Dataset Information

Profiles of immune cell infiltration in head and neck squamous carcinoma.

ABSTRACT: Tumor immune infiltration cells (TIICs) are highly heterogeneous, not only in different cancer subtypes but also within different cancer regions. We conducted the Cell-type Identification using Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) method. We assessed the relative proportions of 22 TIICs in HNSC using publicly available TCGA transcriptional datasets, analyzed the proportions of TIICs between HNSC tissues and normal tissues, along with accompanying clinicopathological data, and the impact of TIICs on clinical outcome. After the filter criteria, a total of 395 patients were included in the analysis. We found significant differences in naïve B cells, monocytes, resting mast cells, activated mast cells, CD8+ T cells, and M0 macrophages between HNSC tissues and adjacent non-cancer tissues. We also found that some TIIC subgroups were significantly associated with clinical parameters. Moreover, the patients with low Tregs fraction had worse OS and DFS than those with high Tregs fraction. However, low M0 macrophages fraction was associated with better OS and DFS in HNSC patients. Moreover, Tregs and M0 macrophages are likely to be important determinants of prognosis, which may serve as a potential immunotherapy target for HNSC. Then, we screened the immune-related differentially expressed genes (DEGs), performed the GO and KEGG enrichment analysis, constructed the protein-protein interaction network, and screened the prognosis-related hub genes in HNSC. However, further clinical investigation and basic experiments are needed to validate our results, and uncover the molecular mechanisms interlinking TIICs in HNSC and their roles in prognosis and therapy.

SUBMITTER: Liang B

PROVIDER: S-EPMC7042147 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Profiles of immune cell infiltration in head and neck squamous carcinoma.

Liang Bin B Tao Ye Y Wang Tianjiao T

Bioscience reports 20200201 2

Tumor immune infiltration cells (TIICs) are highly heterogeneous, not only in different cancer subtypes but also within different cancer regions. We conducted the Cell-type Identification using Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) method. We assessed the relative proportions of 22 TIICs in HNSC using publicly available TCGA transcriptional datasets, analyzed the proportions of TIICs between HNSC tissues and normal tissues, along with accompanying clinicopathological data, a ...[more]

PMID: 32095823

Similar Datasets

Project description:Tyrosine kinase 2 (TYK2) is a member of the Janus kinase (JAK) family and is involved in immune and inflammatory signaling. TYK2 is overexpressed in several types of cancers and promotes the invasion and proliferation of cancer cells. Nevertheless, the roles of TYK2 in the prognosis and immune infiltration of head and neck squamous cell carcinoma (HNSCC) remain to be elucidated. In this study, the expression of TYK2 in HNSCC was evaluated based on the data retrieved from multiple databases and quantitative real-time polymerase chain reaction (qRT-PCR) analysis. The prognostic potential of TYK2 in patients with HNSCC was analyzed by Kaplan-Meier curves and Cox regression analysis. A TYK2-related risk assessment model was subsequently constructed by Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis and stepwise multivariate Cox regression analysis. The association between the expression of TYK2 and the tumor immune microenvironment, immune checkpoints, and drug sensitivity was explored various packages in R. Cell function assays were finally used for exploring the effects of TYK2 on the growth and metastasis of HNSCC tumors. The expression of TYK2 was significantly upregulated in HNSCC and was found to be closely correlated with HPV status, gender, clinical grade, and TP53 mutation status. Survival analysis suggested that TYK2 is associated with better survival outcomes and acts as an independent prognostic indicator of HNSCC. The model constructed herein also performed well in terms of predicting patient prognosis. The expression of TYK2 was positively associated with the population of tumor-infiltrating immune cells, expression of immune checkpoint genes, and antitumor drug susceptibility. Functionally, TYK2 knockdown significantly promoted the proliferation, migration, and invasion of HNSCC cell lines in vitro. The findings demonstrated that TYK2 could serve as a suppressor of tumor growth and holds significant promise as a novel biomarker for assessing the prognosis of patients with HNSCC and aid in immunotherapy against HNSCC.

