Evidence map›Paper›PMID 34659201›Full record

ArticleFrontiers in immunology2021

Development and Validation of a Combined Glycolysis and Immune Prognostic Model for Melanoma.

Yang Yang, Yaling Li, Ruiqun Qi, Lan Zhang

Open access · goldAbstract readValidation Study
In one paragraph

Article in Frontiers in immunology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.9field-weighted citation impact, top 13% 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

14 citing papers in PubMed, 14 citations in OpenAlex.

  1. Trial
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  3. The path of GPR87: from a P2Y-like receptor to its role in cancer progression.Naunyn-Schmiedeberg's archives of pharmacology · 2025
    Review
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  6. Low expression ofTranslational cancer research · 2024
    Article
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  8. Review
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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

4 authors at 2 institutions in 1 country.

Yang YangDepartment of Dermatology, The First Hospital of China Medical University and National Joint Engineering Research Center for Theranostics of Immunological Skin Diseases, The First Hospital of China Medical University and Key Laboratory of Immunodermatology, Ministry of Health and Ministry of Education, Shenyang, China.
Yaling LiDepartment of Dermatology, The First Hospital of China Medical University and National Joint Engineering Research Center for Theranostics of Immunological Skin Diseases, The First Hospital of China Medical University and Key Laboratory of Immunodermatology, Ministry of Health and Ministry of Education, Shenyang, China.
Ruiqun QiDepartment of Dermatology, The First Hospital of China Medical University and National Joint Engineering Research Center for Theranostics of Immunological Skin Diseases, The First Hospital of China Medical University and Key Laboratory of Immunodermatology, Ministry of Health and Ministry of Education, Shenyang, China.
Lan ZhangDepartment of Dermatology, The First Hospital of China Medical University and National Joint Engineering Research Center for Theranostics of Immunological Skin Diseases, The First Hospital of China Medical University and Key Laboratory of Immunodermatology, Ministry of Health and Ministry of Education, Shenyang, China.
China Medical University · CNFirst Hospital of China Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Glycolytic effects and immune microenvironments play important roles in the development of melanoma. However, reliable biomarkers for prognostic prediction of melanoma as based on glycolysis and immune status remain to be identified. Methods: Glycolysis-related genes (GRGs) were obtained from the Molecular Signatures database and immune-related genes (IRGs) were downloaded from the ImmPort dataset. Prognostic GRGs and IRGs in the TCGA (The Cancer Genome Atlas) and GSE65904 datasets were identified. Least absolute shrinkage and selection operator (LASSO) Cox regression and multivariate Cox regression were used for model construction. Glycolysis expression profiles and the infiltration of immune cells were analyzed and compared. Finally, Results: Four prognostic glycolysis- and immune-related signatures ( Conclusion: In this report we present our findings on the development and validation of a novel prognostic classifier for use in patients with melanoma as based on glycolysis and immune expression profiles.

Indexed as

GlycolysisCells, CulturedHumansKinesinsMelanomaNomogramsPrognosisProportional Hazards ModelsReceptors, Lysophosphatidic AcidTumor MicroenvironmentGPR87 protein, humanKIF20A protein, humanKinesinsReceptors, Lysophosphatidic Acidbioinformaticsglycolysisimmunemelanomaprognostic

Identifiers

PMID34659201
PMCPMC8517401
OpenAlexW3202633180

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.