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Deucravacitinib, a novel, selective inhibitor of TYK2 is currently under review at the FDA and EMA for treatment of moderate-to-severe plaque psoriasis. It is unclear whether recent safety concerns (i.e. elevated rates of lung cancer and lymphoma) related to similar medications (i.e. other JAK inhibitors) are shared with this novel TYK2 inhibitor. We used a partial loss-of-function variant in TYK2 (rs34536443), previously shown to protect against psoriasis and other autoimmune diseases, to evaluate the potential effect of therapeutic TYK2 inhibition on risk of lung cancer and non-Hodgkin lymphoma. Summary genetic association data on lung cancer risk were obtained from a GWAS meta-analysis of 29,266 cases and 56,450 controls in the Integrative Analysis of Lung Cancer Risk and Etiology (INTEGRAL) consortium. Summary genetic association data on non-Hodgkin lymphoma risk were obtained from a GWAS meta-analysis of 8,489 cases and 374,506 controls in the UK Biobank and InterLymph consortium. In the primary analysis, each copy of the minor allele of rs34536443, representing partial TYK2 inhibition, was associated with an increased risk of lung cancer (OR 1.15, 95% CI 1.09–1.23, P = 2.29 × 10(−6)) and non-Hodgkin lymphoma (OR 1.18, 95% CI 1.05–1.33, P = 5.25 × 10(−3)). Our analyses using an established partial loss-of-function mutation to mimic TYK2 inhibition provide genetic evidence that therapeutic TYK2 inhibition may increase risk of lung cancer and non-Hodgkin lymphoma. These findings, consistent with recent reports from post-marketing trials of similar JAK inhibitors, could have important implications for future safety assessment of Deucravacitinib and other TYK2 inhibitors in development.

BackgroundUnderstanding the role of circulating proteins in cancer risk can reveal key biological pathways and identify novel therapeutic targets for cancer prevention.MethodsWe investigated the associations of 2,094 circulating proteins with risk of nine common cancers (bladder, breast, endometrium, head and neck, lung, ovary, pancreas, kidney, and malignant non-melanoma) usingcispQTL Mendelian randomisation (MR) and colocalization. Findings for proteins with support from both MR, after correction for multiple-testing, and colocalization were replicated using an independent cancer GWAS. Additionally, MR and colocalization phenome-wide association analyses (PHEWAS) were conducted to identify potential adverse side-effects of altering risk proteins. Finally, we mapped cancer risk proteins to drug and ongoing clinical trials targets.ResultsWe identified 40 proteins associated with cancer risk, of which a majority replicated and were novel. Among these were proteins associated with common cancers, such as PLAUR and risk of breast cancer [odds ratio per standard deviation increment (OR): 2.27, 95% CI: 1.88 to 2.74], and with high-mortality cancers, such as CTRB1 and pancreatic cancer [OR: 0.79, 95% CI: 0.73 to 0.85]. PHEWAS highlighted multiple links between proteins and potential adverse effects of protein-altering interventions. Additionally, 18 proteins associated with cancer risk mapped to existing therapeutic interventions, while 15 were not currently known to be under clinical investigation, such as GAS1 and triple negative breast cancer [OR: 1.88, 95% CI: 1.42 to 2.47].ConclusionOur findings emphasize the importance of proteomics for improving our understanding of cancer aetiology. Additionally, we demonstrate the benefit of in-depth protein PHEWAS analyses on risk proteins to identify potential adverse side-effects of protein-altering interventions. Using these methods, we identify a subset of risk proteins as potential drug targets for the prevention and treatment of cancer as well as opportunities for drug repurposing.

