Rachael Stolzenberg-Solomon, Laufey Amundadottir and colleagues report a genome-wide association study of pancreatic cancer. They identify four new susceptibility loci. We performed a multistage genome-wide association study including 7,683 individuals with pancreatic cancer and 14,397 controls of European descent. Four new loci reached genome-wide significance: rs6971499 at 7q32.3 (LINC-PINT, per-allele odds ratio (OR) = 0.79, 95% confidence interval (CI) 0.74–0.84, P = 3.0 × 10−12), rs7190458 at 16q23.1 (BCAR1/CTRB1/CTRB2, OR = 1.46, 95% CI 1.30–1.65, P = 1.1 × 10−10), rs9581943 at 13q12.2 (PDX1, OR = 1.15, 95% CI 1.10–1.20, P = 2.4 × 10−9) and rs16986825 at 22q12.1 (ZNRF3, OR = 1.18, 95% CI 1.12–1.25, P = 1.2 × 10−8). We identified an independent signal in exon 2 of TERT at the established region 5p15.33 (rs2736098, OR = 0.80, 95% CI 0.76–0.85, P = 9.8 × 10−14). We also identified a locus at 8q24.21 (rs1561927, P = 1.3 × 10−7) that approached genome-wide significance located 455 kb telomeric of PVT1. Our study identified multiple new susceptibility alleles for pancreatic cancer that are worthy of follow-up studies.

Endometrial cancer is the most commonly diagnosed cancer of the female reproductive tract in developed countries. Through genome-wide association studies (GWAS), we have previously identified eight risk loci for endometrial cancer. Here, we present an expanded meta-analysis of 12,906 endometrial cancer cases and 108,979 controls (including new genotype data for 5624 cases) and identify nine novel genome-wide significant loci, including a locus on 12q24.12 previously identified by meta-GWAS of endometrial and colorectal cancer. At five loci, expression quantitative trait locus (eQTL) analyses identify candidate causal genes; risk alleles at two of these loci associate with decreased expression of genes, which encode negative regulators of oncogenic signal transduction proteins (SH2B3 (12q24.12) and NF1 (17q11.2)). In summary, this study has doubled the number of known endometrial cancer risk loci and revealed candidate causal genes for future study.

In 2020, 146,063 deaths due to pancreatic cancer are estimated to occur in Europe and the United States combined. To identify common susceptibility alleles, we performed the largest pancreatic cancer GWAS to date, including 9040 patients and 12,496 controls of European ancestry from the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4). Here, we find significant evidence of a novel association at rs78417682 (7p12/TNS3, P = 4.35 × 10⁻⁸). Replication of 10 promising signals in up to 2737 patients and 4752 controls from the PANcreatic Disease ReseArch (PANDoRA) consortium yields new genome-wide significant loci: rs13303010 at 1p36.33 (NOC2L, P = 8.36 × 10⁻¹⁴), rs2941471 at 8q21.11 (HNF4G, P = 6.60 × 10⁻¹⁰), rs4795218 at 17q12 (HNF1B, P = 1.32 × 10⁻⁸), and rs1517037 at 18q21.32 (GRP, P = 3.28 × 10⁻⁸). rs78417682 is not statistically significantly associated with pancreatic cancer in PANDoRA. Expression quantitative trait locus analysis in three independent pancreatic data sets provides molecular support of NOC2L as a pancreatic cancer susceptibility gene.

