Author

Vincent Alcazer

Centre National de la Recherche ScientifiqueORCID 0000-0003-1843-6286Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Cancer Biology· 1 Immunology· 1

Signature Assays, Organisms & Methods

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Approach:experimental assay· 2 Research Focus:cancer & tumor microenvironment· 1 Research Focus:cell type annotation· 1 Assay:ChIP-seq· 1 Research Focus:differential expression· 1 Assay:DNA methylation· 1 Research Focus:drug response / drug discovery· 1 Organism:human· 1

Frequent Co-Authors

Stéphane DepiliD· 2 shared A. Bolon· 1 shared Adeline PageiD· 1 shared Aikaterini Polyzou· 1 shared Aline RennevilleiD· 1 shared Audrey Merienne· 1 shared Audrey Porquet· 1 shared Aygun Imanci· 1 shared

Activity by Year

2022-2024 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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2 shared papersCancer Biology

Stéphane DepilORCID

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3 papers

Recent·Most cited

Cancer BiologyCommunications BiologyPeer-reviewedNov 22, 2024

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

Donia Hidaoui, Audrey Porquet, Rabie Chelbi…·Françoise Porteu

This study shows that combining DNA hypomethylating agents with H3K9me2 inhibitors reactivates immune pathways and eliminates malignant stem cells in CMML by targeting heterochromatin disorganization.

17 citationstop 4%

humanDNA methylation

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ImmunologybioRxivPreprintMay 23, 2024

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

Estelle Baulu, A. Bolon, Ema Etchegaray…·Stéphane Depil

The paper identifies a shared neoepitope from non-canonical c-MYC translation in cancer cells that activates T cells to kill tumors without harming normal cells.

DOI 10.1101/2024.05.23.595486

experimental assaydrug response / drug discovery

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BioinformaticsJournal of Molecular DiagnosticsPeer-reviewedApr 12, 2022

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

Vincent Alcazer, Pierre Sujobert

PIO optimizes cancer NGS panel informativity by selecting genomic intervals to maximize patient coverage while minimizing panel size.

1 citation

whole-exome sequencingstatistical model

𝕏 PostBluesky