Computational omics biology model predicts therapy response of refractory acute myeloid leukemia:report of 1 case and review of literature
10.3760/cma.j.cn115356-20220523-00143
- VernacularTitle:应用计算生物组学模型预判难治性急性髓系白血病治疗反应1例并文献复习
- Author:
Lina JIN
1
;
Zhenping PENG
;
Xiaoqiang FAN
;
Juan DU
Author Information
1. 海军军医大学第二附属医院 上海长征医院血液病科 全军骨髓瘤与淋巴瘤疾病中心，上海 200003
- Keywords:
Leukemia, myeloid, acute;
Refractory;
Computational biology;
Drug therapy, combination
- From:
Journal of Leukemia & Lymphoma
2022;31(8):464-469
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the value of computational omics biology model (CBM) in treatment of refractory acute myeloid leukemia (AML) patients.Methods:The clinical data of a refractory AML patient who received personalized therapy regimen predicted by Cellworks tumor response index (TRI) test in November 2018 were retrospectively analyzed. The diagnosis, treatment and the therapeutic efficacy were summarized. The literature related to CBM in AML was reviewed.Results:The patient, a 43-year-old female, was diagnosed as AML accompanied with t(6;11)(q27;q23). She failed to respond after 2 courses of induction therapy, and had poor tolerance of chemotherapy. And then the Cellworks TRI test recommended the 3-drug combination regimen of cladribine, trametinib and cytarabine as the optimal chemotherapy regimen. After 1 course of treatment, the patient achieved complete remission and minimal residual disease negative. After remission, the patient successfully underwent haplo-hematopoietic stem cell transplantation. She experienced a prolonged disease-free survival of 19 months and relapsed in November 2020, and passed away in April 2021. The overall survival time was 28.5 months.Conclusions:Cellworks TRI test based on CBM provides a new therapeutic approach for refractory AML patients, and its personalized treatment regimen based on genomics may improve the survival of patients.
