Bovine serum albumin protected gold nanozymes as a novel anti-cancer nanodrug for acute T-type lymphoblastic leukemia treatment via effect on the expression of anti-apoptotic genes

In this paper, the bovine serum albumin protected gold nanozymes (BSA-Au nanozymes) were utilized as a novel nanodrug for treatment of acute T-type lymphoblastic leukemia (Jurkat) by production of excessive ROS and effect on the expression of anti-apoptotic genes. The effect of BSA-Au nanozymes on the Bcl-2 expression and survivin in the Jurkat cell line was checked. The results showed that the expression of anti-apoptotic genes was significantly reduced after treatment of the Jurkat cell line with the BSA-Au nanozymes (p-value of 0.001) as the potential nanodrug while their expression in the normal PBMC was not affected by the nanodrug. Moreover, the cytotoxic effect of the developed nanodrug on the Jurkat cell line was evaluated which illustrated that survival rate in the studied cell line reaches its minimum value (100% lethality, 0.0% survival) after treatment for 48 h. The IC50 for the nanodrug was calculated at 0.05 mM of the developed nanodrug. Overall, the BSA-Au nanozymes can be used as the nanodrug for treatment of T-type lymphoblastic leukemia via reducing the expression of anti-apoptotic genes, increasing the effect of common anticancer drugs such as Adriamycin and ara-C, and consequently increasing the survival of patients with leukemia.

Validation of a method evaluating T cell metabolic potential in compliance with ICH Q2 (R1)

Background Metabolic cell features are able to give reliable information on cell functional state. Thus, metabolic potential assessment of T cells in malignancy setting represents a promising area, especially in adoptive cell therapy procedures. Easy to set up and convenient Seahorse technology have recently been proposed by Agilent Technologies and it could be used to monitor T cells metabolic potential. However, this method demonstrates an inter-assay variability and lacks practices standardization. Results We aimed to overcome these shortcomings thanks to a lymphoblastic derived JURKAT cell line seeding in each experiment to standardize the Seahorse process. We used an adapted XF Cell MitoStress Kit protocol, consisting in the evaluation of basal, stressed and maximal glycolysis and oxidative phosphorylation related parameters, through sequential addition of oligomycin and carbonyl cyanide 4-(trifluoromethoxy)phenylhydrazone (FCCP) to a glucose containing medium. Data were acquired and analyzed through Agilent Seahorse XFe96 analyzer. Indeed, we validated this method in the light of ICH Q2 (R1) guidelines. We were able to confirm the specificity and accuracy of the method. We also demonstrated the precision, linearity and range of the method in our experimental conditions. Conclusion The validation of the method consisting in a JURKAT cell line experimental incorporation as a control material contributes to improve the Seahorse technology’s robustness. These results lay the groundwork for the implementation of this technology to optimize T cell based cellular therapy products production process and monitoring.

Comparative Analysis for Differential Drug Response between Early T-Cell Precursor Acute Lymphoblastic Leukemia (ETP-ALL) and T-Cell Acute Lymphoblastic Leukemia (T-ALL) Patients Using the Cellworks Omics Biology Model (CBM): Mycare-021-03

