Citations

65 Background: The addition of chemotherapy to immune checkpoint inhibitors has been explored clinically in solid tumors in order to overcome one of the challenges of immunotherapy: clinical outcomes are variable, with only a subset of patients achieving durable responses. Further understanding of the immunoregulatory mechanisms of chemotherapy in the setting of immunotherapy is crucial for the development of optimal combinatorial chemo-immunotherapeutic strategies to improve clinical outcomes in patients with advanced cancer. Methods: Metastatic melanoma (MM) patients who failed anti-PD-1 single therapy were subsequently treated with paclitaxel and carboplatin in addition to PD-1 blockade. Using peripheral blood (PB) from MM patients and healthy donor, the phenotypic and functional changes in T cells induced by chemotherapy, in the setting of PD-1 blockade, were examined. Results: Paclitaxel and carboplatin, in combination with PD-1 blockade, were able to induce significant clinical responses in a subset of MM patients who were resistant to anti-PD-1 therapy alone. In patients who responded to this combination, a subset of tumor-reactive effector T cells (CD8+CD11a+PD1+GranzymeB+) survived the treatment, with increased frequency after the addition of chemotherapy. This T cell population preserved its effector phenotype, although ongoing PD-1 blockade was needed to improve its anti-tumor activity. In vitro experiments, using CD8+CD11a+PD1+GranzymeB+isolated from healthy donor PB, also demonstrated its ability to survive chemotherapy treatment. In addition, after cultured with chemotherapy, this T cell subset demonstrated higher cytotoxic T cell functions as well as increased chemotherapy efflux. Conclusions: Chemotherapy regulates a subset of tumor-reactive effector T cells (CD8+CD11a+PD1+GranzymeB+) and increases clinical efficacy of PD-1 blockade. This novel effector T cell population underlies the key cellular and molecular immunoregulatory mechanisms of chemotherapy. It serves as a meaningful marker to measure these collaborative effects and to develop the optimal chemo-immunotherapy strategy to improve clinical responses to current immune checkpoint blocking agents.

PurposeThe dose‐averaged linear energy transfer (LETd) for intensity‐modulated proton therapy (IMPT) calculated by one‐dimensional (1D) analytical models deviates from more accurate but time‐consuming Monte Carlo (MC) simulations. We developed a fast hybrid three‐dimensional (3D) analytical LETd calculation that is more accurate than 1D analytical model.MethodsWe used the Geant4 MC code to generate 3D LETd distributions of monoenergetic proton beams in water for all energies and used a customized error function to fit the LETd lateral profiles at various depths to the MC simulation. The 3D LETd calculation kernel was a lookup table of these fitted coefficients, and LETd was determined directly from spot energies and voxel coordinates during analytical dose calculations. We validated our new method by comparing the calculated LETd distributions to MC results using 3D Gamma index analysis with 3%/2 mm criteria in 12 patient geometries. The significance of the improvement in Gamma index analysis passing rates over the 1D analytical model was determined using the Wilcoxon rank‐sum test.ResultsThe passing rate of 3D Gamma analysis comparing LETd distributions from the hybrid 3D method and the 1D method to MC simulations was significantly improved from 94.0% ± 2.5% to 98.0% ± 1.0% (P = 0.0003). The typical time to calculate dose and LETd simultaneously using an Intel Xeon E5‐2680 2.50 GHz workstation was approximately 2.5 min.ConclusionsOur new method significantly improved the LETd calculation accuracy compared to the 1D method while maintaining significantly shorter calculation time even comparing with the GPU‐based fast MC code.

