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. 2023 Sep 12;7(17):4690-4700.
doi: 10.1182/bloodadvances.2022007456.

Host metabolome predicts the severity and onset of acute toxicities induced by CAR T-cell therapy

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Host metabolome predicts the severity and onset of acute toxicities induced by CAR T-cell therapy

Akansha Jalota et al. Blood Adv. .

Abstract

Anti-CD19 chimeric antigen receptor (CAR) T-cell therapy is a highly effective treatment option for patients with relapsed/refractory large B-cell lymphoma. However, widespread use is deterred by the development of clinically significant acute inflammatory toxicities, including cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS), that induce significant morbidity and require close monitoring. Identification of host biochemical signatures that predict the severity and time-to-onset of CRS and ICANS may assist patient stratification to enable timely mitigation strategies. Here, we report pretreatment host metabolites that are associated with CRS and ICANS induced by axicabtagene ciloleucel or tisagenlecleucel therapy. Both untargeted metabolomics analysis and validation using targeted assays revealed a significant association between the abundance of specific pretreatment biochemical entities and an increased risk and/or onset of clinically significant CRS (q < .1) and ICANS (q < .25). Higher pretreatment levels of plasma glucose and lower levels of cholesterol and glutamate were associated with a faster onset of CRS. In contrast, low baseline levels of the amino acids proline and glycine and the secondary bile acid isoursodeoxycholate were significantly correlated with clinically significant CRS. Lower concentration of the amino acid hydroxyproline was associated with higher grade and faster onset of ICANS, whereas low glutamine was negatively correlated with faster development of ICANS. Overall, our data indicate that the pretreatment host metabolome has biomarker potential in determining the risk of clinically significant CRS and ICANS, and may be useful in risk stratification of patients before anti-CD19 CAR T-cell therapy.

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Conflict of interest statement

Conflict-of-interest disclosure: N.G., B.T.H., D.M.R., A.J., C.E.H., and G.K. have intellectual property related to the detection of CAR T-cell–associated toxicities; D.M.R. has stock and other ownership interests in Interpares Biomedicine and Clariifi and intellectual property related to the detection of liver cancer; B.T.H. has received research funding from Takeda; consultancy, honoraria, research funding from Genentech, Karyopharm, Celgene, AbbVie, Pharmacyclics, BeiGene, AstraZeneca, Kite, a Gilead Company, and Bristol Myers Squibb; and consultancy and honoraria from Novartis, though not used for this study.

Figures

None
Graphical abstract
Figure 1.
Figure 1.
Association between severity, and time-to-onset of CRS with that of ICANS after CAR T-cell therapy. Kinetics of CRS (A) and ICANS (B) in each patient in the study cohort during 14 days of CAR T-cell infusion, colors indicate the grade of toxicity recorded each day. NA indicates that either the patient was discharged, assessment was declined, or grading could not be performed. (C) Maximum grade of ICANS and CRS recorded for patients after CAR T-cell infusion, color indicates the percentage of the cohort affected. (D) Associations between the outcomes (grade and time-to-onset) of CRS with those of ICANS (n = 41 patients). (E) Workflow of metabolomics platform and analysis.
Figure 2.
Figure 2.
Association of metabolites with severity of CRS. (A) Heatmap of median relative abundance of 72 metabolites (rows) significantly associated with CRS severity (P < .05, q < .10), stratified by maximum observed grade of CRS (columns). Color indicates the log2-transformed median relative abundance of each group and metabolites are ordered by their relative abundance in CRS grades 2 to 4. (B) Relative abundance of the most statistically significant metabolites that were negatively associated with maximum observed CRS grade. The ordinal logistic regression q value is displayed in the graph title and the q values from pairwise t test comparisons are displayed on the graph.
Figure 3.
Figure 3.
Association of metabolites with time-to-CRS onset. (A) Forest plot of HRs and 95% CIs for the 155 metabolites, measured on the day of apheresis, associated with time-to-CRS onset from day of treatment initiation (P < .05, q < .10). (B) Kaplan-Meier curves for the 9 metabolites with the highest or lowest HRs display the fraction of patients who experienced CRS, stratified by median metabolite abundance. The dotted red and blue lines indicate the median time-to-CRS for each group.
Figure 4.
Figure 4.
Targeted analysis of metabolites validates significant associations with CRS. Association of glucose, cholesterol, proline, glycine, glutamate, and sphingomyelin concentrations with severity or time-to-onset of CRS were validated using clinical and targeted quantitative assays.

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