Impact of individual level uncertainty of lung cancer polygenic risk score (PRS) on risk stratification.

BACKGROUND: Although polygenic risk score (PRS) has emerged as a promising tool for predicting cancer risk from genome-wide association studies (GWAS), the individual-level accuracy of lung cancer PRS and the extent to which its impact on subsequent clinical applications remains largely unexplored. METHODS: Lung cancer PRSs and confidence/credible interval (CI) were constructed using two statistical approaches for each individual: (1) the weighted sum of 16 GWAS-derived significant SNP loci and the CI through the bootstrapping method (PRS-16-CV) and (2) LDpred2 and the CI through posteriors sampling (PRS-Bayes), among 17,166 lung cancer cases and 12,894 controls with European ancestry from the International Lung Cancer Consortium. Individuals were classified into different genetic risk subgroups based on the relationship between their own PRS mean/PRS CI and the population level threshold. RESULTS: Considerable variances in PRS point estimates at the individual level were observed for both methods, with an average standard deviation (s.d.) of 0.12 for PRS-16-CV and a much larger s.d. of 0.88 for PRS-Bayes. Using PRS-16-CV, only 25.0% of individuals with PRS point estimates in the lowest decile of PRS and 16.8% in the highest decile have their entire 95% CI fully contained in the lowest and highest decile, respectively, while PRS-Bayes was unable to find any eligible individuals. Only 19% of the individuals were concordantly identified as having high genetic risk (> 90th percentile) using the two PRS estimators. An increased relative risk of lung cancer comparing the highest PRS percentile to the lowest was observed when taking the CI into account (OR = 2.73, 95% CI: 2.12-3.50, P-value = 4.13 × 10-15) compared to using PRS-16-CV mean (OR = 2.23, 95% CI: 1.99-2.49, P-value = 5.70 × 10-46). Improved risk prediction performance with higher AUC was consistently observed in individuals identified by PRS-16-CV CI, and the best performance was achieved by incorporating age, gender, and detailed smoking pack-years (AUC: 0.73, 95% CI = 0.72-0.74). CONCLUSIONS: Lung cancer PRS estimates using different methods have modest correlations at the individual level, highlighting the importance of considering individual-level uncertainty when evaluating the practical utility of PRS.

Lung Cancer in Ever- and Never-Smokers: Findings from Multi-Population GWAS Studies.

BACKGROUND: Clinical, molecular, and genetic epidemiology studies displayed remarkable differences between ever- and never-smoking lung cancer. METHODS: We conducted a stratified multi-population (European, East Asian, and African descent) association study on 44,823 ever-smokers and 20,074 never-smokers to identify novel variants that were missed in the non-stratified analysis. Functional analysis including expression quantitative trait loci (eQTL) colocalization and DNA damage assays, and annotation studies were conducted to evaluate the functional roles of the variants. We further evaluated the impact of smoking quantity on lung cancer risk for the variants associated with ever-smoking lung cancer. RESULTS: Five novel independent loci, GABRA4, intergenic region 12q24.33, LRRC4C, LINC01088, and LCNL1 were identified with the association at two or three populations (P < 5 × 10-8). Further functional analysis provided multiple lines of evidence suggesting the variants affect lung cancer risk through excessive DNA damage (GABRA4) or cis-regulation of gene expression (LCNL1). The risk of variants from 12 independent regions, including the well-known CHRNA5, associated with ever-smoking lung cancer was evaluated for never-smokers, light-smokers (packyear ≤ 20), and moderate-to-heavy-smokers (packyear > 20). Different risk patterns were observed for the variants among the different groups by smoking behavior. CONCLUSIONS: We identified novel variants associated with lung cancer in only ever- or never-smoking groups that were missed by prior main-effect association studies. IMPACT: Our study highlights the genetic heterogeneity between ever- and never-smoking lung cancer and provides etiologic insights into the complicated genetic architecture of this deadly cancer.

Diagnostic accuracy of HPV16 early antigen serology for HPV-driven oropharyngeal cancer is independent of age and sex.

