Literature DB >> 22081348

Reverse-phase protein microarrays.

Mariaelena Pierobon1, Amy J Vanmeter, Noemi Moroni, Francesca Galdi, Emanuel F Petricoin.   

Abstract

Cancer is the consequence of intra- and extracellular signaling network deregulation that derives from alteration of genetic and proteomic cellular homeostasis. Mapping the individual molecular circuitry of a patient's tumor cells is the starting point for rational personalized therapy.While genes and RNA encode information about cellular status, proteins are considered the engine of the cellular machine, as they are the effective elements that drive cellular functions, such as proliferation, migration, differentiation, and apoptosis. Consequently, investigations of the cellular protein network are considered a fundamental tool to understand cellular functions. In the last decades, increasing interest has been focused on the improvement of new technologies for proteomic analysis. In this context, reverse-phase protein microarrays (RPMAs) have been developed to study and analyze posttranslational modifications that are responsible for principal cell functions and activities. This innovative technology allows the investigation of protein activation as a consequence of protein-protein interaction or biochemical reactions, such as phosphorylation, glycosylation, ubiquitination, protein cleavage, and conformational alterations.Intracellular balance is carefully conserved by constant rearrangements of proteins through the activity of a series of kinases and phosphatases. Therefore, knowledge of the key cellular signaling cascades reveal information regarding the cellular processes driving a tumor's growth (such as cellular survival, proliferation, invasion, and cell death) and response to treatment.Alteration to cellular homeostasis, driven by elaborate intra- and extracellular interactions, has become one of the most studied fields in the era of personalized medicine and targeted therapy. RPMA technology is a valid tool that can be applied to protein analysis of several diseases for the potential to generate protein interaction and activation maps that lead to the identification of critical nodes for individualized or combinatorial target therapy.

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Year:  2012        PMID: 22081348     DOI: 10.1007/978-1-60327-216-2_14

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  16 in total

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2.  Targetable T-type Calcium Channels Drive Glioblastoma.

Authors:  Ying Zhang; Nichola Cruickshanks; Fang Yuan; Baomin Wang; Mary Pahuski; Julia Wulfkuhle; Isela Gallagher; Alexander F Koeppel; Sarah Hatef; Christopher Papanicolas; Jeongwu Lee; Eli E Bar; David Schiff; Stephen D Turner; Emanuel F Petricoin; Lloyd S Gray; Roger Abounader
Journal:  Cancer Res       Date:  2017-05-16       Impact factor: 12.701

3.  Hepatocyte growth factor sensitizes brain tumors to c-MET kinase inhibition.

Authors:  Ying Zhang; Kaitlyn E Farenholtz; Yanzhi Yang; Fadila Guessous; Charles G Dipierro; Valerie S Calvert; Jianghong Deng; David Schiff; Wenjun Xin; Jae K Lee; Benjamin Purow; James Christensen; Emanuel Petricoin; Roger Abounader
Journal:  Clin Cancer Res       Date:  2013-02-05       Impact factor: 12.531

4.  PRAS40 Phosphorylation Correlates with Insulin-Like Growth Factor-1 Receptor-Induced Resistance to Epidermal Growth Factor Receptor Inhibition in Head and Neck Cancer Cells.

Authors:  Michael I Dougherty; Christine E Lehman; Adam Spencer; Rolando E Mendez; Abel P David; Linnea E Taniguchi; Julie Wulfkuhle; Emanuel F Petricoin; Daniel Gioeli; Mark J Jameson
Journal:  Mol Cancer Res       Date:  2020-05-28       Impact factor: 5.852

5.  Integration of Network Biology and Imaging to Study Cancer Phenotypes and Responses.

Authors:  Ye Tian; Sean S Wang; Zhen Zhang; Olga C Rodriguez; Emanuel Petricoin; Ie-Ming Shih; Daniel Chan; Maria Avantaggiati; Guoqiang Yu; Shaozhen Ye; Robert Clarke; Chao Wang; Bai Zhang; Yue Wang; Chris Albanese
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Review 6.  Preclinical magnetic resonance imaging and systems biology in cancer research: current applications and challenges.

Authors:  Chris Albanese; Olga C Rodriguez; John VanMeter; Stanley T Fricke; Brian R Rood; YiChien Lee; Sean S Wang; Subha Madhavan; Yuriy Gusev; Emanuel F Petricoin; Yue Wang
Journal:  Am J Pathol       Date:  2012-12-04       Impact factor: 4.307

Review 7.  Application of molecular technologies for phosphoproteomic analysis of clinical samples.

Authors:  M Pierobon; J Wulfkuhle; L Liotta; E Petricoin
Journal:  Oncogene       Date:  2014-03-10       Impact factor: 9.867

8.  IGF1R and Src inhibition induce synergistic cytotoxicity in HNSCC through inhibition of FAK.

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9.  HSP-90 inhibitor ganetespib is synergistic with doxorubicin in small cell lung cancer.

Authors:  C-H Lai; K-S Park; D-H Lee; A T Alberobello; M Raffeld; M Pierobon; E Pin; E F Petricoin Iii; Y Wang; G Giaccone
Journal:  Oncogene       Date:  2013-10-28       Impact factor: 9.867

Review 10.  Systems biology approaches to develop innovative strategies for lung cancer therapy.

Authors:  K Viktorsson; R Lewensohn; B Zhivotovsky
Journal:  Cell Death Dis       Date:  2014-05-29       Impact factor: 8.469

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