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974 The FLT3-like Gene Expression Signature Predicts Response to Quizartinib in Wild-Type FLT3 Acute Myeloid Leukemia: An Analysis of the Pethema Quiwi Trial

Program: Oral and Poster Abstracts
Type: Oral
Session: 617. Acute Myeloid Leukemias: Biomarkers, Molecular Markers and Minimal Residual Disease in Diagnosis and Prognosis: Response Predictors to Targeted Therapies and Transplant
Hematology Disease Topics & Pathways:
Acute Myeloid Malignancies, AML, Diseases, Myeloid Malignancies
Monday, December 11, 2023: 4:45 PM

Adrian Mosquera Orgueira, MD, PhD1*, Manuel Perez Encinas2*, Jose Angel Diaz Arias3*, Rebeca Rodriguez Veiga, MD4*, Juan Miguel Bergua Burgues5*, Jesús Lorenzo Algarra6*, Carmen Botella7*, Jose Antonio Perez Simon8*, Teresa Bernal9*, Mar Tormo, M.D.10, Maria Calbacho11*, Olga Salamero, MD12*, Josefina Serrano, MD13*, Victor Noriega14*, Juan Antonio Lopez Lopez15*, Susana Vives16*, Mercedes Colorado17*, Jose Luis Lopez Lorenzo, MD18*, Maria Vidriales Vicente19*, Raimundo Garcia Boyero20*, Maria Teresa Olave Rubio21*, Pilar Herrera Puente22*, Olga Arce23*, Manuel Barrios Garcia24*, Maria Jose Sayas Lloris25*, Marta Polo26*, Maria Isabel Gomez Roncero27*, Eva Barragan, PhD28*, Rosa Ayala, MD, PhD29*, Carmen Chillon30*, Maria Jose Calasanz, PhD31*, Blanca Boluda32*, Andres Peleteiro Raindo33*, Raquel Amigo34*, David Martinez Cuadron35*, Jorge Labrador36* and Pau Montesinos, PhD, MD37*

1University Hospital of Santiago de Compostela, Department of Hematology, IDIS, SANTIAGO DE COMPOSTELA, Spain
2University Hospital of Santiago de Compostela, Department of Hematology, IDIS, SANTIAGO, ESP
3University Hospital of Santiago de Compostela, Department of Hematology, IDIS, A Coruña, Spain
4Hospital Universitary i Politecnic La Fe, VALENCIA, ESP
5Hospital San Pedro de Alcántara, Cáceres, Spain
6Hospital General de Albacete, Albacete, ESP
7Hospital General Universitario de Alicante, Alicante, Spain
8University Hospital Virgen del Rocío, Sevilla, Spain
9Hospital Universitario Central De Asturias, Oviedo, ESP
10Hospital Clínico Universitario de Valencia, Instituto de Investigación Sanitaria INCLIVA, Valencia, Spain
11Hospital Universitario 12 de Octubre, Madrid, Spain
12Hospital Vall d'Hebron, Barcelona, Barcelona, ESP
13Hospital Universitario Reina Sofía, IMIBIC, Cordoba, ESP
14Hospital Clínico de A Coruña, A Coruña, Spain
15Hospital Universitario de Jaen, Jaen, Spain
16Hospital Germans Trias i Pujol, Badalona, ESP
17Hospital Universitario Marqués De Valdecilla, Santander, Spain
18Fundacion Jimenez Diaz, Madrid, ESP
19Hospital Universitario de Salamanca, IBSAL, CIBER-ONC number CB16/12/00233 y Centro de Investigación, Salamanca, Spain
20Hospital General Universitario de Castellon, Castellon, Spain
21Hospital Clinico Universitario Lorenzo Blesa, Zaragoza, ESP
22Hospital Universitario Ramon y Cajal, Madrid, ESP
23Hospital Universitario de Basurto, Bilbao, Spain
24Hospital Universitario Regional de Malaga, Malaga, Spain
25Hospital Dr. Peset, ZARAGOZA, ESP
26Hospital Clinico San Carlos, Madrid, Ma, ESP
27Hospital Virgen de la Salud, Toledo, Spain
28Hematology Research Group, Instituto de Investigación Sanitaria La Fe, Valencia, Spain
29Hospital Universitario 12 de Octubre, I+12, CNIO, Complutense University, CIBERONC, Madrid, Spain
30Hospital Universitario de Salamanca; (CIC, IBMCC USAL-CSIC), Salamanca, ESP
31Cancer Center Clinica Universidad de Navarra, Centro de Investigación Médica Aplicada (CIMA), IDISNA, CIBER-ONC number CB16/12/00369 and CB16/12/00489, Pamplona, Spain
32Hospital Universitari I Politècnic La Fe, Valencia, ESP
33University Hospital of Santiago De Compostela, Department of Hematology, IDIS, SANTIAGO DE COMPOSTELA, ESP
34Instituto de Investigaciones Santiarias La Fe, Valencia, Spain
35Hospital Universitari i Politecnic La Fe, Valencia, Spain
36Hospital Universitario de Burgos, Universidad Isabel I, Burgos, ESP
37Hospital Universitari i Politecnic la Fe, Valencia, Spain


The identification of predictive biomarkers is crucial for guiding treatment decisions in acute myeloid leukemia (AML). Previously, we identified a FLT3-like gene expression signature in FLT3 wild-type AML patients, which clustered a variable proportion of FLT3 wild-type patients with FLT3-ITD and TKD mutated patients. The QUIWI trial was a randomized, placebo-controlled, phase II study preliminary showing a significant increase in overall survival (OS) in wild-type FLT3 AML patients treated with the FLT3 inhibitor quizartinib (Quiza) plus standard chemotherapy. This preplanned correlative study was designed to assess the value of the FLT3-like signature to predict responses to Quiza.


