Citations

Liver transplantation is a complex procedure performed on critically ill patients with multiple comorbidities, which requires the anesthesiologist to be facile with complex hemodynamics and physiology, vascular access procedures, and advanced monitoring. Over the past decade, there has been a continuing debate whether or not liver transplant anesthesia is a general or specialist practice. Yet, as significant data have come out in support of dedicated liver transplant anesthesia teams, there is not a guarantee of liver transplant exposure in domestic residencies. In addition, there are no standards for what competencies are required for an individual seeking fellowship training in liver transplant anesthesia. Using the Accreditation Council for Graduate Medical Education guidelines for residency training as a model, the Society for the Advancement of Transplant Anesthesia Fellowship Committee in conjunction with the Liver Transplant Anesthesia Fellowship Task Force has developed the first proposed standardized core competencies and milestones for fellowship training in liver transplant anesthesiology.

Goals: We sought to determine the incidence of jackhammer esophagus (JE) after lung transplantation (LT) and identify potential risk factors for the development of JE after LT. Background: JE is a rare esophageal motility disorder, and its pathophysiology remains unclear. Lung transplantation has been implicated as a potential risk factor for JE, but the incidence of JE after LT is unknown. Study: A retrospective cohort of adult patients who underwent LT at 2 tertiary care centers over 7.5 years was reviewed. Analysis was performed on patients who underwent a high-resolution esophageal manometry (EM) study before and after LT. JE was defined according to the latest Chicago classification, version 3.0. Results: A total of 57 patients without JE identified on pre-LT EM also underwent an EM study after LT. Fifteen (25.4%) were found to have new JE after LT. Patients with newly diagnosed JE after LT were older (61.3±5.3 y vs. 51.6±15.6 y; P=0.02) and more often had chronic obstructive pulmonary disease (COPD; 47.6% vs. 16.6%; P=0.03) compared with those without COPD. There was a trend toward increased risk for JE among female individuals (60% vs. 33.3%; P=0.07) and those with shorter surgical anastomosis times (75.8±12.2 min vs. 84.4±14.3; P=0.06). There was no significant difference between body mass index, opioid use, pretransplant EM findings, surgical ischemic time, occurrence of gastroparesis, or measured post-LT outcomes between the 2 groups. Conclusions: JE occurs not uncommonly in patients after LT. Older age and COPD pre-LT may be significant risk factors.

