ABSTRACT
Previous studies of genome sequencing (GS) in critically ill childrenhave made use of either modified hardware or working procedureswhich would be difficult, if not impossible, to integrate into existingclinical workflows1. Our lab’s transition from exome sequencing (ES) to GS offered an opportunity to implement in-house rapid genomesequencing (rGS) in critically ill children in a manner which couldintegrate with existing clinical workflows. We conducted a feasibilityand implementation pilot by offering rGS to child-parent triosconcurrently undergoing clinical rapid ES (rES) via a reference lab.The purpose of this study was to identify and address operationalbarriers to implementation of a rGS program capable of communicatinga preliminary result within 7 days of consent. We consideredthis time span to be more reflective of clinical realities than lab-quotedturnaround times (TAT) which typically start at sample receipt andthus do not account for challenges in sample acquisition and pre-testcounseling in a critical care setting, nor the impact of shipping times.Here we present data on TAT and lessons learned from the first 27subjects enrolled.Using rapid cycle improvement methodologies, we identified fourdistinct but inter-related workflows requiring optimization:1. Pre-analytic: patient identification through acquisition ofsamples2. Wet-lab: extraction through sequencing3. Bioinformatics: secondary and tertiary analysis as well as rapididentification of causal variants4. Return of resultsFigure 1 summarizes TAT across cases, demonstrating the markedimprovements in TAT with our programmatic approach to improvement.We used our first 9 cases to determine a baseline TAT for theentire process and to delineate the 4 main workflows (above). Atbaseline, excluding cases delayed by COVID-19 restrictions, mean TATwas 17.12 days (3 sequential deviant range: 7.05–27.19 days).Following deployment of our programmatic approach to rGS, meanTAT fell to 6.19 days (3 sequential deviant range: 0.51–11.87 days).Table 1 summarizes the observations and insights, by workflow, whichimpacted upon TAT and/or implementation. The single biggest impacton TAT was optimization of bioinformatics by removing all manualsteps between starting sequencing and producing human interpretable,filtered, annotated output of high-priority variants for interpretation.The second biggest source of improvement was optimization ofthe sequencing itself as well as prioritizing sample processing for andaccess to sequencing runs. While variant ranking is helpful in identifying causal variants, in 9/10 cases with a diagnostic findingthe causal variant(s)were obvious to the study teamwithin minutes ofviewing the annotated variant list, regardless of variant rank. (Figure Presented) As time required for sequencing and analytic workflows fell, therelative contribution of other workflows to overall TAT shifted and itbecame more obvious that early identification and utilization of thisapproach is very important in lowering overall time to diagnosis(Figure 2). In 6/10 cases with a diagnostic finding, the initial approachof the clinical team was NOT rES (and thus patients were not eligiblefor rGS on a research basis). Had rGS been the initial diagnosticmodality chosen, a diagnosis could have been reached in a median 12days sooner (range 2–28 days). There were also several cases wheresequencing was delayed when one or both parents did not present tothe lab to provide a blood sample in a timely manner. Optimization ofsequencing or analytic workflows cannot meaningfully improveoutcomes either of these situations.Our findings suggest some important considerations for institutionsdeveloping or seeking to improve rapid sequencing programs for acuteand critically ill children: (Table Presented) • Optimization of computational resource utilization and phenotypecuration saves more time than improved variant filtering orprioritization.• Obtaining samples from parents is non-trivial.• Even trained geneticists may fail to recognize appropriatecandidates for rGS.
