暂无摘要。

Over the past decade, the incidence of colorectal cancer has increased in individuals under the age of 50 years. Meanwhile, the incidence has gradually decreased in the older population. As described herein, we reviewed the available literature to summarize the current landscape of early-onset colorectal cancer, including risk factors, clinicopathological presentation, genetic makeup of patients, and management. Currently, early-onset colorectal cancer is treated similarly as late-onset colorectal cancer, yet the available literature shows that early-onset colorectal cancer is more aggressive and different, and this remains a significant unmet need. A detailed understanding of early-onset colorectal cancer is needed to identify risk factors for the increased incidence and tailor treatments accordingly.

To investigate the difference of microbial communities among Diannan small-ear (DNSE), Dahe black (DHB) and Yorkshire (YS) pigs, we compared the microbial taxonomic and functional composition using a metagenomic approach. A total of 1,002,362 non-redundant microbial genes were identified, DHB and YS pigs had more similar genetic makeup compared with DNSE pigs. Bacteroidetes, Firmicutes and Spirochetes were the three most abundant phyla for all pig breeds, and DNSE pigs had a higher abundance of Prevotella genus than DHB and YS pigs. The functional profiles varied among the three pig breeds, DNSE pigs had more active carbohydrate metabolism and more abundant antibiotic resistance genes than the other two pig breeds. Moreover, we found that peptide and macrolide resistances genes in DNSE pigs were more abundant than that in DHB pigs (p < 0.05). This study will help to provide a theoretical basis for the development of native pig breeds in Yunnan Province, China.

Recent advances in Pharmacogenomics have made it possible to understand the reasons behind the different response of a drug. Discovery of genetic variants and its association with the varying response of drug provide the basis for recommending a drug and its dose to an individual patient. Genetic makeup-based prescription, design, and implementation of therapy not only improve the outcome of treatments but also reduce the risk of toxicity and other adverse effects. A better understanding of individual variations and their effect on drug response, metabolism excretion, and toxicity will replace the trial-and-error approach of treatment. Evidence of the clinical utility of pharmacogenetics testing is only available for a few medications, and FDA labels only require pharmacogenetics testing for a small number of drugs. Although there is a great promise, there are not many examples where Pharmacogenomics impacts clinical utility. Some genetic variants related to different diseases have been reported, and many have not been studied yet. The information related to the outcome of treatment with a particular drug and a genetic variant can be used to release a warning/label for the use of that drug. There are many limitations in the way of implementing the goal of personalized medicine. Future advances in the field of genomics, diagnosis approaches, data analysis, clinical decision-making, and sustainable business model for personalization of therapy can speed up the individualization of therapy based on genetic makeup.