types of colorectal cancer tumors. We compared the quantitative signature obtained with the NanoString platform with the expression profiles of colorectal cancer (CRC) Consensus Molecular Subtypes (CMS) as identified, and validated the results in a large independent cohort of human tumor samples. The expression signature derived from the p21-/- cells showed consistent and reliable numbers of upregulated and downregulated genes, as evaluated with two machine learning methods against the four CRC subtypes (i.e., CMS1, 2, 3, and 4). High concordance was found between the upregulated gene signature of HCT116 p21-/- cells and the signature of the CMS4 mesenchymal subtype. At the same time, the upregulated gene signature of the native HCT116 cells was similar to that of CMS1. Using a multivariate Cox regression model to analyze the survival data in the CRC tumor cohort, we selected genes that have a predictive risk power (with a significant

Indexed as

CAM modelCDKN1Acolorectal cancerconsensus molecular subtypes (CMS)epithelial–mesenchymal transition (EMT)HCT116 cellsintermediate EMTSNAI2

Identifiers

PMID35008299
PMCPMC8750372
OpenAlexW4200388780

What Socratic 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 Socratic graph.