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Patients with colorectal liver metastasis (CLM) present with heterogenous clinical outcomes and improved classification is needed to ameliorate the therapeutic output. Macrophages (Mϕ) hold promise as prognostic classifiers and therapeutic targets. Here, stemming from a single-cell analysis of mononuclear phagocytes infiltrating human CLM, we identified two Mϕ markers associated with distinct populations with opposite clinical relevance. The invasive margin of CLM was enriched in pro-inflammatory monocyte-derived Mϕ (MoMϕ) expressing the monocytic marker SERPINB2, and a more differentiated population, tumor-associated Mϕ (TAM), expressing glycoprotein nonmetastatic melanoma protein B (GPNMB). SERPINB2+ MoMϕ had an early inflammatory profile, whereas GPNMB+ TAMs were enriched in pathways of matrix degradation, angiogenesis, and lipid metabolism and were found closer to the tumor margin, as confirmed by spatial transcriptomics on CLM specimens. In a cohort of patients, a high infiltration of SERPINB2+ cells independently associated with longer disease-free survival (DFS; P = 0.033), whereas a high density of GPNMB+ cells correlated with shorter DFS (P = 0.012) and overall survival (P = 0.002). Cell–cell interaction analysis defined opposing roles for MoMϕ and TAMs, suggesting that SERPINB2+ and GPNMB+ cells are discrete populations of Mϕ and may be exploited for further translation to an immune-based stratification tool. This study provides evidence of how multi-omics approaches can identify nonredundant, clinically relevant markers for further translation to immune-based patient stratification tools and therapeutic targets. GPNMB has been shown to set Mϕ in an immunosuppressive mode. Our high dimensional analyses provide further evidence that GPNMB is a negative prognostic indicator and a potential player in the protumor function of Mϕ populations.

The landscape and function of the immune infiltrate of intrahepatic cholangiocarcinoma (iCCA), a rare, yet aggressive tumor of the biliary tract, remains poorly characterized, limiting development of successful immunotherapies. Herein, we aimed to define the molecular characteristics of tumor-infiltrating leukocytes with a special focus on CD4+ regulatory T cells (Tregs).We used high-dimensional single-cell technologies to characterize the T-cell and myeloid compartments of iCCA tissues, comparing these with their tumor-free peritumoral and circulating counterparts. We further used genomics and cellular assays to define the iCCA-specific role of a novel transcription factor, mesenchyme homeobox 1 (MEOX1), in Treg biology.We found poor infiltration of putative tumor-specific CD39+ CD8+ T cells accompanied by abundant infiltration of hyperactivated CD4+ Tregs. Single-cell RNA-sequencing identified an altered network of transcription factors in iCCA-infiltrating compared to peritumoral T cells, suggesting reduced effector functions by tumor-infiltrating CD8+ T cells and enhanced immunosuppression by CD4+ Tregs. Specifically, we found that expression of MEOX1 was highly enriched in tumor-infiltrating Tregs, and demonstrated that MEOX1 overexpression is sufficient to reprogram circulating Tregs to acquire the transcriptional and epigenetic landscape of tumor-infiltrating Tregs. Accordingly, enrichment of the MEOX1-dependent gene program in Tregs was strongly associated with poor prognosis in a large cohort of patients with iCCA.We observed abundant infiltration of hyperactivated CD4+ Tregs in iCCA tumors along with reduced CD8+ T-cell effector functions. Interfering with hyperactivated Tregs should be explored as an approach to enhance antitumor immunity in iCCA.Immune cells have the potential to slow or halt the progression of tumors. However, some tumors, such as intrahepatic cholangiocarcinoma, are associated with very limited immune responses (and infiltration of cancer-targeting immune cells). Herein, we show that a specific population of regulatory T cells (a type of immune cell that actually suppresses the immune response) are hyperactivated in intrahepatic cholangiocarcinoma. Targeting these cells could enable cancer-targeting immune cells to act more effectively and should be looked at as a potential therapeutic approach to this aggressive cancer type.

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Supplementary Figures 1-4, Tables S1 and S5

Chronic inflammation, including that driven by autoimmunity, is associated with the development of B-cell lymphomas. IL1R8 is a regulatory receptor belonging to the IL1R family, which negatively regulates NF-κB activation following stimulation of IL1R or Toll-like receptor family members. IL1R8 deficiency is associated with the development of severe autoimmune lupus-like disease in lpr mice. We herein investigated whether concomitant exacerbated inflammation and autoimmunity caused by the deficiency of IL1R8 could recapitulate autoimmunity-associated lymphomagenesis. We thus monitored B-cell lymphoma development during the aging of IL1R8-deficient lpr mice, observing an increased lymphoid cell expansion that evolved to diffuse large B-cell lymphoma (DLBCL). Molecular and gene-expression analyses showed that the NF-κB pathway was constitutively activated in Il1r8−/−/lpr B splenocytes. In human DLBCL, IL1R8 had reduced expression compared with normal B cells, and higher IL1R8 expression was associated with a better outcome. Thus, IL1R8 silencing is associated with increased lymphoproliferation and transformation in the pathogenesis of B-cell lymphomas associated with autoimmunity.

Supplementary Table S4

Patients with colorectal liver metastasis (CLM) present with heterogenous clinical outcomes and improved classification is needed to ameliorate the therapeutic output. Macrophages (Mϕ) hold promise as prognostic classifiers and therapeutic targets. Here, stemming from a single-cell analysis of mononuclear phagocytes infiltrating human CLM, we identified two Mϕ markers associated with distinct populations with opposite clinical relevance. The invasive margin of CLM was enriched in pro-inflammatory monocyte-derived Mϕ (MoMϕ) expressing the monocytic marker SERPINB2, and a more differentiated population, tumor-associated Mϕ (TAM), expressing glycoprotein nonmetastatic melanoma protein B (GPNMB). SERPINB2+ MoMϕ had an early inflammatory profile, whereas GPNMB+ TAMs were enriched in pathways of matrix degradation, angiogenesis, and lipid metabolism and were found closer to the tumor margin, as confirmed by spatial transcriptomics on CLM specimens. In a cohort of patients, a high infiltration of SERPINB2+ cells independently associated with longer disease-free survival (DFS; P = 0.033), whereas a high density of GPNMB+ cells correlated with shorter DFS (P = 0.012) and overall survival (P = 0.002). Cell–cell interaction analysis defined opposing roles for MoMϕ and TAMs, suggesting that SERPINB2+ and GPNMB+ cells are discrete populations of Mϕ and may be exploited for further translation to an immune-based stratification tool. This study provides evidence of how multi-omics approaches can identify nonredundant, clinically relevant markers for further translation to immune-based patient stratification tools and therapeutic targets. GPNMB has been shown to set Mϕ in an immunosuppressive mode. Our high dimensional analyses provide further evidence that GPNMB is a negative prognostic indicator and a potential player in the protumor function of Mϕ populations.

