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. 2025 Apr 1;8(4):e253455.
doi: 10.1001/jamanetworkopen.2025.3455.

Cytokine Storms in COVID-19, Hemophagocytic Lymphohistiocytosis, and CAR-T Therapy

James P Long  1 , Rishab Prakash  2 , Paul Edelkamp Jr  3 , Mark Knafl  3 , Anath C Lionel  2 , Ranjit Nair  2 , Sairah Ahmed  2 , Paolo Strati  2 , Luis E Malpica Castillo  2 , Ajlan Al-Zaki  2 , Kelly Chien  4 , Dai Chihara  2 , Jason Westin  2 , Fareed Khawaja  5 , Loretta J Nastoupil  2 , Victor Mulanovich  5 , Andrew Futreal  6 , Scott E Woodman  6 , Naval G Daver  4 , Christopher R Flowers  2 , Sattva Neelapu  2 , Joanna-Grace Manzano  7 , Swaminathan P Iyer  2 ; Data-Driven Determinants for COVID-19 Discovery Effort (D3CODE) Team
Collaborators, Affiliations

Cytokine Storms in COVID-19, Hemophagocytic Lymphohistiocytosis, and CAR-T Therapy

James P Long et al. JAMA Netw Open. .

Abstract

Importance: Cytokine storm (CS) is a hyperinflammatory syndrome causing multiorgan dysfunction and high mortality, especially in patients with malignant hematologic neoplasms. Triggers include malignant neoplasm-associated hemophagocytic lymphohistiocytosis (MN-HLH), cytokine release syndrome from chimeric antigen receptor T-cell therapy (CAR-T CRS), and COVID-19, but the underlying mechanisms of inflammation and their impact on outcomes are poorly understood.

Objective: To delineate the inflammatory patterns characterizing different CS etiologies and their association with clinical outcomes.

Design, setting, and participants: This retrospective cohort study was conducted at the MD Anderson Cancer Center in Houston, Texas, between March 1, 2020, and November 20, 2022, using the software-as-a-service Syntropy Foundry Platform. Participants were patients with malignant hematologic neoplasms who developed CS from COVID-19 (COVID-CS), MN-HLH, or CAR-T CRS.

Exposure: Diagnostic criteria for COVID-CS were developed based on surging inflammatory markers (interleukin-6, C-reactive protein, and ferritin), while diagnosis of MN-HLH and CAR-T CRS followed established guidelines.

Main outcomes and measures: The study compared cytokine levels, clinical characteristics, and survival outcomes across the 3 cohorts and focused on inflammatory markers, survival times, and key factors associated with survival identified through univariate and multivariable analyses.

Results: A total of 671 patients met the inclusion criteria. Of those, 220 (33%) had CAR-T CRS, 227 (34%) had COVID-CS, and 224 (33%) had MN-HLH. Patients were predominantly male (435 [65%]), and 461 (69%) were White, with significant differences in median age (CAR-T CRS, 63 [IQR, 54-71] years; COVID-CS, 63 [IQR, 52-72] years; MN-HLH, 55 [IQR, 41-65] years; P < .001) as well as number of admission days and underlying cancer type across cohorts. Marked variations in cytokine levels and survival outcomes were observed, with the MN-HLH cohort exhibiting the highest levels of inflammatory markers (eg, median TNF-α, 105 pg/mL [IQR, 38-201 pg/mL] for MN-HLH vs 23 pg/mL [IQR, 17-42 pg/mL] for COVID-CS) and lowest fibrinogen and albumin levels. The cohort with CAR-T CRS showed substantially longer survival times compared with the cohort with COVID-CS (hazard ratio [HR], 2.93; 95% CI, 1.95-4.41) and the cohort with MN-HLH (HR, 8.12; 95% CI, 5.51-12.00). Clustering analysis showed overlapping patterns between COVID-CS and CAR-T CRS, while MN-HLH formed a distinct cluster.

Conclusions and relevance: This study of CS syndromes found distinct immune responses within each cohort. The distinct clinical patterns and outcomes associated with different CS etiologies emphasize the importance of early diagnosis and timely intervention.

