Neutrophil extracellular traps linked to idiopathic pulmonary fibrosis severity and survival

Background

Idiopathic pulmonary fibrosis (IPF) leads to progressive loss of lung function and mortality. Understanding mechanisms and markers of lung injury in IPF is paramount to improving outcomes for these patients. Despite the lack of systemic involvement in IPF, many analyses focus on identifying circulating prognostic markers. Using a proteomic discovery method followed by ELISA validation in multiple IPF lung compartments and cohorts we explored novel markers of IPF survival.

Methods

In our discovery analysis, agnostic label-free quantitative proteomics differentiated lung tissue protein expression based on survival trajectory (n=10). Following selection of the candidate pathway (neutrophil extracellular trap (NET) formation), we subsequently validated the presence of NETs in the IPF lung microenvironment using fully quantitative assays of known NET remnants in separate IPF cohorts (n=156 and n=52) with bronchoalveolar lavage fluid. We then assessed the correlation of these markers with baseline pulmonary function and survival.

Results

Discovery lung tissue proteomics identified NET formation as significantly associated with poor IPF survival. Using fully quantitative confirmatory tests for reproducibility we confirmed the presence of NET markers in IPF BALF and found significant correlations with worse pulmonary function in both cohorts (p<0.03 and p = 0.04 respectively). In the survival cohort, higher levels of NET markers predicted worse survival after adjusting for gender, age, and baseline physiologic severity (hazard ratio range: 1.79-2.19).

Conclusions

NET markers were associated with disease severity and worse survival in IPF. These findings suggest NET formation contributes to lung injury and decreased survival in IPF and may represent a potential therapeutic target.

MicroRNA Content of Ewing Sarcoma Derived Extracellular Vesicles Leads to Biomarker Potential and Identification of a Previously Undocumented EWS-FLI1 Translocation

Objective: Ewing Sarcoma Family of Tumors (ESFT) are a highly aggressive pediatric bone and soft tissue malignancy with poor outcomes in the refractory and recurrent setting. Over 90% of Ewing Sarcoma (ES) tumors are driven by the pathognomonic EWS-ETS chimeric transcripts and their corresponding oncoproteins. It has been suggested that the EWS-ETS oncogenic action can mediate microRNA (miRNA) processing. Importantly, small extracellular vesicles (sEVs), including those frequently referred to as exosomes have been shown to be highly enriched with tumor-derived small RNAs such as miRNAs. We hypothesized that ESFT-specific sEVs are enriched with certain miRNAs which could be utilized toward an exo-miRNA biomarker signature specific to this disease. Methods: We performed miRNAseq to compare both the exo-derived and cell-derived miRNA content from 8 ESFT, 2 osteosarcoma, 2 non-cancerous cell lines, and pediatric plasma samples. Results: We found that sEVs derived from ESFT cells contained nearly 2-fold more number of unique individual miRNAs as compared to non-ESFT samples. Quantitative analysis of the differential enrichment of sEV miRNAs resulted in the identification of 62 sEV-miRNAs (exo-miRNAs) with significant (P < .05) enrichment variation between ESFT and non-ESFT sEV samples. To determine if we could utilize this miRNA signature to diagnose ESFT patients via a liquid biopsy, we analyzed the RNA content of total circulating sEVs isolated from 500 µL plasma from 5 pediatric ESFT patients, 2 pediatric osteosarcoma patients, 2 pediatric rhabdomyosarcoma patients, and 4 non-cancer pediatric controls. Pearson’s clustering of 60 of the 62 candidate exo-miRNAs correctly identified 80% (4 of 5) of pathology confirmed ESFT patients. Importantly, RNAseq analysis of tumor tissue from the 1 outlier, revealed a previously uncharacterized EWS-FLI1 translocation.Conclusions: Taken together, these findings support the development and validation of an exo-miRNA-based liquid biopsy to aid in the diagnosis and monitoring of ESFT.

Antifungal drug price increases in the United States, 2000-2019

BACKGROUND

Antifungal drugs treat a variety of conditions, ranging from localised dermatologic disease to life-threatening systemic infections. Some common antifungal drugs experienced large price increases in recent years, however, factors contributing to these price increases are poorly understood. We sought to examine trends in antifungal drug prices and determine underlying drivers of price changes.

METHODS

Antifungal drug products in the United States were identified using the Food and Drug Administration (FDA) Label database. For each product, we determined the wholesale acquisition cost per unit over time between 2000 and 2019, adjusting for inflation, and examined variables that could impact price: route of administration, number of FDA indications, the quantity of professional guideline recommendations, use for prophylaxis, number of FDA-approved manufacturers, and whether it was compounded. Price trajectories were clustered into four groups: (1) stable, 2) moderate, (3) high, and (4) extreme price increases.

RESULTS

Of 139 identified drug products, one outlier was removed due to exorbitant price increases. Cluster 1 (n = 31) demonstrated the most stable prices with a 25% mean price increase. Clusters 2 (n = 97), 3 (n = 7), and 4 (n = 3) demonstrated moderate, high, and extreme price increases with 52%, 318%, and 900% mean price increases, respectively. Atypical routes of administration and compounding were over-represented in clusters 3 and 4. There was no correlation between the number of manufacturers and price changes.

CONCLUSIONS

Antifungal drugs exhibited large, inflation-adjusted price increases. Atypical routes of administration and compounding were over-represented within clusters exhibiting extraordinary price increases. Our data support policies aiming to curb large price increases for medically important drugs.

