Biology subjects

Rocha, V.

Publications and source records attributed to Rocha, V..

4 recordsLinked to original sources

bioRxiv2026

End-To-End, Fully Automated Manufacturing of Hematopoietic Stem and Progenitor Cell Therapy Via CCR5-Targeted Integration

Gene therapies utilizing hematopoietic stem and progenitor cells (HSPCs) have curative potential across hematologic diseases, but manual manufacturing workflows are costly and difficult to scale, limiting patient access. Here, we demonstrated automation of an HSPC gene knock-in protocol on a high-throughput manufacturing platform designed for clinical-scale production. The platform executed all steps, from post-thaw HSPC inoculation through Cas9 electroporation, AAV6 transduction, and harvest, producing gene-edited HSPCs (geHSPCs) carrying an anti-HIV antibody transgene at the CCR5 locus with high purity, preserved differentiation potential, and editing efficiencies comparable to small-scale processing. Following transplantation into mice, geHSPCs engrafted and reconstituted multiple hematopoietic lineages, demonstrating that repopulation capacity was preserved. This work shows that clinical-scale doses of geHSPCs meeting release criteria can be produced on an automated, high-throughput platform, while preserving key product attributes and in vivo function, providing a path toward scalable and cost-effective manufacturing that could broaden access to HSPC gene therapies.

genetics↗

bioRxiv2025

STARComm Scalably Detects Emergent Modules of Spatial Cell-Cell Communication in Inflammation and Cancer.

In humans, cell-cell communication orchestrates tissue organization, immune coordination, and repair, yet spatially mapping these interactions remains a challenge for biology. We introduce STARComm, a scalable-interpretable computational method that identifies Multicellular Communication Interaction Modules (MCIMs) by detecting spatially co-located receptor-ligand activity from high-plex spatial transcriptomics in 2D and 3D. Applied to an atlas of >14million cells across 8 cancers, STARComm revealed 24 conserved and tumor-specific MCIMs, including a fibro-immune module with targetable axes linked to immune exclusion and immunotherapy resistance. In chronic graft-versus-host disease, STARComm identified three salivary gland MCIMs predictive of patient death and two druggable axes (CXCL12-CXCR4, CCL5-SDC4), both with FDA-approved therapeutics. STARComm demonstrated that peripheral tissue profiling can forecast fatality nearly 3 years in advance using minor salivary glands. By enabling scalable biomarker discovery, drug targeting, and spatially resolved precision profiling, STARComm bridges the gap between spatial biology and clinical translation, advancing the field of spatial medicine. SUMMARYDespite major advances in spatial biology, no framework has yet linked spatially resolved intercellular communication networks, independent of cell types, to clinical outcomes in human disease. Here, we present STARComm, a scalable method that identifies Multicellular Interaction MCIMs (MCIMs). Applying STARComm to minor salivary gland biopsies from patients with chronic graft-versus-host disease (GVHD), we identify MCIMs that not only distinguish healthy from diseased tissue but also stratify patient survival. High-risk MCIMs are enriched for actionable immune and stromal pathways, including those targetable with existing therapies. These findings establish the first outcome-linked spatial communication framework in any human disease and highlight the translational potential of oral tissues as minimally invasive platforms for real-time immune diagnostics, prognostic modeling, and therapeutic screening.

bioinformatics↗

bioRxiv2024

Spatial Deconvolution of Cell Types and Cell States at Scale Utilizing TACIT

Identifying cell types and states remains a time-consuming and error-prone challenge for spatial biology. While deep learning is increasingly used, it is difficult to generalize due to variability at the level of cells, neighborhoods, and niches in health and disease. To address this, we developed TACIT, an unsupervised algorithm for cell annotation using predefined signatures that operates without training data, using unbiased thresholding to distinguish positive cells from background, focusing on relevant markers to identify ambiguous cells in multiomic assays. Using five datasets (5,000,000-cells; 51-cell types) from three niches (brain, intestine, gland), TACIT outperformed existing unsupervised methods in accuracy and scalability. Integration of TACIT-identified cell with a novel Shiny app revealed new phenotypes in two inflammatory gland diseases. Finally, using combined spatial transcriptomics and proteomics, we discover under- and overrepresented immune cell types and states in regions of interest, suggesting multimodality is essential for translating spatial biology to clinical applications.

bioinformatics↗

bioRxiv2018

Carbapenem-resistant Pseudomonas aeruginosa bloodstream infection: in vitro synergy, virulence and clinical outcome

In the current study carbapanem-resistant P. aeruginosa bloodstream infection (CRPA-BSI) was associated with high 14-day mortality. Although, highly resistant to meropenem, half of the isolates achieved in vitro synergy with the combination of meropenem with colistin, and the patients that received this combination therapy showed a tendency towards lower mortality. Our strains did not carry exoU gene, on the other hand, patients with CRPA-BSI caused by strains harboring gene lasB evolved more frequent to death.

microbiology↗