Crowley, John

Abstract Background: Bone disease in myeloma occurs as a result of complex interactions between myeloma cells and the bone marrow microenvironment. To date, no studies have evaluated the potential impact of genetic polymorphisms upon and/or within this microenvironment. Patients and Methods: Peripheral blood DNA from 282 patients enrolled in the Total Therapy 2 (TT2) protocol was studied using the previously reported Affymetrix 3k BOAC custom chip to evaluate relevant genetic polymorphisms. DKK1 gene expression and high risk GEP gene signatures were assessed as previously reported (Blood109:4470–4477 and 109:2276–2284 2007). Patients were classified using both full skeletal x-rays and MRI findings. The lower cut-off used was absence of focal abnormalities on x-ray and/or <7 focal lesions on MRI (see JCO25:1121–1128 2007). Results: The top 200 SNPs were first evaluated based upon univariate P values linked to limited or extensive bone disease. The top 50 SNPs with the smallest P values were then selected (eliminating closely linked genes) for recursive partitioning analysis. The recursive partitioning was conducted both with and without the insertion of known biologically relevant SNPs. The pruned tree developed with recursive partitioning proved to be quite stable and incorporated 4 dominant SNPs: rs 3766934 Epoxide hydrolase (EPHX1); sr3783408 MAP kinase; sr 1062637 RNA helicase DDX18; and sr3181366 TNFSF8-TNF-α. No alternate SNP substituted for EPHX1 in the recursive model. The 4 SNP signature of EPHX1 GG, MAP4K5 AG/AA, DDX18 GG/CC plus TNFSF8 CT/TT was highly correlated with the number of MRI lesions: mean 8.66 lesions versus 3.33 for alternate SNPs (P<.001). In the univariate association of standard prognostic factors, 4 SNP signature and 70 and 17 gene models for high risk, the best correlation with bone disease was with the 4 SNPs (P<.0001) followed by the 17 gene GEP model (P=0.05). Using stepwise multivariate regression analysis the best correlation with bone disease was Log2DKK-1 expression (P=.0001) but closely followed by SNPs EPHX1 (P=.0009); MAP4K5 (P=.0071) plus TNFSF8 and serum LDH (P=.02). The various analyses training (2/3) and validation sets were used with assessment of sensitivity and specificity. The microenvironmental 4 SNP signature combined with GEP DKK1 provided the best prediction of myeloma bone disease and overall outcome. Conclusions: This first assessment of genetic polymorphisms linked to myeloma bone disease in myeloma has led to the identification of polymorphisms with both potential biologic relevance and utility in prognostic models of myeloma bone disease including risk stratification for bisphosphonate use. Validation of these findings may allow a search for potential therapeutic targets.

Abstract Genetic variations in patient populations likely contribute to disease progression and therapeutic outcomes. We have begun a systematic approach to examine the association of genetic variations (ie. functional, single nucleotide polymorhisms, SNPs) involved in myeloma growth promotion, metabolic events, drug responses, and DNA repair on clinical outcome in the intergroup trial S9321. This trial tested a single high dose regimen with autologous stem cell support against a conventional dose regimen, with further randomization of responders to maintenance with interferon or not, in newly diagnosed patients with multiple myeloma. ECOG, CALGB and SWOG enrolled 899 patients with newly diagnosed MM to receive VAD induction x 4 cycles followed by randomization to PBSC-supported high dose therapy (HDT) versus standard dose therapy (SDT) of VBMCP, using CTX 4.5 g/m2 + G-CSF for PBSC mobilization in all patients. Responders to VBMCP or HDT were randomized to IFN or no maintenance. Specimens were distributed through ECOG for biologic correlative studies, including candidate SNP analysis. SNP assays have been developed using the Sequenom Mass-extend platform for functional SNPs in IL-6, IL-1, IL-RA, IL-10, TNF, Lta, TGFb, MDR1, MPO, CYP3A4, GST (M, P, T), ERCC2 and XRCC1, and are being evaluated on 803 DNA samples prepared from patients enrolled in S9321. Preliminary findings (n=135) demonstrate functional genetic variants of IL-10 (position -1082), IL-1 (position +3953), TGFb (postion -509), and TNFa (position -308) are showing trends associated with differences in progression free survival; and variants in IL-6 (position -174) are associated with response. Median survival of the IL-10 variants was 31 months for A/A low producer alleles versus 19 months for the G/G high producer alleles (p=.5). For TNFa, 2 cases with the high producer A/A alleles died within a year, while the median survival for the lower producer G/G alleles was 2 years (p=.04). For patients with the high producer C/C/ allele of IL-1 (n=67), median survival was 2 years, versus 5 patients with the T/T low producer alleles that had a median survival greater than 5 years (preliminary p=.29). While these preliminary results are now only suggestive of trends in genetic polymorphisms associated with clinical outcome, completion of the full SNP panel on the entire sample base should provide a extensive association study, and analysis of potential differences in therapy arms of the trial. The full panel and association studies will be presented.ααββααα