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Conflict of interest statement

Conflict of Interest Disclosures: Dr Long reported receiving grants from the National Cancer Institute (NCI), National Institutes of Health (NIH) during the conduct of the study. Dr Nair reported serving on the advisory boards of 280 Bio and ADCT outside the submitted work. Dr Khawaja reported receiving grants from Merck, Symbio, and Eurofins Viracor outside the submitted work. Dr Daver reported receiving grants from and being a consultant for Servier, Genentech, Astellas, AbbVie, Amgen, and Trillium; receiving grants from ImmunoGen, Hanmi, Trovagene, Fate Therapeutics, Novimmune, Glycomimetics, Kite, Daiichi-Sankyo, Bristol Meyers Squibb (BMS), Pfizer, and Gilead; being a consultant for Arog, Novartis, Jazz, Celgene, Syndax, Shattuck Labs, Agios, Kite, and Stemline/Menarini; and receiving nonfinancial support from Daiichi-Sankyo, BMS, Pfizer, and Gilead for serving as a consultant, all outside the submitted work. Dr Flowers reported receiving personal fees from AbbVie, Bayer, BeiGene, Celgene, Denovo Biopharma, Foresight Diagnostics, Genentech/Roche, Genmab, Gilead, Karyopharm, N-Power Medicine, Pharmacyclics/Janssen, SeaGen, and Spectrum; having stock or stock options in Foresight Diagnostics and N-Power Medicine; receiving grants for research funding from 4D, Abbvie, Acerta, Adaptimmune, Allogene, Amgen, Bayer, BostonGene, Celgene, Cellectis EMD, Gilead, Genentech/Roche, Guardant, Iovance, Janssen Pharmaceutical, Kite, Morphosys, Nektar, Novartis, Pfizer, Pharmacyclics, Sanofi, Takeda, TG Therapeutics, Xencor, Ziopharm, Burroughs Wellcome Fund, Eastern Cooperative Oncology Group, NCI, and V Foundation; and being the Cancer Prevention and Research Institute of Texas Scholar in Cancer Research outside the submitted work. Dr Neelapu reported receiving grants from Kite/Gilead, BMS, Allogene, Precision Biosciences, Adicet Bio, Sana Biotechnology, and CARGO Therapeutics and personal fees from Kite/Gilead, Merck, SELLAS Life Sciences, Athenex, Allogene, Incyte, Adicet Bio, BMS, Bluebird Bio, Fosun Kite, Sana Biotechnology, Caribou, Astellas Pharma, MorphoSys, Janssen, Chimagen, ImmunoACT, Orna Therapeutics, Takeda, Synthekine, CARSgen, Appia Bio, GlaxoSmithKline, Galapagos, ModeX Therapeutics, and Jazz Pharmaceuticals outside the submitted work. Dr Iyer reported receiving grants from Merck, CRISPR Therapeutics, Acrotech, Pfizer, Dren Bio, Innate, Legend, Electra, March Bio, and the NCI and having stock or stock options in IMPaRT.ai outside the submitted work. No other disclosures were reported.

Figures

Figure 1.
Figure 1.. Box Plots Showing Differences in Laboratory Values by Cytokine Storm Etiology
Circles represent individual laboratory values; the horizontal bar inside the boxes, the median; and the lower and upper ends of the boxes, the first and third quartiles. Whiskers extend from the median up to the lesser of the maximum values and 1.5 times the IQR and down to the greater of the minimum values and 1.5 times the IQR. CAR-T CRS indicates chimeric antigen receptor T-cell cytokine release syndrome; COVID-CS, COVID-19 cytokine storm; IL-6, interleukin 6; MN-HLH, malignant neoplasm–associated hemophagocytic lymphohistiocytosis. aP < .001. bP < .01. cNo significant difference.
Figure 2.
Figure 2.. Heat Map of Laboratory Values and 2-Dimensional Reduction for the 3 Patient Cohorts With Cytokine Storm Etiology
A, Laboratory values (columns) and patients (rows) are clustered. Brackets represent the clustering found in the hierarchical clustering model. Data were transformed using quartile normalization. ALP indicates alkaline phosphatase; ALT, alanine transaminase; CAR-T CRS, chimeric antigen receptor T-cell cytokine release syndrome; COVID-CS, COVID-19 cytokine storm; CRP, C-reactive protein; ESR, erythrocyte sedimentation rate; IL-6, interleukin 6; LDH, lactate dehydrogenase; MN-HLH, malignant neoplasm–associated hemophagocytic lymphohistiocytosis; sIL-2R, soluble interleukin 2 receptor; TNF, tumor necrosis factor; t-SNE, t-distributed stochastic neighbor embedding; WBC, white blood cell.
Figure 3.
Figure 3.. Overall Survival Among the 3 Cytokine Storm Cohorts
Vertical hash marks represent censoring. CAR-T CRS indicates chimeric antigen receptor T-cell cytokine release syndrome; COVID-CS, COVID-19 cytokine storm; MN-HLH, malignant neoplasm–associated hemophagocytic lymphohistiocytosis.
See this image and copyright information in PMC

Comment in

  • doi: 10.1001/jamanetworkopen.2025.3466

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