Letícia da Conceição Braga

Ovarian cancer cell heterogeneity and paclitaxel response in vitro 2D and 3D cancer cell models and xenograft growth in the chicken chorioallantoic membrane (CAM)

Among gynecological malignancies, epithelial ovarian cancer (EOC) is the most lethal, comprising a heterogeneous group of diseases. Paclitaxel is a standard chemotherapeutic agent and an important option for EOC treatment. However, chemotherapy often fails, contributing to a high rate of EOC recurrence. One of the models that best explains the cellular heterogeneity, disease aggressiveness, chemoresistance, recurrence risk, and metastasis observed in ovarian tumors is the presence of cancer stem cells (CSCs). This study aimed to assess the phenotypic changes in three EOC cell lines (TOV-21G, SKOV-3, and OV-90) cultured in monolayer (MN) and tumorsphere (CSCs enrichment-TS) models. After treatment with paclitaxel, we studied different cell subpopulations by immunophenotyping using CSC markers (CD44/CD24) and mesenchymal markers (CD117/CD146). The relative expression of mRNAs (CASP8, TNFRSF10B, TP53, and BCL2) and miRNAs (miR-26a, miR-125b-5p, miR-181c, miR-17-5p, and miR-221) was evaluated by qPCR. In addition, we assessed the growth capacity of residual cells treated with paclitaxel using the chorioallantoic membrane (CAM) model to study disease relapse. After paclitaxel exposure, OV-90 TS and TOV-21G TS cells showed an increase in cell growth ability, while SKOV-3 MN cells maintained colony formation capability. SKOV-3 MN cells were enriched in the CSC-like subset (CD24

The OvarianTag™ Biomarker Panel Emerges as a Prognostic Tool to Guide Clinical Decisions in Cisplatin-Based Treatment of Epithelial Ovarian Cancer

Epithelial ovarian cancer (EOC) is the most lethal gynecologic malignancy, often diagnosed at an advanced stage due to its asymptomatic progression. The high recurrence rate and development of platinum-based chemotherapy resistance contribute to its poor prognosis. Despite advancements in molecular profiling, predictive biomarkers for chemotherapy response and recurrence risk remain limited. In this study, we developed OvarianTag™, a biomarker panel integrating apoptosis and necroptosis pathways, to predict chemotherapy benefit and disease progression in EOC patients. This observational study was conducted in two phases. In the first phase, 45 patients were recruited, and RNA was extracted from fresh ovarian tissues (normal, benign, and malignant). qRT-PCR was performed to assess the relative expression of genes involved in apoptosis and necroptosis-regulated cell death pathways. Machine learning algorithms were applied to identify the relevant prognostic markers, leading to the development of OvarianTag™. In the second phase, 55 additional EOC patients were included, and their formalin-fixed, paraffin-embedded (FFPE) tumor samples were analyzed using qRT-PCR. The classifier algorithm incorporated hierarchical clustering to stratify patients based on gene expression profiles. Significant differences in TNFRSF10C/TRAIL-R3, TNFRSF10B/TRAIL-R2, and CASP8 expression levels were observed between patient groups. CASP8 downregulation was strongly correlated with platinum resistance and a poor prognosis. Decision tree models achieved 83.3% accuracy in predicting platinum response and 79.2% accuracy in recurrence risk stratification. The OvarianTag™ classifier demonstrated high sensitivity and specificity in identifying high-risk patients, supporting its potential as a prognostic tool. The OvarianTag™ panel provides a novel approach for risk stratification in EOC, integrating apoptosis and necroptosis pathways to refine chemotherapy response prediction and recurrence risk assessment. This molecular assay has the potential to guide personalized treatment strategies, enhancing clinical decision-making and improving patient outcomes. Further validation in independent cohorts is warranted to establish its clinical utility.

