Identification of lipid metabolism-related genes as prognostic indicators in papillary thyroid cancer

Author:

Wen Shishuai12,Luo Yi12,Wu Weili3,Zhang Tingting12ORCID,Yang Yichen12,Ji Qinghai12,Wu Yijun4,Shi Rongliang12,Ma Ben12,Xu Midie5ORCID,Qu Ning12

Affiliation:

1. Department of Head and Neck Surgery, Fudan University Shanghai Cancer Center, Shanghai 200032, China

2. Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China

3. Department of Surgical Oncology, Third Affiliated Hospital of Wenzhou Medical University, Wenzhou 325200, China

4. Department of Thyroid Surgery, Zhejiang University, School of Medicine, The First Affiliated Hospital, Hangzhou 310003, China

5. Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai 200032, China

Abstract

Abstract Lipid metabolism plays important roles not only in the structural basis and energy supply of healthy cells but also in the oncogenesis and progression of cancers. In this study, we investigated the prognostic value of lipid metabolism-related genes in papillary thyroid cancer (PTC). The recurrence predictive gene signature was developed and internally and externally validated based on PTC datasets including The Cancer Genome Atlas (TCGA) and GSE33630 datasets. Univariate, LASSO, and multivariate Cox regression analysis were applied to assess prognostic genes and build the prognostic gene signature. The expression profiles of prognostic genes were further determined by immunohistochemistry of tissue microarray using in-house cohorts, which enrolled 97 patients. Kaplan–Meier curve, time-dependent receiver operating characteristic curve, nomogram, and decision curve analyses were used to assess the performance of the gene signature. We identified four recurrence-related genes, PDZK1IP1, TMC3, LRP2 and KCNJ13, and established a four-gene signature recurrence risk model. The expression profiles of the four genes in the TCGA and in-house cohort indicated that stage T1/T2 PTC and locally advanced PTC exhibit notable associations not only with clinicopathological parameters but also with recurrence. Calibration analysis plots indicate the excellent predictive performance of the prognostic nomogram constructed based on the gene signature. Single-sample gene set enrichment analysis showed that high-risk cases exhibit changes in several important tumorigenesis-related pathways, such as the intestinal immune network and the p53 and Hedgehog signaling pathways. Our results indicate that lipid metabolism-related gene profiling represents a potential marker for prognosis and treatment decisions for PTC patients.

Funder

Zhejiang Basic Public Interest Research Project

National Natural Science Foundation of China

Publisher

China Science Publishing & Media Ltd.

Subject

General Medicine,Biochemistry,Biophysics

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3