Cited by 999Cancer Immunotherapy and BiomarkersGastric Cancer Management and OutcomesImmune cells in cancer

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Tumor Microenvironment Characterization in Gastric Cancer Identifies Prognostic and Immunotherapeutically Relevant Gene Signatures

Zeng, Dongqiang, Li, Meiyi, Zhou, Rui, Zhang, Jingwen, Sun, Huiying, Shi, Min, Bin, Jianping, Liao, Yulin, Rao, Jinjun, Liao, Wangjun·2019·Cancer Immunology Research

DOI 10.1158/2326-6066.cir-18-0436

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Abstract

Tumor microenvironment (TME) cells constitute a vital element of tumor tissue. Increasing evidence has elucidated their clinicopathologic significance in predicting outcomes and therapeutic efficacy. Nonetheless, no studies have reported a systematic analysis of cellular interactions in the TME. In this study, we comprehensively estimated the TME infiltration patterns of 1,524 gastric cancer patients and systematically correlated the TME phenotypes with genomic characteristics and clinicopathologic features of gastric cancer using two proposed computational algorithms. Three TME phenotypes were defined, and the TMEscore was constructed using principal component analysis algorithms. The high TMEscore subtype was characterized by immune activation and response to virus and IFNγ. Activation of transforming growth factor β, epithelial–mesenchymal transition, and angiogenesis pathways were observed in the low TMEscore subtype, which are considered T-cell suppressive and may be responsible for significantly worse prognosis in gastric cancer [hazard ratio (HR), 0.42; 95% confidence interval (CI), 0.33–0.54; P < 0.001]. Multivariate analysis revealed that the TMEscore was an independent prognostic biomarker, and its value in predicting immunotherapeutic outcomes was also confirmed (IMvigor210 cohort: HR, 0.63; 95% CI, 0.46–0.89; P = 0.008; GSE78220 cohort: HR, 0.25; 95% CI, 0.07–0.89; P = 0.021). Depicting a comprehensive landscape of the TME characteristics of gastric cancer may, therefore, help to interpret the responses of gastric tumors to immunotherapies and provide new strategies for the treatment of cancers.

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Background
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Method
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Method
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“54 Therefore, we investigated the important biological pathways in TME, including epithelial-mesenchymal transition (EMT), angiogenesis, Wnt signaling pathway, and CD8 T effector, DNA damage repair, and nucleotide excision related pathways from previous research.”
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Background
Construction of ovarian metastasis‐related immune signature predicting prognosis of gastric cancer patients
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Result
MCEMP1 is a potential therapeutic biomarker associated with immune infiltration in advanced gastric cancer microenvironment
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Method
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Background
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MethodSelf-citation
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MethodInfluential
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Xiao, X. M., Cheng, W., Zhang, G., Wang, C., Sun, B., Zha, C., Kong, F., & Jia, Y. (2022) · Frontiers in Oncology · doi:10.3389/fonc.2022.862337 · Cited by 12
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Background
Mechanisms, advances, and challenges of immunotherapy in gastric cancer
Wang, Z., & Wang, T. (2025) · Frontiers in Immunology · doi:10.3389/fimmu.2025.1639487 · Cited by 11
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Method
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Method
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Chen, J., Wang, W. J., Zhang, Y., Wang, C., Wang, W., & Zheng, A. (2023) · Frontiers in Oncology · doi:10.3389/fonc.2023.1221445 · Cited by 11
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Background
Immunotherapy Based on Immune Checkpoint Molecules and Immune Checkpoint Inhibitors in Gastric Cancer–Narrative Review
Poniewierska-Baran, A., Sobolak, K., Niedźwiedzka‐Rystwej, P., Plewa, P., & Pawlik, A. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms25126471 · Cited by 11
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Background
The extracellular matrix protein EMILIN-1 impacts on the microenvironment by hampering gastric cancer development and progression
Capuano, A., Vescovo, M., Canesi, S., Pivetta, E., Doliana, R., Nadin, M. G., Yamamoto, M., Tsukamoto, T., Nomura, S., Pilozzi, E., et al. (2024) · Gastric Cancer · doi:10.1007/s10120-024-01528-z · Cited by 11
“Successful treatment of GC still represents a challenge in therapy and this is in part due to the poor understanding of the intricate players within the tumor micro-environment [29].”
