Gene expression meta-analysis reveals immune response convergence on the IFNγ-STAT1-IRF1 axis and adaptive immune resistance mechanisms in lymphoma

IRF5 mediates adaptive immunity via altered glutamine metabolism, mTORC1 signaling and post-transcriptional regulation following T cell receptor activation

Although dynamic alterations in transcriptional, translational, and metabolic programs have been described in T cells, the factors and pathways guiding these molecular shifts are poorly understood, with recent studies revealing a disassociation between transcriptional responses and protein expression following T cell receptor (TCR) stimulation. Previous studies identified interferon regulatory factor 5 (IRF5) in the transcriptional regulation of cytokines, chemotactic molecules and T effector transcription factors following TCR signaling. In this study, we identified T cell intrinsic IRF5 regulation of mTORC1 activity as a key modulator of CD40L protein expression. We further demonstrated a global shift in T cell metabolism, with alterations in glutamine metabolism accompanied by shifts in T cell populations at the single cell level due to loss of Irf5. T cell conditional Irf5 knockout mice in a murine model of experimental autoimmune encephalomyelitis (EAE) demonstrated protection from clinical disease with conserved defects in mTORC1 activity and glutamine regulation. Together, these findings expand our mechanistic understanding of IRF5 as an intrinsic regulator of T effector function(s) and support the therapeutic targeting of IRF5 in multiple sclerosis.

The Oncogenic Lipid Sphingosine-1-Phosphate Impedes the Phagocytosis of Tumor Cells by M1 Macrophages in Diffuse Large B Cell Lymphoma

BACKGROUND

A total of 30-40% of diffuse large B cell lymphoma (DLBCL) patients will either not respond to the standard therapy or their disease will recur. The first-line treatment for DLBCL is rituximab and combination chemotherapy. This treatment involves the chemotherapy-induced recruitment of tumor-associated macrophages that recognize and kill rituximab-opsonized DLBCL cells. However, we lack insights into the factors responsible for the recruitment and functionality of macrophages in DLBCL tumors.

METHODS

We have studied the effects of the immunomodulatory lipid sphingosine-1-phosphate (S1P) on macrophage activity in DLBCL, both in vitro and in animal models.

RESULTS

We show that tumor-derived S1P mediates the chemoattraction of both monocytes and macrophages in vitro and in animal models, an effect that is dependent upon the S1P receptor S1PR1. However, S1P inhibited M1 macrophage-mediated phagocytosis of DLBCL tumor cells opsonized with the CD20 monoclonal antibodies rituximab and ofatumumab, an effect that could be reversed by an S1PR1 inhibitor.

CONCLUSIONS

Our data show that S1P signaling can modulate macrophage recruitment and tumor cell killing by anti-CD20 monoclonal antibodies in DLBCL. The administration of S1PR1 inhibitors could enhance the phagocytosis of tumor cells and improve outcomes for patients.

Genomic crossroads between non-Hodgkin's lymphoma and common variable immunodeficiency

Common variable immunodeficiency (CVID) represents the largest group of primary immunodeficiencies that may manifest with infections, inflammation, autoimmunity, and cancer, mainly B-cell non-Hodgkin's lymphoma (NHL). Indeed, NHL may result from chronic or recurrent infections and has, therefore, been recognized as a clinical phenotype of CVID, although rare. The more one delves into the mechanisms involved in CVID and cancer, the stronger the idea that both pathologies can be a reflection of the same primer events observed from different angles. The potential effects of germline variants on specific somatic modifications in malignancies suggest that it might be possible to anticipate critical events during tumor development. In the same way, a somatic alteration in NHL could be conditioning a similar response at the transcriptional level in the shared signaling pathways with genetic germline alterations in CVID. We aimed to explore the genomic substrate shared between these entities to better characterize the CVID phenotype immunodeficiency in NHL. By means of an in-silico approach, we interrogated the large, publicly available datasets contained in cBioPortal for the presence of genes associated with genetic pathogenic variants in a panel of 50 genes recurrently altered in CVID and previously described as causative or disease-modifying. We found that 323 (25%) of the 1,309 NHL samples available for analysis harbored variants of the CVID spectrum, with the most recurrent alteration presented in NHL occurring in PIK3CD (6%) and STAT3 (4%). Pathway analysis of common gene alterations showed enrichment in inflammatory, immune surveillance, and defective DNA repair mechanisms similar to those affected in CVID, with PIK3R1 appearing as a central node in the protein interaction network. The co-occurrence of gene alterations was a frequent phenomenon. This study represents an attempt to identify common genomic grounds between CVID and NHL. Further prospective studies are required to better know the role of genetic variants associated with CVID and their reflection on the somatic pathogenic variants responsible for cancer, as well as to characterize the CVID-like phenotype in NHL, with the potential to influence early CVID detection and therapeutic management.

