Genome-wide Polygenic Risk Scores Predict Risk of Glioma and Molecular Subtypes.

Background: Polygenic risk scores (PRS) aggregate the contribution of many risk variants to provide a personalized genetic susceptibility profile. Since sample sizes of glioma genome-wide association studies (GWAS) remain modest, there is a need to find efficient ways of capturing genetic risk factors using available germline data. Methods: We developed a novel PRS (PRS-CS) that uses continuous shrinkage priors to model the joint effects of over 1 million polymorphisms on disease risk and compared it to an approach (PRS-CT) that selects a limited set of independent variants that reach genome-wide significance (P<5×10-8). PRS models were trained using GWAS results stratified by histological (10,346 cases, 14,687 controls) and molecular subtype (2,632 cases, 2,445 controls), and validated in two independent cohorts. Results: PRS-CS was consistently more predictive than PRS-CT across glioma subtypes with an average increase in explained variance (R2) of 21%. Improvements were particularly pronounced for glioblastoma tumors, with PRS-CS yielding larger effect sizes (odds ratio (OR)=1.93, P=2.0×10-54 vs. OR=1.83, P=9.4×10-50) and higher explained variance (R2=2.82% vs. R2=2.56%). Individuals in the 95th percentile of the PRS-CS distribution had a 3-fold higher lifetime absolute risk of IDH mutant (0.63%) and IDH wildtype (0.76%) glioma relative to individuals with average PRS. PRS-CS also showed high classification accuracy for IDH mutation status among cases (AUC=0.895). Conclusions: Our novel genome-wide PRS may improve the identification of high-risk individuals and help distinguish between prognostic glioma subtypes, increasing the potential clinical utility of germline genetics in glioma patient management.

Lifetime Body Weight Trajectories and Risk of Renal Cell Cancer: A Large U.S. Prospective Cohort Study.

BACKGROUND: Body mass index (BMI) is a known risk factor for renal cell cancer (RCC), but data are limited as to the effect of lifetime exposure to excess body weight. METHODS: Using the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (N = 138,614, 527 incident RCCs), we identified several anthropometric measures to capture the lifetime BMI patterns: (i) BMI at specific ages; (ii) adulthood BMI trajectories; (iii) cumulative exposure to overweight/obesity denoted as weighted years of living overweight/obese (WYO); and (iv) weight change during each age span. We conducted multivariable Cox model to quantify the association between each anthropometric metric and incident RCC. RESULTS: A higher BMI at ages 20 and 50 and at baseline was associated with a greater hazard of RCC. Compared with individuals who retained normal BMI throughout adulthood, we observed an increased hazard of RCC for BMI trajectory of progressing from normal BMI to overweight [HR, 1.49; 95% confidence interval (CI), 1.19-1.87], from normal BMI to obesity (HR, 2.22; 95% CI, 1.70-2.90), and from overweight to obesity (HR, 2.78; 95% CI, 1.81-4.27). Compared with individuals who were never overweight (WYO = 0), elevated HRs were observed among individuals who experienced low (HR, 1.31; 95% CI, 0.99-1.74), medium (HR, 1.57; 95% CI, 1.20-2.05), and high (HR, 2.10; 95% CI, 1.62-2.72) WYO tertile. Weight gain of ≥10 kg was associated with increased RCC incidence for each age span. CONCLUSIONS: Across the lifespan, being overweight/obese, weight gain, and higher cumulative exposure to excess weight were all associated with increased RCC risk. IMPACT: It is important to avoid weight gain and assess BMI from a life-course perspective to reduce RCC risk.

Heritable Traits and Lung Cancer Risk: A Two-Sample Mendelian Randomization Study.

