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T-cell clonality testing is integral to the diagnostic work-up of T-cell malignancies; however, current methods lack specificity and sensitivity, which can make the diagnostic process difficult. The recent discovery of a monoclonal antibody (mAb) specific for human TRBC1 will greatly improve the outlook for T-cell malignancy diagnostics. The anti-TRBC1 mAb can be used in flow cytometry immunophenotyping assays to provide a low-cost, robust, and highly specific test that detects clonality of immunophenotypically distinct T-cell populations. Recent studies demonstrate the clinical utility of this approach in several contexts; use of this antibody in appropriately designed flow cytometry panels improves detection of circulating disease in patients with cutaneous T-cell lymphoma, eliminates the need for molecular clonality testing in the context of large granular lymphocyte leukemia, and provides more conclusive results in the context of many other T-cell disorders. It is worth noting that the increased ability to detect discrete clonal T-cell populations means that identification of T-cell clones of uncertain clinical significance (T-CUS) will become more common. This review discusses this new antibody and describes how it defines clonal T-cells. We present and discuss assay design and summarize findings to date about the use of flow cytometry TRBC1 analysis in the field of diagnostics, including lymph node and fluid sample investigations. We also make suggestions about how to apply the assay results in clinical work-ups, including how to interpret and report findings of T-CUS. Finally, we highlight areas that we think will benefit from further research.

Abstract Context. —Bioelectronic sensors, which combine microchip and biological components, are an emerging technology in clinical diagnostic testing. An electronic detection platform using DNA biochip technology (eSensor) is under development for molecular diagnostic applications. Owing to the novelty of these devices, demonstrations of their successful use in practical diagnostic applications are limited. Objective. —To assess the performance of the eSensor bioelectronic method in the validation of 6 Epstein-Barr virus–transformed blood lymphocyte cell lines with clinically important mutations for use as sources of genetic material for positive controls in clinical molecular genetic testing. Two cell lines carry mutations in the CFTR gene (cystic fibrosis), and 4 carry mutations in the HFE gene (hereditary hemochromatosis). Design. —Samples from each cell line were sent for genotype determination to 6 different molecular genetic testing facilities, including the laboratory developing the DNA biochips. In addition to the bioelectronic method, at least 3 different molecular diagnostic methods were used in the analysis of each cell line. Detailed data were collected from the DNA biochip output, and the genetic results were compared with those obtained using the more established methods. Results. —We report the successful use of 2 applications of the bioelectronic platform, one for detection of CFTR mutations and the other for detection of HFE mutations. In all cases, the results obtained with the DNA biochip were in concordance with those reported for the other methods. Electronic signal output from the DNA biochips clearly differentiated between mutated and wild-type alleles. This is the first report of the use of the cystic fibrosis detection platform. Conclusions. —Bioelectronic sensors for the detection of disease-causing mutations performed well when used in a “real-life” situation, in this case, a validation study of positive control blood lymphocyte cell lines with mutations of public health importance. This study illustrates the practical potential of emerging bioelectronic DNA detection technologies for use in current molecular diagnostic applications.