A growing proportion of head and neck cancer (HNC), especially oropharyngeal cancer (OPC), is caused by human papillomavirus (HPV). There are several markers for HPV-driven HNC, one being HPV early antigen serology. We aimed to investigate the diagnostic accuracy of HPV serology and its performance across patient characteristics. Data from the VOYAGER consortium was used, which comprises five studies on HNC from North America and Europe. Diagnostic accuracy, that is, sensitivity, specificity, Cohen's kappa and correctly classified proportions of HPV16 E6 serology, was assessed for OPC and other HNC using p16INK4a immunohistochemistry (p16), HPV in situ hybridization (ISH) and HPV PCR as reference methods. Stratified analyses were performed for variables including age, sex, smoking and alcohol use, to test the robustness of diagnostic accuracy. A risk-factor analysis based on serology was conducted, comparing HPV-driven to non-HPV-driven OPC. Overall, HPV serology had a sensitivity of 86.8% (95% CI 85.1-88.3) and specificity of 91.2% (95% CI 88.6-93.4) for HPV-driven OPC using p16 as a reference method. In stratified analyses, diagnostic accuracy remained consistent across sex and different age groups. Sensitivity was lower for heavy smokers (77.7%), OPC without lymph node involvement (74.4%) and the ARCAGE study (66.7%), while specificity decreased for cases with <10 pack-years (72.1%). The risk-factor model included study, year of diagnosis, age, sex, BMI, alcohol use, pack-years, TNM-T and TNM-N stage. HPV serology is a robust biomarker for HPV-driven OPC, and its diagnostic accuracy is independent of age and sex. Future research is suggested on the influence of smoking on HPV antibody levels.

The tumor multi-omic landscape of endometrial cancers developed on a germline genetic background of adiposity.

High body mass index (BMI) is a causal risk factor for endometrial cancer but the tumor molecular mechanisms affected by adiposity and their therapeutic relevance remain poorly understood. Here we characterize the tumor multi-omic landscape of endometrial cancers that have developed on a background of lifelong germline genetic exposure to elevated BMI. We built a polygenic score (PGS) for BMI in women using data on independent, genome-wide significant variants associated with adult BMI in 434,794 women. We performed germline (blood) genotype quality control and imputation on data from 354 endometrial cancer cases from The Cancer Genome Atlas (TCGA). We assigned each case in this TCGA cohort their genetically predicted life-course BMI based on the BMI PGS. Multivariable generalized linear models adjusted for age, stage, microsatellite status and genetic principal components were used to test for associations between the BMI germline PGS and endometrial cancer tumor genome-wide genomic, transcriptomic, proteomic, epigenomic and immune traits in TCGA. High BMI germline PGS was associated with (i) upregulated tumor gene expression in the IL6-JAK-STAT3 pathway (FDR=4.2×10-7); (ii) increased estimated intra-tumor activated mast cell infiltration (FDR=0.008); (iii) increased single base substitution (SBS) mutational signatures 1 (FDR=0.03) and 5 (FDR=0.09) and decreased SBS13 (FDR=0.09), implicating age-related and APOBEC mutagenesis, respectively; and (iv) decreased tumor EGFR protein expression (FDR=0.07). Alterations in IL6-JAK-STAT3 signaling gene and EGFR protein expression were, in turn, significantly associated with both overall survival and progression-free interval. Thus, we integrated germline and somatic data using a novel study design to identify associations between genetically predicted lifelong exposure to higher BMI and potentially actionable endometrial cancer tumor molecular features. These associations inform our understanding of how high BMI may influence the development and progression of this cancer, impacting endometrial tumor biology and clinical outcomes.

Common genetic variations in telomere length genes and lung cancer: a Mendelian randomisation study and its novel application in lung tumour transcriptome.

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).

Investigation of Shared Genetic Risk Factors Between Parkinson's Disease and Cancers.