Weighted deep factorizing heterogeneous molecular network for genome-phenome association prediction

Genome-phenome association (GPA) prediction can promote the understanding of biological mechanisms about complex pathology of phenotypes (i.e., traits and diseases). Traditional heterogeneous network-based GPA approaches overwhelmingly need to project heterogeneous data toward homogeneous network for data fusion and prediction, such projections result in the loss of heterogeneous network structure information. Matrix factorization based data fusion can avoid such projection by integrating multi-type data in a coherent way, but they typically perform linear factorization and cannot mine the nonlinear relationships between molecules, which compromise the accuracy of GPA analysis. Furthermore, most of them can not selectively synergy network topology and node attribution information in a principle way. In this paper, we propose a weighted deep matrix factorization based solution (WDGPA) to predict GPAs by selectively and differentially fusing heterogeneous molecular network and diverse attributes of nodes. WDGPA firstly assigns weights to inter/intra-relational data matrices and attribute data matrices, and performs deep matrix factorization on these matrices of heterogeneous network in a cooperative manner to obtain the nonlinear representations of different nodes. In addition, it performs low-rank representation learning on the attribute data with the shared nonlinear representations. In this way, both the network topology and node attributes are jointly mined to explore the representations of molecules and complex interplays between molecules and phenotypes. WDGPA then uses the representational vectors of gene and phenotype nodes to predict GPAs. Experimental results on maize and human datasets confirm that WDGPA outperforms competitive methods by a large margin under different evaluation protocols.

Integrative OMICS Data-Driven Procedure Using a Derivatized Meta-Analysis Approach

The wealth of high-throughput data has opened up new opportunities to analyze and describe biological processes at higher resolution, ultimately leading to a significant acceleration of scientific output using high-throughput data from the different omics layers and the generation of databases to store and report raw datasets. The great variability among the techniques and the heterogeneous methodologies used to produce this data have placed meta-analysis methods as one of the approaches of choice to correlate the resultant large-scale datasets from different research groups. Through multi-study meta-analyses, it is possible to generate results with greater statistical power compared to individual analyses. Gene signatures, biomarkers and pathways that provide new insights of a phenotype of interest have been identified by the analysis of large-scale datasets in several fields of science. However, despite all the efforts, a standardized regulation to report large-scale data and to identify the molecular targets and signaling networks is still lacking. Integrative analyses have also been introduced as complementation and augmentation for meta-analysis methodologies to generate novel hypotheses. Currently, there is no universal method established and the different methods available follow different purposes. Herein we describe a new unifying, scalable and straightforward methodology to meta-analyze different omics outputs, but also to integrate the significant outcomes into novel pathways describing biological processes of interest. The significance of using proper molecular identifiers is highlighted as well as the potential to further correlate molecules from different regulatory levels. To show the methodology’s potential, a set of transcriptomic datasets are meta-analyzed as an example.

Comparative analysis of gene expression platforms for cell-of-origin classification of diffuse large B-cell lymphoma shows high concordance

Cell-of-origin subclassification of diffuse large B cell lymphoma (DLBCL) into activated B cell-like (ABC), germinal centre B cell-like (GCB) and unclassified (UNC) or type III by gene expression profiling is recommended in the latest update of the World Health Organization's classification of lymphoid neoplasms. There is, however, no accepted gold standard method or dataset for this classification. Here, we compare classification results using gene expression data for 68 formalin-fixed paraffin-embedded DLBCL samples measured on four different gene expression platforms (Illumina wG-DASL^TM arrays, Affymetrix PrimeView arrays, Illumina TrueSeq RNA sequencing and the HTG EdgeSeq DLBCL Cell of Origin Assay EU using an established platform agnostic classification algorithm (DAC) and the classifier native to the HTG platform, which is CE marked for in vitro diagnostic use (CE-IVD). Classification methods and platforms show a high level of concordance, with agreement in at least 80% of cases and rising to much higher levels for classifications of high confidence. Our results demonstrate that cell-of-origin classification by gene expression profiling on different platforms is robust, and that the use of the confidence value alongside the classification result is important in clinical applications.