Patients with type 2 diabetes and elevated fibrosis-4 are under-referred to hepatology and have unrecognized hepatic decompensation

BACKGROUND AND AIM

The American Association for the Study of Liver Diseases recommends a high index of suspicion for nonalcoholic steatohepatitis and advanced fibrosis in patients with type 2 diabetes (T2D) and an elevated fibrosis-4 index (FIB-4). We investigated the referral pattern of patients with T2D and FIB4 > 3.25 to the hepatology clinic and evaluated the clinical benefits to the patient.

METHODS

We included patients aged 18-80 years with T2D and a FIB4 score >3.25 who had visited the internal medicine, family medicine, endocrinology clinic from 01/01/2014-5/31/2019. The first time point of high-risk FIB-4 was identified as the baseline for time-to-event analysis. The patients were classified based on whether they had visited the hepatology clinic (referred vs not referred).

RESULTS

Of the 2174 patients, 290 (13.3%) were referred to the hepatology clinic, and 1884 (86.7%) were not referred. In multivariate analyses, the referred patients had a lower overall mortality risk (Hazard Ratio: 0.57; 95% CI: 0.38-87). Notably, the referred patients had the same rate of biochemical decompensation, as measured by progression to MELD ≥ 14, but a substantially higher rate of diagnosis in cirrhosis (27, 19-38) and cirrhosis complications, including ascites (2.9, 2.0-4.1), hepatic encephalopathy (99, 13-742), and liver cancer (14, 5-38).

CONCLUSIONS

We found that patients with T2D and high-risk FIB4 are associated with better overall survival after referral to a hepatology clinic. We speculate that the survival difference is due to the increased recognition of cirrhosis and cirrhosis complications in the referred populations.

Maternal Pre-pregnancy BMI Associates With Sex-Specific Placental microRNA Patterns

Objectives

Maternal obesity is communicated to the fetus through the placenta. Mouse studies have shown sex-specific responses to maternal obesity in both the placenta and offspring. Epigenetic mechanisms, like microRNAs, may mediate these changes, as they can modulate gene expression in response to environmental stimulus. Here we test the hypothesis that sex-specific responses to maternal pre-pregnancy BMI (ppBMI) are evident in placental microRNA abundances.

Methods

We used small-RNA sequencing to assay placental microRNAs from the New Hampshire Birth Cohort Study (NHBCS, n = 281) and the Rhode Island Child Health Study (RICHS, n = 187). MicroRNAs previously associated with ppBMI were regressed on the product of ppBMI and infant sex using negative binomial generalized linear models. Cohort-level results were combined using fixed effects meta-analysis.

Results

We found evidence of five microRNAs with sex-specific ppBMI associations (FDR < 0.05) in NHBCS and three microRNAs with consistent interaction effects across both cohorts (meta-analysis p-value < 0.05). In both cohorts, miR-9903, miR-122–5p and miR-548x-3p were downregulated in males, relative to females (51% in NHBCS and RICHS), with ppBMI. mRNA targets of miR-9903 are enriched among pathways related to glucose transport. Both miR-122–5p and miR-548x-3p are predicted to target estrogen receptor 1 transcript (esr1).

Conclusions

This study reveals that placental microRNAs are susceptible to maternal ppBMI, in an infant sex-specific manner. Our results support previous findings in mice and suggest that placental microRNAs may mediate the differential abundance of esr1 in male and female placentae.

Funding Sources

NIEHS (R24ES028507, R01ES025145, P30ES019776), NIMHD R01MD011698 and NICHD 1K99HD104991-01.

Human cytomegalovirus alters immune cell profile with potential implications for patient survival in head and neck cancer

Cytomegalovirus (CMV) is a highly prevalent human herpes virus that exerts a strong influence on immune repertoire which may influence cancer risk. We have tested whether CMV immunoglobulin G (IgG) serostatus is associated with immune cell proportions (n = 132 population controls), human papillomavirus (HPV) co-infection and head and neck cancer risk (n = 184 cancer cases and 188 controls) and patient survival. CMV status was not associated with the proportion of Natural Killer cells, B cells or the neutrophil-to-lymphocyte ratio. However, CD8+ T cells increased with increasing categories of IgG titers (P =1.7 × 10-10), and titers were inversely associated with the CD4:CD8 ratio (P = 5.6 × 10-5). Despite these differences in T cell proportions, CMV was not associated with HPV16 co-infection. CMV seropositivity was similar in cases (52%) and controls (47%) and was not associated with patient survival (hazard ratio [HR] 1.14, 95% confidence interval [CI]: 0.70 to 1.86). However, those patients with the highest titers had the worst survival (HR 1.91, 95% CI: 1.13 to 3.23). Tumor-based data from The Cancer Genome Atlas demonstrated that the presence of CMV transcripts was associated with worse patient survival (HR 1.79, 95% CI: 0.96 to 2.78). These findings confirm that a history of CMV infection alters T cell proportions, but this does not translate to HPV16 co-infection or head and neck cancer risk. Our data suggest that high titers and active CMV virus in the tumor environment may confer worse survival.