INTRODUCTION: Lung cancer is a complex polygenic disorder. Analysis with Mendelian randomization (MR) allows for genetically predicted risks to be estimated between exposures and outcomes. METHODS: We analyzed 345 heritable traits from the United Kingdom Biobank and estimated their associated effects on lung cancer outcomes using two sample MR. In addition to estimating effects with overall lung cancer, adenocarcinoma, small cell lung cancer, and squamous cell lung cancers, we performed conditional effect modeling with multivariate MR (MVMR) and the traits of alcohol use, smoking initiation, average pre-tax income, and educational attainment. RESULTS: Univariate MR provided evidence for increased age at first sexual intercourse (OR, 0.55; P = 6.15 × 10-13), educational attainment (OR, 0.24; P = 1.07 × 10-19), average household income (OR, 0.58; P = 7.85 × 10-05), and alcohol usually taken with meals (OR, 0.19; P = 1.06 × 10-06) associating with decreased odds of overall lung cancer development. In contrast, a lack of additional educational attainment (OR, 8.00; P = 3.48 × 10-12), body mass index (OR, 1.28; P = 9.00 × 10-08), pack years smoking as a proportion of life span (OR, 9.93; P = 7.96 × 10-12), and weekly beer intake (OR, 3.48; P = 4.08 × 10-07) were associated with an increased risk of overall lung cancer development. CONCLUSIONS: Many heritable traits associated with an increased or inverse risk of lung cancer development. Effects vary based on histologic subtype and conditional third trait exposures. IMPACT: We identified several heritable traits and presented their genetically predictable impact on lung cancer development, providing valuable insights for consideration.

The genomic landscape of familial glioma.

Glioma is a rare brain tumor with a poor prognosis. Familial glioma is a subset of glioma with a strong genetic predisposition that accounts for approximately 5% of glioma cases. We performed whole-genome sequencing on an exploratory cohort of 203 individuals from 189 families with a history of familial glioma and an additional validation cohort of 122 individuals from 115 families. We found significant enrichment of rare deleterious variants of seven genes in both cohorts, and the most significantly enriched gene was HERC2 (P = 0.0006). Furthermore, we identified rare noncoding variants in both cohorts that were predicted to affect transcription factor binding sites or cause cryptic splicing. Last, we selected a subset of discovered genes for validation by CRISPR knockdown screening and found that DMBT1, HP1BP3, and ZCH7B3 have profound impacts on proliferation. This study performs comprehensive surveillance of the genomic landscape of familial glioma.

Genome-wide analyses characterize shared heritability among cancers and identify novel cancer susceptibility regions.

BACKGROUND: The shared inherited genetic contribution to risk of different cancers is not fully known. In this study, we leverage results from 12 cancer genome-wide association studies (GWAS) to quantify pairwise genome-wide genetic correlations across cancers and identify novel cancer susceptibility loci. METHODS: We collected GWAS summary statistics for 12 solid cancers based on 376 759 participants with cancer and 532 864 participants without cancer of European ancestry. The included cancer types were breast, colorectal, endometrial, esophageal, glioma, head and neck, lung, melanoma, ovarian, pancreatic, prostate, and renal cancers. We conducted cross-cancer GWAS and transcriptome-wide association studies to discover novel cancer susceptibility loci. Finally, we assessed the extent of variant-specific pleiotropy among cancers at known and newly identified cancer susceptibility loci. RESULTS: We observed widespread but modest genome-wide genetic correlations across cancers. In cross-cancer GWAS and transcriptome-wide association studies, we identified 15 novel cancer susceptibility loci. Additionally, we identified multiple variants at 77 distinct loci with strong evidence of being associated with at least 2 cancer types by testing for pleiotropy at known cancer susceptibility loci. CONCLUSIONS: Overall, these results suggest that some genetic risk variants are shared among cancers, though much of cancer heritability is cancer-specific and thus tissue-specific. The increase in statistical power associated with larger sample sizes in cross-disease analysis allows for the identification of novel susceptibility regions. Future studies incorporating data on multiple cancer types are likely to identify additional regions associated with the risk of multiple cancer types.

Common Germline Risk Variants Impact Somatic Alterations and Clinical Features across Cancers.