Matrix Metallopeptidase 14: A Candidate Prognostic Biomarker for Diffuse Large B-Cell Lymphoma

Background

Matrix metallopeptidase 14 (MMP14) is an important gene in the regulation of T-cell function. However, the correlation between MMP14 expression, prognosis, and immune cell infiltration in diffuse large B-cell lymphoma (DLBCL) remains unclear.

Methods

We investigated the influence of MMP14 on clinical prognosis using data obtained from three Gene Expression Omnibus (GEO) database sets (GSE98588, GSE10846, and GSE4475). The expression of MMP14 was analyzed using the Gene Expression Profiling Interactive Analysis (GEPIA). The correlation between MMP14 and immune cell infiltration was investigated using the Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) and Tumor Immune Estimation Resource (TIMER) tools. In addition, the correlation between MMP14 expression and immune gene markers was analyzed by TIMER and GEPIA.

Results

MMP14 expression positively correlated with favorable progression-free survival (PFS; GSE98588, P = 0.02) and overall survival (OS; GSE98588, P = 0.003; GSE10846, P = 5.517e-05; and GSE4475, P = 9.85e-04). Moreover, MMP14 expression was higher in DLBCL tumors than in normal tissues. Regarding clinical characteristics, high MMP14 expression was found to be correlated with race. MMP14 expression was also correlated with immune cell infiltration and had a remarkable correlation with various immune marker sets. It was found that M0 macrophages were the immune cells most related to survival, decreasing with the increase in Ann Arbor clinical stage. The results especially showed that MMP14 was a prognostic biomarker and related to the macrophages M0.

Conclusion

The results suggest that MMP14 is a novel prognostic molecular marker for DLBCL and is related to the immune cell infiltration, especially related to the macrophages M0. Our study provides insights for understanding the potential roles of MMP14 in tumor immunology and its suitability as a prognosis biomarker in DLBCL.

Sensitization to immune checkpoint blockade through activation of a STAT1/NK axis in the tumor microenvironment

Cancer immunotherapy using antibodies that target immune checkpoints has delivered outstanding results. However, responses only occur in a subset of patients, and it is not fully understood what biological processes determine an effective outcome. This lack of understanding hinders the development of rational combination treatments. We set out to define the pretreatment microenvironment associated with an effective outcome by using the fact that inbred mouse strains bearing monoclonal cancer cell line-derived tumors respond in a dichotomous manner to immune checkpoint blockade (ICB). We compared the cellular composition and gene expression profiles of responsive and nonresponsive tumors from mice before ICB and validated the findings in cohorts of patients with cancer treated with ICB antibodies. We found that responsive tumors were characterized by an inflammatory gene expression signature consistent with up-regulation of signal transducer and activator of transcription 1 (STAT1) and Toll-like receptor 3 (TLR3) signaling and down-regulation of interleukin-10 (IL-10) signaling. In addition, responsive tumors had more infiltrating-activated natural killer (NK) cells, which were necessary for response. Pretreatment of mice with large established tumors using the STAT1-activating cytokine interferon-γ (IFNγ), the TLR3 ligand poly(I:C), and an anti-IL-10 antibody sensitized tumors to ICB by attracting IFNγ-producing NK cells into the tumor, resulting in increased cure rates. Our results identify a pretreatment tumor microenvironment that predicts response to ICB, which can be therapeutically attained. These data suggest a biomarker-driven approach to patient management to establish whether a patient would benefit from treatment with sensitizing therapeutics before ICB.

Early Pregnancy Induces Expression of STAT1, OAS1 and CXCL10 in Ovine Spleen

Interferon-tau is a maternal recognition factor in ruminant species, and spleen plays an essential role in regulating innate and adaptive immune responses. However, it is not fully understood that early pregnancy induces expression of interferon stimulated genes (ISGs) in the spleen during early pregnancy in ewes. In this study, spleens were collected from ewes at day 16 of the estrous cycle, and on days 13, 16, and 25 of gestation (n = 6 for each group), and RT-qPCR, western blot and immunohistochemistry analysis were used to detect the expression of signal transducer and activator of transcription 1 (STAT1), 2',5'-oligoadenylate synthetase 1 (OAS1), myxovirusresistance protein 1 (Mx1) and C-X-C motif chemokine 10 (CXCL10). The results revealed that STAT1, OAS1 and CXCL10 mRNA and proteins were upregulated in the spleens during early pregnancy, and STAT1 protein was located in connective tissue cells in the capsule and trabeculae, and blood cells and lymphocytes in the red pulp. However, early pregnancy had no significant effects on expression of MX1 mRNA and protein. In conclusion, early pregnancy induces expression of STAT1, OAS1 and CXCL10 in maternal spleen, suggesting that maternal spleen is involved in immune regulation of pregnancy in sheep.

