Determination of ancestral profile and basal phenotype in asymptomatic patients versus patients diagnosed with breast cancer in the interval between routine mammograms.

• Grant number: 24/20686-9
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: April 01, 2025
• End date: December 31, 2025
• Field of knowledge: Biological Sciences - Genetics - Human and Medical Genetics
• Principal Investigator: Márcia Maria Chiquitelli Marques Silveira
• Grantee: Matheus Henrique Martins da Cruz
• Host Institution: Hospital do Câncer de Barretos. Fundação Pio XII (FP). Barretos , SP, Brazil

Abstract

Breast cancer, the most common neoplasm in women worldwide, is characterized by heterogeneous genetic alterations in breast cells. Early screening of the disease is crucial for better patient prognosis, playing a key role in combating mortality rates associated with the disease. Interval tumors, which arise between regular screenings, tend to have rapid progression and worse prognosis, often associated with mutations in genes involved in cell cycle control, such as p53 and HER2. Genetic ancestry can influence not only susceptibility to developing breast cancer but also the behavior of tumor cells, such as the expression of specific phenotypes. Due to this, the present study aims to investigate molecular and basal phenotypes among different groups and their distinct characteristics, as well as their relationship with ancestral genotypes, in addition to the correlation of these characteristics with the detection, progression, and clinical outcomes of breast cancer. Ancestry determination will be performed using Multiplex PCR with fluorescent primers to amplify 46 markers from four ancestral origins in symptomatic, asymptomatic, and interval tumor patients. The amplified fragments will be analyzed with the ABI Prism 3000 sequencer to calculate the proportions of each ancestry. The identification of the basal phenotype of tumor samples will be carried out through immunohistochemistry, targeting the EGFR and Cytokeratin 6/7 antigens. For statistical analysis, SPSS version 23 and R Studio software will be used, adopting a significance level of 5%. Through the understanding of genetic characteristics of breast cancer, we hope to foster a scientific environment in the search for biomarkers with strategic application in screening, diagnosis, and more effective treatments based on molecular profiles and individual genetic characteristics.