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1.
Gynecol Oncol ; 155(2): 349-358, 2019 11.
Artigo em Inglês | MEDLINE | ID: mdl-31477281

RESUMO

OBJECTIVE: Platinum compounds have been widely used as a primary treatment for many types of cancer. However, resistance is the major cause of therapeutic failure for patients with metastatic or recurrent disease, thus highlighting the need to identify novel factors driving resistance to Platinum compounds. Metadherin (MTDH, also known as AEG-1 and LYRIC), located in a frequently amplified region of chromosome 8, has been consistently associated with resistance to chemotherapeutic agents, though the precise mechanisms remain incompletely defined. METHODS: The mRNA of FANCD2 and FANCI was pulled down by RNA-binding protein immunoprecipitation. Pristimerin-loaded nanoparticles were prepared using the nanoprecipitation method. Immunocompromised mice bearing patient-derived xenograft tumors were treated with pristimerin-loaded nanoparticles, cisplatin and a combination of the two. RESULTS: MTDH, through its recently discovered role as an RNA binding protein, regulates expression of FANCD2 and FANCI, two components of the Fanconi anemia complementation group (FA) that play critical roles in interstrand crosslink damage induced by platinum compounds. Pristimerin, a quinonemethide triterpenoid extract from members of the Celastraceae family used to treat inflammation in traditional Chinese medicine, significantly decreased MTDH, FANCD2 and FANCI levels in cancer cells, thereby restoring sensitivity to platinum-based chemotherapy. Using a patient-derived xenograft model of endometrial cancer, we discovered that treatment with pristimerin in a novel nanoparticle formulation markedly inhibited tumor growth when combined with cisplatin. CONCLUSIONS: MTDH is involved in post-transcriptional regulation of FANCD2 and FANCI. Pristimerin can increase sensitivity to platinum-based agents in tumors with MTDH overexpression by inhibiting the FA pathway.


Assuntos
Antineoplásicos/farmacologia , Proteína do Grupo de Complementação D2 da Anemia de Fanconi/antagonistas & inibidores , Proteínas de Grupos de Complementação da Anemia de Fanconi/antagonistas & inibidores , Proteínas de Membrana/efeitos dos fármacos , Triterpenos/farmacologia , Animais , Cisplatino/farmacologia , Cistadenocarcinoma Seroso/tratamento farmacológico , Regulação para Baixo , Resistencia a Medicamentos Antineoplásicos/efeitos dos fármacos , Feminino , Masculino , Camundongos Knockout , Nanopartículas , Triterpenos Pentacíclicos , Proteínas de Ligação a RNA , Neoplasias Uterinas/tratamento farmacológico
2.
Int J Mol Sci ; 20(5)2019 Mar 07.
Artigo em Inglês | MEDLINE | ID: mdl-30866519

RESUMO

Nearly one-third of patients with high-grade serous ovarian cancer (HGSC) do not respond to initial treatment with platinum-based therapy. Genomic and clinical characterization of these patients may lead to potential alternative therapies. Here, the objective is to classify non-responders into subsets using clinical and molecular features. Using patients from The Cancer Genome Atlas (TCGA) dataset with platinum-resistant or platinum-refractory HGSC, we performed a genome-wide unsupervised cluster analysis that integrated clinical data, gene copy number variations, gene somatic mutations, and DNA promoter methylation. Pathway enrichment analysis was performed for each cluster to identify the targetable processes. Following the unsupervised cluster analysis, three distinct clusters of non-responders emerged. Cluster 1 had overrepresentation of the stage IV disease and suboptimal debulking, under-expression of miRNAs and mRNAs, hypomethylated DNA, "loss of function" TP53 mutations, and the overexpression of genes in the PDGFR pathway. Cluster 2 had low miRNA expression, generalized hypermethylation, MUC17 mutations, and significant activation of the HIF-1 signaling pathway. Cluster 3 had more optimally cytoreduced stage III patients, overexpression of miRNAs, mixed methylation patterns, and "gain of function" TP53 mutations. However, the survival for all clusters was similar. Integration of genomic and clinical data from patients that do not respond to chemotherapy has identified different subgroups or clusters. Pathway analysis further identified the potential alternative therapeutic targets for each cluster.


Assuntos
Biologia Computacional/métodos , Cistadenocarcinoma Seroso/classificação , Metilação de DNA , Dosagem de Genes , Mutação , Neoplasias Ovarianas/classificação , Análise por Conglomerados , Cistadenocarcinoma Seroso/tratamento farmacológico , Cistadenocarcinoma Seroso/genética , Cistadenocarcinoma Seroso/patologia , Bases de Dados Genéticas , Epigênese Genética , Feminino , Regulação Neoplásica da Expressão Gênica , Redes Reguladoras de Genes , Humanos , Pessoa de Meia-Idade , Estadiamento de Neoplasias , Neoplasias Ovarianas/tratamento farmacológico , Neoplasias Ovarianas/genética , Neoplasias Ovarianas/patologia , Platina/uso terapêutico , Aprendizado de Máquina não Supervisionado
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