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e16686 Background: Genetic alterations in the FGFR pathway are emerging as promising therapeutic targets in CCA. The clinical and molecular features of patients (pts) with CCA harboring FGFR genetic alterations are reported here. Methods: A retrospective chart review was performed in pts with CCA who were found to have an FGFR alteration on tumor molecular profiling as part of routine care between 9/2007 and 12/2019. Data on demographics, risk factors, pathology, molecular characteristics, systemic therapies, radiographical response, time on treatment, and overall survival (OS) were collected in a multi-center collaborative effort across seven academic centers. Results: Among 135 pts with FGFR-altered CCA, the median age at diagnosis was 57 years old (range = 25-92 years), and 80 (59.3%) pts were female, 129 (95.6%) had intrahepatic CCA, and 6 (5.6%) had chronic HBV. At presentation, 28.2% of pts had resectable disease, including 65.0% with Stage I-II, 22.5% with Stage III, and 5.0% with Stage IV. At the time of initial diagnosis, CA19-9 was < 35U/mL in 42.6% of pts. Bone metastases were observed in 41 (30.6%) pts with advanced disease. FGFR2 fusions were the most common FGFR alteration (68.2%), followed by FGFR2 mutations (21.5%), FGFR3 mutations (3.7%), FGFR2 rearrangements (1.5%), FGFR1 amplification (1.5%), and FGFR2 amplification (1.5%). The most common FGFR2 fusion partners were BICC1 (28.3%), SORBS1 (4.4%), POC1B (3.3%), and TACC2 (3.3%). The median lines of palliative systemic therapies received was 3 (range = 0-8), and 40/135 (29.6%) pts received a liver-directed therapy. For the 55 (59.8%) pts with FGFR2 fusions who received gemcitabine/cisplatin as first-line palliative systemic therapy, the median time on treatment was 6.2 months (95% CI: 4.1-9.3). The median OS from time of initial diagnosis was 36.1 months (95% CI: 28.3-51.6) in the FGFR2 fusion positive cohort. Among the 92 pts with FGFR2 fusions, 70 (76.1%) pts received an FGFR inhibitor on a clinical trial; 12 (17.1%) were subsequently treated with a second FGFR inhibitor, and 58.3% stayed on the second FGFR inhibitor for ≥4 months. Pts with a BICC1 fusion partner (n = 16) had an overall response rate of 42.9% on FGFR-selective inhibitors compared to 30.8% in non-BICC1 fusion partners (n = 54). Conclusions: Pts with CCA harboring FGFR alterations were found to have a high rate of normal CA19-9, high rate of bone metastases, and short median time on treatment on first-line palliative gemcitabine/cisplatin. Additional comparative studies are necessary to evaluate these findings.

Abstract PURPOSE: Recent advances in understanding of the molecular alterations that occur at the genetic and epigenetic levels in Multiple Myeloma (MM) have led to major leaps in identifying molecular pathways that regulate progression and resistance to therapeutic agents. However, despite great scientific advances at the genomic level, studies to identify signaling pathways deregulated at the functional proteomic level in MM are limited. In this study, we used a rapid and reproducible antibody-based protein microarray technique to screen the functional differences between malignant plasma cells in samples obtained from patients with MM compared to normal plasma cells (NPC) from the bone marrow of healthy volunteers. METHODS: We determined the protein expression level of 512 polypeptides in 12 samples of newly diagnosed patients with MM using high-throughput proteomic analysis with antibody-based protein microarray. Primary CD138+ sorted MM cells were obtained from the bone marrow of patients after informed consent. MM1.S was used in this study. Using immunohistochemistry and immunoblotting were confirmed. Lentivirus was used to knockdown CRIK. Gene expression datasets from the Mayo Clinic (accession number