Hematological malignancies comprise a genetically heterogeneous spectrum of diseases caused by abnormal proliferation or maturation of a variety of hematological cell lineages. Genomic abnormalities including chromosomal translocations, copy number variations and sequence level gene mutations underlie the pathogenesis of these disorders and frequently serve as important diagnostic, prognostic and/or therapeutic markers. However, the substantial discrepancy in interpretation and reporting of these genomic abnormalities among testing labs creates challenges for patient management. Therefore, standardizing the curation, clinical interpretation and reporting of somatic alterations within the context of their diagnostic, prognostic and therapeutic significance in hematological cancers is critical. In January 2020, the ClinGen Somatic Cancer Clinical Domain working group formed the Hematological Cancer Taskforce (HCT) with a goal to undertake systematic curation and evidence-based clinical interpretation of genes/somatic variants associated with hematological malignancies. The HCT has recruited 32 multi-disciplinary experts including oncologists, molecular pathologists, clinical lab directors, genomic scientists and biocurators with expertise in hematological malignancies. In collaboration with the Clinical Interpretation of Variants in Cancer (CIViC) (civicdb.org) knowledgebase, variants from peer-reviewed publications are curated with editor review for clinical utility as evidence items. Monthly discussions based on these evidence items lead to the creation of summary variant assertions using the AMP/ASCO/CAP guidelines (Li M, et al., Journal of Molecular Diagnostics, 2017). The HCT is currently focused on expert curation and clinical interpretation of somatic variants in FLT3 (internal tandem duplication, tyrosine kinase domain and non tyrosine kinase domain variants) in acute myeloid leukemia (AML). Expert curation of gene fusions in Philadelphia chromosome-like acute lymphoblastic leukemia (Ph-like ALL) in collaboration with the ClinGen somatic pediatric cancer taskforce is currently underway. To date, the HCT has curated 45 evidence items from clinical and pre-clinical studies on the aforementioned genes/variants. In addition, three AMP Tier I, level A variant assertions of FLT3-ITD, D835 and I836, which predict response to Gilteritinib, an FDA-approved drug for relapsed or refractory AML, have been curated. In the future, the HCT plans to extend its focus on curation of BCR-ABL1 kinase domain mutations in chronic myeloid leukemia (CML). Based on the initial pilot curation phase, the HCT will develop gene-specific recommendations to standardize the reporting and interpretation of somatic variants to better assist clinical decisions and apply to become official ClinGen Somatic Expert Panels in each of these gene-disease domains. Disclosures Blombery: Novartis: Consultancy; Invivoscribe: Honoraria; Amgen: Consultancy; Janssen: Honoraria.

Introduction: Richter transformation (RT) refers to transformation of chronic lymphocytic leukemia (CLL) to diffuse large B-cell lymphoma (DLBCL) or other aggressive lymphomas. The incidence, clinical characteristics, and outcomes of RT with CNS involvement remain undefined. Methods: Biopsy-confirmed RT diagnosed from 4/1993 to 4/2018 was identified from the Mayo Clinic CLL database. RT cases with CNS involvement were further reviewed, with clinical characteristics, treatment and follow-up data abstracted. Overall survival (OS) was defined as time from CNS involvement to death from any cause and analyzed using the Kaplan-Meier method. Results: Among 204 CLL patients with biopsy-proven RT, 15 patients had documented CNS involvement by imaging (parenchymal n=11, ocular n=1, parenchymal and ocular n=1, leptomeningeal n=1, cranial and spinal nerve roots n=1). Biopsy confirmation of CNS involvement was available in 11 patients. Of these 15 patients, 10 had CNS involvement at initial RT diagnosis, and 5 patients developed CNS involvement at RT progression, with a median time from RT diagnosis to CNS involvement of 14.9 months (range 2.8-41.1). Prior to RT, 11 patients (73.3%) received no treatment for CLL, 3 (53.4%) received chemoimmunotherapy (CIT) only (1-3 lines), and 1 patient (6.7%) received CIT (1 line) and ibrutinib. CLL FISH results were available in 9 patients, with del(17p) in 2, trisomy 12 in 2, del(13q) in 3, and normal results in 2. One patient had TP53 mutation (FISH result unavailable). IgHV mutation status was known in 3 patients and 1 was unmutated. The median time to RT was 4.4 years (range 0-11.4). The median age at RT diagnosis was 70 years (range 59-78), and 9 (60%) were male. The histology of RT was DLBCL in all 15 patients (diagnosed by CNS biopsy in 8 and other biopsies in 7), with GCB subtype in 6 and non-GCB subtype in 3. MYC rearrangement was detected in 4 of 6 patients tested, and 2 of those also had BCL-2 rearrangement (MYC/BCL-2 double hit). Of the 10 patients with CNS involvement at initial RT diagnosis, 4 had isolated CNS involvement (confirmed by brain biopsy [n=2] or vitreous biopsy [n=2]). All 4 patients were treated with high dose (HD) methotrexate (MTX) based regimen, and 3 patients