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Alcazer, V.

Publications and source records attributed to Alcazer, V..

2 recordsLinked to original sources

Gene signature of circulating platelet-bound neutrophils is associated with poor prognosis in cancer patients

Beyond their critical role in hemostasis, platelets physically interact with neutrophils to form neutrophil-platelet aggregates (NPAs), enhancing neutrophil effector functions during inflammation. NPAs may also promote disease worsening in various inflammatory diseases. However, characterization of NPAs in cancer remains totally unexplored. Using ImageStream(R)X (ISX) imaging flow cytometer, we were not only allowed able to detect CD15+ CD14- CD36+ ITGA2B+ NPAs in both healthy donors (HDs) and cancer patients bloods, but we also showed that NPAs result from the binding of platelets preferentially to low-density neutrophils (LDNs) as opposed to normal-density neutrophils (NDNs). By re-analyzing two independent public scRNAseq data of whole blood leukocytes from cancer patients and HDs, we could identify a subset of neutrophils with high platelet gene expression that may correspond to NPAs. Moreover, we showed that cancer patients derived NPAs possessed a distinct molecular signature compared with the other neutrophil subsets, independently of platelet genes. Gene ontology (GO) term enrichment analysis of this NPAs-associated neutrophil transcriptomic signature revealed a significant enrichment of neutrophil degranulation, chemotaxis and trans-endothelial migration GO terms. Lastly, using The Cancer Genome Atlas (TCGA), we could show by multivariate Cox analysis that the NPAs-associated neutrophil transcriptomic signature was associated with a worse patient prognosis in several cancer types. These results suggest that neutrophils from NPAs are systemically primed by platelets empowering them with cancer progression capacities once at tumor site. NPAs may therefore hold clinical utility as novel non-invasive blood prognostic biomarker in cancer patients with solid tumors. Novelty and ImpactPlatelets physically interact with peripheral blood neutrophils to form neutrophil-platelet aggregates (NPAs), known to promote disease worsening in various inflammatory diseases. However, characterization of NPAs in cancer remains totally unexplored. We showed that NPAs-associated neutrophils were a yet-unreported unique subset of circulating neutrophils associated with a worse patient prognosis in several cancer types. NPAs may hold clinical utility as novel non-invasive blood prognostic biomarker in cancer patients with solid tumors.

immunology↗

Panel Informativity Optimizer (PIO): an R package to improve cancer NGS panel informativity

Mutation detection by next generation sequencing (NGS) is routinely used for cancer diagnosis. Selecting an optimal set of genes for a given cancer is not trivial as it has to optimize informativity (i.e. the number of patients with at least one mutation in the panel), while minimizing panel length in order to reduce sequencing costs and increase sensitivity. We propose herein Panel Informativity Optimizer (PIO), an open-source software developed as an R package with a user-friendly graphical interface to help optimize cancer NGS panel informativity. Using patient-level mutational data from either private datasets or preloaded dataset of 91 independent cohort from 31 different cancer type, PIO selects an optimal set of genomic intervals to maximize informativity and panel size in a given cancer type. Different options are offered such as the definition of genomic intervals at the gene or exon level, and the use of optimization strategy at the patient or patient per kilobase level. PIO can also propose an optimal set of genomic intervals to increase informativity of custom panels. A panel tester function is also available for panel benchmarking. Using public databases, as well as data from real-life settings, we demonstrate that PIO allows panel size reduction of up to 1000kb, and accurately predicts the performance of custom or commercial panels. PIO is available online at https://vincentalcazer.shinyapps.io/Panel_informativity_optimizer/ or can be set on a locale machine from https://github.com/VincentAlcazer/PIO.

bioinformatics↗