Prognostic Matrisomal Gene Panel and Its Association with Immune Cell Infiltration in Head and Neck Carcinomas.
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ABSTRACT:
SUBMITTER: Belotti Y
PROVIDER: S-EPMC8616409 | biostudies-literature |
REPOSITORIES: biostudies-literature
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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.
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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.
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Project description:Head and neck squamous cell carcinoma (HNSCC) is a highly aggressive solid tumor. Because most studies have focused on the intrinsic carcinogenic pathways of tumors, we focused on the relationship between N6-methyladenosine (m6A) and the prognosis of HNSCC in the tumor immune microenvironment. We downloaded RNA-seq data from the TCGA dataset and used univariate Cox regression to screen m6A-related lncRNAs. The expression value of LASSO-screened genes was the sum of LASSO regression coefficients. We then evaluated relationships between the risk score and cellular components or cellular immune response. Differences in immune response under various algorithms were visualized with heat maps. The GSVA package in R was used to analyze GO, BP, KEGG, and hallmark gene sets of immune checkpoint clusters and immune checkpoint scores. The GSEA analysis was performed with the cluster profile package, yielding 21 m6A genes. Related lncRNAs were screened with Pearson's correlations, and the resulting 442 lncRNAs were screened using single-factor analysis. Eight lncRNAs closely related to prognosis were identified through survival random forest. Survival analysis showed that patients with a high risk score had a poor prognosis. Low- and high-risk-score groups differed significantly in m6A gene expression. Prognostic scores from different algorithms were significantly correlated with B cells, T cells, and memory cells in the immune microenvironment. Expression of immune checkpoints and signal pathways differed significantly across risk-score groups, suggesting that m6A could mediate lncRNA-induced immune system dysfunction and affect HNSCC development. A comprehensive study of tumor-cell immune characteristics should provide more insight into the complex immune microenvironment, thus contributing to the development of new immunotherapeutic agents.
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Project description:PurposeHead and neck squamous cell carcinoma (HNSCC) is a highly invasive malignancy with poor survival. Perforin (PRF1) plays essential roles in host immunity. Our research intended to identify the correlations of PRF1 with clinical prognosis and tumor immune infiltration in HNSCC.MethodsWe explored PRF1 expression and its associations with the clinical features of HNSCC via the Tumor Immune Estimation Resource (TIMER), Oncomine and The Cancer Genome Atlas (TCGA) databases. The prognostic value of PRF1 for HNSCC was further explored by Kaplan-Meier plotter and TIMER. Finally, the relation between PRF1 and immune infiltration in HNSCC was estimated via CIBERSORT and TIMER.ResultsPRF1 expression was remarkably elevated in HNSCC and associated with clinical stage and HPV infection. High PRF1 expression predicted favorable outcomes in HNSCC, especially in HPV+ HNSCC. Moreover, higher infiltration of CD8+ T cells and CD4+ T cells were found in the PRF1high group of HNSCC. PRF1 expression in HNSCC was strongly correlated with infiltrating CD8+ T cells and dendritic cells (DCs), with higher relevance in HPV+ HNSCC.ConclusionOur findings suggested that PRF1 could be a novel prognostic biomarker in HNSCC and that its expression was related to immune cell infiltration, which was impacted by HPV status.
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Project description: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.
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Project description:BackgroundRecurrent locally advanced or metastatic head and neck squamous cell carcinoma (HNSCC) is associated with dismal prognosis because of its highly invasive behavior and resistance to conventional intensive chemotherapy. The identification of effective markers for early diagnosis and prognosis is important for reducing mortality and ensuring that therapy for HNSCC is effective. Proteasome 26S subunit, non-ATPase 7 (PSMD7) is an ATP-independent component of the 19S regulatory subunit. The prognostic value of PSMD7 and the association with immune infiltration in HNSCC remains unclear.MethodsThe Sangerbox, Oncomine, UALCAN and Human Protein Atlas (HPA) databases were used to examine PSMD7 expression profiles in HNSCC. The CVCDAP was used to analysis the association of PSMD7 with the prognosis of patients with HNSCC. The mechanism was investigated with gene set enrichment analysis (GSEA). The association between expression of PSMD7 and immune infiltration in HNSCC was investigated using the Tumor Immune Estimation Resource (TIMER), TISIDB database and CIBERSORT algorithm.ResultsPSMD7 expression was significantly up-regulated in HNSCC compared with relative normal tissues. In addition, up-regulated PSMD7 expression was associated with various clinicopathological parameters. High expression of PSMD7 suggested inferior survival of HNSCC patients. GSEA and CERES score indicated that PSMD7 was closely correlated with tumor-related signaling pathways and cell survival. Functional analyses revealed that PSMD7 was positively correlated with various infiltration levels. Moreover, PSMD7 influenced the prognosis of HNSCC patients partially via immune infiltration.ConclusionOur findings suggest that PSMD7 is associated poor prognosis in patients with HNSCC and plays an important role in tumor-related immune infiltration.
