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Plasma cells (PCs) play an important role in the adaptive immune system through a continuous production of antibodies. We have demonstrated that PC differentiation can be modeled in vitro using complex multistep culture systems reproducing sequential differentiation process occurring in vivo. Here we present a comprehensive, temporal program of gene expression data encompassing human PC differentiation (PCD) using RNA sequencing (RNA-seq). Our results reveal 6374 differentially expressed genes classified into four temporal gene expression patterns. A stringent pathway enrichment analysis of these gene clusters highlights known pathways but also pathways largely unknown in PCD, including the heme biosynthesis and the glutathione conjugation pathways. Additionally, our analysis revealed numerous novel transcriptional networks with significant stage-specific overexpression and potential importance in PCD, including BATF2, BHLHA15/MIST1, EZH2, WHSC1/MMSET, and BLM. We have experimentally validated a potent role for BLM in regulating cell survival and proliferation during human PCD. Taken together, this RNA-seq analysis of PCD temporal stages helped identify coexpressed gene modules with associated up/downregulated transcription regulator genes that could represent major regulatory nodes for human PC maturation. These data constitute a unique resource of human PCD gene expression programs in support of future studies for understanding the underlying mechanisms that control PCD.

DNA microarrays have considerably helped to improve the understanding of biological processes and diseases. Large amounts of publicly available microarray data are accumulating, but are poorly exploited due to a lack of easy-to-use bioinformatics resources. The aim of this study is to build a free and convenient data-mining web site (www.genomicscape.com). GenomicScape allows mining dataset from various microarray platforms, identifying genes differentially expressed between populations, clustering populations, visualizing expression profiles of large sets of genes, and exporting results and figures. We show how easily GenomicScape makes it possible to construct a molecular atlas of the B cell differentiation using publicly available transcriptome data of naïve B cells, centroblasts, centrocytes, memory B cells, preplasmablasts, plasmablasts, early plasma cells and bone marrow plasma cells. Genes overexpressed in each population and the pathways encoded by these genes are provided as well as how the populations cluster together. All the analyses, tables and figures can be easily done and exported using GenomicScape and this B cell to plasma cell atlas is freely available online. Beyond this B cell to plasma cell atlas, the molecular characteristics of any biological process can be easily and freely investigated by uploading the corresponding transcriptome files into GenomicScape.

FCRL4 is an immunoregulatory receptor that belongs to the Fc receptor-like (FCRL) family. In healthy individuals, FCRL4 is specifically expressed by memory B cells (MBCs) localized in sub-epithelial regions of lymphoid tissues. Expansion of FCRL4+ B cells has been observed in blood and other tissues in various infectious and autoimmune disorders. Currently, the mechanisms involved in pathological FCRL4+ B cell generation are actively studied, but they remain elusive. As in vivo FCRL4+ cells are difficult to access and to isolate, here we developed a culture system to generate in vitro FCRL4+ B cells from purified MBCs upon stimulation with soluble CD40 ligand and/or CpG DNA to mimic T-cell dependent and/or T-cell independent activation, respectively. After 4 days of stimulation, FCRL4+ B cells represented 17% of all generated cells. Transcriptomic and phenotypic analyses of in vitro generated FCRL4+ cells demonstrated that they were closely related to FCRL4+ tonsillar MBCs. They strongly expressed inhibitory receptor genes, as observed in exhausted FCRL4+ MBCs from blood samples of HIV-infected individuals with high viremia. In agreement, cell cycle genes were significantly downregulated and the number of cell divisions was two-fold lower in in vitro generated FCRL4+ than FCRL4- cells. Finally, due to their reduced proliferation and differentiation potential, FCRL4+ cells were less prone to differentiate into plasma cells, differently from FCRL4- cells. Our in vitro model could be of major interest for studying the biology of normal and pathological FCRL4+ cells.