Aggregation of genome-wide common risk variants, such as polygenic risk score (PRS), can measure genetic susceptibility to cancer. A better understanding of how common germline variants associate with somatic alterations and clinical features could facilitate personalized cancer prevention and early detection. We constructed PRSs from 14 genome-wide association studies (median n = 64,905) for 12 cancer types by multiple methods and calibrated them using the UK Biobank resources (n = 335,048). Meta-analyses across cancer types in The Cancer Genome Atlas (n = 7,965) revealed that higher PRS values were associated with earlier cancer onset and lower burden of somatic alterations, including total mutations, chromosome/arm somatic copy-number alterations (SCNA), and focal SCNAs. This contrasts with rare germline pathogenic variants (e.g., BRCA1/2 variants), showing heterogeneous associations with somatic alterations. Our results suggest that common germline cancer risk variants allow early tumor development before the accumulation of many somatic alterations characteristic of later stages of carcinogenesis. SIGNIFICANCE: Meta-analyses across cancers show that common germline risk variants affect not only cancer predisposition but the age of cancer onset and burden of somatic alterations, including total mutations and copy-number alterations.

Influence of county-level geographic/ancestral origin on glioma incidence and outcomes in US Hispanics.

BACKGROUND: Glioma incidence is 25% lower in Hispanics than White non-Hispanics. The US Hispanic population is diverse, and registry-based analyses may mask incidence differences associated with geographic/ancestral origins. METHODS: County-level glioma incidence data in Hispanics were retrieved from the Central Brain Tumor Registry of the United States. American Community Survey data were used to determine the county-level proportion of the Hispanic population of Mexican/Central American and Caribbean origins. Age-adjusted incidence rate ratios and incidence rate ratios (IRRs) quantified the glioma incidence differences across groups. State-level estimates of admixture in Hispanics were obtained from published 23andMe data. RESULTS: Compared to predominantly Caribbean-origin counties, predominantly Mexican/Central American-origin counties had lower age-adjusted risks of glioma (IRR = 0.83; P < 0.0001), glioblastoma (IRR = 0.86; P < 0.0001), diffuse/anaplastic astrocytoma (IRR = 0.78; P < 0.0001), oligodendroglioma (IRR = 0.82; P < 0.0001), ependymoma (IRR = 0.88; P = 0.012), and pilocytic astrocytoma (IRR = 0.76; P < 0.0001). Associations were consistent in children and adults and using more granular geographic regions. Despite having lower glioma incidence, Hispanic glioblastoma patients from predominantly Mexican/Central American-origin counties had poorer survival than Hispanics living in predominantly Caribbean-origin counties. Incidence and survival differences could be partially explained by state-level estimates of European admixture in Hispanics with European admixture associated with higher incidence and improved survival. CONCLUSIONS: Glioma incidence and outcomes differ in association with the geographic origins of Hispanic communities, with counties of predominantly Mexican/Central American origin at significantly reduced risk and those of Caribbean origin at comparatively greater risk. Although typically classified as a single ethnic group, appreciating the cultural, socioeconomic, and genetic diversity of Hispanics can advance cancer disparities research.

Low-molecular-weight cyclin E deregulates DNA replication and damage repair to promote genomic instability in breast cancer.

Low-molecular-weight cyclin E (LMW-E) is an N-terminus deleted (40 amino acid) form of cyclin E detected in breast cancer, but not in normal cells or tissues. LMW-E overexpression predicts poor survival in breast cancer patients independent of tumor proliferation rate, but the oncogenic mechanism of LMW-E and its unique function(s) independent of full-length cyclin E (FL-cycE) remain unclear. In the current study, we found LMW-E was associated with genomic instability in early-stage breast tumors (n = 725) and promoted genomic instability in human mammary epithelial cells (hMECs). Mechanistically, FL-cycE overexpression inhibited the proliferation of hMECs by replication stress and DNA damage accumulation, but LMW-E facilitated replication stress tolerance by upregulating DNA replication and damage repair. Specifically, LMW-E interacted with chromatin and upregulated the loading of minichromosome maintenance complex proteins (MCMs) in a CDC6 dependent manner and promoted DNA repair in a RAD51- and C17orf53-dependent manner. Targeting the ATR-CHK1-RAD51 pathway with ATR inhibitor (ceralasertib), CHK1 inhibitor (rabusertib), or RAD51 inhibitor (B02) significantly decreased the viability of LMW-E-overexpressing hMECs and breast cancer cells. Collectively, our findings delineate a novel role for LMW-E in tumorigenesis mediated by replication stress tolerance and genomic instability, providing novel therapeutic strategies for LMW-E-overexpressing breast cancers.