Background:Genome-wide association studies (GWASs) have identified genetic susceptibility variants for both leukocyte telomere length (LTL) and lung cancer susceptibility. Our study aims to explore the shared genetic basis between these traits and investigate their impact on somatic environment of lung tumours.Methods:We performed genetic correlation, Mendelian randomisation (MR), and colocalisation analyses using the largest available GWASs summary statistics of LTL (N=464,716) and lung cancer (N=29,239 cases and 56,450 controls). Principal components analysis based on RNA-sequencing data was used to summarise gene expression profile in lung adenocarcinoma cases from TCGA (N=343).Results:Although there was no genome-wide genetic correlation between LTL and lung cancer risk, longer LTL conferred an increased risk of lung cancer regardless of smoking status in the MR analyses, particularly for lung adenocarcinoma. Of the 144 LTL genetic instruments, 12 colocalised with lung adenocarcinoma risk and revealed novel susceptibility loci, including MPHOSPH6, PRPF6, and POLI. The polygenic risk score for LTL was associated with a specific gene expression profile (PC2) in lung adenocarcinoma tumours. The aspect of PC2 associated with longer LTL was also associated with being female, never smokers, and earlier tumour stages. PC2 was strongly associated with cell proliferation score and genomic features related to genome stability, including copy number changes and telomerase activity.Conclusions:This study identified an association between longer genetically predicted LTL and lung cancer and sheds light on the potential molecular mechanisms related to LTL in lung adenocarcinomas.Funding:Institut National du Cancer (GeniLuc2017-1-TABAC-03-CIRC-1-TABAC17‐022), INTEGRAL/NIH (5U19CA203654-03), CRUK (C18281/A29019), and Agence Nationale pour la Recherche (ANR-10-INBS-09).

The blood proteome reflects homeostatic and dynamic cellular processes across human organs. However, few blood proteomics studies of sufficient depth and size have been reported in breast cancer. To comprehensively identify circulating proteins with a causal role in breast cancer we measured 2,929 unique proteins in plasma from 598 women selected from the Karolinska Mammography Project and explored associations between proteins levels, clinical characteristics, and gene variants. The analysis revealed 812 cis-acting protein quantitative trait loci (pQTL), which were used as instruments in Mendelian randomisation (MR) analysis of breast cancer. Five proteins (P < 1.7x10-5, Bonferroni-corrected) with a potential causal role in breast cancer risk were revealed (CD160, DNPH1, LAYN, LRRC37A2 and TLR1). Confirming the MR findings in independent cohorts (FinnGen R9 and the UK Biobank), our study suggests that these proteins should be further explored as potential drug targets in breast cancer.

C-statistics by tumor histology for variable lag-times since blood donation

Purpose: About 60% of ovarian cancers are diagnosed at late stage, when 5-year survival is less than 30% in contrast to 90% for local disease. This has prompted search for early detection biomarkers. For initial testing, specimens taken months or years before ovarian cancer diagnosis are the best source of information to evaluate early detection biomarkers. Here we evaluate the most promising ovarian cancer screening biomarkers in prospectively collected samples from the European Prospective Investigation into Cancer and Nutrition study.Experimental Design: We measured CA125, HE4, CA72.4, and CA15.3 in 810 invasive epithelial ovarian cancer cases and 1,939 controls. We calculated the sensitivity at 95% and 98% specificity as well as area under the receiver operator curve (C-statistic) for each marker individually and in combination. In addition, we evaluated marker performance by stage at diagnosis and time between blood draw and diagnosis.Results: We observed the best discrimination between cases and controls within 6 months of diagnosis for CA125 (C-statistic = 0.92), then HE4 (0.84), CA72.4 (0.77), and CA15.3 (0.73). Marker performance declined with longer time between blood draw and diagnosis and for earlier staged disease. However, assessment of discriminatory ability at early stage was limited by small numbers. Combinations of markers performed modestly, but significantly better than any single marker.Conclusions: CA125 remains the single best marker for the early detection of invasive epithelial ovarian cancer, but can be slightly improved by combining with other markers. Identifying novel markers for ovarian cancer will require studies including larger numbers of early-stage cases. Clin Cancer Res; 22(18); 4664–75. ©2016 AACR.See related commentary by Skates, p. 4542

Case characteristics (median (min-max) or n (%)) by histologic subtypes in the EPIC cohort