BIOM-43. CROSS-PLATFORM ROBUSTNESS IN THE GLUCOCORTICOID RESPONSE PHARMACODYNAMIC BIOMARKER

The neutrophil dexamethasone methylation index (NDMI) is an algorithm-based biomarker to assess individuals’ exposures to dexamethasone, a synthetic glucocorticoid commonly administered for inflammation. Cortisol is the main endogenous glucocorticoid that controls vital processes including the immune response and lipid and carbohydrate metabolism. Variations in the NDMI score reflect individuals’ sensitivities of exposures to both exogenous and endogenous glucocorticoids, and this biomarker was trained using elastic net regression on Illumina’s most recent DNA methylation beadarray, the EPIC array, which contains 850,000 cytosine-guanine (CpG) sites. While technology for microarray research continues to advance over time, researchers are capable of conducting more comprehensive epigenome-wide association studies (EWAS). However, many studies are still run and archived using Illumina’s historical 450K platform with approximately 450,000 CpGs, and there are fewer published databases using the 850K EPIC array. To evaluate the cross-platform bioinformatic comparability, we performed elastic net regression modeling using predictors available in the 450K to train the NDMI. Among the 135 pre-surgery glioma cases from the UCSF Immune Profiles Study (IPS), NDMI scores between the 450K and 850K model were strongly correlated (r = 0.99, p &lt; 0.0001). In the 311 controls from the UCSF Adult Glioma Study (AGS), similar correlations were observed (r = 0.96, p &lt; 0.0001). We observe that NDMI remains a robust tool using historical 450K data and conclude that this algorithmic tool is capable of detecting the variations in individuals’ responses to dexamethasone.

Abstract LB086: Methylation-derived neutrophil-to-lymphocyte ratio and lung cancer risk and survival

The neutrophil-to-lymphocyte ratio (NLR) is a biomarker of systemic inflammation and can be estimated using DNA methylation data as methylation-derived NLR (mdNLR). We examined associations between mdNLR and lung cancer risk in a nested case-control study, and among the cases, lung cancer survival, using pre-diagnostic blood samples of cases (median of 14 years before diagnosis) and controls in the CLUE I/II cohorts. The final analytic dataset included 208 pairs of lung cancer cases and controls matched on age, sex, and smoking intensity. We computed the mdNLR for each sample based on immune cell-proportion estimates obtained using established reference-based deconvolution methods. Using conditional logistic regression (to take into account matching factors), and further adjusting for BMI, batch effects, and a smoking-based methylation score, we observed a 47% increased risk of non-small cell lung cancer (NSCLC) for one standard deviation increase in mdNLR (n = 150 pairs; OR: 1.47 [1.08, 2.02]). To estimate association between mdNLR and lung cancer survival, we used Cox proportional-hazards models, adjusting age, sex, smoking status, smoking methylation score, BMI, batch effect, and stage. We observed a 27% increased risk of dying from lung cancer for one standard deviation increase in mdNLR (n = 145 deaths in 205 cases; HR: 1.27 [1.08, 1.50]). A 50% increased risk of dying from lung cancer for one standard deviation increase in mdNLR was observed for NSCLC cases (n = 103 deaths in 149 cases; HR: 1.50 [1.19, 1.89]). A better understanding of inflammation-associated biomarkers in lung cancer development could provide insight into critical pathways that may help identify new markers of early disease and survival.

Citation Format: Naisi Zhao, Mengyuan Ruan, Devin Koestler, Jiayun Lu, Carmen Marsit, Karl Kelsey, Elizabeth Platz, Dominique S. Michaud. Methylation-derived neutrophil-to-lymphocyte ratio and lung cancer risk and survival [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr LB086.

BIOM-13. DNA METHYLATION MARKS GLUCOCORTICOID PATHWAY RESPONSE IN DEXAMETHASONE-TREATED BRAIN TUMOR PATIENTS

Dexamethasone (DEX) is routinely prescribed in brain tumor patients to limit vasogenic edema but may also exacerbate immunosuppression and adversely affect survival. The wide spectrum of dosing and individual variation in glucocorticoid (GC) response makes it difficult to assess the impact of DEX exposures. A potential marker of steroid pathway activation and GC load affecting the immune system are induced changes in chromatin structure marked by DNA methylation. We identified DEX-responsive DNA methylation sites in blood leukocytes from glioma patients treated with the drug at various doses and times during the course of their disease. Using weighted co-methylation network analysis, we show that DEX-induced hypomethylation includes well-known regulators of GC receptor (GR) sensitivity (e.g., FK506 binding protein 51: FKBP5) and inflammation (e.g., myeloperoxidase: MPO) and is enriched at genomic locations containing glucocorticoid receptor (GR) binding sites. Elastic net regression modeling was used to train a multilocus GC methylation index (GCMI) that discriminates current DEX users and non-users. GCMI scores showed wide interindividual variation among cases and DEX naïve control subjects. Using independent samples of DEX naïve and exposed glioma patients we show that the GCMI is a sensitive and specific indicator of DEX exposure. GCMI measured in non-glioma controls indicated sensitivity to non-DEX steroid treatments (e.g. prednisolone, fluticasone). Subjects with elevated neutrophil and decreased lymphocyte counts demonstrated high GCMI scores, reflecting the clinically relevant in vivo impact of this marker. Among 195 IDH wildtype and hTERT non-mutant glioma subjects, the GCMI was associated with a HR of 1.11 (95% CI 1.06–1.17) p&lt; 0.0001 in Cox survival models that included age and tumor grade. We conclude that epigenetic remodeling in the peripheral immune compartment in response to DEX exposures is a rich source of potentially powerful markers of individual response to GC pathway activation and associated alterations in the immune response.