ABSTRACT
Background: We have previously described AUTO1 (CAT19), a CD19 CAR with a fast off-rate CD19 binding domain, designed to reduce CAR T-cell immune toxicity and improve engraftment. Its clinical activity has been tested in r/r paediatric and adult B-ALL. Cumulatively, this data confirms the intended fucntion of the receptor, with low levels of CRS/ ICANS and long-term engraftment of CAR T-cells observed in both patient groups. Recently, CAR therapy has been explored in indolent lymphomas such as follicluar (FL) and mantle cell lymphoma (MCL), but a high incidence of toxicity inluding Grade 3-4 ICANS has been reported. Aims: We have initiated testing of AUTO1 (CAT19) in the setting of indolent B-cell lymphoma (NCT02935257). Methods: Manufacturing: CAR T-cell products were generated using a semi-automated closed process from non-mobilised leucapheresate. Study design: subjects>/=16y underwent lymhpodepletion with fludarabine (30mg/m2 x3) and cyclophosphamide (60mg/kg x1) followed by a single CAR T-cell infusion of 200 x10
ABSTRACT
Background: Patients with R/M SCC have low response rates to second line therapies, including PD-1 inhibitors nivolumab and pembrolizumab, representing an area of unmet clinical need. Cetuximab has modest activity as a single agent but potentiates the activity of radiotherapy in locally advanced head & neck SCC (HNSCC) and chemotherapy in R/M HNSCC. Cetuximab initiates Natural Killer cell antibody-dependent cell-mediated cytotoxicity, resulting in an anti-tumour immune response and the potential to augment the activity of PD-1/PD-L1 inhibition. Methods: Trial entry required histologically confirmed R/M SCC of any site, unselected by PD-L1 expression, considered incurable by local therapies and no previous treatment with cetuximab for recurrent/metastatic disease. Prior therapy with anti-PD-1, anti-PD-L1 or anti-PD-L2 was excluded. Patients had avelumab 10 mg/kg + cetuximab 500 mg/m2 intravenously every 2 weeks, for up to 1 year. Primary endpoint was occurrence of dose-limiting toxicity within 42 days of treatment starting, graded using CTCAE v5. Secondary endpoints were objective response (ORR) and disease control rate (DCR) at 6 and 12 months using iRECIST. Results: 16 patients, median age 58 years (range 34 – 88), were enrolled from 2 UK hospitals between July 2018 and October 2019. The trial stopped after completing the safety run-in. 5 patients remain on treatment, 9 stopped treatment early (7 disease progression, 1 patient choice, 1 due to risk of COVID-19). 2 patients died whilst on treatment (both unrelated to trial treatment). Grade 3 AEs were seen in 4 patients and grade 5 in 1 patient. None were related to trial treatment. No patients experienced dose-limiting toxicity. Of 10 patients evaluable for response by iRECIST 2 (20%) had complete response, 3 (30%) had partial response and 4 (40%) had stable disease as their best response, representing an ORR of 50%. One patient had confirmed disease progression. In 6 patients who remained on trial for >6 months, all 6 had disease control at 6 months (2 CR, 1 PR, 3 SD). Conclusions: Avelumab + cetuximab is safe and tolerable, and demonstrates promising efficacy in R/M SCC patients. Clinical trial identification: NCT03494322;20/03/2018;Sponsor reference: UCL/17/0560. Legal entity responsible for the study: University College London. Funding: Merck KGaA. Disclosure: M. Forster: Advisory/Consultancy, Travel/Accommodation/Expenses: BMS;Advisory/Consultancy, Research grant/Funding (institution), Travel/Accommodation/Expenses: Merck;Advisory/Consultancy, Research grant/Funding (institution), Travel/Accommodation/Expenses: MSD;Advisory/Consultancy: Novartis;Advisory/Consultancy: PharmaMar;Advisory/Consultancy, Travel/Accommodation/Expenses: Roche;Advisory/Consultancy: Nanobiotix;Advisory/Consultancy, Travel/Accommodation/Expenses: Guardant Health;Advisory/Consultancy: Oxford VacMedix;Advisory/Consultancy, Research grant/Funding (institution), Travel/Accommodation/Expenses: AstraZeneca;Advisory/Consultancy: Takeda;Research grant/Funding (institution): Boehringer Ingelheim;Travel/Accommodation/Expenses: Celgene. J. Sacco: Honoraria (self), Research grant/Funding (institution), Travel/Accommodation/Expenses: BMS;Honoraria (self), Advisory/Consultancy, Travel/Accommodation/Expenses: MSD;Honoraria (self), Advisory/Consultancy: Amgen;Honoraria (self), Advisory/Consultancy, Research grant/Funding (institution): Immunocore;Honoraria (self), Advisory/Consultancy: Delcath;Honoraria (self): Pierre Fabre;Research grant/Funding (institution): AstraZeneca. A. Kong: Honoraria (self), Advisory/Consultancy, Speaker Bureau/Expert testimony, Travel/Accommodation/Expenses: Merck;Honoraria (self), Speaker Bureau/Expert testimony: BMS;Advisory/Consultancy: Centauri Therapeutics;Advisory/Consultancy: Amgen;Advisory/Consultancy, Research grant/Funding (institution): Puma Biotechnology;Speaker Bureau/Expert testimony, Travel/Accommodation/Expenses: MSD;Research grant/Funding (institution): AstraZeneca. G. Wheeler: Honoraria (self): AstraZeneca. J. Hartley: Full/Part-t me employment: AstraZeneca;Advisory/Consultancy, Shareholder/Stockholder/Stock options: ADC Therapeutics. All other authors have declared no conflicts of interest.