Immune landscape in Burkitt lymphoma reveals M2-macrophage polarization and correlation between PD-L1 expression and non-canonical EBV latency program (original) (raw)
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Large scale microarray profiling reveals four stages of immune escape in Non-Hodgkin Lymphomas
OncoImmunology, 2016
Non-Hodgkin B-cell lymphoma (B-NHL) are aggressive lymphoid malignancies that develop in patients due to oncogenic activation, chemo-resistance, and immune evasion. Tumor biopsies show that B-NHL frequently uses several immune escape strategies, which has hindered the development of checkpoint blockade immunotherapies in these diseases. To gain a better understanding of B-NHL immune editing, we hypothesized that the transcriptional hallmarks of immune escape associated with these diseases could be identified from the meta-analysis of large series of microarrays from B-NHL biopsies. Thus, 1446 transcriptome microarrays from seven types of B-NHL were downloaded and assembled from 33 public Gene Expression Omnibus (GEO) datasets, and a method for scoring the transcriptional hallmarks in single samples was developed. This approach was validated by matching scores to phenotypic hallmarks of B-NHL such as proliferation, signaling, metabolic activity, and leucocyte infiltration. Through this method, we observed a significant enrichment of 33 immune escape genes in most diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL) samples, with fewer in mantle cell lymphoma (MCL) and marginal zone lymphoma (MZL) samples. Comparing these gene expression patterns with overall survival data evidenced four stages of cancer immune editing in B-NHL: non-immunogenic tumors (stage 1), immunogenic tumors without immune escape (stage 2), immunogenic tumors with immune escape (stage 3), and fully immuno-edited tumors (stage 4). This model complements the standard international prognostic indices for B-NHL and proposes that immune escape stages 3 and 4 (76% of the FL and DLBCL samples in this data set) identify patients relevant for checkpoint blockade immunotherapies.
Gene expression analysis uncovers similarity and differences among Burkitt lymphoma subtypes
Blood, 2011
Burkitt lymphoma (BL) is classified into 3 clinical subsets: endemic, sporadic, and immunodeficiency-associated BL. So far, possible differences in their gene expression profiles (GEPs) have not been investigated. We studied GEPs of BL subtypes, other B-cell lymphomas, and B lymphocytes; first, we found that BL is a unique molecular entity, distinct from other B-cell malignancies. Indeed, by unsupervised analysis all BLs clearly clustered apart of other lymphomas. Second, we found that BL subtypes presented slight differences in GEPs. Particularly, they differed for genes involved in cell cycle control, B-cell receptor signaling, and tumor necrosis factor/nuclear factor B pathways. Notably, by reverse engineering, we found that endemic and sporadic BLs diverged for genes dependent on RBL2 activity. Furthermore, we found that all BLs were intimately related to germinal center cells, differing from them for molecules involved in cell proliferation, immune response, and signal transduction. Finally, to validate GEP, we applied immunohistochemistry to a large panel of cases and showed that RBL2 can cooperate with MYC in inducing a neoplastic phenotype in vitro and in vivo. In conclusion, our study provided substantial insights on the pathobiology of BLs, by offering novel evidences that may be relevant for its classification and possibly future treatment. (Blood. 2011;117(13): 3596-3608)
Blood, 2010
Several gene-expression signatures predict survival in diffuse large B-cell lymphoma (DLBCL), but the lack of practical methods for genome-scale analysis has limited translation to clinical practice. We built and validated a simple model using one gene expressed by tumor cells and another expressed by host immune cells, assessing added prognostic value to the clinical International Prognostic Index (IPI). LIM domain only 2 (LMO2) was validated as an independent predictor of survival and the "germinal center B cell-like" subtype. Expression of tumor necrosis factor receptor superfamily member 9 (TNFRSF9) from the DLBCL microenvironment was the best gene in bivariate combination with LMO2. Study of TNFRSF9 tissue expression in 95 patients with DLBCL showed expression limited to infiltrating T cells. A model integrating these 2 genes was independent of "cell-of-origin" classification, "stromal signatures," IPI, and added to the predictive power of the IPI. A composite score integrating these genes with IPI performed well in 3 independent cohorts of 545 DLBCL patients, as well as in a simple assay of routine formalin-fixed specimens from a new validation cohort of 147 patients with DLBCL. We conclude that the measurement of a single gene expressed by tumor cells (LMO2) and a single gene expressed by the immune microenvironment (TNFRSF9) powerfully predicts overall survival in patients with DLBCL.
Erciyes Medical Journal, 2021
Primary central nervous system lymphoma (PCNSL) is a rare and aggressive extranodal variant of non-Hodgkin lymphomas with disease confined to the brain, spinal cord, leptomeninges, or orbit, without evidence of systemic involvement. PCNSL has a poor prognosis, with a median overall survival of 30-50 months. We used NanoString Technologies to characterize the cancer immune profiles in PCNSL and associated the findings with clinical outcome. Materials and Methods: A total of 33 patients between 2005 and 2017 were included in our study, and clinical information was collected. A PanCancer IO 360 panel (NanoString Technologies) was used to assess the expression level of 770 genes related to tumor immunity in 12 samples. We also investigated the programmed death ligand 1 (PD-L1) expression and T-cell infiltrate in 25 PCNSL samples using immunohistochemistry. Results: NanoString analysis showed that gene expressions differed between human immunodeficiency virus (HIV)-positive and HIV-negative PCNSL. We identified four genes with deregulated expressions (adjusted p<0.05) with a cluster enrichment in cytotoxicity, DNA damage repair, interferon signaling, and lymphoid compartment-related genes. Furthermore, we found that PD-L1 was expressed in 9 of 25 (36%) cases and 11 had increased CD3+ T-cell infiltrates. However, increased PD-L1 expression and CD3+ T-cell infiltrates were not correlated with the clinical outcome. Conclusion: Our data reveals a distinct PCNSL tumor microenvironment and immune landscape. However, our study needs to be validated in a larger population.