Background:Early T-cell Precursor Acute Lymphoblastic Leukemia (ETP-ALL), an orphan disease, is a sub-type of T-Cell Acute Lymphoblastic Leukemia (T-ALL) with very poor prognosis and limited therapy options. ETP-ALL is a heterogeneous disease with many distinct genomic profiles, often with more myeloid than lymphoid characteristics. However, standard of care (SOC) drugs for acute myeloid leukemia (AML) have shown limited efficacy for ETP-ALL (PMID: 32733662, 25435716). The genomic profiles of ETP-ALL patients have more complex cytogenetics and larger numbers of genomic aberrations when compared to non-ETP-ALL (T-ALL) profiles (PMID: 22237106, 30641417). We present an alternative multi-gene analysis approach using the Cellworks Omics Biology Model (CBM) workflow to identify unique, intersecting protein pathways in patient-specific disease profiles. The CBM predictive workflow was used to design novel personalized therapy options for an ETP-ALL representative PEER human lymphoid cell line in comparison to a T-ALL JURKAT cell line. The predicted combination therapies were then validated in a lab model. Methods:A PEER cell line was selected to represent ETP-ALL and a JURKAT cell line was selected as a representative for non-ETP T-ALL. Next Generation Sequencing (NGS) was performed for the PEER cell line. For the JURKAT cell line, publicly available NGS whole exome sequencing from cBioPortal and Sanger, along with array CGH from Agilent, were used. The genomic data for the PEER and JURKAT cell lines were used as inputs to the CBM to generate dynamic patient-specific disease protein network maps. Biomarkers and pathway characteristics unique to the PEER and JURKAT cell lines were identified. A digital drug library of targeted FDA-approved agents was simulated on the disease models using both single drug agents and drug combinations at varying doses. The treatment impact was assessed by quantitatively measuring drug effect on a cell growth score, which is a composite of the quantified values of cell proliferation, survival and apoptosis along with impact on the patient-specific disease biomarker score. Comparative dose response studies were run to assess IC50 differences for both cell lines. Cellworks VenturaTM predicted novel therapy combinations for the ETP-ALL representative PEER cell line, which were then prospectively validated by in vitro experiments. The same therapy options were predicted to be less effective in the T-ALL representative JURKAT cell line, which was also confirmed by in vitro studies. Results:The CBM predicted three novel combination therapies for the ETP-ALL representative PEER cell line: nilotinib + cytarabine, bortezomib + cytarabine and bortezomib + idarubicin. All three therapies were predicted to be less effective in JURKAT cells. In vitro, PEER cells were sensitive to all 3 combinations, as predicted by the CBM; whereas, JURKAT cell lines were not sensitive to the first 2 combinations (as predicted), but were sensitive to bortezomib + idarubicin. The CBM analysis is supported by scientific rationales for these combinations based on the genomics-driven disease characteristics of the cell-line. The reasons for drug sensitivity and resistance were determined. These combinations were then prospectively validated in vitro on both cell lines and the experimental responses matched the predicted outcomes. Conclusion:The Cellworks Omics Biology Model integrates the multiple genomic abnormalities in a patient to identify disease network characteristics unlike other NGS analytic tools that attempt to interpret the impact of each genomic alteration in isolation. CBM identified 3 novel therapy options for ETP-ALL that were validated in vitro, similar to anecdotal experience in vivo. This predictive technology can improve clinical decision-making and identify novel treatment options. Disclosures Howard: Cellworks:Consultancy;Servier:Consultancy, Other: Speaker;EUSA Pharma:Consultancy;Sanofi:Consultancy, Other: Speaker;Boston Scientific:Consultancy.Kumar:Cellworks Research India Private Limited:Current Employment.Pampana:Cellworks Research India Private Limited:Current Employment.Ullal:Cellworks Research India Private Limited:Current Employment.Tyagi:Cellworks Research India Private Limited:Current Employment.Lala:Cellworks Research India Private Limited:Current Employment.Kumari:Cellworks Research India Private Limited:Current Employment.Joseph:Cellworks Research India Private Limited:Current Employment.Raju:Cellworks Research India Private Limited:Current Employment.Balakrishnan:Cellworks Research India Private Limited:Current Employment.Mundkur:Cellworks Group Inc.:Current Employment.Macpherson:Cellworks Group Inc.:Current Employment.Nair:Cellworks Research India Private Limited:Current Employment.Kapoor:Cellworks Research India Private Limited:Current Employment.

Validation of a method evaluating T cell metabolic potential in compliance with ICH Q2 (R1)

Background Metabolic cell features are able to give reliable information on cell functional state. Thus, metabolic potential assessment of T cells in malignancy setting represents a promising area, especially in adoptive cell therapy procedures. Easy to set up and convenient Seahorse technology have recently been proposed by Agilent Technologies and it could be used to monitor T cells metabolic potential. However, this method demonstrates an inter-assay variability and lacks practices standardization. Results We aimed to overcome these shortcomings thanks to a lymphoblastic derived JURKAT cell line seeding in each experiment to standardize the Seahorse process. We used an adapted XF Cell MitoStress Kit protocol, consisting in the evaluation of basal, stressed and maximal glycolysis and oxidative phosphorylation related parameters, through sequential addition of oligomycin and FCCP to a glucose containing medium. Data were acquired and analyzed through Agilent Seahorse XFe96 analyzer. Indeed, we validated this method in the light of ICH Q2 (R1) guidelines. We were able to confirm the specificity and accuracy of the method. We also demonstrated the precision, linearity and range of the method in our experimental conditions. Conclusion The validation of the method consisting in a JURKAT cell line experimental incorporation as internal control contributes to improve the Seahorse technology’s robustness. These results lay the groundwork for the implementation of this technology to optimize T cell based cellular therapy products production process and monitoring.