BackgroundTumor immune cells influence the efficacy of immune-checkpoint inhibitors (ICIs) and many efforts aim at identifying features of tumor immune microenvironment able to predict benefit from ICIs in proficient mismatch repair (pMMR)/microsatellite stable (MSS) metastatic colorectal cancer (mCRC).MethodsWe characterized tumor immune cell infiltrate, by assessing tumor-infiltrating lymphocytes (TILs), Immunoscore, Immunoscore-IC, and programmed death ligand-1 (PD-L1) expression in tumor samples of patients with mCRC enrolled in the AtezoTRIBE study, a phase II randomized trial comparing FOLFOXIRI/bevacizumab/atezolizumab to FOLFOXIRI/bevacizumab, with the aim of evaluating the prognostic and predictive value of these features.ResultsOut of 218 patients enrolled, 181 (83%), 77 (35%), 157 (72%) and 162 (74%) specimens were successfully tested for TILs, Immunoscore, Immunoscore-IC and PD-L1 expression, respectively, and 69 (38%), 45 (58%), 50 (32%) and 21 (13%) tumors were classified as TILs-high, Immunoscore-high, Immunoscore-IC-high and PD-L1-high, respectively. A poor agreement was observed between TILs and Immunoscore or Immunoscore-IC (K of Cohen <0.20). In the pMMR population, longer progression-free survival (PFS) was reported for Immunoscore-high and Immunoscore-IC-high groups compared with Immunoscore-low (16.4 vs 12.2 months; HR: 0.55, 95% CI: 0.30 to 0.99; p=0.049) and Immunoscore-IC-low (14.8 vs 11.5 months; HR: 0.55, 95% CI: 0.35 to 0.85; p=0.007), respectively, with a significant interaction effect between treatment arms and Immunoscore-IC (p for interaction: 0.006) and a trend for Immunoscore (p for interaction: 0.13). No PFS difference was shown according to TILs and PD-L1 expression. Consistent results were reported in the overall population.ConclusionsThe digital evaluation of tumor immune cell infiltrate by means of Immunoscore-IC or Immunoscore identifies the subset of patients with pMMR mCRC achieving more benefit from the addition of the anti-PD-L1 to the upfront treatment. Immunoscore-IC stands as the most promising predictor of benefit from ICIs.

BackgroundMultiple myeloma (MM) is the second most common hematologic malignancy. Aberrant epigenetic modifications have been reported in MM and could be promising therapeutic targets. As response rates are overall limited but deep responses occur, it is important to identify those patients who could indeed benefit from epigenetic-targeted therapy.MethodsSince HDACi and DNMTi combination have potential therapeutic value in MM, we aimed to build a GEP-based score that could be useful to design future epigenetic-targeted combination trials. In addition, we investigated the changes in GEP upon HDACi/DNMTi treatment.ResultsWe report a new gene expression-based score to predict MM cell sensitivity to the combination of DNMTi/HDACi. A high Combo score in MM patients identified a group with a worse overall survival but a higher sensitivity of their MM cells to DNMTi/HDACi therapy compared to a low Combo score. In addition, treatment with DNMTi/HDACi downregulated IRF4 and MYC expression and appeared to induce a mature BMPC plasma cell gene expression profile in myeloma cell lines.ConclusionIn conclusion, we developed a score for the prediction of primary MM cell sensitivity to DNMTi/HDACi and found that this combination could be beneficial in high-risk patients by targeting proliferation and inducing maturation.

Adjunction of immune response into the TNM classification system improves the prediction of colon cancer (CC) prognosis. However, immune response measurements have not been used as robust biomarkers of pathology in clinical practice until the introduction of Immunoscore (IS), a standardized assay based on automated artificial intelligence assisted digital pathology. The strong prognostic impact of the immune response, as assessed by IS, has been widely validated and IS can help to refine treatment decision making in early CC. In this study, we compared pathologist visual scoring to IS. Four pathologists evaluated tumor specimens from 50 early-stage CC patients and classified the CD3+ and CD8+ T-cell densities at the tumor site (T-score) into 2 (High/Low) categories. Individual and overall pathologist scoring of immune response (before and after training for immune response assessment) were compared to the reference IS (High/Low). Pathologists’ disagreement with the reference IS was observed in almost half of the cases (48%) and training only slightly improved the accuracy of pathologists’ classification. Agreement among pathologists was minimal with a Kappa of 0.34 and 0.57 before and after training, respectively. The standardized IS assay outperformed expert pathologist assessment in the clinical setting.