EPCO-25. AN IMMUNOMETHYLOMIC PLATFORM INTEGRATING SYSTEMIC IMMUNE PROFILES AND EPIGENETIC AGE IN NEURO-ONCOLOGY

Lineage-specific DNA methylation marks differentiate leukocyte cell types while individual biological aging mechanisms impact other methylation alterations. Human glioma incidence and survival times have been shown to be associated with aberrant immune profiles and have a strong dependency on age. Here we developed a single epigenetic analysis framework to evaluate both immune cell fractions and epigenetic age in peripheral blood. We examined these measures in archived blood from 197 triple-negative glioma patients (TNG; IDH wildtype, 1p19q intact and TERT wildtype) and 312 frequency-matched controls from the SF Bay Area Adult Glioma Study (AGS). Significant differences were observed with TNG cases having lower CD4 and CD8 T cell, natural killer, and B cell fractions, and higher neutrophil fractions than controls. TNG cases were significantly older than controls in two of three epigenetic age estimates; however, there was no difference in epigenetic age acceleration once immune cell proportions were considered. For the TNG cases, we augmented results from several machine learning methods to delineate risk groups of TNG patients with significantly different overall survival. We compared survival models built by recursive partitioning, random forest, and elastic net methods. The final model was chosen by repeated bootstrap sampling via the Brier score loss function and validated in an independent set of 72 IDH-mutant only or TERT-mutant only glioma patients also from the AGS. The final model indicated important interactions between immune cell fractions (including CD4 and CD8 T cells and neutrophils) and treatment, age, and dexamethasone status when adjusted for the main effects of epigenetic age, glioblastoma status, and the neutrophil-to-lymphocyte ratio. The capacity of immunomethylomics to capture diverse, clinically relevant information and the simplicity of its implementation make this a powerful tool for personalized patient evaluation in the neuro-oncology clinic.

Utilization of Technology to Improve Efficiency in Investigational Drug Management Processes

Background: Background: An investigational pharmacy is responsible for all tasks related to receiving, storing, and dispensing of any investigational drugs. Traditional methods of inventory and protocol tracking on paper binders are very tedious and could be error-prone. Objective: To evaluate the utilization of the IDS to efficiently manage the inventory within an investigational Pharmacy. We hypothesize that the IDS will reduce the drug processing time. Methods: Our pharmacy tracked the drug processing time before and after using the IDS including the receiving, dispensing, and inventory. As part of the receiving the study drug pharmacists tracked the time it took a pharmacist to complete the tasks of logging the study drug before and after the implementation of the IDS system. In addition, the pharmacy also timed the process for drug dispensing and a full investigational drug inventory check. Wilcoxon signed-rank test was used to compare the difference in the meantime of total processing before and after the IDS. Results: Utilization of the IDS system showed significant reduction in processing time, and improvement of efficiency in inventory management. Additionally, the usability survey of the IDS demonstrated that the IDS system helped pharmacists capture data consistently across every clinical trial. Conclusion: Our results demonstrates how technology helps pharmacists to focus on their actual day to day medication-related tasks rather than worrying about other operational aspects. Informatics team continues to further enhance the features such as monitor portal, and features related to finance - generation of invoices, billing reconciliation, etc.

Abstract 3300: Pre-diagnosis neutrophil-to-lymphocyte ratio and lung cancer mortality

The neutrophil-to-lymphocyte ratio (NLR) is a marker of systemic inflammation that has been reported to be associated with smoking status as well as survival outcomes from chronic diseases including lung cancer. Most prior studies have examined NLR measured in blood collected at diagnosis, which may therefore reflect disease-related inflammation. Although blood cell type counts, and therefore NLR, cannot be quantified in stored samples, algorithms have been developed to estimate blood cell type counts based on lineage-specific DNA methylation patterns across the genome as methylation-derived NLR (mdNLR). We hypothesize that the inflammatory profile reflected by pre-diagnosis mdNLR may be associated with lung cancer mortality. To test this hypothesis, we examined mdNLR and lung cancer-specific mortality, overall and by histotype, among 293 cases from the Beta Carotene and Retinol Efficacy Trial (CARET) of heavy smokers (≥20 pack years). We used the ratio of predicted neutrophil and lymphocyte proportions derived from DNA methylation signatures in whole blood samples collected on average 4.1 years prior to diagnosis, to estimate mdNLR, which was discretized as quartiles ranging from lowest to highest; i.e. low to high levels of systemic inflammation. We fit Cox proportional hazards models adjusted for age, sex, race (white vs non-white), smoking status, intervention arm, asbestos exposure, and pack years smoked to examine the association between mdNLR lung cancer-specific mortality. We also adjusted for time between blood draw and diagnosis and included early versus late stage as a stratification variable. mdNLR was not associated with mortality for all cases combined, nor squamous cell carcinoma (N=100) or small cell lung cancer (N=59). In contrast, for adenocarcinoma (N=122), we observed a statistically significant linear trend (p=0.02) for increasing quartiles of mdNLR and adenocarcinoma-specific mortality, with a hazard ratio (HR) of 2.03 (95% Confidence Interval (CI): 1.03-4.03) comparing the highest (Q4) to lowest (Q1) mdNLR quartiles. Though subgroup analyses were sparse, we observed associations of larger magnitude (Q4 compared to Q1) for those who were younger at blood draw (HR=4.70, 95% CI: 1.73-12.76) and at diagnosis (HR=6.09, 95% CI: 1.98-18.72), as well as those with smoking histories lower than the median of 53 pack years (HR=2.91, 95% CI: 1.03-8.22) and those in the active intervention arm (HR=3.32, 95% CI: 1.11-9.93). Our findings suggest that an inflammatory response prior to diagnosis as indicated by higher mdNLR levels may be associated with mortality in heavy smokers who go on to develop lung adenocarcinoma. Since indicators of survival may be used to guide treatment decisions and gauge response to treatment, further research into the association between mdNLR and lung adenocarcinoma-specific survival is needed to understand its potential clinical utility.

Citation Format: Laurie Grieshober, Stefan Graw, Matt J. Barnett, Mark D. Thornquist, Gary E. Goodman, Chu Chen, Devin Koestler, Carmen Marsit, Jennifer Doherty. Pre-diagnosis neutrophil-to-lymphocyte ratio and lung cancer mortality [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 3300.

