BCL2 and BCL6 atypical/unbalanced gene rearrangements in diffuse large B-cell lymphoma are indicators of an aggressive clinical course

International audienceAims Diffuse large B-cell lymphoma (DLBCL) is the most common type of aggressive non-Hodgkin's lymphoma that represents a heterogeneous group of disease that is differentially characterised by clinical, molecular and cytogenetic features. MYC , BCL2 and BCL6 gene rearrangements have been identified as prognostic factors in DLBCL, especially for MYC . Nevertheless the frequency and effect of atypical/unbalanced BCL6, BCL2 and MYC translocations in DLBCL is not fully documented. Here, we aimed to analyse those atypical/unbalanced rearrangements in DLBCL and to assess their prognostic impact. Methods We collected tumour tissue and clinical data from 97 DLBCL and used interphase fluorescence in situ hybridisation (FISH) with break-apart probe to characterise BCL6, BCL2 and MYC gene pattern. Results 19 of 97 (19,6%) cases of DLBCL had atypical/ unbalanced gene rearrangements (14 involving BCL6 gene, 5 involving BCL2 gene and none involving MYC gene). Compared with patients with simple gene rearrangement and patients without cytogenetic abnormality, patients with atypical/unbalanced gene rearrangement were in an unfavourable risk group by the International Prognostic Index (p=0039), died of disease (p=0012), harboured relapse or progression (p=0011) and had shorter overall (p=0,04), relapse free (p=0029) and event free (p=0026) survival. Conclusions We showed that patients with DLBCL with BCL2 or BCL6 atypical/unbalanced rearrangements constituted a group of patients with poor outcome. We also underlined the importance of FISH analyses, easily feasible in routine practise, at diagnosis of DLBCL to detect the rather frequent and clinically significant atypical/unbalanced aberrations of these genes

Primal-Dual for Classification with Rejection (PD-CR): A novel method for classification and feature selection. An application in metabolomics studies

International audienceBackground: Supervised classification methods have been used for many years for feature selection in metabolomics and other omics studies. We developed a novel primal-dual based classification method (PD-CR) that can perform classification with rejection and feature selection on high dimensional datasets. PD-CR projects data onto a low dimension space and performs classification by minimizing an appropriate quadratic cost. It simultaneously optimizes the selected features and the prediction accuracy with a new tailored, constrained primal-dual method. The primal-dual framework is general enough to encompass various robust losses and to allow for convergence analysis. Here, we compare PD-CR to three commonly used methods : Partial Least Squares Discriminant Analysis (PLS-DA), Random Forests and Support Vector Machines (SVM). We analyzed two metabolomics datasets: one urinary metabolomics dataset concerning lung cancer patients and healthy controls; and a metabolomics dataset obtained from frozen glial tumor samples with mutated isocitrate dehydrogenase (IDH) or wild-type IDH. Results: PD-CR was more accurate than PLS-DA, Random Forests and SVM for classification using the 2 metabolomics datasets. It also selected biologically relevant metabolites. PD-CR has the advantage of providing a confidence score for each prediction, which can be used to perform classification with rejection. This substantially reduces the False Discovery Rate. Conclusion: PD-CR is an accurate method for classification of metabolomics datasets which can outperform PLS-DA, Random Forests and SVM while selecting biologically relevant features. Furthermore the confidence score provided with PD-CR can be used to perform classification with rejection and reduce the false discovery rate

Proof of concept for AAV2/5-mediated gene therapy in iPSC-derived retinal pigment epithelium of a choroideremia patient

Inherited retinal dystrophies (IRDs) comprise a large group of genetically and clinically heterogeneous diseases that lead to progressive vision loss, for which a paucity of disease-mimicking animal models renders preclinical studies difficult. We sought to develop pertinent human cellular IRD models, beginning with choroideremia, caused by mutations in the CHM gene encoding Rab escort protein 1 (REP1). We reprogrammed REP1-deficient fibroblasts from a CHM-/y patient into induced pluripotent stem cells (iPSCs), which we differentiated into retinal pigment epithelium (RPE). This iPSC-derived RPE is a polarized monolayer with a classic morphology, expresses characteristic markers, is functional for fluid transport and phagocytosis, and mimics the biochemical phenotype of patients. We assayed a panel of adeno-associated virus (AAV) vector serotypes and showed that AAV2/5 is the most efficient at transducing the iPSC-derived RPE and that CHM gene transfer normalizes the biochemical phenotype. The high, and unmatched, in vitro transduction efficiency is likely aided by phagocytosis and mimics the scenario that an AAV vector encounters in vivo in the subretinal space. We demonstrate the superiority of AAV2/5 in the human RPE and address the potential of patient iPSC–derived RPE to provide a proof-of-concept model for gene replacement in the absence of an appropriate animal model

A comprehensive profiling of the immune microenvironment of breast cancer brain metastases

Background: Despite potential clinical implications, the complexity of breast cancer (BC) brain metastases (BM) immune microenvironment is poorly understood. Through multiplex immunofluorescence, we here describe the main features of BCBM immune microenvironment (density and spatial distribution) and evaluate its prognostic impact. Methods: Sixty BCBM from patients undergoing neurosurgery at three institutions (2003-2018) were comprehensively assessed using two multiplex immunofluorescence panels (CD4, CD8, Granzyme B, FoxP3, CD68, pan-cytokeratin, DAPI; CD3, PD-1, PD-L1, LAG-3, TIM-3, CD163, pan-cytokeratin, DAPI). The prognostic impact of immune subpopulations and cell-to-cell spatial interactions was evaluated. Results: Subtype-related differences in BCBM immune microenvironment and its prognostic impact were observed. While in HR−/HER2− BM and HER2+ BM, higher densities of intra-tumoral CD8+ lymphocytes were associated with significantly longer OS (HR 0.16 and 0.20, respectively), in HR+/HER2− BCBMs a higher CD4+FoxP3+/CD8+ cell ratio in the stroma was associated with worse OS (HR 5.4). Moreover, a higher density of intra-tumoral CD163+ M2-polarized microglia/macrophages in BCBMs was significantly associated with worse OS in HR−/HER2− and HR+/HER2− BCBMs (HR 6.56 and 4.68, respectively), but not in HER2+ BCBMs. In HER2+ BCBMs, multiplex immunofluorescence highlighted a negative prognostic role of PD-1/PD-L1 interaction: patients with a higher percentage of PD-L1+ cells spatially interacting with (within a 20 µm radius) PD-1+ cells presented a significantly worse OS (HR 4.60). Conclusions: Our results highlight subtype-related differences in BCBM immune microenvironment and identify two potential therapeutic targets, M2 microglia/macrophage polarization in HER2− and PD-1/PD-L1 interaction in HER2+ BCBMs, which warrant future exploration in clinical trials