BACKGROUND: Epidemiological studies that examined the association between Parkinson's disease (PD) and cancers led to inconsistent results, but they face a number of methodological difficulties. OBJECTIVE: We used results from genome-wide association studies (GWASs) to study the genetic correlation between PD and different cancers to identify common genetic risk factors. METHODS: We used individual data for participants of European ancestry from the Courage-PD (Comprehensive Unbiased Risk Factor Assessment for Genetics and Environment in Parkinson's Disease; PD, N = 16,519) and EPITHYR (differentiated thyroid cancer, N = 3527) consortia and summary statistics of GWASs from iPDGC (International Parkinson Disease Genomics Consortium; PD, N = 482,730), Melanoma Meta-Analysis Consortium (MMAC), Breast Cancer Association Consortium (breast cancer), the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (prostate cancer), International Lung Cancer Consortium (lung cancer), and Ovarian Cancer Association Consortium (ovarian cancer) (N comprised between 36,017 and 228,951 for cancer GWASs). We estimated the genetic correlation between PD and cancers using linkage disequilibrium score regression. We studied the association between PD and polymorphisms associated with cancers, and vice versa, using cross-phenotypes polygenic risk score (PRS) analyses. RESULTS: We confirmed a previously reported positive genetic correlation of PD with melanoma (Gcorr = 0.16 [0.04; 0.28]) and reported an additional significant positive correlation of PD with prostate cancer (Gcorr = 0.11 [0.03; 0.19]). There was a significant inverse association between the PRS for ovarian cancer and PD (odds ratio [OR] = 0.89 [0.84; 0.94]). Conversely, the PRS of PD was positively associated with breast cancer (OR = 1.08 [1.06; 1.10]) and inversely associated with ovarian cancer (OR = 0.95 [0.91; 0.99]). The association between PD and ovarian cancer was mostly driven by rs183211 located in an intron of the NSF gene (17q21.31). CONCLUSIONS: We show evidence in favor of a contribution of pleiotropic genes to the association between PD and specific cancers. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

A risk prediction model for head and neck cancers incorporating lifestyle factors, HPV serology and genetic markers.

Head and neck cancer is often diagnosed late and prognosis for most head and neck cancer patients remains poor. To aid early detection, we developed a risk prediction model based on demographic and lifestyle risk factors, human papillomavirus (HPV) serological markers and genetic markers. A total of 10 126 head and neck cancer cases and 5254 controls from five North American and European studies were included. HPV serostatus was determined by antibodies for HPV16 early oncoproteins (E6, E7) and regulatory early proteins (E1, E2, E4). The data were split into a training set (70%) for model development and a hold-out testing set (30%) for model performance evaluation, including discriminative ability and calibration. The risk models including demographic, lifestyle risk factors and polygenic risk score showed a reasonable predictive accuracy for head and neck cancer overall. A risk model that also included HPV serology showed substantially improved predictive accuracy for oropharyngeal cancer (AUC = 0.94, 95% CI = 0.92-0.95 in men and AUC = 0.92, 95% CI = 0.88-0.95 in women). The 5-year absolute risk estimates showed distinct trajectories by risk factor profiles. Based on the UK Biobank cohort, the risks of developing oropharyngeal cancer among 60 years old and HPV16 seropositive in the next 5 years ranged from 5.8% to 14.9% with an average of 8.1% for men, 1.3% to 4.4% with an average of 2.2% for women. Absolute risk was generally higher among individuals with heavy smoking, heavy drinking, HPV seropositivity and those with higher polygenic risk score. These risk models may be helpful for identifying people at high risk of developing head and neck cancer.

Circulating Isovalerylcarnitine and Lung Cancer Risk: Evidence from Mendelian Randomization and Prediagnostic Blood Measurements.

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.

Association of germline TYK2 variation with lung cancer and non-Hodgkin lymphoma risk.

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 (ie, elevated rates of lung cancer and lymphoma) related to similar medications (ie, 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 Aetiology (INTEGRAL) consortium. Summary genetic association data on non-Hodgkin lymphoma risk were obtained from a GWAS meta-analysis of 8489 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 postmarketing trials of similar JAK inhibitors, could have important implications for future safety assessment of deucravacitinib and other TYK2 inhibitors in development.

Genetic Analysis of Lung Cancer and the Germline Impact on Somatic Mutation Burden.