Abstract Background: Immunoprevention via targeting antigens aberrantly expressed on colorectal cancers and adenomatous polyps offers the potential for a less invasive prevention strategy than endoscopic surveillance. Specificity of the immune response and long-term memory provide the potential for prolonged protection. Leveraging the infrastructure of the NCI-funded Cancer Prevention Network (CPN) consortium, we are conducting a double-blind randomized trial in individuals with a diagnosis of advanced colorectal adenomas within the previous year. We are evaluating MUC1 vaccine with the TLR-3 agonist polyICLC as an adjuvant, for its immunogenicity, ability to elicit immune memory and prevent recurrence of colorectal adenomas. Aims: We previously reported on the vaccine immunogenicity at week 12 (vaccine administered at 0, 2, and 10 weeks) compared to placebo. Here we report the ability of the vaccine to elicit long-term memory by measuring increase in anti-MUC1 antibody levels following a booster administered at one year. Methods: Subjects with endoscopically resected advanced adenoma (defined as ≥1cm, tubululovillous or villous histology, or with high grade dysplasia) were randomized. The primary endpoint was the response to the vaccine at week 12 assessed by monitoring anti-MUC1 IgG antibody titer ratio defined as t12/t0, where t0 was the titer pre-vaccination, and t12 was the titer at week 12. The key secondary endpoint was to assess anti-MUC1 IgG response at week 55 to a booster at week 52 in the vaccine arm compared to placebo. Results: 102 eligible subjects were randomized at 6 centers, 52 received MUC1 vaccine and 50 placebo. The mean age was 59.4±7.0 (range 40-70), 60.8% male, 88.2% white, and 18.6% Hispanic or Latino ethnicity. At 12 weeks the IgG ratio was ≥2.0 in 13/52 (25%) of individuals receiving vaccine (ratio range -0.5-17.3), vs. 0/50 in placebo group (2-sided p=.0001), and was ≥1.5 in 19/52 (36.5%) individuals receiving vaccine compared to 1/50 (2%) in placebo group (P<.0001). To evaluate immune memory, 1-year booster data available for 95 patients (51-MUC1, 44-placebo) were analyzed. 10/13 (76.9%) of the week 12 vs. week 0 vaccine responders showed a response at week 52 vs. baseline and 11/13 (84.6%) at week 55 vs. week 52. Using an IgG ratio of 2 (per-protocol), the response rate was 33% for MUC1 vs. 5% for placebo (1-sided p=0.0003). Using a ratio of 1.5 yielded similar results (37% MUC1 vs. 9% Placebo (1-sided p=0.0008). The MUC1 arm had significantly higher IgG at week 52 (1-sided p=0.0294), week 55 (1-sided p=0.0048), and significantly higher week 55 to week 52 IgG ratio values (1-sided p=0.0293). Conclusions: Subjects with a recent history of advanced adenoma receiving a MUC1 vaccine compared with a placebo were significantly more likely to develop an immune response at week 12, confirming the vaccine’s immunogenicity, and to respond again at week 55 to a booster injection on week 52, confirming the vaccine’s ability to elicit immune memory. Follow-up colonoscopy to evaluate the vaccine’s potential to lower adenomatous polyp recurrence rates are in progress. Citation Format: Olivera J. Finn, Lisa Boardman, Marcia Cruz-Correa, Ajay Bansal, David Kastenberg, Chin Hurr, Sharon Kaufman, Colleen Akerley, Lynda Dzubinski, April Felt, Karrie Fursa, L.M. Rodriguez, Ellen Richmond, Asad Umar, Eva Szabo, John McKolanis, Ryan McMurray, Nathan Foster, Andres Salazar, Paul Limburg, Robert Schoen. Randomized, double-blind, placebo-controlled trial of preventative MUC1 vaccine in patients with newly diagnosed advanced adenomas: Results from one-year booster [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr CT236.

Lipid droplet (LD) catabolism in hepatocytes is mediated by a combination of lipolysis and a selective autophagic mechanism called lipophagy, but the relative contributions of these seemingly distinct pathways remain unclear. We find that inhibition of lipolysis, lipophagy, or both resulted in similar overall LD content but dramatic differences in LD morphology. Inhibition of the lipolysis enzyme adipose triglyceride lipase (ATGL) resulted in large cytoplasmic LDs, whereas lysosomal inhibition caused the accumulation of numerous small LDs within the cytoplasm and degradative acidic vesicles. Combined inhibition of ATGL and LAL resulted in large LDs, suggesting that lipolysis targets these LDs upstream of lipophagy. Consistent with this, ATGL was enriched in larger-sized LDs, whereas lipophagic vesicles were restricted to small LDs as revealed by immunofluorescence, electron microscopy, and Western blot of size-separated LDs. These findings provide new evidence indicating a synergistic relationship whereby lipolysis targets larger-sized LDs to produce both size-reduced and nascently synthesized small LDs that are amenable for lipophagic internalization.

Abstract Recent years have seen an explosion in the availability of paired molecular profiling and drug screen data, providing an unprecedented opportunity for the development of targeted therapies based on an individual’s genetic background. Despite a number of recent successes in diseases ranging from cystic fibrosis to cancer, significant hurdles remain in our ability to accurately predict treatments based on molecular profiling data. In particular, few such tools exist that allow the integration of heterogeneous data types (e.g. genomic, transcriptomic, and somatic mutations), along with high-throughput drug screen data to make predictions about treatment efficacy. Here, we describe a generalized open-source pipeline developed for the analysis of precision medicine data, Pharmacogenomics Prediction Pipeline, or “P3”. The modular design of P3 enables the inclusion of arbitrary input data types and the selection from multiple alternative machine learning algorithms, while automated statistical and visualization reporting steps incorporated throughout the pipeline assist in parameter tuning and early detection of problematic data components. Molecular profiling data is further enriched by the incorporation of external biological information in the form of pathway and gene set annotations such and Gene Ontology (GO) and The Molecular Signatures Database (MSigDB). To demonstrate the use of P3 for preclinical biomarker prediction, we applied P3 to an unpublished multiple myeloma dataset consisting of exome, RNA-Seq, CNV, and drug screen data for 1,912 compounds across 47 tumor cell lines. Specifically, P3 was used to predict molecular features associated with response to treatment for all drugs where a differential response to treatment was observed across patients. Furthermore, molecular profiling and drug screen data for 267 drugs and over a thousand cell lines spanning multiple cancer types from the Genomics of Drug Sensitivity in Cancer (GDSC) project were analyzed using P3, providing insights into shared mechanisms of drug sensitivity and resistance across different cancer and treatment types. Citation Format: V Keith Hughitt, Sayeh Gorjifard, Aleksandra M. Michalowski, John K. Simmons, Ryan Dale, Eric C. Polley, Jonathan J. Keats, Beverly A. Mock. A flexible pipeline for precision medicine biomarker detection and prediction of treatment response [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 5113.