achieved complete remission (CR) and underwent autologous stem cell transplant with continued CR, while 1 patient achieved partial remission and received whole brain radiotherapy (WBRT) at disease progression. Six patients had both systemic and CNS involvement (confirmed by brain biopsy [n=2] or CSF examination [n=2] in 4; the other 2 were diagnosed by imaging). All 6 patients received CNS directed therapy (HD MTX [n=5] or WBRT [n=1]) as well as systemic therapy (R-CHOP [n=5] or HyperCVAD [n=1]), with varied short duration of disease control (Figure 1A). Of the 5 patients who developed CNS involvement at RT progression (after 1-2 lines of therapy including first-line R-CHOP), 2 had isolated CNS involvement (1 was confirmed by CSF examination and the other was by imaging only). Both were treated with HD MTX based regimen, and 1 achieved a durable remission of 2 years but eventually had CNS relapse, while the other had no response and received WBRT with limited benefit. Three patients had both systemic and CNS involvement (2 were confirmed by CSF examination and the other was by imaging only), and all 3 patients were treated with HD MTX based regimen but all had CNS disease progression within 3 months (Figure 1A). The OS after CNS involvement for all 15 RT patients was 9.4 months (95% CI 2.3-19.1). Patients with CNS involvement at initial RT diagnosis had numerically longer OS compared to patients who developed CNS involvement at RT progression (median OS 13.0 vs 4.1 months, P = 0.137; Figure 1B). Patients with isolated CNS involvement had better OS compared to patients with both CNS and systemic involvement (median OS 32.0 vs 5.3 months, P = 0.009; Figure 1C). Three of the 4 patients who only had isolated CNS involvement at the time of RT diagnosis have ongoing long term remission and survival (Figure 1A). Conclusions: In this large series of RT, approximately 1 in 14 patients had CNS involvement. Patients with isolated CNS involvement appeared to have favorable long term outcome; however, RT patients with both systemic and CNS involvement had extremely poor survival. The incidence, molecular characteristics, and optimal management of RT with CNS involvement in the novel agent era warrant future multicenter studies. Disclosures Wang: Incyte: Research Funding; Innocare: Research Funding; Novartis: Research Funding. Parikh:GlaxoSmithKline: Honoraria; Pharmacyclics: Honoraria, Research Funding; AstraZeneca: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; MorphoSys: Research Funding; TG Therapeutics: Research Funding; Merck: Research Funding; AbbVie: Honoraria, Research Funding; Ascentage Pharma: Research Funding; Genentech: Honoraria; Verastem Oncology: Honoraria. Kay:Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol Meyer Squib: Membership on an entity's Board of Directors or advisory committees, Research Funding; Acerta Pharma: Research Funding; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Research Funding; MEI Pharma: Research Funding; Sunesis: Research Funding; Astra Zeneca: Membership on an entity's Board of Directors or advisory committees; Agios Pharma: Membership on an entity's Board of Directors or advisory committees; Cytomx: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Rigel: Membership on an entity's Board of Directors or advisory committees; Oncotracker: Membership on an entity's Board of Directors or advisory committees; Dava Oncology: Membership on an entity's Board of Directors or advisory committees; Juno Theraputics: Membership on an entity's Board of Directors or advisory committees. Witzig:AbbVie: Consultancy; MorphSys: Consultancy; Immune Design: Research Funding; Karyopharm Therapeutics: Research Funding; Incyte: Consultancy; Spectrum: Consultancy; Celgene: Consultancy, Research Funding; Acerta: Research Funding. Nowakowski:MorphoSys: Consultancy, Research Funding; Roche: Consultancy, Research Funding; Celgene/BMS: Consultancy, Research Funding; Kite: Consultancy; Denovo: Consultancy; Kymera: Consultancy; Ryvu: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other; Curis: Consultancy; Seattle Genetics: Consultancy; Nanostrings: Research Funding. Ansell:Trillium: Research Funding; AI Therapeutics: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; Takeda: Research Funding; ADC Therapeutics: Research Funding; Seattle Genetics: Research Funding; Bristol Myers Squibb: Research Funding. Kenderian:MorphoSys: Research Funding; Sunesis: Research Funding; Tolero: Research Funding; BMS: Research Funding; Juno: Research Funding; Gilead: Research Funding; Kite: Research Funding; Novartis: Patents & Royalties, Research Funding; Torque: Consultancy; Humanigen: Consultancy, Patents & Royalties, Research Funding; Lentigen: Research Funding; Mettaforge: Patents & Royalties. Ding:DTRM: Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; Beigene: Membership on an entity's Board of Directors or advisory committees; alexion: Membership on an entity's Board of Directors or advisory committees; MEI Pharma: Membership on an entity's Board of Directors or advisory committees; Octapharma: Membership on an entity's Board of Directors or advisory committees; Astra Zeneca: Research Funding; Abbvie: Research Funding.