GSE 6477) and the UAMS (accession number GSE 2658) were obtained from the Gene Expression Omnibus for analysis. The Mayo dataset was generated using Affymetrix U133A platform whereas the UAMS dataset was generated using Affymetrix U133plus 2.0 platform. RESULTS: We identified four subgroups of MM using unsupervised clustering analysis. We confirmed overexpression of some of these proteins including CRIK and CDK4 using immunohistochemistry and immunoblotting. Many of these proteins are known to be deregulated in MM, indicating that this technique can accurately identify proteins that are over or under-expressed in MM in a high-throughput fashion. In addition, we identified novel proteins that are not previously known to be differentially expressed in MM, including the small GTPase member of the Rho family, CRIK protein. We then showed using knockdown of CRIK that this novel protein specifically regulates migration and adhesion in MM. There was no effect on survival of MM cells using the CRIK knockdown. Analyzing the GEP data of the 15 NPC, 46 monoclonal gammopathy of undetermined significance (MGUS) or smoldering myeloma (SMM) and 101 MM samples from the Mayo Clinic, there was a significant increase in expression of CIT from NPC to MM. Among the 351 patients entered into TTII trials from UAMS, CIT expression was similar across the different TC class. Using a cut-off normalized expression level of 1.25 (a level above expression in NPC), MM with a high CIT expression (n=81) had a significantly shorter survival than the other patients. CONCLUSION: In this study, we show that MM cells express a high level of CRIK, and that inhibition of this protein leads to significant inhibition of adhesion and migration of MM cells. In addition, CRIK protein expression correlated with CIT gene expression, with high expression in MM samples compared to NPC. In addition, high CIT expression correlated with poor survival in patients with MM.

Background and Aims Alcoholic hepatitis (AH) is diagnosed by clinical criteria, although several objective scores facilitate risk stratification. Extracellular vesicles (EVs) have emerged as biomarkers for many diseases and are also implicated in the pathogenesis of AH. Therefore, we investigated whether plasma EV concentration and sphingolipid cargo could serve as diagnostic biomarkers for AH and inform prognosis to permit dynamic risk profiling of AH subjects. Approach and Results EVs were isolated and quantified from plasma samples from healthy controls, heavy drinkers, and subjects with end‐stage liver disease (ESLD) attributed to cholestatic liver diseases and nonalcoholic steatohepatitis, decompensated alcohol‐associated cirrhosis (AC), and AH. Sphingolipids were quantified by tandem mass spectroscopy. The median plasma EV concentration was significantly higher in AH subjects (5.38 × 1011/mL) compared to healthy controls (4.38 × 1010/mL; P < 0.0001), heavy drinkers (1.28 × 1011/mL; P < 0.0001), ESLD (5.35 × 1010/mL; P < 0.0001), and decompensated AC (9.2 × 1010/mL; P < 0.0001) disease controls. Among AH subjects, EV concentration correlated with Model for End‐Stage Liver Disease score. When EV counts were dichotomized at the median, survival probability for AH subjects at 90 days was 63.0% in the high‐EV group and 90.0% in the low‐EV group (log‐rank P value = 0.015). Interestingly, EV sphingolipid cargo was significantly enriched in AH when compared to healthy controls, heavy drinkers, ESLD, and decompensated AC (P = 0.0001). Multiple sphingolipids demonstrated good diagnostic and prognostic performance as biomarkers for AH. Conclusions Circulating EV concentration and sphingolipid cargo signature can be used in the diagnosis and differentiation of AH from heavy drinkers, decompensated AC, and other etiologies of ESLD and predict 90‐day survival permitting dynamic risk profiling.

