Nature Biotechnology – Advances in Genomics
In 1997, a Nature Biotechnology article reported how the advances in genomics have been building a foundation for a future of personalized medicine where produced drugs are directed to the individual rather than the “average person.” Over the years in health related industries, individualized medicine has become a powerful term that brings forth a depiction of a medical revolution that graduates from a “one size fits all” approach to one that factors in predictions of disease, diagnosis, and responsiveness to treatment methods for each person (Tutton, 2012). “The top ten highest-grossing drugs in the United States help between 1 in 25 and 1 in 4 of the people who take them,” (Schork, p. 609). Another crucial factor to consider is that there are also developed drugs, which can be detrimental to particular ethnic groups due to some studies biasing Caucasian subjects in traditional clinical trials, which is not very useful considering the United States’ diverse population. Researching and developing personalized, also known as precision, medicine is an iterative process. It requires investigation of the many genetic and/or environmental factors that influence a person’s response to a particular drug or treatment (Schork, 2015).
This field of science and its translation to clinical care had a rich history in order to get to where it is currently at today, where precision medicine is an objective that has become nearly tangible for the common audience. Here, I will go into the path personalized medicine has walked, it’s growth as technological advancements have been made in the medical and scientific spaces, and the power it has begun to show in the clinical setting, especially in regards to cancer patient care.
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Part 1 – History
Although many believe precision medicine originated in the late 1990s with the publication of the 1997 Nature Biotechnology article mentioned earlier, that is actually not the case. In truth it has another deeper history tracing all the way back to the 1800s when clinicians used this term to describe patient-focused care in which the physicians would understand and respond to their patients’ perspectives and “practice the ‘art’ of clinical judgment,” (Tutton, p.1721). Laboratory science’s role in medicine, the role most people are familiar with when thinking about researching therapeutic agents for clinical purposes, began around the 19th century. This was a result of the differing scientific communities contesting claims and counterclaims about the power and abilities of 17th century physician patient-focused care (Tutton, 2012).
Prior to the mid to late 19th century when there was an incited revolution of medicine being studied and tested in the laboratory environment, physicians practice their medical care in a way that could be described as either bedside or biographical medicine, since the majority of their work and care took place at the patient’s bedside in their home (Tutton, p. 1723). During the 19th century, the understanding of diseases was quite different as physicians thought of them as being a general state that affected the mind and body of the patient instead of being specific to certain organs and tissue. “In terms of therapeutic interventions… therapy was governed by the principle of specificity, the notion that therapy had to be matched to the idiosyncratic characteristics of individual patients and to the physical, social, and epidemiological peculiarities of their environments,” (Tutton, p. 1723). The physicians’ practices during this time were based on a belief and understanding that each patient had their own homeostasis, and so the physicians drew their conclusions based on detailed understandings of the individual to have a relatively thorough customization of the treatment strategy for the patient’s disease (Tutton, 2012).
In any case things began to take a turn during the 19th century as physicians either from or influenced by Parisian medical teachings began to question the efficacy of traditional procedures and drugs, which at this time had gone scientifically unproven. This therapeutic reformation movement resulted in several changes in medical practices. Traditional proceedings were overturned, creating a vacuum space as there had been increasing uncertainty about the practice of therapeutics. This discontent and rise in questions about medical procedures were a significant pivot in turning to the experimental sciences to lead the future of medicine. As a result of increased practice of laboratory practice, there was a reinvention of diagnosis. Disease was not longer considered to be an illness unique to a single patient, but rather something with a cause and effect that were similar in all individuals affected by the ailment. With this altered relationship amongst the physician, patient, and medicine as well as new technological developments at the turn of the 20th century, laboratory research began to investigate a new perspective of individual specificity by researching it in terms of a person’s immunological and metabolic characteristics (Tutton, 2012).
The research of English physician Archibald Garrod conducted in the late 1800s to early 1900s began to make a resurgence in the 1950s. At this time it became a major influence in the emergence of pharmacogenetics. As a result, there was now a greater focus on the inherited genetic differences amongst races as a way to explain variations in drug responses. As influential as Garrod’s work was in the 1950s, it began to take off even further in the late 1990s as there were greater advancements in technology and biotechnology, and pharmaceutical firms started to invest in the potential of pharmacogenetics. With the creation of the Human Genome Project in the 1990s, geneticists stressed how important it was to understand human genomic variations as it was these variations that would be the basis of drug development that could break from the antecedent “one size fits all” paradigm (Tutton, 2012).
