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Familial forms of the severe immunoregulatory disease hemophagocytic lymphohistiocytosis (HLH) arise from biallelic mutations in the PRF1, UNC13D, STXBP2, and STX11 genes. Early and accurate diagnosis of the disease is important to determine the most appropriate treatment option, including potentially curative stem cell transplantation. The diagnosis of familial HLH (FHL) is traditionally based on finding biallelic mutations in patients with HLH symptoms and reduced natural killer (NK)-cell cytotoxicity. However, patients often have a low NK-cell count or receive immunosuppressive therapies that may render the NK-cell cytotoxicity assay unreliable. Furthermore, to fully understand the nature of a disease it is critical to directly assess the effect of mutations on cellular function; this will help to avoid instances in which carriers of innocuous mutations may be recommended for invasive procedures including transplantation. To overcome this diagnostic problem, we have developed a rapid and robust method that takes advantage of the functional equivalence of the human and mouse orthologues of PRF1, UNC13D, STX11, and STXBP2 proteins. By knocking out endogenous mouse genes in CD8+ T cells and simultaneously replacing them with their mutated human orthologues, we can accurately assess the effect of mutations on cell function. The wide dynamic range of this novel system allowed us to understand the basis of, otherwise cryptic, cases of FHL or HLH and, in some instances, to demonstrate that previously reported mutations are unlikely to cause FHL. This novel approach provides valuable new information to enable more accurate diagnosis and treatment of patients with HLH or FHL who inherit mutations of undetermined pathogenicity.

BACKGROUND & AIMS: Colorectal cancer risk can be lowered by adherence to the World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) guidelines. We derived metabolic signatures of adherence to these guidelines and tested their associations with colorectal cancer risk in the European Prospective Investigation into Cancer and Nutrition cohort. METHODS: Scores reflecting adherence to the WCRF/AICR recommendations (scale, 1-5) were calculated from participant data on weight maintenance, physical activity, diet, and alcohol among a discovery set of 5738 cancer-free European Prospective Investigation into Cancer and Nutrition participants with metabolomics data. Partial least-squares regression was used to derive fatty acid and endogenous metabolite signatures of the WCRF/AICR score in this group. In an independent set of 1608 colorectal cancer cases and matched controls, odds ratios (ORs) and 95% CIs were calculated for colorectal cancer risk per unit increase in WCRF/AICR score and per the corresponding change in metabolic signatures using multivariable conditional logistic regression. RESULTS: Higher WCRF/AICR scores were characterized by metabolic signatures of increased odd-chain fatty acids, serine, glycine, and specific phosphatidylcholines. Signatures were inversely associated more strongly with colorectal cancer risk (fatty acids: OR, 0.51 per unit increase; 95% CI, 0.29-0.90; endogenous metabolites: OR, 0.62 per unit change; 95% CI, 0.50-0.78) than the WCRF/AICR score (OR, 0.93 per unit change; 95% CI, 0.86-1.00) overall. Signature associations were stronger in male compared with female participants. CONCLUSIONS: Metabolite profiles reflecting adherence to WCRF/AICR guidelines and additional lifestyle or biological risk factors were associated with colorectal cancer. Measuring a specific panel of metabolites representative of a healthy or unhealthy lifestyle may identify strata of the population at higher risk of colorectal cancer.

When killing through the granule exocytosis pathway, cytotoxic lymphocytes release key effector molecules into the immune synapse, perforin and granzymes, to initiate target cell killing. The pore-forming perforin is essential for the function of cytotoxic lymphocytes, as its pores disrupt the target cell membrane and allow diffusion of pro-apoptotic serine proteases, granzyme, into the target cell, where they initiate various cell death cascades. Unlike human perforin, the detection of its murine counterpart in a live cell system has been problematic due its relatively low expression level and the lack of sensitive antibodies. The lack of a suitable methodology to visualise murine perforin secretion into the synapse hinders the study of the cytotoxic lymphocyte secretory machinery in murine models of human disease. Here, we describe a novel recombinant technology, whereby a short ALFA-tag sequence has been fused with the amino-terminus of a mature murine perforin, and this allowed its detection by the highly specific FluoTag®-X2 anti-ALFA nanobodies using both Total Internal Reflection Fluorescence (TIRF) microscopy of an artificial synapse, and confocal microscopy of the physiological immune synapse with a target cell. This methodology can have broad application in the field of cytotoxic lymphocyte biology and for the many models of human disease.