Abstract Abstract 743 Background There has been considerable recent focus upon the molecular classification of myeloma. However, the prognostic impact of molecular changes has mostly been assessed from small and/or incomplete studies from single institutions or groups. There has been no large scale analysis of molecular features linked to ISS stage. Methods In order to clarify the overall impact of molecular changes we undertook a collective analysis of 9,897 patients through the International Myeloma Working Group (IMWG). Within this population 2,295 patients had presence of cytogenetic abnormalities (Any CA); 1,713 hypodiploidy; 1,673 hyperdiploidy; 2,309 cytogenetic deletion 13; 3,226 deletion 13 by FISH; 1,573 FISH t(4;14); 1,486 FISH del p17; 1, 683 FISH t(11:14); and 366 FISH t(4;16). Enrolled patients had complete clinical and treatment details available including baseline standard prognostic factors, ISS stage, as well as both progression free survival (PFS) and overall survival (OS) information. Data came from 14 sites: 3 from the US and the remainder from Europe, Asia, and Latin America as for the ISS staging system analyses. Univariate and multivariate analyses were performed. Results Each of the known adverse molecular features had a negative impact upon both PFS and OS (p=002 - <0.0001). Among the deleterious FISH abnormalities the t(4;14) abnormality was the most highly correlated with poorer outcomes by PFS: 4 year estimate: 32% vs. 60% (p<0.0001). The t(4;14) abnormality combined with ISS Stage also significantly enhanced predictive capability: ISS Stage I without t(4;14) OS 81% @ 4 years; ISS Stage III with t(4;14) OS 22% @ 4 years (P<0.0001) [Figure 1]. The best outcomes were for ISS Stage I in the presence of t(11;14): OS 89% @ 4 years. Absence of any one adverse feature correlated with 80-81% OS @ 4 years for Stage I. Presence of any one adverse feature had a more variable impact and correlated with 22%-40% OS at 4 years for Stage III. In univariate correlations the most predictive correlations with OS were presence of Any CA, t(4;14), 17p-, hypodiploidy, cytogenetic 13q- with R2 values of 6.9%, 4.5%, 4.1% and 3.8% respectively. In multivariate analyses, ISS stage provided the best predictions: R2 values = 13.3%. The added contributions from molecular features were: t(4;14) 3.8%; cytogenetic 13q- 2.9%; Any CA 2.3%; and 17p- 1.0%. The maximum total R2 for OS was 22%. Conclusions This large multicenter analysis confirms the correlations between abnormal molecular findings and outcomes. Combinations with ISS Stage provide the best predictive capability. Presence of Any CA, t(4;14), 17p-, hypodiploidy and cytogenetic 13q- contribute to poorer outcomes by ISS stage. The presence of hyperdiploidy and/or t(11;14) contribute to better outcomes. There is thus validation of prior molecular studies related to prognosis utilizing this large IMWG database. Disclosures: No relevant conflicts of interest to declare.

Abstract Pancreatic adenocarcinoma generally presents with a poor prognosis and an extremely low response rate to first line therapies. There is a critical unmet need to discover and implement effective diagnostic panels to stratify outcomes and tailor treatment strategies to improve survival. The BERG Interrogative Biology® platform utilizes Artificial Intelligence to analyze and integrate multi-omic profiles with clinical annotation to define novel biomarkers and improve treatment interventions. Herein, we analyzed the serum proteome, signaling lipidome, structural lipidome, and metabolome of 163patients at multiple timepoints (pancreatic cancer: 115; pancreatitis: 15; and age-matched healthy controls: 33). Utilizing the power of the Bayesian Network learner, bAIcis™ (BERG Artificial Intelligence Clinical Information System), multi-omic profiles were aligned to the longitudinal clinical information and subjected to AI-algorithms to infer probabilistic cause-and-effect relationships among molecular and clinical variables explicitly explaining pancreatic cancer status, cancer progression, and survival, and defining the interconnectivity of molecular features with clinical phenotype. Network features linking into clinical endpoints and key network pressure points were identified as molecular drivers. The drivers of clinical endpoints were analyzed to rank potential biomarkers. Novel biomarkers were discovered that demonstrate diagnostic potential for pancreatic cancer detection, disease prognosis including metastatic disease progression, patient stratification associated with survival, and response to standard chemotherapy agents like Gemcitibine. A prospective study is underway to validate the biomarkers and discover additional diagnostic and therapeutic molecules to improve the outcomes for patients affected by adenocarcinoma of the pancreas. Citation Format: Niven R. Narain, A James Moser, Ramesh Ramanathan, John Crowley, Amy Stoll-D’Astice, Yezhou Sun, Leonardo O. Rodrigues, Eric M. Grund, Emily Chen, Vivek K. Vishnudas, Michael A. Kiebish, Viatcheslav R. Akmaev, Rangaprasad Sarangarajan. Project Survival: Interrogative Biology® platform mediated discovery of molecular markers for detection, stratification and outcomes in pancreatic 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 786.

