Personalized therapy for acute myeloid leukemia.

Patient-specific ex vivo drug sensitivity and resistance screening can identify rational drug candidates for the testing of personalized targeted therapy. An iterative approach of genomic and drug susceptibility characterization at sequential time points during clinical trials of targeted therapy in acute myeloid leukemia may be useful both for characterizing mechanisms of resistance and clonal evolution and also for identification of novel therapeutic targets and drug combinations.

Hourigan CS ，Karp JE 《-》

Individualized systems medicine strategy to tailor treatments for patients with chemorefractory acute myeloid leukemia.

We present an individualized systems medicine (ISM) approach to optimize cancer drug therapies one patient at a time. ISM is based on (i) molecular profiling and ex vivo drug sensitivity and resistance testing (DSRT) of patients' cancer cells to 187 oncology drugs, (ii) clinical implementation of therapies predicted to be effective, and (iii) studying consecutive samples from the treated patients to understand the basis of resistance. Here, application of ISM to 28 samples from patients with acute myeloid leukemia (AML) uncovered five major taxonomic drug-response subtypes based on DSRT profiles, some with distinct genomic features (e.g., MLL gene fusions in subgroup IV and FLT3-ITD mutations in subgroup V). Therapy based on DSRT resulted in several clinical responses. After progression under DSRT-guided therapies, AML cells displayed significant clonal evolution and novel genomic changes potentially explaining resistance, whereas ex vivo DSRT data showed resistance to the clinically applied drugs and new vulnerabilities to previously ineffective drugs. Here, we demonstrate an ISM strategy to optimize safe and effective personalized cancer therapies for individual patients as well as to understand and predict disease evolution and the next line of therapy. This approach could facilitate systematic drug repositioning of approved targeted drugs as well as help to prioritize and de-risk emerging drugs for clinical testing.

Pemovska T ，Kontro M ，Yadav B ，Edgren H ，Eldfors S ，Szwajda A ，Almusa H ，Bespalov MM ，Ellonen P ，Elonen E ，Gjertsen BT ，Karjalainen R ，Kulesskiy E ，Lagström S ，Lehto A ，Lepistö M ，Lundán T ，Majumder MM ，Marti JM ，Mattila P ，Murumägi A ，Mustjoki S ，Palva A ，Parsons A ，Pirttinen T ，Rämet ME ，Suvela M ，Turunen L ，Västrik I ，Wolf M ，Knowles J ，Aittokallio T ，Heckman CA ，Porkka K ，Kallioniemi O ，Wennerberg K ... -  《-》

Genetic biomarkers of drug resistance: A compass of prognosis and targeted therapy in acute myeloid leukemia.

Acute myeloid leukemia (AML) is a highly aggressive hematological malignancy with complex heterogenous genetic and biological nature. Thus, prognostic prediction and targeted therapies might contribute to better chemotherapeutic response. However, the emergence of multidrug resistance (MDR) markedly impedes chemotherapeutic efficacy and dictates poor prognosis. Therefore, prior evaluation of chemoresistance is of great importance in therapeutic decision making and prognosis. In recent years, preclinical studies on chemoresistance have unveiled a compendium of underlying molecular basis, which facilitated the development of targetable small molecules. Furthermore, routing genomic sequencing has identified various genomic aberrations driving cellular response during the course of therapeutic treatment through adaptive mechanisms of drug resistance, some of which serve as prognostic biomarkers in risk stratification. However, the underlying mechanisms of MDR have challenged the certainty of the prognostic significance of some mutations. This review aims to provide a comprehensive understanding of the role of MDR in therapeutic decision making and prognostic prediction in AML. We present an updated genetic landscape of the predominant mechanisms of drug resistance with novel targeted therapies and potential prognostic biomarkers from preclinical and clinical chemoresistance studies in AML. We particularly highlight the unfolded protein response (UPR) that has emerged as a critical regulatory pathway in chemoresistance of AML with promising therapeutic horizon. Futhermore, we outline the most prevalent mutations associated with mechanisms of chemoresistance and delineate the future directions to improve the current prognostic tools. The molecular analysis of chemoresistance integrated with genetic profiling will facilitate decision making towards personalized prognostic prediction and enhanced therapeutic efficacy.

Long L ，Assaraf YG ，Lei ZN ，Peng H ，Yang L ，Chen ZS ，Ren S ... -  《-》

Treatment of acute myeloid leukemia in the next decade - Towards real-time functional testing and personalized medicine.

Information arising from next generation sequencing of leukemia genome has shed important light on the heterogeneous and combinatorial driver events in acute myeloid leukemia (AML). It has also provided insight into its intricate signaling pathways operative in the disease pathogenesis. These have also become biomarkers and targets for therapeutic intervention. Emerging evidence from in vitro drug screening has demonstrated its potential value in predicting clinical drug responses in specific AML subtypes. However, the best culture conditions and readouts have yet to be standardized and the drugs included in these screening exercises frequently revised in view of the rapid emergence of new therapeutic agents in the oncology field. Testing of leukemia cell functions, including BCL2 profiling, has also been used to predict treatment response to conventional chemotherapy and hypomethylating agents as well as BCL2 antagonist in small patient cohorts. These platforms should be integrated into future clinical trials to develop personalized treatment of AML.

Lam SS ，He AB ，Leung AY 《-》

A machine learning approach to integrate big data for precision medicine in acute myeloid leukemia.

Lee SI ，Celik S ，Logsdon BA ，Lundberg SM ，Martins TJ ，Oehler VG ，Estey EH ，Miller CP ，Chien S ，Dai J ，Saxena A ，Blau CA ，Becker PS ... -  《Nature Communications》