Citations

Abstract Diffuse large B-cell lymphoma (DLBCL) is a molecularly heterogeneous group of malignancies with frequent genetic abnormalities. G-quadruplex (G4) DNA structures may facilitate this genomic instability through association with activation-induced cytidine deaminase (AID), an antibody diversification enzyme implicated in mutation of oncogenes in B-cell lymphomas. Chromatin immunoprecipitation sequencing analyses in this study revealed that AID hotspots in both activated B cells and lymphoma cells in vitro were highly enriched for G4 elements. A representative set of these targeted sequences was validated for characteristic, stable G4 structure formation including previously unknown G4s in lymphoma-associated genes, CBFA2T3, SPIB, BCL6, HLA-DRB5 and MEF2C, along with the established BCL2 and MYC structures. Frequent genome-wide G4 formation was also detected for the first time in DLBCL patient-derived tissues using BG4, a structure-specific G4 antibody. Tumors with greater staining were more likely to have concurrent BCL2 and MYC oncogene amplification and BCL2 mutations. Ninety-seven percent of the BCL2 mutations occurred within G4 sites that overlapped with AID binding. G4 localization at sites of mutation, and within aggressive DLBCL tumors harboring amplified BCL2 and MYC, supports a role for G4 structures in events that lead to a loss of genomic integrity, a critical step in B-cell lymphomagenesis.

Background: Abdominal aortic aneurysm (AAA) is an important cause of cardiovascular mortality; however, its genetic determinants remain incompletely defined. In total, 10 previously identified risk loci explain a small fraction of AAA heritability. Methods: We performed a genome-wide association study in the Million Veteran Program testing ≈18 million DNA sequence variants with AAA (7642 cases and 172 172 controls) in veterans of European ancestry with independent replication in up to 4972 cases and 99 858 controls. We then used mendelian randomization to examine the causal effects of blood pressure on AAA. We examined the association of AAA risk variants with aneurysms in the lower extremity, cerebral, and iliac arterial beds, and derived a genome-wide polygenic risk score (PRS) to identify a subset of the population at greater risk for disease. Results: Through a genome-wide association study, we identified 14 novel loci, bringing the total number of known significant AAA loci to 24. In our mendelian randomization analysis, we demonstrate that a genetic increase of 10 mm Hg in diastolic blood pressure (odds ratio, 1.43 [95% CI, 1.24–1.66]; P =1.6×10 −6 ), as opposed to systolic blood pressure (odds ratio, 1.06 [95% CI, 0.97–1.15]; P =0.2), likely has a causal relationship with AAA development. We observed that 19 of 24 AAA risk variants associate with aneurysms in at least 1 other vascular territory. A 29-variant PRS was strongly associated with AAA (odds ratio PRS , 1.26 [95% CI, 1.18–1.36]; P PRS =2.7×10 −11 per SD increase in PRS), independent of family history and smoking risk factors (odds ratio PRS+family history+smoking , 1.24 [95% CI, 1.14–1.35]; P PRS =1.27×10 −6 ). Using this PRS, we identified a subset of the population with AAA prevalence greater than that observed in screening trials informing current guidelines. Conclusions: We identify novel AAA genetic associations with therapeutic implications and identify a subset of the population at significantly increased genetic risk of AAA independent of family history. Our data suggest that extending current screening guidelines to include testing to identify those with high polygenic AAA risk, once the cost of genotyping becomes comparable with that of screening ultrasound, would significantly increase the yield of current screening at reasonable cost.