INTRODUCTION The cerebral cortex underlies our complex cognitive capabilities. Variations in human cortical surface area and thickness are associated with neurological, psychological, and behavioral traits and can be measured in vivo by magnetic resonance imaging (MRI). Studies in model organisms have identified genes that influence cortical structure, but little is known about common genetic variants that affect human cortical structure. RATIONALE To identify genetic variants associated with human cortical structure at both global and regional levels, we conducted a genome-wide association meta-analysis of brain MRI data from 51,665 individuals across 60 cohorts. We analyzed the surface area and average thickness of the whole cortex and 34 cortical regions with known functional specializations. RESULTS We identified 369 nominally genome-wide significant loci ( P < 5 × 10 −8 ) associated with cortical structure in a discovery sample of 33,992 participants of European ancestry. Of the 360 loci for which replication data were available, 241 loci influencing surface area and 66 influencing thickness remained significant after replication, with 237 loci passing multiple testing correction ( P < 8.3 × 10 −10 ; 187 influencing surface area and 50 influencing thickness). Common genetic variants explained 34% (SE = 3%) of the variation in total surface area and 26% (SE = 2%) in average thickness; surface area and thickness showed a negative genetic correlation ( r G = −0.32, SE = 0.05, P = 6.5 × 10 −12 ), which suggests that genetic influences have opposing effects on surface area and thickness. Bioinformatic analyses showed that total surface area is influenced by genetic variants that alter gene regulatory activity in neural progenitor cells during fetal development. By contrast, average thickness is influenced by active regulatory elements in adult brain samples, which may reflect processes that occur after mid-fetal development, such as myelination, branching, or pruning. When considered together, these results support the radial unit hypothesis that different developmental mechanisms promote surface area expansion and increases in thickness. To identify specific genetic influences on individual cortical regions, we controlled for global measures (total surface area or average thickness) in the regional analyses. After multiple testing correction, we identified 175 loci that influence regional surface area and 46 that influence regional thickness. Loci that affect regional surface area cluster near genes involved in the Wnt signaling pathway, which is known to influence areal identity. We observed significant positive genetic correlations and evidence of bidirectional causation of total surface area with both general cognitive functioning and educational attainment. We found additional positive genetic correlations between total surface area and Parkinson’s disease but did not find evidence of causation. Negative genetic correlations were evident between total surface area and insomnia, attention deficit hyperactivity disorder, depressive symptoms, major depressive disorder, and neuroticism. CONCLUSION This large-scale collaborative work enhances our understanding of the genetic architecture of the human cerebral cortex and its regional patterning. The highly polygenic architecture of the cortex suggests that distinct genes are involved in the development of specific cortical areas. Moreover, we find evidence that brain structure is a key phenotype along the causal pathway that leads from genetic variation to differences in general cognitive function. Identifying genetic influences on human cortical structure. ( A ) Measurement of cortical surface area and thickness from MRI. ( B ) Genomic locations of common genetic variants that influence global and regional cortical structure. ( C ) Our results support the radial unit hypothesis that the expansion of cortical surface area is driven by proliferating neural progenitor cells. ( D ) Cortical surface area shows genetic correlation with psychiatric and cognitive traits. Error bars indicate SE. IMAGE CREDITS: (A) K. COURTNEY; (C) M. R. GLASS