Introduction: Richter's syndrome (RS) represents transformation of chronic lymphocytic leukemia (CLL) into a highly aggressive lymphoma with dismal prognosis. Transcriptomic alterations have been described in CLL but most studies focused on peripheral blood samples with minimal data on RS-involved tissue. Moreover, transcriptomic features of RS have not been well defined in the era of CLL novel therapies. In this study we investigated transcriptomic profiles of CLL/RS-involved nodal tissue using samples from a clinical trial cohort of refractory CLL and RS patients treated with Pembrolizumab (NCT02332980). Methods: Nodal samples from 9 RS and 4 CLL patients in MC1485 trial cohort were reviewed and classified as previously published (Ding et al, Blood 2017). All samples were collected prior to Pembrolizumab treatment. Targeted gene expression profiling of 789 immune-related genes were performed on FFPE nodal samples using Nanostring nCounter® Analysis System (NanoString Technologies, Seattle, WA). Differential expression analysis was performed using NanoStringDiff. Genes with 2 fold-change in expression with a false-discovery rate less than 5% were considered differentially expressed. Results: The details for the therapy history of this cohort were illustrated in Figure 1a. All patients exposed to prior ibrutinib before the tissue biopsy had developed clinical progression while receiving ibrutinib. Unsupervised hierarchical clustering using the 300 most variable genes in expression revealed two clusters: C1 and C2 (Figure 1b). C1 included 4 RS and 3 CLL treated with prior chemotherapy without prior ibrutinib, and 1 RS treated with prior ibrutinib. C2 included 1 CLL and 3 RS received prior ibrutinib, and 1 RS treated with chemotherapy. The segregation of gene expression profiles in samples was largely driven by recent exposure to ibrutinib. In C1 cluster (majority had no prior ibrutinb), RS and CLL samples were clearly separated into two subgroups (Figure 1b). In C2 cluster, CLL 8 treated with ibrutinib showed more similarity in gene expression to RS, than to other CLL samples treated with chemotherapy. In comparison of C2 to C1, we identified 71 differentially expressed genes, of which 34 genes were downregulated and 37 were upregulated in C2. Among the upregulated genes in C2 (majority had prior ibrutinib) are known immune modulating genes including LILRA6, FCGR3A, IL-10, CD163, CD14, IL-2RB (figure 1c). Downregulated genes in C2 are involved in B cell activation including CD40LG, CD22, CD79A, MS4A1 (CD20), and LTB, reflecting the expected biological effect of ibrutinib in reducing B cell activation. Among the 9 RS samples, we compared gene profiles between the two groups of RS with or without prior ibrutinib therapy. 38 downregulated genes and 10 upregulated genes were found in the 4 RS treated with ibrutinib in comparison with 5 RS treated with chemotherapy. The top upregulated genes in the ibrutinib-exposed group included PTHLH, S100A8, IGSF3, TERT, and PRKCB, while the downregulated genes in these samples included MS4A1, LTB and CD38 (figure 1d). In order to delineate the differences of RS vs CLL, we compared gene expression profiles between 5 RS samples and 3 CLL samples that were treated with only chemotherapy. RS samples showed significant upregulation of 129 genes and downregulation of 7 genes. Among the most significantly upregulated genes are multiple genes involved in monocyte and myeloid lineage regulation including TNFSF13, S100A9, FCN1, LGALS2, CD14, FCGR2A, SERPINA1, and LILRB3. Conclusion: Our study indicates that ibrutinib-resistant, RS-involved tissues are characterized by downregulation of genes in B cell activation, but with PRKCB and TERT upregulation. Furthermore, RS-involved nodal tissues display the increased expression of genes involved in myeloid/monocytic regulation in comparison with CLL-involved nodal tissues. These findings implicate that differential therapies for