Abstract Objectives To describe the histologic features that are helpful in the diagnosis of the rare bronchiolar adenomas/ciliated muconodular papillary tumors (BAs/CMPTs) during intraoperative consultation. Methods Multi-institutional retrospective review of frozen sections of 18 BAs/CMPTs. Results In 14 of 18 cases, BA/CMPT was the primary reason for sublobar lung resection, and in 4 cases, BA/CMPT was an incidental finding intraoperatively for resections performed for carcinoma in other lobes. There were 11 proximal-type/classic BAs/CMPTs and 7 distal-type/nonclassic BAs/CMPTs. Only 3 (16.7%) of 18 were correctly diagnosed at the time of frozen section, all of which were proximal type/classic. The remainder were diagnosed as adenocarcinoma (n = 7); invasive mucinous adenocarcinoma (n = 1); non–small cell lung carcinoma (n = 1); cystic mucinous neoplasm, favor adenocarcinoma (either mucinous or colloid type) (n = 1); favor adenocarcinoma, cannot exclude CMPT (n = 1); atypical proliferation (n = 2); mucinous epithelial proliferation (n = 1); and mucous gland adenoma (n = 1). Conclusions BA/CMPT can potentially be misdiagnosed as carcinoma during intraoperative consultation. On retrospective review of the frozen sections, the presence of the following may help to avoid misdiagnosis: a mixture of bland ciliated columnar cells, mucinous cells, and, most important, a basal cell layer, as well as a lack of necrosis, significant atypia, and mitoses.

Abstract Background: Atezolizumab (atezo) and bevacizumab (bev) combination therapy has demonstrated robust clinical activity in patients with unresectable HCC who have not received prior systemic therapy (Lee et al., APPLE 2019; Cheng et al., ESMO Asia 2019). In this exploratory analysis, we aimed to identify tumor-based molecular biomarkers that may be associated with clinical response or resistance to atezo + bev. We also investigated how VEGF blockade with bev could potentiate PD-L1 checkpoint inhibition with atezo in pts with advanced HCC. Methods: Archival tumor tissues or fresh biopsies taken prior to treatment were collected from HCC pts enrolled in the Phase 1b trial GO30140 (NCT02715531). Arm A (n = 104) was a single-arm evaluation of atezo + bev; Arm F (n = 119) was a randomized arm comparing atezo + bev with atezo. Whole-exome sequencing was carried out on these tumor tissues to determine tumor mutation burden (TMB). Gene expression in tumors was profiled by RNAseq analysis. The association between biomarker expression and clinical response (responders [R] vs. non-responders [NR]) or PFS was assessed by t-tests or Cox regression models, respectively. All p-values are descriptive. Results: In Arm A, 90/104 pts were biomarker evaluable. TMB was not associated with response to atezo + bev or PFS. In contrast, analysis of baseline tumor gene expression showed that pre-existing immunity appeared to be associated with clinical response and longer PFS, which included high expression of CD274 (PD-L1) (R vs. NR, p < 2.1 × 10−5; PFS: HR = 0.42 [0.25-0.72]), and T effector signature (GZMB, PRF1, CXCL9) (R vs. NR, p < 0.0004; PFS: HR = 0.46 [0.27-0.78]). Gene expression related to Notch pathway activation (i.e. high expression of HES1) appeared to be associated with lack of response to atezo + bev (p < 0.039) and shorter PFS (HR = 2.1 [1.3-3.6]). In Arm F, 91/119 pts were biomarker evaluable. High expression of VEGF receptor 2 (VEGFR2; HR = 0.36 [0.16-0.81]), Treg (HR = 0.35 [0.15-0.82]), myeloid inflammation (HR = 0.43 [0.19-0.95]), and TREM1/MDSC signatures (HR = 0.43 [0.19-0.94]) was associated with longer PFS in patients treated with atezo + bev than in those treated with atezo alone. Analysis of 12 serial biopsy pairs confirmed reduced levels of VEGFR2 and Treg signatures after atezo + bev treatment. Conclusion: We identified candidate biomarkers for predicting response to atezo + bev in HCC. Furthermore, the findings in Arm F are consistent with previous preclinical studies supporting a multi-faceted role of VEGF/VEGFR signaling in promoting immune suppression in addition to angiogenesis. Overall, the data presented here further support the mechanistic hypotheses on how anti-VEGF may combine with immune checkpoint blockade to increase its clinical benefit. As these results are exploratory, future study is needed to confirm these findings in a larger population. Citation Format: Andrew X. Zhu, Yinghui Guan, Alexander R. Abbas, Hartmut Koeppen, Shan Lu, Chih-Hung Hsu, Kyung-Hun Lee, Michael S. Lee, Aiwu Ruth He, Amit Mahipal, Beiying Ding, Jessica Spahn, Wendy Verret, Baek-Yeol Ryoo, Yulei Wang. Genomic correlates of clinical benefits from atezolizumab combined with bevacizumab vs. atezolizumab alone in patients with advanced hepatocellular carcinoma (HCC) [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr CT044.

