Citations

Autoimmune hepatitis (AIH) in humans is a severe inflammatory liver disease characterized by interface hepatitis, the presence of circulating autoantibodies, and hyper‐gammaglobulinemia. There are two types of AIH, type 1 (AIH‐1) and type 2 (AIH‐2), characterized by distinct autoimmune serology. Patients with AIH‐1 are positive for anti–smooth muscle and/or antinuclear autoantibodies, whereas patients with AIH‐2 have anti–liver kidney microsomal type 1 and/or anti–liver cytosol type 1 autoantibodies. Cytochrome P4502D6 is the antigenic target of anti–liver kidney microsomal type 1, and formiminotransferase cyclodeaminase is the antigenic target of anti–liver cytosol type 1. It is known that AIH, both types 1 and 2, is strongly linked to the human leukocyte antigen (HLA) alleles ‐DR3, ‐DR4, and ‐DR7. However, direct evidence of the association of HLA with AIH is lacking. We developed a novel mouse model of AIH using the HLA‐DR3 transgenic mouse on the nonobese‐diabetic background by immunization of HLA‐DR3– and HLA‐DR3+ nonobese‐diabetic mice with a DNA plasmid, coding for human cytochrome P4502D6/formiminotransferase cyclodeaminase fusion protein. Immunization with cytochrome P4502D6/formiminotransferase cyclodeaminase leads to a sustained elevation of alanine aminotransferase, development of antinuclear autoantibodies and anti–liver kidney microsomal type 1/anti–liver cytosol type 1 autoantibodies, chronic immune cell infiltration, and parenchymal fibrosis on liver histology in HLA‐DR3+ mice. Immunized mice also showed an enhanced T helper 1 immune response and paucity of the frequency of regulatory T cells in the liver. Moreover, HLA‐DR3+ mice with exacerbated AIH showed reduced diversity and total load of gut bacteria. Conclusion: Our humanized animal model has provided a novel experimental tool to further elucidate the pathogenesis of AIH and to evaluate the efficacy and safety of immunoregulatory therapeutic interventions in vivo. (Hepatology 2015;62:1536–1550)

Abstract Background: High body mass index (BMI) is consistently linked to increased risk of colorectal cancer for men, whereas the association is less clear for women. As risk estimates from observational studies may be biased and/or confounded, we conducted a Mendelian randomization study to estimate the causal association between BMI and colorectal cancer. Methods: We used data from 10,226 colorectal cancer cases and 10,286 controls of European ancestry. The Mendelian randomization analysis used a weighted genetic risk score, derived from 77 genome-wide association study–identified variants associated with higher BMI, as an instrumental variable (IV). We compared the IV odds ratio (IV-OR) with the OR obtained using a conventional covariate-adjusted analysis. Results: Individuals carrying greater numbers of BMI-increasing alleles had higher colorectal cancer risk [per weighted allele OR, 1.31; 95% confidence interval (CI), 1.10–1.57]. Our IV estimation results support the hypothesis that genetically influenced BMI is directly associated with risk for colorectal cancer (IV-OR per 5 kg/m2, 1.50; 95% CI, 1.13–2.01). In the sex-specific IV analyses higher BMI was associated with higher risk of colorectal cancer among women (IV-OR per 5 kg/m2, 1.82; 95% CI, 1.26–2.61). For men, genetically influenced BMI was not associated with colorectal cancer (IV-OR per 5 kg/m2, 1.18; 95% CI, 0.73–1.92). Conclusions: High BMI was associated with increased colorectal cancer risk for women. Whether abdominal obesity, rather than overall obesity, is a more important risk factor for men requires further investigation. Impact: Overall, conventional epidemiologic and Mendelian randomization studies suggest a strong association between obesity and the risk of colorectal cancer. Cancer Epidemiol Biomarkers Prev; 24(7); 1024–31. ©2015 AACR.

Abstract Summary: Structural variations (SVs) are large genomic rearrangements that vary significantly in size, making them challenging to detect with the relatively short reads from next-generation sequencing (NGS). Different SV detection methods have been developed; however, each is limited to specific kinds of SVs with varying accuracy and resolution. Previous works have attempted to combine different methods, but they still suffer from poor accuracy particularly for insertions. We propose MetaSV, an integrated SV caller which leverages multiple orthogonal SV signals for high accuracy and resolution. MetaSV proceeds by merging SVs from multiple tools for all types of SVs. It also analyzes soft-clipped reads from alignment to detect insertions accurately since existing tools underestimate insertion SVs. Local assembly in combination with dynamic programming is used to improve breakpoint resolution. Paired-end and coverage information is used to predict SV genotypes. Using simulation and experimental data, we demonstrate the effectiveness of MetaSV across various SV types and sizes. Availability and implementation: Code in Python is at http://bioinform.github.io/metasv/. Contact: rd@bina.com Supplementary information: Supplementary data are available at Bioinformatics online.

Purpose To develop a genomic signature that predicts benefit from trastuzumab in human epidermal growth factor receptor 2–positive breast cancer. Patients and Methods DASL technology was used to quantify mRNA in samples from 1,282 patients enrolled onto the Combination Chemotherapy With or Without Trastuzumab in Treating Women With Breast Cancer (North Central Cancer Treatment Group N9831 [NCCTG-N9831]) adjuvant trastuzumab trial. Cox proportional hazard ratios (HRs), adjusted for significant clinicopathologic risk factors, were used to determine the association of each gene with relapse-free survival (RFS) for 433 patients who received chemotherapy alone (arm A) and 849 patients who received chemotherapy plus trastuzumab (arms B and C). Network and pathway analyses were used to identify key biologic processes linked to RFS. The signature was built by using a voting scheme. Results Network and functional ontology analyses suggested that increased RFS was linked to a subset of immune function genes. A voting scheme model was used to define immune gene enrichment based on the expression of any nine or more of 14 immune function genes at or above the 0.40 quantile for the population. This model was used to identify immune gene–enriched tumors in arm A and arms B and C. Immune gene enrichment was linked to increased RFS in arms B and C (HR, 0.35; 95% CI, 0.22 to 0.55; P < .001), whereas arm B and C patients who did not exhibit immune gene enrichment did not benefit from trastuzumab (HR, 0.89; 95% CI, 0.62 to 1.28; P = .53). Enriched immune function gene expression as defined by our predictive signature was not associated with increased RFS in arm A (HR, 0.90; 95% CI, 0.60 to 1.37; P = .64). Conclusion Increased expression of a subset of immune function genes may provide a means of predicting benefit from adjuvant trastuzumab.

