T/NK Cell-Associated Transcriptomic Profile Informs Response to FLT3 Inhibitors in Acute Myeloid Leukemia
Authors: Nanni Jacopo , Vadakekolathu Jayakumar , Bandini Lorenza , Ciciarello Marilena , Volkava Karyna , Bruno Samantha , Robustelli Valentina , Zannoni Letizia , Sartor Chiara , Cristiano Gianluca , Zingarelli Federico , Romagnoli Andrea Davide , Azzimondi Caterina , Ardizzoia Federica , Ciruolo Raffaele , Marconi Giovanni , Venturi Claudia , Kanapari Ajsi , Mazzocchetti Gaia , Simonetti Giorgia , Ghetti Martina , Testoni Nicoletta , Parisi Sarah , Paolini Stefania , Soverini Simona , Ottaviani Emanuela , Papayannidis Cristina , Cavo Michele , Rutella Sergio , Curti Antonio 
Published: December 2024

Background: FLT3 mutations (FLT3-mut)are one of the most frequent genetic alteration in acute myeloid leukemia (AML). The FLT3 receptor exerts a central role in normal hematopoiesis, especially in monocytic and dendritic-cell differentiation and early-lymphopoiesis. Despite significative improvements in FLT3-mut AML prognosis since FLT3 inhibitors (FLT3i) adoption, still a significant proportion of patients are refractory or relapse after FLT3i-based therapies. Thus far, translational studies have mainly illustrated intrinsic/mutational resistance mechanisms; however, less is known regarding the impact of FLT3-mut on the AML immune microenvironment.This study aims at investigating whether FLT3-mut is associated with a peculiar AML immune transcriptomic profile and whether these features affect response to FLT3i.

Methods: We initially re-analyzed legacy RNA-seq data from the Beat-AML Master Trial, which includes a FLT3-mut (FLT3-pos) and a FLT3-wt (FLT3-neg) cohort of samples. Published gene signatures related to T-cell dysfunction in cancer (Chu et al, Nature Medicine 2023) and AML stem cell hierarchies (Zeng et al, Nat. Med. 2023 and Long et al, Cancer Cell 2022) were used as input to compute gene set enrichment scores. To determine the potential prognostic impact of transcriptomic differences related to FLT3 mutational status, we applied the least absolute shrinkage and selection operator (LASSO)/Cox PH statistical method on DEGs between FLT3-pos and FLT3-neg and we built a prognostic score (PS) which was then used for validation purposes in the entire BEAT-AML2 and TCGA cohorts. The Kaplan-Meier method was used to estimate overall survival (OS). We then profiled a wet-lab cohort of 37 FLT3-mut AML patients treated either with Midostaurin plus chemotherapy (M) or Gilteritinib (G) at Bologna Hematology Institute by using the PanCancer IO 360 Panel (NanoString Technologies, San Diego, CA). Data were collected in accordance with GCP and Helsinki declaration. A public sc-RNA-seq dataset of newly-diagnosed (ND) AML (Dufva et al. Cancer Cell 2020) was used to map DEGs between Responders (R) and Non-Responders (NR) to FLT3i to well annotated BM cell populations. The MV411 and THP1 cell lines were used for in-vitro validation.

Results: We initially compared transcriptomic data from FLT3-pos (n= 173) and a randomly selected subgroup of FLT3-neg (n=185) Beat-AML samples. FLT3-pos cases had a lower ssGSEA score for CD8+ and CD4+ T-Cell functional signatures (e.g. T-cell Activation/Effector function, Exhaustion and Interferon Response). Furthermore, FLT3-pos cases had higher stemness scores, whereas FLT3-neg cases showed a more differentiated state (Monocytic/Erythroid). Using LASSO-penalized regression for feature selection, while also mitigating data collinearity, on the DEGs between FLT3-pos and FLT3-neg cases, we identified 46 genes with non-zero coefficients and we computed a transcriptomic prognostic score (FLT3-PS) for OS (p&lt;0.0001). By applying the same FLT3-PS to the entire BEAT-AML2 and TCGA cohorts, the score retained its prognostic impact irrespective of FLT3 mutational status. The 16 immune-related genes in the PS (34.8 %) maintained the ability to parse patient survival (p&lt;0.0001).

We then quantified immune gene expression in BM aspirates from 17 ND and 20 Relapsed/Refractory FLT3-mut AMLs who received M and G therapy, respectively. Significant differences in immune profiles were observed comparing R with NR, including a higher expression of genes involved in T/NK function in G-R. By projecting the top 30 DEGs genes between G-R and G-NR onto a sc-RNA-seq AML-BM map, we found that they were primarily expressed by effector and central memory CD8+ T cells and NK cells. Conversely, by projecting the top 30 DEGs between M-R and M-NR a wider contribution from different cell-types emerged, with a higher expression of innate immunity genes among M-R.

Finally, our in-vitro experiments supported the in-vivo data by showing that IFN type I-based immune responses are modulated by G in FLT3-mut cell lines.

Conclusion: This study provides evidence that FLT3 mutational status is associated with a unique T-cell activation profile and AML maturation state, and that T/NK cell-associated genes correlate with response to FLT3i. Our RNA metric of FLT3 mutational status could be utilized to refine patient stratification in future clinical trials.

S.R. & A.C. equally contributed