Analysis of Prognostic Alternative Splicing Reveals the Landscape of Immune Microenvironment in Thyroid Cancer

Jian Wu; Yifang Sun; Junzheng Li; Maomao Ai; Lihua You; Jianbo Shi; Feng Yu

doi:10.3389/fonc.2021.763886

Analysis of Prognostic Alternative Splicing Reveals the Landscape of Immune Microenvironment in Thyroid Cancer

Front Oncol. 2021 Oct 18:11:763886. doi: 10.3389/fonc.2021.763886. eCollection 2021.

Authors

Jian Wu¹, Yifang Sun², Junzheng Li¹, Maomao Ai¹, Lihua You¹, Jianbo Shi^{1

3}, Feng Yu¹

Affiliations

¹ Department of Otorhinolaryngology-Head and Neck Surgery, Guangzhou Red Cross Hospital, Jinan University, Guangzhou, China.
² Department of Ophthalmology, Guangzhou Red Cross Hospital, Jinan University, Guangzhou, China.
³ Department of Otorhinolaryngology, The First Affiliated Hospital of Sun Yat-Sen University, Sun Yat-Sen University, Guangzhou, China.

Abstract

Background: The incidence of thyroid cancer (THCA) continues to increase in recent decades. Accumulating evidence showed that the unbalanced alternative splicing (AS) promotes the occurrence of cancers and leads to poor prognosis of patients. However, the research on alternative splicing events in THCA is lacking, and its underlying mechanism is not fully understood. This study identifies a novel prognostic signature based on AS events to reveal the relationship of AS with tumor immune microenvironment.

Methods: Based on the AS data, transcriptional data, and clinical information, the differentially expressed alternative splicings (DEASs) were screened out. Least absolute shrinkage and selection operator (LASSO) regression and multi-Cox regression analyses were employed to identify prognostic results related to AS events and establish a prognostic signature. The predictive ability of the signature was assessed by Kaplan-Meier (K-M) survival curve, risk plots, and receiver operating characteristic (ROC) curves. Furthermore, correlations between tumor-infiltrating immune cells, immune checkpoints, immune score and prognostic signature were analyzed.

Results: According to the LASSO regression analysis, a total of five AS events were selected to construct the signature. K-M survival curve showed that the higher the risk score, the worse the OS of the patients. Risk plots further confirmed this result. ROC curves indicated the high predictive efficiency of the prognostic signature. As for tumor immune microenvironment, patients in the high-risk group had a higher proportion of immune cells, including plasma cell, CD8+ T cell, macrophages (M0 and M2), and activated dendritic cell. Immune checkpoint proteins, such as PDCD1LG2, HAVCR2, CD274, etc., were significantly higher in the high-risk group. We also found that the ESTIMATE score, stromal score, and immune score were lower in the high-risk group, while the result of tumor purity was the opposite.

Conclusions: Collectively, a prognostic signature consisting of five AS events in THCA was established. Furthermore, there was an inextricable correlation between immune cell infiltration, immune checkpoint proteins, and AS events. This study will provide a basis for THCA immunotherapy in the future.

Keywords: alternative splicing; immune checkpoint (ICP); immune microenvironment; immunotherapy; thyroid cancer.