Germline Mutations Landscape in a Cohort of the State of Minas Gerais, Brazil, in Patients Who Underwent Genetic Counseling for Gynecological and Breast Cancer

Abstract Objective The present study evaluated the profile of germline mutations present in patients who underwent genetic counseling for risk assessment for breast cancer (BC), ovarian cancer (OC), and endometrial cancer (EC) with a possible hereditary pattern. Methods Medical records of 382 patients who underwent genetic counseling after signing an informed consent form were analyzed. A total of 55.76% of patients (213/382) were symptomatic (personal history of cancer), and 44.24% (169/382) were asymptomatic (absence of the disease). The variables analyzed were age, sex, place of birth, personal or family history of BC, OC, EC, as well as other types of cancer associated with hereditary syndromes. The Human Genome Variation Society (HGVS) nomenclature guidelines were used to name the variants, and their biological significance was determined by comparing 11 databases. Results We identified 53 distinct mutations: 29 pathogenic variants, 13 variants of undetermined significance (VUS), and 11 benign. The most frequent mutations were BRCA1 c.470_471delCT, BRCA1 c.4675 + 1G > T, and BRCA2 c.2T> G. Furthermore, 21 variants appear to have been described for the first time in Brazil. In addition to BRCA1/2 mutations, variants in other genes related to hereditary syndromes that predispose to gynecological cancers were found. Conclusion This study allowed a deeper understanding of the main mutations identified in families in the state of Minas Gerais and demonstrates the need to assess the family history of non-gynecological cancer for risk assessment of BC, OC, and EC. Moreover, it is an effort that contributes to population studies to evaluate the cancer risk mutation profile in Brazil.

Apoptosis-related gene expression can predict the response of ovarian cancer cell lines to treatment with recombinant human TRAIL alone or combined with cisplatin

The objectives of this study were to determine the sensitivity of ovarian cancer (OC) cell lines (TOV-21G and SKOV-3) to cisplatin and to the recombinant human TRAIL (rhTRAIL), and to evaluate the expression profile of TNFRSF10B, TNFRSF10C, TP53TG5, MDM2, BAX, BCL-2 and CASPASE-8 genes and their participation in the resistance/susceptibility mechanism of these tumor cell lines. To determine the IC50 values associated with Cisplatin and rhTRAIL, inhibition of cell growth was observed using MTT assays in two human OC cell lines (SKOV-3 and TOV-21G). The analysis of gene expression was performed using quantitative real-time polymerase chain reaction (qRT-PCR). Both cell lines had different susceptibility profiles to the tested drugs. In the SKOV-3 cell line, the IC50 values for cisplatin and for rhTRAIL were 270.83 ug/mL and 196.5 ng/mL, respectively. The same concentrations were used for TOV-21G. Different gene expression profiles were observed in each tested cell line. CASPASE-8 and TNFRSF10B expression levels could predict the response of both the cell lines to rhTRAIL alone or the response to a combination of rhTRAIL and cisplatin. In addition, we observed a relationship between BCL-2 and BAX expression that may be helpful in estimating the proliferation rate of the OC cell lines. SKOV-3 and TOV-21G respond differently to cisplatin and rhTRAIL exposure, and expression of CASPASE-8 and TNFRSF10B are good predictors of responses to these treatments.

Membrane transporter genes predict chemoradiotherapy response in patients with cervical cancer