176 Background: Multiple tumour tissue studies have demonstrated the prognostic utility of CNVs in mCRPC. However, accurate assessment of CNVs in plasma cfDNA remains challenging, and prognostic significance has not been well characterized. Using a large customized panel, we correlated plasma CNVs with clinical outcomes in a contemporary cohort of mCRPC patients. Methods: Deep targeted sequencing was performed using a 180-gene cfDNA panel (Predicine) in 56 patients commencing AR pathway inhibitors (enzalutamide or abiraterone; n = 34) or taxane chemotherapy (n = 22) at two Australian institutions. Kaplan-Meier estimates and Cox proportional-hazards models were used to correlate CNVs with progression-free survival (PFS) and overall survival (OS). Significant results were validated in an independent cohort (Mayo Clinic, n = 144). Results: Median follow-up was 19.4 months (mo; IQR 11.3-31.9). The most common CNVs in the Australian cohort are shown (Table). OS was significantly decreased in patients with PI3KCA gain (median 21.7 mo vs 6.6 mo, p < 0.0001), PTEN loss (24.8 mo vs 11.7 mo, p = 0.0019) and AR gain (21.7 mo vs 12.0 mo, p = 0.0083). Furthermore, all three alterations independently predicted for poor survival in multivariable analyses (MVA; Table). Findings in the independent cohort showed similar OS results in MVA: PIK3CA gain (HR 2.0, p = 0.07), PTEN loss (HR 1.7, p = 0.08) and AR gain (HR 1.7, p = 0.03). Conclusions: Sequencing of plasma cfDNA revealed that PTEN loss, and PIK3CA and AR gain are associated with inferior clinical outcomes in patients commencing contemporary systemic treatment. These data support therapeutic strategies co-targeting the PI3K and AR pathways in mCRPC.[Table: see text]

160 Background: mCRPC is a heterogeneous disease state with variable survival and molecular markers that define survival continue to be determined. We applied a 120 gene panel based targeted next-gen sequencing (NGS) approach to probe plasma ctDNA based outcomes for survival. Methods: mCRPC chemo-naive patients (pts) were enrolled in a prospective study and plasma cell free DNA (cfDNA) extracted. ctDNA fractions estimated based on somatic variants. NGS of plasma cfDNA was performed using HiSeq X Ten on a panel of 120 genes (PredicineLDT). Clinical and molecular prognostic factors were determined for overall survival (OS). Cox proportional hazard regression was used to estimate hazard ratios (HR) at the univariate level and only significant associations included in multivariate analysis (significance at P<0.05). Results: 96 mCRPC pts were enrolled. 17/96 pts failed NGS QC. Median cfDNA, ctDNA yields for 79/96 pts are provided in Table. Median follow up for study cohort was 92.5 months (mon) (Range:62.3-109.6); median survival time was 25.9 mon (95% CI:19.9, 31.4) and 72/79 pts had died. TMPRSS2-ERG fusion was detected in 18/79 pts. Significant alterations associated with OS are listed in Table. 49/59 pts underwent subsequent docetaxel chemo. In chemo treated pts significant copy number alterations predictive of survival included AR amplification (p=0.01, HR=2.0, 95% CI[1.2, 3.5], RB1 loss (p=3.20E-06, HR=5.0, 95% CI[2.4, 10.6], PTEN(p=0.009, HR=2.6, 95% CI[1.2, 5.4]), CDH1(p=0.001, HR=4.3, 95% CI[1.6, 11.4]). Conclusions: ctDNA yield in mCRPC state was the most significant prognostic factor for survival, Several specific plasma genomic perturbations were observed topredict docetaxel efficacy and need further evaluation.[Table: see text]

Background: Myelofibrosis (MF) is associated with bone marrow fibrosis (BMF), splenomegaly, a high symptom burden, and poor prognosis; the JAK/STAT pathway is the central pathway implicated in its pathogenesis. Ruxolitinib, a JAK1/2 inhibitor and the only FDA-approved pharmacotherapy for treatment (Tx) of MF patients (pts), improves splenomegaly, but is unable to control all clinical manifestations of disease. Navitoclax is an orally bioavailable, novel small-molecule that targets and binds with high affinity to multiple antiapoptotic B-cell lymphoma 2 (BCL2) family proteins, including BCL-XL, BCL2, and BCL-W. Preclinical studies have demonstrated cytotoxic activity of navitoclax against myeloproliferative neoplasm-derived cell lines. Herein, the results of a phase 2 study (NCT03222609) evaluating the combination of navitoclax with ruxolitinib in pts with MF are reported. Methods: This phase 2 single-arm, multicenter, open-label study assessed the efficacy and safety of navitoclax combined with ruxolitinib in pts with MF. Eligible pts (≥18 yr, diagnosis of primary MF, post-essential thrombocythemia [PET]-MF, or post-polycythemia vera [PPV]-MF, ECOG 0-2, receiving at least 12 wk of continuous ruxolitinib therapy prior to study Tx initiation) received a starting dose of 50 mg navitoclax once-daily combined with the current stable