Metastasis is the major cause of cancer mortality. We aimed to find a metastasis-prone signature for early stage mismatch-repair proficient sporadic colorectal cancer (CRC) patients for better prognosis and informed use of adjuvant chemotherapy. The genome-wide expression profiles of 82 age-, ethnicity- and tissue-matched patients and healthy controls were analyzed using the Affymetrix U133 Plus 2 array. Metastasis-negative patients have 5 years or more of follow-up. A 10 x 10 two-level nested cross-validation design was used with several families of classification models to identify the optimal predictor for metastasis. The best classification model yielded a 54 gene-set (74 probe sets) with an estimated prediction accuracy of 71%. The specificity, sensitivity, negative and positive predictive values of the signature are 0.88, 0.58, 0.84 and 0.65, respectively, indicating that the gene-set can improve prognosis for early stage sporadic CRC patients. These 54 genes, including node molecules YWHAB, MAP3K5, LMNA, APP, GNAQ, F3, NFATC2, and TGM2, integrate multiple bio-functions in various compartments into an intricate molecular network, suggesting that cell-wide perturbations are involved in metastasis transformation. Further, querying the ;Connectivity Map' with a subset (70%) of these genes shows that Gly-His-Lys and securinine could reverse the differential expressions of these genes significantly, suggesting that they have combinatorial therapeutic effect on the metastasis-prone patients. These two perturbagens promote wound-healing, extracellular matrix remodeling and macrophage activation thus highlighting the importance of these pathways in metastasis suppression for early-stage CRC.

Microarray analysis of transcript levels in fetal cerebellum and heart tissues of Down syndrome patients showed a disruption only of chromosome 21 gene expression.

Gastric cancer is the most common cancer in Asia and most developing countries. Despite the use of multimodality therapeutics, it remains the second leading cause of cancer death in the world. To identify the molecular underpinnings of gastric cancer in the Asian population, we applied an RNA-sequencing approach to gastric tumor and noncancerous specimens, generating 680 million informative short reads to quantitatively characterize the entire transcriptome of gastric cancer (including mRNAs and microRNAs). A multi-layer analysis was then developed to identify multiple types of transcriptional aberrations associated with different stages of gastric cancer, including differentially expressed mRNAs, recurrent somatic mutations and key differentially expressed microRNAs. Through this approach, we identified the central metabolic regulator AMPK-α as a potential functional target in Asian gastric cancer. Further, we experimentally demonstrated the translational relevance of this gene as a potential therapeutic target for early-stage gastric cancer in Asian patients. Together, our findings not only provide a valuable information resource for identifying and elucidating the molecular mechanisms of Asian gastric cancer, but also represent a general integrative framework to develop more effective therapeutic targets.