Abstract INTRODUCTION Participating in a clinical trial is a personal choice and an individual experience. Several barriers to recruitment of high risk men and women in chemoprevention trials have been documented; however, to our knowledge, there are no existing reports on participant satisfaction in such trials. Therefore, our aim was to describe and evaluate participants’ perception of their experience with participating in chemoprevention trials conducted by CPN by summarizing the 5-item “Was It Worth It” (WIWI) tool for each trial and across the trials, and according to race/ethnicity, sex, age, site, and organ of primary interest. METHODS Because participants who participate in chemoprevention trials tend to be at increased cancer-risk, but otherwise healthy, the WIWI tool can help answer simple questions about participants’ assessment of whether or not participation in such a trial was worthwhile. The WIWI tool was consistently administered at the end of the intervention period in each trial conducted by CPN; since 2003, 7 trials have completed the study intervention period and are included in the results reported here. RESULTS The scientific focus of the 7 trials targeted 5 organs: breast, colorectum, esophageal, hepatobiliary, and lung. Of the 485 participants registered to these 7 trials, 419 (86.4%) were non-Hispanic white, 19 (3.9%) non-Hispanic black, 32 (6.6%) Hispanic, 14 (2.9%) other race/ethnicity, and 1 (0.2%) unknown race/ethnicity; there were 120 (24.7%) females. In total, 446 (92.0%) participants completed the WIWI questionnaire at the end of their respective intervention period. Across the trials, 93% [95% CI] [90.6%, 95.4%] of the participants indicated that participation was worthwhile and 92% [89.5%, 94.5%] reported that they would participate again. Additionally, 414 (92.8%) participants indicated that they would recommend participating in the current research study to others, while 10 (2.3%) indicated that they would not and 22 (4.9%) were uncertain. Furthermore, several participants provided actionable feedback to the question “If there was one thing that could have been done to improve your experience in this research study, what would it be?” Participant feedback on overall changes in quality of life and on their expectations with participation in the trial was positive but more nuanced, varying according to trial and participant composition. CONCLUSION In this dataset of chemoprevention trial participants enrolled through the CPN consortium, highly favorable feedback was evident with respect to the overall study experience, suggesting that the recruitment and retention methods employed are facilitating success. These data can be used to help advance the NCI accrual quality improvement program in developing/enhancing strategies to improve accrual, retention, and adherence as well as enhance participant diversity in subsequent trials. Citation Format: David Zahrieh, Ryan P. McMurray, Nathan R. Foster, Paul J. Limburg, Sumithra J. Mandrekar. Participant satisfaction with cancer chemoprevention clinical trials: The Mayo Clinic Cancer Prevention Network (CPN) experience [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 5092.

