{'fraction_non_alphanumeric': 0.0493808517064331, 'fraction_numerical': 0.018574448807006948, 'mean_word_length': 5.544466403162056, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Circulating DNA for Molecular Response Prediction, Characterization of Resistance Mechanisms and Quantification of CAR T-Cells during Axicabtagene Ciloleucel Therapy

Background: Anti-CD19 chimeric antigen receptor (CAR19) T-cells have significant activity in patients with relapsed/refractory DLBCL (rrDLBCL). While the majority of rrDLBCL patients receiving axicabtagene ciloleucel (Axi-cel)achieve complete responses, a significant subset of patients experience disease progression (Locke FL, et al. Lancet Oncol. 2019). Circulating tumor DNA (ctDNA) analysis has demonstrated utility for predicting therapeutic benefit in DLBCL, as well as for detecting emergent resistance mechanisms to targeted therapies. Here we apply cell-free DNA (cfDNA) analysis to patients receiving Axi-cel, to characterize molecular responses, resistance mechanisms, and to track CAR19 cells.
 Methods: We performed Cancer Personalized Profiling by Deep Sequencing (CAPP-Seq) on DNA from germline and plasma samples collected prior to CAR T-cell infusion, multiple time-points post infusion, and, where available, at the time of relapse from 30 patients receiving Axi-cel for rrDLBCL at Stanford University. We designed a novel hybrid-capture panel and analysis pipeline designed to detect both tumor variants, as well as Axi-cel specific recombinant retroviral sequences to quantify CAR19 levels in cfDNA. Tumor variants were identified prior to and following Axi-cel therapy to assess for emergent variants, and Axi-cel specific sequences were quantified.
 Results: The median follow-up for the 30 patients after Axi-cel infusion was 10 months, with 47% (14/30) of patients experiencing disease progression after Axi-cel therapy. We identified an average of 164.3 SNVs per case (range:1-685) before Axi-cel therapy; the most common coding variants identified at baseline were in MLL2 (29.2%), BCL2 (22.5%), and TP53 (19.3%). When treated as a continuous variable, pretreatment ctDNA levels were prognostic of PFS (HR 2.16, 95% CI 1.11-4.21, P=0.02). Using a previously established ctDNA threshold to stratify disease burden (2.5 log10(hGE/mL); Kurtz et al. JCO 2018), we observed significantly superior PFS in patients with low pretreatment ctDNA levels treated with Axi-cel (Fig. 1A). In the majority of Axi-cel treated patients (62.9%), ctDNA was detectable at day 28, and PFS was significantly longer in patients with undetectable ctDNA at this time-point (Fig. 1B). Multiple putative resistance mechanisms were identified at relapse after Axi-cel, including emergent variants in CD19, HVEM, and TP53, as well as copy number gains in PD-L1 (Fig. 1C). For example, in one patient, a CD19 stop-gain mutation, which was not detected prior to treatment or at the time of the first interim PET scan, emerged at the time of relapse (Fig. 1D). Finally, we found cfDNA evidence for Axi-cel DNA in 74% of patients 28 days after therapy, including in patients without evidence of circulating CAR T-cells in PBMCs. Axi-cel levels in cfDNA as measured by CAPP-Seq were significantly correlated with CAR19 flow cytometry (Pearson r=0.55, P=.015; Fig. 1E).
 Conclusions: Baseline and interim ctDNA measurements have prognostic significance in DLBCL patients being treated with CAR19 T-cells, and potential emergent resistance mutations, including in CD19, can be identified in patients via cfDNA analysis. Quantification of CAR19 T-cells using cfDNA is significantly correlated with flow cytometric quantification, indicating that these cells can be quantified via cfDNA. Taken together, these data indicate that cfDNA analysis is a powerful tool for predicting response to CAR19 therapy, identifying genomic determinants of resistance and quantifying CAR19 cells, which may in turn inform the next therapeutic steps.
 Figure 1: A) Kaplan Meier analysis of PFS, with patients stratified based on pre-Axi-cel therapy ctDNA level, above and below a previously established threshold (2.5 log10[haploid Genome Equivalents/mL]). B) A Kaplan Meier plot depicting PFS stratification for patients with detectable versus undetectable ctDNA at day 28 after Axi-cel infusion. C) Oncoprint depicting selected emergent and baseline tumor variants in progressors and non-progressors after Axi-cel therapy. D) Change in mean ctDNA variant allele frequency (VAF) and emergence of a CD19 stop-gain mutation (CD19 pTrpX) at the time of relapse in a patient who initially achieved a CR at day 28 after CAR19 infusion. E) Relationship between CAR19 T-cell quantification by cfDNA and flow cytometry. (ND: Not detected)
 
 
 
 Kurtz: Roche: Consultancy. Chabon:Lexent Bio Inc: Consultancy. Khodadoust:Corvus Pharmaceuticals: Research Funding. Majzner:Xyphos Inc.: Consultancy; Lyell Immunopharma: Consultancy. Mackall:Obsidian: Research Funding; Lyell: Consultancy, Equity Ownership, Other: Founder, Research Funding; Nektar: Other: Scientific Advisory Board; PACT: Other: Scientific Advisory Board; Bryologyx: Other: Scientific Advisory Board; Vor: Other: Scientific Advisory Board; Roche: Other: Scientific Advisory Board; Adaptimmune LLC: Other: Scientific Advisory Board; Glaxo-Smith-Kline: Other: Scientific Advisory Board; Allogene: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Apricity Health: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Unum Therapeutics: Equity Ownership, Membership on an entity's Board of Directors or advisory committees. Diehn:Roche: Consultancy; Quanticell: Consultancy; Novartis: Consultancy; AstraZeneca: Consultancy; BioNTech: Consultancy. Miklos:Miltenyi Biotech: Membership on an entity's Board of Directors or advisory committees; Becton Dickinson: Research Funding; AlloGene: Membership on an entity's Board of Directors or advisory committees; Kite-Gilead: Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Juno: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive Biotechnologies: Membership on an entity's Board of Directors or advisory committees; Precision Bioscience: Membership on an entity's Board of Directors or advisory committees. Alizadeh:Genentech: Consultancy; Janssen: Consultancy; Pharmacyclics: Consultancy; Gilead: Consultancy; Celgene: Consultancy; Chugai: Consultancy; Roche: Consultancy; Pfizer: Research Funding.