Germline polymorphisms in MGMT associated with temozolomide-related myelotoxicity risk in patients with glioblastoma treated on NRG Oncology/RTOG 0825.

Background: We sought to identify clinical and genetic predictors of temozolomide-related myelotoxicity among patients receiving therapy for glioblastoma. Methods: Patients (n = 591) receiving therapy on NRG Oncology/RTOG 0825 were included in the analysis. Cases were patients with severe myelotoxicity (grade 3 and higher leukopenia, neutropenia, and/or thrombocytopenia); controls were patients without such toxicity. A risk-prediction model was built and cross-validated by logistic regression using only clinical variables and extended using polymorphisms associated with myelotoxicity. Results: 23% of patients developed myelotoxicity (n = 134). This toxicity was first reported during the concurrent phase of therapy for 56 patients; 30 stopped treatment due to toxicity. Among those who continued therapy (n = 26), 11 experienced myelotoxicity again. The final multivariable clinical factor model included treatment arm, gender, and anticonvulsant status and had low prediction accuracy (area under the curve [AUC] = 0.672). The final extended risk prediction model including four polymorphisms in MGMT had better prediction (AUC = 0.827). Receiving combination chemotherapy (OR, 1.82; 95% CI, 1.02-3.27) and being female (OR, 4.45; 95% CI, 2.45-8.08) significantly increased myelotoxicity risk. For each additional minor allele in the polymorphisms, the risk increased by 64% (OR, 1.64; 95% CI, 1.43-1.89). Conclusions: Myelotoxicity during concurrent chemoradiation with temozolomide is an uncommon but serious event, often leading to treatment cessation. Successful prediction of toxicity may lead to more cost-effective individualized monitoring of at-risk subjects. The addition of genetic factors greatly enhanced our ability to predict toxicity among a group of similarly treated glioblastoma patients.

Pleiotropic MLLT10 variation confers risk of meningioma and estrogen-mediated cancers.

Background: Risk of tumors of the breast, ovary, and meninges has been associated with hormonal factors and with one another. Genome-wide association studies (GWAS) identified a meningioma risk locus on 10p12 near previous GWAS hits for breast and ovarian cancers, raising the possibility of genetic pleiotropy. Methods: We performed imputation-based fine-mapping in three case-control datasets of meningioma (927 cases, 790 controls), female breast cancer (28 108 cases, 22 209 controls), and ovarian cancer (25 509 cases, 40 941 controls). Analyses were stratified by sex (meningioma), estrogen receptor (ER) status (breast), and histotype (ovarian), then combined using subset-based meta-analysis in ASSET. Lead variants were assessed for association with additional traits in UK Biobank to identify potential effect-mediators. Results: Two-sided subset-based meta-analysis identified rs7084454, an expression quantitative trait locus (eQTL) near the MLLT10 promoter, as lead variant (5.7 × 10-14). The minor allele was associated with increased risk of meningioma in females (odds ratio (OR) = 1.42, 95% Confidence Interval (95%CI):1.20-1.69), but not males (OR = 1.19, 95%CI: 0.91-1.57). It was positively associated with ovarian (OR = 1.09, 95%CI:1.06-1.12) and ER+ breast (OR = 1.05, 95%CI: 1.02-1.08) cancers, and negatively associated with ER- breast cancer (OR = 0.91, 95%CI: 0.86-0.96). It was also associated with several adiposity traits (P < 5.0 × 10-8), but adjusting for body mass index did not attenuate its association with meningioma. MLLT10 and ESR1 expression were positively correlated in normal meninges (P = .058) and meningioma tumors (P = .0065). Conclusions: We identify a MLLT10 eQTL positively associated with risk of female meningioma, ER+ breast cancer, ovarian cancer, and obesity, and implicate a potential estrogenic mechanism underlying this pleiotropy.

Breast cancer diagnosis and treatment during the COVID-19 pandemic in a nationwide, insured population.

