LASSO and Bioinformatics Analysis in the Identification of Key Genes for Prognostic Genes of Gynecologic Cancer.

Shao-Hua Yu,Yu-Ting Chung,Jia-Hua Cai,Szu-Han Liao,Jeffrey J P Tsai,Yi-Zhen Lin,Charles C N Wang,De-Lun Chen

doi:10.3390/jpm11111177

Abstract

The aim of this study is to identify potential biomarkers for early diagnosis of gynecologic cancer in order to improve survival. Cervical cancer (CC) and endometrial cancer (EC) are the most common malignant tumors of gynecologic cancer among women in the world. As the underlying molecular mechanisms in both cervical and endometrial cancer remain unclear, a comprehensive and systematic bioinformatics analysis is required. In our study, gene expression profiles of GSE9750, GES7803, GES63514, GES17025, GES115810, and GES36389 downloaded from Gene Expression Omnibus (GEO) were utilized to analyze differential gene expression between cancer and normal tissues. A total of 78 differentially expressed genes (DEGs) common to CC and EC were identified to perform the functional enrichment analyses, including gene ontology and pathway analysis. KEGG pathway analysis of 78 DEGs indicated that three main types of pathway participate in the mechanism of gynecologic cancer such as drug metabolism, signal transduction, and tumorigenesis and development. Furthermore, 20 diagnostic signatures were confirmed using the least absolute shrink and selection operator (LASSO) regression with 10-fold cross validation. Finally, we used the GEPIA2 online tool to verify the expression of 20 genes selected by the LASSO regression model. Among them, the expression of PAMR1 and SLC24A3 in tumor tissues was downregulated significantly compared to the normal tissue, and found to be statistically significant in survival rates between the CC and EC of patients (p < 0.05). The two genes have their function: (1.) PAMR1 is a tumor suppressor gene, and many studies have proven that overexpression of the gene markedly suppresses cell growth, especially in breast cancer and polycystic ovary syndrome; (2.) SLC24A3 is a sodium–calcium regulator of cells, and high SLC24A3 levels are associated with poor prognosis. In our study, the gene signatures can be used to predict CC and EC prognosis, which could provide novel clinical evidence to serve as a potential biomarker for future diagnosis and treatment.

Highlights

Gynecologic cancer is a type of malignant tumor that begins in the female reproductive system
78 differentially expressed genes (DEGs) were identified in gynecologic cancer
The least absolute shrink and selection operator (LASSO) regression model and survival analysis further suggested that two hub genes (PAMR1 and SLC24A3) could serve as potential biomarkers for the treatment or diagnosis of cervical and endometrial cancers

Summary

Introduction

Gynecologic cancer is a type of malignant tumor that begins in the female reproductive system. Of all the gynecologic cancers, cervical cancer (CC) and endometrial cancer (EC) are the most common tumors of the female genital tract in the world, followed by ovarian cancer [1]. Numerous studies have demonstrated that abnormally expressed tumor markers may be involved in cancer initiation and progression, such as p16INKa/ki-67, E6/E7, PTEN, and ANXA2 [2–6]. Despite large efforts to develop novel biomarkers, cervical and endometrial cancers continue to be a serious health problem among women [7,8]. Patients with early stage (or locally advanced) CC and EC have access to a standard treatment comprising a combination of surgery, radiotherapy, and chemotherapy [9–11]. Precise biomarkers and targeted therapy for CC and EC remain limited [12–14]

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