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e16200 Background: Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death worldwide. Indoleamine-2,3-dioxygenase (IDO) is an intracellular enzyme expressed by HCC which helps to orchestrate immune suppression within the tumor microenvironment (TME) and may contribute to primary and acquired resistance of PD-(L)1 inhibitors. BMS-986205 is a novel oral drug that potently and selectively inhibits IDO1. This Phase I/II study is evaluating the safety and tolerability of the combination of BMS-986205 and nivolumab as first-line therapy in HCC. Methods: Patients (pts) ≥18y with untreated, unresectable/metastatic HCC received BMS-986205 in combination with nivolumab. A fixed dose of Nivolumab 240mg/m2 IV was administered on Day 1 of each 14-day cycle. BMS-986205 was an oral tablet administered daily; a total of two dose levels (50-100mg) were given to determine dose limiting toxicities (DLT) during the dose-escalation Phase I of the study. Safety was assessed using CTCAE v5.0 criteria, and efficacy was assessed by objective response rate (ORR) using RECIST v1.1 criteria. Secondary objectives included preliminary data on disease control rate (DCR), duration of response (DOR), ORR using immune RECIST criteria (iRECIST), progression free survival (PFS) and overall survival (OS). Results: Here we report the results of the dose escalation cohort. Eight pts were treated with median age 69y [60-76]; 75% male; and PS 0 (3 pts) or 1 (5 pts). Pts were White (62.5%), Asian (25%), and African American (12.5%). Six of 8 pts had underlying viral hepatitis (5 hepatitis C, 1 hepatitis B), and all pts were Child Pugh A at enrollment with median baseline alpha-fetoprotein (AFP) level 41.8 [3.8–917.2]; 4 pts received prior local therapies. A total of 91 cycles of therapy were administered; 2 pts received 27 and 43 cycles of treatment each. Six pts were evaluable for DLT; 2 pts were replaced for DLT assessment due to insufficient dose administered, unrelated to toxicity. No DLTs were observed at either the 50 or 100mg dose of BMS-986205. There were 24 treatment-related adverse events (TRAEs), 4 of which were Grade 3 events; there were no Grade 4-5 events. The most common TRAEs of all grades were AST elevation and ALT elevation in 3 pts, and diarrhea, maculopapular rash and increased alkaline phosphatase in 2 pts each. Grade 3 events were diarrhea and AST elevation (1 pt), and hyperglycemia and pancreatitis requiring treatment discontinuation (1 pt). Eight pts were evaluable for efficacy with best response of partial response in 1 pt (12.5%) and stable disease in 3 pts (37.5%), yielding a DCR of 50%. Median PFS was 8.5 weeks; median OS has not been reached. Conclusions: Combination BMS-986205 and nivolumab showed a manageable safety profile with durable benefit as 1st line therapy in a meaningful subset of patients with unresectable/metastatic HCC. Clinical trial information: NCT03695250.

NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for Non–Small Cell Lung Cancer (NSCLC) provide recommended management for patients with NSCLC, including diagnosis, primary treatment, surveillance for relapse, and subsequent treatment. Patients with metastatic lung cancer who are eligible for targeted therapies or immunotherapies are now surviving longer. This selection from the NCCN Guidelines for NSCLC focuses on targeted therapies for patients with metastatic NSCLC and actionable mutations.

Abstract Outcomes for marginal zone lymphoma (MZL) and follicular lymphoma (FL) remain suboptimal, owing to the limited number of approved agents and the incurable nature of the diseases. BGB-3111-AU-003 was a phase 1/2, open-label, multicenter, single-agent study of the selective Bruton’s tyrosine kinase inhibitor zanubrutinib in 385 patients with B-cell malignancies. Here, we present safety and efficacy outcomes for the 53 enrolled patients with relapsed/refractory MZL (n = 20) and relapsed/refractory FL (n = 33), all of whom were enrolled during the part 2 dose expansion, and therefore received zanubrutinib at the recommended phase 2 dose. Treatment with zanubrutinib was generally well tolerated, with most adverse events being ≤ grade 2. Atrial fibrillation/flutter was not reported. Two patients required dose reduction, and 4 patients discontinued treatment because of adverse events. Response was assessed by an independent review committee for MZL and the investigators for FL, per Lugano 2014 classification for non-Hodgkin lymphoma. In patients with MZL, the overall response rate (ORR) was 80%, and the complete response (CR) rate was 20%. With median follow-up of 33.8 months, median progression-free survival (PFS) was not reached. In patients with FL, the ORR was 36.4%, and the CR rate was 18.2%. After a median follow-up of 33.9 months, median PFS was 10.4 months. In conclusion, the results of this study suggest a favorable benefit–risk profile and support zanubrutinib as a potentially meaningful addition to available therapies for patients with relapsed/refractory MZL and FL. This trial was registered at www.clinicaltrials.gov as #NCT02343120.

