Citations

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.

Abstract Background Although 20 pancreatic cancer susceptibility loci have been identified through genome-wide association studies in individuals of European ancestry, much of its heritability remains unexplained and the genes responsible largely unknown. Methods To discover novel pancreatic cancer risk loci and possible causal genes, we performed a pancreatic cancer transcriptome-wide association study in Europeans using three approaches: FUSION, MetaXcan, and Summary-MulTiXcan. We integrated genome-wide association studies summary statistics from 9040 pancreatic cancer cases and 12 496 controls, with gene expression prediction models built using transcriptome data from histologically normal pancreatic tissue samples (NCI Laboratory of Translational Genomics [n = 95] and Genotype-Tissue Expression v7 [n = 174] datasets) and data from 48 different tissues (Genotype-Tissue Expression v7, n = 74–421 samples). Results We identified 25 genes whose genetically predicted expression was statistically significantly associated with pancreatic cancer risk (false discovery rate < .05), including 14 candidate genes at 11 novel loci (1p36.12: CELA3B; 9q31.1: SMC2, SMC2-AS1; 10q23.31: RP11-80H5.9; 12q13.13: SMUG1; 14q32.33: BTBD6; 15q23: HEXA; 15q26.1: RCCD1; 17q12: PNMT, CDK12, PGAP3; 17q22: SUPT4H1; 18q11.22: RP11-888D10.3; and 19p13.11: PGPEP1) and 11 at six known risk loci (5p15.33: TERT, CLPTM1L, ZDHHC11B; 7p14.1: INHBA; 9q34.2: ABO; 13q12.2: PDX1; 13q22.1: KLF5; and 16q23.1: WDR59, CFDP1, BCAR1, TMEM170A). The association for 12 of these genes (CELA3B, SMC2, and PNMT at novel risk loci and TERT, CLPTM1L, INHBA, ABO, PDX1, KLF5, WDR59, CFDP1, and BCAR1 at known loci) remained statistically significant after Bonferroni correction. Conclusions By integrating gene expression and genotype data, we identified novel pancreatic cancer risk loci and candidate functional genes that warrant further investigation.

Abstract Background: Pancreatic cancer is associated with development of cachexia, a wasting syndrome thought to limit survival. Few studies have longitudinally quantified peripheral tissues or identified biomarkers predictive of future tissue wasting. Methods: Adipose and muscle tissue were measured by computed tomography (CT) at diagnosis and 50 to 120 days later in 164 patients with advanced pancreatic cancer. Tissue changes and survival were evaluated by Cox proportional hazards regression. Baseline levels of circulating markers were examined in relation to future tissue wasting. Results: Compared with patients in the bottom quartile of muscle change per 30 days (average gain of 0.8 ± 2.0 cm2), those in the top quartile (average loss of 12.9 ± 4.9 cm2) had a hazard ratio (HR) for death of 2.01 [95% confidence interval (CI), 1.12–3.62]. Patients in the top quartile of muscle attenuation change (average decrease of 4.9 ± 2.4 Hounsfield units) had an HR of 2.19 (95% CI, 1.18–4.04) compared with those in the bottom quartile (average increase of 2.4 ± 1.6 Hounsfield units). Changes in adipose tissue were not associated with survival. Higher plasma branched chain amino acids (BCAA; P = 0.004) and lower monocyte chemoattractant protein-1 (MCP-1; P = 0.005) at diagnosis were associated with greater future muscle loss. Conclusions: In patients with advanced pancreatic cancer, muscle loss and decrease in muscle density in 2 to 4 months after diagnosis were associated with reduced survival. BCAAs and MCP-1 levels at diagnosis were associated with subsequent muscle loss. Impact: BCAAs and MCP-1 levels at diagnosis could identify a high-risk group for future tissue wasting.

