Biology subjects

Alcazer, V.

Publications and source records attributed to Alcazer, V..

5 recordsLinked to original sources

bioRxiv2024

Targeting a shared neoepitope derived from non-canonical translation of c-MYC oncogene in cancer cells

Cancer cells rely on alternative modes of translation for protein synthesis, promoting internal ribosome entry site (IRES)-dependent translation of mRNA encoding pro-oncogenic factors. Furthermore, ribosomes translate mRNA with lower fidelity in tumor cells. We proposed that these translational modifications in cancer produce shared tumor-specific epitopes derived from IRES-containing oncogenes. To identify such neoepitopes, we developed an in silico-based method that we applied to c-MYC. We showed that the non-canonical translation of c-MYC mRNA in cancer cells, involving a (+1) ribosomal frameshift, generates a shared neoepitope which induces high-avidity T cells able to kill tumor cells in vitro and in vivo while sparing normal cells. Our data provide preclinical rationale for developing immunotherapies targeting this c-MYC-derived neoepitope and validate a new type of shared translation-associated neoantigens.

immunology↗

bioRxiv2024

Targeting Heterochromatin Eliminates Malignant Stem Cells in Chronic Myelomonocytic Leukemia Through Reactivation of Retroelements and Innate Immune pathways

Chronic myelomonocytic leukemia (CMML) is a severe myeloid malignancy affecting the elderly, for which therapeutic options are limited. DNA hypomethylating agents (HMAs) provide transient responses, failing to eradicate the malignant clone. Hematopoietic stem cell (HSC) aging involves heterochromatin reorganization, evidenced by alterations in histone marks H3K9me2 and H3K9me3. These repressive marks together with DNA methylation are essential for suppressing transposable elements (TEs). In solid cancers, the antitumor efficacy of HMAs involves the derepression of TEs, mimicking a state of viral infection. In this study, we demonstrate a significant disorganization of heterochromatin in CMML HSCs and progenitors (HSPCs) characterized by an increase in the repressive mark H3K9me2, mainly at the level of TEs, and a repression of immune and age-associated transcripts. Combining HMAs with G9A/GLP H3K9me2 methyltransferase inhibitors reactivates these pathways, selectively targeting mutated cells while preserving wild-type HSCs, thus offering new therapeutic avenues for this severe myeloid malignancy.

cancer biology↗

bioRxiv2023

IL-33 drives polyfunctionality and antitumor activity of a unique ST2+ NK cell population

Despite increasing recognition of NK cell diversity, their functional heterogeneity and its relevance to cancer remain incompletely understood. Here, we show that IL-12 promotes the emergence of a distinct ST2/IL33R+ NK cell state poised for robust activation by IL-33. Human ST2 NK cells exhibit a unique transcriptional program, an intermediate differentiation state between CD56bright and CD56dim NK cells, and enhanced polyfunctionality combining proliferation, cytokine production, and cytotoxicity. ST2 NK cells were identified across human and murine tumor datasets. In murine breast cancer models, IL-33 and IL-12 cooperated to elicit potent antitumor responses dependent on IFN-{gamma} and ST2 NK cells. In cancer patients, IL-12 unleashed tumor-infiltrating ST2 NK cells' potential to produce IFN-g in response to IL-33, an IL33hi-NKhi score was associated with prolonged survival, and ST2 NK cells correlated with improved immunotherapy response. Collectively, these findings identify ST2 NK cells as a therapeutically actionable NK cell state promoting antitumor immunity.

cancer biology↗

bioRxiv2021

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↗

bioRxiv2021

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↗