Immune Pathways with Aging Characteristics Improve Immunotherapy Benefits and Drug Prediction in Human Cancer.
Xinyue WangShuang GuoHanxiao ZhouYue SunJing GanYakun ZhangWen ZhengCaiyu ZhangXiaoxi ZhaoJiebin XiaoLi WangYue GaoShang-Wei NingPublished in: Cancers (2023)
(1) Background: Perturbation of immune-related pathways can make substantial contributions to cancer. However, whether and how the aging process affects immune-related pathways during tumorigenesis remains largely unexplored. (2) Methods: Here, we comprehensively investigated the immune-related genes and pathways among 25 cancer types using genomic and transcriptomic data. (3) Results: We identified several pathways that showed aging-related characteristics in various cancers, further validated by conventional aging-related gene sets. Genomic analysis revealed high mutation burdens in cytokines and cytokines receptors pathways, which were strongly correlated with aging in diverse cancers. Moreover, immune-related pathways were found to be favorable prognostic factors in melanoma. Furthermore, the expression level of these pathways had close associations with patient response to immune checkpoint blockade therapy in melanoma and non-small cell lung cancer. Applying a net-work-based method, we predicted immune- and aging-related genes in pan-cancer and utilized these genes for potential immunotherapy drug discovery. Mapping drug target data to our top-ranked genes identified potential drug targets, FYN, JUN, and SRC. (4) Conclusions: Taken together, our systematic study helped interpret the associations among immune-related pathways, aging, and cancer and could serve as a resource for promoting clinical treatment.
Keyphrases
- papillary thyroid
- squamous cell
- prognostic factors
- lymph node metastasis
- emergency department
- childhood cancer
- high resolution
- squamous cell carcinoma
- dna methylation
- machine learning
- drug discovery
- electronic health record
- mesenchymal stem cells
- young adults
- drug induced
- bone marrow
- risk assessment
- big data
- single cell
- artificial intelligence
- case report
- deep learning
- climate change
- tyrosine kinase
- human health