Increasing evidence points to a role for inflammation in lung carcinogenesis. A small number of circulating inflammatory proteins have been identified as showing elevated levels prior to lung cancer diagnosis, indicating the potential for prospective circulating protein concentration as a marker of early carcinogenesis. To identify novel markers of lung cancer risk, we measured a panel of 92 circulating inflammatory proteins in 648 prediagnostic blood samples from two prospective cohorts in Italy and Norway (women only). To preserve the comparability of results and protect against confounding factors, the main statistical analyses were conducted in women from both studies, with replication sought in men (Italian participants). Univariate and penalized regression models revealed for the first time higher blood levels of CDCP1 protein in cases that went on to develop lung cancer compared with controls, irrespective of time to diagnosis, smoking habits, and gender. This association was validated in an additional 450 samples. Associations were stronger for future cases of adenocarcinoma where CDCP1 showed better explanatory performance. Integrative analyses combining gene expression and protein levels of CDCP1 measured in the same individuals suggested a link between CDCP1 and the expression of transcripts of LRRN3 and SEM1. Enrichment analyses indicated a potential role for CDCP1 in pathways related to cell adhesion and mobility, such as the WNT/β-catenin pathway. Overall, this study identifies lung cancer–related dysregulation of CDCP1 expression years before diagnosis.Significance:Prospective proteomics analyses reveal an association between increased levels of circulating CDCP1 and lung carcinogenesis irrespective of smoking and years before diagnosis, and integrating gene expression indicates potential underlying mechanisms.See related commentary by Itzstein et al., p. 3441.

Supplementary Tables S1-3 and Figures S1-3. Table S1: Median, interquartile range (IQR), minimum (Min.) and maximum (max.) of follow-up time by cancer site. Table S2: Hazard ratios (HRs) and 95% confidence intervals (CIs) of cancer risk according to circulating insulin-like growth factor-I concentrations. Table S3: Hazard ratios (HRs) and 95% confidence intervals (CIs) of cancer risk according to circulating insulin-like growth factor-I concentrations stratified by follow-up time, sex and age-group. Figure S1: Flow diagram for reaching the analytical sample. Figure S2: Hazard ratios (HRs) and 95% confidence intervals (CIs) for cancer risk per 5 nmol/l higher insulin-like growth factor-I concentration by cancer site and sex. Figure S3: Hazard ratios (HRs) and 95% confidence intervals (CIs) for cancer risk per 5 nmol/l higher insulin-like growth factor-I concentration by cancer site and age (

Evaluation of added discriminatory ability of each biomarker using Net Reclassification Improvement (NRI)

Supplementary Methods, Figures and Tables.

Circulating insulin-like growth factor I (IGF-I) is positively associated with the risks of colorectal, breast, and prostate cancer, but evidence for other less common cancers is limited. In this study, we investigated associations between serum IGF-I concentrations and incidence of less common cancers in the UK Biobank study. To enable comparison of effect estimates, and as positive controls, both common and less common cancer sites (total 30) were included in an outcome-wide analysis. Data from 394,388 cancer-free participants in the UK Biobank study were analyzed. Multivariable adjusted Cox proportional hazards models were used to determine associations between baseline serum IGF-I concentrations and cancer incidence, using repeated IGF-I measurements from up to 14,149 participants to correct for regression dilution bias. Higher IGF-I concentration was associated with increased risks of thyroid cancer [HR per 5 nmol/L higher concentration 1.18; 95% confidence interval (CI), 1.01–1.37] in addition to colorectal (HR, 1.08; 95% CI, 1.03–1.13), breast (HR, 1.11; 95% CI, 1.07–1.15), and prostate cancer (HR, 1.08; 95% CI, 1.05–1.12), and reduced risks of ovarian and liver cancer. Mean follow-up was 6.9 years and the possibility that the observed associations may be influenced by reverse causality bias cannot be excluded. Additional nominally significant associations with malignant melanoma, multiple myeloma, oral cancer, and esophageal squamous cell carcinoma did not survive correction for multiple testing. Studies with longer follow-up and pooled analyses are needed to further assess how broad the role of IGF-I is in cancer development.Significance:The results from this outcome-wide analysis are consistent with a positive association of IGF-I with cancers at several sites.

