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

Overview

Journal J Inflamm Res

Publisher Dove Medical Press

Date 2024 Dec 10

PMID 39654864

Authors

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

Affiliations

Soon will be listed here.

Abstract

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.

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