Abstract 824P
Background
FLT3-ITD is one of the most common genetic abnormalities in acute myeloid leukemia (AML) and suggests a poor prognosis. The impact of FLT3-ITD on the immune microenvirenment requires further elucidation. Studies have shown that FLT3-ITD can significantly change the level of immune cells in the bone marrow in mice.
Methods
Flow cytometry was used to detect the CD47 mean fluorescent intensity (MFI). The FLT3 wildtype (FLT3-OE, FLT3 over expression) or ITD mutation (FLT3-ITD) stable overexpression K562/HEL cells were constructed by lentiviral transfections. The TRANSFAC database was used to predict the transcription factor binding sites of the CD47 promoter. We analyzed the location of CD47 gene on the chromosome, the sequence of promoter and first non-coding exon of HOXB5 via Jaspar online tool. The AML mouse model was constructed by injection of FLT3-ITD cells.
Results
LDH-induced macrophage killing was less in FLT3-ITD cell lines than FLT3-WT cell lines. Expression of CD47 can help protect tumor cells from attack by macrophages. The CD47 MFI of the FLT3-ITD group was higher than that of the control group. The CD47 MFI of the FLT3-ITD group was significantly higher than that of FLT3-OE group and FLT3 normal control (FLT3-NC) group. Flow cytometry results showed that FLT3-ITD impaired the activity of red-stained macrophages to phagocytizing green-stained K652/HEL cells. Using the TRANSFAC database, we found higher relative expression of CD47 gene in FLT3-ITD group than other groups and that HOXB5 may regulate the expression of CD47 at transcriptional level. Integrated analysis of Jasper online tool, dual luciferase reporter gene assay and ChIP experiment suggest that HOXB5 directly activate CD47. Compared with other groups, combination of CD47 inhibitor and FLT3-ITD inhibitor Quizartinib (AC220) significantly enhanced phagocytic activity of macrophages. The mouse model of AML further showed that combination of CD47 inhibitor and Quizartinib significantly reduced tumor burden in spleen and bone marrow.
Conclusions
Our data show that FLT3-ITD can induce immune escape to macrophages by upregulating CD47. Combination therapy with CD47 inhibitor and FLT3-ITD inhibitor can be promising for the treatment of FLT3-ITD AML.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Sun Yat-sen University Start-Up Funding.
Disclosure
All authors have declared no conflicts of interest.
Resources from the same session
1182P - Determination of tumor PSMA expression in prostate cancer from blood using a novel epigenomic liquid biopsy platform
Presenter: Praful Ravi
Session: Poster session 09
1183P - Impact of multicancer early detection (MCED) test on participant-reported outcomes (PRO) and behavioral intentions by cancer risk
Presenter: Christina Dilaveri
Session: Poster session 09
1184P - Early real-world experience with positive multi-cancer early detection (MCED) test cases and negative initial diagnostic work-up
Presenter: Candace Westgate
Session: Poster session 09
1185P - Clinical applications of a novel blood-based fragmentomics assay for lung cancer detection
Presenter: Marc Siegel
Session: Poster session 09
1186P - SmartCS-LPLLM: Enhancing early cancer detection through ctDNA methylation analysis leveraging large language models
Presenter: Li Chao
Session: Poster session 09
1187P - Molecular diagnosis of lung cancer via ctDNA and ctRNA detection on bronchoscopic fluid specimens from 31 patients: A retrospective analysis
Presenter: Vincent Fallet
Session: Poster session 09
1188P - Modeled economic and clinical impact of a multi-cancer early detection (MCED) test in a population with hereditary cancer syndromes
Presenter: Sana Raoof
Session: Poster session 09
1189P - Cancer genome interpreter: A data-driven tool for tumor mutation interpretation
Presenter: Santiago Demajo
Session: Poster session 09
1190P - Circulating tumor DNA from the tumor-draining pulmonary vein as a biomarker in resected non-small cell lung cancer
Presenter: Raphael Werner
Session: Poster session 09
1191P - Efficient lung cancer stage prediction and outcome informatics with Bayesian deep learning and MCMC method
Presenter: Maria Gkotzamanidou
Session: Poster session 09