Introduction
It is not fully understood by a large portion of the population, that each and every person is truly biologically unique, from our fingerprint to our genome (Topol, 2014, p. 241). This has now been made abundantly clear through the use of compressive ‘omic’ assessments of individuals, including DNA and RNA sequencing, and to a lesser extent the metabolone, proteome, and even the microbiome, autoantibodies and epigenome (Topol, 2014, p. 241). This information can now give rise to the exceptional and unparalleled opportunity to improve medical treatment for those with cancer and develop the preventative strategies required to maintain health (Topol, 2014, p. 241). Topol (2014, p. 248) states that the current classification of cancer, …show more content…
585). Personalised medicine is the application of genetic information to predict the development and progression of a disease and influence decisions about lifestyle choices and/or tailor medical treatment to the individual characteristics of each patient (National Research Council, 2011; NHMRC, 2011, p. 1-2). Personalised medicine is imperative for the future of cancer research and treatment as is allows screening, early intervention and optimization of treatment to be concentrated on those who will benefit, while reducing adverse side effects for those who are unlikely to benefit (NHMRC, 2011, p. 2). Although our understanding of the complex development and biology of cancer is forever expanding the introduction of new personalised therapies, there has still been little impact in the clinical setting (Topol, 2014, p. 248). Clinicians and researchers alike should be working towards the common goal of utilizing these omic technologies to facilitate disease prediction, prevention and treatment strategies, as well as reducing the number of drug related complications and side effects that results from ‘one size fits all’ drugs (NHMRC, 2011, p. …show more content…
583). This complexity stems from the multifaceted interplay of genomics aberrations, and immunological, hormonal environments, and other disease factors, acting individually or in combination (Tan et al., 2012, p. 583). Progress in cancer research and treatment has been dominated by the concepts and methods of molecular genetics, but continuous advances in a number of omic technologies, such as those discussed above, have taken cancer research and treatment to a far deeper and personalised place (Chen & Yates, 2007, 144). It is important to understand that no one omics technology can address all the questions on cancer, but using a multilayer approach by integrating a number of methods should allow for advancements. The cancer genomic medicine of the future will utilize this convergence of omic technologies to form a ‘geographic information system’ of the tumor, with assessment of the DNA sequence, gene expression, RNA-seq, micro RNAs, proteins, copy number variations, and DNA methylation cross references with the individual’s germline DNA (Topol, 2014). Along with these assessment, clinical data will also be assessed to allow for screening, early intervention and optimization of treatment to be concentrated on those who will benefit, while reducing adverse side effects for those who are unlikely to
It is not fully understood by a large portion of the population, that each and every person is truly biologically unique, from our fingerprint to our genome (Topol, 2014, p. 241). This has now been made abundantly clear through the use of compressive ‘omic’ assessments of individuals, including DNA and RNA sequencing, and to a lesser extent the metabolone, proteome, and even the microbiome, autoantibodies and epigenome (Topol, 2014, p. 241). This information can now give rise to the exceptional and unparalleled opportunity to improve medical treatment for those with cancer and develop the preventative strategies required to maintain health (Topol, 2014, p. 241). Topol (2014, p. 248) states that the current classification of cancer, …show more content…
585). Personalised medicine is the application of genetic information to predict the development and progression of a disease and influence decisions about lifestyle choices and/or tailor medical treatment to the individual characteristics of each patient (National Research Council, 2011; NHMRC, 2011, p. 1-2). Personalised medicine is imperative for the future of cancer research and treatment as is allows screening, early intervention and optimization of treatment to be concentrated on those who will benefit, while reducing adverse side effects for those who are unlikely to benefit (NHMRC, 2011, p. 2). Although our understanding of the complex development and biology of cancer is forever expanding the introduction of new personalised therapies, there has still been little impact in the clinical setting (Topol, 2014, p. 248). Clinicians and researchers alike should be working towards the common goal of utilizing these omic technologies to facilitate disease prediction, prevention and treatment strategies, as well as reducing the number of drug related complications and side effects that results from ‘one size fits all’ drugs (NHMRC, 2011, p. …show more content…
583). This complexity stems from the multifaceted interplay of genomics aberrations, and immunological, hormonal environments, and other disease factors, acting individually or in combination (Tan et al., 2012, p. 583). Progress in cancer research and treatment has been dominated by the concepts and methods of molecular genetics, but continuous advances in a number of omic technologies, such as those discussed above, have taken cancer research and treatment to a far deeper and personalised place (Chen & Yates, 2007, 144). It is important to understand that no one omics technology can address all the questions on cancer, but using a multilayer approach by integrating a number of methods should allow for advancements. The cancer genomic medicine of the future will utilize this convergence of omic technologies to form a ‘geographic information system’ of the tumor, with assessment of the DNA sequence, gene expression, RNA-seq, micro RNAs, proteins, copy number variations, and DNA methylation cross references with the individual’s germline DNA (Topol, 2014). Along with these assessment, clinical data will also be assessed to allow for screening, early intervention and optimization of treatment to be concentrated on those who will benefit, while reducing adverse side effects for those who are unlikely to