Part 2 – Development of Personalized Medicine
Taking a slight step back from specifically personalized medicine, yet still relevant to its growth, systems biology is a field that analyzes the relationships among different components of a larger organization and how they fluctuate in response to either genetic or environmental stimuli. Its primary objective is to characterize the system, and it is this practice that has applications in the healthcare industry. The power of system biology in the health sciences has emerged as a result of five main factors: the Human Genome Project, the emergence of interdisciplinary biology stimulating powerful technological developments, the advancement of the Internet as a way to acquire and access large genomic data sets, the conception of treating biology as an informational science, and the development of efficient tools for conducting genomic, proteomic and metabolomic studies, which has made the aggregation of global data sets possible (Weston and Hood, 2004).
Proteins are actually the drivers dictating cell behavior, but they cannot be studied simply by analyzing the mRNAs that make up said proteins. As a result, the field of proteomics was established to focus entirely on studying these proteins. Due to technological advances in mass spectrometry and protein microarrays, proteomics has been able to steadily grow since the early 2000s. The advancements of systems biology and proteomics show promising evolution in predictive, preventative, personalized, and participatory, also known as P4, medicine. In order for this to come to fruition, the technologies for conducting genomic, proteomic, metabolomic, and phenotypic analyses will need to be further developed. Researchers will also need to investigate protein and gene regulatory networks as well as analyze and integrate large global data sets (Weston and Hood, 2004). Even though there are a lot of technical difficulties to work through in these research fields, these type of diagnostic techniques show promising advancements in early cancer detection.
Part 3 – Application in Cancer
Although it is common practice in medicine for cancer patients to undergo chemotherapeutic treatment regimens, only a proportion of them will reap the benefits while all are exposed to the potential toxic effects. Personalized medicine in cancer care will be beneficial in helping identify the optimal medical care for each patient to maximize treatment benefits and minimize adverse reactions in a more streamlined manner. With the primary commonalities of cancer cells being uncontrolled growth, invasion, and metastasis, it is a relatively universal practice to classify cancers by the organ type. However, the goal of this type of care being successfully applied to cancer cannot be realized until researchers steps outside the organ-based classification construct and explore molecular classifications as well. By classifying tumours on the molecular level, scientists can obtain a better comprehension of tumor pathogenesis and predict the behavior of each tumor, thereby optimizing treatment strategies on a more personal level (Ogino et al., 2011).
Examinations of the host-tumor dynamic in the microenvironment has comprised the field of molecular pathological epidemiology (MPE), where researchers would investigate how environmental, lifestyle and genetic factors relate to tumor molecular features, in order to discover carcinogenic mechanisms. Ogino and colleagues believed that host immune cells played a vital role in regulating tumor growth in its microenvironment and therefore could create favorable circumstances for therapeutic and preventative interventions. Assessing immune cell interactions with its environment in the clinical setting will provide results about a patient’s prognosis and also postulate predictive information of patients treated with immunotherapy (Ogino et al., 2011)
Substantial progress has been made in designing therapeutic measures for cancer and other diseases. There are experimental drugs that are currently being designed and developed in order to target either specific tissues in the body or types of cancer. Some of these developing experimental procedures will not only result in unique identification of any malfunctioning signaling pathways, but also of any systems that result in the differentiation between normal and malignant phenotypes without actually needing to know the specific molecular changes that are causing the malignancy (Anderson et al., 2006).
Laboratory techniques such as immunostaining and in situ hybridization are being used to visualize gene expression levels, any abnormal proteins or gene transcripts with high specificity in diagnostic molecular pathology laboratories. Anderson and colleagues stated that single nucleotide polymorphism (SNP) genotypes are valuable impressions of one’s genome that should be analyzed on the large scale. SNPs are a powerful tool as prognostic and predictive markers of disease, and multiple SNPs can be analyzed in identifying cancer-susceptibility genes by either population of family-based studies (Anderson et al. 2006). Even though there have been numerous comprehensive studies on the subject, only a few SNPs have been found to be statistically significant as prognostic markers for breast cancer by correlation with factors such as breast cancer status, tumor size and age of onset (Andersen et al., 2006).
