Immune cell infiltration signatures identified molecular subtypes and underlying mechanisms in gastric cancer

Lin, Yilin; Pan, Xiaoxian; Zhao, Long; Yang, Changjiang; Zhang, Zhen; Wang, Bo; Gao, Zhidong; Jiang, Kewei; Ye, Yingjiang; Wang, Shan; Shen, Zhanlong

doi:10.1038/s41525-021-00249-x

Cited by 28 publications

(27 citation statements)

References 59 publications

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“…A better understanding of antitumor immunity will help predict the prognosis of gastric cancer patients and customize the appropriate therapies in each patient. Therefore, immune profiling of gastric cancer and immunological classification were extensively studied [ [6] , [7] , [8] , [9] ]. Previously, we also proposed a novel immunological classification of gastric cancer [ 10 ].…”

Section: Introductionmentioning

confidence: 99%

Two distinct phenotypes of immunologically hot gastric cancer subtypes

Saito

Kobayashi

Nagaoka

et al. 2021

Biochemistry and Biophysics Reports

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Section: Introductionmentioning

confidence: 99%

Two distinct phenotypes of immunologically hot gastric cancer subtypes

Saito

Kobayashi

Nagaoka

et al. 2021

Biochemistry and Biophysics Reports

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“…Recently, molecular subtyping systems focusing on immune infiltrating signatures have emerged to stratify patients and predict prognosis and immunotherapeutic outcomes in various tumors ( 55 – 57 ). However, these subtyping systems failed to depict detailed immune profiles in TME, which are important for understanding the mechanisms by which immune cells modulate tumor progression and response to ICB therapy.…”

Section: Discussionmentioning

confidence: 99%

Immune-infiltrating signature-based classification reveals CD103+CD39+ T cells associate with colorectal cancer prognosis and response to immunotherapy

et al. 2022

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BackgroundCurrent stratification systems for tumor prognostic prediction and immunotherapeutic efficacy evaluation are less satisfying in colorectal cancer (CRC). As infiltrating immune cells in tumor microenvironment (TME) played a key role in tumor progression and responses to immune checkpoint blockade (ICB) therapy, we want to construct an immune-related scoring system with detailed immune profiles to stratify CRC patients.MethodsWe developed a scoring system based on immune-related signatures and validated its ability to predict prognosis and immunotherapeutic outcomes in CRC. CD45+ cells from CRC patients were sorted to investigate detailed immune profiles of the stratification system using mass cytometry. A single-cell RNA sequencing dataset was used to analyze transcriptomic profiles.ResultsWe constructed an immune-related signature score (IRScore) based on 54 recurrence-free survival (RFS)-related immune signatures to stratify CRC patients. We revealed that IRScore was positively correlated with RFS and favorable outcomes in ICB treatment. Moreover, we depicted a detailed immune profile in TME using mass cytometry and identified that CD103+CD39+ T cells, characterized by an exhaustive, cytotoxic and proliferative phenotype, were enriched in CRC patients with high IRScore. As a beneficial immune signature, CD103+CD39+ T cells could predict prognosis and responses to ICB therapy in CRC.ConclusionsAll the analyses above revealed that IRScore could be a valuable tool for predicting prognosis and facilitating the development of new therapeutic strategies in CRC, and CD103+CD39+ T cells were one of defined immune signatures in IRScore, which might be a key factor for antitumor immunity.

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“…Compared with other subgroups, patients with high TMB/high m6Ascore have the worst prognosis, which also shows that the TMB status does not affect the prognostic value of m6Ascore. m6Ascore has the potential to predict immunotherapy responsiveness, which may be independent of TMB ( Zhang et al, 2020 ; Guan et al, 2021 ; Lin et al, 2021 ; Sun et al, 2021 ; Wu et al, 2021 ). In addition, the TIDE results suggested that the patients in the low-risk group may respond better to immunotherapy.…”

Section: Discussionmentioning

confidence: 99%

The development of a novel signature based on the m6A RNA methylation regulator-related ceRNA network to predict prognosis and therapy response in sarcomas

Lin

Wang

et al. 2022

Front. Genet.

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Background: N6 methyladenosine (m6A)-related noncoding RNAs (including lncRNAs and miRNAs) are closely related to the development of cancer. However, the gene signature and prognostic value of m6A regulators and m6A-associated RNAs in regulating sarcoma (SARC) development and progression remain largely unexplored. Therefore, further research is required.Methods: We obtained expression data for RNA sequencing (RNA-seq) and miRNAs of SARC from The Cancer Genome Atlas (TCGA) datasets. Correlation analysis and two target gene prediction databases (miRTarBase and LncBase v.2) were used to deduce m6A-related miRNAs and lncRNAs, and Cytoscape software was used to construct ceRNA-regulating networks. Based on univariate Cox regression and least absolute shrinkage and selection operator (LASSO) Cox regression analyses, an m6A-associated RNA risk signature (m6Ascore) model was established. Prognostic differences between subgroups were explored using Kaplan–Meier (KM) analysis. Risk score-related biological phenotypes were analyzed in terms of functional enrichment, tumor immune signature, and tumor mutation signature. Finally, potential immunotherapy features and drug sensitivity predictions for this model were also discussed.Results: A total of 16 miRNAs, 104 lncRNAs, and 11 mRNAs were incorporated into the ceRNA network. The risk score was obtained based on RP11-283I3.6, hsa-miR-455-3p, and CBLL1. Patients were divided into two risk groups using the risk score, with patients in the low-risk group having longer overall survival (OS) than those in the high-risk group. The receiver operating characteristic (ROC) curves indicated that risk characteristic performed well in predicting the prognosis of patients with SARC. In addition, lower m6Ascore was also positively correlated with the abundance of immune cells such as monocytes and mast cells activated, and several immune checkpoint genes were highly expressed in the low-m6Ascore group. According to our analysis, lower m6Ascore may lead to better immunotherapy response and OS outcomes. The risk signature was significantly associated with the chemosensitivity of SARC. Finally, a nomogram was constructed to predict the OS in patients with SARC. The concordance index (C-index) for the nomogram was 0.744 (95% CI: 0.707–0.784). The decision curve analysis (DCA), calibration plot, and ROC curve all showed that this nomogram had good predictive performance.Conclusion: This m6Ascore risk model based on m6A RNA methylation regulator-related RNAs may be promising for clinical prediction of prognosis and might contain potential biomarkers for treatment response prediction for SARC patients.

show abstract

Immune cell infiltration signatures identified molecular subtypes and underlying mechanisms in gastric cancer

Cited by 28 publications

References 59 publications

Two distinct phenotypes of immunologically hot gastric cancer subtypes

Two distinct phenotypes of immunologically hot gastric cancer subtypes

Immune-infiltrating signature-based classification reveals CD103+CD39+ T cells associate with colorectal cancer prognosis and response to immunotherapy

The development of a novel signature based on the m6A RNA methylation regulator-related ceRNA network to predict prognosis and therapy response in sarcomas

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