Oferta TFM | ID 28

Renal cell carcinoma (RCC) is a highly heterogeneous disease with marked variability in clinical behavior and response to therapy. Growing evidence indicates that abnormal accumulation of oncometabolites—such as fumarate, succinate, and L-2-hydroxyglutarate (L-2-HG)—resulting from alterations in the Krebs cycle acts as a key driver of tumor progression. However, these metabolic determinants are still largely underexploited for patient stratification and therapeutic decision-making.

This project proposes that systematic characterization of RCC according to oncometabolite profiles will uncover biologically defined subgroups with actionable therapeutic vulnerabilities. The student will join an ongoing translational oncology program aimed at understanding how metabolic rewiring influences tumor aggressiveness and drug response in renal cancer.The work will integrate multi-omics approaches in a large, well-annotated RCC tumor cohort available in the laboratory. Metabolomic, transcriptomic and epigenomic data will be analyzed to identify signatures associated with oncometabolite accumulation and activation of pathways such as HIF signaling. Advanced bioinformatic pipelines, including bulk RNAseq deconvolution methods, will be applied to dissect tumor microenvironment features.

During the fellowship, the student will receive hands-on training in:

• Cancer multi-omics data analysis.
• Integration of metabolomics and transcriptomics.
• Experimental validation using preclinical RCC models (cell lines) to evaluate sensitivity to metabolism-targeted therapies.
• Biomarker discovery linked to tumor metabolism.
• Translational interpretation of molecular findings.

Overall, this project provides interdisciplinary training at the interface of cancer metabolism, precision oncology and computational biology within a highly experienced pharmacogenomics and tumor biomarkers group. The ultimate goal is to contribute to metabolism-based patient stratification strategies that improve therapeutic outcomes in renal cancer.

Research group: Pharmacogenomics and Tumor Biomarkers Group.