PURPOSE: The early months of the COVID-19 pandemic led to reduced cancer screenings and delayed cancer surgeries. We used insurance claims data to understand how breast cancer incidence and treatment after diagnosis changed nationwide over the course of the pandemic. METHODS: Using the Optum Research Database from January 2017 to March 2021, including approximately 19 million US adults with commercial health insurance, we identified new breast cancer diagnoses and first treatment after diagnosis. We compared breast cancer incidence and proportion of newly diagnosed patients receiving pre-operative systemic therapy pre-COVID, in the first 2 months of the COVID pandemic and in the later part of the COVID pandemic. RESULTS: Average monthly breast cancer incidence was 19.3 (95% CI 19.1-19.5) cases per 100,000 women and men pre-COVID, 11.6 (95% CI 10.8-12.4) per 100,000 in April-May 2020, and 19.7 (95% CI 19.3-20.1) per 100,000 in June 2020-February 2021. Use of pre-operative systemic therapy was 12.0% (11.7-12.4) pre-COVID, 37.7% (34.9-40.7) for patients diagnosed March-April 2020, and 14.8% (14.0-15.7) for patients diagnosed May 2020-January 2021. The changes in breast cancer incidence across the pandemic did not vary by demographic factors. Use of pre-operative systemic therapy across the pandemic varied by geographic region, but not by area socioeconomic deprivation or race/ethnicity. CONCLUSION: In this US-insured population, the dramatic changes in breast cancer incidence and the use of pre-operative systemic therapy experienced in the first 2 months of the pandemic did not persist, although a modest change in the initial management of breast cancer continued.

Racial Differences in the Tumor Immune Landscape and Survival of Women with High-Grade Serous Ovarian Carcinoma.

BACKGROUND: Tumor-infiltrating lymphocytes (TIL) confer a survival benefit among patients with ovarian cancer; however, little work has been conducted in racially diverse cohorts. METHODS: The current study investigated racial differences in the tumor immune landscape and survival of age- and stage-matched non-Hispanic Black and non-Hispanic White women with high-grade serous ovarian carcinoma (HGSOC) enrolled in two population-based studies (n = 121 in each racial group). We measured TILs (CD3+), cytotoxic T cells (CD3+CD8+), regulatory T cells (CD3+FoxP3+), myeloid cells (CD11b+), and neutrophils (CD11b+CD15+) via multiplex immunofluorescence. Multivariable Cox proportional hazard regression was used to estimate the association between immune cell abundance and survival overall and by race. RESULTS: Overall, higher levels of TILs, cytotoxic T cells, myeloid cells, and neutrophils were associated with better survival in the intratumoral and peritumoral region, irrespective of tissue compartment (tumor, stroma). Improved survival was noted for T-regulatory cells in the peritumoral region and in the stroma of the intratumoral region, but no association for intratumoral T-regulatory cells. Despite similar abundance of immune cells across racial groups, associations with survival among non-Hispanic White women were consistent with the overall findings, but among non-Hispanic Black women, most associations were attenuated and not statistically significant. CONCLUSIONS: Our results add to the existing evidence that a robust immune infiltrate confers a survival advantage among women with HGSOC; however, non-Hispanic Black women may not experience the same survival benefit as non-Hispanic White women with HGSOC. IMPACT: This study contributes to our understanding of the immunoepidemiology of HGSOC in diverse populations.

Shared genomic architecture between COVID-19 severity and numerous clinical and physiologic parameters revealed by LD score regression analysis.

The COVID-19 pandemic has produced broad clinical manifestations, from asymptomatic infection to hospitalization and death. Despite progress from genomic and clinical epidemiology research, risk factors for developing severe COVID-19 are incompletely understood and identification of modifiable risk factors is desperately needed. We conducted linkage disequilibrium score regression (LDSR) analysis to estimate cross-trait genetic correlation between COVID-19 severity and various polygenic phenotypes. To attenuate the genetic contribution of smoking and BMI, we further conducted sensitivity analyses by pruning genomic regions associated with smoking/BMI and repeating LDSR analyses. We identified robust positive associations between the genetic architecture of severe COVID-19 and both BMI and smoking. We observed strong positive genetic correlation (rg) with diabetes (rg = 0.25) and shortness of breath walking on level ground (rg = 0.28) and novel protective associations with vitamin E (rg = - 0.53), calcium (rg = - 0.33), retinol (rg = - 0.59), Apolipoprotein A (rg = - 0.13), and HDL (rg = - 0.17), but no association with vitamin D (rg = - 0.02). Removing genomic regions associated with smoking and BMI generally attenuated the associations, but the associations with nutrient biomarkers persisted. This study provides a comprehensive assessment of the shared genetic architecture of COVID-19 severity and numerous clinical/physiologic parameters. Associations with blood and plasma-derived traits identified biomarkers for Mendelian randomization studies to explore causality and nominates therapeutic targets for clinical evaluation.

