Evidence map›Paper›PMID 35898192›Full record

ArticleMatrix biology plus2022

Characterizing the extracellular matrix transcriptome of cervical, endometrial, and uterine cancers.

Carson J Cook, Andrew E Miller, Thomas H Barker, Yanming Di, Kaitlin C Fogg

Open access · goldAbstract read
In one paragraph

Article in Matrix biology plus, 2022. 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
1.7field-weighted citation impact, top 16% 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, 12 citations in OpenAlex.

  1. Article
  2. Article
  3. Characterizing the Extracellular Matrix Transcriptome of Endometriosis.Reproductive sciences (Thousand Oaks, Calif.) · 2024
    Article
  4. Article
  5. Article
  6. 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

5 authors at 3 institutions in 1 country.

Carson J CookDepartment of Bioengineering, Oregon State University, Corvallis, OR 97331, USA.
Andrew E MillerDepartment of Biomedical Engineering, University of Virginia, Charlottesville, VA 22904, USA.
Thomas H BarkerDepartment of Biomedical Engineering, University of Virginia, Charlottesville, VA 22904, USA.
Yanming DiDepartment of Statistics, Oregon State University, Corvallis, OR 97331, USA.
Kaitlin C FoggDepartment of Bioengineering, Oregon State University, Corvallis, OR 97331, USA.
Oregon State University · USUniversity of Virginia · USOregon Health & Science University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Increasingly, the matrisome, a set of proteins that form the core of the extracellular matrix (ECM) or are closely associated with it, has been demonstrated to play a key role in tumor progression. However, in the context of gynecological cancers, the matrisome has not been well characterized. A holistic, yet targeted, exploration of the tumor microenvironment is critical for better understanding the progression of gynecological cancers, identifying key biomarkers for cancer progression, establishing the role of gene expression in patient survival, and for assisting in the development of new targeted therapies. In this work, we explored the matrisome gene expression profiles of cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), uterine corpus endometrial carcinoma (UCEC), and uterine carcinosarcoma (UCS) using publicly available RNA-seq data from The Cancer Genome Atlas (TCGA) and The Genotype-Tissue Expression (GTEx) portal. We hypothesized that the matrisomal expression patterns of CESC, UCEC, and UCS would be highly distinct with respect to genes which are differentially expressed and hold inferential significance with respect to tumor progression, patient survival, or both. Through a combination of statistical and machine learning analysis techniques, we identified sets of genes and gene networks which characterized each of the gynecological cancer cohorts. Our findings demonstrate that the matrisome is critical for characterizing gynecological cancers and transcriptomic mechanisms of cancer progression and outcome. Furthermore, while the goal of pan-cancer transcriptional analyses is often to highlight the shared attributes of these cancer types, we demonstrate that they are highly distinct diseases which require separate analysis, modeling, and treatment approaches. In future studies, matrisome genes and gene ontology terms that were identified as holding inferential significance for cancer stage and patient survival can be evaluated as potential drug targets and incorporated into

Indexed as

Extracellular matrixGynecological cancerMatrisomeRNA-seqTCGA

Identifiers

PMID35898192
PMCPMC9309672
OpenAlexW4285601682

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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.