2022
Although a lymph node infiltrated by classic Hodgkin lymphoma is mostly composed of non-neoplastic immune cells, the malignant Hodgkin Reed-Sternberg cells (HRSC) successfully suppress an anti-tumor immune response, to create a cancer-permissive microenvironment. Accordingly, unleashing the dormant immune cells, for example by checkpoint inhibition, has been a central focus of recent therapeutic advances for this disease. Here, we profiled the global immune cell composition of normal and diseased lymph nodes by single-cell RNA sequencing, as a basis for interrogating the immediate vicinity of HRSC, first regionally and then at cellular resolution. Our analyses revealed specific immune cells and functional states associated with HRSC. Most prominently, we discovered a non-random spatial association of immunoregulatory mononuclear phagocytes positioned around HRSC, which express the immune checkpoints PD-L1, TIM-3, and the tryptophan-catabolizing protein IDO1. These findings provide a...
Human tumors contain populations of both cancerous and host immune cells whose malignant signaling interactions may define each patient's disease trajectory. We used multiplexed phospho-flow cytometry to profile single cells within human follicular lymphoma tumors and discovered a subpopulation of lymphoma cells with impaired B cell antigen receptor (BCR) signaling. The abundance of BCR-insensitive cells in each tumor negatively correlated with overall patient survival. These lymphoma negative prognostic (LNP) cells increased as tumors relapsed following chemotherapy. Loss of antigen receptor expression did not explain the absence of BCR signaling in LNP tumor cells, and other signaling responses were intact in these cells. Furthermore, BCR signaling responses could be reactivated in LNP cells, indicating that BCR signaling is not missing but rather specifically suppressed. LNP cells were also associated with changes to signaling interactions in the tumor microenvironment. Lower IL-7 signaling in tumor infiltrating T cells was observed in tumors with high LNP cell counts. The strength of signaling through T cell mediator of B cell function CD40 also stratified patient survival, particularly for those whose tumors contained few LNP cells. Thus, analysis of cell-cell interactions in heterogeneous primary tumors using signaling network profiles can identify and mechanistically define new populations of rare and clinically significant cells. Both the existence of these LNP cells and their aberrant signaling profiles provide targets for new therapies for follicular lymphoma.
Immunological network signatures of cancer progression and survival
BMC Medical Genomics, 2011
Background The immune contribution to cancer progression is complex and difficult to characterize. For example in tumors, immune gene expression is detected from the combination of normal, tumor and immune cells in the tumor microenvironment. Profiling the immune component of tumors may facilitate the characterization of the poorly understood roles immunity plays in cancer progression. However, the current approaches to analyze the immune component of a tumor rely on incomplete identification of immune factors. Methods To facilitate a more comprehensive approach, we created a ranked immunological relevance score for all human genes, developed using a novel strategy that combines text mining and information theory. We used this score to assign an immunological grade to gene expression profiles, and thereby quantify the immunological component of tumors. This immunological relevance score was benchmarked against existing manually curated immune resources as well as high-throughput studies. To further characterize immunological relevance for genes, the relevance score was charted against both the human interactome and cancer information, forming an expanded interactome landscape of tumor immunity. We applied this approach to expression profiles in melanomas, thus identifying and grading their immunological components, followed by identification of their associated protein interactions. Results The power of this strategy was demonstrated by the observation of early activation of the adaptive immune response and the diversity of the immune component during melanoma progression. Furthermore, the genome-wide immunological relevance score classified melanoma patient groups, whose immunological grade correlated with clinical features, such as immune phenotypes and survival. Conclusions The assignment of a ranked immunological relevance score to all human genes extends the content of existing immune gene resources and enriches our understanding of immune involvement in complex biological networks. The application of this approach to tumor immunity represents an automated systems strategy that quantifies the immunological component in complex disease. In so doing, it stratifies patients according to their immune profiles, which may lead to effective computational prognostic and clinical guides.
Pan-cancer analysis identifies PD-L2 as a tumor promotor in the tumor microenvironment
Frontiers in Immunology
BackgroundProgrammed cell death protein 1 (PD-1) receptor has two ligands,programmed death-ligand 1 (PD-L1) and PD-L2. When compared with PD-L1, PD-L2 has not received much attention, and its role remains unclear.MethodsThe expression profiles of pdcd1lg2 (PD-L2-encoding gene) mRNA and PD-L2 protein were analyzed using TCGA, ICGC, and HPA databases. Kaplan-Meier and Cox regression analyses were used to assess the prognostic significance of PD-L2. We used GSEA, Spearman’s correlation analysis and PPI network to explore the biological functions of PD-L2. PD-L2-associated immune cell infiltration was evaluated using the ESTIMATE algorithm and TIMER 2.0. The expressions of PD-L2 in tumor-associated macrophages (TAMs) in human colon cancer samples, and in mice in an immunocompetent syngeneic setting were verified using scRNA-seq datasets, multiplex immunofluorescence staining, and flow cytometry. After fluorescence-activated cell sorting, flow cytometry and qRT-PCR and transwell and colo...