RS and CLL patients need to be adopted based on their prior therapy and gene expression signatures. Studies using large sample size will be needed to verify this hypothesis. Figure Disclosures Zhao: Merck: Current Employment. Blumenschein:Merck: Current Employment. Yearley:Merck: Current Employment. Wang:Novartis: Research Funding; Incyte: Research Funding; Innocare: Research Funding. Parikh:Verastem Oncology: Honoraria; GlaxoSmithKline: Honoraria; Pharmacyclics: Honoraria, Research Funding; MorphoSys: Research Funding; Ascentage Pharma: Research Funding; Genentech: Honoraria; AbbVie: Honoraria, Research Funding; Merck: Research Funding; TG Therapeutics: Research Funding; AstraZeneca: Honoraria, Research Funding; Janssen: Honoraria, Research Funding. Kenderian:Sunesis: Research Funding; MorphoSys: Research Funding; Humanigen: Consultancy, Patents & Royalties, Research Funding; Gilead: Research Funding; BMS: Research Funding; Tolero: Research Funding; Lentigen: Research Funding; Juno: Research Funding; Mettaforge: Patents & Royalties; Torque: Consultancy; Kite: Research Funding; Novartis: Patents & Royalties, Research Funding. Kay:Astra Zeneca: Membership on an entity's Board of Directors or advisory committees; Acerta Pharma: Research Funding; Juno Theraputics: Membership on an entity's Board of Directors or advisory committees; Dava Oncology: Membership on an entity's Board of Directors or advisory committees; Oncotracker: Membership on an entity's Board of Directors or advisory committees; Sunesis: Research Funding; MEI Pharma: Research Funding; Agios Pharma: Membership on an entity's Board of Directors or advisory committees; Bristol Meyer Squib: Membership on an entity's Board of Directors or advisory committees, Research Funding; Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Research Funding; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Rigel: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Cytomx: Membership on an entity's Board of Directors or advisory committees. Braggio:DASA: Consultancy; Bayer: Other: Stock Owner; Acerta Pharma: Research Funding. Ding:DTRM: Research Funding; Astra Zeneca: Research Funding; Abbvie: Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; Octapharma: Membership on an entity's Board of Directors or advisory committees; MEI Pharma: Membership on an entity's Board of Directors or advisory committees; alexion: Membership on an entity's Board of Directors or advisory committees; Beigene: Membership on an entity's Board of Directors or advisory committees.

Background: Clonal cytopenias of Undetermined Significance (CCUS) have a higher risk of progression to myeloid neoplasm (MN) compared to idiopathic cytopenias of undetermined significance (ICUS) (Malcovati et al., Blood, 2017). The implementation of flow cytometric (FC) immune-phenotyping and next generation sequencing (NGS) in clinical practice has improved the diagnosis of these entities but the clinical significance and interaction of these abnormal results are still unknown. In this study we investigated predictive factors that play role in survival and progression to MN in patients with ICUS/CCUS. Methods: Patients (Pts) who had undergone evaluation for unexplained cytopenia and had undergone FC and bone marrow morphological assessment between 3/2015-3/2020 at Mayo Clinic Rochester were included. Pts were excluded if a malignant hematological disorder was diagnosed prior to the time of FC. FC included evaluation of the following parameters: Abnormal expression of HLA-DR/CD13, CD2, CD7, CD45, and CD56 on blasts; and abnormal CD13/CD16 expression and side scatter on granulocytic cells. NGS panel up to 2018 included 34 genes, ASXL1, BCOR, BRAF, CALR, CBL, CEBPA, CSF3R, DNMT3A, ETV6, EZH2, FLT3, GATA1, GATA2, IDH1, IDH2, JAK2, KIT, KRAS, MPL, MYD88, NOTCH1, NPM1, NRAS, PHF6, PTPN11, RUNX1, SETBP1, SF3B1, TERT, TET2, TP53, U2AF1, WT1, and ZRSR2; in 2018, BRAF was omitted and 12 genes were