Abstract 5052: Immune profiles in the San Francisco Adult Glioma Study using Immunomethylomics

Glioma patients demonstrate abnormalities in peripheral blood leukocytes that have been associated with survival time. Here we assessed immune cell profiles in archival blood samples obtained 5-25 years ago using a novel epigenetic approach called immunomethylomics. We first validated the approach to measure the proportions of CD4 T, CD8 T cells, B cells, NK cells, neutrophils, and monocytes in archival blood using the new 850,000 feature EPIC Illumina methylation bead array. The immunomethylomic assay was shown to match the performance of multiparametric flow cytometry and thus is a highly accurate method for immune profiling. We next measured cell profiles in blood from 312 molecularly defined AGS subjects. In this cohort we enriched for patients with triple negative tumor subtypes (IDH wildtype, 1p19q negative, TERT non-mutant). Elevations in the neutrophil lymphocyte ratio (NLR) significantly increased with grade, whereas the proportions of T and B cells decreased with increasing grade. Using an established cut point of &gt; 4.0 for the NLR revealed that this immune parameter was associated with shorter survival times in glioblastoma (median overall survival (mOS) 12.6 vs. 16.9 months) and non-glioblastoma (mOS 16.7 vs. 36 months) patients. Ongoing analyses of the cohort will be presented to evaluate the effects of age, gender, surgery, chemoradiation and tumor grade on the survival results. Because DNA based immune cell profiles do not require intact cells nor preserved proteins, they provide a powerful tool to glean potentially important immunologic information from historic stored samples that would otherwise be useless using current cytometry-based approaches.

Citation Format: John K. Wiencke, Annette Molinaro, Warrier Gayathri, Jennifer Clarke, Jennie Taylor, Devin Koestler, Joe Wiemels, Helen Hanson, Lee Sean, Terri Rice, Lucie McCoy, Lucas Salas, Wrensch Margaret, Brock Christensen, Karl T. Kelsey. Immune profiles in the San Francisco Adult Glioma Study using Immunomethylomics [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 5052.

Abstract LB-195: Immune cell proportions and risk of pancreatic cancer using prediagnostic bloods

In 2018, approximately 55,440 individuals were diagnosed with pancreatic cancer in the US, and only 8% of these individuals will survive the next five years. Given the high fatality rate of pancreatic ductal adenocarcinoma, and the silent progression of this cancer, identifying early detection biomarkers for risk stratification for screening and surveillance is critical to improve prognosis. While the immune response plays a critical role in tumor growth and survival, understanding its role in the development of cancer has been hampered by the lack of data on immune status prior to cancer diagnosis. The identification of DNA methylation markers to estimate immune cell proportions in archived bloods provides a method to examine the long-term impact of immune cell types on pancreatic cancer risk. For this study, we included pre-diagnostic bloods from 322 pancreatic cancer cases and 343 controls (matched on age, race, sex, date of blood draw) from three independent prospective cohort studies to examine associations with immune cell proportions based on validated differentially methylated regions (DMRs) of cell lineage. DNA methylation from archived buffy coat samples for the cases and controls was measured using Illumina’s Infinium MethylationEPIC array; the range of time of blood draw to cancer diagnosis in cancer patients was 6 months to 26 years. We examined associations with pancreatic cancer for the methylation-derived neutrophil-to-lymphocyte ratio (mdNLR) and the ratio of CD4/CD8 cell types. The NLR has been linked to pancreatic cancer prognosis in several studies but has never been examined as a risk factor for incidence of pancreatic cancer (i.e., using blood drawn prior to cancer diagnosis). The CD4/CD8 ratio reflects the overall balance of T helper cells to cytotoxic T cells which is known to play a role in cancer immune surveillance in the tumor environment, and it may be associated with risk prior to diagnosis. In this nested case-control study, mdNLR was not associated the risk of pancreatic cancer (conditional OR = 1.19, 95% CI = 0.81 to 1.75, comparing top to bottom tertiles of mdNLR, additionally adjusting for smoking status). Furthermore, the association did not vary by sex or by time between blood draw and cancer diagnosis (&lt; 5 years, OR = 1.18; 5-10 years, OR = 1.22; &gt;10 years, OR =1.21). Similarly, we observed no association for the CD4/CD8 ratio and pancreatic cancer risk (OR = 0.94, 95% CI = 0.63 to 1.41) overall, or by time between blood draw and cancer diagnosis (&lt; 5 years, OR = 0.97; 5-10 years, OR = 0.62; &gt;10 years, OR =1.17). Our findings suggest that while the mdNLR may provide valuable information on prognosis after diagnosis of pancreatic cancer, a higher mdNLR in healthy individuals did not increase the risk of developing pancreatic cancer. In addition, prediagnostic CD4/CD8 ratio was not associated with pancreatic cancer risk. Further work examining additional immune cell type subfractions is currently underway.

Citation Format: Dominique S. Michaud, Mengyuan Ruan, Devin Koestler, Dong Pei, Carmen Marsit, Immaculata DeVivo, Karl Kelsey. Immune cell proportions and risk of pancreatic cancer using prediagnostic bloods [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 LB-195.