BACKGROUND: Epidemiological studies of associations between metabolites and cancer risk have typically focused on specific cancer types separately. Here, we designed a multivariate pan-cancer analysis to identify metabolites potentially associated with multiple cancer types, while also allowing the investigation of cancer type-specific associations. METHODS: We analysed targeted metabolomics data available for 5828 matched case-control pairs from cancer-specific case-control studies on breast, colorectal, endometrial, gallbladder, kidney, localized and advanced prostate cancer, and hepatocellular carcinoma nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. From pre-diagnostic blood levels of an initial set of 117 metabolites, 33 cluster representatives of strongly correlated metabolites and 17 single metabolites were derived by hierarchical clustering. The mutually adjusted associations of the resulting 50 metabolites with cancer risk were examined in penalized conditional logistic regression models adjusted for body mass index, using the data-shared lasso penalty. RESULTS: Out of the 50 studied metabolites, (i) six were inversely associated with the risk of most cancer types: glutamine, butyrylcarnitine, lysophosphatidylcholine a C18:2, and three clusters of phosphatidylcholines (PCs); (ii) three were positively associated with most cancer types: proline, decanoylcarnitine, and one cluster of PCs; and (iii) 10 were specifically associated with particular cancer types, including histidine that was inversely associated with colorectal cancer risk and one cluster of sphingomyelins that was inversely associated with risk of hepatocellular carcinoma and positively with endometrial cancer risk. CONCLUSIONS: These results could provide novel insights for the identification of pathways for cancer development, in particular those shared across different cancer types.

BACKGROUND: Excess bodyweight and related metabolic perturbations have been implicated in kidney cancer aetiology, but the specific molecular mechanisms underlying these relationships are poorly understood. In this study, we sought to identify circulating metabolites that predispose kidney cancer and to evaluate the extent to which they are influenced by body mass index (BMI). METHODS AND FINDINGS: We assessed the association between circulating levels of 1,416 metabolites and incident kidney cancer using pre-diagnostic blood samples from up to 1,305 kidney cancer case-control pairs from 5 prospective cohort studies. Cases were diagnosed on average 8 years after blood collection. We found 25 metabolites robustly associated with kidney cancer risk. In particular, 14 glycerophospholipids (GPLs) were inversely associated with risk, including 8 phosphatidylcholines (PCs) and 2 plasmalogens. The PC with the strongest association was PC ae C34:3 with an odds ratio (OR) for 1 standard deviation (SD) increment of 0.75 (95% confidence interval [CI]: 0.68 to 0.83, p = 2.6 × 10-8). In contrast, 4 amino acids, including glutamate (OR for 1 SD = 1.39, 95% CI: 1.20 to 1.60, p = 1.6 × 10-5), were positively associated with risk. Adjusting for BMI partly attenuated the risk association for some-but not all-metabolites, whereas other known risk factors of kidney cancer, such as smoking and alcohol consumption, had minimal impact on the observed associations. A mendelian randomisation (MR) analysis of the influence of BMI on the blood metabolome highlighted that some metabolites associated with kidney cancer risk are influenced by BMI. Specifically, elevated BMI appeared to decrease levels of several GPLs that were also found inversely associated with kidney cancer risk (e.g., -0.17 SD change [ßBMI] in 1-(1-enyl-palmitoyl)-2-linoleoyl-GPC (P-16:0/18:2) levels per SD change in BMI, p = 3.4 × 10-5). BMI was also associated with increased levels of glutamate (ßBMI: 0.12, p = 1.5 × 10-3)