added, ANRD26, DDX41, ELANE, ETNK1, KDM6A, MYD88, NOTCH1, RAD21, SH2B3, SRP72, SMC3, and STAG2. Results: Characteristics: Of 490 consecutive pts, 238 (median age 69 years (range 19-92), 66% males) met our inclusion criteria as ICUS. 86 (36%) pts had CCUS (abnormal cytogenetics and/or tested positive for pathogenic mutations on NGS). After a median follow-up of 28 months (95% CI: 20 to 31 months), 21 (25%) patients developed MN and 23 (27%) died during follow-up. Comparing ICUS vs CCUS: upon comparing CCUS pts to ICUS, several factors were found to be significantly different: CCUS pts were older (p= .02); majority male (p= .04), had more abnormal HLA-DR/CD13 (p <.0001), more side-scattered light by FC (p <.0001), more pancytopenia on follow up (p= .02) and more morphologic atypia (<.0001). Overall survival (OS) outcomes in CCUS: Several covariates were significant in univariate models, and model selection was used to generate a risk score based on abnormal CD7, abnormal CD13/CD16, abnormal HLA-DR/CD13, splenomegaly and history of prior chemotherapy or radiotherapy (range: 0 - 4; HR=2.58, [95 CI: 1.69 - 3.94], p<.0001). Risk scores were grouped as low risk (score=0), intermediate risk (score=1), and high risk (score=2+), with estimated 2-yr-OS of 95%, 84%, 40%, respectively (Figure 1). An extended risk score model including NGS factors added ASXL1 and IDH1 mutation status to the previous model (range: 0 - 6; HR=2.72, [95 CI 1.82 - 4.06], p<0.0001). MN-free survival (MNFS) in CCUS: 37 pts either progressed to MN and/or died with a median follow up time for MNFS of 22.4 months. Similar for OS, model selection approaches yielded a composite risk score: splenomegaly, BCOR mutation status, mutation in RAS signaling pathway, abnormal expression of flow markers CD13/CD16, HLA-DR/CD13 or CD7 (HR=3.23, [95 CI: 1.90 - 5.49], p=<0.0001). Risk scores were grouped as low risk (score=0), intermediate risk (score=1), and high risk (score ≥ 2), with estimated 1-yr MNFS of 84%, 74%, and 31%, respectively (Figure 2). Conclusion: CCUS has unique features compared to ICUS. Several factors, including clinical characteristics, immune-phenotyping by FC, and somatic mutations have important impact on risk of progression to MN and on overall survival. Our findings serve as proof-of-concept that such integrated models could help identify CCUS patients at higher risks for progression to MN or death. They can guide treatment accordingly and should be evaluated further. Disclosures Shah: Dren Bio: Consultancy.

Abstract Hidradenitis suppurativa (HS) is a chronic and often debilitating inflammatory condition characterized by frequent nodules, abscesses, sinus tracts, and scars impacting the intertriginous areas. Many patients with HS often report limited treatment success and symptom coverage with conventional therapies. Recent studies have reported the widespread use of complementary and alternative medicine (CAM) among patients with HS. In this study, our aim was to examine current physician practice patterns, opinions, and comfort with recommending CAM. Our results indicate that provider comfort and opinions on CAM varied based on the provider's experiences, demographics, and the CAM modality itself. Overall, nearly two‐thirds (n = 30, 61.2%) of respondents agreed that CAM and conventional medicine were more effective together than either alone. Meanwhile, 44.9% (n = 22) of respondents routinely recommend CAM while 64.6% (n = 31) of respondents reported that they are routinely asked about CAM. The majority (n = 41, 83.7%) of respondents indicated a lack of scientific evidence in the medical literature as a barrier to recommending CAM along with efficacy concerns (n = 34, 69.4%) and ability to recommend reputable CAM products (n = 32, 65.3%) and practitioners (n = 32, 65.3%). Future investigations are warranted to establish a better understanding of the efficacy and benefit of CAM methods in conjunction with conventional methods.