Background While there is a long history of measuring death and disability from injuries, modern research methods must account for the wide spectrum of disability that can occur in an injury, and must provide estimates with sufficient demographic, geographical and temporal detail to be useful for policy makers. The Global Burden of Disease (GBD) 2017 study used methods to provide highly detailed estimates of global injury burden that meet these criteria. Methods In this study, we report and discuss the methods used in GBD 2017 for injury morbidity and mortality burden estimation. In summary, these methods included estimating cause-specific mortality for every cause of injury, and then estimating incidence for every cause of injury. Non-fatal disability for each cause is then calculated based on the probabilities of suffering from different types of bodily injury experienced. Results GBD 2017 produced morbidity and mortality estimates for 38 causes of injury. Estimates were produced in terms of incidence, prevalence, years lived with disability, cause-specific mortality, years of life lost and disability-adjusted life-years for a 28-year period for 22 age groups, 195 countries and both sexes. Conclusions GBD 2017 demonstrated a complex and sophisticated series of analytical steps using the largest known database of morbidity and mortality data on injuries. GBD 2017 results should be used to help inform injury prevention policy making and resource allocation. We also identify important avenues for improving injury burden estimation in the future.

AbstractIt is of great scientific interest to identify interactions between genetic variants and environmental exposures that may modify the risk of complex diseases. However, larger sample sizes are usually required to detect gene‐by‐environment interaction (G × E) than required to detect genetic main association effects. To boost the statistical power and improve the understanding of the underlying molecular mechanisms, we incorporate functional genomics information, specifically, expression quantitative trait loci (eQTLs), into a data‐adaptive G × E test, called aGEw. This test adaptively chooses the best eQTL weights from multiple tissues and provides an extra layer of weighting at the genetic variant level. Extensive simulations show that the aGEw test can control the Type 1 error rate, and the power is resilient to the inclusion of neutral variants and noninformative external weights. We applied the proposed aGEw test to the Pancreatic Cancer Case–Control Consortium (discovery cohort of 3,585 cases and 3,482 controls) and the PanScan II genome‐wide association study data (replication cohort of 2,021 cases and 2,105 controls) with smoking as the exposure of interest. Two novel putative smoking‐related pancreatic cancer susceptibility genes, TRIP10 and KDM3A, were identified. The aGEw test is implemented in an R package aGE.

Abstract Background: Lung cancer remains the leading cause of cancer death worldwide, with 15% to 20% occurring in never smokers. To assess genetic determinants for prognosis among never smokers, we conducted a genome-wide investigation in the International Lung Cancer Consortium (ILCCO). Methods: Genomic and clinical data from 1,569 never-smoking patients with lung cancer of European ancestry from 10 ILCCO studies were included. HRs and 95% confidence intervals of overall survival were estimated. We assessed whether the associations were mediated through mRNA expression–based 1,553 normal lung tissues from the lung expression quantitative trait loci (eQTL) dataset and Genotype-Tissue Expression (GTEx). For cross-ethnicity generalization, we assessed the associations in a Japanese study (N = 887). Results: One locus at 13q22.2 was associated with lung adenocarcinoma survival at genome-wide level, with carriers of rs12875562-T allele exhibiting poor prognosis [HR = 1.71 (1.41–2.07), P = 3.60 × 10−8], and altered mRNA expression of LMO7DN in lung tissue (GTEx, P = 9.40 × 10−7; Lung eQTL dataset, P = 0.003). Furthermore, 2 of 11 independent loci that reached the suggestive significance level (P < 10−6) were significant eQTL affecting mRNA expression of nearby genes in lung tissues, including CAPZB at 1p36.13 and UBAC1 at 9q34.3. One locus encoding NWD2/KIAA1239 at 4p14 showed associations in both European [HR = 0.50 (0.38–0.66), P = 6.92 × 10−7] and Japanese populations [HR = 0.79 (0.67–0.94), P = 0.007]. Conclusions: Based on the largest genomic investigation on the lung cancer prognosis of never smokers to date, we observed that lung cancer prognosis is affected by inherited genetic variants. Impact: We identified one locus near LMO7DN at genome-wide level and several potential prognostic genes with cis-effect on mRNA expression. Further functional genomics work is required to understand their role in tumor progression.