Spearman coefficients of correlation between detection markers

BackgroundTo evaluate whether circulating proteins are associated with survival after lung cancer diagnosis, and whether they can improve prediction of prognosis.MethodsWe measured up to 1159 proteins in blood samples from 708 participants in 6 cohorts. Samples were collected within 3 years prior to lung cancer diagnosis. We used Cox proportional hazards models to identify proteins associated with overall mortality after lung cancer diagnosis. To evaluate model performance, we used a round-robin approach in which models were fit in 5 cohorts and evaluated in the 6th cohort. Specifically, we fit a model including 5 proteins and clinical parameters and compared its performance with clinical parameters only.FindingsThere were 86 proteins nominally associated with mortality (p < 0.05), but only CDCP1 remained statistically significant after accounting for multiple testing (hazard ratio per standard deviation: 1.19, 95% CI: 1.10–1.30, unadjusted p = 0.00004). The external C-index for the protein-based model was 0.63 (95% CI: 0.61–0.66), compared with 0.62 (95% CI: 0.59–0.64) for the model with clinical parameters only. Inclusion of proteins did not provide a statistically significant improvement in discrimination (C-index difference: 0.015, 95% CI: −0.003 to 0.035).InterpretationBlood proteins measured within 3 years prior to lung cancer diagnosis were not strongly associated with lung cancer survival, nor did they importantly improve prediction of prognosis beyond clinical information.FundingNo explicit funding for this study. Authors and data collection supported by the US National Cancer Institute (U19CA203654), INCA (France, 2019-1-TABAC-01), Cancer Research Foundation of Northern Sweden (AMP19-962), and Swedish Department of Health Ministry. Background: To evaluate whether circulating proteins are associated with survival after lung cancer diagnosis, and whether they can improve prediction of prognosis. Methods: We measured up to 1159 proteins in blood samples from 708 participants in 6 cohorts. Samples were collected within 3 years prior to lung cancer diagnosis. We used Cox proportional hazards models to identify proteins associated with overall mortality after lung cancer diagnosis. To evaluate model performance, we used a round-robin approach in which models were fit in 5 cohorts and evaluated in the 6th cohort. Specifically, we fit a model including 5 proteins and clinical parameters and compared its performance with clinical parameters only. Findings: There were 86 proteins nominally associated with mortality (p < 0.05), but only CDCP1 remained statistically significant after accounting for multiple testing (hazard ratio per standard deviation: 1.19, 95% CI: 1.10–1.30, unadjusted p = 0.00004). The external C-index for the protein-based model was 0.63 (95% CI: 0.61–0.66), compared with 0.62 (95% CI: 0.59–0.64) for the model with clinical parameters only. Inclusion of proteins did not provide a statistically significant improvement in discrimination (C-index difference: 0.015, 95% CI: −0.003 to 0.035). Interpretation: Blood proteins measured within 3 years prior to lung cancer diagnosis were not strongly associated with lung cancer survival, nor did they importantly improve prediction of prognosis beyond clinical information. Funding: No explicit funding for this study. Authors and data collection supported by the US National Cancer Institute ( U19CA203654), INCA (France, 2019-1-TABAC-01), Cancer Research Foundation of Northern Sweden ( AMP19-962), and Swedish Department of Health Ministry.

