EXPLORING CAUSAL RELATIONS BETWEEN ADVERSE REACTIONS AND PACLITAXEL AND CARBOPLATIN CHEMOTHERAPY IN PATIENTS WITH GYNECOLOGICAL TUMORS IN A BRAZILIAN POPULATION: A MENDELIAN RANDOMIZATION STUDY.

• Grant number: 25/01842-2
• Support Opportunities: Scholarships abroad - Research Internship - Doctorate
• Start date: September 01, 2025
• End date: August 31, 2026
• Field of knowledge: Health Sciences - Pharmacy
• Principal Investigator: Patricia Moriel
• Grantee: Nadine de Godoy Torso
• Supervisor: Marie Verbanck
• Host Institution: Faculdade de Ciências Médicas (FCM). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Institution abroad: Institut Curie, France
• Associated to the scholarship: 22/06532-3 - Assessment of possible associations of genetic polymorphisms with adverse reactions and survival in patients with gynecological tumors treated with paclitaxel and carboplatin, BP.DR

Abstract

Gynecological tumors represent a major global health issue, being among the most common and lethal cancers in women. Standard treatment for advanced stages involves chemotherapy with carboplatin and paclitaxel which, though effective, are associated with significant adverse drug reactions (ADRs). The interindividual variability in the incidence and severity of these ADRs may be partially explained by single-nucleotide polymorphisms (SNPs) influencing the pharmacokinetics and pharmacodynamics of these drugs. Mendelian randomization (MR) is a promising approach to investigate the causal relationship between exposures and clinical outcomes using genetic variants. However, the predominance of genetic studies in European populations limits the applicability of the findings to admixed populations, such as the Brazilian one. Therefore, this project aims to leverage population-specific SNPs identified in the student's PhD (grant number 2022/06532-3) and apply MR to evaluate the causal relationship between exposure to chemotherapy using carboplatin and paclitaxel, with ADRs and survival in Brazilian patients with gynecological tumors. The analysis will use data from 503 patients, complemented by public data from genome-wide association studies (GWAS). Genomic ancestry inference will be performed to minimize population structure biases. Genetic data were obtained using the iScan microarray (Illumina), in the student's PhD project, and missing genotypes will be imputed to expand coverage. Statistical analyses will be conducted using the R software, with adjustments for multiple comparisons. The interpretation of genomic results requires not only advanced statistical knowledge but also the application of robust computational methods to control biases. The experience acquired by the student at an international center will contribute to the introduction of new methodological approaches and the training of the research group the student is associated with in Brazil.