A phase Ib trial of cabozantinib in combination with durvalumab (MEDI4736) in previously treated patients with advanced gastroesophageal cancer and other gastrointestinal (GI) malignancies (CAMILLA)

TPS56

Background: GI malignancies including Gastric (GC), esophageal (EAC), colon (CRC), and hepatocellular carcinoma (HCC) remain a significant health problem in the US & globally. The current standard upfront therapy has < 12 month median survival. Hypoxia mimetic agents such as VEGFR targeted therapy down regulate the angiogenesis pathway and sensitize tumors to chemotherapy. Cabozantinib targets multiple tyrosine kinases, including VEGFR, MET, and AXL, and has been reported to show immunomodulatory properties that may counteract tumor-induced immunosuppression, providing a rationale for combining it with PD-1 or PD-L1 inhibitors. We believe that modulating the tumor microenvironment with small molecule inhibitors like cabozantinib will have synergistic effect when combined with checkpoint based immunotherapy like durvaluamb in patients with chemo refractory GC, EAC, CRC and HCC. Methods: The study is funded by research grants from both Exelixis and AstraZeneca. A phase 1 dose escalation is followed by an open-label single arm expansion. Dose escalation will be conducted using a 3+3 design. Starting dose for cabozantinib is 20mg daily. Single agent durvalumab MTD has been used, given that a regimen with full dose durvalumab may be better accepted as a backbone for comparison in future studies. MTD of cabozantinib in combination with standard dose durvalumab will be defined as the highest safely tolerated dose where 0/6 or 1/6 patients experience a DLT and ≥ 2 patients have experienced a DLT at the next higher dose level. Primary objective is to determine the Recommended Phase 2 Dose (RP2D). Secondary objectives include safety, ORR, PFS and OS. Eligible patients received > 1 line of therapy, no prior checkpoint inhibitors, have measurable disease, & ECOG PS 0-1. Phase 1 dose escalation will enroll 9-18 patients and the expansion phase will enroll 12-21 patients. Correlative studies include assessment of tumor microenvironment, angiogenesis & immune molecular markers. The dose escalation phase is currently enrolling. Clinical trial information: NCT03539822.

VaDiR: an integrated approach to Variant Detection in RNA

Background

Advances in next-generation DNA sequencing technologies are now enabling detailed characterization of sequence variations in cancer genomes. With whole-genome sequencing, variations in coding and non-coding sequences can be discovered. But the cost associated with it is currently limiting its general use in research. Whole-exome sequencing is used to characterize sequence variations in coding regions, but the cost associated with capture reagents and biases in capture rate limit its full use in research. Additional limitations include uncertainty in assigning the functional significance of the mutations when these mutations are observed in the non-coding region or in genes that are not expressed in cancer tissue.

Results

We investigated the feasibility of uncovering mutations from expressed genes using RNA sequencing datasets with a method called Variant Detection in RNA(VaDiR) that integrates 3 variant callers, namely: SNPiR, RVBoost, and MuTect2. The combination of all 3 methods, which we called Tier 1 variants, produced the highest precision with true positive mutations from RNA-seq that could be validated at the DNA level. We also found that the integration of Tier 1 variants with those called by MuTect2 and SNPiR produced the highest recall with acceptable precision. Finally, we observed a higher rate of mutation discovery in genes that are expressed at higher levels.

Conclusions

Our method, VaDiR, provides a possibility of uncovering mutations from RNA sequencing datasets that could be useful in further functional analysis. In addition, our approach allows orthogonal validation of DNA-based mutation discovery by providing complementary sequence variation analysis from paired RNA/DNA sequencing datasets.

Reduced mitochondrial reactive oxygen species production in peripheral nerves of mice fed a ketogenic diet

NEW FINDINGS

What is the central question of this study? Do peripheral sensory neurons metabolize fat-based fuel sources, and does a ketogenic diet modify these processes? What is the main finding and its importance We show that peripheral axons from mice fed a ketogenic diet respond to fat-based fuel sources with reduced respiration and H₂ O₂ emission compared with mice fed a control diet. These results add to our understanding of the responses of sensory neurons to neuropathy associated with poor diet, obesity and metabolic syndrome. These findings should be incorporated into current ideas of axonal protection and might identify how dietary interventions may change mitochondrial function in settings of sensory dysfunction.

ABSTRACT

Metabolic syndrome and obesity are increasing epidemics that significantly impact the peripheral nervous system and lead to negative changes in sensation and peripheral nerve function. Research to understand the consequences of diet, obesity and fuel usage in sensory neurons has commonly focused on glucose metabolism. Here, we tested whether mouse sensory neurons and nerves have the capacity to metabolize fat-based fuels (palmitoyl-CoA) and whether these effects are altered by feeding of a ketogenic (90% kcal fat) diet compared with a control diet (14% kcal fat). Male C57Bl/6 mice were placed on the diets for 10 weeks, and after the mice were killed, the dorsal root ganglion (DRG) and sciatic nerve (SN) were placed in an Oroboros oxygraph-2K to examine diet-induced alterations in metabolism (respiration) of palmitoyl-CoA and H₂ O₂ emission (fluorescence). In addition, RNAseq was performed on the DRG of mice fed a control or a ketogenic diet for 12 weeks, and genes associated with mitochondrial respiratory function were analysed. Our results suggest that the sciatic nerves from mice fed a ketogenic diet display reduced O₂ respiration and H₂ O₂ emission when metabolizing palmitoyl-CoA compared with mice fed a control diet. Assessments of changes in mRNA gene expression reveal alterations in genes encoding the NADH dehydrogenase complex and complex IV, which could alter production of reactive oxygen species. These new findings highlight the ability of sensory neurons and axons to oxidize fat-based fuel sources and show that these mechanisms are adaptable to dietary changes.

