Advancing pediatric germ cell tumor classification through Nanopore sequencing

• Grant number: 23/15715-7
• Support Opportunities: Scholarships abroad - Research Internship - Doctorate (Direct)
• Start date: May 01, 2024
• End date: March 31, 2025
• Field of knowledge: Biological Sciences - Genetics - Human and Medical Genetics
• Principal Investigator: Mariana Tomazini Pinto
• Grantee: Ana Flávia Souza Péres
• Supervisor: Jeremy Wang
• Host Institution: Hospital do Câncer de Barretos. Barretos , SP, Brazil
• Institution abroad: University of North Carolina at Chapel Hill (UNC), United States
• Associated to the scholarship: 22/07041-3 - Feasibility of nanopore sequencing for classification of pediatric germ cell tumors, BP.DD

Abstract

Pediatric germ cell tumors (GCTs) are rare and account for 3.3% of malignant tumors in children. GCTs are characterized as benign or malignant neoplasms and can occur in gonadal or extragonadal sites. They are classified histologically as seminoma, dysgerminoma, yolk sac tumor, embryonal carcinoma, choriocarcinoma, mixed tumors, and mature and immature teratoma. Because GCTs are heterogeneous, it is difficult to generalize the behavior of these tumors. Due to the rarity of pediatric GCTs, most studies are performed in adult patients, with a scarcity of information in pediatric patients. The diagnosis of GCTs is performed with the aid of radiological images and tumor markers, the main markers being alpha-fetoprotein and the beta fraction of human chorionic gonadotropin. However, they are not specific markers and have limitations in terms of sensitivity. Thus, it is necessary to investigate specific biomarkers to help diagnose patients with GCTs and the search for precision medicine. Sequencing platforms, including Oxford Nanopore Technologies, are among the most widely used techniques. Thus, this study aims to analyze the feasibility of nanopore sequencing for classifying pediatric GCTs into their respective histological types. Therefore, the RNA of pediatric patients with GCTs will be extracted to analyze gene expression using the Nanopore platform. Next, machine learning algorithms will be developed to classify the GCTs according to histology in partnership with the Saint Jude Children's Research Hospital and the University of North Carolina teams. The classification of tumors through nanopore sequencing will enable an early and assertive diagnosis and be able to conduct personalized treatments/directed to the altered genes, improving the patient's clinical management. (AU)