Cancer represents a heterogeneous group of diseases. It is characterized by uncontrolled cell growth and a collapse of all multicellular co-operations (Zhang, et al., 2016; Zhang and Sun, 2015; Zhong, et al., 2016). Cancer promotes tumor development and metastasis (Ahmed, et al., 2013; Zhu, et al., 2016). Tumors are characterized by six essential alterations in cell physiology. These are self-sufficiency in growth signals, continued angiogenesis, insensitivity to growth inhibition signals, dodging of apoptosis, boundless replicative potential, and tissue invasion and metastasis (Zhou, et al., 2016; Zhu, et al., 2016). These are common in most tumors and the latter two are the most lethal trademarks of malignant tumors (Zhong, et al., 2016).
…show more content…
Liver cancer is the foremost cause of cancer deaths in Asia and Africa. Liver cancer is a malignancy with exceptionally low prospects of the five-year survival rate of less than 9% (Zuo, et al., 2015). Though, the mortality rates vary across the world. In the UK, around 5000 people are diagnosed with liver cancer every year and around the same number die every year. Early stage diagnosis allows better and improved treatment of patients. Prevention rate is around forty-two percent, if diagnosed at early stages (Zhou, et al., 2015; Zhou, et al., 2014; Zhou, et al., 2016; Zhou, et al., 2016). Hence, the demand to find biomarkers of liver cancer is increasing day by …show more content…
Thus, it is essential to identify gene/biomarkers that can distinguish patients with high and low risks of recurrence (Zhi, et al., 2016; Zhong, et al., 2016). RNA quantification enables us to understand the switch on and off of a particular gene, i.e., gene expression. Expression profiling of RNA explains the real-time activity of cells along with its expressed genes in those concerned cells. Microarrays mainly deal with exon-level and hence, it has its limitation and biases. RNA-seq permits a wider and deeper examination of gene expression. Calculating for the influence of mi-RNA effects role in cancer has been shown as an important step in understanding its
Liver cancer is the foremost cause of cancer deaths in Asia and Africa. Liver cancer is a malignancy with exceptionally low prospects of the five-year survival rate of less than 9% (Zuo, et al., 2015). Though, the mortality rates vary across the world. In the UK, around 5000 people are diagnosed with liver cancer every year and around the same number die every year. Early stage diagnosis allows better and improved treatment of patients. Prevention rate is around forty-two percent, if diagnosed at early stages (Zhou, et al., 2015; Zhou, et al., 2014; Zhou, et al., 2016; Zhou, et al., 2016). Hence, the demand to find biomarkers of liver cancer is increasing day by …show more content…
Thus, it is essential to identify gene/biomarkers that can distinguish patients with high and low risks of recurrence (Zhi, et al., 2016; Zhong, et al., 2016). RNA quantification enables us to understand the switch on and off of a particular gene, i.e., gene expression. Expression profiling of RNA explains the real-time activity of cells along with its expressed genes in those concerned cells. Microarrays mainly deal with exon-level and hence, it has its limitation and biases. RNA-seq permits a wider and deeper examination of gene expression. Calculating for the influence of mi-RNA effects role in cancer has been shown as an important step in understanding its