Distinct Temporal Dynamic Serum Metabolite Profiles Characterize Treatment Response and Early Toxicity after B-Cell Lymphoma Directed CAR-T-Cell Therapy
Authors: Cordas dos Santos David M. , Hadzic Amar , Kirmaier Martin E. , Schmitz Werner , Blumenberg Viktoria , Rejeski Kai , Buecklein Veit L. , von Bergwelt-Baildon Michael , Subklewe Marion , Theurich Sebastian 
Published: December 2023

Introduction:

CD19 chimeric antigen receptor T-cell therapy (CD19.CAR-T) has profoundly improved treatment options for patients with relapsed/refractory B-cell lymphomas (r/r BCL), but is also associated with distinct toxicities. To elucidate host-intrinsic immunometabolic factors contributing to clinical benefit or immunotoxicity, we recently demonstrated that an increase of metabolically high-risk adipose tissue mass is associated with an elevated cytokine release syndrome (CRS) risk but also with improved survival (Haematologica 2022, CIR 2023). To gain further insights into the underlying immunometabolic mechanisms, we analyzed temporal dynamic changes of serum metabolites in r/r BCL patients during the first 14 days of CD19.CAR-T treatment.

Methods:

In this single-center analysis, we studied patients receiving CD19.CAR-T for r/r large BCL or mantle cell lymphoma (MCL) between 01/2019 and 12/2021 in a real-world setting. All patients were consecutively treated in our department (LMU University Hospital) and serum was prospectively collected in the morning hours from fasted patients beginning at the day of CAR-T infusion (D0), and 3-5 and 14 days later. Using liquid chromatography mass-spectrometry, we quantitatively analyzed a total of 305 water-soluble metabolites and 734 lipids. Metabolomic data was integrated with clinical patient records including CRS, 1-year progression-free survial (PFS) and amount of visceral adipose tissue (VAT).

Results:

In total, we measured 170 serum samples from 55 r/r LBCL and 4 r/r MCL patients, of which 52 had serial samples at all three time points (D0: 55, D3-5: 59, D14: 56). The following CAR-T products were administered: axi-cel (n = 26), tisa-cel (n = 29) and brexu-cel (n = 4). 25 (42.4%) patients developed a CRS grade ≥ 2, while 34 patients had a CRS grade 0-1. The best 90-day overall response rate was 52.5%, with a complete remission rate of 42.4%. At 1 year, 67.8% of patients progressed.

From the 1039 metabolites measured, 525 metabolites passed quality control. Metabolite values were normalized and auto-scaled for further analysis. A partial least square differential analysis based on the collected time points led to a clear separation of samples with uric acid, desoxy-ribose-5-phosphate (dRibose-P), essential amino acids and (phospho)lipids having the strongest impact. Whereas 56 metabolites showed a significant increase from D0 to D14 led by uric and essential amino acids, 34 metabolites decreased over the course of treatment with the strongest reduction in dRibose-P and sphingosine phosphate. Performing a metabolic pathway enrichment analysis based on the most altered metabolite levels, we detected 22 significantly affected metabolic pathways and programs including aerobic glycolysis, urea cycle, amino acid and lipid metabolism (FDR &lt; 0.1, Fig. 1A).

To further delineate metabolite changes in regards to CRS, 1-year PFS and amount of VAT, we conducted a multivariate empirical bayes analysis of variance to specifically detect metabolites with differential temporal dynamics and considered all metabolites with an FDR &lt; 0.1. Patients who developed a CRS ≥ 2° showed increased levels of kynurenine, phosphatidylethanolamides and lysophosphatidylserines, and decreased levels of ornithine and phosphatidylinositols. 1-year progressors showed a significant increase of several phosphatidylinositols beginning at D3-5 after CAR-T infusion, and decreased levels of phosphatidylcholines. For VAT, we used a threshold of 144 cm² which was derived from previously conducted computer tomography segmentation analyses. As expected, VAT cohorts mostly differed in fatty acid metabolism-associated metabolites including (acyl)carnitines, cholesterol esters, triglycerides and xanthine.

In order to identify metabolites being associated with multiple outcomes, we looked for mutual metabolites among distinct cohort profiles. Here, one example is phosphatidylinositol-(22:5/16:0), which was increased in CRS 0-1° and 1y-progressors ( Fig. 1B).

Conclusions:

Our study highlights that CD19.CAR-T treatment is accompanied by broad changes in the serum metabolome of r/r BCL patients, which can be used to profile patients being affected by CAR-T-related immunotoxicity and their response to treatment. In ongoing analyses, we evaluate the use of these profiles for predictive models, and assess their impact on CAR-T cell function in-vitro.