BACKGROUND: Metabolomics is a promising molecular tool for identifying novel etiological pathways leading to cancer. In an earlier prospective study among pre- and postmenopausal women not using exogenous hormones, we observed a higher risk of breast cancer associated with higher blood concentrations of one metabolite (acetylcarnitine) and a lower risk associated with higher blood concentrations of seven others (arginine, asparagine, phosphatidylcholines (PCs) aa C36:3, ae C34:2, ae C36:2, ae C36:3, and ae C38:2). METHODS: To identify determinants of these breast cancer-related metabolites, we conducted a cross-sectional analysis to identify their lifestyle and anthropometric correlates in 2358 women, who were previously included as controls in case-control studies nested within the European Prospective Investigation into Cancer and Nutrition cohort and not using exogenous hormones at blood collection. Associations of each metabolite concentration with 42 variables were assessed using linear regression models in a discovery set of 1572 participants. Significant associations were evaluated in a validation set (n = 786). RESULTS: For the metabolites previously associated with a lower risk of breast cancer, concentrations of PCs ae C34:2, C36:2, C36:3, and C38:2 were negatively associated with adiposity and positively associated with total and saturated fat intakes. PC ae C36:2 was also negatively associated with alcohol consumption and positively associated with two scores reflecting adherence to a healthy lifestyle. Asparagine concentration was negatively associated with adiposity. Arginine and PC aa C36:3 concentrations were not associated to any of the factors examined. For the metabolite previously associated with a higher risk of breast cancer, acetylcarnitine, a positive association with age was observed. CONCLUSIONS: These associations may indicate possible mechanisms underlying associations between lifestyle and anthropometric factors, and risk of breast cance

BACKGROUND: Endometrial cancer is strongly associated with obesity and dysregulation of metabolic factors such as estrogen and insulin signaling are causal risk factors for this malignancy. To identify additional novel metabolic pathways associated with endometrial cancer we performed metabolomic analyses on pre-diagnostic plasma samples from 853 case-control pairs from the European Prospective Investigation into Cancer and Nutrition (EPIC). METHODS: A total of 129 metabolites (acylcarnitines, amino acids, biogenic amines, glycerophospholipids, hexoses, and sphingolipids) were measured by liquid chromatography-mass spectrometry. Conditional logistic regression estimated the associations of metabolites with endometrial cancer risk. An analysis focusing on clusters of metabolites using the bootstrap lasso method was also employed. RESULTS: After adjustment for body mass index, sphingomyelin [SM] C18:0 was positively (OR1SD: 1.18, 95% CI: 1.05-1.33), and glycine, serine, and free carnitine (C0) were inversely (OR1SD: 0.89, 95% CI: 0.80-0.99; OR1SD: 0.89, 95% CI: 0.79-1.00 and OR1SD: 0.91, 95% CI: 0.81-1.00, respectively) associated with endometrial cancer risk. Serine, C0 and two sphingomyelins were selected by the lasso method in >90% of the bootstrap samples. The ratio of esterified to free carnitine (OR1SD: 1.14, 95% CI: 1.02-1.28) and that of short chain to free acylcarnitines (OR1SD: 1.12, 95% CI: 1.00-1.25) were positively associated with endometrial cancer risk. Further adjustment for C-peptide or other endometrial cancer risk factors only minimally altered the results. CONCLUSION: These findings suggest that variation in levels of glycine, serine, SM C18:0 and free carnitine may represent specific pathways linked to endometrial cancer development. If causal, these pathways may offer novel targets for endometrial cancer prevention.

Pooling metabolomics data across studies is often desirable to increase the statistical power of the analysis. However, this can raise methodological challenges as several preanalytical and analytical factors could introduce differences in measured concentrations and variability between datasets. Specifically, different studies may use variable sample types (e.g., serum versus plasma) collected, treated, and stored according to different protocols, and assayed in different laboratories using different instruments. To address these issues, a new pipeline was developed to normalize and pool metabolomics data through a set of sequential steps: (i) exclusions of the least informative observations and metabolites and removal of outliers; imputation of missing data; (ii) identification of the main sources of variability through principal component partial R-square (PC-PR2) analysis; (iii) application of linear mixed models to remove unwanted variability, including samples' originating study and batch, and preserve biological variations while accounting for potential differences in the residual variances across studies. This pipeline was applied to targeted metabolomics data acquired using Biocrates AbsoluteIDQ kits in eight case-control studies nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Comprehensive examination of metabolomics measurements indicated that the pipeline improved the comparability of data across the studies. Our pipeline can be adapted to normalize other molecular data, including biomarkers as well as proteomics data, and could be used for pooling molecular datasets, for example in international consortia, to limit biases introduced by inter-study variability. This versatility of the pipeline makes our work of potential interest to molecular epidemiologists.

