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

ABSTRACT: Increasing evidence has clarified that the tumor microenvironment (TME) is closely related to the prognosis and therapeutic efficacy of cancer. However, there is no reliable TME evaluation system used to accurately predict the prognosis of and therapeutic efficacy in gastric cancer. We evaluated the immune microenvironment score (IMS) of 1422 gastric cancer samples based on 51 immune cell signatures. We explored the relationship between the IMS and prognosis, immune cell infiltration, cancer subtype, and potential immune escape mechanisms. The results show that activation of the stroma and decreased levels of immune infiltration were associated with a low IMS. A high IMS was characterized by Epstein-Barr virus infection, increased mutation load, microsatellite instability, and immune cell infiltration. A high IMS was also related to high expression of immune checkpoint molecules (PD-1/PD-L1). Finally, patients with a high IMS had a better response to PD-1/PD-L1 inhibitors and may be more suitable for immune checkpoint inhibitors (area under the curve = 0.81). In addition, a low IMS may be converted into the immune-infiltrating subtype after romidepsin treatment. Stratification based on the IMS may enable gastric cancer patients to benefit more from immunotherapy and help identify new cancer treatment strategies.

SUBMITTER: Lin Y

PROVIDER: S-EPMC8505616 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

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

Lin Yilin Y Pan Xiaoxian X Zhao Long L Yang Changjiang C Zhang Zhen Z Wang Bo B Gao Zhidong Z Jiang Kewei K Ye Yingjiang Y Wang Shan S Shen Zhanlong Z Shen Zhanlong Z

NPJ genomic medicine 20211011 1

Increasing evidence has clarified that the tumor microenvironment (TME) is closely related to the prognosis and therapeutic efficacy of cancer. However, there is no reliable TME evaluation system used to accurately predict the prognosis of and therapeutic efficacy in gastric cancer. We evaluated the immune microenvironment score (IMS) of 1422 gastric cancer samples based on 51 immune cell signatures. We explored the relationship between the IMS and prognosis, immune cell infiltration, cancer sub ...[more]

PMID: 34635662

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Project description:BackgroundAT-rich interaction domain 1A (ARID1A) is an essential subunit of the switch/sucrose non-fermentable chromatin remodeling complex and is considered to be a tumor suppressor. The Cancer Genome Atlas (TCGA) molecular classification has deepened our understanding of gastric cancer at the molecular level. This study explored the significance of ARID1A expression in TCGA subtypes of gastric adenocarcinoma.MethodsWe collected 1248 postoperative patients with gastric adenocarcinoma, constructed tissue microarrays, performed immunohistochemistry for ARID1A, and obtained correlations between ARID1A and clinicopathological variables. We then carried out the prognostic analysis of ARID1A in TCGA subtypes. Finally, we screened patients by random sampling and propensity score matching method and performed multiplex immunofluorescence to explore the effects of ARID1A on CD4, CD8, and PD-L1 expression in TCGA subtypes.ResultsSeven variables independently associated with ARID1A were screened out: mismatch repair proteins, PD-L1, T stage, differentiation status, p53, E-cadherin, and EBER. The independent prognostic variables in the genomically stable (GS) subtype were N stage, M stage, T stage, chemotherapy, size, and ARID1A. PD-L1 expression was higher in the ARID1A negative group than in the ARID1A positive group in all TCGA subgroups. CD4 showed higher expression in the ARID1A negative group in most subtypes, while CD8 did not show the difference in most subtypes. When ARID1A was negative, PD-L1 expression was positively correlated with CD4/CD8 expression; while when ARID1A was positive, this correlation disappeared.ConclusionsThe negative expression of ARID1A occurred more frequently in the Epstein-Barr virus and microsatellite instability subtypes and was an independent adverse prognostic factor in the GS subtype. In the TCGA subtypes, ARID1A negative expression caused increased CD4 and PD-L1 expression, whereas CD8 expression appeared independent of ARID1A. The expression of CD4/CD8 induced by ARID1A negativity was accompanied by an increase in PD-L1 expression.