INTRODUCTIONStudies have suggested sleep duration may be associated with Alzheimer’s disease risk, but findings based on self-reported sleep duration are likely to be influenced by reverse causation and residual confounding bias.METHODSA polygenic score (PGS) for device-measured sleep duration was constructed using LDpred2-auto in 77,770 white British UK Biobank participants. We applied the PGS to 264,746 white British participants independent of the sample from which the PGS was developed. We assessed the association of fifths of genetically predicted sleep duration with Alzheimer’s disease risk (1,451 cases/264,746 individuals over median 12.5y of follow-up).RESULTSThe PGS explained ∼2% of variation in device-measured sleep duration. Compared to individuals in the middle fifth of PGS, those in the highest fifth (indicating ∼15 mins/day longer sleep) had a lower risk of Alzheimer’s disease (HR=0.79[95%CI,0.67-0.94]).DISCUSSIONOur results indicate that genetic predisposition to relatively long sleep duration is associated with a lower Alzheimer’s disease risk.

Esophageal squamous cell carcinoma (ESCC) shows remarkable variation in incidence that is not fully explained by known lifestyle and environmental risk factors. It has been speculated that an unknown exogenous exposure(s) could be responsible. Here we combine the fields of mutational signature analysis with cancer epidemiology to study 552 ESCC genomes from eight countries with varying incidence rates. Mutational profiles were similar across all countries studied. Associations between specific mutational signatures and ESCC risk factors were identified for tobacco, alcohol, opium and germline variants, with modest impacts on mutation burden. We find no evidence of a mutational signature indicative of an exogenous exposure capable of explaining differences in ESCC incidence. Apolipoprotein B mRNA-editing enzyme, catalytic polypeptide-like (APOBEC)-associated mutational signatures single-base substitution (SBS)2 and SBS13 were present in 88% and 91% of cases, respectively, and accounted for 25% of the mutation burden on average, indicating that APOBEC activation is a crucial step in ESCC tumor development.

Dietary factors are assumed to play an important role in cancer risk, apparent in consensus recommendations for cancer prevention that promote nutritional changes. However, the evidence in this field has been generated predominantly through observational studies, which may result in biased effect estimates because of confounding, exposure misclassification, and reverse causality. With major geographical differences and rapid changes in cancer incidence over time, it is crucial to establish which of the observational associations reflect causality and to identify novel risk factors as these may be modified to prevent the onset of cancer and reduce its progression. Mendelian randomization (MR) uses the special properties of germline genetic variation to strengthen causal inference regarding potentially modifiable exposures and disease risk. MR can be implemented through instrumental variable (IV) analysis and, when robustly performed, is generally less prone to confounding, reverse causation and measurement error than conventional observational methods and has different sources of bias (discussed in detail below). It is increasingly used to facilitate causal inference in epidemiology and provides an opportunity to explore the effects of nutritional exposures on cancer incidence and progression in a cost-effective and timely manner. Here, we introduce the concept of MR and discuss its current application in understanding the impact of nutritional factors (e.g., any measure of diet and nutritional intake, circulating biomarkers, patterns, preference or behaviour) on cancer aetiology and, thus, opportunities for MR to contribute to the development of nutritional recommendations and policies for cancer prevention. We provide applied examples of MR studies examining the role of nutritional factors in cancer to illustrate how this method can be used to help prioritise or deprioritise the evaluation of specific nutritional factors as intervention targets in randomised controlled trials. We describe possible biases when using MR, and methodological developments aimed at investigating and potentially overcoming these biases when present. Lastly, we consider the use of MR in identifying causally relevant nutritional risk factors for various cancers in different regions across the world, given notable geographical differences in some cancers. We also discuss how MR results could be translated into further research and policy. We conclude that findings from MR studies, which corroborate those from other well-conducted studies with different and orthogonal biases, are poised to substantially improve our understanding of nutritional influences on cancer. For such corroboration, there is a requirement for an interdisciplinary and collaborative approach to investigate risk factors for cancer incidence and progression.