Abstract Identifying risk factors for women at high risk of symptom-detected breast cancers that were missed by screening would enable targeting of alternative prevention strategies. To identify breast cancer risk factors by mode of detection, we examined these associations in heavily-screened women from the Cancer Prevention Study (CPS)-II Nutrition Cohort. Among 76,406 women followed for a median of 13.8 years, 2,469 screen-detected and 1,189 symptom-detected breast cancer cases were diagnosed. Multivariable-adjusted associations were estimated using joint Cox proportional hazards regression models with person-time calculated contingent on screening. The mean (standard deviation) age at baseline was 62.0 (6.6) years for non-cases, 61.6 (6.1) for screen-detected cases, and 61.5 (6.2) for symptom-detected cases. Women with symptom-detected tumors were diagnosed at a slightly younger age (mean=69.4) and less likely to be diagnosed with a localized tumor (65.3%), than women with a screen-detected tumor (mean age at diagnosis=70.4 and localized tumors=83.3%). Factors associated with higher risks of symptom detected vs. screen detected breast cancer, included: current combined menopausal hormone use (HR=2.04, 95% CI 1.70 - 2.46 vs. HR=1.43, 95% CI 1.25 - 1.63), current estrogen only menopausal hormone use (HR=1.41, 95% CI 1.15 - 1.72 vs. HR=0.94, 95% CI 0.82 - 1.09), and history of benign breast disease (HR=1.89, 95% CI 1.67 - 2.13 vs. HR=1.49, 95% CI 1.36 - 1.62). The opposite pattern of higher risk of screen detected vs. symptom detected breast cancer was observed for greater adult weight gain (HR=2.32, 95% CI 1.91 - 2.82 vs. HR=1.42, 95% CI 1.10 - 1.84) and alcohol intake (HR=1.39, 95% CI 1.24 - 1.64 vs. HR=1.20, 95% CI 0.92 - 1.58). Our results suggest that understanding risk factors for symptom-detected cancers may help identify women who would benefit from more intensive screening to facilitate early detection. Citation Format: Mia M. Gaudet, Emily Deubler, W. Ryan Diver, Samantha Puvanesarajah, Alpa V. Patel, Ted Gansler, Dana Flanders, Mark Sherman, Susan Gapstur. Breast cancer risk factors by mode of detection among screened women in the Cancer Prevention Study-II [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4211.

Abstract BACKGROUND: Approximately 5% of gliomas occur in individuals with a family history of glioma, and first-degree relatives of brain tumor cases have a two-fold increase in risk of brain tumor. Recent somatic characterization has shown that tumors from familial cases are indistinguishable from sporadic cases, suggesting that familial cases may arise through similar mechanisms of gliomagenesis, and therefore may be associated with common variants as well as rare mutations. In this analysis, we assessed whether previously identified common risk variants are associated with familial glioma. METHODS: Data were obtained from the Glioma International Case Control (GICC) and Gliogene studies for 448 cases with reported family history, 4,405 cases without reported family history, and 3,288 controls. We assessed 25 risk loci previously identified by glioma GWAS, and odds ratios (OR) and 95% confidence intervals (95%CI) were calculated using an additive genetic logistic regression model adjusted for age, sex, and the first two principal components for familial cases versus unaffected controls, and non-familial cases versus controls. Results were considered significant at p<0.002 (Bonferroni correction for 25 tests). RESULTS: Significant associations were detected at 5/25 loci, including TERT, EGFR, CCDC26, CDKN2B, and RTEL1. The strongest association was at rs55705857 (CCDC26, OR=2.7, p=7.49x10-17). For GBM (222 familial cases), significant associations were detected at 6/26 loci (TERT, EGFR, CDKN2B, TP53 and RTEL1), while in non-GBM (205 familial cases) significant associations were detected at 3/25 loci (LRIG1, CCDC26, PHLDB1). These SNPs were further examined using a case-only approach comparing familial to non-familial cases, and there was no significant difference in allele frequencies by family history status. There was a strong correlation between log(OR) for familial cases only versus non-familial cases (adjusted R2=0.88). CONCLUSIONS: In this analysis we identified a significant association between familial glioma and five common risk loci previously identified by glioma GWAS. This provides further evidence of shared pathways of genetic risk and gliomagenesis between familial and non-familial glioma. Further exploration is necessary to determine the overall contribution of common genetic variation to risk of familial glioma. Citation Format: Quinn T. Ostrom, Georgina Armstrong, Christopher I. Amos, Jonine L. Bernstein, Elizabeth B. Claus, Jeanette E. Eckel-Passow, Dora Il'yasova, Christoffer Johansen, Daniel H. Lachance, Rose K. Lai, Ryan T. Merrell, Sara H. Olson, Joellen H. Schildkraut, Sanjay S. Shete, Richard S. Houlston, Robert B. Jenkins, Margaret R. Wrensch, Beatrice Melin, Jill S. Barnholtz-Sloan, Melissa L. Bondy. Previously identified common glioma risk SNPs are associated with familial glioma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4173.