Publications by authors named "S Granjeaud"
Mass cytometry enables deep profiling of biological samples at single-cell resolution. This technology is more than relevant in cancer research due to high cellular heterogeneity and complexity. Downstream analysis of high-dimensional datasets increasingly relies on machine learning (ML) to extract clinically relevant information, including supervised algorithms for classification and regression purposes.
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- The LSC-17 score, based on a gene expression profile related to stemness, indicates poor outcomes in acute myeloid leukemia (AML), but how leukemic stem cell anchoring affects disease progression is unclear.
- Conditional inactivation of the adhesion molecule JAM-C in a mouse model of AML showed that its deletion affected HSC expansion but not disease initiation or progression, revealing insights into leukemic cell behavior in the bone marrow niche.
- Findings suggest that the AP-1/TNF-α gene signature, which correlated with different prognosis in AML, provides additional prognostic information alongside the LSC-17 score, highlighting the importance of niche interactions in leukemia.
Article Synopsis
- In patients with acute myeloid leukemia (AML), a higher presence of Vγ9Vδ2 T cells at diagnosis is associated with better overall and relapse-free survival rates.
- This study analyzed immunophenotypic data from 198 newly diagnosed AML patients to determine how Vγ9Vδ2 T-cell frequency impacts prognosis while adjusting for various confounding factors.
- The findings support the importance of Vγ9Vδ2 T cells in AML prognosis and suggest potential treatment strategies that could boost these T-cell responses in patients.
IMPRINTS-CETSA (Integrated Modulation of Protein Interaction States-Cellular Thermal Shift Assay) provides a highly resolved means to systematically study the interactions of proteins with other cellular components, including metabolites, nucleic acids and other proteins, at the proteome level, but no freely available and user-friendly data analysis software has been reported. Here, we report IMPRINTS.CETSA, an R package that provides the basic data processing framework for robust analysis of the IMPRINTS-CETSA data format, from preprocessing and normalization to visualization.
View Article and Find Full Text PDFSummary: DIAgui is an R package to simplify the processing of the report file from the DIA-NN software thanks to a Shiny application. It returns the quantification of either the precursors, the peptides, the proteins, or the genes thanks to the MaxLFQ algorithm. In addition, the latest version provides the Top3 and iBAQ quantification and the number of peptides used for the quantification.
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