The applications of metabolomics in the molecular diagnostics of cancer.

Introduction: Metabolomics, the study of metabolites, is a promising research field for cancers. The metabolic pathway in a tumor cell is different from a normal tissue cell. There are two approaches to study the metabolism, targeted and untargeted. The general approach is that metabolomic data are interpreted by bioinformatics tools correlating with metabolomic databases to obtain significant findings. With the use of specific analysis tools, such as nuclear magnetic resonance (NMR) and mass spectrometer (MS) combined with chromatography, metabolic profile or metabolic fingerprint of various biological specimens could be obtained. The applications of metabolomics are used to discover potential cancer biomarkers and monitor the metastatic state, therapeutic and drug response for better patient management. Areas covered: In this review, the author introduce metabolomics and discuss the use of metabolomics approaches in different cancers, including the study of colorectal cancer, prostate cancer, liver cancer, pancreatic cancer and breast cancer using NMR and MS. Expert opinion: Knowledge on the molecular basis of cancer metabolism and its potential clinical applications has been improving recently. However, there are still many challenges for the technological development and integration of metabolomics with other omics spaces such as genomics. In the near future, it is expected that metabolomics will play an important role in cancer molecular diagnostics.

The applications of big data in molecular diagnostics.

Introduction: Big Data technologies instilled an informational perspective to our understanding of the world. However, fundamental issues such as the management and storage of data can create privacy concerns. Heterogeneous types of data pose challenges in reproducibility and standardization. It is now an opportunity for us to help the health-care professionals, educators, and policy-makers understand the impact of Big Data, and steer the development roadmap to positively impact the molecular diagnostic industry. Area covered: In this review, we discuss the latest trends in applying Big Data to several key areas of molecular diagnostics: metagenomics, Mendelian disease screening, personalized medicine, and metabolomics. The limitations of utilizing bioinformatics and Big Data analytic tools are also summarized. We further propose an action plan on how to prepare a new generation of health-care professionals to step into the age of Big Data through a tailor-made bioinformatics training program. Expert opinion: In order to cope with the development of these powerful technologies, issues of ethics, regulations, and data format standardization are urgently needed. Besides, a long-term planning to train medical scientists, pathologists, and specialists on bioinformatics is necessary. It is an appropriate time to review all these issues before implementing these tests for patients' diagnosis, prognosis and treatment efficacy.

Current and future molecular diagnostics of gastric cancer.

Introduction: Gastric cancer (GC) is the fifth most common cancer and confers the second-highest mortality among other cancers. Improving the survival rates of GC patients requires prompt and accurate diagnosis and effective treatment which is often preceded by the poorly understood pathogenic mechanisms. Area covered: This literature review aims to summarize current understanding of genetic and molecular alterations that promote carcinogenesis including (1) activation of oncogenes, (2) overexpression of growth factors, receptors and matrix metalloproteinases, (3) inactivation of tumor suppressor genes, DNA repair genes, and cell adhesion molecules and (4) alterations of cell-cycle regulators that regulate biological characteristics of cancer cells. Moreover, the significance of molecular biomarkers such as micro-RNAs (miRNAs) and long non-coding RNAs (lncRNAs) and advanced molecular techniques including droplet digital polymerase chain reaction (ddPCR), quantitative PCR (qPCR) and next-generation sequencing (NGS) are also discussed. Expert opinion: A GC-specific panel of biomarkers based on the NGS or ddPCR has the potential for diagnosis, prognosis, and monitoring treatment response in GC patients. Despite the requirements for validation in larger population in clinical studies, race-specific differences in the gene panel have also to be examined by performing the clinical trials in subjects with different races.