In order to identify biomarkers involved in breast cancer, gene expression profiling was conducted using human breast cancer tissues. Total RNAs were extracted from 150 clinical patient tissues covering three breast cancer subtypes (Luminal A, Luminal B, and Triple negative) as well as normal tissues. The expression profiles of a total of 50,739 genes were established from a training set of 32 samples using the Agilent Sure Print G3 Human Gene Expression Microarray technology. Data were analyzed using Agilent Gene Spring GX 12.6 software. The expression of several genes was validated using real-time RT-qPCR. Data analysis with Agilent GeneSpring GX 12.6 software showed distinct expression patterns between cancer and normal tissue samples. A group of 28 promising genes were identified with ≥ 10-fold changes of expression level and p-values < 0.05. In particular, MMP11 and HPSE2 were closely examined due to the important roles they play in cancer cell growth and migration. Real-time RT-qPCR analyses of both training and testing sets validated the gene expression profiles of MMP11 and HPSE2. Our findings identified these 2 genes as a novel breast cancer biomarker gene set, which may facilitate the diagnosis and treatment in breast cancer clinical therapies.

One of the keys for successfully developing drugs against the broad spectrum of cancer cell types is structural diversity. In the current study, we focused on a family of isosteviol derivatives as potential novel antitumor agents. Isosteviol is a tetracyclic diterpenoid obtained by acid hydrolysis of steviol glycoside extracts isolated from abundant Stevia rebaudiana plants. In this work, we have designed and synthesized a panel of isosteviol triazole conjugates using “click” chemistry methodology. Evaluation of these compounds against a series of cancer cell lines derived from primary and metastatic tumors demonstrated that these conjugates exhibit cytotoxic activities with IC₅₀ in the low μM range. In addition, their anti-proliferative activities are cancer cell type specific. Taken together, our studies underscore the importance of structural diversity in achieving cancer cell type specific drug development.

Breast cancer is the second leading cause of death by cancer in women. To identify biomarkers with potential diagnostic and therapeutic utilities in breast cancer, gene expression profiling from real patient tissues was used to discover significantly deregulated genes out of 50,739 genes of human transcriptome. Total RNAs were extracted, and the gene expression profiles of 32 cancerous and normal tissues were established using Agilent gene expression microarray technology. The results were analyzed with Agilent GeneSpring 12.6 software. Here we provide detailed experimental methods and analysis for the microarray data, which have been deposited into Gene Expression Omnibus (GEO) under GSE57297.

Background: For the last two decades, diterpenoid isosteviol and its derivatives have gained significant attention for novel chemical transformation in the drug discovery field. Results: An efficient way towards the synthesis of structurally diverse isosteviol derivatives was described here employing unsaturated functionalities as attractive templates for further transformation such as epoxidation. These structurally diverse compounds exhibited promising cytotoxic activities on different types of cancer cell lines, leading to drug discovery derived from natural products for the treatment of cancer. Conclusion: In this work, novel isosteviol derivatives with Michael acceptors were synthesized to expand the diversity and complexity of a class of isosteviol-derived triazole conjugates to facilitate the development of potential antitumor agents.

Lung cancer continues to be one the most prevalent and life threatening cancers worldwide. In order to study the gene regulation pattern in lung cancer for new therapeutics discovery, gene expression profiling using human lung cancer tissues was conducted. The gene expression profiles were established using Affymetrix Human Exon 1.0 ST Array with RNA extracts from six clinical patients (five lung cancer samples and one normal control). The raw data were analyzed with Affymetrix Expression Console and Affymetrix Transcriptome Analysis Console 2.0. The regulation of several genes was further validated using real-time reverse transcription quantitative polymerase chain reaction (RT-qPCR). Here we provide detailed experimental methods and analysis for the microarray data, which have been deposited into Gene Expression Omnibus (GEO) under GSE63571.