Felipe Prósper

This paper develops conductive polymer-hydrogel scaffolds for cardiac tissue engineering using melt electrowriting, showing that gold coating supports better contractile activity than other conductivity methods.

This study characterizes gene expression in human growth plates, identifying novel markers and sub-populations of resting zone chondrocytes with features of quiescent stem cells.

This study identifies transcriptional changes in stromal and endothelial cells during MGUS to myeloma progression and treatment response, revealing a tumor-permissive BME signature that is modulated by therapy.

This study engineers sdAb-based CAR T cells targeting BCMA, showing improved antitumor efficacy and persistence in multiple myeloma compared to existing therapies.

This study uses single-cell RNA sequencing to analyze EDA-CAR-T cell dynamics in the tumor microenvironment, revealing temporal reprogramming toward dysfunction and identifying immunosuppressive pathways that impair therapeutic efficacy in solid tumors.

This study shows that inhibiting G9a enhances the effectiveness of immune checkpoint inhibitors in hepatocellular carcinoma by improving tumor immunogenicity and T cell infiltration.

This study shows clonal hematopoiesis promotes fibrosis by altering macrophage behavior and tissue repair processes in lung disease.

This study uses single-cell multiomics to analyze CAR T cell dynamics in multiple myeloma, identifying regulatory mechanisms affecting persistence and dysfunction.

The paper introduces genetic Minimal Intervention Sets (gMISs) to identify lethal genetic interactions beyond synthetic lethality in human cells and demonstrates their application in cancer research.

This study uses spatial transcriptomics to analyze bone marrow in MM mouse models and patients, revealing altered T-cell distribution, neutrophil traps, and inflammatory signaling in MM.

The paper constructs a CAR-T cell functional atlas from over one million cells across 13 studies to link product composition with clinical response and identify sex- and age-dependent effects.

This study shows that airway basal stem cells maintain intraepithelial airway macrophages via Notch signaling, enabling localized allergic inflammation in the trachea but not distal lung tissues.

This study identifies novel RAB13+ endothelial and profibrotic mesenchymal cells in aged human bone marrow using single-cell RNA sequencing and spatial transcriptomics.

The paper identifies molecular dynamics and a new marker, Aspn, for reparative cardiac fibroblasts in mice, pigs, and patients after myocardial infarction.

This study maps epigenetic and transcriptional changes in myeloma progression from precursor to advanced stages, identifying key transcription factors involved in disease development.

This study shows that pentanoate, a microbial postbiotic, is metabolized to citrate, which influences T cell differentiation and anti-cancer CAR T cell efficacy through epigenetic mechanisms.

This study shows gene therapy can restore the transcriptional program of hematopoietic stem cells in Fanconi Anemia patients, making them resemble healthy donor cells.

This study uses single-cell RNA sequencing to analyze changes in hematopoietic stem and progenitor cells during aging and myeloid malignancies, identifying altered gene expression and regulatory networks.

gMCStool identifies metabolic vulnerabilities in cancer by predicting synthetic lethal interactions using genome-scale metabolic networks and RNA-seq data.

This study uses CRISPR screens and Perturb-Seq to analyze 550 chromatin factors in haematopoiesis and AML, revealing lineage-specific roles and therapeutic implications.

BOSO is a novel feature selection algorithm for linear regression that outperforms existing methods in high-dimensional datasets, demonstrated through drug sensitivity prediction in cancer.

The paper improves prediction of lethal gene dependencies using the HUGE method, achieving 75x higher statistical power than existing methods in cancer genomics.

This paper introduces a network-based method to predict synthetic lethality in cancer metabolism by integrating genetic interactions and nutrient environments, identifying potential vulnerabilities in tumor cells.

This study examines 3D genome architecture changes during B cell differentiation and in B cell neoplasias using Hi-C and multi-omic data, revealing dynamic compartment shifts and tumor-specific chromatin reorganization.

This paper introduces LIBRA, a neural network framework for integrating and predicting across paired single-cell multi-omics data, showing improved clustering resolution and predictive power.

scMomentum infers cell-type-specific regulatory networks and energy landscapes from single-cell transcriptomic data without needing temporal or perturbation experiments.

The paper introduces SimiC, a method for inferring gene regulatory networks per cell phenotype and comparing them across conditions, revealing regulatory dynamics missed by single GRN approaches.