Evidence map›Paper›PMID 35572498›Full record

ArticleFrontiers in immunology2022

Tumor Microenvironment Characterization for Assessment of Recurrence and Survival Outcome in Gastric Cancer to Predict Chemotherapy and Immunotherapy Response.

Yan Chen, Zepang Sun, Li Wan, Hongzhuan Chen, Tieju Xi, Yuming Jiang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 2 pooled it
3.0field-weighted citation impact, top 8% 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, 2 syntheses or guidelines pooled it, 20 citations in OpenAlex.

  1. Pooled it
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  3. Predictors of immunotherapy response in gastric cancer: the role of the tumor microenvironment and integrative predictive models.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
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  9. Research advances in the molecular classification of gastric cancer.Cellular oncology (Dordrecht, Netherlands) · 2024
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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 2 countries.

Yan ChenShatou Community Health Service Center, Shenzhen Hospital of Integrated Traditional Chinese and Western Medicine, The Second People's Hospital of Bao'an Shenzhen (Group), Shenzhen Bao'an Shajing People's Hospital, Guangzhou Medical University, Shenzhen, China.
Zepang SunDepartment of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China.
Li WanShatou Community Health Service Center, Shenzhen Hospital of Integrated Traditional Chinese and Western Medicine, The Second People's Hospital of Bao'an Shenzhen (Group), Shenzhen Bao'an Shajing People's Hospital, Guangzhou Medical University, Shenzhen, China.
Hongzhuan ChenShatou Community Health Service Center, Shenzhen Hospital of Integrated Traditional Chinese and Western Medicine, The Second People's Hospital of Bao'an Shenzhen (Group), Shenzhen Bao'an Shajing People's Hospital, Guangzhou Medical University, Shenzhen, China.
Tieju XiShatou Community Health Service Center, Shenzhen Hospital of Integrated Traditional Chinese and Western Medicine, The Second People's Hospital of Bao'an Shenzhen (Group), Shenzhen Bao'an Shajing People's Hospital, Guangzhou Medical University, Shenzhen, China.
Yuming JiangDepartment of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China.
Shenzhen Bao'an District People's Hospital · CNNanfang Hospital · CNGuangzhou Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The tumor microenvironment (TME) is crucial for tumor recurrence, prognosis, and therapeutic responses. We comprehensively investigated the TME characterization associated with relapse and survival outcomes of gastric cancer (GC) to predict chemotherapy and immunotherapy response. Methods: A total of 2,456 GC patients with complete gene-expression data and clinical annotations from twelve cohorts were included. The TME characteristics were evaluated using three proposed computational algorithms. We then developed a TME-classifier, a TME-cluster, and a TME-based risk score for the assessment of tumor recurrence and prognosis in patients with GC to predict chemotherapy and immunotherapy response. Results: Patients with tumor recurrence presented with inactive immunogenicity, namely, high infiltration of tumor-associated stromal cells, low infiltration of tumor-associated immunoactivated lymphocytes, high stromal score, and low immune score. The TME-classifier of 4 subtypes with distinct clinicopathology, genomic, and molecular characteristics was significantly associated with tumor recurrence (P = 0.002), disease-free survival (DFS, P <0.001), and overall survival (OS, P <0.001) adjusted by confounding variables in 1,193 stage I-III GC patients who underwent potential radical surgery. The TME cluster and TME-based risk score can also predict DFS (P <0.001) and OS (P <0.001). More importantly, we found that patients in the TMEclassifier-A, TMEclassifier-C, and TMEclassifier-D groups benefited from adjuvant chemotherapy, and patients in the TMEclassifier-B group without chemotherapy benefit responded best to pembrolizumab treatment (PD-1 inhibitor), followed by patients in the TMEclassifier-A, while patients in the C and D groups of the TMEclassifier responded poorly to immunotherapy. Conclusion: We determined that TME characterization is significantly associated with tumor recurrence and prognosis. The TME-classifier we proposed can guide individualized chemotherapy and immunotherapy decision-making.

Indexed as

Stomach NeoplasmsTumor MicroenvironmentHumansImmunotherapyNeoplasm Recurrence, LocalPrognosischemotherapyclassifier (classification tool)gastric cancerimmunotherapyprognosisrecurrencetumor microenvironment

Identifiers

PMID35572498
PMCPMC9101297
OpenAlexW4225160330

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.