Preoperative risk factors predicting postoperative complications in radical cystectomy for bladder cancer

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Background: Radical cystectomy is an extensive operation with complications reported in up to 30.5% of patients. High complication rates contribute to increased costs, patient morbidity and mortality. Accurate prospective predictions of patients’ risk for post−surgical complications have the potential to identify at risk patients. Risk estimators have been developed but often involve an extensive number of factors or produce expansive results that are not clinically useful. Methods: 330 patients who underwent radical cystectomy for bladder cancer from January 2008 to July 2014 were included in this study. Potential preoperative risk predictors were collected from medical history, TURBT pathology, preoperative labs, proposed procedure type, and prior treatments. Postoperative complications were graded using the Clavien−Dindo scale. Multivariate logistic regression models were used to predict post−operative complications. Accuracy of prediction models was assessed using the area under the receiver operating characteristic curve. Results: Of the potential preoperative risk factors, 5, 10 and 16 unique predictors along with two way interactions were determined to have strong association with 90 day postoperative complications, yielding an AUC of 0.69, 0.79 and 0.91 respectively. Conclusions: Our findings suggest routinely collected preoperative patient−level clinical variables may be useful for determining patient risk for short−term postoperative complications. The flexibility in our prediction model for the number of predictor inputs allow users to tailor the degree of risk assessment based on a patient’s baseline heath status. A simple and accessible prediction model with selective predictors may help identify at risk patients for patient education, counseling and development of risk reduction strategies.

digit—a tool fordetection andidentification ofgenomicinterchromosomaltranslocations

Structural variations (SVs) in genomic DNA can have profound effects on the evolution of living organisms, on phenotypic variations and on disease processes. A critical step in discovering the full extent of structural variations is the development of tools to characterize these variations accurately in next generation sequencing data. Toward this goal, we developed a software pipeline named digit that implements a novel measure of mapping ambiguity to discover interchromosomal SVs from mate-pair and pair-end sequencing data. The workflow robustly handles the high numbers of artifacts present in mate-pair sequencing and reduces the false positive rate while maintaining sensitivity. In the simulated data set, our workflow recovered 96% of simulated SVs. It generates a self-updating library of common translocations and allows for the investigation of patient- or group-specific events, making it suitable for discovering and cataloging chromosomal translocations associated with specific groups, traits, diseases or population structures.

An ensemble-based Cox proportional hazards regression framework for predicting survival in metastatic castration-resistant prostate cancer (mCRPC) patients

From March through August 2015, nearly 60 teams from around the world participated in the Prostate Cancer Dream Challenge (PCDC). Participating teams were faced with the task of developing prediction models for patient survival and treatment discontinuation using baseline clinical variables collected on metastatic castrate-resistant prostate cancer (mCRPC) patients in the comparator arm of four phase III clinical trials. In total, over 2,000 mCRPC patients treated with first-line docetaxel comprised the training and testing data sets used in this challenge. In this paper we describe: (a) the sub-challenges comprising the PCDC, (b) the statistical metrics used to benchmark prediction performance, (c) our analytical approach, and finally (d) our team’s overall performance in this challenge. Specifically, we discuss our curated, ad-hoc, feature selection (CAFS) strategy for identifying clinically important risk-predictors, the ensemble-based Cox proportional hazards regression framework used in our final submission, and the adaptation of our modeling framework based on the results from the intermittent leaderboard rounds. Strong predictors of patient survival were successfully identified utilizing our model building approach. Several of the identified predictors were new features created by our team via strategically merging collections of weak predictors. In each of the three intermittent leaderboard rounds, our prediction models scored among the top four models across all participating teams and our final submission ranked 9 ^th place overall with an integrated area under the curve (iAUC) of 0.7711 computed in an independent test set. While the prediction performance of teams placing between 2 ^nd- 10 ^th (iAUC: 0.7710-0.7789) was better than the current gold-standard prediction model for prostate cancer survival, the top-performing team, FIMM-UTU significantly outperformed all other contestants with an iAUC of 0.7915.  In summary, our ensemble-based Cox regression framework with CAFS resulted in strong overall performance for predicting prostate cancer survival and represents a promising approach for future prediction problems.

Targeted or whole genome sequencing of formalin fixed tissue samples: potential applications in cancer genomics

Current genomic studies are limited by the poor availability of fresh-frozen tissue samples. Although formalin-fixed diagnostic samples are in abundance, they are seldom used in current genomic studies because of the concern of formalin-fixation artifacts. Better characterization of these artifacts will allow the use of archived clinical specimens in translational and clinical research studies. To provide a systematic analysis of formalin-fixation artifacts on Illumina sequencing, we generated 26 DNA sequencing data sets from 13 pairs of matched formalin-fixed paraffin-embedded (FFPE) and fresh-frozen (FF) tissue samples. The results indicate high rate of concordant calls between matched FF/FFPE pairs at reference and variant positions in three commonly used sequencing approaches (whole genome, whole exome, and targeted exon sequencing). Global mismatch rates and C·G > T·A substitutions were comparable between matched FF/FFPE samples, and discordant rates were low (<0.26%) in all samples. Finally, low-pass whole genome sequencing produces similar pattern of copy number alterations between FF/FFPE pairs. The results from our studies suggest the potential use of diagnostic FFPE samples for cancer genomic studies to characterize and catalog variations in cancer genomes.