BACKGROUND: Germline genetic variation contributes to lung cancer (LC) susceptibility. Previous genome-wide association studies (GWAS) have implicated susceptibility loci involved in smoking behaviors and DNA repair genes, but further work is required to identify susceptibility variants. METHODS: To identify LC susceptibility loci, a family history-based genome-wide association by proxy (GWAx) of LC (48 843 European proxy LC patients, 195 387 controls) was combined with a previous LC GWAS (29 266 patients, 56 450 controls) by meta-analysis. Colocalization was used to explore candidate genes and overlap with existing traits at discovered susceptibility loci. Polygenic risk scores (PRS) were tested within an independent validation cohort (1 666 LC patients vs 6 664 controls) using variants selected from the LC susceptibility loci and a novel selection approach using published GWAS summary statistics. Finally, the effects of the LC PRS on somatic mutational burden were explored in patients whose tumor resections have been profiled by exome (n = 685) and genome sequencing (n = 61). Statistical tests were 2-sided. RESULTS: The GWAx-GWAS meta-analysis identified 8 novel LC loci. Colocalization implicated DNA repair genes (CHEK1), metabolic genes (CYP1A1), and smoking propensity genes (CHRNA4 and CHRNB2). PRS analysis demonstrated that these variants, as well as subgenome-wide significant variants related to expression quantitative trait loci and/or smoking propensity, assisted in LC genetic risk prediction (odds ratio = 1.37, 95% confidence interval = 1.29 to 1.45; P < .001). Patients with higher genetic PRS loads of smoking-related variants tended to have higher mutation burdens in their lung tumors. CONCLUSIONS: This study has expanded the number of LC susceptibility loci and provided insights into the molecular mechanisms by which these susceptibility variants contribute to LC development.

A Large-Scale Genome-Wide Gene-Gene Interaction Study of Lung Cancer Susceptibility in Europeans With a Trans-Ethnic Validation in Asians.

INTRODUCTION: Although genome-wide association studies have been conducted to investigate genetic variation of lung tumorigenesis, little is known about gene-gene (G × G) interactions that may influence the risk of non-small cell lung cancer (NSCLC). METHODS: Leveraging a total of 445,221 European-descent participants from the International Lung Cancer Consortium OncoArray project, Transdisciplinary Research in Cancer of the Lung and UK Biobank, we performed a large-scale genome-wide G × G interaction study on European NSCLC risk by a series of analyses. First, we used BiForce to evaluate and rank more than 58 billion G × G interactions from 340,958 single-nucleotide polymorphisms (SNPs). Then, the top interactions were further tested by demographically adjusted logistic regression models. Finally, we used the selected interactions to build lung cancer screening models of NSCLC, separately, for never and ever smokers. RESULTS: With the Bonferroni correction, we identified eight statistically significant pairs of SNPs, which predominantly appeared in the 6p21.32 and 5p15.33 regions (e.g., rs521828C6orf10 and rs204999PRRT1, ORinteraction = 1.17, p = 6.57 × 10-13; rs3135369BTNL2 and rs2858859HLA-DQA1, ORinteraction = 1.17, p = 2.43 × 10-13; rs2858859HLA-DQA1 and rs9275572HLA-DQA2, ORinteraction = 1.15, p = 2.84 × 10-13; rs2853668TERT and rs62329694CLPTM1L, ORinteraction = 0.73, p = 2.70 × 10-13). Notably, even with much genetic heterogeneity across ethnicities, three pairs of SNPs in the 6p21.32 region identified from the European-ancestry population remained significant among an Asian population from the Nanjing Medical University Global Screening Array project (rs521828C6orf10 and rs204999PRRT1, ORinteraction = 1.13, p = 0.008; rs3135369BTNL2 and rs2858859HLA-DQA1, ORinteraction = 1.11, p = 5.23 × 10-4; rs3135369BTNL2 and rs9271300HLA-DQA1, ORinteraction = 0.89, p = 0.006). The interaction-empowered polygenetic risk score that integrated classical polygenetic risk score and G × G information score was remarkable in lung cancer risk stratification. CONCLUSIONS: Important G × G interactions were identified and enriched in the 5p15.33 and 6p21.32 regions, which may enhance lung cancer screening models.

High-risk subtypes of chronic lymphocytic leukemia are detectable as early as 16 years prior to diagnosis.

