Citations

Abstract Several papers have implicated mutations in the AT-rich interactive domain containing protein 1B (ARID1B) in carcinoma formation in multiple tissue types, including the lung. The ARID1B protein functions as part of SWI/SNF, a multi-subunit chromatin remodeling complex that repositions nucleosomes and may act as a tumor suppressor in cancer. ARID1B is located in a region in 6q that was previously shown to have strong evidence of linkage with lung cancer risk. As it is one of the more promising candidates within the target region, this study presents the viability of ARID1B as a candidate gene for familial lung cancer. Here, we chose individuals from families in our previous linkage study that showed the strongest linkage signal on 6q. 75 individuals from 9 families were sequenced for 37Mb of chromosome 6 from 130Mb to 167Mb using Illumina technology and a custom Agilent kit. Genotypes were imported into GoldenHelix SVS 7 for quality control and dropped if read depth < 10, quality score < 10 or a quality score to read depth ratio < 0.5. Variants with more than 1 Mendelian error were dropped. Variants with a single Mendelian inconsistency were dropped only for that family. Two-point parametric linkage analysis at theta = 0 was performed using R and an implementation of the Elston-Stewart algorithm in the paramlink package using a penetrance model of 0.01/0.1/0.1 (dd/Dd/DD) and a disease allele (D) frequency of 0.01. Family 102 showed strong evidence for linkage near ARID1B. The highest LOD score (1.34) out of all sequenced variants was located near this gene in a known conserved intergenic region between ARID1B and NOX3. Four other LOD scores > 0.7 were found in the intergenic region between these two genes. Two are transcription factor binding sites; two are conserved genomic elements. We also observed two linked intronic variants of ARID1B in this family; an enhancer (LOD = 0.89) and a transcribed region (LOD = 0.73). Two other families (47 and 59) displayed evidence of linkage in ARID1B. Here, the interest is not the value of the LOD scores (top scores were 0.64 and 0.54), but the centering of the linked haplotype around the gene. Family 47 has 60 variants with LODs between 0.64 and 0.61; 45 located within ARID1B or known regulatory regions. Family 59 has 61 variants with LODs between 0.54 and 0.51; 29 located within ARID1B or known regulatory regions The variants appear to be spread evenly throughout ARID1B, suggesting the presence of linked haplotypes. Analyses are currently underway to reconstruct possible haplotypes in these families. The results of this study show that variants in the ARID1B gene at least partially account for the linkage signal on 6q in three of the nine most strongly linked families in our cohort and thus we believe that ARID1B is a plausible candidate gene for further studies involving familial lung cancer. Replication studies using 27 new extended families are currently underway to confirm this initial result. Citation Format: Anthony M. Musolf, Claire L. Simpson, Mariza de Andrade, Diptasri Mandal, Colette Gaba, Ping Yang, Ming You, Elena Y. Kupert, Marshall W. Anderson, Ann G. Schwartz, Susan M. Pinney, Christopher I. Amos, Joan E. Bailey-Wilson. Chromatin remodeling gene ARID1B is linked to familial lung cancer. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2542.

ABSTRACTRare variants (RVs) have been shown to be significant contributors to complex disease risk. By definition, these variants have very low minor allele frequencies and traditional single‐marker methods for statistical analysis are underpowered for typical sequencing study sample sizes. Multimarker burden‐type approaches attempt to identify aggregation of RVs across case‐control status by analyzing relatively small partitions of the genome, such as genes. However, it is generally the case that the aggregative measure would be a mixture of causal and neutral variants, and these omnibus tests do not directly provide any indication of which RVs may be driving a given association. Recently, Bayesian variable selection approaches have been proposed to identify RV associations from a large set of RVs under consideration. Although these approaches have been shown to be powerful at detecting associations at the RV level, there are often computational limitations on the total quantity of RVs under consideration and compromises are necessary for large‐scale application. Here, we propose a computationally efficient alternative formulation of this method using a probit regression approach specifically capable of simultaneously analyzing hundreds to thousands of RVs. We evaluate our approach to detect causal variation on simulated data and examine sensitivity and specificity in instances of high RV dimensionality as well as apply it to pathway‐level RV analysis results from a prostate cancer (PC) risk case‐control sequencing study. Finally, we discuss potential extensions and future directions of this work.

Background: We aim to provide data on a diabetes technology simulation course (DTSC) that instructs internal medicine residents in the use of continuous subcutaneous insulin infusion (CSII) and continuous glucose monitoring system (CGMS) devices. Methods: The DTSC was implemented during calendar year 2012 and conducted in the institution's simulation center. It consisted of a set of prerequisites, a practicum, and completion of a web-based inpatient CSII-ordering simulation. DTSC participants included only those residents in the outpatient endocrinology rotation. Questionnaires were used to determine whether course objectives were met and to assess the satisfaction of residents with the course. Questionnaires were also administered before and after the endocrine rotation to gauge improvement in familiarity with CSII and CGMS technologies. Results: During the first year, 12 of 12 residents in the outpatient endocrinology rotation completed the DTSC. Residents reported that the course objectives were fully met. The mean satisfaction score with the course ranged from 4.0 to 4.9 (maximum, 5), with most variables rated above 4.5. Self-reported familiarity with the operation of CSII and CGMS devices increased significantly in the postrotation survey compared with that on the prerotation survey (both p < .01). Conclusions: In this pilot program, simulation-based education increased the perceived familiarity of residents with CSII and CGMS technologies. In light of these preliminary findings, the course will continue to be offered, with further data accrual. Future work will involve piloting the DTSC approach among other types of providers, such as residents in other specialties or inpatient nursing staff.

