Evidence map›Paper›PMID 34572330›Full record

ArticleBiomedicines2021

Identifying GPSM Family Members as Potential Biomarkers in Breast Cancer: A Comprehensive Bioinformatics Analysis.

Huy-Hoang Dang, Hoang Dang Khoa Ta, Truc T T Nguyen, Gangga Anuraga, Chih-Yang Wang, Kuen-Haur Lee, Nguyen Quoc Khanh Le

Open access · goldAbstract read
In one paragraph

Article in Biomedicines, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed, 1 pooled it
4.6field-weighted citation impact, top 4% 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

43 citing papers in PubMed, 1 synthesis or guideline pooled it, 60 citations in OpenAlex.

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  17. [GPSM2 is highly expressed in gastric cancer to affect patient prognosis by promoting tumor cell proliferation].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2025
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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

7 authors at 4 institutions in 1 country.

Huy-Hoang DangInternational Ph.D. Program for Cell Therapy and Regeneration Medicine, College of Medicine, Taipei Medical University, Taipei 11031, Taiwan.
Hoang Dang Khoa TaPh.D. Program for Cancer Molecular Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University and Academia Sinica, Taipei 11031, Taiwan.
Truc T T NguyenTranslational Medicine Division, Graduate Institute of Biomedical Informatics, Taipei Medical University, Taipei 110, Taiwan.ORCID 0000-0002-7206-2521
Gangga AnuragaPh.D. Program for Cancer Molecular Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University and Academia Sinica, Taipei 11031, Taiwan.ORCID 0000-0002-0902-3968
Chih-Yang WangPh.D. Program for Cancer Molecular Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University and Academia Sinica, Taipei 11031, Taiwan.
Kuen-Haur LeePh.D. Program for Cancer Molecular Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University and Academia Sinica, Taipei 11031, Taiwan.ORCID 0000-0002-6354-3315
Nguyen Quoc Khanh LeInternational Ph.D. Program for Cell Therapy and Regeneration Medicine, College of Medicine, Taipei Medical University, Taipei 11031, Taiwan.ORCID 0000-0003-4896-7926
Taipei Medical University · TWTaipei Medical University Hospital · TWUniversitas PGRI Adi Buana SurabayaWan Fang Hospital · TW

Funding

Ministry of Education DP2-110-21121-01-A-06
6 · The paper itself

Abstract

G-protein signaling modulators (GPSMs) are a class of proteins involved in the regulation of G protein-coupled receptors, the most abundant family of cell-surface receptors that are crucial in the development of various tumors, including breast cancer. This study aims to identify the potential therapeutic and prognostic roles of GPSMs in breast cancer. Oncomine and UALCAN databases were queried to determine GPSM expression levels in breast cancer tissues compared to normal samples. Survival analysis was conducted to reveal the prognostic significance of GPSMs in individuals with breast cancer. Functional enrichment analysis was performed using cBioPortal and MetaCore platforms. Finally, the association between GPSMs and immune infiltration cells in breast cancer was identified using the TIMER server. The experimental results then showed that all GPSM family members were significantly differentially expressed in breast cancer according to Oncomine and UALCAN data. Their expression levels were also associated with advanced tumor stages, and GPSM2 was found to be related to worse distant metastasis-free survival in patients with breast cancer. Functional enrichment analysis indicated that GPSMs were largely involved in cell division and cell cycle pathways. Finally, GPSM3 expression was correlated with the infiltration of several immune cells. Members of the GPSM class were differentially expressed in breast cancer. In conclusion, expression of GPSM2 was linked with worse distant metastasis-free outcomes, and hence could potentially serve as a prognostic biomarker. Furthermore, GPSM3 has potential to be a possible target for immunotherapy for breast cancer.

Indexed as

biomarkerbreast cancerfunctional enrichment analysisgene expressionG-protein signaling modulatorimmunotherapysurvival analysis

Identifiers

PMID34572330
PMCPMC8471503
OpenAlexW3197590856

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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.