Chronic lymphocytic leukemia (CLL) is preceded by monoclonal B-cell lymphocytosis (MBL), a CLL precursor state with a prevalence of up to 12% in aged individuals; however, the duration of MBL and the mechanisms of its evolution to CLL remain largely unknown. In this study, we sequenced the B-cell receptor (BcR) immunoglobulin heavy chain (IGH) gene repertoire of 124 patients with CLL and 118 matched controls in blood samples taken up to 22 years prior to diagnosis. Significant skewing in the BcR IGH gene repertoire was detected in the majority of patients, even before the occurrence of lymphocytosis and irrespective of the clonotypic IGH variable gene somatic hypermutation status. Furthermore, we identified dominant clonotypes belonging to major stereotyped subsets associated with poor prognosis up to 16 years before diagnosis in 14 patients with CLL. In 22 patients with longitudinal samples, the skewing of the BcR IGH gene repertoire increased significantly over time to diagnosis or remained stable at high levels. For 14 of 16 patients with available samples at diagnosis, the CLL clonotype was already present in the prediagnostic samples. Overall, our data indicate that the preclinical phase of CLL could be longer than previously thought, even in adverse-prognostic cases.

Germline determinants of humoral immune response to HPV-16 protect against oropharyngeal cancer.

Although several oropharyngeal cancer (OPC) susceptibility loci have been identified, most previous studies lacked detailed information on human papillomavirus (HPV) status. We conduct a genome-wide analysis by HPV16 serology status in 4,002 oral cancer cases (OPC and oral cavity cancer (OCC)) and 5,256 controls. We detect four susceptibility loci pointing to a distinct genetic predisposition by HPV status. Our most notable finding in the HLA region, that is now confirmed to be specific of HPV(+)OPC risk, reveal two independent loci with strong protective effects, one refining the previously reported HLA class II haplotype association. Antibody levels against HPV16 viral proteins strongly implicate the protective HLA variants as major determinants of humoral response against L1 capsid protein or E6 oncoprotein suggesting a natural immune response against HPV(+)OPC promoted by HLA variants. This indicates that therapeutic vaccines that target E6 and attenuate viral response after established HPV infections might protect against HPV(+)OPC.

The shared genetic architecture between epidemiological and behavioral traits with lung cancer.

The complex polygenic nature of lung cancer is not fully characterized. Our study seeks to identify novel phenotypes associated with lung cancer using cross-trait linkage disequilibrium score regression (LDSR). We measured pairwise genetic correlation (rg) and SNP heritability (h2) between 347 traits and lung cancer risk using genome-wide association study summary statistics from the UKBB and OncoArray consortium. Further, we conducted analysis after removing genomic regions previously associated with smoking behaviors to mitigate potential confounding effects. We found significant negative genetic correlations between lung cancer risk and dietary behaviors, fitness metrics, educational attainment, and other psychosocial traits. Alcohol taken with meals (rg = - 0.41, h2 = 0.10, p = 1.33 × 10-16), increased fluid intelligence scores (rg = - 0.25, h2 = 0.22, p = 4.54 × 10-8), and the age at which full time education was completed (rg = - 0.45, h2 = 0.11, p = 1.24 × 10-20) demonstrated negative genetic correlation with lung cancer susceptibility. The body mass index was positively correlated with lung cancer risk (rg = 0.20, h2 = 0.25, p = 2.61 × 10-9). This analysis reveals shared genetic architecture between several traits and lung cancer predisposition. Future work should test for causal relationships and investigate common underlying genetic mechanisms across these genetically correlated traits.

Large-scale cross-cancer fine-mapping of the 5p15.33 region reveals multiple independent signals.