Project description:Copper toxicity involves the destruction of mitochondrial metabolic enzymes, triggering an unusual mechanism of cell death called cuproptosis, which proposes a novel approach using copper toxicity to treat cancer. However, the biological function of cuproptosis has not been fully elucidated in kidney renal clear cell carcinoma (KIRC). Using the expression profile of 13 cuproptosis regulators, we first identified two molecular subtypes related to cuproptosis defined as "hot tumor" and "cold tumor", having different levels of biological function, clinical prognosis, and immune cell infiltration. We obtained three gene clusters using the differentially expressed genes between the two cuproptosis-related subtypes, which were associated with different molecular activities and clinical characteristics. Next, we developed and validated a cuproptosis prognostic model that included two genes (FDX1 and DBT). The calculated risk score could divide patients into high- and low-risk groups. The high-risk group had a poorer prognosis, lower level of immune infiltration, higher frequency of gene alterations, and greater levels of FDX1 methylation and limited DBT methylation. The risk score was also an independent predictive factor for overall survival in KIRC. The established nomogram calculating the risk score achieved a high predictive ability for the prognosis of individual patients (area under the curve: 0.860). We then identified small molecular inhibitors as potential treatments and analyzed the sensitivity to chemotherapy of the signature genes. Tumor immune dysfunction and exclusion (TIDE) showed that the high-risk group had a higher level of TIDE, exclusion and dysfunction that was lower than the low-risk group, while the microsatellite instability of the high-risk group was significantly lower. The results of two independent immunotherapy datasets indicated that cuproptosis regulators could influence the response and efficacy of immunotherapy in KIRC. Our study provides new insights for individualized and comprehensive therapy of KIRC.

Project description:BackgroundBrain tumor ranks as the most devastating cancer type. The complex tumor immune microenvironment prevents brain tumor from receiving therapeutic benefits. The purpose of this study was to stratify brain tumors based on their distinct immune infiltration signatures to facilitate better clinical decision making and prognosis prediction.MethodsWe developed a deep learning model to characterize immune infiltration from transcriptome. The developed model was applied to distill expression signatures of transcriptome of brain tumor samples. We performed molecular subtyping with the extracted expression signatures to unveil brain tumor subtypes. Computational methods, including gene set enrichment analysis, Kaplan-Meier survival and multivariate Cox regression analyses, were employed.ResultsWe identified two distinctive subtypes (i.e. C1/2) of brain tumor featured by distinct immune infiltration signatures. The C1 subtype is characterized by protective immune infiltration signatures, including high infiltration of CD8+ T cells and activation of CX3CL1. The C2 subtype has an extensive infiltration of tumor-associated macrophages and microglia, and was enriched with immune suppressive, wound-healing, and angiogenic signatures. The C1 subtype had significantly better prognosis as compared with C2 (Log-rank test, HR: 2.5, 95% CI: 2.2 - 2.7; P = 8.2e-78). This difference remained statistically significant (multivariate Cox model, HR: 2.2, 95% CI: 1.7 - 2.9; P = 3.7e-10) by taking into account age, gender, recurrent/secondary status at sampling time, tumor grade, histology, radio-chemotherapy, IDH mutation, MGMT methylation, and co-deletion of 1p and 19q. This finding was validated in six datasets. The C2 subtype of glioblastoma patients with IDH mutation has poor survival analogous to those without IDH mutation (Log-rank test, adjusted P = 0.8), while C1 has favorable prognosis as compared with glioblastoma of C2 subtype with IDH mutation (Log-rank test, adjusted P = 1.2e-3) or without IDH mutation (Log-rank test, adjusted P = 1.3e-6).ConclusionsWe identified two distinctive subtypes of brain tumor with different immune infiltration signatures, which might be helpful as an independent prognosticator for brain tumor.

Project description:PurposeHypoxia and immune cell infiltration play an important role in the progression and metastasis of gastric cancer. However, the molecular classification of gastric cancer combined with hypoxia and immune cell infiltration remains unknown.Materials and methodsssGSEA was used to evaluate the hypoxic state and immune cell infiltration of 1059 gastric cancer samples collected from the GEO and TCGA database. Based on the results, unsupervised clustering was performed to obtain different gastric cancer subtypes. The differentially expressed genes related to OS between these subtypes were utilized for LASSO analysis to construct a prognostic signature (HIscore). Subsequently, small-molecule drugs were predicted using the Connectivity Map (CMAP) database.ResultsWe obtained three hypoxic-immune infiltration patterns (HIcluster A-C) with different prognoses and classified them as low hypoxic/low immune, high hypoxic/high immune, and low hypoxic/high immune subtypes. Based on the differential genes between HIclusters, we have also obtained other three gastric cancer subtypes (genecluster A-C) and a 13-gene signature (HIscore). At the same time, we extensively explored the clinical and transcriptome traits in different clusters and groups with high or low HIscore. We proved that HIscore is an independent prognostic biomarker and an indicator of genome stability and EMT. Using the CMAP database, we found 96 small-molecule drugs that could reverse the poor prognosis and could serve as therapeutic drugs, especially for gastric cancer patients with high HIscore.ConclusionOur study evaluated the hypoxic state and immune cell infiltration in gastric tumors, and identified different gastric cancer subtypes. In addition, we established a hypoxia-immune signature to predict prognosis which is tightly linked to tumor EMT and genomic stability. Based on HIscore, we used the CMAP database to explore small-molecule drugs that may have the potential in serving as therapeutic drugs.

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

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

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