More than 50% of all patients with colorectal cancer (CRC) develop liver metastases (CLM), a clinical condition characterized by poor prognosis and lack of reliable prognostic markers. Vδ1 cells are a subset of tissue-resident gamma delta (γδ) T lymphocytes endowed with a broad array of antitumor functions and showing a natural high tropism for the liver. However, little is known about their impact in the clinical outcomes of CLM.We isolated human γδ T cells from peripheral blood (PB) and peritumoral (PT) tissue of 93 patients undergone surgical procedures to remove CLM. The phenotype of freshly purified γδ T cells was assessed by multiparametric flow cytometry, the transcriptional profiles by single cell RNA-sequencing, the functional annotations by Gene Ontology enrichment analyses and the clonotype by γδ T cell receptor (TCR)-sequencing.The microenvironment of CLM is characterized by a heterogeneous immune infiltrate comprising different subsets of γδ tumor-infiltrating lymphocytes (TILs) able to egress the liver and re-circulate in PB. Vδ1 T cells represent the largest population of γδ TILs within the PT compartment of CLM that is greatly enriched in Vδ1 T effector (TThe enrichment of tissue-resident CD69

Tumor-associated macrophages (TAMs) are correlated with the progression of prostatic adenocarcinoma (PCa). The mechanistic basis of this correlation and therapeutic strategies to target TAMs in PCa remain poorly defined. Here, single-cell RNA sequencing was used to profile the transcriptional landscape of TAMs in human PCa, leading to identification of a subset of macrophages characterized by dysregulation in transcriptional pathways associated with lipid metabolism. This subset of TAMs correlates positively with PCa progression and shorter disease-free survival and is characterized by an accumulation of lipids that is dependent on Marco. Mechanistically, cancer cell–derived IL-1β enhances Marco expression on macrophages, and reciprocally, cancer cell migration is promoted by CCL6 released by lipid-loaded TAMs. Moreover, administration of a high-fat diet to tumor-bearing mice raises the abundance of lipid-loaded TAMs. Finally, targeting lipid accumulation by Marco blockade hinders tumor growth and invasiveness and improves the efficacy of chemotherapy in models of PCa, pointing to combinatorial strategies that may influence patient outcomes.

The plasma membrane tetraspan molecule MS4A4A is selectively expressed by macrophage-lineage cells, but its function is unknown. Here we report that MS4A4A was restricted to murine and human mononuclear phagocytes and was induced during monocyte-to-macrophage differentiation in the presence of interleukin 4 or dexamethasone. Human MS4A4A was co-expressed with M2/M2-like molecules in subsets of normal tissue-resident macrophages, infiltrating macrophages from inflamed synovium and tumor-associated macrophages. MS4A4A interacted and colocalized with the β-glucan receptor dectin-1 in lipid rafts. In response to dectin-1 ligands, Ms4a4a-deficient macrophages showed defective signaling and defective production of effector molecules. In experimental models of tumor progression and metastasis, Ms4a4a deficiency in macrophages had no impact on primary tumor growth, but was essential for dectin-1-mediated activation of macrophages and natural killer (NK) cell–mediated metastasis control. Thus, MS4A4A is a tetraspan molecule selectively expressed in macrophages during differentiation and polarization, essential for dectin-1-dependent activation of NK cell–mediated resistance to metastasis.

Fibrosis is a progressive biological condition, leading to organ dysfunction in various clinical settings. Although fibroblasts and macrophages are known as key cellular players for fibrosis development, a comprehensive functional model that considers their interaction in the metabolic/immunologic context of fibrotic tissue has not been set up. Here we show, by transcriptome-based mathematical modeling in an in vitro system that represents macrophage-fibroblast interplay and reflects the functional effects of inflammation, hypoxia and the adaptive immune context, that irreversible fibrosis development is associated with specific combinations of metabolic and inflammatory cues. The in vitro signatures are in good alignment with transcriptomic profiles generated on laser captured glomeruli and cortical tubule-interstitial area, isolated from human transplanted kidneys with advanced stages of glomerulosclerosis and interstitial fibrosis/tubular atrophy, two clinically relevant conditions associated with organ failure in renal allografts. The model we describe here is validated on tissue based quantitative immune-phenotyping of biopsies from transplanted kidneys, demonstrating its feasibility. We conclude that the combination of in vitro and in silico modeling represents a powerful systems medicine approach to dissect fibrosis pathogenesis, applicable to specific pathological conditions, and develop coordinated targeted approaches.

The cancer-free photosensitive trichothiodystrophy (PS-TTD) and the cancer-prone xeroderma pigmentosum (XP) are rare monogenic disorders that can arise from mutations in the same genes, namely ERCC2/XPD or ERCC3/XPB. Both XPD and XPB proteins belong to the 10-subunit complex transcription factor IIH (TFIIH) that plays a key role in transcription and nucleotide excision repair, the DNA repair pathway devoted to the removal of ultraviolet-induced DNA lesions. Compelling evidence suggests that mutations affecting the DNA repair activity of TFIIH are responsible for the pathological features of XP, whereas those also impairing transcription give rise to TTD. By adopting a relatives-based whole transcriptome sequencing approach followed by specific gene expression profiling in primary fibroblasts from a large cohort of TTD or XP cases with mutations in ERCC2/XPD gene, we identify the expression alterations specific for TTD primary dermal fibroblasts. While most of these transcription deregulations do not impact on the protein level, very low amounts of prostaglandin I(2) synthase (PTGIS) are found in TTD cells. PTGIS catalyzes the last step of prostaglandin I(2) synthesis, a potent vasodilator and inhibitor of platelet aggregation. Its reduction characterizes all TTD cases so far investigated, both the PS-TTD with mutations in TFIIH coding genes as well as the nonphotosensitive (NPS)-TTD. A severe impairment of TFIIH and RNA polymerase II recruitment on the PTGIS promoter is found in TTD but not in XP cells. Thus, PTGIS represents a biomarker that combines all PS- and NPS-TTD cases and distinguishes them from XP.

The cancer-free photosensitive trichothiodystrophy (PS-TTD) and the cancer-prone xeroderma pigmentosum (XP) are rare monogenic disorders that can arise from mutations in the same genes, namely ERCC2/XPD or ERCC3/XPB Both XPD and XPB proteins belong to the 10-subunit complex transcription factor IIH (TFIIH) that plays a key role in transcription and nucleotide excision repair, the DNA repair pathway devoted to the removal of ultraviolet-induced DNA lesions. Compelling evidence suggests that mutations affecting the DNA repair activity of TFIIH are responsible for the pathological features of XP, whereas those also impairing transcription give rise to TTD. By adopting a relatives-based whole transcriptome sequencing approach followed by specific gene expression profiling in primary fibroblasts from a large cohort of TTD or XP cases with mutations in ERCC2/XPD gene, we identify the expression alterations specific for TTD primary dermal fibroblasts. While most of these transcription deregulations do not impact on the protein level, very low amounts of prostaglandin I2 synthase (PTGIS) are found in TTD cells. PTGIS catalyzes the last step of prostaglandin I2 synthesis, a potent vasodilator and inhibitor of platelet aggregation. Its reduction characterizes all TTD cases so far investigated, both the PS-TTD with mutations in TFIIH coding genes as well as the nonphotosensitive (NPS)-TTD. A severe impairment of TFIIH and RNA polymerase II recruitment on the PTGIS promoter is found in TTD but not in XP cells. Thus, PTGIS represents a biomarker that combines all PS- and NPS-TTD cases and distinguishes them from XP.