dose of ruxolitinib (≥10 mg BID). Weekly intra-patient dose-escalation of navitoclax was allowed to a maximum daily dose of 300 mg based on tolerability and platelet count. Tx continued until the end of clinical benefit, unacceptable toxicity, or discontinuation. The primary efficacy endpoint was percentage reduction in splenic volume from baseline. Secondary endpoints included effect on total symptom score (TSS), overall response rate, rate of anemia response, improvement in BMF, and safety profile. Results: As of May 1, 2019, 34 pts (primary MF, n=16; PET-MF, n=5; PPV-MF, n=13) had received ≥1 dose of navitoclax in combination with ruxolitinib. Median age was 68 yr (range 42-86), 68% were male, and 9 pts (26%) had ≥3 prior lines of MF therapy. The median duration of prior ruxolitinib exposure was 745 days (range 134-4549). Of the 34 pts enrolled, 27 (79%) had JAK2 and 7 pts (21%) had CALR mutations. There were no pts enrolled with triple-negative MF. Of 33 pts with available baseline testing, 17 (52%) had high molecular risk, defined by mutations within ASXL1, EZH2, IDH1/2, SRSF2, or U2AF1. The mean baseline platelet count was 231 x 109/L (range 99-706); mean baseline Hgb was 10.8 g/dL; 19 (56%) pts had elevated WBC at baseline (&gt;1.5× ULN). Maximal navitoclax dose of 300 mg was achieved in 23 pts (68%). Of the 25 (74%) pts that enrolled on ruxolitinib doses &gt;10 mg BID, 22 (88%) subsequently had the dose of ruxolitinib reduced to 10 mg BID. At the time of this analysis, 24 pts were evaluable for efficacy, with 20 pts completing ≥24 wk on study and 4 pts with Tx discontinuations prior to 24 wk. At wk 24, 7 of 24 pts (29%) achieved a spleen volume reduction of ≥35% (SVR35) from baseline by MRI as determined by prespecified central review; the median TSS was 7.4 (range 0-23), a 20% improvement from baseline. A SVR35 at any time on study was achieved in 10 pts (42%). Reductions in driver mutation allelic burden of &gt;5% were observed in 10 (42%) pts; 6 pts (25%) had BMF improvement of ≥1 grade. One pt (4%) had an anemia response; the mean Hgb at wk 24 was slightly improved over baseline at 11.3 g/dL. Of the 19 pts with elevated baseline WBC, 16 (84%) reduced to within normal limits during Tx, with a median WBC reduction of 17.7 × 109/L. All pts experienced a Tx-emergent adverse event (TEAE); most common (≥20%) were thrombocytopenia (82%), diarrhea (62%), fatigue (53%), anemia (27%), nausea (27%), contusion (24%), and vomiting (21%). Grade ≥3 TEAEs occurred in 26 pts (77%); most common were thrombocytopenia (n=15, 44%; Grade 4 n=1, 3%) and anemia (n=8, 24%; no Grade 4). Five pts (15%) experienced serious AEs that resolved including anemia, upper abdominal pain, vomiting, chest pain, increased C-reactive protein, and abnormal liver function test (3% each). There were no significant episodes of bleeding and no TEAE-related deaths. Conclusions: Navitoclax in combination with ruxolitinib was well tolerated with clinically meaningful spleen responses, allelic burden reductions, TSS improvements, and encouraging improvements in BMF in pts with MF who have received prior Tx with ruxolitinib. Disclosures Harrison: CTI: Speakers Bureau; Promedior: Honoraria; Roche: Honoraria; Celgene: Honoraria, Speakers Bureau; Gilead: Speakers Bureau; Shire: Speakers Bureau; Incyte: Speakers Bureau; Sierra Oncology: Honoraria; Janssen: Speakers Bureau. Garcia:Genentech: Research Funding; Abbvie: Research Funding. Mesa:CTI: Research Funding; Galena Biopharma: Consultancy; Samus: Research Funding; Genotech: Research Funding; AbbVie: Research Funding; NS Pharma: Research Funding; Baxalta: Consultancy; LaJolla: Consultancy; Shire: Honoraria; PharmaEssentia: Research Funding; Genentech: Consultancy; Celgene Corporation: Research Funding; AOP Orphan Pharmaceuticals: Honoraria, Other: travel, accommodations, expenses; Promedior: Research Funding; Novartis: Consultancy, Honoraria, Other: travel, accommodations, expenses; Incyte: Other: travel, accommodations, expenses, Research Funding; Gilead Sciences: Research Funding; Pfizer: Research Funding; Sierra Oncology: Consultancy. Somervaille:Novartis: Consultancy. Komrokji:pfizer: Consultancy; celgene: Consultancy; DSI: Consultancy; Incyte: Consultancy; Agios: Consultancy; JAZZ: Consultancy; Novartis: Speakers Bureau; JAZZ: Speakers Bureau. Pemmaraju:sagerstrong: Research Funding; celgene: Consultancy, Honoraria; Stemline Therapeutics: Consultancy, Honoraria, Research Funding; Daiichi-Sankyo: Research