Background
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Ramesh, P., Nisar, M., Neha, Ammankallu, S., Babu, S., Nandakumar, R., Abhinand, C. S., Prasad, T. S. K., Codi, J. A. K., & Raju, R. (2024) · Journal of Proteomics · doi:10.1016/j.jprot.2024.105262 · Cited by 11
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Gu, J.-X., Huang, K., Zhao, W.-L., Zheng, X.-M., Wu, Y., Yan, S., Huang, Y., & Hu, P. (2024) · International Journal of Molecular Medicine · doi:10.3892/ijmm.2024.5408 · Cited by 11
“The package ‘ggalluvial’ of R software (version 4.2.1) was used to build Sankey diagram (17).”
MethodInfluential
Multi-omics analysis of polyamine metabolism implicates NT5E/CD73 in the progression of pancreatic cancer
Zhang, E., Ding, X., Zhang, J., Liu, W., Liu, G., Li, M., Liu, X., Wang, Y., Zhang, F., Li, B., et al. (2025) · Cancer Letters · doi:10.1016/j.canlet.2025.217887 · Cited by 11
Self-citation
Association Between the Microsatellite Instability Status and the Efficacy of Postoperative Adjuvant Chemoradiotherapy in Patients With Gastric Cancer
Dai, D., Zhao, X., Li, X., Shu, Y., Shen, B., Chen, X., Chen, D., & Wang, D. (2020) · Frontiers in Oncology · doi:10.3389/fonc.2019.01452 · Cited by 11
“gov/) and the NCBI Gene Expression Omnibus (GEO; GSE62254 for ACRG) and processed as previously described (21).”
Method
Immune Escape in Prostate Cancer
Reva, B. A., Omelchenko, T., Nair, S. S., & Tewari, A. K. (2020) · Urologic Clinics of North America · doi:10.1016/j.ucl.2020.10.004 · Cited by 11
A quantitative score of immune cell infiltration predicts the prognosis in pancreatic ductal adenocarcinoma
Chen, Z., Wang, Y., Fong, W. P., Hu, M.-T., Liang, J., Wang, L., & Li, Y. (2021) · International Immunopharmacology · doi:10.1016/j.intimp.2021.107890 · Cited by 11
DNA Methylation Regulator-Meditated Modification Patterns Define the Distinct Tumor Microenvironment in Lung Adenocarcinoma
Yuan, D.-D., Wei, Z., Wang, Y., Cheng, F., Zeng, Y.-J., Yang, L., Zhang, S., Li, J.-B., & Tang, R. (2021) · Frontiers in Oncology · doi:10.3389/fonc.2021.734873 · Cited by 7
“We constructed the DMS using an algorithm similar to the GGI: DMS = S(PC1i + PC2 i), where i stood for the relevant gene expression of the selected set (22, 23).”
Method
Characteristics of the Immune Cell Infiltration Landscape in Gastric Cancer to Assistant Immunotherapy
Li, C., Pan, J., Jiang, Y., Yu, Y., Jin, Z., & Chen, X. (2022) · Frontiers in Genetics · doi:10.3389/fgene.2021.793628 · Cited by 11
“TME analysis revealed higher stromal and immune scores were found in ICI cluster C than other two clusters, indicating anti-tumor immune response was significantly activated in ICI cluster C of GC (Zeng et al., 2019).”
Background
Prediction of Two Molecular Subtypes of Gastric Cancer Based on Immune Signature
Wu, D., Feng, M., Shen, H., Shen, X., Hu, J., Liu, J., Yang, Y., Li, Y., Yang, M., Wang, W., et al. (2022) · Frontiers in Genetics · doi:10.3389/fgene.2021.793494 · Cited by 11
Analysis of m6A Methylation Modification Patterns and Tumor Immune Microenvironment in Breast Cancer
Dong, M., Shen, W., Yang, G., Zhifang, Y., & Li, X. (2022) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2022.785058 · Cited by 12
Comprehensive analysis of pyroptosis regulation patterns and their influence on tumor immune microenvironment and patient prognosis in glioma
Fan, T., Wan, Y., Niu, D., Wang, B., Zhang, B., Zhang, Z., Zhang, Y., Gong, Z., & Zhang, L. (2022) · Discover Oncology · doi:10.1007/s12672-022-00474-5 · Cited by 11
“PSscore was defined by using a method was analogous to GGI [30, 31]: where “i” was the expression of pyroptosis-related genes.”