Complement has emerged as a component of tumor-promoting inflammation. We conducted a systematic assessment of the role of complement activation and effector pathways in sarcomas. C3−/−, MBL1/2−/− and C4−/− mice showed reduced susceptibility to 3-methylcholanthrene sarcomagenesis and transplanted sarcomas, whereas C1q and factor B deficiency had marginal effects. Complement 3a receptor (C3aR), but not C5aR1 and C5aR2, deficiency mirrored the phenotype of C3−/− mice. C3 and C3aR deficiency were associated with reduced accumulation and functional skewing of tumor-associated macrophages, increased T-cell activation and response to anti-PD-1 therapy. Transcriptional profiling of sarcoma-infiltrating macrophages and monocytes revealed the enrichment of the major histocompatibility complex II–dependent antigen presentation pathway in C3-deficient cells. In patients, C3aR expression correlated with a macrophage population signature, and C3-deficiency-associated signatures predicted better clinical outcome. These results suggest that the lectin pathway and C3a–C3aR axis are key components of complement and macrophage-mediated sarcoma promotion and immunosuppression. Magrini et. al. study sarcoma development and antitumor immune response in complement-deficient murine hosts, demonstrating a role for the C3a–C3aR axis in promoting immunosuppressive macrophages.

Rapidly dividing cancer cells show elevated levels of DNA double-strand breaks (DSBs) resulting from replication stress and linked to genome instability. To verify the hypothesis that a low level of endogenous replicative DNA damage may impact gene expression programs and cell biology features relevant to cancer progression, we used DNA ligase I (LigI) defective 46BR.1G1 fibroblasts, deriving from a patient who died at 19 for lymphoma, and the 7A3 cell clone, obtained from 46BR.1G1 by stably expressing ectopic wild-type LigI. LigI deficiency impairs maturation of newly synthesized DNA and increases the number of DSBs and γH2AX foci, features associated with genome instability commonly found also in pre-neoplastic lesions. In order to decipher the strategy used to cope with replicative DNA damage, we have compared gene expression profiles in 46BR.1G1 and 7A3 cells. Among the differentially expressed genes, we identified a group of long noncoding RNAs (lncRNAs) which show significant transcriptional alteration in 46BR.1G1 cells, and appear to be relevant for cancer progression. An interesting up-regulated lncRNA in 46BR.1G1 cells is LINP1 (lncRNA in nonhomologous end joining (NHEJ) pathway 1) which has been shown to be involved in DNA repair. We have observed that LINP1 up-regulation contributes to proliferation and survival of 46BR.1G1 that could account for genome instability. Moreover, we observed that LINP1 is upregulated at later times in control human fibroblasts exposed to exogenous sources of DNA damage. Our observations support the notion that LINP1 lncRNA targeting could reduce the DNA repair efficacy of tumour cells. * These authors contributed equally to this work.

Description, The inner workings of the clock system rely on communicating signals between distal tissues to maintain daily metabolism., The mammalian circadian clock, expressed throughout the brain and body, controls daily metabolic homeostasis. Clock function in peripheral tissues is required, but not sufficient, for this task. Because of the lack of specialized animal models, it is unclear how tissue clocks interact with extrinsic signals to drive molecular oscillations. Here, we isolated the interaction between feeding and the liver clock by reconstituting Bmal1 exclusively in hepatocytes (Liver-RE), in otherwise clock-less mice, and controlling timing of food intake. We found that the cooperative action of BMAL1 and the transcription factor CEBPB regulates daily liver metabolic transcriptional programs. Functionally, the liver clock and feeding rhythm are sufficient to drive temporal carbohydrate homeostasis. By contrast, liver rhythms tied to redox and lipid metabolism required communication with the skeletal muscle clock, demonstrating peripheral clock cross-talk. Our results highlight how the inner workings of the clock system rely on communicating signals to maintain daily metabolism.

Background: Inflammation is a key component of cardiac disease, with macrophages and T lymphocytes mediating essential roles in the progression to heart failure. Nonetheless, little insight exists on other immune subsets involved in the cardiotoxic response. Methods: Here, we used single-cell RNA sequencing to map the cardiac immune composition in the standard murine nonischemic, pressure-overload heart failure model. By focusing our analysis on CD45 + cells, we obtained a higher resolution identification of the immune cell subsets in the heart, at early and late stages of disease and in controls. We then integrated our findings using multiparameter flow cytometry, immunohistochemistry, and tissue clarification immunofluorescence in mouse and human. Results: We found that most major immune cell subpopulations, including macrophages, B cells, T cells and regulatory T cells, dendritic cells, Natural Killer cells, neutrophils, and mast cells are present in both healthy and diseased hearts. Most cell subsets are found within the myocardium, whereas mast cells are found also in the epicardium. Upon induction of pressure overload, immune activation occurs across the entire range of immune cell types. Activation led to upregulation of key subset-specific molecules, such as oncostatin M in proinflammatory macrophages and PD-1 in regulatory T cells, that may help explain clinical findings such as the refractivity of patients with heart failure to anti–tumor necrosis factor therapy and cardiac toxicity during anti–PD-1 cancer immunotherapy, respectively. Conclusions: Despite the absence of infectious agents or an autoimmune trigger, induction of disease leads to immune activation that involves far more cell types than previously thought, including neutrophils, B cells, Natural Killer cells, and mast cells. This opens up the field of cardioimmunology to further investigation by using toolkits that have already been developed to study the aforementioned immune subsets. The subset-specific molecules that mediate their activation may thus become useful targets for the diagnostics or therapy of heart failure.

Deciphering the molecular alterations leading to disease initiation and progression is currently crucial to identify the most relevant targets for precision therapy in cancer patients. Cancers express a complex chemokine network influencing leucocyte infiltration and angiogenesis. Moreover, malignant cells also express a selective repertoire of chemokine receptors that sustain their growth and spread. At present, different cancer types have been shown to overexpress C-X-C chemokine receptor type 4 (CXCR4)and to respond to its ligand C-X-C motif chemokine 12 (CXCL12). The CXCL12/CXCR4 axis influences cancer biology, promoting survival, proliferation, and angiogenesis, and plays a pivotal role in directing migration of cancer cells to sites of metastases, making it a prognostic marker and a therapeutic target. More recently, mutations in the C-terminus of CXCR4 have been identified in the genomic landscape of patients affected by Waldenstrom’s macroglobulinemia, a rare B cell neoplasm. These mutations closely resemble those occurring in Warts, Hypogammaglobulinemia, Immunodeficiency, and Myelokathexis (WHIM) syndrome, an immunodeficiency associated with CXCR4 aberrant expression and activity and with chemotherapy resistance in clinical trials. In this review, we summarize the current knowledge on the relevance of CXCR4 mutations in cancer biology, focusing on its importance as predictors of clinical presentation and response to therapy.

