0000000000470653

AUTHOR

Alexey Moiseev

showing 3 related works from this author

Oncobox, gene expression-based second opinion system for predicting response to treatment in advanced solid tumors.

2019

e13143 Background: Anticancer Targeted Drugs (ATDs) specifically target one or a few types of tumor-related molecules in a cell. More than two hundred of ATDs were approved worldwide. They have different mechanisms of action and are effective for different cohorts of patients. However, many individual cases remain poorly responsive and it is of great importance to identify predictive markers of ATD efficacy. Our aim was to develop a platform enabling smart selection of the most efficient ATD therapies. Methods: We generated a second-opinion platform for clinical oncologists termed Oncobox. It is based on the analysis of gene expression profile of a cancer sample in comparison with the corr…

Cancer Researchbusiness.industrySecond opinionCellResponse to treatment03 medical and health sciences0302 clinical medicinemedicine.anatomical_structureOncology030220 oncology & carcinogenesisGene expressionCancer researchMedicinebusiness030215 immunologyJournal of Clinical Oncology
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Disparity between Inter-Patient Molecular Heterogeneity and Repertoires of Target Drugs Used for Different Types of Cancer in Clinical Oncology

2020

Inter-patient molecular heterogeneity is the major declared driver of an expanding variety of anticancer drugs and personalizing their prescriptions. Here, we compared interpatient molecular heterogeneities of tumors and repertoires of drugs or their molecular targets currently in use in clinical oncology. We estimated molecular heterogeneity using genomic (whole exome sequencing) and transcriptomic (RNA sequencing) data for 4890 tumors taken from The Cancer Genome Atlas database. For thirteen major cancer types, we compared heterogeneities at the levels of mutations and gene expression with the repertoires of targeted therapeutics and their molecular targets accepted by the current guideli…

Gene mutationMedical OncologychemotherapyGenomeTranscriptomelcsh:ChemistryDrug Delivery SystemsProstateNeoplasmstumor heterogeneityMedicineCluster AnalysisMolecular Targeted TherapyPathology MolecularPrecision Medicinelcsh:QH301-705.5targeted therapeuticscancer drugsSpectroscopyExome sequencingGeneral MedicineGenomicspersonalized medicineComputer Science ApplicationsDrug repositioningmedicine.anatomical_structureAntineoplastic AgentsComputational biologyCatalysisArticleInorganic Chemistrymolecular diagnosticsGenetic HeterogeneityDrug TherapyExome SequencingHumansPhysical and Theoretical ChemistryMolecular Biologygenomeclinical oncologybusiness.industryOrganic ChemistryMolecular diagnosticsmutationslcsh:Biology (General)lcsh:QD1-999MutationPersonalized medicinebusinesstranscriptomeInternational Journal of Molecular Sciences
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RNA sequencing for research and diagnostics in clinical oncology.

2020

Molecular diagnostics is becoming one of the major drivers of personalized oncology. With hundreds of different approved anticancer drugs and regimens of their administration, selecting the proper treatment for a patient is at least nontrivial task. This is especially sound for the cases of recurrent and metastatic cancers where the standard lines of therapy failed. Recent trials demonstrated that mutation assays have a strong limitation in personalized selection of therapeutics, consequently, most of the drugs cannot be ranked and only a small percentage of patients can benefit from the screening. Other approaches are, therefore, needed to address a problem of finding proper targeted thera…

0301 basic medicineProteomicsCancer ResearchGenomicsComputational biologyMedical OncologyGenomeTranscriptome03 medical and health sciences0302 clinical medicineNeoplasmsBiomarkers TumorMedicineHumansGeneClinical Oncologybusiness.industrySequence Analysis RNAGene Expression ProfilingRNAComputational BiologyGenomicsMolecular diagnosticsPrognosis030104 developmental biology030220 oncology & carcinogenesisPersonalized medicinebusinessSeminars in cancer biology
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