Abstract
Last thirty years, a rapid progresses of bioinformatics technology and medical applications has been seen globally. Cancer bioinformatics is one of such important multi-omics branches for anticancer drug developments and cancer diagnostic strategies. Same as other biological techniques or systems, bioinformatics techniques and strategies are not omni-potent and decisive now. They have their own limits and shortcomings. This article addresses the whole-picture of bioinformatics in cancer researches and clinical applications. Their advantageous and drawbacks are discussed generally.
Introduction
Cancer is one of the serious human health problems despite rapid progress in cancer research and drug development (claiming the lives of about 7-10 million people annually) in the world [1-2]. Correspondingly, the treatment of cancer is a great therapeutic challenge and an advancing opportunity worldwide [3-4]. Since cancer bioinformatics systems have advantages and shortcomings, medical or technical shortcomings slow down the popularity and updating of cancer bioinformatics in biomedical research and anticancer drug evaluations [5] and general cancer diagnostic techniques in early experimental and clinical studies worldwide [6-17].
Personalized cancer therapy (PCT)
Since cancer is a progressive disease with a lot of different genetic alterations and molecular abnormalities, personalized strategies are emerged in the last 2-3 decades [18-22]. In addition, different types of cancers are caused by different pathogeneses, like genetic abnormalities, such as mutation, translocation, deletion or replication etc. Thus before an appropriate therapy can be initiated, pictures of genetic alterations and molecular abnormalities of individual cancer should be determined.
Technical analysis
Drug sensitivity testing, cancer bioinformatics, pharmacogenetics and individualized antimetastatic therapies are major parts of PCT that are designed to reveal these genetic alteration and molecular abnormality information and select optimal anticancer drugs [19-22]. Among these categories of personalized cancer therapies, cancer bioinformatics and individualized antimetastatic therapies are underestimated, yet of great clinical significance. Because they are not directly linked with drug responses or clinical outcomes now. Many steps are proposed to promote them now [23-25]
Mathematics and Artificial Intelligence
As bioinformatics techniques should be high throughput methods, the causative biomarkers should be determined in drug or therapeutic selections. It includes mathematical or computational systems to assist oncogenic genomic and molecular information mining [26-27]. Good hospital routines and paradigms should be popularized. It needs to be easy to handle, cost-effective, high-throughput, and as effective as possible.
Cancer metastasis contains 80-90% all cancer deaths [28- 29]. In depth studies are welcomed in the areas, including cancer bioinformatics or others.
Future Perspectives
Currently, bioinformatics techniques are diversified [30]. In order to safeguard the quality and cost of hospital routines, standard guidelines should be renewed every 4-5 years. By these bio-sample assays, we can move forward as easy as possible in drug development and clinical drug selection [31- 34].
Conclusion
Cancer bioinformatics research is important for cancer treatment improvement. New era will be coming via bioinformatics technical and therapeutic studies.