Purpose: To describe and validate the dose calculation algorithm of an independent second-dose check software for spot scanning proton delivery systems with full width at half maximum between 5 and 14 mm and with a negligible spray component. Methods: The analytical dose engine of our independent second-dose check software employs an altered pencil beam algorithm with 3 lateral Gaussian components. It was commissioned using Geant4 and validated by comparison to point dose measurements at several depths within spread-out Bragg peaks of varying ranges, modulations, and field sizes. Water equivalent distance was used to compensate for inhomogeneous geometry. Twelve patients representing different disease sites were selected for validation. Dose calculation results in water were compared to a fast Monte Carlo code and ionization chamber array measurements using dose planes and dose profiles as well as 2-dimensional–3-dimensional and 3-dimensional–3-dimensional γ-index analysis. Results in patient geometry were compared to Monte Carlo simulation using dose–volume histogram indices, 3-dimensional–3-dimensional γ-index analysis, and inpatient dose profiles. Results: Dose engine model parameters were tuned to achieve 1.5% agreement with measured point doses. The in-water γ-index passing rates for the 12 patients using 3%/2 mm criteria were 99.5% ± 0.5% compared to Monte Carlo. The average inpatient γ-index analysis passing rate compared to Monte Carlo was 95.8% ± 2.9%. The average difference in mean dose to the clinical target volume between the dose engine and Monte Carlo was −0.4% ± 1.0%. For a typical plan, dose calculation time was 2 minutes on an inexpensive workstation. Conclusions: Following our commissioning process, the analytical dose engine was validated for all treatment sites except for the lung or for calculating dose–volume histogram indices involving point doses or critical structures immediately distal to target volumes. Monte Carlo simulations are recommended for these scenarios.

Background: Multiple myeloma (MM) is common among the elderly, with 35% of patients (pts) diagnosed being aged ≥75 years (y). With increasing overall life expectancy, the incidence and prevalence of newly diagnosed and previously treated MM patients ≥80 y is expected to increase over time. Because elderly pts are often excluded from clinical trials, data focused on their treatment patterns and clinical outcomes are lacking. The Connect® MM Registry (NCT01081028) is a large, US, multicenter, prospective observational cohort study of pts with newly diagnosed MM (NDMM) designed to examine real-world diagnostic patterns, treatment patterns, clinical outcomes, and health-related quality of life patient-reported outcomes. This analysis reviews treatment patterns and outcomes in elderly pts from the Connect MM Registry. Methods: Pts enrolled in the Connect MM registry at 250 community, academic, and government sites were included in this analysis. Eligible pts were adults aged ≥18 y with symptomatic MM diagnosed ≤2 months before enrollment, as defined by International Myeloma Working Group criteria; no exclusion criteria were applied. For this analysis, pts were categorized into 4 age groups: <65, 65 to 74, 75 to 84, and ≥85 y. Pts were followed from time of enrollment to the earliest of disease progression (or death), loss to follow-up, or data cutoff date of February 7, 2019. Descriptive statistics were used for baseline characteristics and treatment regimens. Survival outcomes were analyzed using Cox regression. Time to progression (TTP) analysis excluded causes of death not related to MM. Results: Of 3011 pts enrolled (median age 67 y), 132 (4%) were aged ≥85 y, and 615 (20%) were aged 75-84 y at baseline. More pts aged ≥85 y had poor prognostic factors such as ISS stage III disease and reduced hemoglobin (<10 g/dL or >2 g/dL <LLN) compared with other age groups, although no notable differences between creatinine and calcium levels were observed across age groups (Table). A lower proportion of elderly pts (75-84 and ≥85 y) received triplet regimens as frontline therapy. More elderly pts received a single novel agent, whereas use of 2 novel agents was more common in younger pts (Table). The most common frontline regimens among elderly pts were bortezomib (V) + dexamethasone (D), followed by lenalidomide (R) + D, whereas those among younger pts