DNA damage repair gene mutations and their association with tumor immune regulatory gene expression in muscle invasive bladder cancer subtypes

BACKGROUND

Molecular subtyping of urothelial cancer (UC) has significantly advanced the understanding of bladder tumor heterogeneity and development of prognostic and predictive biomarkers. Evolving evidence across cancers strongly suggests that tumor immunoediting has a profound impact on the behaviour of cancer cells and their adaptation to the co-evolving microenvironment and response to treatment. In alignment with these concepts, recent immune checkpoint blockade (ICB) therapies in UC have demonstrated the predictive potential of mutations in the DNA damage repair (DDR) genes. A comprehensive understanding of DDR gene inactivation associated expression of immune regulatory genes could thus aid in expansion of current immunotherapies and predictive biomarkers for the design of patient-tailored combination treatments.

METHODS

We investigated pre-treatment tumor transcriptomic profiles of the five recently described molecular subtypes of muscle invasive urothelial cancer (MIUC; n = 408) from The Cancer Genome Atlas, to determine subtype specific immune cell abundance, expression of 67 immune regulatory genes, and association with DDR gene inactivation (via mutation, copy number alteration) profiles.

RESULTS

Analysis using CIBERSORT immune cell abundance determination tool showed significant differences in immune cell profiles and abundance between MIUC subtypes. Expression patterns of a selected panel of 67 genes including both immune stimulatory and inhibitory genes, showed significant associations with subtypes, and DDR gene mutation status.

CONCLUSION

Findings from our study provide compelling evidence for co-expression of multiple immune checkpoint genes including, PD-1, PD-L1, IDO1, TIGIT, TIM-3, TGFB1, LAG3, and others, that potentially contribute to compensatory immune evasion in bladder tumors. Our findings also emphasize the urgent need for biomarker discovery approaches that combine molecular subtype, DDR gene mutation status, tumor immune landscape classification, and immune checkpoint gene expression to increase the number of patients responding to immunotherapies.

Regulation of S1PR2 by the EBV oncogene LMP1 in aggressive ABC-subtype diffuse large B-cell lymphoma

The Epstein-Barr virus (EBV) is found almost exclusively in the activated B-cell (ABC) subtype of diffuse large B-cell lymphoma (DLBCL), yet its contribution to this tumour remains poorly understood. We have focused on the EBV-encoded latent membrane protein-1 (LMP1), a constitutively activated CD40 homologue expressed in almost all EBV-positive DLBCLs and which can disrupt germinal centre (GC) formation and drive lymphomagenesis in mice. Comparison of the transcriptional changes that follow LMP1 expression with those that follow transient CD40 signalling in human GC B cells enabled us to define pathogenic targets of LMP1 aberrantly expressed in ABC-DLBCL. These included the down-regulation of S1PR2, a sphingosine-1-phosphate (S1P) receptor that is transcriptionally down-regulated in ABC-DLBCL, and when genetically ablated leads to DLBCL in mice. Consistent with this, we found that LMP1-expressing primary ABC-DLBCLs were significantly more likely to lack S1PR2 expression than were LMP1-negative tumours. Furthermore, we showed that the down-regulation of S1PR2 by LMP1 drives a signalling loop leading to constitutive activation of the phosphatidylinositol-3-kinase (PI3-K) pathway. Finally, core LMP1-PI3-K targets were enriched for lymphoma-related transcription factors and genes associated with shorter overall survival in patients with ABC-DLBCL. Our data identify a novel function for LMP1 in aggressive DLBCL. Copyright © 2019 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Sphingosine-1-phosphate signalling drives an angiogenic transcriptional programme in diffuse large B cell lymphoma

Although the over-expression of angiogenic factors is reported in diffuse large B-cell lymphoma (DLBCL), the poor response to anti-VEGF drugs observed in clinical trials suggests that angiogenesis in these tumours might be driven by VEGF-independent pathways. We show that sphingosine kinase-1 (SPHK1), which generates the potent bioactive sphingolipid sphingosine-1-phosphate (S1P), is over-expressed in DLBCL. A meta-analysis of over 2000 cases revealed that genes correlated with SPHK1 mRNA expression in DLBCL were significantly enriched for tumour angiogenesis meta-signature genes; an effect evident in both major cell of origin (COO) and stromal subtypes. Moreover, we found that S1P induces angiogenic signalling and a gene expression programme that is present within the tumour vasculature of SPHK1-expressing DLBCL. Importantly, S1PR1 functional antagonists, including Siponimod, and the S1P neutralising antibody, Sphingomab, inhibited S1P signalling in DLBCL cells in vitro. Furthermore, Siponimod, also reduced angiogenesis and tumour growth in an S1P-producing mouse model of angiogenic DLBCL. Our data define a potential role for S1P signalling in driving an angiogenic gene expression programme in the tumour vasculature of DLBCL and suggest novel opportunities to target S1P-mediated angiogenesis in patients with DLBCL.

