Biomedical subjects

Nicholas E Navin

Publications and source records attributed to Nicholas E Navin.

2 recordsLinked to original sources

PubMed2026

Tumor microbial burden drives immune responses through regulation of Interferon signaling.

Tumor microbes are increasingly recognized for modulating tumor behavior and therapy responses. Intratumoral microbial burden (ITMB) analysis across cancers revealed regulation of immune pathways, and activated mast cells, mostly in colorectal (CRC) and gastric (STAD) cancers. High ITMB CRC leads to interferon regulation and is associated with improved outcomes in advanced disease. Single-cell sequencing revealed induction of interferon-related genes (IRGs) within microbes-containing human CRC. GI-luminal mismatch repair deficiency (MMRd) tumors had higher ITMB than proficient tumors (MMRp). In a rectal MMRd cohort with 100% remission after immune checkpoint blockade (ICB), tumor microbes and microbes-containing mast cells increased. In ICB-sensitive syngeneic murine MMRd tumor models, local tumor microbial depletion, impaired ICB efficacy while downregulating IFN signaling. Forced upregulation of IRGs in ADAR1-deficient cancer cells restored immunotherapy responses during microbial ablation. These data highlight dynamic interplay between ITMB, host defense, and immunogenicity which seems key to determine therapy responses.

Journal Article↗

PubMed2025

Coalescing single-cell genomes and transcriptomes to decode breast cancer progression.

Understanding epithelial lineages of breast cancer and genotype-phenotype relationships requires direct measurements of the genome and transcriptome of the same single cells at scale. To achieve this, we developed wellDR-seq, a high-genomic-resolution, high-throughput method to simultaneously profile the genome and transcriptome of thousands of single cells. We profiled 33,646 single cells from 12 estrogen-receptor-positive breast cancers and identified ancestral subclones in multiple patients that showed a luminal hormone-responsive lineage, indicating a potential cell of origin. In contrast to bulk studies, wellDR-seq enabled the study of subclone-level gene-dosage relationships, which showed near-linear correlations in large chromosomal segments and extensive variation at the single-gene level. We identified dosage-sensitive and dosage-insensitive genes, including many breast cancer genes as well as sporadic copy-number aberrations in non-cancer cells. Overall, these data reveal complex relationships between copy number and gene expression in single cells, improving our understanding of breast cancer progression.

Breast Neoplasms↗