included RVD, followed by VD and CyBorD (Table). No pt aged ≥85 y, and 4% of pts aged 75-84 y received high-dose chemotherapy and autologous stem cell transplant (vs 61% in the <65 y and 37% in the 65-74 y age group). The most common maintenance therapy was RD in pts ≥85 y (although the use was low) and R alone in other age groups (Table). In the ≥85 y group, 27%, 10%, and 4% of pts entered 2L, 3L, and 4L treatments respectively, vs 43%, 23%, and 13% in the <65 y group. Progression-free survival was significantly shorter in the ≥85 y age group vs the 75-84 y age group (P=0.003), 65-74 y age group (P<0.001), and <65 y age group (P<0.001; Fig.1). TTP was significantly shorter in the ≥85 y group vs the <65 y group (P=0.020); however, TTP was similar among the 65-74 y, 75-84 y, and ≥85 y cohorts (Fig. 2). Overall survival was significantly shorter in the ≥85 y group vs the 75-84 y, 65-74 y, and <65 y groups (all P<0.001; Fig. 3). The mortality rate was lowest (46%) during first-line treatment (1L) in pts aged ≥85 y (mainly attributed to MM progression) and increased in 2L and 3L (47% and 54%, respectively); a similar trend was observed in the younger age groups. The main cause of death was MM progression (29% in the ≥85 y vs 16% in the <65 y group). Other notable causes of death in the ≥85 y group included cardiac failure (5% vs 2% in <65 y group) and pneumonia (5% vs 1% in <65 y group). Conclusions: In this analysis, elderly pts received similar types of frontline and maintenance regimens as younger pts, although proportions varied with decreased use of triplet regimens with age. Considering similarities in TTP across the 65-74 y, 75-84 y, and ≥85 y cohorts, these real-world data support active treatment and aggressive supportive care of elderly symptomatic pts, including with novel agents. Additionally, further clinical studies specific to elderly patients with MM should be explored. Disclosures Lee: Amgen: Consultancy, Research Funding; GlaxoSmithKline plc: Research Funding; Sanofi: Consultancy; Daiichi Sankyo: Research Funding; Celgene: Consultancy, Research Funding; Takeda: Consultancy, Research Funding; Janssen: Consultancy, Research Funding. Ailawadhi:Janssen: Consultancy, Research Funding; Takeda: Consultancy; Pharmacyclics: Research Funding; Amgen: Consultancy, Research Funding; Celgene: Consultancy; Cellectar: Research Funding. Gasparetto:Celgene: Consultancy, Honoraria, Other: Travel, accommodations, or other expenses paid or reimbursed ; Janssen: Consultancy, Honoraria, Other: Travel, accommodations, or other expenses paid or reimbursed ; BMS: Consultancy, Honoraria, Other: Travel, accommodations, or other expenses paid or reimbursed . Jagannath:AbbVie: Consultancy; Merck & Co.: Consultancy; Bristol-Myers Squibb: Consultancy; Karyopharm Therapeutics: Consultancy; Celgene Corporation: Consultancy; Janssen Pharmaceuticals: Consultancy. Rifkin:Celgene: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees. Durie:Amgen, Celgene, Johnson & Johnson, and Takeda: Consultancy. Narang:Celgene: Speakers Bureau. Terebelo:Celgene: Honoraria; Jannsen: Speakers Bureau; Newland Medical Asociates: Employment. Toomey:Celgene: Consultancy. Hardin:Celgene: Membership on an entity's Board of Directors or advisory committees. Wagner:Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; American Cancer Society: Other: Section editor, Cancer journal. Omel:Celgene, Takeda, Janssen: Other: Patient Advisory Committees. Srinivasan:Celgene: Employment, Equity Ownership. Liu:TechData: Consultancy. Dhalla:Celgene: Employment. Agarwal:Celgene Corporation: Employment, Equity Ownership. Abonour:BMS: Consultancy; Celgene: Consultancy, Research Funding; Takeda: Consultancy, Research Funding; Janssen: Consultancy, Research Funding.