SNPs in p53, estrogen and progesterone receptors were found to be associated with a reduced risk of breast cancer, while genes involved in DNA repair correlated with an greater risk of breast cancer (Anderson et al., p. 200). One example is human epidermal growth factor receptor 2 (HER-2), which is overexpressed in 10-34% of breast cancer cases and its overexpression has been recognized to be a strong prognostic and predictive marker (Anderson et al., p. 200). The characterization of more SNPs is anticipated to occur in the foreseeable future. This progress will be able to provide a powerful tool in identifying susceptibility genes by conducting linkage disequilibrium studies and assessing any predictive or prognostic markers by these SNPs (Anderson et al., 2006).
The combination of traditional cell biology methods such as autoradiography and in situ hybridization, with biophysical methodologies such as nuclear magnetic resonance or infrared spectroscopy, have been applied to monitoring significant physiological changes with great success. It is through these combinatorial approaches that it is feasible to observe changes in tissue biochemistry when there’s a shift from normal or pathological. “For example, a lower than normal concentration of taurine and carnitine in dystrophic muscles from the muscular dystrophy (mdx) mouse model of Duchenne Muscular Dystrophy was revealed [by McIntosh and colleagues in 1998] using proton [nuclear magnetic resonance] NMR spectroscopy,” (Anderson et al., p. 202). Another study by Shaw and colleagues in 1996 applied Fourier-transformed infrared spectroscopy of mdx muscles to track the progression of fibrotic muscles upon diagnosis of dystrophy. As a result, they were able to trace partial alleviation of collagen accumulation following steroid treatment. These past studies on Muscular Dystrophy progression and treatment have demonstrated how correlations on measurements taken independently from different approaches can broaden the impact that the conclusions reaches. Similar combination studies in cancer diagnosis and treatment outcomes have shown to be advantageous and effective (Anderson et al., 2006).
One of the more difficult challenges to investigators is discovering the test(s) that are both specific and sensitive enough to unveil a particular genetic or biochemical matter in a predictive manner. The advancement of imaging techniques and metabolomic approaches in recent years have greatly contributed to the rapid and powerful advances. With these technological advancements, new approaches to identify and quantify proteins that contribute to cancer formation and development are in progress. One useful marker in cancer diagnosis that researchers have been investigating is the monitoring of changes in intracellular protein phosphorylation patterns. It has been known mutations in protein kinases that lead to more changes in protein phosphorylation are prominent in tumor development and progression (Anderson et al., 2006).
To combat this tumor development and proliferation, most anticancer treatment protocols work to kill the targeted cells by inducing their apoptosis. Cytochrome C is a protein with one of its functions being cell death regulation. For cancer patients, increased levels of Cytochrome C correlate well with ongoing cell death induced by their cancer therapy, indicating it also correlates with long-term survival. Tracking prognostic markers such as Cytochrome C in this context can be helpful in predicting a disease’s outcome and therefore can be utilized in determining high-risk patients that are in need of either more aggressive or experimental therapy. Combining biochemical apoptotic markers, with indicators for specific tissues and/or developmental stages and genetic diagnostics, SNP mapping, histological, and NMR tests have the potential to one day allow not just precise detection and localization of cell death in vivo, but also facilitate semi-automatization of the diagnostic process and decisions in determining treatment (Anderson et al., 2006).
Part 4 – Current and Future Work
With the convergence of systems biology, big data analysis, and technological evolution, medicine has emerged that is predictive, preventative, personalized, and participatory. Predictive medicine will be insightful in optimizing one’s wellness by allowing clinicians to detect illnesses at the earliest detectable phase whether it be weeks or months before symptoms become noticeable (Hood, 2013). Preventative medicine will use drugs to bring disease-perturbed environments back to their normal status, thereby curing or treating the disease. With preventative medicine diseases will be ranked according to the individual’s genetic foundation, and in doing so, treatments will be optimized according to the individual patient, making them their own control in establishing a standard of well-being. As a result of greater engagement of the patient in medicine, participatory medicine will have patient-directed communities that will aid in revolutionizing their medical care. “The ultimate objectives of P4 medicine are simple: 1) improve health care; 2) reduce the cost of health care; and 3) stimulate innovation and new company creation” (Hood, p. 13). Achieving these objectives of P4 medicine will positively reform the medical care space with an “N-of-1” approach that will allow the patient to have more power and understanding of their treatment.