Perforin is a pore forming protein used by cytotoxic T lymphocytes to remove cancerous or virus-infected cells during the immune response. During the response, the lymphocyte membrane becomes refractory to perforin function by accumulating densely ordered lipid rafts and externalizing negatively charged lipid species. The dense membrane packing lowers the capacity of perforin to bind, and the negatively charged lipids scavenge any residual protein before pore formation. Using atomic force microscopy on model membrane systems, we here provide insight into the molecular basis of perforin lipid specificity.

BACKGROUND: Although lifestyle factors have been studied in relation to individual non-communicable diseases (NCDs), their association with development of a subsequent NCD, defined as multimorbidity, has been scarcely investigated. The aim of this study was to investigate associations between five lifestyle factors and incident multimorbidity of cancer and cardiometabolic diseases. METHODS: In this prospective cohort study, 291,778 participants (64% women) from seven European countries, mostly aged 43 to 58 years and free of cancer, cardiovascular disease (CVD), and type 2 diabetes (T2D) at recruitment, were included. Incident multimorbidity of cancer and cardiometabolic diseases was defined as developing subsequently two diseases including first cancer at any site, CVD, and T2D in an individual. Multi-state modelling based on Cox regression was used to compute hazard ratios (HR) and 95% confidence intervals (95% CI) of developing cancer, CVD, or T2D, and subsequent transitions to multimorbidity, in relation to body mass index (BMI), smoking status, alcohol intake, physical activity, adherence to the Mediterranean diet, and their combination as a healthy lifestyle index (HLI) score. Cumulative incidence functions (CIFs) were estimated to compute 10-year absolute risks for transitions from healthy to cancer at any site, CVD (both fatal and non-fatal), or T2D, and to subsequent multimorbidity after each of the three NCDs. RESULTS: During a median follow-up of 11 years, 1910 men and 1334 women developed multimorbidity of cancer and cardiometabolic diseases. A higher HLI, reflecting healthy lifestyles, was strongly inversely associated with multimorbidity, with hazard ratios per 3-unit increment of 0.75 (95% CI, 0.71 to 0.81), 0.84 (0.79 to 0.90), and 0.82 (0.77 to 0.88) after cancer, CVD, and T2D, respectively. After T2D, the 10-year absolute risks of multimorbidity were 40% and 25% for men and women, respectively, with unhealthy lifestyle, and 30% and 18% for men and

BACKGROUND: Bile acids have been proposed to promote colon carcinogenesis. However, there are limited prospective data on circulating bile acid levels and colon cancer risk in humans. METHODS: Associations between prediagnostic plasma levels of 17 primary, secondary, and tertiary bile acid metabolites (conjugated and unconjugated) and colon cancer risk were evaluated in a nested case-control study within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Bile acid levels were quantified by tandem mass spectrometry in samples from 569 incident colon cancer cases and 569 matched controls. Multivariable logistic regression analyses were used to estimate odds ratios (ORs) for colon cancer risk across quartiles of bile acid concentrations. RESULTS: Positive associations were observed between colon cancer risk and plasma levels of seven conjugated bile acid metabolites: the primary bile acids glycocholic acid (ORquartile 4 vs quartile 1= 2.22, 95% confidence interval [CI] = 1.52 to 3.26), taurocholic acid (OR = 1.78, 95% CI = 1.23 to 2.58), glycochenodeoxycholic acid (OR = 1.68, 95% CI = 1.13 to 2.48), taurochenodeoxycholic acid (OR = 1.62, 95% CI = 1.11 to 2.36), and glycohyocholic acid (OR = 1.65, 95% CI = 1.13 to 2.40), and the secondary bile acids glycodeoxycholic acid (OR = 1.68, 95% CI = 1.12 to 2.54) and taurodeoxycholic acid (OR = 1.54, 95% CI = 1.02 to 2.31). By contrast, unconjugated bile acids and tertiary bile acids were not associated with risk. CONCLUSIONS: This prospective study showed that prediagnostic levels of certain conjugated primary and secondary bile acids were positively associated with risk of colon cancer. Our findings support experimental data to suggest that a high bile acid load is colon cancer promotive.

