Histopathology image analysis is a gold standard for cancer recognition and diagnosis. Automatic analysis of histopathology images can help pathologists diagnose tumor and cancer subtypes, alleviating the workload of pathologists. There are two basic types of tasks in digital histopathology image analysis: image classification and image segmentation. Typical problems with histopathology images that hamper automatic analysis include complex clinical representations, limited quantities of training images in a dataset, and the extremely large size of singular images (usually up to gigapixels). The property of extremely large size for a single image also makes a histopathology image dataset be considered large-scale, even if the number of images in the dataset is limited. In this paper, we propose leveraging deep convolutional neural network (CNN) activation features to perform classification, segmentation and visualization in large-scale tissue histopathology images. Our framework transfers features extracted from CNNs trained by a large natural image database, ImageNet, to histopathology images. We also explore the characteristics of CNN features by visualizing the response of individual neuron components in the last hidden layer. Some of these characteristics reveal biological insights that have been verified by pathologists. According to our experiments, the framework proposed has shown state-of-the-art performance on a brain tumor dataset from the MICCAI 2014 Brain Tumor Digital Pathology Challenge and a colon cancer histopathology image dataset. The framework proposed is a simple, efficient and effective system for histopathology image automatic analysis. We successfully transfer ImageNet knowledge as deep convolutional activation features to the classification and segmentation of histopathology images with little training data. CNN features are significantly more powerful than expert-designed features.

Understanding of the mechanism of colorectal carcinogenesis has been gaining momentum for some years on account of its high incidence and impact on the lives of individuals affected. Different genetic abnormalities have been found in colorectal cancers from different sites. For example, proximal colon cancer is usually related to the nucleotide instability pathway, as microsatellite instability (MSI). However, distal colon cancer is usually associated with specific chromosomal instability (CIN). The development of cancer at the rectum, though similar to that at the colon, displays its own unique features. These differences might be partially attributed to different embryological development and physiological circumstances. Environmental factors such as diet and alcohol intake also differ in their role in the development of tumors in the three segments, proximal colon, distal colon, and rectum. “Proximal shift” of colon cancer has been known for some time, and survival rates of colorectal cancer are higher when rectal cancers are excluded, both of which emphasize the three different segments of colorectal cancer and their different properties. Meanwhile, colonic and rectal cancers are distinctive therapeutic entities. The concept of three entities of colorectal cancer may be important in designing clinical trails or therapeutic strategies. However, the dispute about the inconsistency of data concerning the site-specific mechanism of colorectal carcinoma does exist, and more evidence about molecular events of carcinogenesis and targeted therapy needs to be collected to definitely confirm the conception.

Background: The pathogenesis of obesity is reportedly related to variations in the fat mass and an obesity-associated gene (FTO); however, as the number of reports increases, particularly with respect to varying ethnicities, there is a need to determine more precisely the effect sizes in each ethnic group. In addition, some reports have claimed ethnic-specific associations with alternative SNPs, and to that end there has been a degree of confusion. Methods: We searched PubMed, MEDLINE, Web of Science, EMBASE, and BIOSIS Preview to identify studies investigating the associations between the five polymorphisms and obesity risk. Individual study odds ratios (OR) and their 95% confidence intervals (CI) were estimated using per-allele comparison. Summary ORs were estimated using a random effects model. Results: We identified 59 eligible case-control studies in 27 articles, investigating 41,734 obesity cases and 69,837 healthy controls. Significant associations were detected between obesity risk and the five polymorphisms: rs9939609 (OR: 1.31, 95% CI: 1.26 to 1.36), rs1421085 (OR: 1.43, 95% CI: 1.33 to 1.53), rs8050136 (OR: 1.25, 95% CI: 1.13 to 1.38), rs17817449 (OR: 1.54, 95% CI: 1.41 to 1.68), and rs1121980 (OR: 1.34, 95% CI: 1.10 to 1.62). Begg's and Egger's tests provided no evidence of publication bias for the polymorphisms except rs1121980. There is evidence of higher heterogeneity, with I ² test values ranging from 38.1% to 84.5%. Conclusions: This meta-analysis suggests that FTO may represent a low-penetrance susceptible gene for obesity risk. Individual studies with large sample size are needed to further evaluate the associations between the polymorphisms and obesity risk in various ethnic populations.

Apoptosis has a vital role in maintaining tissue homeostasis, and dysregulation of the apoptotic pathway is now widely recognized as a key step in tumourigenesis. Increasingly, evidence has demonstrated that microRNA (miRNA) can exert various biological functions in tumours by targeting oncogenes or tumour suppressors. Nevertheless, the role of miRNA in apoptosis remains unclear. Here we show that ectopical expression of miR-148a can induce apoptosis in colorectal cancer cells. In addition, MYB can inhibit miR-148a by directly acting on the transcription factor binding site in miR-148a gene and miR-148a can posttranscriptionally silence Bcl-2. Subsequently, the intrinsic apoptosis pathway is activated by releasing cytochrome c, cleaving caspase 9, caspase 3 and PARP, which eventually induce cancer-cell apoptosis. These findings are part of a hitherto undocumented apoptotic regulatory pathway in which a pleiotropic transcription factor controls the expression of a miRNA and the miRNA inhibits the target, leading to activation of an intrinsic mitochondrial pathway and tumour apoptosis.