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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.

To obtain microRNA (miRNA) profile and clarify their biological function in tumorigenic Sca-1(+) CD34(+) cells during carcinogenesis of lung adenocarcinoma. After intranasal infection with recombinant Adeno-Cre viruses (AdV-Cre), lung adenocarcinoma was identified pathologically in Lox-stop-lox Kras (LSL-Kras) G12D mice. Sca-1(+) CD34(+) cells were sorted by flow cytometry and tested for tumor-initiating ability, self-renewal and tumorigenicity. MiRNA profiles were obtained using microarray and further confirmed by real-time RT-PCR (qRT-PCR). MiRNA functions were predicted bioinformatically, and miR-294 function was verified to explore its role in tumor migration and invasion. Lung adenocarcinoma was induced in LSL-Kras G12D mice within 30 days. In vivo, the tumorigenicity of Sca-1(+) CD34(+) cells was 25 times stronger than Sca-1(-) CD34(-) cells. During tumorigenesis of lung adenocarcinoma, the expression of 145 miRNAs in Sca-1(+) CD34(+) cells increased and 72 miRNAs decreased (P < 0.01). Four successively up-regulated miRNAs (miR-15a*, miR-203, miR-294 and miR-295*) and three successively down-regulated ones (miR-19b, miR-483 and miR-615-5p) were identified. Among them, miR-294 could constitutively bind to 3'-UTR of matrix metalloproteinase 3 (MMP3), and down-regulate MMP3 protein expression. MiR-294 also significantly inhibited migration and invasion of Lewis lung cancer cells. MiRNAs are characteristically expressed in tumor-initiating Sca-1(+) CD34(+) cells of lung adenocarcinoma, and may play important roles during the carcinogenesis of lung adenocarcinoma.

Background This study aimed to determine the miRNA profile in breast cancer stem cells (BCSCs) and to explore the functions of characteristic BCSC miRNAs. Methods We isolated ESA+CD44+CD24-/low BCSCs from MCF-7 cells using fluorescence-activated cell sorting (FACS). A human breast cancer xenograft assay was performed to validate the stem cell properties of the isolated cells, and microarray analysis was performed to screen for BCSC-related miRNAs. These BCSC-related miRNAs were selected for bioinformatic analysis and target prediction using online software programs. Results The ESA+CD44+CD24-/low cells had up to 100- to 1000-fold greater tumor-initiating capability than the MCF-7 cells. Tumors initiated from the ESA+CD44+CD24-/low cells were included of luminal epithelial and myoepithelial cells, indicating stem cell properties. We also obtained miRNA profiles of ESA+CD44+CD24-/low BCSCs. Most of the possible targets of potential tumorigenesis-related miRNAs were oncogenes, anti-oncogenes or regulatory genes. Conclusions We identified a subset of miRNAs that were differentially expressed in BCSCs, providing a starting point to explore the functions of these miRNAs. Evaluating characteristic BCSC miRNAs represents a new method for studying breast cancer-initiating cells and developing therapeutic strategies aimed at eradicating the tumorigenic subpopulation of cells in breast cancer.