Funding; samus: Research Funding; novartis: Consultancy, Research Funding; plexxikon: Research Funding; incyte: Consultancy, Research Funding; abbvie: Consultancy, Honoraria, Research Funding; mustangbio: Consultancy, Research Funding; cellectis: Research Funding; affymetrix: Research Funding. Papadantonakis:Agios: Consultancy, Honoraria. Foran:Agios: Honoraria, Research Funding. O'Connell:Astex: Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Research Funding; Pfizer: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees; Shionogi: Membership on an entity's Board of Directors or advisory committees. Holes:AbbVie Inc: Employment, Other: Stock/stock options. Jia:AbbVie: Employment, Other: Stock/stock options. Harb:AbbVie Inc: Employment, Other: Stock/stock options. Hutti:AbbVie: Employment, Other: Stock/stock options.

Background: Overexpression of the anti-apoptotic BCL-2 protein promotes multiple myeloma (MM) cell survival. Venetoclax (Ven) is a highly selective, potent, oral BCL-2 inhibitor that induces apoptosis and has shown synergistic activity with bortezomib (B) and dexamethasone (d). Phase 1 studies in relapsed/refractory (RR) MM demonstrated encouraging clinical efficacy of Ven + d in t(11;14) MM and in a broader patient (pt) population in combination with Bd. Recent results from the Phase 3 BELLINI study of Ven vs placebo (Pbo) + Bd in pts with RRMM demonstrated that pts treated with Ven + Bd had improved clinical response rates and progression-free survival (PFS) vs Pbo, although the overall survival (OS) result was in favor of Pbo. Subgroup analyses showed different efficacy and survival outcomes based on tumor cytogenetics and BCL-2 expression. Results of pre-specified subgroup analyses and additional retrospective correlative biomarker analyses in the Phase 3 BELLINI study are described herein. Methods: BELLINI (NCT02755597) was a randomized, double-blind, multicenter Phase 3 study of Ven or Pbo + Bd in pts with RRMM who received 1-3 prior therapies and were either sensitive or naïve to PIs. Pts were randomized 2:1 to receive Ven 800 mg/day or Pbo + Bd. The following biomarker analyses were performed by central laboratory assessments of pre-treatment tumor samples: BCL-2 protein expression by immunohistochemistry (IHC) analysis of bone marrow (BM) core biopsies; BCL2 gene expression by quantitative PCR (qPCR) and cytogenetic abnormalities by interphase fluorescence in situ hybridization (FISH) analysis of CD138-enriched BM mononuclear cells. Correlation between BCL-2 (protein and gene) expression, cytogenetics, and outcomes were examined by Kruskal-Wallis tests and by hazard ratio (HR) using the Cox proportional hazard model. Results: As of the data cut-off of 18 Mar 2019, 291 pts were randomized, 194 to the Ven arm and 97 to the Pbo arm. Out of the 291 pts randomized, 177 pts (61%) were evaluable by IHC, 257 pts (88%) by qPCR, and 262 pts (90%) by FISH. A broad range of BCL2 gene expression was observed (median 2-DCt: 0.212 [range: 0-5.21]), which strongly correlated with protein expression (median 2-DCt 0.115 in BCL-2 IHC Low vs 0.277 in BCL-2 IHC High, p=0.0021). t(11;14) MM had the highest levels of BCL-2 expression (23/23 BCL-2 High by IHC; median 2-DCt 0.406 vs 0.212 in t(11;14) negative, p=0.0132), however high BCL-2 expression was not limited to the t(11;14) subgroup. Univariate analyses showed higher BCL2 expression in pt tumor samples with del(13q) (median 2-DCt 0.333 vs 0.159 in pts without del(13q), p=0.0008) and gain(1q) (median 2-DCt 0. 295 vs 0.180 in pts without gain(1q), p=0.0059). Bootstrapping and aggregating thresholds from trees (BATTing) was used retrospectively to identify an estimated threshold value for BCL2 expression (2-DCt ≥0.323) that could provide optimum selection of pts with maximum improvement in PFS when treated with Ven+Bd. Biomarker subgroups with the greatest PFS improvement were t(11;14) (HR=0.10; 95% CI: 0.02-0.46, p=0.003) and High BCL2 by qPCR (HR=0.26; 95% CI: 0.13-0.51, p&lt;0.001; Table 1). Since the t(11;14) and High BCL2 patient populations do not completely overlap (20% of High BCL2 pts were t(11;14) and 54% of t(11;14) were High BCL2), a combined subgroup analysis was performed. For pts with t(11;14) or High BCL2, the median PFS was not reached in the Ven arm vs 9.9 mo in Pbo (HR=0.26, 95% CI: 0.14-0.48, p&lt;0.001; Table 1). Higher overall response (ORR, 88% vs 70%), very good partial response or better (≥VGPR, 73% vs 33%), and complete response or better (≥CR, 42% vs 3%) rates were observed in the Ven vs Pbo arm (Table 2). Minimal residual disease negativity (MRD-, 10-5) rate was also higher for t(11;14) or High BCL2 pts in the Ven vs Pbo arm (19% vs 0%). Median overall survival (OS) was not reached in either arm but was similar between treatment arms for the combined group with t(11;14) or High BCL2 pts (HR=0.92, 95% CI=0.39-2.16, p=0.85). In contrast, in the t(11;14) negative and Low BCL2 pts, OS favored Pbo (HR=3.13, 95% CI=1.2-8.13, p=0.019; Table 1). Conclusions: Adding Ven to Bd demonstrates significant efficacy in pts with RRMM harboring either t(11;14) or tumor cells expressing high levels of BCL2. The benefit-risk profile appears to be favorable in these subsets of pts and additional studies to gain further safety and efficacy information are warranted. Disclosures Harrison: GSK: Consultancy, Research Funding; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: investigator on studies, Research Funding; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen Cilag: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Cavo:celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel accommodations, Speakers Bureau; sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; novartis: Honoraria; takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel accommodations, Speakers Bureau; bms: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. De La Rubia:AMGEN: Consultancy; Takeda: Consultancy; AbbVie: Consultancy; Janssen: Consultancy; Celgene Corporation: Consultancy. Popat:Celgene Corporation: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel, accommodations, expenses; Janssen: Honoraria, Other: travel support to meetings; GSK: Consultancy, Honoraria; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Other: travel, accommodations, expenses. Gasparetto:Janssen: Consultancy, Honoraria, Other: Travel, accommodations, or other expenses paid or reimbursed ; BMS: Consultancy, Honoraria, Other: Travel, accommodations, or other expenses paid or reimbursed ; Celgene: Consultancy, Honoraria, Other: Travel, accommodations, or other expenses paid or reimbursed . Hungria:Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; BMS: Consultancy, Honoraria, Speakers Bureau; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; BMS: Consultancy, Honoraria, Speakers Bureau; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Salwender:Amgen: Honoraria, Other: Travel or accommodations; Bristol-Myers Squibb: Honoraria, Other: Travel or accommodations; Janssen Cilag: Honoraria, Other: Travel or accommodations; Sanofi: Honoraria, Other: Travel or accommodations; Celgene: Honoraria, Other: Travel or accommodations; AbbVie: Honoraria; Takeda: Honoraria, Other: Travel or accommodations. Suzuki:Ono: Research Funding; BMS: Honoraria, Research Funding; Takeda: Honoraria; Janssen: Honoraria; Celgene: Honoraria. Moreau:Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria. Spencer:AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Secura Bio: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Specialised Therapeutics Australia: Consultancy, Honoraria; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Servier: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Haemalogix: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen Oncology: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. O'Dwyer:Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Consultancy; GlycoMimetics Inc: Research Funding; BMS: Research Funding; Onkimmune: Equity Ownership, Membership on an entity's Board of Directors or advisory committees, Research Funding. Garg:Janssen: Honoraria; Novartis, Janssen: Research Funding; Janssen, Takeda, Novartis: Other: Travel expenses. Punnoose:Roche: Other: Stock/stock options; Genentech, Inc.: Employment. Jalaluddin:AbbVie: Employment, Other: Stock/stock options. Jia:AbbVie: Employment, Other: Stock/stock options. Yang:AbbVie: Employment, Other: Stock/stock options. Sun:AbbVie: Employment, Other: Stock/stock options. Ward:AbbVie: Employment, Other: Stock/stock options. Maciag:AbbVie: Employment, Other: Stock/stock options. Ross:AbbVie: Employment, Other: Stock/stock options. Kumar:Takeda: Research Funding; Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding. OffLabel Disclosure: Venetoclax is a BCL-2 inhibitor that is FDA-approved in some indications. This presentation will focus on venetoclax for treatment of multiple myeloma, which is not an approved indication.