Method
Immune Infiltration Characteristics and a Gene Prognostic Signature Associated With the Immune Infiltration in Head and Neck Squamous Cell Carcinoma
Zhu, C., Wu, Q., Yang, N., Zheng, Z., Zhou, F., & Zhou, Y. (2022) · Frontiers in Genetics · doi:10.3389/fgene.2022.848841 · Cited by 11
“We presented the expression profile of TCGA cohort similar with the results from the GSE65858 cohort and GSE41613 cohort, so that the data were comparable among samples (Wagner et al., 2012; Zeng et al., 2019).”
Method
AP3S1 is a Novel Prognostic Biomarker and Correlated With an Immunosuppressive Tumor Microenvironment in Pan-Cancer
Wu, G., Chen, M., Ren, H., Sha, X., He, M., Ren, K., Qi, J., & Lin, F. (2022) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2022.930933 · Cited by 11
“The TME-related pathways were obtained and pathway scores were calculated according to the published paper (Zeng et al., 2019).”
Method
A comprehensive analysis focusing on cuproptosis to investigate its clinical and biological relevance in uterine corpus endometrial carcinoma and its potential in indicating prognosis
Wu, Q., Tian, R., Tan, H. L. E., Liu, J., Ou, C., Li, Y., & Fu, X. (2022) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2022.1048356 · Cited by 11
“The TME context correlated with the immune response and benefit of chemotherapy, and different dominant cell populations within the TME could result in distinct clinical outcomes of cancers (Zeng et al., 2019).”
Background
Cuproptosis-Mediated Patterns Characterized by Distinct Tumor Microenvironment and Predicted the Immunotherapy Response for Gastric Cancer
Wang, X.-X., Deng, S., Wu, L., Liu, Q.-Q., Zheng, G., Du, K., Dou, Q.-Y., Zheng, J., & Zhang, H. (2023) · ACS Omega · doi:10.1021/acsomega.2c07052 · Cited by 11
Cuproptosis‐related miRNAs signature and immune infiltration characteristics in colorectal cancer
Zhu, Z., Guo, T., Weng, J., Li, S., Zhu, C., Zhao, Q., & Xu, Y. (2023) · Cancer Medicine · doi:10.1002/cam4.6270 · Cited by 10
A novel m6A/m5C/m1A score signature to evaluate prognosis and its immunotherapy value in colon cancer patients
Liu, J., Dou, M., Liu, X., Lu, Y., & Lu, W. (2023) · Journal of Cancer Research and Clinical Oncology · doi:10.1007/s00432-023-05033-1 · Cited by 11
Targeting the immune milieu in gastrointestinal cancers
Turkes, F., Mencel, J., & Starling, N. (2020) · Journal of Gastroenterology · doi:10.1007/s00535-020-01710-x · Cited by 11
Prognostic signature of ovarian cancer based on 14 tumor microenvironment-related genes
Nie, X., Song, L., Li, X., Wang, Y., & Qu, B. (2021) · Medicine · doi:10.1097/md.0000000000026574 · Cited by 11
Tumor Microenvironment Characteristics of Pancreatic Cancer to Determine Prognosis and Immune-Related Gene Signatures
Zhang, C., Ding, J., Xu, X., Liu, Y., Huang, W., Da, L., Ma, Q., & Chen, S. (2021) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2021.645024 · Cited by 11
“Many studies have proved that it has clinical significance in predicting prognosis and treatment (Zeng et al., 2019; Zhang et al., 2020).”
Background
Regulatory role of the transforming growth factor-β signaling pathway in the drug resistance of gastrointestinal cancers
Lv, X., & Xu, G. (2021) · World Journal of Gastrointestinal Oncology · doi:10.4251/wjgo.v13.i11.1648 · Cited by 11
Multi-Omics Analysis of Novel Signature for Immunotherapy Response and Tumor Microenvironment Regulation Patterns in Urothelial Cancer
Chu, G., Shan, W., Ji, X., Wang, Y., & Niu, H. (2021) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2021.764125 · Cited by 11
“Therefore, the different states of macrophages between the high- and low-score groups worth investigating further and may contribute to the accurate application of treatments (Li et al., 2019b; Tang et al., 2013).”
