Dysregulated Immunological Functionome and Dysfunctional Metabolic Pathway Recognized for the Pathogenesis of Borderline Ovarian Tumors by Integrative Polygenic Analytics.

Chia-Ming Chang,Yao-Feng Li,Kai-Hsi Lu,Kuo-Min Su,Li-Chun Liu,Cheng-Chang Chang,Hsin-Chung Lin,Tzu-Wei Lin

doi:10.3390/ijms22084105

Abstract

The pathogenesis and molecular mechanisms of ovarian low malignant potential (LMP) tumors or borderline ovarian tumors (BOTs) have not been fully elucidated to date. Surgery remains the cornerstone of treatment for this disease, and diagnosis is mainly made by histopathology to date. However, there is no integrated analysis investigating the tumorigenesis of BOTs with open experimental data. Therefore, we first utilized a functionome-based speculative model from the aggregated obtainable datasets to explore the expression profiling data among all BOTs and two major subtypes of BOTs, serous BOTs (SBOTs) and mucinous BOTs (MBOTs), by analyzing the functional regularity patterns and clustering the separate gene sets. We next prospected and assembled the association between these targeted biomolecular functions and their related genes. Our research found that BOTs can be accurately recognized by gene expression profiles by means of integrative polygenic analytics among all BOTs, SBOTs, and MBOTs; the results exhibited the top 41 common dysregulated biomolecular functions, which were sorted into four major categories: immune and inflammatory response-related functions, cell membrane- and transporter-related functions, cell cycle- and signaling-related functions, and cell metabolism-related functions, which were the key elements involved in its pathogenesis. In contrast to previous research, we identified 19 representative genes from the above classified categories (IL6, CCR2 for immune and inflammatory response-related functions; IFNG, ATP1B1, GAS6, and PSEN1 for cell membrane- and transporter-related functions; CTNNB1, GATA3, and IL1B for cell cycle- and signaling-related functions; and AKT1, SIRT1, IL4, PDGFB, MAPK3, SRC, TWIST1, TGFB1, ADIPOQ, and PPARGC1A for cell metabolism-related functions) that were relevant in the cause and development of BOTs. We also noticed that a dysfunctional pathway of galactose catabolism had taken place among all BOTs, SBOTs, and MBOTs from the analyzed gene set databases of canonical pathways. With the help of immunostaining, we verified significantly higher performance of interleukin 6 (IL6) and galactose-1-phosphate uridylyltransferase (GALT) among BOTs than the controls. In conclusion, a bioinformatic platform of gene-set integrative molecular functionomes and biophysiological pathways was constructed in this study to interpret the complicated pathogenic pathways of BOTs, and these important findings demonstrated the dysregulated immunological functionome and dysfunctional metabolic pathway as potential roles during the tumorigenesis of BOTs and may be helpful for the diagnosis and therapy of BOTs in the future.

Highlights

Ovarian low malignancy potential (LMP) tumors, or borderline ovarian tumors (BOTs), are a unique subtype of epithelial ovarian cancers (EOCs) that are the leading cause of death of gynecologic cancers and the fifth leading cause of all cancer-related deaths among women
The variation in the gene set regularity (GSR) indices between each BOT group consisting of all BOTs, serous BOTs (SBOTs), and MBPTs and normal controls indicated that the biomolecular functions were widely dysregulated in the BOT groups compared with the normal controls with statistical significance
With the assistance of machine learning, we applied a genome-wide expression profile to evaluate the various global functionomes and related pathogenic pathways of all BOTs, SBOTs, and mucinous BOTs (MBOTs) compared with controls and first found that there were obvious deviations in terms of the GSR index between all case samples and the control group, especially the MBOT subtype

Summary

Introduction

Ovarian low malignancy potential (LMP) tumors, or borderline ovarian tumors (BOTs), are a unique subtype of epithelial ovarian cancers (EOCs) that are the leading cause of death of gynecologic cancers and the fifth leading cause of all cancer-related deaths among women. The BOT accounts for approximately 10~15% of EOCs and usually occurs in younger women compared with generally common high-grade serous ovarian, tubal, and peritoneal cancers with a stepwise manner of progression from precursor lesions to invasive disease [5,6]. Clear evidence has shown that the BOT does have intercalary biologic, histologic, pathogenetic, and molecular features intermediate between clearly benign and frankly malignant ovarian neoplasms, and BOTs are classified into serous borderline ovarian tumors (SBOTs), mucinous borderline ovarian tumors (MBOTs), seromucinous borderline tumors, endometrial borderline tumors, clear cell borderline tumors, transitional (Brenner) and other subtypes on the basis of histogenesis and histopathology in light of the recent 2014 WHO classification of tumors of female genital organs [4]. SBOTs, approximately 65% of BOTs [7], occur mostly in

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