CRISPR/Cas9 has become a powerful method to engineer genomes and to activate or to repress genes expression. As such, in cancer research CRISPR/Cas9 technology represents an efficient tool to dissect mechanisms of tumorigenesis and to discover novel targets for drug development. Here, we employed the CRISPR/Cas9 technology for studying the role of prostaglandin-endoperoxide synthase 2 (PTGS2) in melanoma development and progression. Melanoma is the most aggressive form of skin cancer with a median survival of less than 1 year. Although oncogene-targeted drugs and immune checkpoint inhibitors have demonstrated a significant success in improving overall survival in patients, related toxicity and emerging resistance are ongoing challenges. Gene therapy appears to be an appealing option to enhance the efficacy of currently available melanoma therapeutics leading to better patient prognosis. Several gene therapy targets have been identified and have proven to be effective against melanoma cells. Particularly, PTGS2 is frequently expressed in malignant melanomas and its expression significantly correlates with poor survival in patients. In this study we investigated on the effect of ptgs2 knockdown in B16F10 murine melanoma cells. Our results show that reduced expression of ptgs2 in melanoma cells: i) inhibits cell proliferation, migration, and invasiveness; ii) modulates immune response by impairing myeloid derived suppressor cell differentiation; iii) reduces tumor development and metastasis in vivo. Collectively, these findings indicate that ptgs2 could represent an ideal gene to be targeted to improve success rates in the development of new and highly selective drugs for melanoma treatment.

Macrophage morphology could be used to stratify metastasis risk for CRC patients., Using macrophage morphology in human colorectal cancer liver metastasis, Donadon et al. in this issue of JEM (https://doi.org/10.1084/jem.20191847) provide a window into lipid metabolism and foamy macrophages, which accrue in numerous pathological states and here are shown to have clinical application.

Brittle and “tiger-tail” hair is the diagnostic hallmark of trichothiodystrophy (TTD), a rare recessive disease associated with a wide spectrum of clinical features including ichthyosis, intellectual disability, decreased fertility, and short stature. As a result of premature abrogation of terminal differentiation, the hair is brittle and fragile and contains reduced cysteine content. Hypersensitivity to UV light is found in about half of individuals with TTD; all of these individuals harbor bi-allelic mutations in components of the basal transcription factor TFIIH, and these mutations lead to impaired nucleotide excision repair and basal transcription. Different genes have been found to be associated with non-photosensitive TTD (NPS-TTD); these include MPLKIP (also called TTDN1), GTF2E2 (also called TFIIEβ), and RNF113A. However, a relatively large group of these individuals with NPS-TTD have remained genetically uncharacterized. Here we present the identification of an NPS-TTD-associated gene, threonyl-tRNA synthetase (TARS), found by next-generation sequencing of a group of uncharacterized individuals with NPS-TTD. One individual has compound heterozygous TARS variants, c.826A>G (p.Lys276Glu) and c.1912C>T (p.Arg638∗), whereas a second individual is homozygous for the TARS variant: c.680T>C (p.Leu227Pro). We showed that these variants have a profound effect on TARS protein stability and enzymatic function. Our results expand the spectrum of genes involved in TTD to include genes implicated in amino acid charging of tRNA, which is required for the last step in gene expression, namely protein translation. We previously proposed that some of the TTD-specific features derive from subtle transcription defects as a consequence of unstable transcription factors. We now extend the definition of TTD from a transcription syndrome to a “gene-expression” syndrome.

Summary Neutrophils are a component of the tumor microenvironment and have been predominantly associated with cancer progression. Using a genetic approach complemented by adoptive transfer, we found that neutrophils are essential for resistance against primary 3-methylcholantrene-induced carcinogenesis. Neutrophils were essential for the activation of an interferon-γ-dependent pathway of immune resistance, associated with polarization of a subset of CD4− CD8− unconventional αβ T cells (UTCαβ). Bulk and single-cell RNA sequencing (scRNA-seq) analyses unveiled the innate-like features and diversity of UTCαβ associated with neutrophil-dependent anti-sarcoma immunity. In selected human tumors, including undifferentiated pleomorphic sarcoma, CSF3R expression, a neutrophil signature and neutrophil infiltration were associated with a type 1 immune response and better clinical outcome. Thus, neutrophils driving UTCαβ polarization and type 1 immunity are essential for resistance against murine sarcomas and selected human tumors., Graphical Abstract, Highlights • Neutrophils mediate antitumor response by sustaining an IL-12/IFNγ-dependent pathway • Neutrophils are essential for unconventional αβ T cell (UTCαβ) type 1 polarization • Type 1 UTCαβ possess an innate-like phenotype and display antitumor potential in vivo • Neutrophil infiltration is associated with good prognosis in selected human tumors, Tumor-associated neutrophils (TANs) have mainly been portrayed as tumor-promoters. Here, we describe a novel antitumor pathway in which TANs promote IL-12 production by macrophages, leading to type 1 polarization of a subset of unconventional αβ T cell (UTCαβ). Type 1 UTCαβ possess an innate-like phenotype and antitumor potential in vivo. In selected human tumors, neutrophil infiltration is associated with type 1 immunity and better clinical outcome.

Chronic inflammation, including that driven by autoimmunity, is associated with the development of B-cell lymphomas. IL1R8 is a regulatory receptor belonging to the IL1R family, which negatively regulates NF-κB activation following stimulation of IL1R or Toll-like receptor family members. IL1R8 deficiency is associated with the development of severe autoimmune lupus-like disease in lpr mice. We herein investigated whether concomitant exacerbated inflammation and autoimmunity caused by the deficiency of IL1R8 could recapitulate autoimmunity-associated lymphomagenesis. We thus monitored B-cell lymphoma development during the aging of IL1R8-deficient lpr mice, observing an increased lymphoid cell expansion that evolved to diffuse large B-cell lymphoma (DLBCL). Molecular and gene-expression analyses showed that the NF-κB pathway was constitutively activated in Il1r8−/−/lpr B splenocytes. In human DLBCL, IL1R8 had reduced expression compared with normal B cells, and higher IL1R8 expression was associated with a better outcome. Thus, IL1R8 silencing is associated with increased lymphoproliferation and transformation in the pathogenesis of B-cell lymphomas associated with autoimmunity.

In the past few years, the role of long noncoding RNAs (lncRNAs) in tumor development and progression has been disclosed although their mechanisms of action remain to be elucidated. An important contribution to the comprehension of lncRNAs biology in cancer could be obtained through the integrated analysis of multiple expression datasets. However, the growing availability of public datasets requires new data mining techniques to integrate and describe relationship among data. In this perspective, we explored the powerness of the Association Rule Mining (ARM) approach in gene expression data analysis. By the ARM method, we performed a meta-analysis of cancer-related microarray data which allowed us to identify and characterize a set of ten lncRNAs simultaneously altered in different brain tumor datasets. The expression profiles of the ten lncRNAs appeared to be sufficient to distinguish between cancer and normal tissues. A further characterization of this lncRNAs signature through a comodulation expression analysis suggested that biological processes specific of the nervous system could be compromised.

376 Background: Genetic lesions that drive prostate cancer (PCa) development are able to modify the immune response and tumor infiltrating immune subsets, resulting in tumor progression. We investigated the profile of the immune microenvironment in PCa by high dimensional single cell analysis. Methods: We conducted an immune profiling study based on integrated RNA single cell sequencing and multiparametric flow cytometry in order to dissect the immune landscape of PCa. CD45+ immune cells infiltrating tumoral and adjacent non tumoral tissues were isolated from patients with PCa who underwent software assisted fusion biopsy, based on MRI, and/or radical prostatectomy, and analyzed by single cell sequencing. The primary endpoint was to evaluate the effectiveness of single cell RNA sequencing on CD45+ cell sorted from tumoral and adjacent non-tumoral tissues. Secondary endpoint was the identification of tumor-driven immune changes in prostatic lesions. Results: The cohort consisted of 3 patients who underwent radical prostatectomy (RP) and 45 patients with positive prostate biopsy; the negative control was checked by pathological assessment. In patients who underwent RP the gene expression analysis identified a modulation in the abundance of several immune subsets infiltrating the tumoral tissue, when compared with the non tumoral, evident for Tumor associated macrophages (TAMs), Natural Killer cells (NK) and T regulatory cells. We then implemented a 22 parameters flow cytometry panel that we tested on fresh prostatic tissue and peripheral blood from positive PCa biopsies. We identified a subset of tumor infiltrating macrophages showing an altered gene expression profile when compared with macrophages infiltrating the non-tumoral tissue. Importantly we derived a genetic signature from this subset of tumoral TAMs that resulted to be associated with cancer progression. Conclusions: Our findings support the effectiveness of single cell RNA sequencing in the dissection of the immune landscape in PCa and identified immune changes in patients when comparing neoplastic tissue with non tumoral areas. Such data may be useful for understanding the role of immune system in PCa carcinogenesis.