Background: Progress in genome technology allows analysis of previously completed trials to identify subgroups potentially benefiting from therapy. Enzastaurin is a potent inhibitor of protein kinase C beta (PKC-β) and suppresses the phosphoinositide 3-kinase (PI3K)/AKT pathway. The safety and efficacy of Enzastaurin has been tested in more than 60 clinical trials including 2 major studies in DLBCL: (1) PRELUDE (A phase III maintenance trial of Enzastaurin vs Placebo, N=758) (Crump, 2016), and (2) S028 (A randomized phase II study of Enzastaurin/R-CHOP vs R-CHOP in frontline intermediate/high-risk DLBCL, N=101) (Hainsworth, 2016). DNA samples extracted from blood of patients from PRELUDE were retrospectively genotyped using whole genome SNP arrays. From the genome wide screening a novel genetic biomarker, DGM1, was identified showing high correlation with response to Enzastaurin treatment (Luo, ASH 2018). Importantly, these findings were replicated in the phase II S028 study. In the S028 study the hazard ratio (HR) for OS in high-risk (IPI ≥ 3) DGM1 positive (+) patients who received Enzastaurin/R-CHOP was 0.28 (0.1-0.81) when compared to subjects who received R-CHOP, a benefit favoring Enzastaurin (p=0.018). These data suggest that addition of Enzastaurin to R-CHOP may significantly improve outcome in frontline high-risk DGM1 (+) DLBCL. The ENGINE study was initiated to validate this finding in a prospective study. Study Design and Methods: Adult patients must have untreated CD20+ DLBCL, IPI ≥ 3. Patients are randomized 1:1 to Enzastaurin/R-CHOP or Placebo/R-CHOP for 6 cycles during combination phase. Each subject's treatment assignment will be unblinded after response assessment at the end of the combination phase. Subjects randomized to the investigational arm who have a complete or partial response will have the option to continue in the single agent phase to receive Enzastaurin for up to 2 additional years. The study intends to enroll approximately 235 patients with primary endpoint of OS in DGM1 (+) patients. The study is ongoing with 57 sites open in the US and China. As of 20 July 2019, 128 patients have been randomized. Clinical trial information: NCT03263026. Disclosures Nowakowski: Genentech, Inc.: Research Funding; Curis: Research Funding; Bayer: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; F. Hoffmann-La Roche Ltd: Research Funding; Selvita: Membership on an entity's Board of Directors or advisory committees; NanoString: Research Funding; MorphoSys: Consultancy, Research Funding. Brody:Acerta Pharma: Research Funding; Merck: Research Funding; Celldex Therapeutics: Research Funding; Genentech: Research Funding; Oncovir, Inc.: Research Funding; BMS: Research Funding; Kite Pharma: Research Funding. Lue:Kymera Therapeutics: Honoraria; Astex Pharmaceuticals: Honoraria. Luo:Denovo Biopharma LLC: Employment, Equity Ownership, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties. Zhang:Denovo Biopharma LLC: Employment. Han:Denovo Biopharma LLC: Employment. Jivani:TRACON Pharmaceuticals, Inc.: Other: Stock; Denovo Biopharma LLC: Employment. Liu:Denovo Biopharma LLC: Employment. Li:Denovo Biopharma LLC: Employment. Sun:Novartis: Other: Stock; Denovo Biopharma LLC: Employment.

AbstractPurposeWe conducted a phase 1/2 trial of the poly(ADP‐ribose) polymerase 1/2 inhibitor talazoparib in combination with low‐dose temozolomide (TMZ) to determine the dose‐limiting toxicities (DLTs), recommended phase 2 dose (RP2D), and pharmacokinetics of this combination in children with recurrent/refractory solid tumors; and to explore clinical activity in Ewing sarcoma (EWS) (NCT02116777).MethodsTalazoparib (400‐600 µg/m2/dose, maximum daily dose 800‐1000 µg) was administered q.d. or b.i.d. orally on day 1 followed by q.d. dosing concomitant with q.d. dosing of oral TMZ (20‐55 mg/m2/day) on days 2 to 6, every 28 days.ResultsForty patients, aged 4 to 25 years, were enrolled. Talazoparib was increased to 600 µg/m2/dose b.i.d. on day 1, and q.d. thereafter, with 20 mg/m2/day of TMZ, without DLTs. TMZ was subsequently increased, during which dose‐limiting neutropenia and thrombocytopenia occurred in two of three subjects at 55 mg/m2/day, two of six subjects at 40 mg/m2/day, and one of six subjects at 30 mg/m2/day. During dose‐finding, two of five EWS and four of 25 non‐EWS subjects experienced prolonged stable disease (SD), and one subject with malignant glioma experienced a partial response. In phase 2, 0 of 10 EWS subjects experienced an objective response; two experienced prolonged SD.ConclusionsTalazoparib and low‐dose TMZ are tolerated in children with recurrent/refractory solid tumors. Reversible neutropenia and thrombocytopenia were dose limiting. The RP2D is talazoparib 600 µg/m2 b.i.d. on day 1 followed by 600 µg/m2 q.d. on days 2 to 6 (daily maximum 1000 µg) in combination with temozolomide 30 mg/m2/day on days 2 to 6. Antitumor activity was not observed in EWS, and limited antitumor activity was observed in central nervous system tumors.

