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Ferrone, C.

Publications and source records attributed to Ferrone, C..

2 recordsLinked to original sources

Distinct malignant cell states and myeloid glutamate signaling associated with aggressive pancreatic neuroendocrine tumors

Pancreatic neuroendocrine tumors (PNET) are rare malignancies of the endocrine pancreas with diverse clinical outcomes. While some PNETs are indolent, others are aggressive and metastasize quickly. However, clinically-relevant molecular stratification for PNET to predict outcomes and guide therapeutic decision-making is limited. Thus, there is an urgent need to understand the molecular heterogeneity of PNETs to refine prognostication and discover novel therapeutic vulnerabilities. We performed single-nucleus RNA sequencing on resected primary and metastatic PNETs (n = 20), including two PNETs with neoadjuvant treatment. We inferred gene expression programs (GEPs) of malignant and non-malignant cells and investigated associations with clinical outcomes. Next, we inferred interactions in the tumor microenvironment (TME) and performed transwell assays for functional validation. Finally, we explored genomic and transcriptomic evolution in a unique case study of an untreated primary PNET with two asynchronous hepatic metastases. A malignant GEP enriched for neural/synaptic signaling genes was associated with worse overall survival, broad chromosomal loss of heterozygosity, and alternative lengthening of telomeres. Another malignant GEP enriched for VEGF signaling increased throughout metastatic progression in our case study. We found that macrophage-derived glutamate drives polarization towards an immunosuppressive phenotype and activates the MAPK/ERK pathway in malignant cells to increase migratory capacity. This study provides a detailed single-nucleus transcriptomic classification of malignant, stromal, and immune cell types and states in PNETs, their interactions in the TME, and associations with clinical outcomes. The refined molecular taxonomy of PNET may guide the development of more efficacious biomarkers and therapeutic strategies.

cancer biology↗

Single-cell transcriptomics reveals the impact of sex and age in the healthy human liver

Background & AimsThe liver is a vital organ composed of parenchymal, nonparenchymal, and immune cell populations. Single-cell sequencing approaches now provide the opportunity to understand how sex and age influence gene expression and cellular function across cell types within the liver. MethodsWe analyzed the cellular composition and interactions for the human liver through single-nucleus RNA sequencing (snRNA-seq), incorporating insights from 37 healthy liver samples. The dataset contains cells from female and male donors spanning more than seven decades of life, and analysis was performed to evaluate the impact of sex and age on differential gene expression, pathway enrichment, and predicted ligand-receptor and protein-protein interactions. ResultsExcluding the X and Y chromosomes, we identified 374 genes uniquely enriched in cells of the female liver and 520 genes enriched in cells of the male liver. Differential expression analysis defined unique circuitries enriched within each cell type between females and males and their impact on cell-cell communication and response to external signals, including enrichment of cholesterol/lipid metabolism, transforming growth factor beta (TGF-beta) signaling, and fibronectin (FN1) production in female cells and bone morphogenic protein (BMP) signaling in male cells. With increased age, we observe a greater diversity in gene expression, including enrichment of genes that regulate neuregulin (NGR) signaling at older ages, while genes regulating insulin growth factor (IGF) signaling are enriched at younger ages. Senescence signatures were also identified for each cell type within the liver. ConclusionsThese results define the activities of healthy cell types within the liver across sex and age and provide a foundation for studies to examine how ancestry, geography, and disease states influence liver function within these contexts. Impact and ImplicationsOur study analyzes 37 human liver samples at the single-cell level to understand how sex and age influence gene expression, cell interactions, and response to signals across liver cell types and sub-types. These findings are of particular significance for researchers who need to understand how sex and age may influence the response of individual cell types to injury or treatment of injury. This dataset will also provide a healthy reference for future studies to understand how ancestry, geography, and disease states shape liver biology across age and sex.

cell biology↗