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PurposeThis randomized, multicenter, open-label, phase Ib/II study assessed durvalumab and tremelimumab in combination or as monotherapy for chemotherapy-refractory gastric cancer or gastroesophageal junction (GEJ) cancer.Patients and methodsSecond-line patients were randomized 2:2:1 to receive durvalumab plus tremelimumab (arm A), or durvalumab (arm B) or tremelimumab monotherapy (arm C), and third-line patients received durvalumab plus tremelimumab (arm D). A tumor-based IFNγ gene signature was prospectively evaluated as a potential predictive biomarker in second- and third-line patients receiving the combination (arm E). The coprimary endpoints were objective response rate and progression-free survival (PFS) rate at 6 months.ResultsA total of 113 patients were treated: 6 in phase Ib and 107 (arm A, 27; arm B, 24; arm C, 12; arm D, 25; arm E, 19) in phase II. Overall response rates were 7.4%, 0%, 8.3%, 4.0%, and 15.8% in the five arms, respectively. PFS rates at 6 months were 6.1%, 0%, 20%, 15%, and 0%, and 12-month overall survival rates were 37.0%, 4.6%, 22.9%, 38.8%, and NA, respectively. Treatment-related grade 3/4 adverse events were reported in 17%, 4%, 42%, 16%, and 11% of patients, respectively.ConclusionsResponse rates were low regardless of monotherapy or combination strategies. No new safety signals were identified. Including use of a tumor-based IFNγ signature and change in baseline and on-treatment circulating tumor DNA are clinically feasible and may be novel strategies to improve treatment response in this difficult-to-treat population.

Pharmacometric models were used to investigate the utility of biomarkers in predicting the efficacy (Crohn's Disease Activity Index [CDAI]) of brazikumab and provide a data‐driven framework for precision therapy for Crohn's disease (CD). In a phase IIa trial in patients with moderate to severe CD, treatment with brazikumab, an anti‐interleukin 23 monoclonal antibody, was associated with clinical improvement. Brazikumab treatment effect was determined to be dependent on the baseline IL‐22 (BIL22) or baseline C‐reactive protein (BCRP; predictive biomarkers), and placebo effect was found to be correlated with the baseline CDAI (a prognostic biomarker). A maximal total inhibition on CDAI input function of 50.6% and 42.4% was predicted for patients with extremely high BIL22 or BCRP, compared to a maximal total inhibition of 20.9% and 17.8% for patients with extremely low BIL22 or BCRP, respectively, which were mainly due to the placebo effect. We demonstrated that model‐derived baseline biomarker levels that achieve 50% of maximum unbound systemic concentration of 22.8 pg/mL and 8.03 mg/L for BIL22 and BCRP as the cutoffs to select subpopulations can effectively identify high‐response subgroup patients with improved separation of responders when compared to using the median values as the cutoff. This work exemplifies the utility of pharmacometrics to quantify biomarker‐driven responses in biologic therapies and distinguish between predictive and prognostic biomarkers, complementing clinical efforts of identifying subpopulations with higher likelihood of response to brazikumab. [ABSTRACT FROM AUTHOR]

It has recently been demonstrated that memory B cells can reenter and reengage germinal center (GC) reactions, opening the possibility that multi-hit lymphomagenesis gradually occurs throughout life during successive immunological challenges. Here, we investigated this scenario in follicular lymphoma (FL), an indolent GC-derived malignancy. We developed a mouse model that recapitulates the FL hallmark t(14;18) translocation, which results in constitutive activation of antiapoptotic protein B cell lymphoma 2 (BCL2) in a subset of B cells, and applied a combination of molecular and immunofluorescence approaches to track normal and t[(14;18).sup.+] memory B cells in human and BCL2-overexpressing B cells in murine lymphoid tissues. BCL2-overexpressing B cells required multiple GC transits before acquiring FL-associated developmental arrest and presenting as GC B cells with constitutive activation-induced cytidine deaminase (AID) mutator activity. Moreover, multiple reentries into the GC were necessary for the progression to advanced precursor stages of FL. Together, our results demonstrate that protracted subversion of immune dynamics contributes to early dissemination and progression of t[(14;18).sup.+] precursors and shapes the systemic presentation of FL patients., Introduction Germinal centers (GCs) represent critical sites within lymphoid tissues, where B cell responses to antigen are amplified and refined through the mechanism of affinity maturation (1). Recently, key dynamic [...]

Purpose: Tumor mutational burden (TMB) has been shown to be predictive of survival benefit in patients with non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors. Measuring TMB in the blood (bTMB) using circulating cell-free tumor DNA (ctDNA) offers practical advantages compared with TMB measurement in tissue (tTMB); however, there is a need for validated assays and identification of optimal cutoffs. We describe the analytic validation of a new bTMB algorithm and its clinical utility using data from the phase III MYSTIC trial., Patients and Methods: The dataset used for the clinical validation was from MYSTIC, which evaluated first-line durvalumab (anti-PD-L1 antibody) ± tremelimumab (anticytotoxic T-lymphocyte-associated antigen-4 antibody) or chemotherapy for metastatic NSCLC. bTMB and tTMB were evaluated using the GuardantOMNI and FoundationOne CDx assays, respectively. A Cox proportional hazards model and minimal P value cross-validation approach were used to identify the optimal bTMB cutoff., Results: In MYSTIC, somatic mutations could be detected in ctDNA extracted from plasma samples in a majority of patients, allowing subsequent calculation of bTMB. The success rate for obtaining valid TMB scores was higher for bTMB (809/1,001; 81%) than for tTMB (460/735; 63%). Minimal P value cross-validation analysis confirmed the selection of bTMB ≥20 mutations per megabase (mut/Mb) as the optimal cutoff for clinical benefit with durvalumab + tremelimumab., Conclusions: Our study demonstrates the feasibility, accuracy, and reproducibility of the GuardantOMNI ctDNA platform for quantifying bTMB from plasma samples. Using the new bTMB algorithm and an optimal bTMB cutoff of ≥20 mut/Mb, high bTMB was predictive of clinical benefit with durvalumab + tremelimumab versus chemotherapy., (©2020 American Association for Cancer Research.)