Background
A Support Vector Machine Based on Liquid Immune Profiling Predicts Major Pathological Response to Chemotherapy Plus Anti-PD-1/PD-L1 as a Neoadjuvant Treatment for Patients With Resectable Non-Small Cell Lung Cancer
Peng, J., Zou, D., Han, L., Yin, Z., & Hu, X. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.778276 · Cited by 12
“In addition to clinical factors and radiological response, detailed knowledge of the patient’s immune status of peripheral blood is needed to evaluate the efficacy of combination anti-PD-1/ PD-L1 treatment, and tumor immunogenicity score is evaluated as a predictor of immune checkpoint inhibitor response (31, 32).”
Background
Alternative splicing and alternative polyadenylation define tumor immune microenvironment and pharmacogenomic landscape in clear cell renal carcinoma
Zhong, W., Wu, Y., Zhu, M., Zhong, H., Huang, C., Lin, Y., & Huang, J. (2022) · Molecular Therapy — Nucleic Acids · doi:10.1016/j.omtn.2022.01.014 · Cited by 11
“As previously reported, the formula was employed to define the AS or APA score: AS or APA score = P (PC1i + PC2i), where i represented the PDUI or PSI value of the selected AS or APA event.(42,43)”
Method
ISYNA1: An Immunomodulatory-Related Prognostic Biomarker in Colon Adenocarcinoma and Pan-Cancer
Jia, Z., & Wan, X. (2022) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2022.792564 · Cited by 11
Pyroptosis patterns and immune infiltrates characterization in head and neck squamous cell carcinoma
Deng, H.-X., Wei, Z.-Y., Qiu, S.-J., Ye, D., Gu, S., Shen, Y., Shen, Z.-S., Jin, Y., & Zhou, C. (2022) · Journal of clinical laboratory analysis (Print) · doi:10.1002/jcla.24292 · Cited by 10
Tumor Microenvironment Profiling Identifies Prognostic Signatures and Suggests Immunotherapeutic Benefits in Neuroblastoma
Feng, C., Li, T., Xiao, J., Wang, J., Meng, X., Niu, H., Jiang, B., Huang, L., Deng, X., Yan, X., et al. (2022) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2022.814836 · Cited by 11
MiR-520a-5p/PPP5C regulation pattern is identified as the key to gemcitabine resistance in pancreatic cancer
Fu, R., Shao, Q., Yang, B., Chen, Y., Ye, Q., Chen, X., & Zhu, J. (2022) · Frontiers in Oncology · doi:10.3389/fonc.2022.903484 · Cited by 11
“However, because of the small sample size of genome-wide association studies related to pancreatic cancer, compared with, for example, breast and colorectal cancer, there are fewer associated genes and fewer variant sites in pancreatic cancer (8).”
Background
5-Methylcytosine (m5C) Modification Patterns and Tumor Immune Infiltration Characteristics in Clear Cell Renal Cell Carcinoma
Chen, C., Chen, L., Zhang, J., & Xu, H. (2022) · Current Oncology · doi:10.3390/curroncol30010044 · Cited by 10
Self-citation
Metastasis-Related Signature for Clinically Predicting Prognosis and Tumor Immune Microenvironment of Osteosarcoma Patients
Zhang, Q., Deng, Z., & Yang, Y. (2023) · Molecular Biotechnology · doi:10.1007/s12033-023-00681-7 · Cited by 11
A novel biomarker associated with EBV infection improves response prediction of immunotherapy in gastric cancer
Li, X., Xiong, F., Hu, Z., Qing, T., Yang, Y., Qiao, X., Peng, C., Jiang, Y., Han, M., Dong, K., et al. (2024) · Journal of Translational Medicine · doi:10.1186/s12967-024-04859-8 · Cited by 10
Multi-omics landscape analysis reveals the pan-cancer association of arginine biosynthesis genes with tumor immune evasion and therapy resistance
Tan, Z., Li, H., Huang, Y., Fu, S., Wang, H., & Wang, J. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e26804 · Cited by 10
“…the correlation between the arginine biosynthesis score and tumor immune microenvironment by referring to the method described by Zeng et al. [15], and the arginine biosynthesis score was negatively related to immune-related pathways (Antigen_processing_machinery, Immune_Checkpoint,…”
Method
Identification of T-cell exhaustion-related genes and prediction of their immunotherapeutic role in lung adenocarcinoma
Lian, C., Li, F., Xie, Y., Zhang, L., Chen, H., Wang, Z., Pan, X., Wang, X., & Zhang, J. (2024) · Journal of Cancer · doi:10.7150/jca.92839 · Cited by 10
“We collected three GEO immunotherapy cohorts (GSE78220[30] GSE35640[31] and GSE100797[32]), along with the IMvigor210 cohort, to investigate the relationship between TEX characteristics and immunotherapy.”
