Lukas Chávez

This paper introduces ecEvol, a method to infer ecDNA emergence time and other parameters from bulk whole-genome sequencing data, finding that ecDNA typically emerges early and is associated with poorer survival.

This study compares ecDNA prevalence, conservation, and clonal dynamics in PDX models and primary tumors of childhood cancers, finding high sequence conservation and selective growth advantage of ecDNA-positive clones.

This paper develops a deep learning framework to detect extrachromosomal DNA from histopathology images, identifying ecDNA-amplified tumours across twelve cancer types.

The paper introduces ec3D, a method to reconstruct 3D structures of ecDNA from Hi-C data, revealing spherical configurations and unique long-range interactions in cancer.

This study shows that interferon gamma restores antigen presentation in medulloblastoma and enhances T cell-mediated tumor killing in a mouse model.

This study identifies RREB1 as a key driver of Group 3 medulloblastoma, showing its role in tumor growth and survival through the c-MET signaling pathway.

This paper identifies how PVT1 rearrangements in MYC+ cancers generate oncogenic peptides that synergistically activate MYC, AKT, and RAS-MAPK pathways, enhancing tumor aggressiveness.

ecPath detects ecDNA in tumors using H&E images, achieving good performance in predicting ecDNA status and identifying poor prognoses in low grade glioma patients.