Genome-wide association studies (GWASs) have identified thousands of cancer risk loci revealing many risk regions shared across multiple cancers. Characterizing the cross-cancer shared genetic basis can increase our understanding of global mechanisms of cancer development. In this study, we collected GWAS summary statistics based on up to 375,468 cancer cases and 530,521 controls for fourteen types of cancer, including breast (overall, estrogen receptor [ER]-positive, and ER-negative), colorectal, endometrial, esophageal, glioma, head/neck, lung, melanoma, ovarian, pancreatic, prostate, and renal cancer, to characterize the shared genetic basis of cancer risk. We identified thirteen pairs of cancers with statistically significant local genetic correlations across eight distinct genomic regions. Specifically, the 5p15.33 region, harboring the TERT and CLPTM1L genes, showed statistically significant local genetic correlations for multiple cancer pairs. We conducted a cross-cancer fine-mapping of the 5p15.33 region based on eight cancers that showed genome-wide significant associations in this region (ER-negative breast, colorectal, glioma, lung, melanoma, ovarian, pancreatic, and prostate cancer). We used an iterative analysis pipeline implementing a subset-based meta-analysis approach based on cancer-specific conditional analyses and identified ten independent cross-cancer associations within this region. For each signal, we conducted cross-cancer fine-mapping to prioritize the most plausible causal variants. Our findings provide a more in-depth understanding of the shared inherited basis across human cancers and expand our knowledge of the 5p15.33 region in carcinogenesis.

The PI3K/mTOR Pathway Is Targeted by Rare Germline Variants in Patients with Both Melanoma and Renal Cell Carcinoma.

Background: Malignant melanoma and RCC have different embryonic origins, no common lifestyle risk factors but intriguingly share biological properties such as immune regulation and radioresistance. An excess risk of malignant melanoma is observed in RCC patients and vice versa. This bidirectional association is poorly understood, and hypothetic genetic co-susceptibility remains largely unexplored. Results: We hereby provide a clinical and genetic description of a series of 125 cases affected by both malignant melanoma and RCC. Clinical germline mutation testing identified a pathogenic variant in a melanoma and/or RCC predisposing gene in 17/125 cases (13.6%). This included mutually exclusive variants in MITF (p.E318K locus, N = 9 cases), BAP1 (N = 3), CDKN2A (N = 2), FLCN (N = 2), and PTEN (N = 1). A subset of 46 early-onset cases, without underlying germline variation, was whole-exome sequenced. In this series, thirteen genes were significantly enriched in mostly exclusive rare variants predicted to be deleterious, compared to 19,751 controls of similar ancestry. The observed variation mainly consisted of novel or low-frequency variants (<0.01%) within genes displaying strong evolutionary mutational constraints along the PI3K/mTOR pathway, including PIK3CD, NFRKB, EP300, MTOR, and related epigenetic modifier SETD2. The screening of independently processed germline exomes from The Cancer Genome Atlas confirmed an association with melanoma and RCC but not with cancers of established differing etiology such as lung cancers. Conclusions: Our study highlights that an exome-wide case-control enrichment approach may better characterize the rare variant-based missing heritability of multiple primary cancers. In our series, the co-occurrence of malignant melanoma and RCC was associated with germline variation in the PI3K/mTOR signaling cascade, with potential relevance for early diagnostic and clinical management.

Studying the Utility of Using Genetics to Predict Smoking-Related Outcomes in a Population-Based Study and a Selected Cohort.

INTRODUCTION: The purpose of this study is to examine the predictive utility of polygenic risk scores (PRSs) for smoking behaviors. AIMS AND METHODS: Using summary statistics from the Sequencing Consortium of Alcohol and Nicotine use consortium, we generated PRSs of ever smoking, age of smoking initiation, cigarettes smoked per day, and smoking cessation for participants in the population-based Atherosclerosis Risk in Communities (ARIC) study (N = 8638), and the Collaborative Genetic Study of Nicotine Dependence (COGEND) (N = 1935). The outcomes were ever smoking, age of smoking initiation, heaviness of smoking, and smoking cessation. RESULTS: In the European ancestry cohorts, each PRS was significantly associated with the corresponding smoking behavior outcome. In the ARIC cohort, the PRS z-score for ever smoking predicted smoking (odds ratio [OR]: 1.37; 95% confidence interval [CI]: 1.31, 1.43); the PRS z-score for age of smoking initiation was associated with age of smoking initiation (OR: 0.87; 95% CI: 0.82, 0.92); the PRS z-score for cigarettes per day was associated with heavier smoking (OR: 1.17; 95% CI: 1.11, 1.25); and the PRS z-score for smoking cessation predicted successful cessation (OR: 1.24; 95% CI: 1.17, 1.32). In the African ancestry cohort, the PRSs did not predict smoking behaviors. CONCLUSIONS: Smoking-related PRSs were associated with smoking-related behaviors in European ancestry populations. This improvement in prediction is greatest in the lowest and highest genetic risk categories. The lack of prediction in African ancestry populations highlights the urgent need to increase diversity in research so that scientific advances can be applied to populations other than those of European ancestry. IMPLICATIONS: This study shows that including both genetic ancestry and PRSs in a single model increases the ability to predict smoking behaviors compared with the model including only demographic characteristics. This finding is observed for every smoking-related outcome. Even though adding genetics is more predictive, the demographics alone confer substantial and meaningful predictive power. However, with increasing work in PRSs, the predictive ability will continue to improve.

