Professor Jesús María Hernández Rivas is Full Professor and deputy director in the Department of Medicine at the University of Salamanca. He is responsible for two subjects in the degrees of Medicine, Pharmacy, Physiotherapy and Biotechnology being also responsible of the subject “Molecular Cytogenetics in Oncology” in the Master “Biology and Clinic of Cancer”. Moreover, he has directed 9 Master thesis Projects and 16 PhD thesis, and he has been tutor of 27 internship students. Additionally, he has being in charge of more than 45 graduates coming from other countries (Italy, Portugal, Poland, Czech Republic, England, Latin America, Iran) who have spent between 2 months and a year learning molecular genetics in the molecular Cytogenetics Unit (MCU) at the Cancer Research Centre (University of Salamanca).
Prof. Hernández Rivas is also senior staff member of the Dept. of Hematology at the University Hospital in Salamanca. He leads the research group of Molecular Cytogenetics at the Instituto de Estudios de Ciencias de la Salud de Castilla y León- Instituto de Investigación Biomédica de Salamanca (IECSCYL-IBSAL). Moreover, he heads the (MCU), a facility devoted to the molecular cytogenetics and next generation sequencing of cancer patients. More than 100 hospitals in Spain, and occasionally others from the EU, have used the MCU services. The group is also composed by seven postdoctoral researchers with extensive experience in the cellular and molecular biology of hematological and solid tumors, seven predoctoral students, two master student, as well as five specialists in hematology and hemotherapy and pediatrics.
Research line:
The Oncohematology group has published more than 229 papers in international scientific journals and directed 38 research projects and 16 doctoral theses. Specifically, the group has an extensive and productive research line focused on the study of hematological malignancies, in collaboration with national and international groups.
The group’s contributions to the knowledge of the molecular mechanisms involved in the development of hematological neoplasms are relevant. The group actively participates in the CLL sequencing. A part of their work has focused on the study of the prognostic value of the molecular cytogenetics and the number of alterations which are present in patients with hematological malignancies (CLL, ALL, MDS). To this regard, new genetic anomalies have been described in specific chromosomal regions by the application of genomic arrays. During the last years, the group has been part of the Spanish CLL Genome Consortium (International Cancer Genome Consortium, ICGC) and has collaborated in works using the NGS techniques, which have led to the characterization of driver mutations in CLL (Puente et al., Nature 2011, Quesada et al, Nat Genet 2012), non-coding regions (Quesada et al, Nature, 2015) and the characterization of its prognostic value (Villamor et al, Leukemia 2013, Martínez-Trillos et al., Blood 2014). A new technology has been included in the group with the incorporation of Clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 which will allow us to create CLL in vitro models and study the effects of mutations observed in CLL patients thanks to an international collaboration with Dr. Wu’s lab (Dana-Farber Cancer Institute, Boston) (García-Tuñon et al., Oncotarget 2017) (Quijada M, et al. Blood 2019 under Review).
Currently, Jesus Maria Hernandez is the project coordinator of two European research Projects: “SYNTHERAPY” (2019-2021) from the EraPermed programme and the HARMONY project (2017-2021), a large IMI funded project which aims to facilitate the use of diverse data sources to deliver results that reflect health outcomes of treatments that are meaningful for patients, clinicians, regulators, researchers, healthcare decision-makers, and others. The aim of the SYNTHERAPY project is to develop a machine learning-based model to predict personalized treatment for relapsed or refractory Acute Leukemia. We will exploit two new and promising Synthetic Lethality approaches by multilayer analysis of omics data
