Cervical Cancer Stem-Like Cell Transcriptome Profiles Predict Response to Chemoradiotherapy.

Luciana W Zuccherato,Rodrigo Drummond,Andrea Teixeira-Carvalho,Kenneth J Gollob,Telma M R F Franco,Israel Tojal Da Silva,Sálua O C Paula,Christina M T Machado,Paulo Guilherme O Salles,Patrícia R Martins,Letícia C Braga,Wagner C S Magalhães,Olindo A Martins-Filho,Larissa S Campos

doi:10.3389/fonc.2021.639339

Abstract

Cervical cancer (CC) represents a major global health issue, particularly impacting women from resource constrained regions worldwide. Treatment refractoriness to standard chemoradiotheraphy has identified cancer stem cells as critical coordinators behind the biological mechanisms of resistance, contributing to CC recurrence. In this work, we evaluated differential gene expression in cervical cancer stem-like cells (CCSC) as biomarkers related to intrinsic chemoradioresistance in CC. A total of 31 patients with locally advanced CC and referred to Mário Penna Institute (Belo Horizonte, Brazil) from August 2017 to May 2018 were recruited for the study. Fluorescence-activated cell sorting was used to enrich CD34+/CD45- CCSC from tumor biopsies. Transcriptome was performed using ultra-low input RNA sequencing and differentially expressed genes (DEGs) using Log2 fold differences and adjusted p-value < 0.05 were determined. The analysis returned 1050 DEGs when comparing the Non-Responder (NR) (n=10) and Responder (R) (n=21) groups to chemoradiotherapy. These included a wide-ranging pattern of underexpressed coding genes in the NR vs. R patients and a panel of lncRNAs and miRNAs with implications for CC tumorigenesis. A panel of biomarkers was selected using the rank-based AUC (Area Under the ROC Curve) and pAUC (partial AUC) measurements for diagnostic sensitivity and specificity. Genes overlapping between the 21 highest AUC and pAUC loci revealed seven genes with a strong capacity for identifying NR vs. R patients (ILF2, RBM22P2, ACO16722.1, AL360175.1 and AC092354.1), of which four also returned significant survival Hazard Ratios. This study identifies DEG signatures that provide potential biomarkers in CC prognosis and treatment outcome, as well as identifies potential alternative targets for cancer therapy.

Highlights

Cervical Cancer (CC) is the second most frequent cancer and the fourth leading cause of cancer deaths in women worldwide
Given the importance of cancer stem cell (CSC) in the tumorigenic process of solid tumors, we aimed to study differential expressed genes (DEG) in cervical cancer stem-like cells (CCSC) from tumor biopsies taken before treatment began in a cohort of CC
Based on the 1050 DEGs from the comparison between NR and R CCSC, we evaluated the prediction performance based on the partial area under the Receiver operating characteristic curve (ROC) curve statistic

Summary

Introduction

Cervical Cancer (CC) is the second most frequent cancer and the fourth leading cause of cancer deaths in women worldwide. The Global Cancer Observatory (GLOBOCAN) estimates the burden of CC incidence in 2018 reached almost 570,000 women and a mortality rate of 54.6% (311,365 patients). 85% of cases occur in low- and middle-income countries (LMICs), and are predominantly diagnosed in advanced stages [1]. Despite the scientific advances in primary and secondary prevention (vaccine, HPV screening and precancerous lesions treatment, respectively), CC continues to be a major global health challenge. Around 50% of patients with CC died as a consequence of treatment failure and other cancer- related complications. This dismal scenario is reflected in South American patients [2], and highlights the importance of developing novel therapeutic approaches for CC and achieving a more personalized medical care

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