U.S. flag

An official website of the United States government

Display Settings:

Format

Send to:

Choose Destination
Accession: PRJNA705088 ID: 705088

Cervical cancer stem-like cell transcriptome profiles predict response to chemoradiotherapy

Cervical cancer (CC) represents a major global health issue, particularly impacting women from resource constrained regions worldwide. Treatment refractoriness to standard chemo-radiotherapy 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 Mario Penna Institute (Belo Horizonte, Brazil) from August 2017 to May 2018 were recruited for the study. Fluorescence-activated cell sorting (FACS) 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. 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. The analysis showed 1062 DEGs comparing between the Non-Responder (n=10) and Responder (n=21) groups to chemoradiotherapy. Overlapping of the 20 highest AUC and pAUC values revealed five transcripts potentially implicated in innate chemoresistance (ILF2, SNX2, COPZ1, AC016722.1 and AL360175.1). This study identifies DEG signatures that serve as potential biomarkers in CC prognosis and treatment outcome, as well as identifies potential alternative targets for cancer therapy.
AccessionPRJNA705088
Data TypeRaw sequence reads
ScopeMultispecies
Publications
  • Published online: Zuccherato L et al., "Cervical Cancer Stem-Like Cell Transcriptome Profiles Predict Response to Chemoradiotherapy", Frontiers in Oncology, 2021;11
Grants
  • "PRONON" (Grant ID 25000.159953/2014-2018, Ministerio da saude)
SubmissionRegistration date: 26-Feb-2021
Instituto Mario Penna
RelevanceMedical
Project Data:
Resource NameNumber
of Links
Sequence data
SRA Experiments31
Other datasets
BioSample31
SRA Data Details
ParameterValue
Data volume, Gbases103
Data volume, Mbytes41809

Supplemental Content

Recent activity

Your browsing activity is empty.

Activity recording is turned off.

Turn recording back on

See more...
Support Center