Pr Adriano Sabino est invité par Vanessa Desplat, équipe 10, Cellules souches hématopoïétiques normales et leucémiques.

Title: Omics Sciences Applied to the Investigation of Potential Biomarkers and Therapeutic Targets in Acute Leukemias

Presenter: Prof. Adriano de Paula Sabino – Federal University of Minas Gerais (UFMG), Brazil

Bio: Associate Professor at the Federal University of Minas Gerais (UFMG), Brazil. Holds a Ph.D. in Pharmaceutical Sciences with postdoctoral training in cancer therapy resistance at Michigan State University. Academic and research expertise in Clinical, Experimental, and Molecular Hematology. Research interests encompass cancer biology, acute and chronic leukemias, chemotherapy resistance, molecular and cellular biomarkers, functional genomics, proteomics, metabolomics, nanobiomaterials, regenerative medicine, cell-based therapies, and the application of bioinformatics to precision medicine.

Abstract:

Acute leukemias, including Acute Lymphoblastic Leukemia (ALL) and Acute Myeloid Leukemia (AML), are aggressive hematologic malignancies with high biological heterogeneity and limited predictive tools for therapeutic response and disease progression. In this context, omics sciences offer powerful strategies to unravel the molecular complexity underlying these diseases and support the identification of new biomarkers and therapeutic targets.

This seminar will provide an overview of our translational research efforts combining metabolomics, clinical peptidomics, and machine learning. We will discuss the conceptual and methodological foundations for applying mass spectrometry-based omics approaches (LC-MS and MALDI-TOF/MS) to plasma samples, as well as the integration of artificial intelligence algorithms to enhance biomarker discovery, risk stratification, and individualized therapeutic guidance.

Additionally, we present the rationale and design of predictive modeling studies employing clinical and genomic datasets from AML patients. These models, based on supervised learning techniques, aim to improve the accuracy of outcome prediction and inform precision oncology strategies.

Our interdisciplinary approach highlights the potential of integrating systems biology, data science, and clinical research to advance personalized medicine in oncohematology.

Keywords: Acute leukemia, ALL, AML, biomarkers, omics sciences, LC-MS, MALDI-TOF/MS, machine learning, precision oncology, clinical stratification.

📆 Vendredi 04-07, 11h

📌 salle de conférence BBS, 2 rue Dr Hoffmann Martinot Bordeaux