It is unclear if body weight in early life affects cancer risk independently of adult body weight. To investigate this question for 6 obesity-related cancers, we performed univariable and multivariable analyses using 1) Mendelian randomization (MR) analysis and 2) longitudinal analyses in prospective cohorts. Both the MR and longitudinal analyses indicated that larger early life body size was associated with higher risk of endometrial (odds ratioMR = 1.61, 95% confidence interval = 1.23 to 2.11) and kidney (odds ratioMR = 1.40, 95% confidence interval = 1.09 to 1.80) cancer. These associations were attenuated after accounting for adult body size in both the MR and cohort analyses. Early life body mass index (BMI) was not consistently associated with the other investigated cancers. The lack of clear independent risk associations suggests that early life BMI influences endometrial and kidney cancer risk mainly through pathways that are common with adult BMI.

The Integrative Analysis of Lung Cancer Etiology and Risk (INTEGRAL) program is an NCI-funded initiative with an objective to develop tools to optimize lung cancer screening. Here, we describe the rationale and design for the Risk Biomarker and Nodule Malignancy projects within INTEGRAL. The overarching goal of these projects is to systematically investigate circulating protein markers to include on a panel for use (i) pre-LDCT, to identify people likely to benefit from screening, and (ii) post-LDCT, to differentiate benign versus malignant nodules. To identify informative proteins, the Risk Biomarker project measured 1,161 proteins in a nested-case control study within 2 prospective cohorts (n=252 lung cancer cases and 252 controls) and replicated associations for a subset of proteins in 4 cohorts (n=479 cases and 479 controls). Eligible participants had any history of smoking and cases were diagnosed within 3 years of blood draw. The Nodule Malignancy project measured 1,077 proteins among participants with a heavy smoking history within 4 LDCT screening studies (n=425 cases within 5 years of blood draw, 398 benign-nodule controls, and 430 nodule-free controls). The INTEGRAL panel will enable absolute quantification of 21 proteins. We will evaluate its lung cancer discriminative performance in the Risk Biomarker project using a case-cohort study including 14 cohorts (n=1,696 cases and 2,926 subcohort representatives), and in the Nodule Malignancy project within 5 LDCT screening studies (n=675 cases, 648 benign-nodule controls, and 680 nodule-free controls). Future progress to advance lung cancer early detection biomarkers will require carefully designed validation, translational, and comparative studies.

Cancer risk is determined by a complex interplay of environmental and heritable factors. Polygenic risk scores (PRS) provide a personalized genetic susceptibility profile that may be leveraged for disease prediction. Using data from the UK Biobank (413,753 individuals; 22,755 incident cancer cases), we quantify the added predictive value of integrating cancer-specific PRS with family history and modifiable risk factors for 16 cancers. We show that incorporating PRS measurably improves prediction accuracy for most cancers, but the magnitude of this improvement varies substantially. We also demonstrate that stratifying on levels of PRS identifies significantly divergent 5-year risk trajectories after accounting for family history and modifiable risk factors. At the population level, the top 20% of the PRS distribution accounts for 4.0% to 30.3% of incident cancer cases, exceeding the impact of many lifestyle-related factors. In summary, this study illustrates the potential for improving cancer risk assessment by integrating genetic risk scores., Predicting cancer risk requires large datasets and sophisticated models. Here the authors integrate polygenic risk scores and modifiable risk factors for multiple cancers in the UK Biobank, improving general risk prediction and distinguishing cases where genetic or lifestyle factors have stronger associations.

Publisher Copyright: © 2022 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC. Previous studies had limited power to assess the associations of testosterone with aggressive disease as a primary endpoint. Further, the association of genetically predicted testosterone with aggressive disease is not known. We investigated the associations of calculated free and measured total testosterone and sex hormone-binding globulin (SHBG) with aggressive, overall and early-onset prostate cancer. In blood-based analyses, odds ratios (OR) and 95% confidence intervals (CI) for prostate cancer were estimated using conditional logistic regression from prospective analysis of biomarker concentrations in the Endogenous Hormones, Nutritional Biomarkers and Prostate Cancer Collaborative Group (up to 25 studies, 14 944 cases and 36 752 controls, including 1870 aggressive prostate cancers). In Mendelian randomisation (MR) analyses, using instruments identified using UK Biobank (up to 194 453 men) and outcome data from PRACTICAL (up to 79 148 cases and 61 106 controls, including 15 167 aggressive cancers), ORs were estimated using the inverse-variance weighted method. Free testosterone was associated with aggressive disease in MR analyses (OR per 1 SD = 1.23, 95% CI = 1.08-1.40). In blood-based analyses there was no association with aggressive disease overall, but there was heterogeneity by age at blood collection (OR for men aged