379 Background: A single priming dose of T (anti-CTLA-4) added to D (anti-PD-L1) in the STRIDE (Single T Regular Interval D) regimen, formerly T300+D, showed encouraging clinical activity and limited toxicity in a phase 2 uHCC study (Study 22, NCT02519348), suggesting single exposure to T is sufficient to improve upon D activity. HIMALAYA (NCT03298451) evaluated the efficacy and safety of STRIDE or D vs sorafenib (S) in uHCC. Methods: HIMALAYA is an open-label, multicenter, phase 3 study, in which pts with uHCC and no prior systemic therapy were initially randomized to STRIDE (T 300 mg plus D 1500 mg [one dose] plus D 1500 mg every 4 weeks [Q4W]), D (1500 mg Q4W), S (400 mg twice daily), or T 75 mg Q4W (4 doses) plus D 1500 mg Q4W (T75+D). Recruitment to T75+D ceased after a planned analysis of Study 22 showed T75+D did not meaningfully differ from D. The primary objective was overall survival (OS) for STRIDE vs S. The secondary objective was OS noninferiority (NI) of D to S (NI margin: 1.08). Secondary endpoints included progression-free survival (PFS), objective response rate (ORR; RECIST v.1.1), duration of response (DoR), and safety. Results: In total, 1171 pts were randomized to STRIDE (N=393), D (N=389), or S (N=389). At data cutoff (DCO), the primary objective was met: OS was significantly improved for STRIDE vs S (hazard ratio [HR], 0.78; 96% confidence interval [CI], 0.65–0.92; p=0.0035; Table). D met the objective of OS NI to S (HR, 0.86; 96% CI, 0.73–1.03). ORRs were higher for STRIDE (20.1%) and D (17.0%) than for S (5.1%). No new safety signals were identified. Grade 3/4 treatment-related adverse events (TRAEs) occurred in 25.8% (STRIDE), 12.9% (D), and 36.9% (S) of pts. Grade 3/4 hepatic TRAEs occurred in 5.9% (STRIDE), 5.2% (D), and 4.5% (S) of pts. No TRAE of esophageal varices hemorrhage occurred. Rates of TRAEs leading to discontinuation were 8.2% (STRIDE), 4.1% (D), and 11.0% (S). Conclusions: HIMALAYA was the first large phase 3 trial with a diverse, representative uHCC population and extensive long-term follow-up to assess both mono- and combination immunotherapy. D was noninferior to S with favorable safety. The combination of a single priming dose of T plus D in STRIDE displayed superior efficacy and a favorable benefit-risk profile vs S. STRIDE is a proposed, novel, first-line standard of care systemic therapy for uHCC. Clinical trial information: NCT03298451. [Table: see text]

Abstract Purpose: Diffuse large B-cell lymphoma (DLBCL) is molecularly and clinically heterogeneous, and can be subtyped according to genetic alterations, cell-of-origin, or microenvironmental signatures using high-throughput genomic data at the DNA or RNA level. Although high-throughput proteomic profiling has not been available for DLBCL subtyping, MYC/BCL2 protein double expression (DE) is an established prognostic biomarker in DLBCL. The purpose of this study is to reveal the relative prognostic roles of DLBCL genetic, phenotypic, and microenvironmental biomarkers. Experimental Design: We performed targeted next-generation sequencing; IHC for MYC, BCL2, and FN1; and fluorescent multiplex IHC for microenvironmental markers in a large cohort of DLBCL. We performed correlative and prognostic analyses within and across DLBCL genetic subtypes and MYC/BCL2 double expressors. Results: We found that MYC/BCL2 double-high-expression (DhE) had significant adverse prognostic impact within the EZB genetic subtype and LymphGen-unclassified DLBCL cases but not within MCD and ST2 genetic subtypes. Conversely, KMT2D mutations significantly stratified DhE but not non-DhE DLBCL. T-cell infiltration showed favorable prognostic effects within BN2, MCD, and DhE but unfavorable effects within ST2 and LymphGen-unclassified cases. FN1 and PD-1–high expression had significant adverse prognostic effects within multiple DLBCL genetic/phenotypic subgroups. The prognostic effects of DhE and immune biomarkers within DLBCL genetic subtypes were independent although DhE and high Ki-67 were significantly associated with lower T-cell infiltration in LymphGen-unclassified cases. Conclusions: Together, these results demonstrated independent and additive prognostic effects of phenotypic MYC/BCL2 and microenvironment biomarkers and genetic subtyping in DLBCL prognostication, important for improving DLBCL classification and identifying prognostic determinants and therapeutic targets.