STING agonist therapy in combination with PD-1 immune checkpoint blockade enhances response to carboplatin chemotherapy in high-grade serous ovarian cancer

Background

High-grade serous carcinoma (HGSC) of the ovary is predominantly diagnosed at late stages and primarily treated with debulking surgery followed by platinum/taxane-based chemotherapy. Although certain patients benefit significantly from currently used chemotherapy, there are patients who either do not respond or have an inadequate duration of response. We previously showed that tumours from chemoresistant patients have an immunosuppressed pre-existing tumour immune microenvironment with decreased expression of Type I Interferon (IFN1) genes.

Methods

Efficacy of a ‘STimulator of INterferon Genes’ agonist was evaluated in combination with carboplatin chemotherapy and PD-1 immune checkpoint blockade therapy in the ID8-Trp53^−/− immunocompetent murine model of HGSC.

Results

Treatment with STING agonist led to decreased ascites accumulation and decreased tumour burden. Survival of mice treated with a combination of carboplatin, STING agonist and anti-PD-1 antibody was the longest. Tumour immune transcriptomic profiling revealed higher IFN response, antigen presentation and MHC II genes in tumours from STING agonist-treated mice compared to vehicle controls. Flow cytometry analysis revealed significantly higher intra-tumoural PD-1⁺ and CD69⁺CD62L⁻, CD8⁺ T cells in STING agonist-treated mice.

Conclusions

These findings will enable rational design of clinical trials aimed at combinatorial approaches to improve chemotherapy response and survival in HGSC patients.

Molecular heterogeneity in diffuse large B-cell lymphoma and its implications in clinical diagnosis and treatment

Over half of patients with diffuse large B-cell lymphoma (DLBCL) can be cured by standard R-CHOP treatment (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone). However, the remaining patients are refractory and ultimately succumb to progressive or relapsed disease. During the past decade, there has been significant progress in the understanding of molecular mechanisms in DLBCL, largely owing to collaborative efforts in large-scale gene expression profiling and deep sequencing, which have identified genetic alterations critical in lymphomagenesis through activation of key signaling transduction pathways in DLBCL. These discoveries have not only led to the development of targeted therapies, including several currently in clinical trials, but also laid a solid foundation for the future identification of more effective therapies for patients not curable by R-CHOP. This review summarizes the recent advances in our understanding of the molecular characterization and pathogenesis of DLBCL and new treatment directions.

PD-1-PD-L1 immune-checkpoint blockade in B-cell lymphomas

Cancer cells can escape T-cell-mediated cellular cytotoxicity by exploiting the inhibitory programmed cell-death protein 1 (PD-1)/programmed cell death 1 ligand 1 (PD-L1) immune checkpoint. Indeed, therapeutic antibodies that block the PD-1-PD-L1 axis induce durable clinical responses against a growing list of solid tumours. B-cell lymphomas also leverage this checkpoint to escape immune recognition, although the outcomes of PD-1-PD-L1 blockade, and the correlations between PD-L1 expression and treatment responses, are less-well elucidated in these diseases than in solid cancers. Nevertheless, in patients with Hodgkin lymphoma, amplification of the gene encoding PD-L1 is commonly associated with increased expression of this protein on Reed-Sternberg cells. Correspondingly, PD-1 blockade with nivolumab has been demonstrated to result in response rates as high as 87% in unselected patients with relapsed and/or refractory Hodgkin lymphoma, leading to the FDA approval of nivolumab for this indication in May 2016. The PD-1/PD-L1 axis is probably also important for immune evasion of B-cell lymphomas with a viral aetiology, including those associated with human immunodeficiency virus (HIV) and Epstein-Barr virus (EBV). This Review is focused on the role of PD-1-PD-L1 blockade in unleashing host antitumour immune responses against various B-cell lymphomas, and summarizes the clinical studies of this approach performed to date.