Deucravacitinib, a novel, selective inhibitor of TYK2 is currently under review at the FDA and EMA for treatment of moderate-to-severe plaque psoriasis. It is unclear whether recent safety concerns (i.e. elevated rates of lung cancer and lymphoma) related to similar medications (i.e. other JAK inhibitors) are shared with this novel TYK2 inhibitor. We used a partial loss-of-function variant in TYK2 (rs34536443), previously shown to protect against psoriasis and other autoimmune diseases, to evaluate the potential effect of therapeutic TYK2 inhibition on risk of lung cancer and non-Hodgkin lymphoma. Summary genetic association data on lung cancer risk were obtained from a GWAS meta-analysis of 29,266 cases and 56,450 controls in the Integrative Analysis of Lung Cancer Risk and Etiology (INTEGRAL) consortium. Summary genetic association data on non-Hodgkin lymphoma risk were obtained from a GWAS meta-analysis of 8,489 cases and 374,506 controls in the UK Biobank and InterLymph consortium. In the primary analysis, each copy of the minor allele of rs34536443, representing partial TYK2 inhibition, was associated with an increased risk of lung cancer (OR 1.15, 95% CI 1.07-1.24, P = 1.72 × 10-4) and non-Hodgkin lymphoma (OR 1.18, 95% CI 1.05-1.33, P = 5.25 × 10-3). In secondary analyses, there was weak evidence of an association of rs34536443 with advanced prostate cancer risk (OR 1.08, 95% CI 1.00-1.17, P = 0.04), but little evidence of association with three other common adult cancers examined. Our analyses using an established partial loss-of-function mutation to mimic TYK2 inhibition provide genetic evidence that therapeutic TYK2 inhibition may increase risk of lung cancer and non-Hodgkin lymphoma. These findings, consistent with recent reports from post-marketing trials of similar JAK inhibitors, could have important implications for future safety assessment of Deucravacitinib and other TYK2 inhibitors in development.

Background: Tobacco exposure causes 8 of 10 lung cancers, and identifying additional risk factors is challenging due to confounding introduced by smoking in traditional observational studies. Materials and Methods: We used Mendelian randomization (MR) to screen 207 metabolites for their role in lung cancer predisposition using independent genome-wide association studies (GWAS) of blood metabolite levels (n = 7,824) and lung cancer risk (n = 29,266 cases/56,450 controls). A nested case–control study (656 cases and 1,296 matched controls) was subsequently performed using prediagnostic blood samples to validate MR association with lung cancer incidence data from population-based cohorts (EPIC and NSHDS). Results: An MR-based scan of 207 circulating metabolites for lung cancer risk identified that blood isovalerylcarnitine (IVC) was associated with a decreased odds of lung cancer after accounting for multiple testing (log10-OR = 0.43; 95% CI, 0.29–0.63). Molar measurement of IVC in prediagnostic blood found similar results (log10-OR = 0.39; 95% CI, 0.21–0.72). Results were consistent across lung cancer subtypes. Conclusions: Independent lines of evidence support an inverse association of elevated circulating IVC with lung cancer risk through a novel methodologic approach that integrates genetic and traditional epidemiology to efficiently identify novel cancer biomarkers. Impact: Our results find compelling evidence in favor of a protective role for a circulating metabolite, IVC, in lung cancer etiology. From the treatment of a Mendelian disease, isovaleric acidemia, we know that circulating IVC is modifiable through a restricted protein diet or glycine and L-carnatine supplementation. IVC may represent a modifiable and inversely associated biomarker for lung cancer.

