Background: Bladder cancer (BLCA) is a common malignancy from urinary tract. Although the diagnosis and treatment of bladder cancer has made great progress in the past few decades, the effects of existing treatment methods are still limited. Therefore, it is still necessary to develop new methods to assist in the disease management and treatment. Tumor antigens are tumor-specific surface molecules and are generally considered to be the main components of a typical cancer vaccine, which could initiate and active immune cells to recognize and eliminate cancer cells. In the context of the COVID-19 pandemic, mRNA vaccines have re-entered people's vision. Methods: The genomic and clinical data of 411 BLCA and 19 normal tissues were acquired from The Cancer Genome Atlas (TCGA) and GSE13507 cohorts. Differential expression genes and mutation analysis were performed to screen out potential antigens, Kaplan-Meier curves were carried out to investigate the correlation between the level of potential antigens and OS of patients. Immuno-phenotyping of 411 tumor samples was based on the single-sample gene sets enrichment analysis (ssGSEA). The tumor immune microenvironment characteristics was explored in each immune subtype. Weighted gene co-expression network analysis (WGCNA) was used to clusterimmune-related genes and screen the hub genes, and pathway enrichment analyses were performed on the hub modules related to immune subtypes in the WGCNA.Results: Through genetic and transcriptional analysis on TCGA and GSE13507 datasets, we have identified 6 genes as potential candidate genes for BLCA specific tumor antigens. We also identified 3 immune subtypes of BLCA, which displayed distinct clinical, molecular and immune-related characteristics. In addition, we have constructed immune landscape to identify the immune cell components of each BLCA patient, which could predict clinical outcome of the patients, and assist in the development of personalized mRNA vaccines. Conclusions: our findings indicated that 6 genes such as PTPN6 may be potential tumor antigens, and provide a reliable reference for the further development and management of cancer vaccines.
Background Autophagy degraded and recycled cytoplasmic components to maintain cellular homeostasis under stress conditions, which was recognized as double-edged sword in oncogenesis and novel target in cancer treatment. However, comprehensive analysis of the relationship between autophagy regulation and immunity has not been reported yet. Methods Unsupervised consensus clustering algorithm was used to identify autophagy regulation patterns. LASSO cox regression algorithm was used to build a scoring system (ATGscore) to represent the individual autophagy regulation pattern. Then integrated analysis of autophagy regulation patterns and ATGscore was performed. Results We have successful depicted five autophagy regulation patterns and established a scoring system (ATGscore) to represent it, which was shown to be significantly correlated with TIME infiltration, immune phenotypes, molecular subtypes, and genetic variation, etc. in 1165 head and neck squamous cell carcinoma (HNSCC) patients. Moreover, ATGscore was an independent prognostic factor and potent predictor for clinical response to immune-checkpoint inhibitors (ICIs) targeting immunotherapy. Conclusions Understanding the molecular characteristics of autophagy regulation patterns in HNSCC could help us to depict the underlying mechanism of tumour immunity and lay a solid foundation on combination of autophagy targeting therapies and immunotherapies for clinical application in HNSCC.
Both the absence of autophagy and excessive autophagy is double-edged sword in tumorigenesis. Due to the specificity of autophagy, its role in head and neck squamous cell carcinoma (HNSCC) is still unclear. In this study, we established five autophagy-related patterns in 1165 HNSCC patients with distinct cellular and molecular characteristics. Additionally, we developed a new scoring system (ATPscore) based on the differentially expressed genes (DEGs) among these five patterns, to represent the individual autophagy regulation pattern. ATPscore was shown to be significantly correlated with tumor immune microenvironment (TIME) infiltration, immune phenotypes, molecular subtypes, and genetic variations. We further found that ATPscore was both an independent prognostic factor and a potent predictor of clinical response to immune-checkpoint inhibitors (ICIs) based immunotherapy. We further verified the value of key gene SRPX in ATPscore in HNSCC cell lines with the in-depth research of ATPscore and found that it is closely related to immune subtypes, molecular subtypes, and immune activation-related markers. Our research could help us to understand the underlying mechanisms of tumor immunity and provide a solid foundation for combination of autophagy-targeted therapies with immunotherapies for clinical application in HNSCC.
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