Abstract Registry-based epidemiologic studies suggest associations between chronic inflammatory intestinal diseases and pancreatic ductal adenocarcinoma (PDAC). As genetic susceptibility contributes to a large proportion of chronic inflammatory intestinal diseases, we hypothesize that the genomic regions surrounding established genome-wide associated variants for these chronic inflammatory diseases are associated with PDAC. We examined the association between PDAC and genomic regions (±500 kb) surrounding established common susceptibility variants for ulcerative colitis, Crohn's disease, inflammatory bowel disease, celiac disease, chronic pancreatitis, and primary sclerosing cholangitis. We analyzed summary statistics from genome-wide association studies data for 8,384 cases and 11,955 controls of European descent from two large consortium studies using the summary data-based adaptive rank truncated product method to examine the overall association of combined genomic regions for each inflammatory disease group. Combined genomic susceptibility regions for ulcerative colitis, Crohn disease, inflammatory bowel disease, and chronic pancreatitis were associated with PDAC at P values < 0.05 (0.0040, 0.0057, 0.011, and 3.4 × 10−6, respectively). After excluding the 20 PDAC susceptibility regions (±500 kb) previously identified by GWAS, the genomic regions for ulcerative colitis, Crohn disease, and inflammatory bowel disease remained associated with PDAC (P = 0.0029, 0.0057, and 0.0098, respectively). Genomic regions for celiac disease (P = 0.22) and primary sclerosing cholangitis (P = 0.078) were not associated with PDAC. Our results support the hypothesis that genomic regions surrounding variants associated with inflammatory intestinal diseases, particularly, ulcerative colitis, Crohn disease, inflammatory bowel disease, and chronic pancreatitis are associated with PDAC. Significance: The joint effects of common variants in genomic regions containing susceptibility loci for inflammatory bowel disease and chronic pancreatitis are associated with PDAC and may provide insights to understanding pancreatic cancer etiology.

Abstract Background: Obesity and diabetes are major modifiable risk factors for pancreatic cancer. Interactions between genetic variants and diabetes/obesity have not previously been comprehensively investigated in pancreatic cancer at the genome-wide level. Methods: We conducted a gene–environment interaction (GxE) analysis including 8,255 cases and 11,900 controls from four pancreatic cancer genome-wide association study (GWAS) datasets (Pancreatic Cancer Cohort Consortium I–III and Pancreatic Cancer Case Control Consortium). Obesity (body mass index ≥30 kg/m2) and diabetes (duration ≥3 years) were the environmental variables of interest. Approximately 870,000 SNPs (minor allele frequency ≥0.005, genotyped in at least one dataset) were analyzed. Case–control (CC), case-only (CO), and joint-effect test methods were used for SNP-level GxE analysis. As a complementary approach, gene-based GxE analysis was also performed. Age, sex, study site, and principal components accounting for population substructure were included as covariates. Meta-analysis was applied to combine individual GWAS summary statistics. Results: No genome-wide significant interactions (departures from a log-additive odds model) with diabetes or obesity were detected at the SNP level by the CC or CO approaches. The joint-effect test detected numerous genome-wide significant GxE signals in the GWAS main effects top hit regions, but the significance diminished after adjusting for the GWAS top hits. In the gene-based analysis, a significant interaction of diabetes with variants in the FAM63A (family with sequence similarity 63 member A) gene (significance threshold P < 1.25 × 10−6) was observed in the meta-analysis (PGxE = 1.2 ×10−6, PJoint = 4.2 ×10−7). Conclusions: This analysis did not find significant GxE interactions at the SNP level but found one significant interaction with diabetes at the gene level. A larger sample size might unveil additional genetic factors via GxE scans. Impact: This study may contribute to discovering the mechanism of diabetes-associated pancreatic cancer.