Dataset Information

Characterization of the Immune Cell Infiltration Landscape in Head and Neck Squamous Cell Carcinoma to Aid Immunotherapy.

ABSTRACT: The tumor microenvironment (TME) chiefly consists of tumor cells and tumor-infiltrating immune cells admixed with the stromal component. A recent clinical trial has shown that the tumor immune cell infiltration (ICI) is correlated with the sensitivity to immunotherapy and the head and neck squamous cell carcinoma (HNSC) prognosis. However, to date, the immune infiltrative landscape of HNSC has not yet been elucidated. Herein, we proposed two computational algorithms to unravel the ICI landscape of 1,029 HNSC patients. Three ICI patterns were defined, and the ICI scores were determined by using principal-component analysis. A high ICI score was characterized by an increased tumor mutation burden (TMB) and the immune-activating signaling pathways. Activation of transforming growth factor-? (TGF-?) and WNT signaling pathways were observed in low ICI score subtypes, indicating T cell suppression, and may be responsible for poor prognosis. Two immunotherapy cohorts confirmed patients with higher ICI scores demonstrated significant therapeutic advantages and clinical benefits. This study demonstrated that the ICI scores serve as an effective prognostic biomarker and predictive indicator for immunotherapy. Evaluating the ICI patterns of a larger cohort of samples will extend our understanding of TME, and it may provide directions to the current research investigations on immunotherapeutic strategies for HNSC.

SUBMITTER: Zhang X

PROVIDER: S-EPMC7522342 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Characterization of the Immune Cell Infiltration Landscape in Head and Neck Squamous Cell Carcinoma to Aid Immunotherapy.

Zhang Xinhai X Shi Mengqi M Chen Tielou T Zhang Boxin B

Molecular therapy. Nucleic acids 20200829

The tumor microenvironment (TME) chiefly consists of tumor cells and tumor-infiltrating immune cells admixed with the stromal component. A recent clinical trial has shown that the tumor immune cell infiltration (ICI) is correlated with the sensitivity to immunotherapy and the head and neck squamous cell carcinoma (HNSC) prognosis. However, to date, the immune infiltrative landscape of HNSC has not yet been elucidated. Herein, we proposed two computational algorithms to unravel the ICI landscape ...[more]

PMID: 33230435

Similar Datasets

Project description:BackgroundN6-Methyladenosine (m6A), which is a prevalent regulator of mRNA expression, has gathered increasing study interests. Though the role of m6A as being important in many biological processes (such as growth and proliferation of cancers) has been well documented, its potential role in tumor immune microenvironment (TIME) has rarely been analyzed.MethodsWe downloaded RNA expression, single nucleotide polymorphism (SNP), and copy number variation (CNV) data from The Cancer Genome Atlas (TCGA). We then curated 21 m6A regulators and clustered patients into three m6A subtypes and m6A-related gene subtypes and compared them based on overall survival (OS). The combination of CIBERSORT as well as ssGSEA quantified the infiltration levels of immune cells and immune-related functions. The m6A scores were determined by using principal component analysis (PCA) algorithm. Furthermore, we evaluate the correlation of m6A regulators with immune and response to therapy.ResultsThree m6A clusters were identified based on the TCGA-HNSCC cohort, and there were significant associations among them in overall outcomes and caner-related pathways. We found that three m6A clusters were consistent with three phenotypes: immune-inflamed, immune-dessert, and immune-excluded. HNSCC patients were divided into high- and low-m6A score groups based on the cutoff of m6A score. Patients with lower m6A score had better overall survival outcome. Further analysis indicated that patients with higher m6A score presented higher tumor mutation burden (TMB). In addition, patients in low-m6A score subgroup had high chemotherapeutics sensitivity. GEO cohort confirmed patients with low m6A score demonstrated significant overall survival advantages and clinical benefits. Low m6A score carry an increased neoantigen load, eliciting a response to immunotherapy, and its value in predicting survival outcomes of immunotherapy was also confirmed in three anti-PD-1 cohorts.ConclusionsOur study demonstrated that m6A regulators are closely related to TIME and the m6A score was an effective prognostic biomarker and predictive indicator for immunotherapy and chemotherapeutics. Comprehensive evaluation of m6A regulators in tumors will extend our understanding of TIME and effectively guide increasing study investigations on immunotherapy and chemotherapy strategies for HNSCC.