MethodSelf-citation
Machine learning developed a macrophage signature for predicting prognosis, immune infiltration and immunotherapy features in head and neck squamous cell carcinoma
Wang, Y., Mou, Y.-K., Liu, W.-C., Wang, H., Song, X., Yang, T., Ren, C., & Song, X. (2024) · Scientific Reports · doi:10.1038/s41598-024-70430-6 · Cited by 10
Development of a Prognostic Model for Ovarian Cancer Patients Based on Novel Immune Microenvironment Related Genes
Wang, W., Wu, Q., Wang, Z., Ren, S., Shen, H., Shi, W., & Xu, Y. (2021) · Frontiers in Oncology · doi:10.3389/fonc.2021.647273 · Cited by 10
“Many previous study have applied the algorithm to various types of cancer, such as breast cancer (11), colon cancer (12), gastric cancer (13) and brain cancer (14).”
Method
Profiles of immune infiltration in the tumor microenvironment of hepatocellular carcinoma
Meng, L., Ma, R., Yan, R., Yuan, D., Li, Y., Shi, L., & Li, K. (2021) · Journal of Gastrointestinal Oncology · doi:10.21037/jgo-21-291 · Cited by 10
“Previous studies have shown TME score to be a prognostic biomarker that could predict immunotherapeutic efficacy (23).”
Association of Angiogenesis Gene Expression With Cancer Prognosis and Immunotherapy Efficacy
Li, X., Ma, W., Su, L., Shen, Y., Zhang, L., Shao, Y.-H., Wang, D., Wang, Z., Wen, M., & Yang, X. (2022) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2022.805507 · Cited by 10
Machine learning and bioinformatics analysis revealed classification and potential treatment strategy in stage 3–4 NSCLC patients
Li, C., Tian, C., Zeng, Y.-L., Liang, J.-Y., Yang, Q.-F., Gu, F., Hu, Y., & Liu, L. (2022) · BMC Medical Genomics · doi:10.1186/s12920-022-01184-1 · Cited by 10
“The abundance of LM22 (22 immune cell types) was calculated using CIBERSORT algorithm [16] (model = relative, permutation = 1000, disable quantile normalization = True, https:// ciber sort. stanf ord. edu/).”
MethodInfluential
Identification of lncRNAs based on different patterns of immune infiltration in gastric cancer
Chen, S., Ben, X., Guo, L., & Li, X. (2022) · Journal of Gastrointestinal Oncology · doi:10.21037/jgo-21-833 · Cited by 10
“Studies have shown that different immune subtypes result in different prognoses (28).”
Background
Characterization of m6A Methylation Modification Patterns in Colorectal Cancer Determines Prognosis and Tumor Microenvironment Infiltration
Yue, Q., Zhang, Y., Wang, F., Cao, F., Bai, J. Y., & Duan, X. (2022) · Journal of Immunology Research · doi:10.1155/2022/8766735 · Cited by 10
“Next, principal component analysis (PCA) was performed for dimension reduction, and the final weight values of PC1 and PC2 were used to construct the m6Ascore model with the formula as follows [35]: m6Ascore =∑ðPC 1i + PC2iÞ, where “i” represents the expression of m6A regulator cluster-associated DEGs.”
Lactate score predicts survival, immune cell infiltration and response to immunotherapy in breast cancer
Yin, T., Huang, M.-X., Wang, F., Jiang, Y., Long, J., Li, L., & Cao, J. (2022) · Frontiers in Genetics · doi:10.3389/fgene.2022.943849 · Cited by 10
“Later, this study determined lactate score by gene expression grade index (GGI) (Sotiriou et al., 2006; Zeng et al., 2019): Lactate score ∑(PC1i + PC2i) in the formula, i stands for LRG expression levels.”
Method
Molecular subtypes of osteosarcoma classified by cancer stem cell related genes define immunological cell infiltration and patient survival
Guo, L., Yan, T., Guo, W., Niu, J., Wang, W., Ren, T., Huang, Y., Xu, J., & Wang, B. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.986785 · Cited by 11
“We also defined CSC score using a similar approach from previous studies (44, 45).”