Genetic modulation of longitudinal change in neurocognitive function among adult glioma patients.

PURPOSE: Impaired neurocognitive function (NCF) is extremely common in patients with higher grade primary brain tumor. We previously reported evidence of genetic variants associated with NCF in glioma patients prior to treatment. However, little is known about the effect of genetic variants on NCF decline after adjuvant therapy. METHODS: Patients (N = 102) completed longitudinal NCF assessments that included measures of verbal memory, processing speed, and executive function. Testing was conducted in the postoperative period with an average follow up interval of 1.3 years. We examined polymorphisms in 580 genes related to five pathways (inflammation, DNA repair, metabolism, cognitive, and telomerase). RESULTS: Five polymorphisms were associated with longitudinal changes in processing speed and 14 polymorphisms with executive function. Change in processing speed was strongly associated with MCPH1 rs17631450 (P = 2.2 × 10-7) and CCDC26 rs7005206 (P = 9.3 × 10-7) in the telomerase pathway; while change in executive function was more strongly associated with FANCF rs1514084 (P = 2.9 × 10-6) in the DNA repair pathway and DAOA rs12428572 (P = 2.4 × 10-5) in the cognitive pathway. Joint effect analysis found significant genetic-dosage effects for longitudinal changes in processing speed (Ptrend = 1.5 × 10-10) and executive function (Ptrend = 2.1 × 10-11). In multivariable analyses, predictors of NCF decline included progressive disease, lower baseline NCF performance, and more at-risk genetic variants, after adjusting for age, sex, education, tumor location, histology, and disease progression. CONCLUSION: Our longitudinal analyses revealed that polymorphisms in telomerase, DNA repair, and cognitive pathways are independent predictors of decline in NCF in glioma patients.

Psychosocial factors associated with genetic testing status among African American women with ovarian cancer: Results from the African American Cancer Epidemiology Study.

BACKGROUND: Racial disparities in the uptake of cancer genetic services are well documented among African American (AA) women. Understanding the multiple social and psychological factors that can influence the uptake of genetic testing among AA women is needed. METHODS: Data came from 270 AA women diagnosed with ovarian cancer and participating in a population-based, case-control study of ovarian cancer who were asked about genetic testing. Logistic regression analyses tested the associations of predisposing, enabling, and need factors with reported genetic testing uptake. RESULTS: One-third of the sample (35%) reported having had genetic testing. In the multivariable model, AA women with higher incomes had more than double the odds of being tested than those with the lowest income (odds ratio [OR] for $25,000-$74,999, 2.04; 95% confidence interval [CI], 1.06-3.99; OR for ≥$75,000, 2.32; 95% CI, 0.92-5.94). AA women who reported employment discrimination were significantly less likely to report genetic testing than those who did not report job discrimination (OR, 0.39; 95% CI, 0.14-0.95). Marital status, Medicaid versus other insurance, prayer frequency, and perceived social support were significantly associated with genetic testing uptake in bivariate analyses but were not significant contributors in multivariable analyses. CONCLUSIONS: Consistent with other studies of AA women, a minority of African American Cancer Epidemiology Study participants had undergone genetic testing. Having a lower income and experiencing job discrimination decreased the likelihood of testing. These results provide foundational evidence supporting the need for interventions to improve the uptake of genetic testing among AA women by reducing cost barriers and providing credible assurances that genetic results will be kept private and not affect social factors such as employability.

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.

Partitioned glioma heritability shows subtype-specific enrichment in immune cells.