Background Multiple myeloma (MM) is a malignant plasma cell disease with a poor survival, characterized by the accumulation of myeloma cells (MMCs) within the bone marrow. Epigenetic modifications in MM are associated not only with cancer development and progression, but also with drug resistance. Methods We identified a significant upregulation of the polycomb repressive complex 2 (PRC2) core genes in MM cells in association with proliferation. We used EPZ-6438, a specific small molecule inhibitor of EZH2 methyltransferase activity, to evaluate its effects on MM cells phenotype and gene expression prolile. Results PRC2 targeting results in growth inhibition due to cell cycle arrest and apoptosis together with polycomb, DNA methylation, TP53, and RB1 target genes induction. Resistance to EZH2 inhibitor is mediated by DNA methylation of PRC2 target genes. We also demonstrate a synergistic effect of EPZ-6438 and lenalidomide, a conventional drug used for MM treatment, activating B cell transcription factors and tumor suppressor gene expression in concert with MYC repression. We establish a gene expression-based EZ score allowing to identify poor prognosis patients that could benefit from EZH2 inhibitor treatment. Conclusions These data suggest that PRC2 targeting in association with IMiDs could have a therapeutic interest in MM patients characterized by high EZ score values, reactivating B cell transcription factors, and tumor suppressor genes.

BackgroundTumor-infiltrating immune cells play an important role against cancer and are critical to controlling tumor growth and spread. Immunotherapy drugs such as immune checkpoint inhibitors, despite inducing long-term responses in many cancer types, remain ineffective for a majority of patients. A better understanding of the tumor microenvironment (TME), and the characterization of populations of immune cells, their activation status, spatial distribution, and relationship, along with cytokine signaling, may help to better stratify patients and explain mechanisms of resistance to immunotherapy.Veracyte’s Brightplex® is a chromogenic multiplex immunohistochemistry (IHC) technology that leverages digital pathology enhanced by artificial intelligence. It allows the detection of up to eight biomarkers on a single FFPE slide to identify cellular subpopulations. However, to characterize the exact role of an immune cell it is often necessary to determine if it expresses soluble proteins which cannot be detected by IHC, such as cytokines or activation factors. In that case, the detection of the corresponding RNA transcripts by in situ hybridization (ISH) can be used as a substitute for protein detection.MethodsHere, we propose a multiplex technology automated on the Leica Bond RX platform which combines ISH and IHC staining on a single FFPE tissue section. In brief, that tissue section is sequentially stained to detect biomarkers of interest either with antibodies for proteins or nucleic probes for transcripts. Each round of staining is followed by the digitization of the slide. Whole slide images are fused to create a virtual multi-channel image where biomarkers are detected by digital pathology and combined to identify immune cell populations. The spatial distribution and cell-to-cell interactions within a slide or between multiple adjacent slides are assessed by combining multiplex ISH/IHC panels.ResultsThis technology allowed us to quantify different sub-populations of tumor-infiltrating-lymphocytes (activated, cytotoxic and exhausted), interferon-γ producing cells, and tumor-associated-macrophages expressing the chemokine CXCL9. We investigated the spatial distribution of these immune cells within the TME. We also assessed the cell-to-cell proximity between these populations to assess their interactions.ConclusionsIntegrated into an Immunogram, an analytics platform that integrates multi-omics datasets from Veracyte Biopharma Atlas, this new tool could be a powerful solution to decipher the tumor landscape and predict response to immunotherapy and patient outcome.

High throughput DNA microarray has made it possible to outline genes whose expression in malignant plasma cells is associated with short overall survival of patients with Multiple Myeloma (MM). A further step is to elucidate the mechanisms encoded by these genes yielding to drug resistance and/or patients' short survival. We focus here on the biological role of the DEP (for Disheveled, EGL-10, Pleckstrin) domain contained protein 1A (DEPDC1A), a poorly known protein encoded by DEPDC1A gene, whose high expression in malignant plasma cells is associated with short survival of patients. Using conditional lentiviral vector delivery of DEPDC1A shRNA, we report that DEPDC1A knockdown delayed the growth of human myeloma cell lines (HMCLs), with a block in G2 phase of the cell cycle, p53 phosphorylation and stabilization, and p21(Cip1) accumulation. DEPDC1A knockdown also resulted in increased expression of mature plasma cell markers, including CXCR4, IL6-R and CD38. Thus DEPDC1A could contribute to the plasmablast features of MMCs found in some patients with adverse prognosis, blocking the differentiation of malignant plasma cells and promoting cell cycle.