Purpose of review Spinal epidural abscess (SEA) is still a rare but potentially very morbid infection of the spine. In recent years, the incidence has risen sharply but the condition remains a medical conundrum wrought with unacceptably long diagnostic delays. The outcome depends on timely diagnosis and missed opportunities can be associated with catastrophic consequences. Management and outcomes have improved over the past decade. This review focuses on risk factors and markers that can aid in establishing the diagnosis, the radiological characteristics of SEA on MRI and their clinical implications, as well as the importance of establishing clear indications for surgical decompression. Recent findings This once exclusively surgically managed entity is increasingly treated conservatively with antimicrobial therapy. Patients diagnosed in a timely fashion, prior to cord involvement and the onset of neurologic deficits can safely be managed without decompressive surgery with targeted antimicrobial therapy. Patients with acute cord compression and gross neurologic deficits promptly undergo decompression. The greatest therapeutic dilemma remains the group with mild neurological deficits. As failure rates of delayed surgery approach 40%, recent research is focused on predictive models for failure of conservative SEA management. In addition, protocols are being implemented with some success, to shorten the diagnostic delay of SEA on initial presentation. Summary SEA is a potentially devastating condition that is frequently missed. Protocols are put in place to facilitate early evaluation of back pain in patients with red flags with appropriate cross-sectional imaging, namely contrast-enhanced MRI. Efforts for establishing clear-cut indications for surgical decompression of SEA are underway.

Abstract Background: CA125 is elevated in 80% of ovarian cancer cases and has proven utility in assessing response to therapy and prognosis. Unfortunately, CA125 is elevated in a variety of benign conditions and only in 50% of early stage ovarian cancers, resulting in a sensitivity and specificity unacceptable for population-based screening. Therefore, understanding factors that influence CA125 at presentation could provide important insights for interpreting CA125 values. Methods: Using pre-treatment CA125 and detailed epidemiologic data from 12 studies participating in the Ovarian Cancer Association Consortium (OCAC), we evaluated factors previously reported to influence CA125 levels, including age, race, oral contraceptive use, parity, tubal ligation, endometriosis, body mass index (BMI), personal history of breast cancer, or a family history of breast or ovarian cancer. We used linear regression to estimate the association between each variable and CA125 probit scores, which we used to standardize values between studies. Secondary analyses included adjustment for histologic subtype. We also estimated the associations within each study using log-transformed CA125 as the outcome and estimated summary measures using random effects meta-analyses. Results: Of the 4417 cases included in the analysis, 2918 (66%) were serous, 227 (5%) were mucinous, 484 (11%) were endometrioid, and 258 (6%) were clear cell carcinomas. Median CA125 values varied between studies with a high of 831 U/mL and a low of 271 U/mL. We observed no association between race, oral contraceptive use, tubal ligation, endometriosis, prior breast cancer, and family history of breast cancer and pre-treatment CA125. However, we observed increased pre-treatment CA125 levels with older age (>70 vs. < 50, p=0.03), parity (p=0.01), number of children (p=0.02), obesity (BMI>30 vs. 21-25, p=0.03), and family history of ovarian cancer (p=0.05). Results were similar but attenuated when we calculated summary estimates of the association using meta-analysis of study specific estimates of the association with log-transformed CA125 rather than probit scores. Age and BMI remained predictive of pre-treatment CA125 values after adjustment for histologic subtype. Our data are limited by between site variability in CA125 assays; therefore, validation of these findings is needed with adjustment for type of assay used or in a study population in which all cases had pre-treatment CA125 values measured with the same assay. Conclusions: Despite these limitations, results from this analysis of over 4000 ovarian cancer cases suggest that age and body size may influence pre-treatment CA125 values. Citation Format: KL Terry, A Babic, BY Karlan, MT Goodman, D Lambrechts, F Heitz, K Matsuo, I McNeish, T Pejovic, S Kruger Kjaer, PM Webb, E Hogdall, EL Goode, DW Cramer, for the Ovarian Cancer Association Consortium. Epidemiologic predictors of pre-treatment CA125 in women with ovarian cancer [abstract]. In: Proceedings of the 10th Biennial Ovarian Cancer Research Symposium; Sep 8-9, 2014; Seattle, WA. Philadelphia (PA): AACR; Clin Cancer Res 2015;21(16 Suppl):Abstract nr AS13.