Abstract African American Hereditary Prostate Cancer Study (AAHPC) was developed as a national collaboration to explore the role of genetics in the causation of hereditary prostate cancer (HPC) in African American (AA) men. AAHPC is in partnership with the International Consortium for Prostate Cancer Genetics (ICPCG), which conducts collaborative studies of HPC genetics in multiplex families. As part of an ICPCG sequencing study of 539 affected individuals from 366 HPC pedigrees, we performed whole exome sequencing in 21 ICPCG AA families, of which there were 14 AAHPC affected men from 11 pedigrees. The combined ICPCG AA cohort consisted of N=26 affected members. Post-variant calling quality control (QC) was implemented using Golden Helix SVS 8 software with filters set for removal of variants with Read Depth &lt; 10, Quality Score &lt; 20, Quality Score: Read Depth Ratio &lt; 0.5, Call Rate &lt; 0.75. Variants were additionally filtered by MAF based on the NHLBI ESP650051-V2 exomes variant frequencies for the AA population using a MAF threshold of 5%. Following QC, 176/299 SNVs and 20/39 INDELs remained for further analysis. In these analyses, we focused on 13 known cancer genes (MSR1, AR, BRCA1, BRCA2, BTNL2, EPHB2, CDH1, RNASEL, ELAC2, HOXB13, CHEK2, TP53 and NBN). Three sequenced families had &gt; 1 affected members sequenced (2 or 3 per family) and the remaining 18 families had one member sequenced. Under the dominant model, our preliminary results show that no rare variants in the 13 candidate genes were found in 3/3 affecteds in two families. Rare SNVs in seven candidate genes (AR, CDH1, ELAC2, HOXB13, RNASEL, BRCA2 and EPHB2) were found in 2/3 affecteds for two families and 2/2 affecteds in one family. Several of the remaining 18 affected men (1 sequenced per pedigree) shared the same rare SNV in these candidate genes. For INDELs, rare variants in three candidate genes were found in pedigrees with ≥ 2 affecteds. Several of the remaining 18 affected men (one sequenced per pedigree) shared the same rare INDEL. Additional QC is underway to validate these variants and bioinformatic analyses are being used to predict effects of the variants in an effort to unravel the complex genetic heterogeneity of HPC in AA. Citation Format: Cheryl D. Cropp, Shannon K. McDonnell, Sumit Middha, Melissa DeRycke, Danielle M. Karyadi, Daniel Schaid, Stephen N. Thibodeau, William B. Isaacs, Elaine A. Ostrander, Janet Stanford, Kathleen A. Cooney, Joan E. Bailey-Wilson, John D. Carpten. Rare variant discovery in known cancer genes from whole-exome sequencingof African American hereditary prostate cancer families. [abstract]. In: Proceedings of the Eighth AACR Conference on The Science of Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; Nov 13-16, 2015; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2016;25(3 Suppl):Abstract nr B40.

OBJECTIVE Improvement in treatment outcome for patients with glioblastoma multiforme (GBM) requires a multifaceted approach due to dysregulation of numerous signaling pathways. The murine double minute 2 (MDM2) protein may fulfill this requirement because it is involved in the regulation of growth, survival, and invasion. The objective of this study was to investigate the impact of modulating MDM2 function in combination with front-line temozolomide (TMZ) therapy in GBM. METHODS The combination of TMZ with the MDM2 protein–protein interaction inhibitor nutlin3a was evaluated for effects on cell growth, p53 pathway activation, expression of DNA repair proteins, and invasive properties. In vivo efficacy was assessed in xenograft models of human GBM. RESULTS In combination, TMZ/nutlin3a was additive to synergistic in decreasing growth of wild-type p53 GBM cells. Pharmacodynamic studies demonstrated that inhibition of cell growth following exposure to TMZ/nutlin3a correlated with: 1) activation of the p53 pathway, 2) downregulation of DNA repair proteins, 3) persistence of DNA damage, and 4) decreased invasion. Pharmacokinetic studies indicated that nutlin3a was detected in human intracranial tumor xenografts. To assess therapeutic potential, efficacy studies were conducted in a xenograft model of intracranial GBM by using GBM cells derived from a recurrent wild-type p53 GBM that is highly TMZ resistant (GBM10). Three 5-day cycles of TMZ/nutlin3a resulted in a significant increase in the survival of mice with GBM10 intracranial tumors compared with single-agent therapy. CONCLUSIONS Modulation of MDM2/p53-associated signaling pathways is a novel approach for decreasing TMZ resistance in GBM. To the authors' knowledge, this is the first study in a humanized intracranial patient-derived xenograft model to demonstrate the efficacy of combining front-line TMZ therapy and an inhibitor of MDM2 protein–protein interactions.