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A Molecular Signature of the Ubiquitin-Proteasome System for Forecasting Prognosis in Thyroid Carcinoma Patients

基因 肿瘤微环境 生物 计算生物学 肿瘤科 蛋白酶体 免疫系统 生物信息学 癌症研究 内科学 医学 免疫学 遗传学
作者
Hong Zeng,Xitong Geng,Hao Wan,Xiaoyu Qu,Shengwei Tang,Ruiyu Zhang,Minqin Zhou,Zichuan Yu,Jingying Pan,Hao Zheng,Yanting Zhu,Shuhan Huang,Da Huang
出处
期刊:Journal of Inflammation Research [Dove Medical Press]
卷期号:Volume 17: 10397-10419
标识
DOI:10.2147/jir.s499820
摘要

Background: The ubiquitin-proteasome system (UPS) is vital for protein quality control and its dysregulation is linked to diseases, including cancer. Targeting the UPS is becoming a promising approach in cancer therapy. However, the role of UPS modulation in thyroid carcinoma (THCA) remains to be fully elucidated. Methods: Initially, we utilized data from The Cancer Genome Atlas (TCGA) database to employ weighted gene co-expression network analysis (WGCNA) with LASSO regression to develop a prognostic model for core UPS genes implicated in THCA. Subsequently, we stratified the THCA training set into two distinct subtypes based on ubiquitin-proteasome system prognostic model score (UPS-PMS) characteristics. Key genes within the model were then subjected to functional analysis, immunotherapy evaluation, and drug sensitivity studies. Results: We delineated a prognostic model of the UPS comprising six genes, which we subsequently demonstrated was capable of forecasting patient prognosis. Moreover, our findings indicated a substantial correlation between UPS-PMS and immune microenvironmental factors, notably a negative correlation with myeloid immune cells and a potential influence on the Th1 to Th2 cells ratio. Especially, we observed a significant association between high UPS-PMS and an immunosuppressive microenvironment. Then, we elucidated the biological distinctions among various THCA sample subtypes, highlighting that the cluster_1 subtype is associated with an unfavorable prognosis. Of note, KCNA1 was identified as a pivotal prognostic gene within the UPS-PMS framework. We constructed a three-tiered regulatory network centered on KCNA1-related competing endogenous RNA (ceRNA). Furthermore, our results suggested that KCNA1 has potential as a target for immunotherapeutic strategies. Concurrently, drug sensitivity analyses demonstrated that high KCNA1 expression promoted gemcitabine resistance in patients, while KCNA1 knockdown increased sensitivity to gemcitabine. Conclusion: In conclusion, we developed a novel UPS-based prognostic model for THCA, identified key gene KCNA1, and assessed immunotherapy and drug sensitivity, revealing new therapeutic targets. Keywords: ubiquitin-proteasome system, thyroid carcinoma, prognostic model, immune microenvironment, drug sensitivity

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