Alison Klein and colleagues report a genome-wide meta-analysis to identify loci associated with pancreatic cancer risk. They identify associated variants at 17q25.1, 3q29, 7p13 and 2p13.3. Pancreatic cancer is the fourth leading cause of cancer death in the developed world1. Both inherited high-penetrance mutations in BRCA2 (ref. 2), ATM3, PALB2 (ref. 4), BRCA1 (ref. 5), STK11 (ref. 6), CDKN2A7 and mismatch-repair genes8 and low-penetrance loci are associated with increased risk9,10,11,12. To identify new risk loci, we performed a genome-wide association study on 9,925 pancreatic cancer cases and 11,569 controls, including 4,164 newly genotyped cases and 3,792 controls in 9 studies from North America, Central Europe and Australia. We identified three newly associated regions: 17q25.1 (LINC00673, rs11655237, odds ratio (OR) = 1.26, 95% confidence interval (CI) = 1.19–1.34, P = 1.42 × 10−14), 7p13 (SUGCT, rs17688601, OR = 0.88, 95% CI = 0.84–0.92, P = 1.41 × 10−8) and 3q29 (TP63, rs9854771, OR = 0.89, 95% CI = 0.85–0.93, P = 2.35 × 10−8). We detected significant association at 2p13.3 (ETAA1, rs1486134, OR = 1.14, 95% CI = 1.09–1.19, P = 3.36 × 10−9), a region with previous suggestive evidence in Han Chinese12. We replicated previously reported associations at 9q34.2 (ABO)9, 13q22.1 (KLF5)10, 5p15.33 (TERT and CLPTM1)10,11, 13q12.2 (PDX1)11, 1q32.1 (NR5A2)10, 7q32.3 (LINC-PINT)11, 16q23.1 (BCAR1)11 and 22q12.1 (ZNRF3)11. Our study identifies new loci associated with pancreatic cancer risk.

Purpose: D-limonene is a plant extract with widespread application, and it has been recently reported to have antiproliferative and proapoptotic effects on cancer cells. However, the mechanisms by which D-limonene achieves these effects, especially in lung cancer, are not entirely clear. Therefore, the goal of this study was to examine the effects of D-limonene on lung cancer and explore its mechanisms of action. Methods: We examined the therapeutic effects of D-limonene on lung cancer cells and in a xenograft animal model by characterizing its effects on the pathways of apoptosis and autophagy. Cell proliferation was measured using the Cell Counting Kit-8, and apoptosis was determined by flow cytometric analysis. Levels of LC3 puncta, an autophagy marker, were analyzed by laser scanning confocal microscopy. Autophagy and apoptosis-related gene expression were assessed by real-time quantitative polymerase chain reaction and Western blot. Results: D-limonene inhibited the growth of lung cancer cells and suppressed the growth of transplanted tumors in nude mice. Expression of apoptosis and autophagy-related genes were increased in tumors after treatment with D-limonene. Furthermore, the use of chloroquine, an autophagy inhibitor, and knockdown of the atg5 gene, suppressed the apoptosis induced by D-limonene. Conclusion: D-limonene may have a therapeutic effect on lung cancer as it can induce apoptosis of lung cancer cells by promoting autophagy.

Case-cohort studies have become common in epidemiological studies of rare disease, with Cox regression models the principal method used in their analysis. However, no appropriate procedures to assess the assumption of proportional hazards of case-cohort Cox models have been proposed. We extended the correlation test based on Schoenfeld residuals, an approach used to evaluate the proportionality of hazards in standard Cox models. Specifically, pseudolikelihood functions were used to define “case-cohort Schoenfeld residuals”, and then the correlation of these residuals with each of three functions of event time (i.e., the event time itself, rank order, Kaplan-Meier estimates) was determined. The performances of the proposed tests were examined using simulation studies. We then applied these methods to data from a previously published case-cohort investigation of the insulin/IGF-axis and colorectal cancer. Simulation studies showed that each of the three correlation tests accurately detected non-proportionality. Application of the proposed tests to the example case-cohort investigation dataset showed that the Cox proportional hazards assumption was not satisfied for certain exposure variables in that study, an issue we addressed through use of available, alternative analytical approaches. The proposed correlation tests provide a simple and accurate approach for testing the proportional hazards assumption of Cox models in case-cohort analysis. Evaluation of the proportional hazards assumption is essential since its violation raises questions regarding the validity of Cox model results which, if unrecognized, could result in the publication of erroneous scientific findings.