Project description:Background: Immunotherapy has become the new standard of care for recurrent and metastatic head and neck squamous cell carcinoma (HNSCC), and PD-L1 is a widely used biomarker for immunotherapeutic response. However, PD-L1 expression in most cancer patients is low, and alternative biomarkers used to screen the population benefiting from immunotherapy are still being explored. Tumor microenvironment (TME), especially tumor immune-infiltrating cells, regulates the body's immunity, affects the tumor growth, and is expected to be a promising biomarker for immunotherapy. Purpose: This article mainly discussed how the immune-infiltrating cell patterns impacted immunity, thereby affecting HNSCC patients' prognosis. Method: The immune-infiltrating cell profile was generated by the CIBERSORT algorithm based on the transcriptomic data of HNSCC. Consensus clustering was used to divide groups with different immune cell infiltration patterns. Differentially expressed genes (DEGs) obtained from the high and low immune cell infiltration (ICI) groups were subjected to Kaplan-Meier and univariate Cox analysis. Significant prognosis-related DEGs were involved in the construction of a prognostic signature using multivariate Cox analysis. Results: In our study, 408 DEGs were obtained from high- and low-ICI groups, and 59 of them were significantly associated with overall survival (OS). Stepwise multivariate Cox analysis developed a 16-gene prognostic signature, which could distinguish favorable and poor prognosis of HNSCC patients. An ROC curve and nomogram verified the sensitivity and accuracy of the prognostic signature. The AUC values for 1 year, 2 years, and 3 years were 0.712, 0.703, and 0.700, respectively. TCGA-HNSCC cohort, GSE65858 cohort, and an independent GSE41613 cohort proved a similar prognostic significance. Notably, the prognostic signature distinguished the expression of promising immune inhibitory receptors (IRs) well and could predict the response to immunotherapy. Conclusion: We established a tumor immune cell infiltration (TICI)-based 16-gene signature, which could distinguish patients with different prognosis and help predict the response to immunotherapy.

Project description:BackgroundHead and neck squamous cell carcinoma (HNSCC) is a frequently lethal malignancy, and the mortality is considerably high. The tumor microenvironment (TME) has been identified as a critical participation in cancer development, treatment, and prognosis. However, competing endogenous RNA (ceRNA) networks grouping with immune/stromal scores of HNSCC patients need to be further illustrated. Therefore, our study aimed to provide clues for searching promising prognostic markers of TME in HNSCC.Materials and methodsESTIMATE algorithm was used to calculate immune scores and stromal scores of the enrolled HNSCC patients. Differentially expressed genes (DEGs), lncRNAs (DELs), and miRNAs (DEMs) were identified by comparing the expression difference between high and low immune/stromal scores. Then, a ceRNA network and protein-protein interaction (PPI) network were constructed for selecting hub regulators. In addition, survival analysis was performed to access the association between immune scores, stromal scores, and differentially expressed RNAs in the ceRNA network and the overall survival (OS) of HNSCC patients. Then, the GSE65858 datasets from Gene Expression Omnibus (GEO) database was used for verification. At last, the difference between the clinical characteristics and immune cell infiltration in different expression groups of IL10RA, PRF1, and IL2RA was analyzed.ResultsSurvival analysis showed a better OS in the high immune score group, and then we constructed a ceRNA network composed of 97 DEGs, 79 DELs and 22 DEMs. Within the ceRNA network, FOXP3, IL10RA, STAT5A, PRF1, IL2RA, miR-148a-3p, miR-3065-3p, and lncRNAs, including CXCR2P1, HNRNPA1P21, CTA-384D8.36, and IGHV1OR15-2, were closely correlated with the OS of HNSCC patients. Especially, using the data from GSE65858, we successfully verified that IL10RA, PRF1, and IL2RA were not only significantly upregulated in patients high immune scores, but also their high expressions were associated with longer survival time. In addition, stratified analysis showed that PRF1 and IL2RA might be involved in the mechanism of tumor progress.ConclusionIn conclusion, we constructed a ceRNA network related to the TME of HNSCC, which provides candidates for therapeutic intervention and prognosis evaluation.

Dataset Information

Profiles of immune cell infiltration in head and neck squamous carcinoma.

Publications

Profiles of immune cell infiltration in head and neck squamous carcinoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets