Finding Colon Cancer- and Colorectal Cancer-Related Microbes Based on Microbe-Disease Association Prediction.

Microbes are closely associated with the formation and development of diseases. The identification of the potential associations between microbes and diseases can boost the understanding of various complex diseases. Wet experiments applied to microbe-disease association (MDA) identification are costly and time-consuming. In this manuscript, we developed a novel computational model, NLLMDA, to find unobserved MDAs, especially for colon cancer and colorectal carcinoma. NLLMDA integrated negative MDA selection, linear neighborhood similarity, label propagation, information integration, and known biological data. The Gaussian association profile (GAP) similarity of microbes and GAPs similarity and symptom similarity of diseases were firstly computed. Secondly, linear neighborhood method was then applied to the above computed similarity matrices to obtain more stable performance. Thirdly, negative MDA samples were selected, and the label propagation algorithm was used to score for microbe-disease pairs. The final association probabilities can be computed based on the information integration method. NLLMDA was compared with the other five classical MDA methods and obtained the highest area under the curve (AUC) value of 0.9031 and 0.9335 on cross-validations of diseases and microbe-disease pairs. The results suggest that NLLMDA was an effective prediction method. More importantly, we found that Acidobacteriaceae may have a close link with colon cancer and Tannerella may densely associate with colorectal carcinoma.

Downregulation of miR-497 promotes tumor growth and angiogenesis by targeting HDGF in non-small cell lung cancer.

MicroRNAs (miRNAs) play important roles in the development of various cancers. MiRNA-497 functions as a tumor-suppressor that is downregulated in several malignancies; however, its role in non-small cell lung cancer (NSCLC) has not been examined in detail. Here, we showed that miR-497 is downregulated in NSCLC tumors and cell lines and its ectopic expression significantly inhibits cell proliferation and colony formation. Integrated analysis identified HDGF as a downstream target of miR-497, and the downregulation of HDGF by miR-497 overexpression confirmed their association. Rescue experiments showed that the inhibitory effect of miR-497 on cell proliferation and colony formation is predominantly mediated by the modulation of HDGF levels. Furthermore, tumor samples from NSCLC patients showed an inverse relationship between miR-497 and HDGF levels, and ectopic expression of miR-497 significantly inhibited tumor growth and angiogenesis in a SCID mouse xenograft model. Our results suggest that miR-497 may serve as a biomarker in NSCLC, and the modulation of its activity may represent a novel therapeutic strategy for the treatment of NSCLC patients.