Background Colorectal liver metastases (CLM) display a high heterogeneity, responsible for a wide array of clinical presentations and responsiveness to treatments. In the era of precision medicine, there is a critical need of reliable prognostic markers to improve patient stratification and, for their predominance in metastatic tissues, tumor-associated macrophages (TAMs) emerge as promising candidates. The aim of this study was to test the presence of discrete TAM populations in CLM patients on the basis of morphology, and to test the impact of TAMs morphology on recurrence-free survival (RFS). Methods NCT038888638 is a single-center study conducted in a tertiary-referral university hospital that examined a cohort of patients with CLMs that underwent hepatectomy between 2005 and 2017. TAMs cell density, cell area and cell perimeter were systematically quantified in 3 non-contiguous and non-overlapping areas of CLM sections by means of immuno-reactive area of CD163+ macrophages. The association of TAMs metrics and RFS was tested by using receiver operating characteristics (ROC) curves, multivariate Cox regression analysis and survival analysis. Results A cohort of 101 CLM patients resected between 2005 and 2017 was considered. Among density (AUC=0.555; 95%CI=0.410-0.701; P = 0.449), perimeter (AUC=0.526; 95%CI=0.383-0.671; P = 0.708) and area (AUC=0.791; 95%CI=0.572-0.841; P = 0.006) ofCD163+ TAMs, only the latter was significantly associated with differences in survival time. Small and large TAMs, as defined by using the best cutoff value extrapolated from the ROC curve (area: 60.39 μm2; Se = 0.79; Sp = 0.44), were clearly associated with significantly different 5-year RFS rates of 27.8% and 0.2% respectively (P Conclusions Macrophage morphology is critically associated with prognosis of CLM patients. The results reported here support that accurate quantitative morphometric characterization of TAMs can serve as an easily quantifiable correlate of functional diversity with prognostic significance. Clinical trial identification NCT038888638. Legal entity responsible for the study The authors. Funding Associazione Italiana per la Ricerca sul Cancro (AIRC). Disclosure All authors have declared no conflicts of interest.

Moderate DNA damage resulting from metabolic activities or sub-lethal doses of exogenous insults may eventually lead to cancer onset. Human 46BR.1G1 cells bear a mutation in replicative DNA ligase I (LigI) which results in low levels of replication-dependent DNA damage. This replication stress elicits a constitutive phosphorylation of the ataxia telangiectasia mutated (ATM) checkpoint kinase that fails to arrest cell cycle progression or to activate apoptosis or cell senescence. Stable transfection of wild type LigI, as in 7A3 cells, prevents DNA damage and ATM activation. Here we show that parental 46BR.1G1 and 7A3 cells differ in important features such as cell morphology, adhesion and migration. Comparison of gene expression profiles in the two cell lines detects Bio-Functional categories consistent with the morphological and migration properties of LigI deficient cells. Interestingly, ATM inhibition makes 46BR.1G1 more similar to 7A3 cells for what concerns morphology, adhesion and expression of cell-cell adhesion receptors. These observations extend the influence of the DNA damage response checkpoint pathways and unveil a role for ATM kinase activity in modulating cell biology parameters relevant to cancer progression.

