Linking tumor immune infiltrate and systemic immune mediators to treatment response and prognosis in advanced cervical cancer.

Cervical cancer (CC) poses a significant burden on individuals in developing regions, exhibiting heterogeneous responses to standard chemoradiation therapy, and contributing to substantial mortality rates. Unraveling host immune dynamics holds promise for innovative therapies and discovery of clinically relevant biomarkers. We studied prospectively locally advanced CC patients pre-treatment, stratifying them as responders (R) or non-responders (NR). R patients had increased tumor-infiltrating lymphocytes (TILs), while NR patients showed elevated PD-1 scores, CD8+ and PD-L2+ TILs, and PD-L1 immune reactivity. NR patients exhibited higher systemic soluble mediators correlating with TIL immune markers. R patients demonstrated functional polarization of CD4 T cells (Th1, Th2, Th17, and Treg), while CD8+ T cells and CD68+ macrophages predominated in the NR group. Receiver operating characteristic analysis identified potential CC response predictors, including PD-L1-immunoreactive (IR) area, PD-L2, CD8, FGF-basic, IL-7, IL-8, IL-12p40, IL-15, and TNF-alpha. Dysfunctional TILs and imbalanced immune mediators contribute to therapeutic insufficiency, shedding light on local and systemic immune interplay. Our study informs immunological signatures for treatment prediction and CC prognosis.

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 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.