RESUMO
Trastuzumab is a standard molecular targeted therapy for human epidermal growth factor receptor 2(HER2) -positive breast cancer, which can significantly improve the survival of patients with this molecular subtype of breast cancer. However, the clinical problem of onset or secondary resistance to trastuzumab has limited its efficacy. Therefore, it is very important to explore the mechanism of trastuzumab resistance and formulate countermeasures. Our study described the underlying molecular mechanism of trastuzumab resistance including ERBB2 mutations and nuclear localization, transcriptional and post-translational alterations of ERBB2, over-activation of bypass signaling pathways activation and so on. Then summarize the potential emerging predicting biomarkers and therapeutic strategies for trastuzumab resistance, in order to provide research direction for reversing trastuzumab resistance.
RESUMO
In recent years, emerging databases were designed to lower the barriers for approaching the intricate cancer genomic datasets, thereby, facilitating investigators to analyze and interpret genes, samples and clinical data across different types of cancer. Herein, we describe a practical operation procedure, taking ID1 (Inhibitor of DNA binding proteins 1) as an example, to characterize the expression patterns of biomarker and survival predictors of breast cancer based on pooled clinical datasets derived from online accessible databases, including ONCOMINE, bcGenExMiner v4.0 (Breast cancer gene-expression miner v4.0), GOBO (Gene expression-based Outcome for Breast cancer Online), HPA (The human protein atlas), and Kaplan-Meier plotter. The analysis began with querying the expression pattern of the gene of interest (e.g., ID1) in cancerous samples vs. normal samples. Then, the correlation analysis between ID1 and clinicopathological characteristics in breast cancer was performed. Next, the expression profiles of ID1 was stratified according to different subgroups. Finally, the association between ID1 expression and survival outcome was analyzed. The operation procedure simplifies the concept to integrate multidimensional data types at the gene level from different databases and test hypotheses regarding recurrence and genomic context of gene alteration events in breast cancer. This method can improve the credibility and representativeness of the conclusions, thereby, present informative perspective on a gene of interest.
Assuntos
Biomarcadores Tumorais/metabolismo , Neoplasias da Mama/metabolismo , Mineração de Dados , Bases de Dados Factuais , Biomarcadores Tumorais/genética , Neoplasias da Mama/genética , Neoplasias da Mama/patologia , Feminino , Regulação Neoplásica da Expressão Gênica , Humanos , Metástase Linfática , Probabilidade , Prognóstico , RNA Mensageiro/genética , RNA Mensageiro/metabolismo , Análise de SobrevidaRESUMO
Catalyst investigation is a typical "trial and error" process. In order to discover a good catalyst, people usually test a huge number of potential catalyst candidates. High-throughput experimentation (HTE) is an efficient methodology for catalyst discovery and optimization. HTE is capable of synthesizing and testing hundreds of catalysts in a short period of time. And it is now becoming a widely applied tool in catalyst discovery and catalyst composition optimization. The development of high throughput experimentation in catalysis includes three steps, which are 1) design and synthesis of catalyst libraries, 2) design of the reactor system for catalytic reactions, and 3) product analysis and data reduction in a high throughput manner. Hence, in this mini-review, the recent developments of high throughput experimentation and these three steps are discussed. The review is focused on the research progress over the last few years.