AMPK promotes the survival of colorectal cancer stem cells.

BACKGROUND: Colorectal cancer (CRC) is the third most commonly diagnosed cancer in males and the second in females worldwide in 2012. In the past 20 years, strong evidence suggests that cancer stem cells are the main culprit of cancer metastasis, chemotherapy resistance, and relapse. METHODS: To further understand the unique biological properties of cancer stem cells and uncover novel molecular targets to eradicate them, we first established a panel of patient-derived xenograft (PDX) tumor models using tumors surgically removed from human colorectal cancer patients. We then isolated CRC cancer stem cells based on their ALDH activity using fluorescent-activated cell sorting (FACS) and characterized their metabolic properties. RESULTS: Interestingly, we found that the CRC cancer stem cells (ie, CRC cells with higher ALDH activity, or ALDH+) express higher level of antioxidant genes and have lower level of reactive oxygen species (ROS) than non-CRC cancer stem cells (ie, CRC cells with lower ALDH activity, or ALDH-). The CRC cancer stem cells also possess more mitochondria mass and show higher mitochondrial activity. More intriguingly, we observed higher AMP-activated protein kinase (AMPK) activities in these CRC cancer stem cells. Inhibition of the AMPK activity using 2 AMPK inhibitors, Compound C and Iodotubercidin, preferentially induces cell death in CRC cancer stem cells. CONCLUSION: We propose that AMPK inhibitors may help to eradicate the CRC cancer stem cells and prevent the relapse of CRCs.

Analysis of pathway activity in primary tumors and NCI60 cell lines using gene expression profiling data.

To determine cancer pathway activities in nine types of primary tumors and NCI60 cell lines, we applied an in silica approach by examining gene signatures reflective of consequent pathway activation using gene expression data. Supervised learning approaches predicted that the Ras pathway is active in approximately 70% of lung adenocarcinomas but inactive in most squamous cell carcinomas, pulmonary carcinoids, and small cell lung carcinomas. In contrast, the TGF-beta, TNF-alpha, Src, Myc, E2F3, and beta-catenin pathways are inactive in lung adenocarcinomas. We predicted an active Ras, Myc, Src, and/or E2F3 pathway in significant percentages of breast cancer, colorectal carcinoma, and gliomas. Our results also suggest that Ras may be the most prevailing oncogenic pathway. Additionally, many NCI60 cell lines exhibited a gene signature indicative of an active Ras, Myc, and/or Src, but not E2F3, beta-catenin, TNF-alpha, or TGF-beta pathway. To our knowledge, this is the first comprehensive survey of cancer pathway activities in nine major tumor types and the most widely used NCI60 cell lines. The "gene expression pathway signatures" we have defined could facilitate the understanding of molecular mechanisms in cancer development and provide guidance to the selection of appropriate cell lines for cancer research and pharmaceutical compound screening.

Improve survival prediction using principal components of gene expression data.

The purpose of many microarray studies is to find the association between gene expression and sample characteristics such as treatment type or sample phenotype. There has been a surge of efforts developing different methods for delineating the association. Aside from the high dimensionality of microarray data, one well recognized challenge is the fact that genes could be complicatedly inter-related, thus making many statistical methods inappropriate to use directly on the expression data. Multivariate methods such as principal component analysis (PCA) and clustering are often used as a part of the effort to capture the gene correlation, and the derived components or clusters are used to describe the association between gene expression and sample phenotype. We propose a method for patient population dichotomization using maximally selected test statistics in combination with the PCA method, which shows favorable results. The proposed method is compared with a currently well-recognized method.