Óscar Lapuente-Santana

The paper presents a pan-cancer single-cell atlas linking intratumoral states to therapeutic vulnerabilities by integrating transcriptomics, copy-number alterations, and drug-response predictions across 34 tumor types.

The paper identifies CD74+ microglia/macrophages driven by MIF as clinically relevant subpopulations in brain metastasis and other CNS disorders, showing their role in disease progression and therapeutic targeting potential.

The paper introduces a mathematical model, RaCInG, to infer cell-cell interaction networks in the tumor microenvironment using bulk RNA-seq data, revealing patient-specific features and immune response associations.

This paper develops a signature, iHet, to capture tumor microenvironment heterogeneity linked to immune activity and evasion using transcriptomic data from lung cancer.

The paper introduces easier, an R/Bioconductor package that predicts antitumor immune response from bulk RNA-seq data, outperforming existing methods in four cancers.