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Project description:To investigate the relationship between the transcription factor, E2F4, and head and neck squamous cell carcinoma (HNSCC), and to preliminarily explore the signaling pathways and immunological role of E2F4. The mRNA expression of E2F4 in HNSCC was evaluated by searching Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) datasets. E2F4 protein expression was analyzed by immunohistochemistry using the CMU1h-ENT database. The association between E2F4 expression and tumor infiltration of immune cells was analyzed. Intracellular signaling by E2F4 was explored using KEGG and GO analysis. The correlation of E2F4 expression with clinical characteristics and its prognostic role were validated and analyzed in TCGA database. From the analysis of GEO and TCGA data, E2F4 expression was found to be up-regulated in HNSCC tumor tissues, and its level was associated with T, Grade, and M staging. Kaplan-Meier curve and Cox analyses indicated that the high expression of E2F4 was related to a poor prognosis. Thus, E2F4 was considered a potential prognostic factor for HNSCC. Immunohistochemical staining showed that E2F4 was mainly localized in the cell nucleus; it was highly expressed in HNSCC tissues, with a significant difference noted from that in pericancerous mucosa tissues. A correlation was observed between the differential expression of E2F4 and the immune infiltration of HNSCC. As revealed by KEGG and GO analysis, differential enrichment was found in the cell cycle, spliceosome, meiosis, microbial polysaccharide synthesis, and WNT signaling pathway, as well as in cyclic adenosine monophosphate, ERBB2, VEGF, GCNP and MYC pathways. E2F4 plays an important role in tumor progression and may be a critical biological prognostic factor for HNSCC. In addition, it functions in the nucleus as a transcription factor, regulates immune cells, and could be a promising molecular target for the diagnosis and treatment of HNSCC.
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Project description:Survival analysis of the Cancer Genome Atlas (TCGA) dataset is a well-known method for discovering gene expression-based prognostic biomarkers of head and neck squamous cell carcinoma (HNSCC). A cutoff point is usually used in survival analysis for patient dichotomization when using continuous gene expression values. There is some optimization software for cutoff determination. However, the software's predetermined cutoffs are usually set at the medians or quantiles of gene expression values. There are also few clinicopathological features available in pre-processed datasets. We applied an in-house workflow, including data retrieving and pre-processing, feature selection, sliding-window cutoff selection, Kaplan-Meier survival analysis, and Cox proportional hazard modeling for biomarker discovery. In our approach for the TCGA HNSCC cohort, we scanned human protein-coding genes to find optimal cutoff values. After adjustments with confounders, clinical tumor stage and surgical margin involvement were found to be independent risk factors for prognosis. According to the results tables that show hazard ratios with Bonferroni-adjusted p values under the optimal cutoff, three biomarker candidates, CAMK2N1, CALML5, and FCGBP, are significantly associated with overall survival. We validated this discovery by using the another independent HNSCC dataset (GSE65858). Thus, we suggest that transcriptomic analysis could help with biomarker discovery. Moreover, the robustness of the biomarkers we identified should be ensured through several additional tests with independent datasets.
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Project description:Clear cell renal cell carcinomas (ccRCCs) are highly immune infiltrates, and many of them respond to immunotherapy with checkpoint inhibitors including anti-PD-L1 or anti-PD1 agents. However, the effect of immune genes on clinical outcomes in ccRCCs has not been fully studied. Here, we show in this study that an immune-associated gene panel has a prognostic value for clear cell renal cell carcinomas. We performed single-sample gene set enrichment analysis (ssGSEA) and cell type identification by estimating subsets of RNA transcripts (CIBERSORT) algorithms on patient-matched normal renal and RCC tissues to characterize two immunophenotypes and immunological characteristic subpopulations. Furthermore, LASSO Cox regression was applied to develop a novel prognosis-associated model for ccRCC patients based on an immune-gene panel. The results were verified by the Gene Expression Omnibus (GEO) dataset and coordinated with the clinicopathological characteristics of ccRCCs, along with genomic signatures. Finally, based on the above perspectives, we generated a nomogram with a high prognostic efficiency for ccRCC patients. Overall, this study offers a unique perspective that can contribute to improving the accuracy of prognosis prediction and treatment with immunotherapy.
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Project description:ObjectiveTo investigate the expression of TTC7B and its prognostic significance, biological roles, and impact on the immune system in patients with head and neck squamous cell carcinoma (HNSCC).Materials and methodsClinical and genomic data were obtained from TCGA (The Cancer Genome Atlas), GEO (Gene Expression Omnibus), GEPIA2 (Gene Expression Profiling Interactive Analysis 2.0), and TIMER2.0 (Tumor Immune Estimation Resource 2.0) databases. R software was utilized to process the retrieved data. qPCR and immunohistochemical assays were performed to validate the findings obtained from the databases.ResultsHigh expression of TTC7B was observed in HNSCC, and this heightened expression is significantly associated with reduced overall survival (OS) in patients, making it an independent risk factor impacting OS. TTC7B is correlated with focal adhesions and cell migration pathways based on functional enrichment analysis. CIBERSORT analysis and TIMER2.0 show a positive link between TTC7B and multiple immune cells, particularly macrophages. Pearson's analysis reveals a significant correlation between TTC7B and ferroptosis-related genes.ConclusionIn all, TTC7B could serve as a promising prognostic indicator of HNSCC, and is closely associated with focal adhesions, immune infiltration, and ferroptosis.
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