377 Background: Neoadjuvant therapy has been associated with a median overall survival (OS) of 18 – 23 months (mo) in patients (pts) with BR pancreatic ductal adenocarcinoma (PDAC). To establish reference regimens to which novel treatments can be compared in future studies, we evaluated neoadjuvant mFOLFIRINOX with or without RT in BR PDAC in a phase II National Clinical Trials Network (NCTN) trial. Methods: Pts with ECOG PS 0-1 and BR PDAC confirmed by central real-time radiographic review after pre-registration were randomized to either arm A: 8 cycles of neoadjuvant mFOLFIRINOX (oxaliplatin 85 mg/m2, irinotecan 180 mg/m2, leucovorin 400 mg/m2 and infusional 5-fluorouracil 2400 mg/m2 over 46 hours), or arm B: 7 cycles of mFOLFIRINOX followed by stereotactic body RT (SBRT, 33-40 Gy in 5 fractions [fx]) or hypofractionated image guided RT (HIGRT, 25 Gy in 5 fx). Pts in either arm without disease progression underwent pancreatectomy, then 4 cycles of adjuvant mFOLFOX6 (oxaliplatin 85 mg/m2, leucovorin 400 mg/m2 and infusional 5-fluorouracil 2400 mg/m2 over 46 hours). The primary endpoint, 18-mo OS rate, of each arm was compared to a historical control of 50%. Planned interim analysis mandated closure of either arm in which <11 of first 30 accrued pts underwent R0 resection. Results: 155 pts pre-registered and 126 pts were enrolled to arm A (N=70; 54 randomized, 16 following closure of arm B) or arm B (N=56; closed at interim analysis, all pts randomized prior to closure). Median age (A: 63y, B: 67y), median CA 19-9 level (A: 171 U/ml, B: 248 U/ml) and ECOG PS (A: 51% PS 0, B: 57% PS 0) of registered pts were similar between arms (p > 0.05). Treatment detailed in Table. The 18-mo OS rate based on Kaplan Meier estimates was 67.9% (95%CI: 54.6 – 78.0) in arm A and 47.3% (95%CI: 33.7 – 59.7) in arm B. Among pts who underwent pancreatectomy, 18-mo OS rate was 93.1% (95%CI: 84.3 – 100) and 78.9% (95%CI: 62.6 – 99.6) in arm A and B, respectively. With median follow-up of 27 and 31 mo, median OS was 31.0 (95%CI: 22.2 – NE) mo and 17.1 (95%CI: 12.8 – 24.4) mo in arm A and B, respectively. Conclusions: Neoadjuvant mFOLFIRINOX was associated with favorable OS relative to historical data in pts with BL PDAC in this phase II NCTN trial. mFOLFIRINOX with hypofractionated RT did not improve OS compared to historical data. mFOLFIRINOX represents a reference regimen in this setting and a backbone on which to add novel agents. Support: U10CA180821, U10CA180882, U24CA196171; https://acknowledgments.alliancefound.org Clinical trial information: NCT02839343. [Table: see text]

343 Background: Alliance/CALGB 80802, a randomized phase III trial, evaluated sorafenib plus doxorubicin vs. doxorubicin in pts with HCC and showed no improvement in median overall survival (OS) (HR[95CI] 1.05[0.83-1.31]) or PFS (HR[95CI] 0.93[0.75-1.16]). In HCC surrogacy of tumor response with OS remains controversial, in part due to varying criteria used for response evaluation (e.g., RECIST1.1 and mRECIST). We evaluated the performance of several models to predict OS using pretreatment clinical and radiomic variables. Methods: In CALBG 80802, we segmented all measurable tumor lesions on sequential CT scans. A lesion’s imaging phenotype was deciphered with 23 uncorrelated quantitative imaging features measured at baseline and week (wk) 10 (first follow-up). An OS landmark survival analysis was conducted at wk 10. Patients were randomly assigned (3:1) to training (n = 92) and validation (n = 37) sets. In a training set, 6 random forest predictive models (6 signatures) used features that best predicted OS using 3 sets of variables: radiomics only (n = 23), clinical only (n = 9), radiomics and clinical (n = 32). Two time points (baseline only or