Publisher's version (útgefin grein), Objective: To explore genetic and lifestyle risk factors of MRI-defined brain infarcts (BI) in large population-based cohorts. Methods We performed meta-analyses of genome-wide association studies (GWAS) and examined associations of vascular risk factors and their genetic risk scores (GRS) with MRI-defined BI and a subset of BI, namely, small subcortical BI (SSBI), in 18 population-based cohorts (n=20,949) from 5 ethnicities (3,726 with BI, 2,021 with SSBI). Top loci were followed up in 7 population-based cohorts (n = 6,862; 1,483 with BI, 630 with SBBI), and we tested associations with related phenotypes including ischemic stroke and pathologically defined BI. Results: The mean prevalence was 17.7% for BI and 10.5% for SSBI, steeply rising after age 65. Two loci showed genome-wide significant association with BI: FBN2, p = 1.77 × 10-8; and LINC00539/ZDHHC20, p = 5.82 × 10-9. Both have been associated with blood pressure (BP)-related phenotypes, but did not replicate in the smaller follow-up sample or show associations with related phenotypes. Age- and sex-adjusted associations with BI and SSBI were observed for BP traits (p value for BI, p[BI] = 9.38 × 10-25; p [SSBI] = 5.23 × 10-14 for hypertension), smoking (p[BI]= 4.4 × 10-10; p [SSBI] = 1.2 × 10 -4), diabetes (p[BI] = 1.7 × 10 -8; p [SSBI] = 2.8 × 10 -3), previous cardiovascular disease (p [BI] = 1.0 × 10-18; p [SSBI] = 2.3 × 10-7), stroke (p [BI] = 3.9 × 10-69; p [SSBI] = 3.2 × 10 -24), and MRI-defined white matter hyperintensity burden (p [BI]=1.43 × 10-157; p [SSBI] = 3.16 × 10-106), but not with body mass index or cholesterol. GRS of BP traits were associated with BI and SSBI (p ≤ 0.0022), without indication of directional pleiotropy. Conclusion: In this multiethnic GWAS meta-analysis, including over 20,000 population-based participants, we identified genetic risk loci for BI requiring validation once additional large datasets become available. High BP, including genetically determined, was the most significant modifiable, causal risk factor for BI., CHAP: R01-AG-11101, R01-AG-030146, NIRP-14-302587. SMART: This study was supported by a grant from the Netherlands Organization for Scientific Research–Medical Sciences (project no. 904-65–095). LBC: The authors thank the LBC1936 participants and the members of the LBC1936 research team who collected and collated the phenotypic and genotypic data. The LBC1936 is supported by Age UK (Disconnected Mind Programme grant). The work was undertaken by The University of Edinburgh Centre for Cognitive Ageing and Cognitive Epidemiology, part of the cross-council Lifelong Health and Wellbeing Initiative (MR/K026992/1). The brain imaging was performed in the Brain Research Imaging Centre (https://www.ed.ac.uk/clinical-sciences/edinburgh-imaging), a center in the SINAPSE Collaboration (sinapse.ac.uk) supported by the Scottish Funding Council and Chief Scientist Office. Funding from the UK Biotechnology and Biological Sciences Research Council (BBSRC) and the UK Medical Research Council is acknowledged. Genotyping was supported by a grant from the BBSRC (ref. BB/F019394/1). PROSPER: The PROSPER study was supported by an investigator-initiated grant obtained from Bristol-Myers Squibb. Prof. Dr. J.W. Jukema is an Established Clinical Investigator of the Netherlands Heart Foundation (grant 2001 D 032). Support for genotyping was provided by the seventh framework program of the European commission (grant 223004) and by the Netherlands Genomics Initiative (Netherlands Consortium for Healthy Aging grant 050-060-810). SCES and SiMES: National Medical Research Council Singapore Centre Grant NMRC/CG/013/2013. C.-Y.C. is supported by the National Medical Research Council, Singapore (CSA/033/2012), Singapore Translational Research Award (STaR) 2013. Dr. Kamran Ikram received additional funding from the Singapore Ministry of Health's National Medical Research Council (NMRC/CSA/038/2013). SHIP: SHIP is part of the Community Medicine Research net of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research (grants no. 01ZZ9603, 01ZZ0103, and 01ZZ0403), the Ministry of Cultural Affairs, as well as the Social Ministry of the Federal State of Mecklenburg–West Pomerania, and the network “Greifswald Approach to Individualized Medicine (GANI_MED)” funded by the Federal Ministry of Education and Research (grant 03IS2061A). Genome-wide data have been supported by the Federal Ministry of Education and Research (grant no. 03ZIK012) and a joint grant from Siemens Healthineers, Erlangen, Germany, and the Federal State of Mecklenburg–West Pomerania. Whole-body MRI was supported by a joint grant from Siemens Healthineers, Erlangen, Germany, and the Federal State of Mecklenburg–West Pomerania. The University of Greifswald is a member of the Caché Campus program of the InterSystems GmbH. OATS (Older Australian Twins Study): OATS was supported by an Australian National Health and Medical Research Council (NHRMC)/Australian Research Council (ARC) Strategic Award (ID401162) and by a NHMRC grant (ID1045325). OATS was facilitated via access to the Australian Twin Registry, which is supported by the NHMRC Enabling Grant 310667. The OATS genotyping was partly supported by a Commonwealth Scientific and Industrial Research Organisation Flagship Collaboration Fund Grant. NOMAS: The Northern Manhattan Study is funded by the NIH grant “Stroke Incidence and Risk Factors in a Tri-Ethnic Region” (NINDS R01NS 29993). TASCOG: NHMRC and Heart Foundation. AGES: The study was funded by the National Institute on Aging (NIA) (N01-AG-12100), Hjartavernd (the Icelandic Heart Association), and the Althingi (the Icelandic Parliament), with contributions from the Intramural Research Programs at the NIA, the National Heart, Lung, and Blood Institute (NHLBI), and the National Institute of Neurological Disorders and Stroke (NINDS) (Z01 HL004607-08 CE). ERF: The ERF study as a part of European Special Populations Research Network (EUROSPAN) was supported by European Commission FP6 STRP grant no. 018947 (LSHG-CT-2006-01947) and also received funding from the European Community's Seventh Framework Programme (FP7/2007–2013)/grant agreement HEALTH-F4-2007-201413 by the European Commission under the programme “Quality of Life and Management of the Living Resources” of 5th Framework Programme (no. QLG2-CT-2002-01254). High-throughput analysis of the ERF data was supported by a joint grant from Netherlands Organization for Scientific Research and the Russian Foundation for Basic Research (NWO-RFBR 047.017.043). Exome sequencing analysis in ERF was supported by the ZonMw grant (project 91111025). Najaf Amin is supported by the Netherlands Brain Foundation (project no. F2013[1]-28). ARIC: The Atherosclerosis Risk in Communities study was performed as a collaborative study supported by NHLBI contracts (HHSN268201100005C, HSN268201100006C, HSN268201100007C, HHSN268201100008C, HHSN268201100009C, HHSN268201100010C, HHSN268201100011C, and HHSN268201100012C), R01HL70825, R01HL087641, R01HL59367, and R01HL086694; National Human Genome Research Institute contract U01HG004402; and NIH contract HHSN268200625226C. Infrastructure was partly supported by grant no. UL1RR025005, a component of the NIH and NIH Roadmap for Medical Research. This project was also supported by NIH R01 grant NS087541 to M.F. FHS: This work was supported by the National Heart, Lung and Blood Institute's Framingham Heart Study (contracts no. N01-HC-25195 and no. HHSN268201500001I), and its contract with Affymetrix, Inc. for genotyping services (contract no. N02-HL-6-4278). A portion of this research utilized the Linux Cluster for Genetic Analysis (LinGA-II) funded by the Robert Dawson Evans Endowment of the Department of Medicine at Boston University School of Medicine and Boston Medical Center. This study was also supported by grants from the NIA (R01s AG033040, AG033193, AG054076, AG049607, AG008122, and U01-AG049505) and the NINDS (R01-NS017950, UH2 NS100605). Dr. DeCarli is supported by the Alzheimer's Disease Center (P30 AG 010129). ASPS: The research reported in this article was funded by the Austrian Science Fund (FWF) grant nos. P20545-P05, P13180, and P20545-B05, by the Austrian National Bank Anniversary Fund, P15435, and the Austrian Ministry of Science under the aegis of the EU Joint Programme–Neurodegenerative Disease