480 Background: Currently, there is a lack of imaging biomarkers of immunotherapy outcome in hepatocellular carcinoma (HCC). The study aim was to determine if HCC enhancement on MRI and stiffness change measured by magnetic resonance elastography (MRE) can predict immunotherapy response. Methods: This was a prospective, Institutional Review Board approved study of 38 patients with HCC treated with immune checkpoint blockade (ICB) therapy. All patients had liver MRI/MRE and HCC biopsy at baseline, and MRI/MRE with biopsy or resection after 6 weeks therapy. HCC stiffness (kPa) was measured on MRE elastograms (liver stiffness maps). HCC enhancement and change in stiffness were compared with treatment response to ICB in 1) non-surgical patients (pembrolizumab), and 2) surgical patients (nivolumab +/- ipilimumab). For non-surgical patients, treatment response was defined as overall survival >1 year. For surgical patients, treatment response was defined as <50% viable tumor at time of resection. Analysis was performed using descriptive statistics and Spearman correlation; p-value <0.05 was considered statistically significant. Results: Twenty-five patients were evaluable. Median age was 67 years (32, 78). Etiology of liver disease was NASH (n=8), HCV (n=8), HBV (n=2) and unknown (n=7). Treatment response occurred in 11/25 (44%) patients. Median HCC size and change in size were 4.7 cm (1.2, 14.0) and –0.32 cm, respectively. Median baseline HCC stiffness and change in stiffness were 5 kPa (2.2, 12.4) and –0.1 kPa (–2.2, 1.5), respectively. Median change in HCC size for responders and non-responders was –1.2 cm (–4.8, 0.4) and 0 cm (–1.5, 1.1), respectively (p = 0.02). Treatment response was associated with absence of portal venous phase capsular enhancement and increase in HCC stiffness, (p<0.001). Conclusions: Capsular enhancement and MRE stiffness change may be useful biomarkers of immune cell activated response to ICB therapy.

Single nucleotide variants in the open reading frames (ORFs) of pharmacogenes are important causes of interindividual variability in drug response. The functional characterization of variants of unknown significance within ORFs remains a major challenge for pharmacogenomics. Deep mutational scanning (DMS) is a high‐throughput technique that makes it possible to analyze the functional effect of hundreds of variants in a parallel and scalable fashion. We adapted a “landing pad” DMS system to study the function of missense variants in the ORFs of cytochrome P450 family 2 subfamily C member 9 ( CYP2C9 ) and cytochrome P450 family 2 subfamily C member 19 ( CYP2C19 ). We studied 230 observed missense variants in the CYP2C9 and CYP2C19 ORFs and found that 19 of 109 CYP2C9 and 36 of 121 CYP2C19 variants displayed less than ~ 25% of the wild‐type protein expression, a level that may have clinical relevance. Our results support DMS as an efficient method for the identification of damaging ORF variants that might have potential clinical pharmacogenomic application.