Literature DB >> 18370315

Reverse phase protein microarrays for theranostics and patient-tailored therapy.

Virginia Espina1, Julia Wulfkuhle, Valerie S Calvert, Lance A Liotta, Emanuel F Petricoin.   

Abstract

Although the genome provides information about the somatic genetic changes existing in the tissue and underpins pathology, it is the proteins that do the work of the cell and are functionally responsible for almost all disease processes. Moreover, many diseases such as cancer are a manifestation of deranged cellular protein molecular networks and cell-signaling pathways. These pathways contain a large and growing collection of drug targets, governing cellular survival, proliferation, invasion, and cell death. Thus, the promise of proteomics resides in the study of molecules that extend beyond correlation to causality. The clinical utility of reverse phase protein microarrays, a new technology invented in our laboratory, lies in its ability to generate a functional map of known cell-signaling networks or pathways for an individual patient obtained directly from a biopsy specimen. This patient-specific circuit diagram provides key information that identifies critical nodes or pathways that may serve as drug targets for individualized or combinatorial therapy through the quantification of phosphorylation states of proteins. Using this technique, the entire cellular proteome is immobilized on a substratum with subsequent immunodetection of the phosphorylated, or activated, state of cell-signaling proteins. The results of which pathways are "in use" can then be correlated with biological and clinical information and serve as both a diagnostic and a therapeutic guide: thus providing a "theranostic" endpoint.

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Year:  2008        PMID: 18370315     DOI: 10.1007/978-1-60327-047-2_8

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


  10 in total

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Journal:  Antiviral Res       Date:  2017-04-23       Impact factor: 5.970

Review 2.  Innovations, challenges and future prospects of oncoproteomics.

Authors:  Kewal K Jain
Journal:  Mol Oncol       Date:  2008-05-28       Impact factor: 6.603

3.  Feasibility and safety of sequential research-related tumor core biopsies in clinical trials.

Authors:  Jung-min Lee; John L Hays; Anne M Noonan; Jennifer Squires; Lori Minasian; Christina Annunziata; Bradford J Wood; Minshu Yu; Katherine R Calvo; Nicole Houston; Nilofer Azad; Elise C Kohn
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4.  Expression of TOMM34 and Its Clinicopathological Correlations in Urothelial Carcinoma of the Bladder.

Authors:  Mohamed A H Ahmed; Mohamed Hassan Ali; Hashem Hafez Abbas; Gamal Ali Elatrash; Abd AlRahman Mohammad Foda
Journal:  Pathol Oncol Res       Date:  2018-10-31       Impact factor: 3.201

5.  Proteomic Analysis of Cardioembolic and Large Artery Atherosclerotic Clots Using Reverse Phase Protein Array Technology Reveals Key Cellular Interactions Within Clot Microenvironments.

Authors:  Mehdi Abbasi; Sean Fitzgerald; Jennifer Ayers-Ringler; Virginia Espina; Claudius Mueller; Sally Rucker; Ramanathan Kadirvel; David Kallmes; Waleed Brinjikji
Journal:  Cureus       Date:  2021-02-22

6.  Spatial normalization of reverse phase protein array data.

Authors:  Poorvi Kaushik; Evan J Molinelli; Martin L Miller; Weiqing Wang; Anil Korkut; Wenbin Liu; Zhenlin Ju; Yiling Lu; Gordon Mills; Chris Sander
Journal:  PLoS One       Date:  2014-12-12       Impact factor: 3.240

7.  A new bioavailable fenretinide formulation with antiproliferative, antimetabolic, and cytotoxic effects on solid tumors.

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Journal:  Cell Death Dis       Date:  2019-07-23       Impact factor: 8.469

Review 8.  Protein microarrays for personalized medicine.

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Journal:  Clin Chem       Date:  2010-01-14       Impact factor: 8.327

9.  TP53/miR-34a-associated signaling targets SERPINE1 expression in human pancreatic cancer.

Authors:  Shaw M Akula; Peter P Ruvolo; James A McCubrey
Journal:  Aging (Albany NY)       Date:  2020-01-27       Impact factor: 5.682

10.  Development of reverse phase protein microarrays for the validation of clusterin, a mid-abundant blood biomarker.

Authors:  Adriana Aguilar-Mahecha; Christiane Cantin; Maureen O'Connor-McCourt; Andre Nantel; Mark Basik
Journal:  Proteome Sci       Date:  2009-04-06       Impact factor: 2.480

  10 in total

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