Abstract BACKGROUND: Concentrations of specific cytokines/chemokines are consistently associated with patient prognosis in different cancer types. In the context of chronic lymphocytic leukemia (CLL), the impact of baseline cytokine levels on biological features and clinical outcomes remains poorly understood. METHODS: Plasma from newly diagnosed CLL patients was extracted and then analyzed using a bead-based 27-plex enzymatic assay. Different optimal cut-offs for overall survival (OS), probability of Richter transformation (RT) and second malignancies risk analyses were defined using maximally selected rank statistics for every specific cytokine/chemokine. The machine-learning algorithms “self-organizing map” (SOM) and “K-means” were applied to divide patients into clusters based on cytokine/chemokine levels. RESULTS: A total of 244 patients with newly diagnosed CLL were included. Median age at diagnosis was 68.9 years; 73 patients (29.9%) had unmutated immunoglobulin heavy chain variable region (IGHV) genes, and 16 (6.6%) had TP53 disruption. After a median follow-up of 13.4 years, the median OS was 15.7 years. By correlating cytokines/chemokines with patient baseline clinical and molecular features, elevated MIP-1α levels were significantly associated with unmutated IGHV genes (p0.0001), greater lymph node diameter (p0.0001), and advanced Rai and Binet stages (both p0.0001). Higher IP-10 levels significantly associated with advanced Rai (p=0.02) and Binet (p=0.01) stages. Elevated GM-CSF levels were associated with del(17p) (p=0.03). At diagnosis, multiple cytokines/chemokines with levels exceeding the optimal cut-offs for predicting OS, namely MIP-1α (p= 0.001), IP-10 (p= 0.003), G-CSF (p= 0.011), PDGF-BB (p= 0.023), IL-4 (p=0.023), GM-CSF (p=0.025), IL-5 (p=0.025), IL-6 (p=0.027), and IL-2 (p=0.027) were significantly associated with shorter survival. In multivariate analysis (adjusted for age, IGHV, and TP53 status), high levels of IL-4, using a cut-off of 5.78 pg/mL, independently associated with shorter OS (HR 2.2, p=0.008). Pathway gene enrichment analysis revealed that cytokines/chemokines predicting shorter OS are involved in key molecular pathways regulating cell proliferation, survival, and apoptosis. In particular, G-CSF, GM-CSF, IL-2, IL-4, IL-5, IL-6, and PDGF-BB clustered in the JAK-STAT signaling pathway (fold enrichment 109.9, p=2.23E-12), whereas G-CSF, IL-2, IL-4, IL-6, and PDGF-BB clustered in the PI3K-Akt pathway (fold enrichment 35.9, p=9.17E-07). Regarding RT, high levels of GM-CSF (p0.0001), MIP1-α (p=0.034), IL-4 (p=0.034), and IL-10 (p=0.034) were significantly associated with increased risk of RT in univariate analysis. GM-CSF, with a cutoff of 0.86 pg/mL, independently predicted RT in multivariate analysis (HR 9.32, p=0.009). Moreover, among patients who developed a second malignancy after CLL diagnosis, high levels of MIP-1β (p=0.0001), RANTES (p=0.023), and MIP-1α (p=0.023) were linked to shorter time of cancer occurrence. Unsupervised clustering identified three patient groups, namely clusters 1, 2, and 3, with distinct cytokine/chemokine profiles. Cluster 1 is characterized by elevated levels of MIP-1α, MIP-1β, IL-6, TNF-α, IL-8, GCSF, IL-2, and VEGF. Cluster 2 is associated with generally low cytokine/chemokine expression, while cluster 3 shows higher concentrations of IL-10, IL-9, IL-7, IP-10, and RANTES. In the pathway gene enrichment analysis, cluster 1 displayed higher activation of inflammation-related pathways, such as the PI3K/Akt signaling pathway. Conversely, cluster 3 was characterized by the activation of autoimmunity and infection response pathways. Survival analysis demonstrated that patients in cluster 1 had significantly worse OS (p = 0.02), a finding confirmed in multivariate analysis (p = 0.02). Furthermore, Binet A and B patients in cluster 3 exhibited a significantly shorter time to first treatment (TTFT) compared to the other clusters (p = 0.02).CONCLUSIONS: Plasma levels of immunomodulatory cytokines/chemokines are associated with unfavorable clinical and biological features at the time of CLL diagnosis and might predict lower OS, higher risk of RT and second malignancies. Moreover, patients can be divided into groups based on their plasma cytokine/chemokine profile to better stratify OS and TTFT. If confirmed also in the context of patients treated with BTK inhibitors and BCL2 inhibitors, cytokine/chemokine levels might integrate current prognostic biomarkers in CLL.
Cosentino et al. (Mon,) studied this question.