Cely, Fabio Samir Vargas

Abstract Introduction Matrix assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS, mass fix) represents a sensitive and specific alternative to electrophoresis and immunofixation for quantifying monoclonal antibodies in patients with multiple myeloma (MM). Here we report real world data utilizing mass fix and compare its test characteristics to a gold standard of minimal residual disease (MRD) quantification utilizing next generation sequencing (NGS). Results All patients who had obtained mass fix and MRD testing by NGS as part of routine clinical care at Mayo Clinic Arizona were screened for this study. In total, 343 pairs of mass fix and NGS testing within 50 days of each other representing 269 unique patients with secretory multiple myeloma were included. Cases of IgD myeloma and those secreting only free light chains were excluded. The threshold of MRD negativity was set at <1x10-6(less than one malignant cell in one million) and was assessed utilizing the clonoSEQ NGS assay. The median age of our cohort is 67, it is 44% female, and primarily Caucasian (88%) with a median follow-up of 7.3 months from testing date. FISH testing was performed in 96% of patients and at least one high risk cytogenetic abnormality (t(4;14), t(14;16), del(17p)) was found in 23% of patients. The t(11;14) translocation was found in 18%, +1q in 26%, and amp(1q) in 6% of evaluated patients. Notably, patients at all stages of treatment or disease status were included in our study. Induction treatment for newly diagnosed MM (NDMM, 133 patients) was mostly daratumumab-containing quadruplet (63%) or triplet drug regimens (36%). Autologous stem cell transplant (ASCT) was performed in 79% of NDMM and 80% of relapsed refractory MM patients (RRMM, 138 patients). Of the RRMM patients, 94% were triple class exposed and 41% were penta-exposed. Overall agreement between NGS and mass fix results was 65% (Kappa statistic: 0.31, 95% CI: 0.22 – 0.41). Most discordant cases were instances of mass fix negativity and NGS positivity (n = 89, 26% of all testing pairs). Only 7% of cases (n= 30) represented mass fix positivity with NGS negativity. Mass fix was able to define therapeutic monoclonal antibody by its unique mass spectrometric profile in 38 of the total test pairs that otherwise would have been considered disease associated. Of the 30 patients testing mass fix positive and NGS negative, 25 (83%) represent post-treatment evaluations. Thus, ongoing mass fix positivity represents monoclonal protein washout kinetics. All of these cases are noted to have declining mass fix levels at last follow up and 40% had undetectable monoclonal protein. The discordant mass fix negative and NGS positive cases were evenly distributed across NDMM and RRMM representing 32% and 20% of test pairs in each group, respectively. Amongst these 89 total test pairs, the median abundance of malignant clone by NGS was 10 cells per million (range 0.06 to 297,895). This is in contrast to 136 concordantly positive test pairs where the median was 2960 cells per million (range 0.353 to 1,017,360). The median monoclonal protein identified (in those with a quantifiable M-spike) was 0.30 g/dL. Receiver operating characteristic curves using NGS as gold standard found the optimal mass fix threshold to be 0.010g/dL (specificity 95%, sensitivity 51%) for NDMM patients and 0.046g/dL (specificity 84%, sensitivity 55%) in RRMM patients. Conclusions Development of a MRD assay based on peripheral blood sampling could greatly improve the ease and speed of obtaining these assessments. Our experience highlights both the great potential and need to identify appropriate clinical contexts for optimal use of mass fix MRD assessment. A significant limitation of our data is that low level monoclonal proteins without a previous reference above a threshold of 20mg/dL are not reported as positive and may account for a significant fraction of discordant cases reported here. All clonoSEQ NGS samples are referenced to a positive control greatly increasing specificity. The currently reported dataset is biased against mass fix as not all test pairs reported are known to have a positive reference. Further delineation of these cases is forthcoming. Previous reports have also noted that mass fix test characteristics can improve with time from treatment which will be assessed with future follow-up.

