Evidence map›Paper›PMID 34121340›Full record

ArticleCancer medicine2021

A five-gene signature is a prognostic biomarker in pan-cancer and related with immunologically associated extracellular matrix.

Chunlai Yu, Mingliang You, Peizhen Zhang, Sheng Zhang, Yuzhu Yin, Xiao Zhang

Open access · goldAbstract read
In one paragraph

Article in Cancer medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
1.8field-weighted citation impact, top 14% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.

  1. Pooled it
  2. Review
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  5. Article
  6. Prognostic Value and Immunological Role of P4HA3 in Colon Adenocarcinoma.International journal of general medicine · 2023
    Article
  7. Article
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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

6 authors at 4 institutions in 1 country.

Chunlai YuBioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, China.
Mingliang YouKey Laboratory of Clinical Cancer Pharmacology and Toxicology Research of Zhejiang Province, Hangzhou Cancer Institute, Affiliated Hangzhou Cancer Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Peizhen ZhangDepartment of Obstetrics and Gynecology, Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China.
Sheng ZhangBioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, China.
Yuzhu YinDepartment of Obstetrics and Gynecology, Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China.
Xiao ZhangBioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, China.ORCID 0000-0002-3894-8513
Guangzhou Regenerative Medicine and Health Guangdong Laboratory · CNSun Yat-sen University · CNGuangzhou Institutes of Biomedicine and Health · CNZhejiang Cancer Hospital · CN

Funding

the Key Research & Development Program of Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory) 2019GZR1104060the Scientific Instrumentation Development Program of Chinese Academy of Sciences ZDZBGCH2018005
6 · The paper itself

Abstract

The tumor microenvironment (TME) is related to extracellular matrix (ECM) dynamics and has a broad fundamental and mechanistic role in tumorigenesis and cancer progression. We hypothesized that ECM regulators might play an essential role in pan-cancer attribution by causing a generic effect through its regulation of the dynamics of ECM alteration. By analyzing data from TCGA using GSEA and univariate Cox regression analysis, we found that ECM regulator genes were significantly enriched and contributed to mortality in various cancer types. Notably, UMAP analysis revealed that ECM regulator genes dominated the differences between tumor and adjacent normal tissues based on 59 or 31 pan-survival-related ECM gene sets. Subsequently, a five-gene signature consisting of the predominant ECM regulators ADAM12, MMP1, SERPINE1, PLOD3, and P4HA3 was identified. We found that this five-gene signature was pro-mortality in 18 types of cancer in TCGA, and validated eleven other cancer types in TCGA and seven types in the TARGET and CoMMpass databases using overall survival analysis. KEGG pathway enrichment and Pearson correlation analysis indicated that these five component genes that were correlated with specific ECM proteins involved in tumorigenesis from the ECM receptor interaction gene set. Additionally, the fitted results of a linear model were applied to strengthen the discovery, demonstrating that the five genes were correlated with immune infiltration score and especially associated with typically immunologically "cold" tumors. We thus conclude that the ADAM12, MMP1, SERPINE1, PLOD3, and P4HA3 signature showed a close association with a pan-cancer effect on prognosis and is related to ECM proteins in the TME which corresponding with immunologically "cold" cancer types.

Indexed as

Gene Expression ProfilingGenes, RegulatorTranscriptomeADAM12 ProteinExtracellular MatrixGenetic MarkersHumansKaplan-Meier EstimateMatrix Metalloproteinase 1NeoplasmsPlasminogen Activator Inhibitor 1Procollagen-Lysine, 2-Oxoglutarate 5-DioxygenaseProcollagen-Proline DioxygenasePrognosisProportional Hazards ModelsTumor MicroenvironmentADAM12 ProteinADAM12 protein, humanGenetic MarkersMatrix Metalloproteinase 1MMP1 protein, humanP4HA3 protein, humanPlasminogen Activator Inhibitor 1PLOD3 protein, humanProcollagen-Lysine, 2-Oxoglutarate 5-DioxygenaseProcollagen-Proline DioxygenaseSERPINE1 protein, humanECM depositionECM regulatorimmune cell infiltrationimmunologically coldpan-cancer signature

Identifiers

PMID34121340
PMCPMC8267129
OpenAlexW3170757319

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.