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GRANJEAUD, S.

Publications and source records attributed to GRANJEAUD, S..

2 recordsLinked to original sources

CytoBatchNorm: an R package with graphical interface for batch effects correction of cytometry data

Innovation in cytometry propelled it to an almost "omic" dimension technique during the last decade. The application fields concomitantly enlarged, resulting in generation of high-dimensional high-content data sets which have to be adequately designed, handled and analyzed. Experimental solutions and detailed data processing pipelines were developed to reduce both the staining conditions variability between samples and the number of tubes to handle. However, an unavoidable variability appears between samples, barcodes, series and instruments (in multicenter studies) contributing to "batch effects" that must be properly controlled. Computer aid to this aim is necessary, and several methods have been published so far, but configuring and carrying out batch normalization remains unintuitive for scientists with "pure" academic backgrounds in biology. To address this challenge, we developed an R package called CytoBatchNorm that offers an intuitive and user-friendly graphical interface. Although the processing is based on the script by Schuyler et al., the graphical interface revolutionizes its use. CytoBatchNorm enables users to define a specific correction for each marker in a single run. It provides a graph that guides you through quickly setting the correction for each marker. It allows corrections to be previewed and inter-marker effects to be checked as the settings are made. CytoBatchNorm will help the cytometry community to adequately scale data between batches, reliably reducing batch effects and improving subsequent dimension reduction and clustering. VISUAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=129 SRC="FIGDIR/small/596492v1_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@600a1eorg.highwire.dtl.DTLVardef@13860cborg.highwire.dtl.DTLVardef@5ad915org.highwire.dtl.DTLVardef@6218dc_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

Tertiary lymphoid structures are associated with enhanced macrophage and dendritic cell activation and proximity to CD8+ T cells, which better predict the clinical outcome of cervical cancer patients

BackgroundCervical tumors are usually treated using surgery, chemotherapy, and radiotherapy, and would benefit from immunotherapies. However, the immune microenvironment in cervical cancer remains poorly described. Tertiary lymphoid structures (TLS) were recently described as markers for better immunotherapy response and overall better prognosis in cancer patients. MethodsWe integratedly evaluated the cervical tumor immune microenvironment, and specifically TLS importance, using combined high-throughput phenotyping, soluble factor dosage, spatial interaction analyses, and statistical analyses. ResultsWe demonstrate that TLS presence is associated with a more inflammatory soluble microenvironment, with the presence of B cells as well as more activated macrophages and dendritic cells (DCs). Furthermore, this myeloid cell activation is associated with expression of immune checkpoints, such as PD-L1 and CD40, and close proximity of activated conventional DC2 to CD8+ T cells, therefore indicating better immune interactions and tumor control. Finally, we associate TLS presence, greater B cell density, and activated DC density to improved progression-free survival, and present it as an additional prognostic marker. ConclusionTo conclude, our results provide an exhaustive depiction of the cervical tumor immune microenvironment where TLS presence marks cell activation and immunotherapy target expression. These findings provide predictive clues for patient response to targeted immunotherapies. SignificanceTLS maturation stratifies cervical cancer patients and associates with improved prognosis. TLS associate with the expression of immune checkpoints, notably in the macrophage compartment, which may represent a new therapeutic strategy.

immunology↗