Background: Chimeric Antigen Receptor (CAR) T-cell clinical trials are growing exponentially. Database analysis can help identify scientific trends and generate projections regarding potential approvals before the results of the studies are completed or published. This is particularly interesting in pediatric oncology, where available analyses from repository databases are scarce or not available. Because of that reason, we sought to analyze the clinical trial public records from entries related to CAR T-cell clinical studies in pediatric patients (18 years or younger) uploaded to the clinicaltrials.gov database. Methods: We query the available data from clinicaltrials.gov using the following keywords: “CAR T cell in pediatrics”, “CAR T cell and cancer”, “chimeric antigen receptor”, “CAR T AND tumor antigen”, 'CAR T cell antigens“, ”Tumor antigens targeted by CAR T cells“, ”engineered T cells“, ”modified T cell“, ”CAR T cells in Cancer“, ”CAR T cell therapy“, ”CAR T cell therapy AND Cancer“ (data cut off July-2023). The data were tabulated, and the trials that did not meet the search criteria were excluded manually. Data cleansing was performed using published scientific data, web search-based information, and patent databases. Results: We found 4297 results in the Clinicaltrials.gov platform; we excluded 3978 clinical trials that did not involve the pediatric population (<18 years) or CAR T-cell intervention. The final analysis included 319 clinical trials posted on the clinicaltrials.gov website by the cut-off date. 207 (64.9%) were conducted in China, 74 (23.2%) in the US, and 21 (6.5%) in Europe. Most CAR T-cell trials focused on hematological cancer (89%), followed by non-CNS solid tumors 8%, and CNS tumors 3%. The most frequent targets were CD19 (46%), CD7 (7%), followed by GD2, CD22, CD123, CD19 + CD22 and CD30. Most clinical trials did not report the construct generation used in their CAR T cell product (58%). Among the trials with that information, second-generation constructs (2G) were used in 32% of the studies, followed by 3G and 4G constructs (5% of studies each). Most clinical trials were in early stages of development, Phase 1 or 2 (75%). We observed a continuous increase in the number of clinical trials registered yearly, except for a small reduction in 2022 and 2021, probably related to COVID restrictions and challenges. Overall, the general trend predicts at least a 50% yearly increase in registered studies ( Figure 1). Similarly, to what is observed in adult clinical trials, the most common signaling domains are 2G CAR constructs expressing either CD28 or 4-1BB as costimulatory domains. Among those, 4-1BB being is the most popular choice. Conclusion: Our findings indicate a growing interest in the clinical development of CAR T-cell therapies applied to pediatric oncology. Most of these studies are in early phase I and II and focus primarily on hematological cancers using second-generation constructs targeting CD19. The is a steady increase in the number of studies registered each year that predicts future FDA approvals using CAR T-cell products.

Keywords: Chimeric Antigen Receptor T cell, Pharmacoeconomic, Pediatric, Clinical Trials With the success of Chimeric Antigen Receptor (CAR) T-cell therapy in the pediatric population, new clinical trials have surged worldwide. To date, no previous study has analyzed the effect of socioeconomic factors on the development of clinical trials for CAR T-cells in the pediatric population. In recent years new countries and emerging economies have contributed significantly to the development of CAR T-cell clinical trials. A better understanding of the socioeconomic factors that influenced these trends will facilitate the future development of this cellular therapy field. To assess the impact of socioeconomic factors related to the development of clinical trials on CAR T-cell therapies in the pediatric population, we analyzed data entries from clinical trials registered to the Clinicaltrials.gov database. To query the information, we used the following keywords “(leukemia OR cancer OR lymphoma OR malignancies OR tumor OR solid tumor) AND (CAR OR chimeric antigen receptor OR CAR T-cell OR adoptive immunotherapy OR immune effector OR cellular therapy) AND (Child)”. In addition, we used different filters that allowed the selection of studies that focused on patients 18 years of age and younger. Data corresponding to entries with a data cut-off of July-2023 were included. In addition, we use the World Bank country's macroeconomic database (January 1 st, 2009 to December 31 st, 2022). We found 4,297 results in the Clinicaltrials.gov platform; we excluded 3,978 clinical trials that did not involve the pediatric population (≤18 years) or CAR T-cell intervention. There were 319 clinical trials included, sponsored in 19 countries, as shown in Figure A. Of those studies, 207 (64.9%) were conducted in China, 74 (23.2%) in the U.S., and 21 (6.5%) in Europe. Not surprisingly, the number of clinical trials is strictly proportional to each country's Gross Domestic Product (GDP) and Research and Development (R&D) expenditure, as shown in Figure B. Pearsons' coefficient between GDP and the number of trials registered per country is 0.8 (p-value < 0.001); similarly, Pearsons's coefficient between R&D expenditure and the number of problems reported per country is 0.64 (p-value < 0.004). The United States and China are developing 88% of the Clinical trials, and 96% of the clinical trials occur in countries ranked in the top 10 highest GDP. Our database analysis shows a notable disparity in the countries leading cutting-edge research in CAR T-cell therapy for pediatric oncology. The primary locations for these clinical studies are countries ranked in the top 10 in terms of GDP, with China and the USA being the main contributors. Access to clinical trials plays a crucial role in improving cancer patients' outcomes, and this disparity in the development of cellular therapies is likely to impact children from middle and low-GDP countries significantly. Urgent strategies are required to address this issue and ensure more equitable access to advanced technologies and clinical trials in cellular therapy for pediatric cancers. These strategies should become a high priority for national and international health departments and organizations in the coming years. By promoting more comprehensive clinical trial access and collaboration, we can work towards reducing these disparities and providing better treatment options for all children facing pediatric cancer.