Research (JPND) (jpnd.eu). LLS: The Leiden Longevity Study has received funding from the European Union's Seventh Framework Programme (FP7/2007–2011) under grant agreement no. 259679. This study was supported by a grant from the Innovation-Oriented Research Program on Genomics (SenterNovem IGE05007), the Centre for Medical Systems Biology, and the Netherlands Consortium for Healthy Ageing (grant 050-060-810), all in the framework of the Netherlands Genomics Initiative, Netherlands Organization for Scientific Research (NWO), UnileverColworth, and by BBMRI-NL, a Research Infrastructure financed by the Dutch government (NWO 184.021.007). CHS: This CHS research was supported by contracts HHSN268201200036C, HHSN268200800007C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086, N01HC15103, and HHSN268200960009C and grants U01HL080295, R01HL087652, R01HL105756, R01HL103612, R01HL120393, R01HL085251, and R01HL130114 from the NHLBI with additional contribution from NINDS. Additional support was provided through R01AG023629 from the NIA. A full list of principal CHS investigators and institutions can be found at CHS-NHLBI.org. The provision of genotyping data was supported in part by the National Center for Advancing Translational Sciences, CTSI grant UL1TR001881, and the National Institute of Diabetes and Digestive and Kidney Disease Diabetes Research Center grant DK063491 to the Southern California Diabetes Endocrinology Research Center. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. Rotterdam Study: The generation and management of GWAS genotype data for the Rotterdam Study is supported by the Netherlands Organisation of Scientific Research (NWO) Investments (no. 175.010.2005.011, 911-03-012). This study is funded by the Research Institute for Diseases in the Elderly (014-93-015; RIDE2), the Netherlands Genomics Initiative (NGI)/NWO project no. 050-060-810. The Rotterdam Study is funded by Erasmus MC Medical Center and Erasmus MC University, Rotterdam, Netherlands Organization for Health Research and Development (ZonMw), the Research Institute for Diseases in the Elderly (RIDE), the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the European Commission (DG XII), and the Municipality of Rotterdam. M.A.I. is supported by an NWO Veni grant (916.13.054). The 3-City Study: The 3-City Study is conducted under a partnership agreement among the Institut National de la Santé et de la Recherche Médicale (INSERM), the University of Bordeaux, and Sanofi-Aventis. The Fondation pour la Recherche Médicale funded the preparation and initiation of the study. The 3C Study is also supported by the Caisse Nationale Maladie des Travailleurs Salariés, Direction Générale de la Santé, Mutuelle Générale de l’Education Nationale (MGEN), Institut de la Longévité, Conseils Régionaux of Aquitaine and Bourgogne, Fondation de France, and Ministry of Research–INSERM Programme “Cohortes et collections de données biologiques.” C.T. and S.D. have received investigator-initiated research funding from the French National Research Agency (ANR) and from the Fondation Leducq. S.D. is supported by a starting grant from the European Research Council (SEGWAY), a grant from the Joint Programme of Neurodegenerative Disease research (BRIDGET), from the European Union's Horizon 2020 research and innovation programme under grant agreements No 643417 & No 640643, and by the Initiative of Excellence of Bordeaux University. Part of the computations were performed at the Bordeaux Bioinformatics Center (CBiB), University of Bordeaux. This work was supported by the National Foundation for Alzheimer's Disease and Related Disorders, the Institut Pasteur de Lille, the Labex DISTALZ, and the Centre National de Génotypage. ADGC: The Alzheimer Disease Genetics Consortium is supported by NIH. NIH-NIA supported this work through the following grants: ADGC, U01 AG032984, RC2 AG036528; NACC, U01 AG016976; NCRAD, U24 AG021886; NIA LOAD, U24 AG026395, U24 AG026390; Banner Sun Health Research Institute, P30 AG019610; Boston University, P30 AG013846, U01 AG10483, R01 CA129769, R01 MH080295, R01 AG017173, R01 AG025259, R01AG33193; Columbia University, P50 AG008702, R37 AG015473; Duke University, P30 AG028377, AG05128; Emory University, AG025688; Group Health Research Institute, UO1 AG06781, UO1 HG004610; Indiana University, P30 AG10133; Johns Hopkins University, P50 AG005146, R01 AG020688; Massachusetts General Hospital, P50 AG005134; Mayo Clinic, P50 AG016574; Mount Sinai School of Medicine, P50 AG005138, P01 AG002219; New York University, P30 AG08051, MO1RR00096, UL1 RR029893, 5R01AG012101, 5R01AG022374, 5R01AG013616, 1RC2AG036502, 1R01AG035137; Northwestern University, P30 AG013854; Oregon Health & Science University, P30 AG008017, R01 AG026916; Rush University, P30 AG010161, R01 AG019085, R01 AG15819, R01 AG17917, R01 AG30146; TGen, R01 NS059873; University of Alabama at Birmingham, P50 AG016582, UL1RR02777; University of Arizona, R01 AG031581; University of California, Davis, P30 AG010129; University of California, Irvine, P50 AG016573, P50, P50 AG016575, P50 AG016576, P50 AG016577; University of California, Los Angeles, P50 AG016570; University of California, San Diego, P50 AG005131; University of California, San Francisco, P50 AG023501, P01 AG019724; University of Kentucky, P30 AG028383, AG05144; University of Michigan, P50 AG008671; University of Pennsylvania, P30 AG010124; University of Pittsburgh, P50 AG005133, AG030653; University of Southern California, P50 AG005142; University of Texas Southwestern, P30 AG012300; University of Miami, R01 AG027944, AG010491, AG027944, AG021547, AG019757; University of Washington, P50 AG005136; Vanderbilt University, R01 AG019085; and Washington University, P50 AG005681, P01 AG03991. The Kathleen Price Bryan Brain Bank at Duke University Medical Center is funded by NINDS grant NS39764, NIMH MH60451, and by GlaxoSmithKline. Genotyping of the TGEN2 cohort was supported by Kronos Science. The TGen series was also funded by NIA grant AG041232, the Banner Alzheimer's Foundation, The Johnnie B. Byrd Sr. Alzheimer's Institute, the Medical Research Council, and the state of Arizona and also includes samples from the following sites: Newcastle Brain Tissue Resource (funding via the Medical Research Council [MRC], local NHS trusts, and Newcastle University), MRC London Brain Bank for Neurodegenerative Diseases (funding via the Medical Research Council), South West Dementia Brain Bank (funding via numerous sources including the Higher Education Funding Council for England [HEFCE], Alzheimer's Research Trust [ART], BRACE, as well as North Bristol NHS Trust Research and Innovation Department and DeNDRoN), The Netherlands Brain Bank (funding via numerous sources including Stichting MS Research, Brain Net Europe, Hersenstichting Nederland Breinbrekend Werk, International Parkinson Fonds, Internationale Stiching Alzheimer Onderzoek), Institut de Neuropatologia, Servei Anatomia Patologica, and Universitat de Barcelona). ADNI: Funding for ADNI is through the Northern California Institute for Research and Education by grants from Abbott, AstraZeneca AB, Bayer Schering Pharma AG, Bristol-Myers Squibb, Eisai Global Clinical Development, Elan Corporation, Genentech, GE Healthcare, GlaxoSmithKline, Innogenetics, Johnson & Johnson, Eli Lilly and Co., Medpace, Inc., Merck and Co., Inc., Novartis AG, Pfizer Inc, F. Hoffman-La Roche, Schering-Plough, Synarc, Inc., Alzheimer's Association, Alzheimer's Drug Discovery Foundation, the Dana Foundation, and the National Institute of Biomedical Imaging and Bioengineering and NIA grants U01 AG024904, RC2 AG036535, and K01 AG030514. Support was also provided by the Alzheimer's Association (LAF, IIRG-08-89720; MAP-V, IIRG-05-14147) and the US Department of Veterans Affairs Administration, Office of Research and Development, Biomedical Laboratory Research Program. SiGN: Stroke Genetic Network (SiGN) was supported in part by award nos. U01NS069208 and R01NS100178 from NINDS. Genetics of Early-Onset Stroke (GEOS) Study was supported by the NIH Genes, Environment and Health Initiative (GEI) grant U01 HG004436, as part of the GENEVA consortium under GEI, with additional support provided by the Mid-Atlantic Nutrition and Obesity Research Center (P30 DK072488); and the Office of Research and Development, Medical Research Service, and the Baltimore Geriatrics