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1.
BMC Cancer ; 16: 200, 2016 Mar 09.
Artigo em Inglês | MEDLINE | ID: mdl-26955870

RESUMO

BACKGROUND: "Biomarker-driven targeted therapy," the practice of tailoring patients' treatment to the expression/activity levels of disease-specific genes/proteins, remains challenging. For example, while the anti-ERBB2 monoclonal antibody, trastuzumab, was first developed using well-characterized, diverse in vitro breast cancer models (and is now a standard adjuvant therapy for ERBB2-positive breast cancer patients), trastuzumab approval for ERBB2-positive gastric cancer was largely based on preclinical studies of a single cell line, NCI-N87. Ensuing clinical trials revealed only modest patient efficacy, and many ERBB2-positive gastric cancer (GC) patients failed to respond at all (i.e., were inherently recalcitrant), or succumbed to acquired resistance. METHOD: To assess mechanisms underlying GC insensitivity to ERBB2 therapies, we established a diverse panel of GC cells, differing in ERBB2 expression levels, for comprehensive in vitro and in vivo characterization. For higher throughput assays of ERBB2 DNA and protein levels, we compared the concordance of various laboratory quantification methods, including those of in vitro and in vivo genetic anomalies (FISH and SISH) and xenograft protein expression (Western blot vs. IHC), of both cell and xenograft (tissue-sectioned) microarrays. RESULTS: The biomarker assessment methods strongly agreed, as did correlation between RNA and protein expression. However, although ERBB2 genomic anomalies showed good in vitro vs. in vivo correlation, we observed striking differences in protein expression between cultured cells and mouse xenografts (even within the same GC cell type). Via our unique pathway analysis, we delineated a signaling network, in addition to specific pathways/biological processes, emanating from the ERBB2 signaling cascade, as a potential useful target of clinical treatment. Integrated analysis of public data from gastric tumors revealed frequent (10 - 20 %) amplification of the genes NFKBIE, PTK2, and PIK3CA, each of which resides in an ERBB2-derived subpathway network. CONCLUSION: Our comprehensive bioinformatics analyses of highly heterogeneous cancer cells, combined with tumor "omics" profiles, can optimally characterize the expression patterns and activity of specific tumor biomarkers. Subsequent in vitro and in vivo validation, of specific disease biomarkers (using multiple methodologies), can improve prediction of patient stratification according to drug response or nonresponse.


Assuntos
Neoplasias Gástricas/etiologia , Neoplasias Gástricas/metabolismo , Animais , Antineoplásicos/farmacologia , Biomarcadores , Linhagem Celular Tumoral , Modelos Animais de Doenças , Avaliação Pré-Clínica de Medicamentos , Feminino , Amplificação de Genes , Perfilação da Expressão Gênica , Regulação Neoplásica da Expressão Gênica , Redes Reguladoras de Genes , Humanos , Camundongos , Terapia de Alvo Molecular , Estadiamento de Neoplasias , Receptor ErbB-2/genética , Receptor ErbB-2/metabolismo , Transdução de Sinais , Neoplasias Gástricas/tratamento farmacológico , Neoplasias Gástricas/patologia , Ensaios Antitumorais Modelo de Xenoenxerto
2.
Oncotarget ; 8(41): 69808-69822, 2017 Sep 19.
Artigo em Inglês | MEDLINE | ID: mdl-29050243

RESUMO

The recent creation of enormous, cancer-related "Big Data" public depositories represents a powerful means for understanding tumorigenesis. However, a consistently accurate system for clinically evaluating single/multi-biomarkers remains lacking, and it has been asserted that oft-failed clinical advancement of biomarkers occurs within the very early stages of biomarker assessment. To address these challenges, we developed a clinically testable, web-based tool, CANcer-specific single/multi-biomarker Evaluation System (CANES), to evaluate biomarker effectiveness, across 2,134 whole transcriptome datasets, from 94,147 biological samples (from 18 tumor types). For user-provided single/multi-biomarkers, CANES evaluates the performance of single/multi-biomarker candidates, based on four classification methods, support vector machine, random forest, neural networks, and classification and regression trees. In addition, CANES offers several advantages over earlier analysis tools, including: 1) survival analysis; 2) evaluation of mature miRNAs as markers for user-defined diagnostic or prognostic purposes; and 3) provision of a "pan-cancer" summary view, based on each single marker. We believe that such "landscape" evaluation of single/multi-biomarkers, for diagnostic therapeutic/prognostic decision-making, will be highly valuable for the discovery and "repurposing" of existing biomarkers (and their specific targeted therapies), leading to improved patient therapeutic stratification, a key component of targeted therapy success for the avoidance of therapy resistance.

3.
Oncotarget ; 7(49): 81435-81451, 2016 Dec 06.
Artigo em Inglês | MEDLINE | ID: mdl-27806312

RESUMO

Gastric cancer (GC) is a highly heterogeneous disease, in dire need of specific, biomarker-driven cancer therapies. While the accumulation of cancer "Big Data" has propelled the search for novel molecular targets for GC, its specific subpathway and cellular functions vary from patient to patient. In particular, mutations in the small GTPase gene RHOA have been identified in recent genome-wide sequencing of GC tumors. Moreover, protein overexpression of RHOA was reported in Chinese populations, while RHOA mutations were found in Caucasian GC tumors. To develop evidence-based precision medicine for heterogeneous cancers, we established a systematic approach to integrate transcriptomic and genomic data. Predicted signaling subpathways were then laboratory-validated both in vitro and in vivo, resulting in the identification of new candidate therapeutic targets. Here, we show: i) differences in RHOA expression patterns, and its pathway activity, between Asian and Caucasian GC tumors; ii) in vitro and in vivo perturbed RHOA expression inhibits GC cell growth in high RHOA-expressing cell lines; iii) inverse correlation between RHOA and RHOB expression; and iv) an innovative small molecule design strategy for RHOA inhibitors. In summary, RHOA, and its oncogenic signaling pathway, represent a strong biomarker-driven therapeutic target for Asian GC. This comprehensive strategy represents a promising approach for the development of "hit" compounds.


Assuntos
Biomarcadores Tumorais/genética , Neoplasias Gástricas/genética , Proteína rhoA de Ligação ao GTP/genética , Animais , Antineoplásicos/farmacologia , Povo Asiático/genética , Biomarcadores Tumorais/metabolismo , Linhagem Celular Tumoral , Proliferação de Células , Biologia Computacional , Bases de Dados Genéticas , Inibidores Enzimáticos/farmacologia , Regulação Enzimológica da Expressão Gênica , Regulação Neoplásica da Expressão Gênica , Estudos de Associação Genética , Humanos , Camundongos SCID , Terapia de Alvo Molecular , Interferência de RNA , República da Coreia , Transdução de Sinais , Neoplasias Gástricas/tratamento farmacológico , Neoplasias Gástricas/etnologia , Neoplasias Gástricas/patologia , Fatores de Tempo , Transcriptoma , Transfecção , Carga Tumoral , Regulação para Cima , População Branca/genética , Ensaios Antitumorais Modelo de Xenoenxerto , Proteína rhoA de Ligação ao GTP/antagonistas & inibidores , Proteína rhoA de Ligação ao GTP/metabolismo , Proteína rhoB de Ligação ao GTP/genética , Proteína rhoB de Ligação ao GTP/metabolismo
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