MicroRNAs are important gene regulators that potentially play a profound role in tumorigenesis. Increasing evidence indicates that miR-145 is a tumor suppressor capable of inhibiting breast and colon cancer cell growth both in vitro and in vivo. However, the biological function of miR-145 in non-small cell lung cancer (NSCLC) is largely unknown. In colon cancer cells, c-Myc is a confirmed direct target for miR-145. The aim of this work was to investigate the effect of miR-145 and c-Myc on proliferation of NSCLC cells, using the NSCLC cell lines A549 and H23 as models. We determined the expression level of miR-145 in tumor tissues relative to adjacent non-tumor tissues, and in NSCLC cell lines relative to non-malignant lung cells. Downregulation of miR-145 was seen in tumor tissues and the two NSCLC cell lines by real-time quantitative reverse transcription polymerase chain reaction. MTT and focus formation assays were conducted to measure cell proliferation rates. Cell growth was inhibited and the G1/S transition was blocked by miR-145 in transfection assays of A549 and H23 cells. We further showed that c-Myc was a direct target for miR-145. Introduction of miR-145 dramatically suppressed the c-Myc/eIF4E pathway, which was demonstrated to be crucial for cell proliferation in NSCLC cells. Furthermore, we found that CDK4 was regulated by miR-145 in cell cycle control. Taken together, our study results demonstrate that miR-145 inhibits proliferation of NSCLC cells through c-Myc. Increasing miR-145 expression may provide a novel approach for the treatment of NSCLC.

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A recent study showed that sarcosine may be potentially useful for the diagnosis and prognosis of prostate cancer (PCa). The aim of this study was to validate diagnostic value of sarcosine for PCa, to evaluate urine metabolomic profiles in patients with PCa in comparison of non-cancerous control, and to further explore the other potential metabolic biomarkers for PCa. Isotope dilution gas chromatography/mass spectrometry (ID GC/MS) metabolomic approach was applied to evaluate sarcosine using [methyl-D(3)]-sarcosine as an internal standard. Microwave-assisted derivatization (MAD) together with GC/MS was utilized to obtain the urinary metabolomic information in 20 PCa patients compared with eight patients with benign prostate hypertrophy and 20 healthy men. Acquired metabolomic data were analyzed using a two-sample t test. Diagnostic models for PCa were constructed using principal component analysis and were assessed with receiver-operating characteristic curves. Results showed that the urinary sarcosine level has no statistical difference between the PCa group and the control group. In addition, nine metabolomic markers between the PCa group and the healthy male group were selected, which constructed a diagnostic model with a high area under the curve value of 0.9425. We conclude that although urinary sarcosine value has limited potential in the diagnostic algorithm of PCa, urinary metabolomic panel based on GC/MS assay following MAD may potentially become a diagnostic tool for PCa.

Gastric cancer screening or diagnosis is mainly based on endoscopy and biopsy. The aim of this study was to identify the difference of metabolomic profile between normal and malignant gastric tissue, and to further explore tumor biomarkers. Chemical derivatization together with gas chromatography/mass spectrometry (GC/MS) was utilized to obtain the metabolomic information of the malignant and non-malignant tissues of gastric mucosae in 18 gastric cancer patients. Acquired metabolomic data was analyzed using the Wilcoxon rank sum test to find the tissue metabolic biomarkers for gastric cancer. A diagnostic model for gastric cancer was constructed using principal component analysis (PCA), and was assessed with receiver-operating characteristic (ROC) curves. Results showed that 18 metabolites were detected differently between the malignant tissues and the adjacent non-malignant tissues of gastric mucosa. Five metabolites were also detected differently between the non-invasive tumors and the invasive tumors. The diagnostic model could discriminate tumors from normal mucosae with an area under the curve (AUC) value of 0.9629, and another diagnostic model constructed for clinical staging was assessed with an AUC value of 0.969. We conclude that the metabolomic profile of malignant gastric tissue was different from normal, and that the selected tissue metabolites could probably be applied for clinical diagnosis or staging for gastric cancer.

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