Multiomic correlates of ex vivo αCD19 chimeric antigen receptor T-cell (CART) cytotoxicity in venetoclax-treated patients with chronic lymphocytic leukemia (CLL)
Bibliographic record
Abstract
Abstract Introduction: Chronic Lymphocytic Leukemia (CLL) results in the expansion of immunosuppressive B-cells leading to risk for secondary malignancies, infection, and suboptimal T-cell based immunotherapeutic responses. Treatments that restore immune function (e.g. ibrutinib) may improve the efficacy of CD19 CAR T-cell (CART) therapies. We previously demonstrated that venetoclax (Ven) causes complex immunologic changes which broadly improve circulating immune cell (including T-cell) function. While we found that Ven appears to improve CD19 CART cytotoxicity in most patients, some CD19 CAR T-cells manufactured after Ven treatment did not perform as well in ex vivo cytotoxicity assays. We performed a multiomic correlation analysis to elucidate germane molecular features that may help predict and optimize Ven-enhanced CD19 CART cytotoxicity. Methods: We collected peripheral blood mononuclear cells (PBMCs) and serum from 13 consented CLL patients initiating standard of care Ven-based therapy (Ven-monotherapy N = 9, Ven+ɑCD20 N = 4; BDR-164122). Specimens were collected before treatment (D0) and after 30 days (D30) of therapy. CD19 CART were manufactured for 6 patients at both timepoints using an ɑCD19 construct (scFv/CD28/TCRζ via retroviral transduction). Cytotoxicity was measured against Raji-Luciferase cells. D0 and D30 specimens were analyzed by flow cytometry (including T-cell subsets and exhaustion markers) and RNA-seq (with xCell for cell-type deconvolution, rMATS for splicing, LISA for master regulator analysis). Enrichment analysis identified biological processes linked to cytotoxicity with statistical significance calculated as False Discovery Rate (FDR) adjusted P value. Metabolomics were performed with the Biocrates MxP Quant 500 XL assay. For each multiomic feature, magnitude change from D0 to D30 was calculated. These changes were correlated with changes in CD19 CART ytotoxicity across 7 effector-to-target ratios (1:8 through 8:1) using Spearman's correlation. Results: Enhanced CD19 CART cytotoxicity correlated with increased NK-cell frequency (CD56+/CD57+, CD56-/CD57+) determined by flow cytometry and cell-type deconvolution. In addition, RNA sequencing studies demonstrated that CD19 CART activity correlated with gene expression changes in interferon-ɑ (IFNA1, FDR<0.001) and interferon-ɣ (IFNG, FDR<0.002) response pathways. Specifically, an increase in key interferon signaling genes (GZMA, STAT1, CASP1) were associated with improved CD19 CART cytotoxicity. Moreover, a decrease in some interferon signaling genes (JAK2, STAT2, IFNAR2) was associated with a decrease in CD19 CART activity. LISA analysis identified POU2F2 and HDAC1 as key transcriptional regulators of genes associated with enhanced post-Ven CD19 CART killing. Elevated anti-inflammatory metabolites (cortisol, cortisone), as well as cysteine and phosphatidyl lipids correlated with improved CD19 CART cytotoxicity. Diminished CD19 CART cytotoxicity correlated with increased CD4+ LAG3+ T-cells coexpressing TIM3/TIGIT, and total CD3+ T-cells. Cell-type deconvolution demonstrated an inverse correlation between regulatory T-cells (T-regs) and CD19 CART cytotoxicity. Increase in NFκB signaling and splicing factor genes (e.g. RELA, RELB, NFKB1, NFKB2, TNF, U2AF1, U2AF2) were associated with a decrease in CD19 CART cytotoxicity (FDR<0.001). Alternative splicing by rMATS analysis identified a MAP3K7 (TAK1) event resulting in a TAK1 variant lacking its negative regulatory domain. This alternative splice form of TAK1 enhances NFκB signaling and impacts CD19 CART activity. Elevated serum triacylglycerols, GABA, spermine, and taurine detected by metabolic studies correlated with diminished CD19 CART cytotoxicity. Conclusion: Using a comprehensive multiomic approach we uncovered signaling pathways associated with improved CD19 CART activity following Ven-based therapy in CLL patients. The activation of the interferon-ɑ, interferon-ɣ and glucocorticoid signaling pathways enhance CART activity. In contrast, NFκB signaling and spliceosome-related pathways contribute to sustained immune activation and negative impacts on CAR T-cell function. Venetoclax treatment appears to alter T-cell (especially T-reg) and NK-cell subtypes, which influence the anti-tumor activity of CD19 CAR T-cells. Our work provides a foundation for further mechanistic inquiry into Ven-related immunologic impacts, which can improve synergistic combination treatments using CART for CLL patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".