Esophageal cancer is the sixth leading cause of death from cancer and one of the least studied cancers worldwide. The global microRNA expression profile of esophageal cancer has not been reported previously. Here, for the first time, we have investigated expressed microRNAs in cryopreserved esophageal cancer tissues using advanced microRNA microarray techniques. Our microarray analyses identified seven microRNAs that could distinguish malignant esophageal cancer lesions from adjacent normal tissues. Some microRNAs could be correlated with the different clinicopathologic classifications. High expression of hsa-miR-103/107 correlated with poor survival by univariate analysis as well as by multivariate analysis. These results indicate that microRNA expression profiles are important diagnostic and prognostic markers of esophageal cancer, which might be analyzed simply using economical approaches such as reverse transcription-PCR.

Purpose: Recent studies have suggested that microRNA biomarkers could be useful for stratifying lung cancer subtypes, but microRNA signatures varied between different populations. Squamous cell carcinoma (SCC) is one major subtype of lung cancer that urgently needs biomarkers to aid patient management. Here, we undertook the first comprehensive investigation on microRNA in Chinese SCC patients.Experimental Design: MicroRNA expression was measured in cancerous and noncancerous tissue pairs strictly collected from Chinese SCC patients (stages I-III), who had not been treated with chemotherapy or radiotherapy prior to surgery. The molecular targets of proposed microRNA were further examined.Results: We identified a 5-microRNA classifier (hsa-miR-210, hsa-miR-182, hsa-miR-486-5p, hsamiR-30a, and hsa-miR-140-3p) that could distinguish SCC from normal lung tissues. The classifier had an accuracy of 94.1% in a training cohort (34 patients) and 96.2% in a test cohort (26 patients). We also showed that high expression of hsa-miR-31 was associated with poor survival in these 60 SCC patients by Kaplan-Meier analysis (P ¼ 0.007), by univariate Cox analysis (P ¼ 0.011), and by multivariate Cox analysis (P ¼ 0.011). This association was independently validated in a separate cohort of 88 SCC patients (P ¼ 0.008, 0.011, and 0.003 in Kaplan-Meier analysis, univariate Cox analysis, and multivariate Cox analysis, respectively). We then determined that the tumor suppressor DICER1 is a target of hsa-miR-31. Expression of hsa-miR-31 in a human lung cancer cell line repressed DICER1 activity but not PPP2R2A or LATS2.Conclusions: Our results identified a new diagnostic microRNA classifier for SCC among Chinese patients and a new prognostic biomarker, hsa-miR-31. Clin Cancer Res; 17(21); 6802-11. Ó2011 AACR.

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Autophagy defect has been shown to be correlated with malignant phenotype and poor prognosis of human cancers, however, the detailed mechanisms remain obscure. In this study, we investigated the biological changes induced by autophagy inhibition in gastric cancer. We showed that inhibition of autophagy in gastric cancer cells promotes epithelial-mesenchymal transition (EMT) and metastasis, alters metabolic phenotype from mitochondrial oxidative phosphorylation to aerobic glycolysis and converts cell phenotype toward malignant, which maybe further contribute to chemoresistance and poor prognosis of gastric cancer. We also identified that the EMT and metabolism alterations induced by autophagy inhibition were dependent on ROS-NF-κB-HIF-1α pathway. More importantly, scavenging of ROS by the antioxidant N-acetylcysteine (NAC) attenuated activation of NF-κB and HIF-1α in autophagydeficient gastric cancer cells, and autophagy inhibition induced metastasis and glycolysis were also diminished by NAC in vivo. Taken together, our findings suggested that autophagy defect promotes metastasis and glycolysis of gastric cancer, and antioxidants could be used to improve disease outcome for gastric cancer patients with autophagy defect.