BACKGROUND: Metabolomics is a promising molecular tool to identify novel etiologic pathways leading to cancer. Using a targeted approach, we prospectively investigated the associations between metabolite concentrations in plasma and breast cancer risk. METHODS: A nested case-control study was established within the European Prospective Investigation into Cancer cohort, which included 1624 first primary incident invasive breast cancer cases (with known estrogen and progesterone receptor and HER2 status) and 1624 matched controls. Metabolites (n = 127, acylcarnitines, amino acids, biogenic amines, glycerophospholipids, hexose, sphingolipids) were measured by mass spectrometry in pre-diagnostic plasma samples and tested for associations with breast cancer incidence using multivariable conditional logistic regression. RESULTS: Among women not using hormones at baseline (n = 2248), and after control for multiple tests, concentrations of arginine (odds ratio [OR] per SD = 0.79, 95% confidence interval [CI] = 0.70-0.90), asparagine (OR = 0.83 (0.74-0.92)), and phosphatidylcholines (PCs) ae C36:3 (OR = 0.83 (0.76-0.90)), aa C36:3 (OR = 0.84 (0.77-0.93)), ae C34:2 (OR = 0.85 (0.78-0.94)), ae C36:2 (OR = 0.85 (0.78-0.88)), and ae C38:2 (OR = 0.84 (0.76-0.93)) were inversely associated with breast cancer risk, while the acylcarnitine C2 (OR = 1.23 (1.11-1.35)) was positively associated with disease risk. In the overall population, C2 (OR = 1.15 (1.06-1.24)) and PC ae C36:3 (OR = 0.88 (0.82-0.95)) were associated with risk of breast cancer, and these relationships did not differ by breast cancer subtype, age at diagnosis, fasting status, menopausal status, or adiposity. CONCLUSIONS: These findings point to potentially novel pathways and biomarkers of breast cancer development. Results warrant replication in other epidemiological studies.

Killer T cells (cytotoxic T lymphocytes, CTLs) maintain immune homoeostasis by eliminating virus-infected and cancerous cells. CTLs achieve this by forming an immunological synapse with their targets and secreting a pore-forming protein (perforin) and pro-apoptotic serine proteases (granzymes) into the synaptic cleft. Although the CTL and the target cell are both exposed to perforin within the synapse, only the target cell membrane is disrupted, while the CTL is invariably spared. How CTLs escape unscathed remains a mystery. Here, we report that CTLs achieve this via two protective properties of their plasma membrane within the synapse: high lipid order repels perforin and, in addition, exposed phosphatidylserine sequesters and inactivates perforin. The resulting resistance of CTLs to perforin explains their ability to kill target cells in rapid succession and to survive these encounters. Furthermore, these mechanisms imply an unsuspected role for plasma membrane organization in protecting cells from immune attack.

Identifying the metabolites associated with alcohol consumption may provide insights into the metabolic pathways through which alcohol may affect human health. We studied associations of alcohol consumption with circulating concentrations of 123 metabolites among 2974 healthy participants from the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Alcohol consumption at recruitment was self-reported through dietary questionnaires. Metabolite concentrations were measured by tandem mass spectrometry (BIOCRATES AbsoluteIDQTM p180 kit). Data were randomly divided into discovery (2/3) and replication (1/3) sets. Multivariable linear regression models were used to evaluate confounder-adjusted associations of alcohol consumption with metabolite concentrations. Metabolites significantly related to alcohol intake in the discovery set (FDR q-value < 0.05) were further tested in the replication set (Bonferroni-corrected p-value < 0.05). Of the 72 metabolites significantly related to alcohol intake in the discovery set, 34 were also significant in the replication analysis, including three acylcarnitines, the amino acid citrulline, four lysophosphatidylcholines, 13 diacylphosphatidylcholines, seven acyl-alkylphosphatidylcholines, and six sphingomyelins. Our results confirmed earlier findings that alcohol consumption was associated with several lipid metabolites, and possibly also with specific acylcarnitines and amino acids. This provides further leads for future research studies aiming at elucidating the mechanisms underlying the effects of alcohol in relation to morbid conditions.

