Research Paper|Volume 12, Issue 18|pp 18163—18180

Bioinformatics analysis of the clinical value and potential mechanisms of AHNAK2 in papillary thyroid carcinoma

Zhenyu Xie¹, Yu Lun¹, Xin Li¹, Yuzhen He¹, Song Wu¹, Shiyue Wang¹, Jianjian Sun¹, Yuchen He¹, Jian Zhang¹

¹Department of Vascular and Thyroid Surgery, The First Hospital, China Medical University, Shenyang, China

Received: February 25, 2020Accepted: June 22, 2020Published: September 23, 2020

Copyright: © 2020 Xie et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Background: AHNAK2 has been recently reported as a biomarker in many cancers. However, a systematic investigation of AHNAK2 in papillary thyroid carcinoma (PTC) has not been conducted.

Results: AHNAK2 is overexpressed in PTC tissues and could be an independent prognostic factor. AHNAK2 expression was significantly high in patients with advanced stage, advanced T classification, lymph node metastasis, increased BRAF mutations and decreased RAS mutations. Cell adhesion-, cell junction-, and immune-related pathways were the most frequently noted in gene set enrichment analysis. AHNAK2 expression in PTC was positively correlated with immune infiltration and negatively correlated with AHNAK2 methylation. AHNAK2 expression was significantly positively correlated with tumor progression and poor overall survival (OS) in pan-cancer patients.

Conclusions: AHNAK2 is a good biomarker for the diagnosis and prognosis of PTC. AHNAK2 may promote thyroid cancer progression through cell adhesion-, cell junction-, and immune-related pathways. Methylation may act as an upstream regulator to inhibit the expression and biological function of AHNAK2. Additionally, AHNAK2 has broad prognostic value in pan-cancer.

Methods: Based on The Cancer Genome Atlas (TCGA) data, we screened AHNAK2-related genes through weighted gene coexpression network analysis and explored the clinical value and the potential mechanism of AHNAK2 in PTC by multiomics analysis.