Project description:Background: Long non-coding RNA (lncRNA) plays a significant role in the development, establishment, and progression of head and neck squamous cell carcinoma (HNSCC). This article aims to develop an immune-related lncRNA (irlncRNA) model, regardless of expression levels, for risk assessment and prognosis prediction in HNSCC patients. Methods: We obtained clinical data and corresponding full transcriptome expression of HNSCC patients from TCGA, downloaded GTF files to distinguish lncRNAs from Ensembl, discerned irlncRNAs based on co-expression analysis, distinguished differentially expressed irlncRNAs (DEirlncRNAs), and paired these DEirlncRNAs. Univariate Cox regression analysis, LASSO regression analysis, and stepwise multivariate Cox regression analysis were then performed to screen lncRNA pairs, calculate the risk coefficient, and establish a prognosis model. Finally, the predictive power of this model was validated through the AUC and the ROC curves, and the AIC values of each point on the five-year ROC curve were calculated to select the maximum inflection point, which was applied as a cut-off point to divide patients into low- or high-risk groups. Based on this methodology, we were able to more effectively differentiate between these groups in terms of survival, clinico-pathological characteristics, tumor immune infiltrating status, chemotherapeutics sensitivity, and immunosuppressive molecules. Results: A 13-irlncRNA-pair signature was built, and the ROC analysis demonstrated high sensitivity and specificity of this signature for survival prediction. The Kaplan-Meier analysis indicated that the high-risk group had a significantly shorter survival rate than the low-risk group, and the chi-squared test certified that the signature was highly related to survival status, clinical stage, T stage, and N stage. Additionally, the signature was further proven to be an independent prognostic risk factor via the Cox regression analyses, and immune infiltrating analyses showed that the high-risk group had significant negative relationships with various immune infiltrations. Finally, the chemotherapeutics sensitivity and the expression level of molecular markers were also significantly different between high- and low-risk groups. Conclusion: The signature established by paring irlncRNAs, with regard to specific expression levels, can be utilized for survival prediction and to guide clinical therapy in HNSCC.

Project description:Background: Immune-checkpoint blockade (ICB) has been routinely implemented to treat head and neck squamous cell carcinoma (HNSCC) patients. However, only a few patients benefit from immune checkpoint inhibitor (ICI) therapies. Methods: In this study, we used a combined cohort (including the GSE41613, GSE65858, TCGA, and CELL cohorts) to identify hub genes significantly associated with ICB and activated CD8+ T-cell gene signatures. We performed single-sample gene set enrichment analysis (ssGSEA) to quantify the expression of hub genes; we then constructed a novel immune signature named "the IMS" that can predict immunotherapy responsiveness, prognosis, immune infiltration, and clinical characteristics. Data from the GSE102349 external cohort and the pembrolizumab cohort obtained from a clinical trial were used to validate the efficiency of the IMS. In addition, we revealed potential mechanisms of the antitumor response by analyzing the HNSCC single-cell database. Finally, we used the LASSO algorithm to build an IMS-related risk model. Results: The high IMS group was associated with significant immune activation, better prognosis, and increased immunotherapy responsiveness; thus, the IMS potentially represents a candidate biomarker for ICB. Moreover, a tumor microenvironment with a higher IMS underwent remarkable metabolic reprogramming characterized by enrichment in the glycolysis/gluconeogenesis, oxidative phosphorylation, and citrate cycle (TCA cycle) pathways. We also revealed key information on cellular crosstalk between the IMS and other immune lineages, which may mechanistically explain immune escape. In addition, we constructed and validated a risk prediction model (CD2, TBC1D10C, and CD3E) that could stratify HNSCC patients based on survival and response to ICB treatment. Conclusion: IMS is a signature closely correlated with the tumor immune microenvironment. The findings of this study contribute to the understanding of the immune landscape in HNSCC patients. IMS may aid in the clinical management of HNSCC patients through the identification of effective immunotherapies for specific patients.

Dataset Information

Characterization of the Immune Cell Infiltration Landscape in Head and Neck Squamous Cell Carcinoma to Aid Immunotherapy.

Publications

Characterization of the Immune Cell Infiltration Landscape in Head and Neck Squamous Cell Carcinoma to Aid Immunotherapy.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets