DEK regulates B-cell proliferative capacity and is associated with aggressive disease in low-grade B-cell lymphomas.

This study sheds light on the pivotal role of the oncoprotein DEK in B-cell lymphoma. We reveal DEK expression correlates with increased tumor proliferation and inferior overall survival in cases diagnosed with low-grade B-cell lymphoma (LGBCL). We also found significant correlation between DEK expression and copy number alterations in LGBCL tumors, highlighting a novel mechanism of LGBCL pathogenesis that warrants additional exploration. To interrogate the mechanistic role of DEK in B-cell lymphoma, we generated a DEK knockout cell line model, which demonstrated DEK depletion caused reduced proliferation and altered expression of key cell cycle and apoptosis-related proteins, including Bcl-2, Bcl-xL, and p53. Notably, DEK depleted cells showed increased sensitivity to apoptosis-inducing agents, including venetoclax and staurosporine, which underscores the therapeutic potential of targeting DEK in B-cell lymphomas. Overall, our study contributes to a better understanding of DEK's role as an oncoprotein in B-cell lymphomas, highlighting its potential as both a promising therapeutic target and a novel biomarker for aggressive LGBCL. Further research elucidating the molecular mechanisms underlying DEK-mediated tumorigenesis could pave the way for improved treatment strategies and better clinical outcomes for patients with B-cell lymphoma.

Applications of artificial intelligence to myeloproliferative neoplasms: a narrative review.

INTRODUCTION: Artificial intelligence (AI) is a rapidly growing field of computational research with the potential to extract nuanced biomarkers for the prediction of outcomes of interest. AI implementations for the prediction for clinical outcomes for myeloproliferative neoplasms (MPNs) are currently under investigation. AREAS COVERED: In this narrative review, we discuss AI investigations for the improvement of MPN clinical care utilizing either clinically available data or experimental laboratory findings. Abstracts and manuscripts were identified upon querying PubMed and the American Society of Hematology conference between 2000 and 2023. Overall, multidisciplinary researchers have developed AI methods in MPNs attempting to improve diagnostic accuracy, risk prediction, therapy selection, or pre-clinical investigations to identify candidate molecules as novel therapeutic agents. EXPERT OPINION: It is our expert opinion that AI methods in MPN care and hematology will continue to grow with increasing clinical utility. We believe that AI models will assist healthcare workers as clinical decision support tools if appropriately developed with AI-specific regulatory guidelines. Though the reported findings in this review are early investigations for AI in MPNs, the collective work developed by the research community provides a promising framework for improving decision-making in the future of MPN clinical care.

Graph Fourier transform for spatial omics representation and analyses of complex organs.

Spatial omics technologies decipher functional components of complex organs at cellular and subcellular resolutions. We introduce Spatial Graph Fourier Transform (SpaGFT) and apply graph signal processing to a wide range of spatial omics profiling platforms to generate their interpretable representations. This representation supports spatially variable gene identification and improves gene expression imputation, outperforming existing tools in analyzing human and mouse spatial transcriptomics data. SpaGFT can identify immunological regions for B cell maturation in human lymph nodes Visium data and characterize variations in secondary follicles using in-house human tonsil CODEX data. Furthermore, it can be integrated seamlessly into other machine learning frameworks, enhancing accuracy in spatial domain identification, cell type annotation, and subcellular feature inference by up to 40%. Notably, SpaGFT detects rare subcellular organelles, such as Cajal bodies and Set1/COMPASS complexes, in high-resolution spatial proteomics data. This approach provides an explainable graph representation method for exploring tissue biology and function.

Multiomics analysis of IgM monoclonal gammopathies reveals epigenetic influence on oncogenesis via DNA methylation.

ABSTRACT: Currently, the role of DNA methylation in the immunoglobulin M (IgM) monoclonal gammopathy disease spectrum remains poorly understood. In the present study, a multiomics prospective analysis was conducted integrating DNA methylation, RNA sequencing (RNA-seq), and whole-exome sequencing data in 34 subjects (23 with Waldenström macroglobulinemia [WM], 6 with IgM monoclonal gammopathy of undetermined significance [MGUS], and 5 normal controls). Analysis was focused on defining differences between IgM gammopathies (WM/IgM-MGUS) compared with controls, and specifically between WM and IgM-MGUS. Between groups, genome-wide DNA methylation analysis demonstrated a significant number of differentially methylated regions that were annotated according to genomic region. Next, integration of RNA-seq data was performed to identify potentially epigenetically deregulated pathways. We found that pathways involved in cell cycle, metabolism, cytokine/immune signaling, cytoskeleton, tumor microenvironment, and intracellular signaling were differentially activated and potentially epigenetically regulated. Importantly, there was a positive enrichment of the CXCR4 signaling pathway along with several interleukin (interleukin 6 [IL-6], IL-8, and IL-15) signaling pathways in WM compared with IgM-MGUS. Further assessment of known tumor suppressor genes and oncogenes uncovered differential promoter methylation of several targets with concordant change in gene expression, including CCND1 and CD79B. Overall, this report defines how aberrant DNA methylation in IgM gammopathies may play a critical role in the epigenetic control of oncogenesis and key cellular functions.

Multiomic analysis identifies a high-risk signature that predicts early clinical failure in DLBCL.

Recent genetic and molecular classification of DLBCL has advanced our knowledge of disease biology, yet were not designed to predict early events and guide anticipatory selection of novel therapies. To address this unmet need, we used an integrative multiomic approach to identify a signature at diagnosis that will identify DLBCL at high risk of early clinical failure. Tumor biopsies from 444 newly diagnosed DLBCL were analyzed by WES and RNAseq. A combination of weighted gene correlation network analysis and differential gene expression analysis was used to identify a signature associated with high risk of early clinical failure independent of IPI and COO. Further analysis revealed the signature was associated with metabolic reprogramming and identified cases with a depleted immune microenvironment. Finally, WES data was integrated into the signature and we found that inclusion of ARID1A mutations resulted in identification of 45% of cases with an early clinical failure which was validated in external DLBCL cohorts. This novel and integrative approach is the first to identify a signature at diagnosis, in a real-world cohort of DLBCL, that identifies patients at high risk for early clinical failure and may have significant implications for design of therapeutic options.

Follicular lymphoma B cells exhibit heterogeneous transcriptional states with associated somatic alterations and tumor microenvironments.

Follicular lymphoma (FL) is an indolent non-Hodgkin lymphoma of germinal center origin, which presents with significant biologic and clinical heterogeneity. Using RNA-seq on B cells sorted from 87 FL biopsies, combined with machine-learning approaches, we identify 3 transcriptional states that divide the biological ontology of FL B cells into inflamed, proliferative, and chromatin-modifying states, with relationship to prior GC B cell phenotypes. When integrated with whole-exome sequencing and immune profiling, we find that each state was associated with a combination of mutations in chromatin modifiers, copy-number alterations to TNFAIP3, and T follicular helper cells (Tfh) cell interactions, or primarily by a microenvironment rich in activated T cells. Altogether, these data define FL B cell transcriptional states across a large cohort of patients, contribute to our understanding of FL heterogeneity at the tumor cell level, and provide a foundation for guiding therapeutic intervention.

MicroRNA and long non-coding RNA analysis in IgM monoclonal gammopathies reveals epigenetic influence on cellular functions and oncogenesis.

Not available.

Multiomic Analysis Identifies a High-Risk Metabolic and TME Depleted Signature that Predicts Early Clinical Failure in DLBCL.

PURPOSE: 60-70% of newly diagnosed diffuse large B-cell lymphoma (DLBCL) patients avoid events within 24 months of diagnosis (EFS24) and the remainder have poor outcomes. Recent genetic and molecular classification of DLBCL has advanced our knowledge of disease biology, yet were not designed to predict early events and guide anticipatory selection of novel therapies. To address this unmet need, we used an integrative multiomic approach to identify a signature at diagnosis that will identify DLBCL at high risk of early clinical failure. PATIENTS AND METHODS: Tumor biopsies from 444 newly diagnosed DLBCL were analyzed by WES and RNAseq. A combination of weighted gene correlation network analysis and differential gene expression analysis followed by integration with clinical and genomic data was used to identify a multiomic signature associated with high risk of early clinical failure. RESULTS: Current DLBCL classifiers are unable to discriminate cases who fail EFS24. We identified a high risk RNA signature that had a hazard ratio (HR, 18.46 [95% CI 6.51-52.31] P < .001) in a univariate model, which did not attenuate after adjustment for age, IPI and COO (HR, 20.8 [95% CI, 7.14-61.09] P < .001). Further analysis revealed the signature was associated with metabolic reprogramming and a depleted immune microenvironment. Finally, WES data was integrated into the signature and we found that inclusion of ARID1A mutations resulted in identification of 45% of cases with an early clinical failure which was validated in external DLBCL cohorts. CONCLUSION: This novel and integrative approach is the first to identify a signature at diagnosis that will identify DLBCL at high risk for early clinical failure and may have significant implications for design of therapeutic options.

Molecular classification and identification of an aggressive signature in low-grade B-cell lymphomas.

Non-follicular low-grade B-cell lymphomas (LGBCL) are biologically diverse entities that share clinical and histologic features that make definitive pathologic categorization challenging. While most patients with LGBCL have an indolent course, some experience aggressive disease, highlighting additional heterogeneity across these subtypes. To investigate the potential for shared biology across subtypes, we performed RNA sequencing and applied machine learning approaches that identified five clusters of patients that grouped independently of subtype. One cluster was characterized by inferior outcome, upregulation of cell cycle genes, and increased tumor immune cell content. Integration of whole exome sequencing identified novel LGBCL mutations and enrichment of TNFAIP3 and BCL2 alterations in the poor survival cluster. Building on this, we further refined a transcriptomic signature associated with early clinical failure in two independent cohorts. Taken together, this study identifies unique clusters of LGBCL defined by novel gene expression signatures and immune profiles associated with outcome across diagnostic subtypes.

Sonicate Fluid Cellularity Predicted by Transcriptomic Deconvolution Differentiates Infectious from Non-Infectious Arthroplasty Failure.

BACKGROUND: Although cellularity is traditionally assessed morphologically, deep sequencing approaches being used for microorganism detection may be able to provide information about cellularity. We hypothesized that cellularity predicted using CIBERSORTx (Stanford University), a transcriptomic-based cellular deconvolution tool, would differentiate between infectious and non-infectious arthroplasty failure. METHODS: CIBERSORTx-derived cellularity profiles of 93 sonicate fluid samples, including 53 from subjects who underwent failed arthroplasties due to periprosthetic joint infection (PJI) (abbreviated for the purpose of this study as PJIF) and 40 from subjects who had undergone non-infectious arthroplasty failure (abbreviated NIAF) that had been subjected to bulk RNA sequencing were evaluated. RESULTS: Samples from PJIF and NIAF subjects were differentially clustered by principal component analysis based on the cellularity profile. Twelve of the 22 individual predicted cellular fractions were differentially expressed in the PJIF cases compared with the NIAF cases, including increased predicted neutrophils (mean and standard error, 9.73% ± 1.06% and 0.81% ± 0.60%), activated mast cells (17.12% ± 1.51% and 4.11% ± 0.44%), and eosinophils (1.96% ± 0.37% and 0.42% ± 0.21%), and decreased predicted M0 macrophages (21.33% ± 1.51% and 39.75% ± 2.45%), M2 macrophages (3.56% ± 0.52% and 8.70% ± 1.08%), and regulatory T cells (1.57% ± 0.23% and 3.20% ± 0.34%). The predicted total granulocyte fraction was elevated in the PJIF cases (32.97% ± 2.13% and 11.76% ± 1.61%), and the samples from the NIAF cases had elevated predicted total macrophage and monocyte (34.71% ± 1.71% and 55.34% ± 2.37%) and total B cell fractions (5.89% ± 0.30% and 8.62% ± 0.86%). Receiver operating characteristic curve analysis identified predicted total granulocytes, neutrophils, and activated mast cells as highly able to differentiate between the PJIF cases and the NIAF cases. Within the PJIF cases, the total granulocyte, total macrophage and monocyte, M0 macrophage, and M2 macrophage fractions were differentially expressed in Staphylococcus aureus compared with Staphylococcus epidermidis -associated samples. Within the NIAF cases, the predicted total B cell, naïve B cell, plasma cell, and M2 macrophage fractions were differentially expressed among different causes of failure. CONCLUSIONS: CIBERSORTx can predict the cellularity of sonicate fluid using transcriptomic data, allowing for the evaluation of the underlying immune response during the PJIF and NIAF cases, without a need to phenotypically assess cell composition.

Molecular Clusters and Tumor-Immune Drivers of IgM Monoclonal Gammopathies.

PURPOSE: IgM monoclonal gammopathy of undetermined significance (MGUS) and Waldenström macroglobulinemia (WM) represent a disease spectrum with highly varied therapeutic management, ranging from observation to chemoimmunotherapy. The current classification relies solely on clinical features and does not explain the heterogeneity that exists within each of these conditions. Further investigation is warranted to shed light on the biology that may account for the clinical differences. EXPERIMENTAL DESIGN: We used bone marrow (BM) clonal CD19+ and/or CD138+ sorted cells, matched BM supernatant, and peripheral blood serum from 32 patients (7 MGUS, 25 WM) to perform the first multi-omics approach including whole-exome sequencing, RNA sequencing, proteomics, metabolomics, and mass cytometry. RESULTS: We identified three clusters with distinct pathway activation, immune content, metabolomic, and clinical features. Cluster 1 included only patients with WM and was characterized by transcriptional silencing of genes involved in cell cycle and immune response, enrichment of mitochondrial metabolism, infiltration of senescent T effector memory cells, and aggressive clinical behavior. Genetic/structural alterations of TNFAIP3 were distinct events of this cluster. Cluster 2 comprised both MGUS and WM patients with upregulation of inflammatory response, senescence and glycolysis signatures, increased activated T follicular helper and T regulatory cells, and indolent clinical behavior. Cluster 3 also included both MGUS and WM patients and exhibited intermediate features, including proliferative and inflammatory signaling, as well as glycolysis and mitochondrial metabolism. CONCLUSIONS: We have identified three distinct molecular clusters, suggesting a potential biologic classification that may have therapeutic implications.

Phenotype, Function, and Clinical Significance of CD26+ and CD161+Tregs in Splenic Marginal Zone Lymphoma.

PURPOSE: Regulatory T-cells (Treg) are essential to Tregs homeostasis and modulate the antitumor immune response in patients with lymphoma. However, the biology and prognostic impact of Tregs in splenic marginal zone lymphoma (SMZL) have not been studied. EXPERIMENTAL DESIGN: Biopsy specimens from 24 patients with SMZL and 12 reactive spleens (rSP) from individuals without lymphoma were analyzed by using CITE-seq (cellular indexing of transcriptomes and epitopes by sequencing), CyTOF (mass cytometry) analysis, and flow cytometry to explore the phenotype, transcriptomic profile, and clinical significance of intratumoral Tregs and their subsets. The biological characteristics and cell signaling pathways of intratumoral Treg subsets were confirmed by in vitro functional assays. RESULTS: We found that Tregs are more abundant in SMZL patients' spleens than rSP, and Tregs from patients with SMZL and rSP can be separated into CD161+Treg and CD26+Treg subsets. CD161+Tregs are increased in SMZL but have dysregulated immune function. We found that CD161+Treg and CD26+Tregs have unique gene expression and phenotypic profiles and are differentially correlated with patient outcomes. Specifically, increased CD161+Tregs are significantly associated with a favorable prognosis in patients with SMZL, whereas CD26+Tregs are associated with a poor prognosis. Furthermore, activation of the IL2/STAT5 pathway contributes to the induction of CD26+Tregs and can be reversed by STAT5 inhibition. CONCLUSIONS: IL2/STAT5-mediated expansion of CD26+Tregs contributes to a poor clinical outcome in SMZL and may represent a therapeutic opportunity in this disease.

Chronic lymphocytic leukemia B-cell-derived TNFα impairs bone marrow myelopoiesis.

TNFα is implicated in chronic lymphocytic leukemia (CLL) immunosuppression and disease progression. TNFα is constitutively produced by CLL B cells and is a negative regulator of bone marrow (BM) myelopoiesis. Here, we show that co-culture of CLL B cells with purified normal human hematopoietic stem and progenitor cells (HSPCs) directly altered protein levels of the myeloid and erythroid cell fate determinants PU.1 and GATA-2 at the single-cell level within transitional HSPC subsets, mimicking ex vivo expression patterns. Physical separation of CLL cells from control HSPCs or neutralizing TNFα abrogated upregulation of PU.1, yet restoration of GATA-2 required TNFα neutralization, suggesting both cell contact and soluble-factor-mediated regulation. We further show that CLL patient BM myeloid progenitors are diminished in frequency and function, an effect recapitulated by chronic exposure of control HSPCs to low-dose TNFα. These findings implicate CLL B-cell-derived TNFα in impaired BM myelopoiesis.

Targeting of inflammatory pathways with R2CHOP in high-risk DLBCL.

Diffuse large B-cell lymphoma (DLBCL) is the most common lymphoma, and front line therapies have not improved overall outcomes since the advent of immunochemotherapy. By pairing DNA and gene expression data with clinical response data, we identified a high-risk subset of non-GCB DLBCL patients characterized by genomic alterations and expression signatures capable of sustaining an inflammatory environment. These mutational alterations (PIM1, SPEN, and MYD88 [L265P]) and expression signatures (NF-κB, IRF4, and JAK-STAT engagement) were associated with proliferative signaling, and were found to be enriched in patients treated with RCHOP that experienced unfavorable outcomes. However, patients with these high-risk mutations had more favorable outcomes when the immunomodulatory agent lenalidomide was added to RCHOP (R2CHOP). We are the first to report the genomic validation of a high-risk phenotype with a preferential response towards R2CHOP therapy in non-GCB DLBCL patients. These conclusions could be translated to a clinical setting to identify the ~38% of non-GCB patients that could be considered high-risk, and would benefit from alternative therapies to standard RCHOP based on personalized genomic data.

Somatic copy number gains in MYC, BCL2, and BCL6 identifies a subset of aggressive alternative-DH/TH DLBCL patients.

Double/triple hit lymphoma (DH/TH), known as high-grade B-cell lymphoma (HGBL), is an aggressive diffuse large B cell lymphoma (DLBCL), defined as having concurrent MYC, BCL2, and/or BCL6 gene rearrangements. While gene rearrangements represent significant genetic events in cancer, copy number alterations (CNAs) also play an important role, and their contributions to rearrangements have yet to be fully elucidated. Using FISH and high-resolution CNA data, we defined the landscape of concurrent gene rearrangements and copy gains in MYC, BCL2, and BCL6, in a cohort of 479 newly diagnosed DLBCL. We also show that concurrent translocations and copy number alterations, in combinations similar to DH/TH, identify a unique subset of DLBCL, alternative DH/TH, that have survival outcomes similar to DH/TH DLBCL patients.

TIGIT Expression Is Associated with T-cell Suppression and Exhaustion and Predicts Clinical Outcome and Anti-PD-1 Response in Follicular Lymphoma.

PURPOSE: T-cell immunoglobulin and ITIM domain (TIGIT), a member of the immune checkpoint family, is important in normal T-cell biology. However, the phenotypical profile and clinical relevance of TIGIT in follicular lymphoma is largely unknown. EXPERIMENTAL DESIGN: Biopsy specimens from a cohort of 82 patients with follicular lymphoma were analyzed using mass cytometry to explore the phenotype and biological and clinical significance of TIGIT+ T cells. RESULTS: TIGIT is highly expressed on intratumoral T cells and its expression alters T-cell phenotype in follicular lymphoma. TIGIT is abundantly expressed on Treg cells, resulting in an enhanced suppressive property. TIGIT expression on non-Treg/TFH T cells defines a population that exhibits an exhausted phenotype. Clinically, increased numbers of TIGIT+ T cells are associated with inferior patient outcomes and poor survival. We observe that anti-PD-1 therapy with pembrolizumab alters the phenotype of TIGIT+ T subsets and identifies a role for CD28 expression on TIGIT+ T cells in treatment response. CONCLUSIONS: The current study provides a comprehensive analysis of the phenotypic profile of intratumoral TIGIT+ T subsets and their prognostic relevance in follicular lymphoma. Inhibition of TIGIT signaling may be an additional mechanism to prevent T-cell suppression and exhaustion in B-cell lymphoma.

Intratumoral immune activation with TLR4 agonist synergizes with effector T cells to eradicate established murine tumors.

Effective T cell-based immunotherapy of solid malignancies requires intratumoral activity of cytotoxic T cells and induction of protective immune memory. A major obstacle to intratumoral trafficking and activation of vaccine-primed or adoptively transferred tumor-specific T cells is the immunosuppressive tumor microenvironment (TME), which currently limits the efficacy of both anti-tumor vaccines and adoptive cell therapy (ACT). Combination treatments to overcome TME-mediated immunosuppression are therefore urgently needed. We combined intratumoral administration of the synthetic toll-like receptor 4 agonist glucopyranosyl lipid A (oil-in-water formulation, G100) with either active vaccination or adoptive transfer of tumor-specific CD8 T cells to mice bearing established melanomas or orthotopically inoculated glioblastomas. In combination with cancer vaccines or ACT, G100 significantly increased expression of innate immune genes, infiltration and expansion of activated effector T cells, antigen spreading, and durable immune responses. Complete tumor regression of both injected and non-injected tumors was observed only in mice receiving combination immunotherapy. TLR4-based intratumoral immune activation may be a viable approach to enhance the efficacy of therapeutic cancer vaccines and ACT in patients.

Adaptable Angled Stereotactic Approach for Versatile Neuroscience Techniques.

Stereotactic surgery is an essential tool in the modern neuroscience lab. However, the ability to precisely and accurately target difficult-to-reach brain regions still presents a challenge, particularly when targeting brain structures along the midline. These challenges include avoiding of the superior sagittal sinus and third ventricle and the ability to consistently target selective and discrete brain nuclei. In addition, more advanced neuroscience techniques (e.g., optogenetics, fiber photometry, and two-photon imaging) rely on targeted implantation of significant hardware to the brain, and spatial limitations are a common hindrance. Presented here is a modifiable protocol for stereotactic targeting of rodent brain structures using an angled coronal approach. It can be adapted to 1) mouse or rat models, 2) various neuroscience techniques, and 3) multiple brain regions. As a representative example, it includes the calculation of stereotactic coordinates for targeting of the mouse hypothalamic ventromedial nucleus (VMN) for an optogenetic inhibition experiment. This procedure begins with the bilateral microinjection of an adeno-associated virus (AAV) encoding a light-sensitive chloride channel (SwiChR++) to a Cre-dependent mouse model, followed by the angled bilateral implantation of fiberoptic cannulae. Using this approach, findings show that activation of a subset of VMN neurons is required for intact glucose counterregulatory responses to insulin-induced hypoglycemia.

Amplification of 9p24.1 in diffuse large B-cell lymphoma identifies a unique subset of cases that resemble primary mediastinal large B-cell lymphoma.

Copy number alterations (CNAs) of 9p24.1 occur frequently in Hodgkin lymphoma, primary mediastinal large B-cell lymphoma (PMBCL), primary central nervous system lymphoma, and primary testicular lymphoma, resulting in overexpression of PD-L1 and sensitivity to PD-1 blockade-based immunotherapy. While 9p24.1 CNA was also reported in diffuse large B-cell lymphoma (DLBCL), little is known about its molecular or clinical significance. In this study, we analyzed the prevalence of 9p24.1 CNA in newly diagnosed DLBCL and examined its association with PD-L1, PD-L2, and JAK2 expression, clinical characteristics, and outcome. We found that 10% of DLBCL cases had CNA of 9p24.1, with 6.5% gains, and 3.5% amplifications. Only the cases with a 9p24.1 amplification had high levels of PD-L1, PD-L2, and JAK2 expression. Gains or amplifications of 9p24.1 were associated with a younger age and the ABC/non-GCB subtype. Compared with DLBCL cases without 9p24.1 CNA, the cases with a 9p24.1 amplification had a trend of better event-free survival. Furthermore, the amplification cases had a gene expression and mutation profile similar to those of PMBCL. Our data suggest that amplification of 9p24.1 identifies a unique subset of DLBCL with clinical and molecular features resembling PMBCL that may be amenable to PD-1 blockade-based immunotherapy.

Sex differences in microglial CX3CR1 signalling determine obesity susceptibility in mice.

Female mice are less susceptible to the negative metabolic consequences of high-fat diet feeding than male mice, for reasons that are incompletely understood. Here we identify sex-specific differences in hypothalamic microglial activation via the CX3CL1-CX3CR1 pathway that mediate the resistance of female mice to diet-induced obesity. Female mice fed a high-fat diet maintain CX3CL1-CX3CR1 levels while male mice show reductions in both ligand and receptor expression. Female Cx3cr1 knockout mice develop 'male-like' hypothalamic microglial accumulation and activation, accompanied by a marked increase in their susceptibility to diet-induced obesity. Conversely, increasing brain CX3CL1 levels in male mice through central pharmacological administration or virally mediated hypothalamic overexpression converts them to a 'female-like' metabolic phenotype with reduced microglial activation and body-weight gain. These data implicate sex differences in microglial activation in the modulation of energy homeostasis and identify CX3CR1 signalling as a potential therapeutic target for the treatment of obesity.