BACKGROUND: Epidemiological studies of adult glioma have identified genetic syndromes and 25 heritable risk loci that modify individual risk for glioma, as well increased risk in association with exposure to ionizing radiation and decreased risk in association with allergies. In this analysis, we assess whether there is a shared genome-wide genetic architecture between glioma and atopic/autoimmune diseases. METHODS: Using summary statistics from a glioma genome-wide association studies (GWAS) meta-analysis, we identified significant enrichment for risk variants associated with gene expression changes in immune cell populations. We also estimated genetic correlations between glioma and autoimmune, atopic, and hematologic traits using linkage disequilibrium score regression (LDSC), which leverages genome-wide single-nucleotide polymorphism (SNP) associations and patterns of linkage disequilibrium. RESULTS: Nominally significant negative correlations were observed for glioblastoma (GB) and primary biliary cirrhosis (rg = -0.26, P = .0228), and for non-GB gliomas and celiac disease (rg = -0.32, P = .0109). Our analyses implicate dendritic cells (GB pHM = 0.0306 and non-GB pHM = 0.0186) in mediating both GB and non-GB genetic predisposition, with GB-specific associations identified in natural killer (NK) cells (pHM = 0.0201) and stem cells (pHM = 0.0265). CONCLUSIONS: This analysis identifies putative new associations between glioma and autoimmune conditions with genomic architecture that is inversely correlated with that of glioma and that T cells, NK cells, and myeloid cells are involved in mediating glioma predisposition. This provides further evidence that increased activation of the acquired immune system may modify individual susceptibility to glioma.

The Shared Genetic Architectures Between Lung Cancer and Multiple Polygenic Phenotypes in Genome-Wide Association Studies.

BACKGROUND: Prior genome-wide association studies have identified numerous lung cancer risk loci and reveal substantial etiologic heterogeneity across histologic subtypes. Analyzing the shared genetic architecture underlying variation in complex traits can elucidate common genetic etiologies across phenotypes. Exploring pairwise genetic correlations between lung cancer and other polygenic traits can reveal the common genetic etiology of correlated phenotypes. METHODS: Using cross-trait linkage disequilibrium score regression, we estimated the pairwise genetic correlation and heritability between lung cancer and multiple traits using publicly available summary statistics. Identified genetic relationships were also examined after excluding genomic regions known to be associated with smoking behaviors, a major risk factor for lung cancer. RESULTS: We observed several traits showing moderate single nucleotide polymorphism-based heritability and significant genetic correlations with lung cancer. We observed highly significant correlations between the genetic architectures of lung cancer and emphysema/chronic bronchitis across all histologic subtypes, as well as among lung cancer occurring among smokers. Our analyses revealed highly significant positive correlations between lung cancer and paternal history of lung cancer. We also observed a strong negative correlation with parental longevity. We observed consistent directions in genetic patterns after excluding genomic regions associated with smoking behaviors. CONCLUSIONS: This study identifies numerous phenotypic traits that share genomic architecture with lung carcinogenesis and are not fully accounted for by known smoking-associated genomic loci. IMPACT: These findings provide new insights into the etiology of lung cancer by identifying traits that are genetically correlated with increased risk of lung cancer.

POT1 Regulates Proliferation and Confers Sexual Dimorphism in Glioma.

Germline POT1 mutations are found in a spectrum of cancers and confer increased risk. Recently, we identified a series of novel germline POT1 mutations that predispose carrier families to the development of glioma. Despite these strong associations, how these glioma-associated POT1 mutations contribute to glioma tumorigenesis remains undefined. Here we show that POT1-G95C increases proliferation in glioma-initiating cells in vitro and in progenitor populations in the developing brain. In a native mouse model of glioma, loss of Pot1a/b resulted in decreased survival in females compared with males. These findings were corroborated in human glioma, where low POT1 expression correlated with decreased survival in females. Transcriptomic and IHC profiling of Pot1a/b-deficient glioma revealed that tumors in females exhibited decreased expression of immune markers and increased expression of cell-cycle signatures. Similar sex-dependent trends were observed in human gliomas that had low expression of POT1. Together, our studies demonstrate context-dependent functions for POT1 mutation or loss in driving progenitor proliferation in the developing brain and sexual dimorphism in glioma. SIGNIFICANCE: This study shows that manipulation of POT1 expression in glioma has sex-specific effects on tumorigenesis and associated immune signatures.