Evidence map›Paper›PMID 33145269›Full record

ArticleAnnals of translational medicine2020

Identification of molecular features correlating with tumor immunity in gastric cancer by multi-omics data analysis.

Yin He, Xiaosheng Wang

Open access · diamondAbstract read
In one paragraph

Article in Annals of translational medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed
4.3field-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

37 citing papers in PubMed, 48 citations in OpenAlex.

  1. Review
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  7. CD8 + T Cells in Gastrointestinal Cancer: a Perspective on Targeting MicroRNA.Journal of molecular medicine (Berlin, Germany) · 2025
    Review
  8. Article
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  12. Immunotherapy and Cancer: The Multi-Omics Perspective.International journal of molecular sciences · 2024
    Review
  13. Article
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  19. Article
  20. LncRNA and its role in gastric cancer immunotherapy.Frontiers in cell and developmental biology · 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

2 authors at 1 institution in 1 country.

Yin HeBiomedical Informatics Research Lab, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China.
Xiaosheng WangBiomedical Informatics Research Lab, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China.
China Pharmaceutical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlthough immunotherapy has achieved success in treating various refractory malignancies including gastric cancers (GCs) with DNA mismatch repair deficiency, only a subset of cancer patients are responsive to immunotherapy. Therefore, the identification of useful biomarkers or interventional targets for improving cancer immunotherapy response is urgently needed.

methodsWe investigated the associations between various molecular features and immune signatures using three multi-omics GC datasets. These molecular features included genes, microRNAs (miRNAs), long non-coding RNAs (lncRNAs), proteins, and pathways, and the immune signatures included CD8+ T cell infiltration, immune cytolytic activity (ICA), and

resultsThe mutations of some important oncogenes and tumor suppressor genes were appreciably associated with immune signatures in GC, including

conclusionsThe molecular features significantly associated with GC immunity could be useful biomarkers for stratifying GC patients responsive to immunotherapy or intervention targets for promoting antitumor immunity and immunotherapy response in GC.

Indexed as

biomarkerGastric cancer (GC)multi-omics data analysistumor immunitytumor immunotherapy

Identifiers

PMID33145269
PMCPMC7575957
OpenAlexW3084619987

What OpenQuestion holds

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Registered trials

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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.