Abstract 412: DNA methylation in ductal carcinoma in situ and its relation with disease progression

Ductal carcinoma in situ (DCIS) of the breast is a non-invasive lesion associated with a ten-fold increased relative risk for future invasive ductal cancer (IDC). DNA methylation is recognized as an important epigenetic regulator of gene expression and DNA methylation alterations are widespread in breast cancer. In addition, not all patients with DCIS will later present with invasive disease and epigenetic alterations in DCIS associated with disease progression are not clear. To investigate the relation of methylation with progression from DCIS to IDC we first identified patients with DCIS and a subsequent diagnosis of IDC through the New Hampshire Mammography Network (n=13). Next, we identified age-matched subjects with DCIS who did not have a subsequent diagnosis of IDC over a similar follow up period (n=27). Slides from all 40 patients underwent central pathology review by a breast pathologist, and 2 or 3 mm tissue cores were taken from archived FFPE blocks from selected areas of DCIS and adjacent normal tissue for DNA extraction and bisulfite modification. We measured DNA methylation genome-wide using the Illumina HumanMethylation450 BeadChip and processed the data using the ChAMP pipeline for quality control and normalization, after which 380,000 CpG sites remained in the data set. To investigate the relation of methylation with progression from DCIS to IDC, locus-specific differences in DNA methylation of 40 DCIS samples were examined using linear regression models fit to each of 380,000 CpG sites, modeling the logit-transformed methylation beta-values and adjusting for subject age and DCIS grade. Over 1,000 CpG sites exhibited large differences in DNA methylation levels (probes with a median Δβ &gt; 0.2), and had a nominal P-value &lt; 0.05, between patients with and without a subsequent diagnosis of IDC. Among the 1,007 CpG loci with significant and sizable changes in methylation, the majority (87.1%) exhibited increased methylation in women with a subsequent diagnosis of IDC compared to those without. We also sought to determine the relation of DNA methylation with DCIS grade among CpG loci that track to genes previously associated with DCIS grade, modeling the methylation as the dependent variable and DCIS grade (low/intermediate or high) as the independent variable. Comparing DCIS samples of low/intermediate grade with high grade we found that 15 CpG loci located near the transcriptional start site of the APC gene demonstrated significant (P &lt; 0.05) hypermethylation in high grade DCIS compared to low/intermediate grade DCIS. Ongoing analyses are highlighting profound differences between DCIS and available matched adjacent-normal samples (n=15) and examining the enrichment of regulatory features among differentially methylated loci. This work contributes to the understanding of epigenetic alterations that occur in earlier stages of disease and illustrates the potential of DNA methylation as a predictive marker in DCIS.

Citation Format: Kevin C. Johnson, Panpan Chen, Devin Koestler, Julia E. Weiss, Erik G. Jenson, Jonathan D. Marotti, Tracy Onega, Brock C. Christensen. DNA methylation in ductal carcinoma in situ and its relation with disease progression. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 412. doi:10.1158/1538-7445.AM2014-412

In utero arsenic exposure and fetal immune repertoire in a US pregnancy cohort

Arsenic has wide-ranging effects on human health and there is evidence that it alters the immune response by influencing CD4+/CD8+ T cell ratios, IL-2 cytokine levels, and the expression of immune-response genes. We investigated the impact of in utero environmental arsenic exposure on immune development and function in newborns participating in a pregnancy cohort in New Hampshire, U.S., where arsenic levels have exceeded the current EPA maximum contaminant level of 10 μg/L. Our results showed that maternal urinary arsenic concentrations were inversely related to absolute total CD45RA+ CD4+ cord blood CD69+ T cell counts (N=116, p=0.04) and positively associated with CD45RA+ CD69- CD294+ cell counts (p=0.01). In placental samples (N=70), higher in utero urinary arsenic concentrations were positively associated with the expression of IL1β (p=0.03). These data provide evidence that relatively low-level arsenic exposure in utero may alter the fetal immune system and lead to immune dysregulation.

Neonatal intensive care unit: predictive models for length of stay

OBJECTIVE

Hospital length of stay (LOS) is important to administrators and families of neonates admitted to the neonatal intensive care unit (NICU). A prediction model for NICU LOS was developed using predictors birth weight, gestational age and two severity of illness tools, the score for neonatal acute physiology, perinatal extension (SNAPPE) and the morbidity assessment index for newborns (MAIN).

STUDY DESIGN

Consecutive admissions (n=293) to a New England regional level III NICU were retrospectively collected. Multiple predictive models were compared for complexity and goodness-of-fit, coefficient of determination (R (2)) and predictive error. The optimal model was validated prospectively with consecutive admissions (n=615). Observed and expected LOS was compared.

RESULT

The MAIN models had best Akaike's information criterion, highest R (2) (0.786) and lowest predictive error. The best SNAPPE model underestimated LOS, with substantial variability, yet was fairly well calibrated by birthweight category. LOS was longer in the prospective cohort than the retrospective cohort, without differences in birth weight, gestational age, MAIN or SNAPPE.

CONCLUSION

LOS prediction is improved by accounting for severity of illness in the first week of life, beyond factors known at birth. Prospective validation of both MAIN and SNAPPE models is warranted.

Birthweight is associated with DNA promoter methylation of the glucocorticoid receptor in human placenta

Birthweight has been associated with a number of health outcomes throughout life. Crucial to proper infant growth and development is the placenta, and alterations to placental gene function may reflect differences in the intrauterine environment which functionally contribute to infant growth and may ultimately affect the child's health. To examine if epigenetic alteration to the glucocorticoid receptor (GR) gene was linked to infant growth, we analyzed 480 human placentas for differential methylation of the GR gene exon 1F and examined how this variation in methylation extent was associated with fetal growth. Multivariable linear regression revealed a significant association (p < 0.0001) between differential methylation of the GR gene and large for gestational age (LGA) status. Our work is one of the first to link infant growth as a measure of the intrauterine environment and epigenetic alterations to the GR and suggests that DNA methylation may be a critical determinant of placental function.