Biology subjects

D'Rozario, J.

Publications and source records attributed to D'Rozario, J..

3 recordsLinked to original sources

bioRxiv2026

Mapping the immune landscape in small cell lung cancer unveils a distinct tumor-reactive CD8+ T cell molecular signature

Small cell lung cancer (SCLC) is a highly aggressive malignancy with limited therapeutic advances. Unlike many other cancers, its immune landscape, particularly immune competence and T cell recognition, remains poorly characterized. Here, we generate a single-cell transcriptome atlas of the SCLC immune microenvironment with paired T cell receptor (TCR) sequencing. By linking T cell states with clonality and a multilayered functional screening, we identify 6 tumor-reactive TCRs that recognize and eradicate autologous SCLC cell lines. We delineate a novel SCLC-reactive CD8+ T cell signature (SCLC_TR), enabling the identification of 47 further SCLC-reactive TCRs. The SCLC_TR signature performs extremely well in pancreatic ductal adenocarcinoma (PDAC), another immune-cold tumor indication, and, most strikingly, patients with elevated SCLC_TR signature scores exhibited significantly improved survival, underlining its prognostic potential. Comparative cell-cell interaction analyses implicate several immunosuppressive mechanisms, with myeloid cells and CD4 regulatory T cells possibly acting as counterbalances to effector T cell activity in SCLC. In summary, our study challenges the prevailing notion of SCLC as an immune-cold tumor type by providing direct evidence of tumor-reactive T cell responses and introduces the SCLC_TR signature as a tool to identify tumor-specific T cells and their microenvironmental restraints and escape mechanisms, ultimately shaping next-generation immunotherapeutic strategies. O_FIG O_LINKSMALLFIG WIDTH=195 HEIGHT=200 SRC="FIGDIR/small/735200v1_ufig1.gif" ALT="Figure 1"> View larger version (69K): org.highwire.dtl.DTLVardef@1c25f2eorg.highwire.dtl.DTLVardef@1f6f519org.highwire.dtl.DTLVardef@553e57org.highwire.dtl.DTLVardef@6fe7e1_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2026

A ML-framework for the discovery of next-generation IBD targets using a harmonized single-cell atlas of patient tissue

Target discovery for IBD has traditionally relied on genetic associations, which lack the cellular resolution needed to identify novel, actionable, cell type-specific disease pathways. Here, we describe an integrated analytical and experimental framework that leverages harmonized single-cell data to systematically discover novel therapeutic strategies for IBD. We used AMICA DBTM, Immunais harmonized database of single-cell RNA datasets to construct a harmonized 1 million single-cell atlas of the human intestine. We applied a machine learning framework (Immune Patient Representation, IPR) to identify disease-associated transcriptional programs and cell type-specific gene targets. Candidate targets were prioritized using atlas-derived metrics, refined using custom criteria emphasizing translational actionability, and validated across independent clinical cohorts. Select candidates were evaluated in human primary-cell models reflecting the targets cell-type context. The IPR framework identified 85 disease-associated transcriptional programs and ranked 400 cell type-specific target genes across immune and stromal lineages. Disease-associated programs were interpreted using a structured AI-assisted reasoning framework for structured biological reasoning, linking them to IBD-relevant pathways and guiding the identification of novel, promising gene targets. Functional validation of two cell-type-specific candidates, PTGIR in myeloid cells and IL6ST in fibroblasts, confirmed the reduction of inflammatory and fibrotic pathways linked to IBD pathology. Multi-omic profiling and projection of in vitro phenotypes to patient datasets demonstrated the reversal of disease-associated programs via mechanisms distinct from those of existing biologics. Our single-cell anchored, machine-learning framework integrates in silico discovery with experimental validation, revealing new cell type-specific therapeutic opportunities and supporting a scalable approach for precision target discovery in IBD and other immune-mediated diseases.

bioinformatics↗

bioRxiv2021

Fibroblastic reticular cells provide a supportive niche for lymph node-resident macrophages

The lymph node (LN) is home to resident macrophage populations that are essential for immune function and homeostasis. The T cell paracortical zone is a major site of macrophage efferocytosis of apoptotic cells, but key factors controlling this niche are undefined. Here we show that fibroblastic reticular cells (FRCs) are an essential component of the LN macrophage niche. Macrophages co-localised with FRCs in human LNs, and murine single-cell RNA-sequencing revealed that most reticular cells expressed master macrophage regulator CSF1. Functional assays showed that CSF1R signalling was sufficient to support macrophage development. In the presence of LPS, FRCs underwent a mechanistic switch and maintained support through CSF1R-independent mechanisms. These effects were conserved between mouse and human systems. Rapid loss of macrophages and monocytes from LNs was observed upon genetic ablation of FRCs. These data reveal a critically important role for FRCs in the creation of the parenchymal macrophage niche within LNs.

immunology↗