Abstract Background: The genomes of metastatic pancreatic cancers contain a myriad of intrachromosomal aberrations indicating a likely high prevalence of DNA repair deficiencies indicating sensitivity to DNA damaging agents such as the platinum’s. Because of this, the drug cisplatin was added to an albumin-bound paclitaxel + gemcitabine regimen, which has already been determined to improve survival over gemcitabine alone in a randomized phase III trial (NEJM 2013; 369:1691-1703). Objectives: To determine the efficacy and safety of albumin-bound paclitaxel and gemcitabine plus cisplatin for patients with advanced pancreatic cancer Methods: Eligibility criteria included Stage IV pancreatic cancer, no prior chemotherapy for systemic disease, KPS ≥ 70; life expectancy ≥ 12 weeks and measurable disease. The doses were albumin-bound paclitaxel 125 mg/m2 undiluted, gemcitabine 1000 mg/m2 in 500 ml of normal saline (NS), each infused over 30 minutes on days 1 and 8 of a 21 day cycle, along with 3 different dose levels of cisplatin (25, 37.5 or 50 mg/m2) in 500 ml of NS infused over 60 minutes, after the nab-paclitaxel infusion. Pre and post cisplatin hydration was given. Results: To date, 10 patients have been entered on study with all patients being evaluable, (baseline and at least one follow up CT scans completed). There have been 2 complete responses (20%), 6 partial responses (PR), (60%), 1 stable disease (10%), and 1 patient with progressive disease (10%), by RECIST 1.1 criteria. An exponential decrease in CA19-9 correlating with the t1/2 of the marker was noted. Response was seen rapidly with PR observed at the first staging evaluation at 9 weeks in 7 of 10 patients. The 8th patient achieved a PR at 18 weeks. Serious adverse events occurred in 4 patients: non-neutropenic sepsis/pneumonia (n = 1), and non-neutropenic bacteremia (n = 1) in the cisplatin 25 mg/m2 cohort; clostridium difficile colitis (n = 1) with cisplatin 37.5 mg/m2; and neutropenic fever/pneumonia (n = 1) with cisplatin 50mg/m2. Discussion: The study has completed phase Ib and will be expanded at the phase II dose of cisplatin 25 mg/m2 for a total of 25 patients. If this favorable response rate is confirmed, this 3 drug regimen could be further developed both for patients with advanced disease as well as in neoadjuvant and adjuvant settings. Supported by grants from the Seena Magowitz Foundation and the SU2C Dream Team Citation Format: Gayle S. Jameson, Erkut Borazanci, Elizabeth Poplin, Michael T. Barrett, John Crowley, Adam Rosenthal, Amy Stoll-D'Astice, Karen L. Ansaldo, Steven Boone, Leticia Lebron, Ramesh K. Ramanathan, Ronald L. Korn, Daniel D. Von Hoff. High complete and partial response rate in a phase Ib pilot trial with cisplatin plus albumin-bound paclitaxel and gemcitabine in patients with advanced pancreatic cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr LB-003. doi:10.1158/1538-7445.AM2015-LB-003

AbstractWe compiled and analyzed a database of cooperative group trials in advanced pancreatic cancer to develop historical benchmarks for overall survival (OS) and progression-free survival (PFS). Such benchmarks are essential for evaluating new therapies in a single-arm setting. The analysis included patients with untreated metastatic pancreatic cancer receiving regimens that included gemcitabine, between 1995 and 2005. Prognostic baseline factors were selected by their significance in Cox regression analysis. Outlier trial arms were identified by comparing individual 6-month OS and PFS rates against the entire group. The dataset selected for the generation of OS and PFS benchmarks was then tested for intertrial arm variability using a logistic-normal model with the selected baseline prognostic factors as fixed effects and the individual trial arm as a random effect. A total of 1,132 cases from eight trials qualified. Performance status and sex were independently significant for OS, and performance status was prognostic for PFS. Outcomes for one trial (NCCTG-034A) were significantly different from the other trial arms. When this trial was excluded, the remaining trial arms were homogeneous for OS and PFS outcomes after adjusting for performance status and sex. Benchmark values for 6-month OS and PFS are reported along with a method for using these values in future study design and analysis. The benchmark survival values were generated from a dataset that was homogeneous between trials. The benchmarks can be used to enable single-arm phase II trials using a gemcitabine platform, especially under certain circumstances. Such circumstances might be when a randomized control arm is not practically feasible, an early signal of activity of an experimental agent is being explored such as in expansion cohorts of phase I studies, and in patients who are not candidates for combination cytotoxic therapy. Clin Cancer Res; 20(16); 4176–85. ©2014 AACR.