Human Interactomics: Comparative Analysis of Different Protein Interaction Resources and Construction of a Cancer Protein–Drug Bipartite Network

Rivas, Javier De Las; Alonso-López, Diego; Arroyo, Monica M.

doi:10.1016/bs.apcsb.2017.09.002

Cited by 11 publications

(11 citation statements)

References 33 publications

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“…One of the most comprehensive efforts was accomplished ten years ago using genome-wide expression profiling in the diagnosis and subclassification of many different types of leukemias [ 230 ]. Following this line of research, artificial intelligence (AI) and machine learning (ML) methods have been proven to be also very useful for integrating large-scale- omics data from cancer patients and for analyzing gene expression profiles in response to different drugs [ 231 ]. In this scenario, positive associations between gene expression and anticancer drug activity allowed the discovery of gene targets for the drugs tested [ 232 ].…”

Section: Methodologies To Access Tki Resistancementioning

confidence: 99%

Resistance to Tyrosine Kinase Inhibitors in Chronic Myeloid Leukemia—From Molecular Mechanisms to Clinical Relevance

Alves

Gonçalves

Rutella

et al. 2021

Cancers

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Resistance to targeted therapies is a complex and multifactorial process that culminates in the selection of a cancer clone with the ability to evade treatment. Chronic myeloid leukemia (CML) was the first malignancy recognized to be associated with a genetic alteration, the t(9;22)(q34;q11). This translocation originates the BCR-ABL1 fusion gene, encoding the cytoplasmic chimeric BCR-ABL1 protein that displays an abnormally high tyrosine kinase activity. Although the vast majority of patients with CML respond to Imatinib, a tyrosine kinase inhibitor (TKI), resistance might occur either de novo or during treatment. In CML, the TKI resistance mechanisms are usually subdivided into BCR-ABL1-dependent and independent mechanisms. Furthermore, patients’ compliance/adherence to therapy is critical to CML management. Techniques with enhanced sensitivity like NGS and dPCR, the use of artificial intelligence (AI) techniques, and the development of mathematical modeling and computational prediction methods could reveal the underlying mechanisms of drug resistance and facilitate the design of more effective treatment strategies for improving drug efficacy in CML patients. Here we review the molecular mechanisms and other factors involved in resistance to TKIs in CML and the new methodologies to access these mechanisms, and the therapeutic approaches to circumvent TKI resistance.

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Section: Methodologies To Access Tki Resistancementioning

confidence: 99%

Resistance to Tyrosine Kinase Inhibitors in Chronic Myeloid Leukemia—From Molecular Mechanisms to Clinical Relevance

Alves

Gonçalves

Rutella

et al. 2021

Cancers

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“…It is well known that drugs can have multiple molecular targets inside our body and that the specific molecular interaction of many drugs is often unknown and can be quite variable from one individual to another. Genome and proteome-wide information associated to the drugs activity in human cells is essential to generate better maps of the molecular targets of each drug (De Las Rivas et al 2018 ). Construction of this type of drug-target interaction mapping has been successful in the field of cancer genomics thanks to the possibility of testing the activity of hundreds of cancer drugs in multiple human cancer cell lines (Arroyo et al 2020 ).…”

Section: Bioinformatic Investigation In Drug Resistance and In Emtmentioning

confidence: 99%

Cancer drug resistance induced by EMT: novel therapeutic strategies

et al. 2021

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Over the last decade, important clinical benefits have been achieved in cancer patients by using drug-targeting strategies. Nevertheless, drug resistance is still a major problem in most cancer therapies. Epithelial-mesenchymal plasticity (EMP) and tumour microenvironment have been described as limiting factors for effective treatment in many cancer types. Moreover, epithelial-to-mesenchymal transition (EMT) has also been associated with therapy resistance in many different preclinical models, although limited evidence has been obtained from clinical studies and clinical samples. In this review, we particularly deepen into the mechanisms of which intermediate epithelial/mesenchymal (E/M) states and its interconnection to microenvironment influence therapy resistance. We also describe how the use of bioinformatics and pharmacogenomics will help to figure out the biological impact of the EMT on drug resistance and to develop novel pharmacological approaches in the future.

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“…The size of a disease related PIN of some certain disease might be quite small (containing several or tens of proteins) [ 40 ], whereas the network for some general disease (such as cancer) or all the human diseases can be quite large. For example, De Las Rivas et al [ 41 ] constructed a cancer related PIN which included 582 cancer proteins and 4968 interactions. Carson et al [ 42 ] constructed a PIN related to all the known human diseases which is composed of the products of 3104 genes, that is, 32% of HPRD proteins with a disease association.…”

Section: Identification Of Durg Targets Using Disease-related Pinsmentioning

confidence: 99%

Analyzing of Molecular Networks for Human Diseases and Drug Discovery

Hao

Wang

Zhao

et al. 2018

CTMC

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Molecular networks represent the interactions and relations of genes/proteins, and also encode molecular mechanisms of biological processes, development and diseases. Among the molecular networks, protein-protein Interaction Networks (PINs) have become effective platforms for uncovering the molecular mechanisms of diseases and drug discovery. PINs have been constructed for various organisms and utilized to solve many biological problems. In human, most proteins present their complex functions by interactions with other proteins, and the sum of these interactions represents the human protein interactome. Especially in the research on human disease and drugs, as an emerging tool, the PIN provides a platform to systematically explore the molecular complexities of specific diseases and the references for drug design. In this review, we summarized the commonly used approaches to aid disease research and drug discovery with PINs, including the network topological analysis, identification of novel pathways, drug targets and sub-network biomarkers for diseases. With the development of bioinformatic techniques and biological networks, PINs will play an increasingly important role in human disease research and drug discovery.

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Human Interactomics: Comparative Analysis of Different Protein Interaction Resources and Construction of a Cancer Protein–Drug Bipartite Network

Cited by 11 publications

References 33 publications

Resistance to Tyrosine Kinase Inhibitors in Chronic Myeloid Leukemia—From Molecular Mechanisms to Clinical Relevance

Resistance to Tyrosine Kinase Inhibitors in Chronic Myeloid Leukemia—From Molecular Mechanisms to Clinical Relevance

Cancer drug resistance induced by EMT: novel therapeutic strategies

Analyzing of Molecular Networks for Human Diseases and Drug Discovery

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