Genome-wide association meta-analysis identifies pleiotropic risk loci for aerodigestive squamous cell cancers.

Squamous cell carcinomas (SqCC) of the aerodigestive tract have similar etiological risk factors. Although genetic risk variants for individual cancers have been identified, an agnostic, genome-wide search for shared genetic susceptibility has not been performed. To identify novel and pleotropic SqCC risk variants, we performed a meta-analysis of GWAS data on lung SqCC (LuSqCC), oro/pharyngeal SqCC (OSqCC), laryngeal SqCC (LaSqCC) and esophageal SqCC (ESqCC) cancers, totaling 13,887 cases and 61,961 controls of European ancestry. We identified one novel genome-wide significant (Pmeta<5x10-8) aerodigestive SqCC susceptibility loci in the 2q33.1 region (rs56321285, TMEM273). Additionally, three previously unknown loci reached suggestive significance (Pmeta<5x10-7): 1q32.1 (rs12133735, near MDM4), 5q31.2 (rs13181561, TMEM173) and 19p13.11 (rs61494113, ABHD8). Multiple previously identified loci for aerodigestive SqCC also showed evidence of pleiotropy in at least another SqCC site, these include: 4q23 (ADH1B), 6p21.33 (STK19), 6p21.32 (HLA-DQB1), 9p21.33 (CDKN2B-AS1) and 13q13.1(BRCA2). Gene-based association and gene set enrichment identified a set of 48 SqCC-related genes rel to DNA damage and epigenetic regulation pathways. Our study highlights the importance of cross-cancer analyses to identify pleiotropic risk loci of histology-related cancers arising at distinct anatomical sites.

Sequencing at lymphoid neoplasm susceptibility loci maps six myeloma risk genes.

Inherited genetic risk factors play a role in multiple myeloma (MM), yet considerable missing heritability exists. Rare risk variants at genome-wide association study (GWAS) loci are a new avenue to explore. Pleiotropy between lymphoid neoplasms (LNs) has been suggested in family history and genetic studies, but no studies have interrogated sequencing for pleiotropic genes or rare risk variants. Sequencing genetically enriched cases can help discover rarer variants. We analyzed exome sequencing in familial or early-onset MM cases to identify rare, functionally relevant variants near GWAS loci for a range of LNs. A total of 149 distinct and significant LN GWAS loci have been published. We identified six recurrent, rare, potentially deleterious variants within 5 kb of significant GWAS single nucleotide polymorphisms in 75 MM cases. Mutations were observed in BTNL2, EOMES, TNFRSF13B, IRF8, ACOXL and TSPAN32. All six genes replicated in an independent set of 255 early-onset MM or familial MM or precursor cases. Expansion of our analyses to the full length of these six genes resulted in a list of 39 rare and deleterious variants, seven of which segregated in MM families. Three genes also had significant rare variant burden in 733 sporadic MM cases compared with 935 control individuals: IRF8 (P = 1.0 × 10-6), EOMES (P = 6.0 × 10-6) and BTNL2 (P = 2.1 × 10-3). Together, our results implicate six genes in MM risk, provide support for genetic pleiotropy between LN subtypes and demonstrate the utility of sequencing genetically enriched cases to identify functionally relevant variants near GWAS loci.