Research, Education, and Clinical Center of the Department of Veterans Affairs. Genotyping services were provided by the Johns Hopkins University Center for Inherited Disease Research (CIDR), which is fully funded through a federal contract from the NIH to Johns Hopkins University (contract no. HHSN268200782096C). Assistance with data cleaning was provided by the GENEVA Coordinating Center (U01 HG 004446; PI Bruce S. Weir). Study recruitment and assembly of datasets were supported by a Cooperative Agreement with the Division of Adult and Community Health, Centers for Disease Control and Prevention, and by grants from NINDS and the NIH Office of Research on Women's Health (R01 NS45012, U01 NS069208-01). METASTROKE: ASGC: Australian population control data were derived from the Hunter Community Study. This research was funded by grants from the Australian National and Medical Health Research Council (NHMRC Project Grant ID: 569257), the Australian National Heart Foundation (NHF Project Grant ID: G 04S 1623), the University of Newcastle, the Gladys M Brawn Fellowship scheme, and the Vincent Fairfax Family Foundation in Australia. E.G.H. was supported by a Fellowship from the NHF and National Stroke Foundation of Australia (ID: 100071). J.M. was supported by an Australian Postgraduate Award. BRAINS: Bio-Repository of DNA in Stroke (BRAINS) is partly funded by a Senior Fellowship from the Department of Health (UK) to P.S., the Henry Smith Charity, and the UK-India Education Research Institutive (UKIERI) from the British Council. GEOS: Genetics of Early Onset Stroke (GEOS) Study, Baltimore, was supported by GEI Grant U01 HG004436, as part of the GENEVA consortium under GEI, with additional support provided by the Mid-Atlantic Nutrition and Obesity Research Center (P30 DK072488), and the Office of Research and Development, Medical Research Service, and the Baltimore Geriatrics Research, Education, and Clinical Center of the Department of Veterans Affairs. Genotyping services were provided by the Johns Hopkins University Center for Inherited Disease Research (CIDR), which is fully funded through a federal contract from the NIH to the Johns Hopkins University (contract no. HHSN268200782096C). Assistance with data cleaning was provided by the GENEVA Coordinating Center (U01 HG 004446; PI Bruce S. Weir). Study recruitment and assembly of datasets were supported by a Cooperative Agreement with the Division of Adult and Community Health, Centers for Disease Control and Prevention, and by grants from NINDS and the NIH Office of Research on Women's Health (R01 NS45012, U01 NS069208-01). HPS: Heart Protection Study (HPS) (ISRCTN48489393) was supported by the UK MRC, British Heart Foundation, Merck and Co. (manufacturers of simvastatin), and Roche Vitamins Ltd. (manufacturers of vitamins). Genotyping was supported by a grant to Oxford University and CNG from Merck and Co. J.C.H. acknowledges support from the British Heart Foundation (FS/14/55/30806). ISGS: Ischemic Stroke Genetics Study (ISGS)/Siblings With Ischemic Stroke Study (SWISS) was supported in part by the Intramural Research Program of the NIA, NIH project Z01 AG-000954-06. ISGS/SWISS used samples and clinical data from the NIH-NINDS Human Genetics Resource Center DNA and Cell Line Repository (ccr.coriell.org/ninds), human subjects protocol nos. 2003-081 and 2004-147. ISGS/SWISS used stroke-free participants from the Baltimore Longitudinal Study of Aging (BLSA) as controls. The inclusion of BLSA samples was supported in part by the Intramural Research Program of the NIA, NIH project Z01 AG-000015-50, human subjects protocol no. 2003-078. The ISGS study was funded by NIH-NINDS Grant R01 NS-42733 (J.F.M.). The SWISS study was funded by NIH-NINDS Grant R01 NS-39987 (J.F.M.). This study used the high-performance computational capabilities of the Biowulf Linux cluster at the NIH (biowulf.nih.gov). MGH-GASROS: MGH Genes Affecting Stroke Risk and Outcome Study (MGH-GASROS) was supported by NINDS (U01 NS069208), the American Heart Association/Bugher Foundation Centers for Stroke Prevention Research 0775010N, the NIH and NHLBI's STAMPEED genomics research program (R01 HL087676), and a grant from the National Center for Research Resources. The Broad Institute Center for Genotyping and Analysis is supported by grant U54 RR020278 from the National Center for Research resources. Milan: Milano–Besta Stroke Register Collection and genotyping of the Milan cases within CEDIR were supported by the Italian Ministry of Health (grant nos.: RC 2007/LR6, RC 2008/LR6; RC 2009/LR8; RC 2010/LR8; GR-2011-02347041), FP6 LSHM-CT-2007-037273 for the PROCARDIS control samples. WTCCC2: Wellcome Trust Case-Control Consortium 2 (WTCCC2) was principally funded by the Wellcome Trust, as part of the Wellcome Trust Case Control Consortium 2 project (085475/B/08/Z and 085475/Z/08/Z and WT084724MA). The Stroke Association provided additional support for collection of some of the St George's, London cases. The Oxford cases were collected as part of the Oxford Vascular Study, which is funded by the MRC, Stroke Association, Dunhill Medical Trust, National Institute of Health Research (NIHR), and the NIHR Biomedical Research Centre, Oxford. The Edinburgh Stroke Study was supported by the Wellcome Trust (clinician scientist award to C.L.M.S.) and the Binks Trust. Sample processing occurred in the Genetics Core Laboratory of the Wellcome Trust Clinical Research Facility, Western General Hospital, Edinburgh. Much of the neuroimaging occurred in the Scottish Funding Council Brain Imaging Research Centre (https://www.ed.ac.uk/clinical-sciences/edinburgh-imaging), Division of Clinical Neurosciences, University of Edinburgh, a core area of the Wellcome Trust Clinical Research Facility, and part of the SINAPSE (Scottish Imaging Network: A Platform for Scientific Excellence) collaboration (sinapse.ac.uk), funded by the Scottish Funding Council and the Chief Scientist Office. Collection of the Munich cases and data analysis was supported by the Vascular Dementia Research Foundation. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreements no. 666881, SVDs@target (to M.D.) and no. 667375, CoSTREAM (to M.D.); the DFG as part of the Munich Cluster for Systems Neurology (EXC 1010 SyNergy) and the CRC 1123 (B3) (to M.D.); the Corona Foundation (to M.D.); the Fondation Leducq (Transatlantic Network of Excellence on the Pathogenesis of Small Vessel Disease of the Brain) (to M.D.); the e:Med program (e:AtheroSysMed) (to M.D.) and the FP7/2007-2103 European Union project CVgenes@target (grant agreement no. Health-F2-2013-601456) (to M.D.). M.F. and A.H. acknowledge support from the BHF Centre of Research Excellence in Oxford and the Wellcome Trust core award (090532/Z/09/Z). VISP: The GWAS component of the Vitamin Intervention for Stroke Prevention (VISP) study was supported by the US National Human Genome Research Institute (NHGRI), grant U01 HG005160 (PI Michèle Sale and Bradford Worrall), as part of the Genomics and Randomized Trials Network (GARNET). Genotyping services were provided by the Johns Hopkins University Center for Inherited Disease Research (CIDR), which is fully funded through a federal contract from the NIH to Johns Hopkins University. Assistance with data cleaning was provided by the GARNET Coordinating Center (U01 HG005157; PI Bruce S. Weir). Study recruitment and collection of datasets for the VISP clinical trial were supported by an investigator-initiated research grant (R01 NS34447; PI James Toole) from the US Public Health Service, NINDS, Bethesda, MD. Control data obtained through the database of genotypes and phenotypes (dbGAP) maintained and supported by the United States National Center for Biotechnology Information, US National Library of Medicine. WHI: Funding support for WHI-GARNET was provided through the NHGRI GARNET (grant no. U01 HG005152). Assistance with phenotype harmonization and genotype cleaning, as well as with general study coordination, was provided by the GARNET Coordinating Center (U01 HG005157). Funding support for genotyping, which was performed at the Broad Institute of MIT and Harvard, was provided by the GEI (U01 HG004424). R.L. is a senior clinical investigator of FWO Flanders. F.W.A. is supported by a Dekker scholarship-Junior Staff Member 2014T001–Netherlands Heart Foundation and UCL Hospitals NIHR Biomedical Research Centre.