BackgroundLittle is known about the association between physical activity before cancer diagnosis and survival among lung cancer patients. In this pooled analysis of 11 prospective cohorts, we investigated associations of prediagnosis leisure-time physical activity (LTPA) with all-cause and lung cancer–specific mortality among incident lung cancer patients.MethodsUsing self-reported data on regular engagement in exercise and sports activities collected at study enrollment, we assessed metabolic equivalent hours (MET-h) of prediagnosis LTPA per week. According to the Physical Activity Guidelines for Americans, prediagnosis LTPA was classified into inactivity, less than 8.3 and at least 8.3 MET-h per week (the minimum recommended range). Cox regression was used to estimate hazard ratios (HRs) and 95% confidence interval (CIs) for all-cause and lung cancer–specific mortality after adjustment for major prognostic factors and lifetime smoking history.ResultsOf 20 494 incident lung cancer patients, 16 864 died, including 13 596 deaths from lung cancer (overall 5-year relative survival rate = 20.9%, 95% CI = 20.3% to 21.5%). Compared with inactivity, prediagnosis LTPA of more than 8.3 MET-h per week was associated with a lower hazard of all-cause mortality (multivariable-adjusted HR = 0.93, 95% CI = 0.88 to 0.99), but not with lung cancer–specific mortality (multivariable-adjusted HR = 0.99, 95% CI = 0.95 to 1.04), among the overall population. Additive interaction was found by tumor stage (Pinteraction = .008 for all-cause mortality and .003 for lung cancer–specific mortality). When restricted to localized cancer, prediagnosis LTPA of at least 8.3 MET-h per week linked to 20% lower mortality: multivariable-adjusted HRs were 0.80 (95% CI = 0.67 to 0.97) for all-cause mortality and 0.80 (95% CI = 0.65 to 0.99) for lung cancer–specific mortality.ConclusionsRegular participation in LTPA that met or exceeded the minimum Physical Activity Guidelines was associated with reduced hazards of mortality among lung cancer patients, especially those with early stage cancer.

Simple Summary Malignant pleural mesothelioma (MPM) is an aggressive and still incurable cancer. There is an urgent need to identify effective and reliable tools for detecting and diagnosing the early onset of MPM. In our study, we investigated the whole miRNAs expression profile from serum extracellular vesicles to identify early changes related to MPM development. miR-11400, miR-148a-3p, and miR-409-3p levels were increased in pre-clinical MPM patients up to five years before their diagnosis. The three-miRNA pattern showed a good discrimination capacity to distinguish pre-clinical MPM from cancer-free controls. The three miRNAs also displayed high diagnostic capabilities for differentiating between MPM patients and controls. This study identified a potential EV miRNA signature in preclinical MPM up to five years before diagnosis and raises the possibility of early intervention. Malignant pleural mesothelioma (MPM) is an aggressive cancer with a dismal prognosis. Early therapeutic interventions could improve patient outcomes. We aimed to identify a pattern of microRNAs (miRNAs) as potential early non-invasive markers of MPM. In a case-control study nested in the European Prospective Investigation into Cancer and Nutrition cohort, we screened the whole miRNome in serum extracellular vesicles (EVs) of preclinical MPM cases. In a subgroup of 20 preclinical samples collected five years prior MPM diagnosis, we observed an upregulation of miR-11400 (fold change (FC) = 2.6, adjusted p-value = 0.01), miR-148a-3p (FC = 1.5, p-value = 0.001), and miR-409-3p (FC = 1.5, p-value = 0.04) relative to matched controls. The 3-miRNA panel showed a good classification capacity with an area under the receiver operating characteristic curve (AUC) of 0.81 (specificity = 0.75, sensitivity = 0.70). The diagnostic ability of the model was also evaluated in an independent retrospective cohort, yielding a higher predictive power (AUC = 0.86). A signature of EV miRNA can be detected up to five years before MPM; moreover, the identified miRNAs could provide functional insights into the molecular changes related to the late carcinogenic process, preceding MPM development.