Method
The Ferroptosis Molecular Subtype Reveals Characteristics of the Tumor Microenvironment, Immunotherapeutic Response, and Prognosis in Gastric Cancer
Xu, X., Zhou, N., Lan, H., Yang, F., Dong, B., & Zhang, X. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23179767 · Cited by 10
“As the immune checkpoint-related signatures, we chose CD274, CTLA4, LAG3, HAVCR2, IDO1, and PDCD1; as the immunological activity-related signatures, we chose CD8A, CXCL10, GZMA, CXCL9, GZMB, GZMA, IFNG, PRF1, TBX2, and TNF [42,43].”
Prognostic and predictive value of a mRNA signature in peripheral T‐cell lymphomas: A mRNA expression analysis
Tu, J., Kuang, Z., Xie, X., Wu, S., Wu, T., & Chen, S. (2020) · Journal of Cellular and Molecular Medicine · doi:10.1111/jcmm.15851 · Cited by 10
Machine Learning for Future Subtyping of the Tumor Microenvironment of Gastro-Esophageal Adenocarcinomas
Klein, S., & Duda, D. G. (2021) · Cancers · doi:10.3390/cancers13194919 · Cited by 10
Significance of CD8+ T cell infiltration-related biomarkers and the corresponding prediction model for the prognosis of kidney renal clear cell carcinoma
Tian, Y., Wei, Y., Liu, H., Shang, H., Xu, Y., Wu, T., Liu, W., Huang, A., Dang, Q., & Sun, Y. (2021) · Aging · doi:10.18632/aging.203584 · Cited by 10
Cell Differentiation Trajectory-Associated Molecular Classification of Osteosarcoma
Xu, A., Qian, C., Lin, J., Yu, W., Jin, J., Liu, B., & Tao, H. (2021) · Genes · doi:10.3390/genes12111685 · Cited by 10
“gov/programs/target/projects/osteosarcoma, accessed on 9 August 2021) were also gathered, and FPKM values were transformed into transcripts per kilobase million (TPM) values and then log2(TPM+1) values, which are more comparable between samples and more similar to data from microarrays [15,16].”

Authors: Zeng, D., Li, M., Zhou, R., Zhang, J., Sun, H., Shi, M., Bin, J., Liao, Y., Rao, J., & Liao, W.
Affiliations: Nanfang Hospital (CN)
Southern Medical University (CN)
ORCID: Zeng, Dongqiang
Li, Meiyi
Zhou, Rui
Zhang, Jingwen
Sun, Huiying
Shi, Min
Bin, Jianping
Liao, Yulin
Liao, Wangjun
Venue: Cancer Immunology Research
Publisher: American Association for Cancer Research (AACR)
Published: 2019-05-01
Volume: 7
Issue: 5
Pages: 737-750
ISSN: 2326-6066 (ISSN-L)
2326-6074
DOI: 10.1158/2326-6066.cir-18-0436
OpenAlex: W2920600229
Semantic Scholar: 180648d1827a7e8c086f03b00ca69831a1ca538e
Cited by: 986
References: 76
Citations by year: 2026: 38 · 2025: 87 · 2024: 164 · 2023: 211 · 2022: 251 · 2021: 162 · 2020: 64 · 2019: 9
FWCI: 53.10
Type: journal article
Language: en
Open access: closed
Locations: Cancer Immunology Research (publishedVersion)
PubMed (publishedVersion)
Funders: National Natural Science Foundation of China (81772580)
Topics: Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
Health Sciences › Medicine › Oncology › Gastric Cancer Management and Outcomes
Life Sciences › Immunology and Microbiology › Immunology › Immune cells in cancer
Keywords: gastric cancer, tumor microenvironment, prognostic factors, immunotherapy response, immune cell infiltration, T cell suppression, epithelial-mesenchymal transition, angiogenesis, TGF-beta signaling, IFN-gamma response, gene expression signatures, IMvigor210
MeSH terms: Antineoplastic Agents, Immunological, Algorithms, Humans, Immunotherapy, Phenotype, Prognosis, Stomach Neoplasms, Gene Expression Regulation, Neoplastic, Tumor Microenvironment

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Tumor Microenvironment Characterization in Gastric Cancer Identifies Prognostic and Immunotherapeutically Relevant Gene Signatures

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