ASPP2 is an important tumor suppressor protein promoting p53‐dependent and‐independent apoptosis. However, it has been unclear how ASPP2 protein is regulated. Here, we identified Itch as the E3 ubiquitin ligase for ASPP2. Itch interacts with ASPP2 and mediates its degradation and ubiquitination in vivo. The PPXY motif of ASPP2 interacts with the WW domains of Itch. Yap1 competes with Itch for binding to ASPP2, and prevents Itch‐mediated degradation and ubiquitination of ASPP2. Together, these observations reveal that Itch and Yap1 have antagonistic roles in the regulation of ASPP2 protein stability through competing post‐translational regulatory mechanism of ASPP2.

The following, from the 12th OESO World Conference: Cancers of the Esophagus, includes commentaries on translational research on Barrett's esophagus that address evidence for genetic instability in esophageal cancer; the role of microsatellite instability; the use of histologic and serum Doublecortin‐like kinase 1 expression for progression of Barrett's esophagus to adenocarcinoma; the oxidative stress in Barrett's tumorigenesis; the genomic alterations in esophageal cancer; in vivo modeling in Barrett's esophagus; epigenetic and transcriptional regulation in Barrett's esophagus and esophageal adenocarcinoma; and normal and disordered regeneration in Barrett's esophagus.

Abstract Background: Genetic and environmental factors influence colorectal cancer (CRC) risk. Previous studies have provided additional etiologic insight by examining multiplicative gene-environment interactions for individual susceptibility loci. However, individual loci confer only modest risks, which may limit statistical power and clinical significance. A genetic risk score comprising known CRC loci may provide a more comprehensive assessment of risk. Further, there is a paucity of data on the role of additive gene-environment interactions, which may have greater public health implications than multiplicative interactions. We thus evaluated both additive and multiplicative interactions between a genetic risk score and 15 key environmental factors on risk of CRC. Methods: We conducted an analysis of 10,491 CRC cases and 10,725 controls of European ancestry in 7 cohort and 6 case-control studies participating in the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO) or Colon Cancer Family Registry (CCFR). To provide a global measure of genetic predisposition, information across multiple risk variants was combined by calculating a genetic risk score based on 24 polymorphisms near 21 genetic loci identified in previous genome-wide association studies. For the genetic score and environmental factors, the reference category corresponded to that associated with lower CRC risk. We tested for additive interactions by estimating relative excess risk due to interactions (RERIs) using logistic regression; for multiplicative interactions we used an empirical-Bayes approach. Nominal P values ≤ 0.05 were considered statistically significant. Results: After adjustment for age, sex, center, study, principal components, and total energy, as appropriate, we observed super-additive gene-environment interactions for CRC risk between the genetic risk score and body mass index (RERI=0.15; 95% CI: 0.00-0.31), ever smoking (RERI=0.14; 95% CI: 0.00-0.28), pack-years of smoking (RERI=0.23; 95% CI: 0.05-0.41), postmenopausal hormone therapy use (RERI=0.38; 95% CI: 0.17-0.59), and intake of processed meat (RERI=0.23; 95% CI: 0.06-0.40). Of the 15 environmental risk factors, 12 showed RERIs &gt; 0 – suggesting an overall trend toward super-additive interactions for these factors. In addition, we observed evidence of sub-multiplicative interactions for use of aspirin and non-steroidal anti-inflammatory drugs. There were no other statistically significant multiplicative interactions. Conclusions: We observed evidence for super-additive effects of genetic predisposition and environmental risk factors on risk of CRC. Our findings suggest that certain environmental risk factors have stronger effects on absolute risk among individuals with higher genetic risk of CRC. If confirmed in future studies, these results may have implications for targeted prevention strategies. Citation Format: Mengmeng Du, Sonja I. Berndt, Hermann Brenner, Bette J. Caan, Peter T. Campbell, Graham Casey, Andrew Chan, Jenny Chang-Claude, Stephen J. Chanock, Nilanjan Chatterjee, David V. Conti, David Duggan, Jane C. Figueiredo, Steven Gallinger, Jian Gong, Robert W. Haile, Tabitha A. Harrison, Richard B. Hayes, Michael Hoffmeister, John L. Hopper, Li Hsu, Thomas J. Hudson, Carolyn M. Hutter, Eric J. Jacobs, Mark A. Jenkins, Shuo Jiao, Laurence N. Kolonel, Peter Kraft, Loic Le Marchand, Mathieu Lemire, Yi Lin, Noralane M. Lindor, Polly A. Newcomb, John D. Potter, Robert E. Schoen, Fredrick R. Schumacher, Daniela Seminara, Martha L. Slattery, Stephen N. Thibodeau, Cornelia M. Ulrich, Aung Ko Win, Emily White, Brent W. Zanke, Ulrike Peters. Additive and multiplicative gene-environment interactions for colorectal cancer risk. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 4831. doi:10.1158/1538-7445.AM2013-4831