BACKGROUND: Hepatocellular carcinoma (HCC), the most prevalent form of liver cancer, is difficult to diagnose and has limited treatment options with a low survival rate. Aside from a few key risk factors, such as hepatitis, high alcohol consumption, smoking, obesity, and diabetes, there is incomplete etiologic understanding of the disease and little progress in identification of early risk biomarkers. METHODS: To address these aspects, an untargeted nuclear magnetic resonance metabolomic approach was applied to pre-diagnostic serum samples obtained from first incident, primary HCC cases (n = 114) and matched controls (n = 222) identified from amongst the participants of a large European prospective cohort. RESULTS: A metabolic pattern associated with HCC risk comprised of perturbations in fatty acid oxidation and amino acid, lipid, and carbohydrate metabolism was observed. Sixteen metabolites of either endogenous or exogenous origin were found to be significantly associated with HCC risk. The influence of hepatitis infection and potential liver damage was assessed, and further analyses were made to distinguish patterns of early or later diagnosis. CONCLUSION: Our results show clear metabolic alterations from early stages of HCC development with application for better etiologic understanding, prevention, and early detection of this increasingly common cancer.

BACKGROUND: Results from several cohort and case-control studies suggest a protective association between current alcohol intake and risk of thyroid carcinoma, but the epidemiological evidence is not completely consistent and several questions remain unanswered. METHODS: The association between alcohol consumption at recruitment and over the lifetime and risk of differentiated thyroid carcinoma was examined in the European Prospective Investigation into Cancer and Nutrition. Among 477 263 eligible participants (70% women), 556 (90% women) were diagnosed with differentiated thyroid carcinoma over a mean follow-up of 11 years. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using multivariable Cox proportional hazards models. RESULTS: Compared with participants consuming 0.1-4.9 g of alcohol per day at recruitment, participants consuming 15 or more grams (approximately 1-1.5 drinks) had a 23% lower risk of differentiated thyroid carcinoma (HR=0.77; 95% CI=0.60-0.98). These findings did not differ greatly when analyses were conducted for lifetime alcohol consumption, although the risk estimates were attenuated and not statistically significant anymore. Similar results were observed by type of alcoholic beverage, by differentiated thyroid carcinoma histology or according to age, sex, smoking status, body mass index and diabetes. CONCLUSIONS: Our study provides some support to the hypothesis that moderate alcohol consumption may be associated with a lower risk of papillary and follicular thyroid carcinomas.

The effective engagement of cytotoxic lymphocytes (CLs) with their target cells is essential for the removal of virus-infected and malignant cells from the body. The spatiotemporal properties that define CL engagement and killing of target cells remain largely uncharacterized due to a lack of biological reporters. We have used a novel live cell microscopy technique to visualize the engagement of primary human and mouse CL with their targets and the subsequent delivery of the lethal hit. Extensive quantitative real-time analysis of individual effector-target cell conjugates demonstrated that a single effector calcium flux event was sufficient for the degranulation of human CLs, resulting in the breach of the target cell membrane by perforin within 65-100 s. In contrast, mouse CLs demonstrated distinct calcium signaling profiles leading to degranulation: whereas mouse NKs required a single calcium flux event, CD8(+) T cells typically required several calcium flux events before perforin delivery. Irrespective of their signaling profile, every target cell that was damaged by perforin died by apoptosis. To our knowledge, we demonstrate for the first time that perforin pore delivery is unidirectional, occurring exclusively on the target cell membrane, but sparing the killer cell. Despite this, the CTL membrane was not intrinsically perforin resistant, as intact CTLs presented as targets to effector CTLs were capable of being killed by perforin-dependent mechanisms. Our results highlight the remarkable efficiency and specificity of perforin pore delivery by CLs.