We performed RNA sequencing (RNAseq) analysis on a subset of patients from the clinical trial. RNA was extracted using standard methods, followed by assessment of nucleic acid integrity (TapeStation) and quantification (Qubit). Total mRNA sequencing was performed using polyA RNAseq with TruSeq technology. A total of 206 adequate samples from bone marrow and peripheral blood were sequenced (161 from FLT3-ITD negative enrolled in QUIWI; and 55 from FLT3-ITD positive patients who were screen failure of the QUIWI trial by this reason). The sequences were aligned to the GRCh37 reference genome using the Hisat algorithm. Gene expression quantification was performed using the Bioconductor workflow, and gene expression estimates (FPKM) were obtained. The gene expression estimates were log2 normalized. Finally, those genes mapping to the original FLT3-like signature (595 genes) were selected for downstream analysis. Clustering was based on the hierarchical method, using standard euclidean distance metrics. OS was defined as time from start of screening to death. Event-free survival (EFS) was defined as time from randomization to failure to achieve CR/CRi after 1 or 2 cycles, death in CR/CRi, or relapse (whichever occurred the first). Relapse-free survival was defined as time from randomization to disease relapse or death by any cause.


Among the total 206 patients, a cluster of 54.37% (N=112) was enriched in FLT3-mutant cases (71.11% of cases, Figure 1A). This subgroup comprised 49.67% of wild-type FLT3 cases (N=80), hereafter FLT3-like patients. In the group of not FLT3-like patients, no differences were identified between the placebo and Quiza group in the total number of deaths (Fisher’s p-value, 0.63), EFS (cox p-value, 0.83; HR 1.07 [0.56-2.06]), RFS (cox p-value 0.76; HR 0.88 [0.38-2.01]) and OS (cox p-value, 0.62; HR 1.22 [0.55-2.67]). Among FLT3-like patients, significant differences were identified in the total number of deaths (Fisher’s p-value, 0.004), EFS (cox p-value, 0.009; HR 0.45 [0.25-0.82], RFS (cox p-value 0.01, HR 0.37 [0.18-0.79]) and OS (cox p-value 0.01, HR, 0.41 [0.20-0.84]) (Figure 1B). No statistically significant association was observed between the FLT3-like pattern and the ELN-17 classification: 30.4% were low risk, 40.5% intermediate risk, 29.1% high risk.


The FLT3-like gene expression signature successfully identified a subset of patients who derived the most benefit from Quiz, while patients without the FLT3-like signature did not demonstrate a benefit compared with placebo. These findings support the use of the FLT3-like signature as a potential biomarker to identify those wild-type FLT3 AML patients who may benefit from Quiz, providing a valuable insight for personalized treatment in AML.

Disclosures: Mosquera Orgueira: AstraZeneca: Consultancy; Janssen: Consultancy. Bergua Burgues: Fundesalud. Grants of Europena funds.Daychii: Research Funding; Daychii: Consultancy; Hospital San Pedro de Alcántara. Servicio de Hematologia. Cáceres. SPAIN: Current Employment. Tormo: MSD: Honoraria; SOBI: Other: Participation on Data Safety Monitoring Board; Gilead: Honoraria; BMS: Honoraria; Pfizer: Honoraria; Jannsen: Other: Support for attending meetings; Astellas: Honoraria; AbbVie: Honoraria; Jazz: Other: support for attending meetings. Salamero: BMS: Consultancy, Honoraria; Jazz: Consultancy, Honoraria; Astellas: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria. Ayala: Novartis: Consultancy, Speakers Bureau; Incyte: Consultancy; Astellas, BMS: Speakers Bureau. Montesinos: Ryvu: Consultancy; Abbvie: Consultancy, Research Funding, Speakers Bureau; Menarini-Stemline: Consultancy, Research Funding; Astellas: Consultancy, Speakers Bureau; Kura oncology: Consultancy; Jazz pharma: Consultancy, Research Funding, Speakers Bureau; Janssen: Speakers Bureau; GILEAD: Consultancy; Takeda: Consultancy, Research Funding; Daiichi Sankyo: Consultancy, Research Funding; INCYTE: Consultancy; Novartis: Consultancy, Research Funding; OTSUKA: Consultancy; BEIGENE: Consultancy; NERVIANO: Consultancy; Celgene: Consultancy; Pfizer: Consultancy, Research Funding, Speakers Bureau; BMS: Consultancy, Other, Research Funding.

*signifies non-member of ASH