This study aimed to explore membrane transporter gene expression as a predictive biomarker of chemoradiotherapy response in cervical cancer. The differential expression of ATP1B3 and SLCO1B3 accurately classified patients as responders or non-responders with 90% accuracy, highlighting their potential for personalized treatment strategies. Two gene groups with contrasting expression profiles were identified. The ATP1B3 and SLCOB3 gene profiles classified patients with 90% accuracy. The ATP1B3 and SLCOB3 gene signature is a potential predictor of treatment response. Cervical cancer is the fourth most common cancer in women worldwide. Resistance to chemoradiotherapy in cervical cancer has been widely associated with membrane transport-related genes, particularly those encoding efflux transport proteins, such as the ATP-binding cassette family members (including P-glycoprotein), which act by expelling chemotherapeutic agents from tumor cells, as well as solute carrier proteins, whose expression impairs the uptake of antineoplastic drugs by cancer cells. This study aimed to identify specific membrane transport-related gene expression profiles as potential biomarkers for predicting chemoradiotherapy response in cervical cancer. Cervical biopsies were collected from 31 patients (21 responders and 10 non-responders) at Hospital Luxemburgo - Instituto Mário Penna. Fluorescence-activated cell sorting was used to separate non-stem cancer cells from cervical cancer biopsies. cDNA libraries from the 21 responders and 10 non-responders were sequenced using the Illumina platform. Expression analysis was performed using R and the DESeq2 package, with differentially expressed genes identified based on log fold change >1 or <-1 and padj ≤0.05. WEKA software and decision tree methods were used to analyze membrane transporters. The results revealed two major gene groups with contrasting differentially expressed genes profiles. The first group, comprising SLC35 and ATP13, was overexpressed in non-responders, while the second group, consisting of SLC25 and ATP6, was overexpressed in responders. Decision tree analysis revealed that ATP1B3 and SLCOB3 expression profiles accurately classified patients into responder and non-responder groups with 90% accuracy, indicating that ATP1B3 and SLCOB3 are potential predictors of chemoradiotherapy response. Our results strongly suggest the presence of a candidate gene signature comprising ATP1B3 and SLCO1B3 that holds predictive value for chemoradiotherapy response in cervical cancer.

Association of a CHEK2 somatic variant with tumor microenvironment calprotectin expression predicts platinum resistance in a small cohort of ovarian carcinoma

High-grade serous ovarian cancer (HGSOC) low overall survival rate is often attributed to platinum resistance. Recent studies suggest that the tumor associated-microenvironment (TME) is a determining factor in malignant tumor progression and DNA damage plays a crucial role in this process. Here, we sought to identify platinum resistance biomarkers associating the TME immune profile and the mutational landscape of the homologous repair pathway genes with the HGSOC patients prognosis and response to chemotherapy. Using a decision tree classifier approach, we found that platinum resistant (PR) patients were characterized by the presence of a novel deep intronic variant, the CHEK2 c.319+ 3943A &gt; T, and higher L1 expression (p =  0.016), (100% accuracy). Chek2 protein is an important component of DNA repair and L1, also known as calprotectin, is one component of the neutrophil extracellular traps (NETs) during inflammation, previously suggested as a key contributor to the metastatic process in HGSOC. Also, PD-L2 levels were significantly higher in PR patients positive for this CHEK2 variant (p =  0.048), underscoring the need to explore its potential therapeutic role for this cancer. Our results suggest an interplay between TME and DNA repair variants that results in a multifactorial nature of HGSOC resistance to platinum chemotherapy.

Validation of cervical cancer genetic signature in minimally invasive samples

Abstract Cervical cancer remains the leading cause of cancer death in 36 countries, and high-risk human papillomavirus types are responsible for most cases. Identifying strategies to make treatment more targeted and effective has become a priority. This study aims to validate a set of differentially expressed genes previously identified in cervical cancer stem cells as predictive biomarkers for response to chemoradiotherapy using minimally invasive samples. Additionally, it aims to elucidate the relationship between high-risk human papillomavirus infection and cervical cancer patients’ response to treatment. Gene expression for three differentially expressed genes (COPZ1, ILF2, and SNX2) was evaluated from 20 cervical cancer patients’ cervical cytology brushes. Unmapped reads from the same transcriptome were used to evaluate the presence of human papillomavirus in tumor tissue through qualitative screening of 13 high-risk human papillomavirus types. Our study did not clarify the relationship between high-risk human papillomavirus infection and the treatment response. However, we found downregulation of COPZ1 in patients who responded to treatment compared to non-responders, and ILF2 in patients with more advanced tumor stages. This suggests that COPZ1 and ILF2 expressions are potential cervical cancer prognostic biomarkers that can be assessed using samples commonly used in clinical practice.