SummaryThe phase I/II AU‐003 study in patients with treatment‐naïve (TN) or relapsed/refractory (R/R) chronic lymphocytic leukaemia/small lymphocytic lymphoma demonstrated that zanubrutinib therapy results in clinically meaningful and durable responses with acceptable safety and tolerability. We report updated safety and efficacy data for 123 patients with a median follow‐up of 47·2 months. Patients received zanubrutinib 160 mg twice daily (81 patients), 320 mg once daily (40), or 160 mg once daily (two). Discontinuations due to adverse events or disease progression were uncommon. The overall response rate (ORR) was 95·9% (TN, 100%; R/R, 95%) with 18·7% achieving complete response (CR). Ongoing response at 3 years was reported in 85·7%. The ORR in patients with del(17p)/tumour protein p53 mutation was 87·5% (CR 16·7%). The 2‐ and 3‐year progression‐free survival estimates were 90% (TN, 90%; R/R, 91%) and 83% (TN, 81%; R/R, 83%) respectively. The most reported Grade ≥3 adverse events were neutropenia (15·4%), pneumonia (9·8%), hypertension (8·9%) and anaemia (6·5%). The annual incidence of atrial fibrillation, major haemorrhage, Grade ≥3 neutropenia and Grade ≥3 infection decreased over time. With a median follow‐up of ~4 years, responses remain clinically meaningful and durable and long‐term tolerability to zanubrutinib therapy continues.