BackgroundImmune checkpoint inhibitors (ICIs) are associated with long-term survival in ~20% of advanced NSCLC patients while biological mechanisms triggering resistance are not fully elucidated. The PIONeeR project (NCT03493581, ANR-17-RHUS-0007) aims to predict the response/resistance to PD1/L1 ICIs in advanced NSCLC patients through comprehensive agnostic multiparametric biomarkers assessment. The immune system is crucial for tumor evolution and is composed of different subsets of immune cells that can be activating (T-, B-lymphocytes, ...) or regulating such as regulatory T-cells (Treg).MethodsTumor was sampled at diagnosis from 101 advanced pretreated NSCLC patients, ECOG PS0/1, treated with standard PD1/L1 ICIs monotherapy. Complete database of ≥2nd line PIONeeR patients was released in July 2023. Overall Response Rate was assessed by RECIST 1.1. Multiplex IHC Brightplex® T-cells exhaustion quantifies cytotoxic (Tc) (CD3+CD8+) and helper (Th) (CD3+CD8-) T-lymphocytes in both tumor parenchyma and stroma. This quantification allows stratification into 4 tumor groups: Hot, Parenchyma Hot, Cold and Stroma Tumor Infiltrating Lymphocytes (TILs).1 2 Dual staining CD4 FOXP3 quantifies Treg density in parenchyma and stroma. Correlation analyses: spearman non-parametric test. Samples’ classification: unsupervised neural-network-based machine learning algorithm Self-Organizing Maps (SOM). Statistical significance of progression-free/overall survival (PFS/OS) differences: log-rank test. Response distribution differences: Fisher’s test.ResultsPatients were mainly male (65%), current/previous smoker (92%), <70yrs (68%) with median PFS=4.4months. Across the 101 tumors, Treg were not strongly correlated to any other cell type (Tc: R=0.54, Th: R=0.59). As expected, Brightplex® TCE identified 4 patient groups based on Th/Tc infiltration revealing outcome differences: Hot (N=32), Cold (N=19), Parenchyma Hot (N=15) and Stroma TILs (N=35). Each group was stratified according to Th/Treg infiltration. The 35 Stroma TILs patients (median PFS=6.4) were split into 4 groups (SOM): low Th/Treg-infiltration (N=10); Th-only parenchyma-infiltration (N=7); intermediate Treg+Th infiltration in both compartments (N=9); Treg+Th high infiltration (N=9). The two lowest infiltrated groups had poorer outcome (median PFS=1.6/1.8; median OS=6.9/7.4 respectively) than both infiltrated groups (median PFS=17.3/14.1; median OS=17.3/not reached respectively), p=4.1e-4. 10/11 responders were part of both infiltrated groups (p=2.6e-3) regardless of PDL1 status.ConclusionsTreg infiltration evaluation improved previous lymphocyte-associated NSCLC classification regarding response to anti-PD1/L1 ICIs.1 2 Absence of Treg, regardless of Th cells infiltration, in the Stroma TILs patient subset, was associated with early progression and poor survival. These unexpected results were already described in some cancers and could be linked to Tregs’ ability to suppress general inflammation that itself triggers cell proliferation and metastasis.AcknowledgementsThis work benefited from a government grant handled by the French National Research Agency (ANR) as part of the France 2030 investment plan, under the reference ANR-17-RHUS-0007. A partnership of AMU, AP-HM, CNRS, Inserm, Centre Léon Bérard, Institut Paoli-Calmettes, AstraZeneca, Veracyte, Innate Pharma & ImCheck Therapeutics, sponsored by AP-HM and initiated by Marseille Immunopole. Drug supply is funded by AstraZeneca.Trial RegistrationNCT03493581ReferencesGhezali L, Landri M, Monville F, et al. Brightplex® TCE and Brightplex® MDSC assays combination improves NSCLC patients’ stratification under anti-PD1/L1 immunotherapy in the PIONeeR project. Journal for ImmunoTherapy of Cancer 2022;10.Leca V, Kassambara A, Ghezali L, et al. Spatial distribution of infiltrating T lymphocytes with Immunoscore® CR T Cells Exhaustion test helps stratification of NSCLC patients treated with PD1/PDL1 inhibitors in the PIONeeR project. Journal for ImmunoTherapy of Cancer 2021;9.Ethics ApprovalThe study is conducted in accordance with Good Clinical Practice and the French applicable regulatory requirements (Public Health Code, article L.1121-1/La loi n° 2012–300 du 5 mars 2012 relative aux recherches impliquant la personne humaine (dite loi Jardé), the applicable subject privacy requirements, and the ethical principles that are outlined in the Declaration of Helsinski. The study was approved by the French Ethic Committee, CPP Ouest II - Angers, ref. CPP: 2028/08, Ref ANSM (French competent authority) 2018020500208, 2018072600120, 2019083000148. Freely given written informed consent was signed and obtained from each individual participating in the study, before any study specific procedure was undertaken and after the provision of information about the study by the investigator during a physician-patient consultation and sufficient time for reflection.