Analysis of Nuclear Encoded Mitochondrial Gene Networks in Cervical Cancer.

Cecile Meneur,Sandeep Mallya,Sanjiban Chakrabarty,Nadeem G,Sriharikrishnaa S,Sangavi Eswaran,Shama Prasada Kabekkodu,Divya Adiga

doi:10.31557/apjcp.2021.22.6.1799

Abstract

Background:Cervical cancer (CC) is one of the most common female cancers in many developing and underdeveloped countries. High incidence, late presentation, and mortality suggested the need for molecular markers. Mitochondrial defects due to abnormal expression of nuclear-encoded mitochondrial genes (NEMG) have been reported during cancer progression. Nevertheless, the application of NEMG for the prognosis of CC is still elusive. Herein, we aimed to investigate the associations between NEMG and CC prognosis. Materials and Methods:The differentially expressed genes (DEG) in the TCGA-CESC dataset and NEMGs were retrieved from TACCO and Mitocarta2.0 databases, respectively. The impact of methylation on NEMG expression were predicted using DNMIVD and UALCAN tools. HCMDB tool was used to predict genes having metastatic potential. The prognostic models were constructed using DNMIVD, TACCO, GEPIA2, and SurvExpress. The functional enrichment analysis (FEA) was performed using clusterProfiler. The protein-protein interaction network (PPIN) was constructed to identify the hub genes (HG) using String and CytoHubba tools. Independent validation of the HG was performed using Oncomine and Human Protein Atlas databases. The druggable genes were predicted using DGIdb.Results:Among the 52 differentially expressed NEMG, 15 were regulated by DNA methylation. The expression level of 16, 10, and 7 has the potential for CC staging, prediction of metastasis, and prognosis. Moreover, 1 driver gene and 16 druggable genes were also identified. The FEA identified the enrichment of cancer-related pathways, including AMPK and carbon metabolism in cancer. The combined expression of 10 HG has been shown to affect patient survival. Conclusion:Our findings suggest that the abnormal expression of NEMGs may play a critical role in CC development and progression. The genes identified in our study may serve as a prognostic indicator and therapeutic target in CC.

Highlights

Cervical cancer (CC) is a significant public health problem affecting women in countries with low resource settings
Materials and Methods: The differentially expressed genes (DEG) in the TCGA-CESC dataset and nuclear-encoded mitochondrial genes (NEMG) were retrieved from Transcriptome Alterations in Cancer Omnibus (TACCO) and Mitocarta2.0 databases, respectively
We have identified the DEGs in the TCGA-CESC data set using the “select DEGs” function with cut-off criteria of adjusted p-value < 0.05 and expression value log 2-fold change of +2 and -2 between tumor and normal tissue samples

Summary

Introduction

Cervical cancer (CC) is a significant public health problem affecting women in countries with low resource settings. CC with advanced stage shows recurrence and therapy resistance and most patients succumb within three years (Canfell et al, 2020; Charakorn et al, 2018) This suggests the need for biomarkers to identify the patients with poor prognosis at an early stage for intensified treatment for improved patient care. In this direction, identifying the molecular markers and associated networks may be useful. Materials and Methods: The differentially expressed genes (DEG) in the TCGA-CESC dataset and NEMGs were retrieved from TACCO and Mitocarta2.0 databases, respectively. The druggable genes were predicted using DGIdb. Results: Among the 52 differentially expressed NEMG, 15 were regulated by DNA methylation.

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