In an ideal world, precision, medicine would join molecular profiling with clinical-pathological principles to create diagnostic, therapeutic and prognostic regimens uniquely tailored to each patient’s needs. Despite what people may think, precision medicine is more than just classifying individual therapies and causes. Knowing the ins and outs of a patient’s genetic profile will guide physicians in selecting the optimal medication and therapeutic protocol, minimizing any adverse reactions. Focusing on the future of personalized medicine in cancer treatment, therapeutic strategies based on any abnormal genetic changes have actually already made an impact on the care of cancer patients. One such example is treating cancers with an Epidermal Growth Factor Receptor (EGFR) gene mutation by EGFR kinase inhibitors. Another interesting aspect of precision medicine in cancer treatment to mention is the utilization of biomarkers that can express one’s response to chemotherapy. What is known as DNA methylation profiling can be appropriated to evaluate a patient’s response to chemotherapeutic agents (Yan et al., 2016).
“It is now a well-established concept that epigenetic alterations are driver events in the pathogenesis of human cancers,” (Yan et al., p. 127). Epigenetic therapy is an umbrella term encompassing the utilization of drugs or other epigenome-based techniques with the goal to treat medical conditions. In the sphere of cancer research, epigenetic therapy is investigated to target specific proteins that influence the cancer genome. It has become apparent histone lysine methylation is a decisive factor in regulating gene expression, the cell cycle, genome stability and nuclear organization as it can signal either activation or repression depending on the lysine residue that is methylated. A lot of work is underway to discover and/or develop drugs that have the ability to revert specific histone methylation marks or target histone methyltransferases (HMTs) or demethylases (HDMs) (Yan et al., 2016).
Within each cancer patient’s case, there are typically multiple epigenetic abnormalities that have accumulated into their cancer diagnosis. The research on cancer and personalized medicine has been considering demethylation agents and histone deacetylase (HDAC) inhibitors that could synergistically reactivate gene expression, resulting in more effective tumor suppression. In addition to the demethylating agents and HDAC inhibitors previously mentioned, there are other epigenetic targeting agents that could result in tumor cells becoming more sensitive and responsive to chemotherapeutic agents. Cancer researchers have also been looking into RNA-based cancer therapeutics, mi-RNA being one of them. For example RNA gene miR-21 has oncogenic capabilities and there have been studies focused on targeting miR-21. These investigations serve as one of the first examples of inhibiting cancer pathogenesis by decreasing oncogenic miRNA expression (Yan et al., 2016).
As of present genetic alterations have only been used in directing therapeutic strategies for small subsets of certain types of cancer with a specific alteration. Also suitable for precision medicine, altering DNA methylation functions have been applied to identify tumor-specific drug responsiveness (Yan et al., 2016). Based upon Yan and colleagues’ discussion, it would be a significant milestone in the future to build upon this current research and develop therapeutic strategies for other types of cancer to both identify drug responsiveness and strengthen a tumor’s sensitivity to chemotherapeutic agents.
“Personalized medicine will provide the link between an individual’s molecular and clinical profiles, allowing physicians to make the right patient-care decisions and allowing patient the opportunity to make informed and directed lifestyle decisions for their future well-being,” (Ginsburg and McCarthy, p. 491). Before it comes to making these N-of-1, individualized trials more common and accessible, there are still many barriers that need to be overcome. Regulatory agencies, clinicians and some researchers are hesitant about deviating from the standard clinical trials. Also, pharmaceutical companies tend to place their focus on drugs that can be used by the masses. Moreover, one of the important things to address is that personalizing medicine on an individual basis is very expensive. For example, there is currently the Foundation Medicine company in Cambridge, MA that charges patients between $5,000-$7,500 to sequence their tumors and use that data to consult on potentially effective treatment methods for said patient (Schork, 2015).
However, there is still promise these barriers will be overcome for a few reasons. As of recent, there has been a growing interest in assays that investigate a person’s unique characteristics at the molecular level. Researchers have been looking into assaying people’s blood metabolites and the unique microbes in their bodies as well as DNA and RNA. Additionally, government divisions and life-science firms are becoming increasingly understanding and supportive of not only developing a more targeted approach in medicine, but also having greater patient engagement. This type of development has been shown by the 2010 establishment of the US Patient-Centered Outcomes Research Institute (Schork, 2015).
Although a very expensive and iterative process, researching and developing personalized medicine has grown over the decades to have the potential to save millions of dollars currently being spent on the management of recurring diseases and other forms of unsuitable interventions (Schork, 2015). In regards to cancer research and practice in the clinical setting, it is till very much limited as there is a balance between risk versus reward for each patient to account for. That type of information is still an unknown, but is a goal for the scientific community to work towards.”