Introduction: It is known that overexpression of DNA methyltransferases (e.g., DNMT1) is frequent and changes of DNA cytosine methylation (5mC) are a constant feature of cancers. DNA methylation inhibitors, such as 5-aza-2'-deoxycytidine (Dec), have been in clinics for patients with leukemia. It is classically believed that promoter hypomethylation coupled by reexpression of epigenetically-suppressed tumor suppressors is a core mechanism behind Dec-impaired leukemia cell growth. However, the fact that global DNA methylation profiling barely predicts Dec-response suggests a demethylation-independent mechanism of Dec-induced cell death. N6-methyladenine (m6A) has been identified recently as an abundant DNA modification in eukaryotes (Wu, Nature 2016;532:329). Importantly, m6A is extensively present in the human genome, and m6A abundance is associated with tumorigenesis (Xie, Cell 2018;71:306). Furthermore, the DNA m6A is dynamically modulated by the methyltransferases (i.e., METTL3, N6AMT1) and demethylases (i.e., ALKBH1), and changes in m6A predict gene expression (Wu, Nature 2016;532:329). Given a potential crosstalk between m6A and distinct epigenetic mechanisms (Yao, Nat. Commun 2017;8:1122), we hypothesized that the anticancer actions of Dec may partially result from changes in DNA m6A in leukemia cells. Methods: Protein expression of target genes was assessed by Western blotting. The levels of DNA cytosine methylation (5mC) and N6-methyladenine (m6A) were measured by dotblotting or liquid chromatography-mass spectrometry (LC-MS/MS). The cell viability and apoptosis were determined by the Cell Counting Kit 8 (CCK8) assays as well as the Annexin V/Propidium Iodide staining and flow cytometry. The peripheral blood mononuclear cells (PBMCs) of leukemia patients from Mayo Clinic were prepared by Ficoll-Hypaque gradient centrifugation. Results: To test our hypothesis, leukemia cells, Kasumi-1, MV4-11, K562 and KU812, were exposed to 2 µM Dec, a clinical achievable concentration, for 72 hours. As expected, Dec treatment led to a downregulation of DNMT1 and DNMT3a, a reduction of 5mC levels by dotblotting using anti-5mC antibody, a blockage of cell proliferation and a promotion of cell apoptosis. When genomic DNA was subjected to dotblotting using anti-m6A antibody, the results revealed a marked decrease of DNA m6A levels in all Dec-treated cells. Then genomic DNA from K562 and MV4-11 cells was enzymatically digested to 2'-deoxynucleosides. dA was quantified by HPLC-UV, while the amount of m6A was measured by isotope dilution HPLC-ESI-MS/MS using 15N labeled internal standard. The standard curves were generated using pure standards, from which the m6A/A ratio was calculated. In agreement with dotblotting results, Dec treatment significantly decreased DNA m6A abundance in both cell lines. Mechanistically, exposure to Dec led to a consistent increase of demethylase fat mass and obesity-associated protein (FTO), but not METTL3 nor ALKBH1 and ALKBH5. Further, knockdown of FTO increased DNA m6A, which was further confirmed by treatment with FTO inhibitors rhein and meclofenamic acid (MA). These data indicate that FTO may be responsible for Dec-induced m6A changes in leukemia cells. To investigate the clinical implications of DNA m6A, we obtained PBMCs from AML patients (n = 10), who received Dec therapy (20 mg/m2 daily for 5 days every 4 weeks) in Mayo Clinic. These PBMCs were further cultured for 48 hours, frozen and stored in 100% ethanol before DNA extraction. The results from dotblotting using anti-5mC or anti-m6A showed that a trend of decrease in both m6A and 5mC abundance is observed, and the pattern of changes in m6A and 5mC displays a positive correlation. Finally, exposure of leukemia cells to the combination of Dec (2 µM) with FTO inhibitor MA (50 µM) induced more cell apoptosis and greater inhibition on cell proliferation as compared to single agent in vitro, supporting FTO inhibitors as new therapeutic agents in leukemia. Conclusion: Our studies suggest that the FTO-DNA m6A axis may partially mediate the therapeutic outcomes of Dec in leukemia. Our findings provide a new mechanistic paradigm for the anticancer activities of Dec, and define the m6A methylation status in leukemia cells as a new pharmacodynamic marker for their response to Dec-based therapy, pointing to a novel treatment strategy for incorporating m6A modulators to enhance the therapeutic index of Dec. Disclosures Al-Kali: Astex Pharmaceuticals, Inc.: Research Funding.