Abstract Introduction: Multiple studies have demonstrated that diffuse large B-cell lymphoma (DLBCL) can be divided into subgroups based on their biology. However, these biological subgroups overlap clinically. While R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone) remains the standard of care for treating patients with DLBCL, predicting which patients will not benefit from such therapy is important so that alternative therapy or clinical trials can be considered. Most of the studies stratifying patients select biomarkers first, then explore how these biomarkers can stratify patients based on outcome. We explored the potential of using machine learning to first group patients with DLBCL based on survival, then isolating the biomarkers necessary for predicting these survival subgroups. Methods: RNA was extracted from tissue paraffin blocks from 379 R-CHOP treated patients with de novo DLBCL, and from 247 patients with extranodal DLBCL. A targeted hybrid capture RNA panel of 1408 genes was used for next generation sequencing (NGS). Sequencing was performed using an Illumina NextSeq 550 System platform. Ten million reads per sample in a single run were required, and the read length was 2 × 150 bp. An expression profile was generated from the sequencing coverage profile of each individual sample using Cufflinks. A machine learning system was developed to classify patients into four groups based on their overall survival. This machine learning approach based on Naïve Bayesian algorithm was also used to discover the relevant subset of genes with which to classify patients into each of the four survival groups. To eliminate the underflow problem commonly associated with the standard Naïve Bayesian classifiers, we applied Geometric Mean Naïve Bayesian (GMNB) as the classifier to predict the survival group for each patient. Results: Using machine learning, patients were first divided into two groups: short survival (S) and long survival (L). To refine this model, we used the same approach and divided the patients in each group into two subgroups, generating four groups: long survival in the long group (LL), short survival in the long group (LS), long survival in the short group (SL), and short survival in the short group (SS). The hazard ratio for this model was 0.174 (confidence interval: 0.120-0.251), and P-value <0.0001. After defining these four groups, a machine learning algorithm was used to discover the biomarkers from the expression data of the 1408 genes from NGS data. To reduce the effects of noise and avoid overfitting, we employed a 12-step cross validation to obtain a robust measure. For an individual gene, a generalized Naïve Bayesian classifier was constructed on the training of one of the 12 subsets and tested on the other 11 testing subsets. This allowed us to limit the prediction process to 60 genes for each separation step. Using the selected biomarkers, we classified the patients in the original set (379 patients) into LL, LS, SL, and SS groups and then evaluated the survival pattern of these groups. As shown in Fig. 1A, the selected biomarkers predicted survival as expected in the overall survival groups prior to biomarker selection. For additional validation of the system, we used the selected biomarkers to classify a completely new set of 247 samples of patients with extranodal DLBCL. As shown in Fig. 1B, these selected biomarkers successfully predicted the overall survival in this group of patients with an HR of 0.530 (confidence interval: 0.234-1.197, P=0.005). This classification correlated with cell of origin classification, TP53 mutation status, MYC expression, and IRF4 expression. However, in a multivariate analysis, only TP53 mutation was independent in predicting prognosis (P=0.005) and age (below or over 60) (P=0.01) along with the survival grouping (P<0.000001). Conclusions: Using a novel machine learning approach with the expression levels of 180 genes, we developed a model that can reliably stratify patients with DLBCL treated with R-CHOP into four survival subgroups. This model can be used to identify patients who may not respond well to R-CHOP to be considered for alternative therapy and clinical trials. Figure 1 Figure 1. Disclosures Hsi: AbbVie Inc, Eli Lilly: Research Funding. Ferreri: Ospedale San Raffaele srl: Patents & Royalties; BMS: Research Funding; Pfizer: Research Funding; Beigene: Research Funding; Hutchison Medipharma: Research Funding; Amgen: Research Funding; Genmab: Research Funding; ADC Therapeutics: Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Membership on an entity's Board of Directors or advisory committees, Research Funding; PletixaPharm: Membership on an entity's Board of Directors or advisory committees; x Incyte: Membership on an entity's Board of Directors or advisory committees; Adienne: Membership on an entity's Board of Directors or advisory committees. Piris: Millenium/Takeda, EUSA, Jansen, NanoString, Kyowa Kirin, Gilead and Celgene.: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Winter: BMS: Other: Husband: Data and Safety Monitoring Board; Actinium Pharma: Consultancy; Janssen: Other: Husband: Consultancy; Agios: Other: Husband: Consultancy; Gilead: Other: Husband: Consultancy; Epizyme: Other: Husband: Data and Safety Monitoring Board; Ariad/Takeda: Other: Husband: Data and Safety Monitoring Board; Merck: Consultancy, Honoraria, Research Funding; Novartis: Other: Husband: Consultancy, Data and Safety Monitoring Board; Karyopharm (Curio Science): Honoraria.

ObjectiveThe relative risk of SARS–CoV‐2 infection and COVID‐19 disease severity among people with rheumatic and musculoskeletal diseases (RMDs) compared to those without RMDs is unclear. This study was undertaken to quantify the risk of SARS–CoV‐2 infection in those with RMDs and describe clinical outcomes of COVID‐19 in these patients.MethodsWe conducted a systematic literature review using 14 databases from January 1, 2019 to February 13, 2021. We included observational studies and experimental trials in RMD patients that described comparative rates of SARS–CoV‐2 infection, hospitalization, oxygen supplementation/intensive care unit (ICU) admission/mechanical ventilation, or death attributed to COVID‐19. Methodologic quality was evaluated using the Joanna Briggs Institute critical appraisal tools or the Newcastle‐Ottawa scale. Risk ratios (RRs) and odds ratios (ORs) with 95% confidence intervals (95% CIs) were calculated, as applicable for each outcome, using the Mantel‐Haenszel formula with random effects models.ResultsOf the 5,799 abstracts screened, 100 studies met the criteria for inclusion in the systematic review, and 54 of 100 had a low risk of bias. Among the studies included in the meta‐analyses, we identified an increased prevalence of SARS–CoV‐2 infection in patients with an RMD (RR 1.53 [95% CI 1.16–2.01]) compared to the general population. The odds of hospitalization, ICU admission, and mechanical ventilation were similar in patients with and those without an RMD, whereas the mortality rate was increased in patients with RMDs (OR 1.74 [95% CI 1.08–2.80]). In a smaller number of studies, the adjusted risk of outcomes related to COVID‐19 was assessed, and the results varied; some studies demonstrated an increased risk while other studies showed no difference in risk in patients with an RMD compared to those without an RMD.ConclusionPatients with RMDs have higher rates of SARS–CoV‐2 infection and an increased mortality rate.