Evidence map›Paper›PMID 35508972›Full record

ArticleMolecular medicine (Cambridge, Mass.)2022

Pan-cancer analysis reveals RIPK2 predicts prognosis and promotes immune therapy resistance via triggering cytotoxic T lymphocytes dysfunction.

Junquan Song, Runyu Yang, Rongyuan Wei, Yue Du, Pengcheng He, Xiaowen Liu

Open access · goldAbstract read
In one paragraph

Article in Molecular medicine (Cambridge, Mass.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 1 pooled it
3.9field-weighted citation impact, top 5% 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

28 citing papers in PubMed, 1 synthesis or guideline pooled it, 37 citations in OpenAlex.

  1. Pooled it
  2. Ripk2 promotes CD8Cell death & disease · 2026
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  12. TSPAN4Frontiers in immunology · 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

6 authors at 3 institutions in 1 country.

Junquan Song *Department of Gastric Surgery, Fudan University Shanghai Cancer Center, 200030, Shanghai, China.
Runyu Yang *Department of Hematology, The First Affiliated Hospital of Xi'an Jiaotong University, 710000, Xi'an, China.
Rongyuan WeiDepartment of Gastric Surgery, Fudan University Shanghai Cancer Center, 200030, Shanghai, China.
Yue DuDepartment of Hematology, The First Affiliated Hospital of Xi'an Jiaotong University, 710000, Xi'an, China.
Pengcheng HeDepartment of Hematology, The First Affiliated Hospital of Xi'an Jiaotong University, 710000, Xi'an, China. hepc@163.com.
Xiaowen LiuDepartment of Gastric Surgery, Fudan University Shanghai Cancer Center, 200030, Shanghai, China. liuxw1129@hotmail.com.
First Affiliated Hospital of Xi'an Jiaotong University · CNShanghai Medical College of Fudan University · CNFudan University Shanghai Cancer Center · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundReceptor-interacting protein kinase 2 (RIPK2, also known as RIP2) was reported to be associated with bacterial infections as well as inflammatory responses. However, the role of RIPK2 in prognosis and immunotherapy response is yet to be elucidated in human pan-cancer.

methodsIn this study, we investigated the expression, gene alteration landscape and prognostic value of RIPK2 in 33 cancers through various databases including Ualcan, cBioportal and Gene Expression Profiling Interactive Analysis 2 (GEPIA2). Then, the correlation between RIPK2 and immune infiltration, immune score, stromal score, and ESTIMATE score was investigated in the Cancer Genome Atlas (TCGA) and tumor immune estimation resource (TIMER) databases. Independent cohorts were utilized to explore the role of RIPK2 in tumor immunotherapy response. Furthermore, Gene set enrichment analysis (GSEA) was conducted to explore the mechanisms by which RIPK2 regulates immune therapy resistance. Single-cell RNA-seq datasets were used to analyze the expression level of RIPK2 on different immune cells. Moreover, CellMiner database was used to explore the relationship between RIPK2 expression with drug response.

resultCompared with normal tissue, tumor tissue had a higher expression level of RIPK2 in various cancers. Survival analysis showed that high expression of RIPK2 associated with poor prognosis in numerous cancers. RIPK2 was found to promote a series of immune cell infiltration and B cells, macrophages, and neutrophils were significantly positively correlated with the expression of RIPK2. Moreover, RIPK2 affected immune score, stromal score and ESTIMATE score for a wide range of cancers. In the vast majority of 33 cancers, gene co-expression analysis showed that RIPK2 was positively correlated with the expression of immune checkpoint markers, such as PDCD1 (PD-1), CD274 (PD-L1), CTLA4 and TIGIT. RIPK2 aggravated cytotoxic T lymphocyte (CTL) dysfunction and related to the poor efficacy of immune checkpoint blockade in skin cutaneous melanoma (SKCM) and kidney renal clear cell carcinoma (KIRC). High expression of RIPK2 promoted innate immunotherapy resistance and adaptive immunotherapy resistance through IL-6/JAK/STAT3 signaling, interferon-gamma response, and interferon-alpha response pathway.

conclusionsThese results confirmed that RIPK2 could serve as a prognostic biomarker and promoted immune therapy resistance via triggering cytotoxic T lymphocytes dysfunction.

Indexed as

Carcinoma, Renal CellKidney NeoplasmsMelanomaSkin NeoplasmsBiomarkers, TumorCutaneous Malignant MelanomaFemaleHumansMaleReceptor-Interacting Protein Serine-Threonine Kinase 2T-Lymphocytes, CytotoxicBiomarkers, TumorReceptor-Interacting Protein Serine-Threonine Kinase 2RIPK2 protein, humanBiomarkerImmunotherapyInflammationReceptor-interacting protein kinase 2RIPK2Tumor immunity

Identifiers

PMID35508972
PMCPMC9066895
OpenAlexW4225410812

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LicenceCC BY
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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.