baseline + wk 10) were assessed. Each signature's output was an individualized prediction and a continuous value ranging from 0 to 1 (from most to least favorable predicted OS). The primary endpoint was to compare these models' performance to predict OS using error rate (Harrell's concordance-index) in the validation set. Results: Of the 6 training signatures evaluated, the one achieving the highest performance in the validation set was an 8-feature signature combining radiomics and clinical variables measured at two time points (baseline + wk 10) with an error rate of 35.6%. The variables [rank of importance] (table) selected by the signature included baseline clinical features (albumin[1], AFP[2], Child-Pugh[4]), baseline radiomics features (component 17[3], component 1[5], component 9[7], tumor volume[8]) and wk 10 radiomics features (delta tumor volume[6]). Variable delta tumor volume [6] used a more enhanced estimation of tumor burden at baseline and a delta tumor volumetric measurement; compared to RECIST1.1 measurement of percentage change in unidimensional measurement of a subset of target lesions. The four quartiles of the signature were significantly associated with OS (Log-Rank, P < 0.0001). Conclusions: The selected combined radiomic and clinical composite signature provided the best prediction for OS in the 80802 study patients’ population. It is a suggested way forward to go beyond single anatomic measurement techniques such as RECIST or mRECIST. [Table: see text]

325 Background: Alliance/CALGB 80802 randomized phase III trial evaluated DO+S vs. S in pts with aHCC, and showed no improvement in median OS. Multi-drug resistant pathway mitigation by the Ras/Raf/MEK/ERK pathway and bFGF-mediated activation of Raf-1 promotes the formation of antiapoptotic Raf-1 and ASK1 complex, induced by anthracyclines. S efficiently blocks NS5A-recruited c-Raf mediated HCV replication and viral gene expression. Once inhibited by S, VEGF expression of HepG2 may limit HCV cellular entry. Release of Raf-1-Ask-1 dimer and inhibition of Raf-1 via S putatively differ in the presence or absence of DO. We hypothesize treatment with S reduces HCV titer levels (TL) and influence pts’ outcome. Methods: In 80802 HCV pts, TL were evaluated in both arms at baseline and post-baseline at Day 1 of Cycles 2, 3, and every 2 cycles and at progression or discontinuation of therapy. HCV undetectable (HCV-UN) levels were defined as < 50 copies/mL. TL were evaluated in relation to OS and PFS. HCV RNA levels were measured by TaqMan PCR and by genotype. Results: Of 356 pts, 83 were HCV+ with more Black/African American (25/50 = 50%) vs. White (54/239 = 23%) or other race groups (4/67 = 6%) (p < 0.0001). HCV titer data were available on 54 pts (S: 28, DO+S: 26). At baseline, 12 pts (S: 7, DO+S: 5) were HCV-UN, and post-baseline HCV TL did not significantly differ between treatment arms; one patient in each arm went from detectable (HCV-D) to HCV-UN. Post-baseline, 40 pts were HCV-D vs. 14 who were HCV-UN (S+DO: 8, S: 6 pts). Except for the two pts who became HCV-UN, baseline HCV-D vs. HCV-UN titers was similar to that status post-baseline. PFS and OS between HCV-D and HCV-UN both at baseline and post-baseline are delineated in the table. Conclusions: We observed that S did not influence HCV TL. Pts treated with DO+S vs. S had worse PFS if they had HCV-UN, and further that higher levels of HCV titers at baseline were associated with significantly improved PFS. Given the small sample size, these findings warrant further prospective evaluation. Support: U10CA180821, U10CA180882, U24CA196171; Bayer, Bristol-Myers-Squibb, and Sanofi. https://acknowledgments.alliancefound.org . Clinical trial information: NCT01015833. [Table: see text]