Therapeutic biomarkers in acute myeloid leukemia: functional and genomic approaches.

Acute myeloid leukemia (AML) is clinically and genetically a heterogeneous disease characterized by clonal expansion of abnormal hematopoietic progenitors. Genomic approaches to precision medicine have been implemented to direct targeted therapy for subgroups of AML patients, for instance, IDH inhibitors for IDH1/2 mutated patients, and FLT3 inhibitors with FLT3 mutated patients. While next generation sequencing for genetic mutations has improved treatment outcomes, only a fraction of AML patients benefit due to the low prevalence of actionable targets. In recent years, the adoption of newer functional technologies for quantitative phenotypic analysis and patient-derived avatar models has strengthened the potential for generalized functional precision medicine approach. However, functional approach requires robust standardization for multiple variables such as functional parameters, time of drug exposure and drug concentration for making in vitro predictions. In this review, we first summarize genomic and functional therapeutic biomarkers adopted for AML therapy, followed by challenges associated with these approaches, and finally, the future strategies to enhance the implementation of precision medicine.

Acquired Multidrug Resistance in AML Is Caused by Low Apoptotic Priming in Relapsed Myeloblasts.

In many cancers, mortality is associated with the emergence of relapse with multidrug resistance (MDR). Thus far, the investigation of cancer relapse mechanisms has largely focused on acquired genetic mutations. Using acute myeloid leukemia (AML) patient-derived xenografts (PDX), we systematically elucidated a basis of MDR and identified drug sensitivity in relapsed AML. We derived pharmacologic sensitivity for 22 AML PDX models using dynamic BH3 profiling (DBP), together with genomics and transcriptomics. Using in vivo acquired resistant PDXs, we found that resistance to unrelated, narrowly targeted agents in distinct PDXs was accompanied by broad resistance to drugs with disparate mechanisms. Moreover, baseline mitochondrial apoptotic priming was consistently reduced regardless of the class of drug-inducing selection. By applying DBP, we identified drugs showing effective in vivo activity in resistant models. This study implies evasion of apoptosis drives drug resistance and demonstrates the feasibility of the DBP approach to identify active drugs for patients with relapsed AML. SIGNIFICANCE: Acquired resistance to targeted therapy remains challenging in AML. We found that reduction in mitochondrial priming and common transcriptomic signatures was a conserved mechanism of acquired resistance across different drug classes in vivo. Drugs active in vivo can be identified even in the multidrug resistant state by DBP.

Physicochemical Significance of Topological Indices: Importance in Drug Discovery Research.

BACKGROUND: Quantitative Structure-Activity Relationship (QSAR) studies describing the correlations between biological activity as dependent parameters and physicochemical and structural descriptors, including topological indices (TIs) as independent parameters, play an important role in drug discovery research. The emergence of graph theory in exploring the structural attributes of the chemical space has led to the evolution of various TIs, which have made their way into drug discovery. The TIs are easy to compute compared to the empirical parameters, but they lack physiochemical interpretation, which is essential in understanding the mechanism of action. OBJECTIVES: Hence, efforts have been made to review the work on the advances in topological indices, their physicochemical significance, and their role in developing QSAR models. METHODS: A literature search has been carried out, and the research article providing evidence of the physicochemical significance of the topological parameters as well as some recent studies utilizing these parameters in the development of QSAR models, have been evaluated. RESULT: In this review, the physicochemical significance of TIs have been described through their correlations between empirical parameters in terms of explainable physicochemical properties, along with their application in the development of predictive QSAR models. CONCLUSION: Most of these findings suggest a common trend of TIs correlation with MR rather than logP or other parameters; nevertheless, the developed models may be useful in both drug and vaccine development.

Combinatorial drug therapy in cancer - New insights.

Cancer can arise due to mutations in numerous pathways present in our body and thus has many alternatives for getting aggravated. Due to this attribute, it gets difficult to treat cancer patients with monotherapy alone and has a risk of not being eliminated to the full extent. This necessitates the introduction of combinatorial therapy as it employs cancer treatment using more than one method and shows a greater success rate. Combinatorial therapy involves a complementary combination of two different therapies like a combination of radio and immunotherapy or a combination of drugs that can target more than one pathway of cancer formation like combining CDK targeting drugs with Growth factors targeting drugs. In this review, we discuss the various aspects of cancer which include, its causes; four regulatory mechanisms namely: apoptosis, cyclin-dependent kinases, tumor suppressor genes, and growth factors; some of the pathways involved; treatment: monotherapy and combinatorial therapy and combinatorial drug formulation in chemotherapy. The present review gives a holistic account of the different mechanisms of therapies and also drug combinations that may serve to not only complement the monotherapy but can also surpass the resistance against monotherapy agents.