6.1 Introduction

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History

 

Until the mid 20th century, surgery dominated the field of cancer treatment, yielding many successful patient remissions (6). However, as noted by several physicians, remission was undoubtedly followed by relapse, and eventually death (6). Despite great advances in cancer research, progress was slow and finding a cure seemed to be out of reach.

 

Although a cure was not found, intensive efforts finally brought upon great achievements in treatment; such as the use of combinatorial chemotherapy and ionizing radiation, which would ultimately lengthen the patient’s life by several months or years (6). Nevertheless, the occurrence of relapse was inevitable, often with a more aggressive form of cancer, and while every attempt was seen as a step closer, it was not enough (6).

 

It was not until the vast advancements in science’s genetic technologies, such as gene expression profiling, that a key missing piece became apparent. It was discovered that tumours are distinct both at the gross and molecular levels (10). Moreover, tumours typically derived from a single cell (i.e. monoclonal) were often composed of different subpopulations arising from the selectively for advantageous mutations (10). It is this concept of tumour heterogeneity that made it impossible for a single cure to exist. As a result, cancer is considered as a disease that is distinct to the individual. It is from this idea that personalized cancer therapy is considered the only approach towards a cure (11).

 

Chapter Overview

Figure 6.1.1. Cancer drugs only work on some cancer cells.Treatments work for some cancers and not others.  Each cancer is unique, with different genes involved and therefore different sensitivity to drugs. As cancer cells grow and change, some cells in the same patient may become resistant to a drug.  These cells will remain after treatment, causing relapses. Released under the Creative Commons Attribution-ShareAlike 4.0 International license (CC BY-SA 4.0).

In this chapter the fundamental aspects of personalized cancer therapy including common laboratory techniques, the essential components required to develop patient-tailored therapy, and an analysis of some successful cases of personalized cancer therapy will be discussed. 

Two essential laboratory techniques that have revolutionized the field of cancer research will be elaborated: DNA sequencing and genotyping. DNA sequencing is a technique used to determine the exact sequence of nucleotides in a DNA molecule (4). Current techniques stem from the development of Sanger sequencing in 1977, which remained the first-line sequencing methods up until the end of the Human Genome Project in 2003 (4). Since then, sequencing technology has rapidly evolved to produce high throughput methods at a reduced cost and is referred to as next generation sequencing (NGS) (4). For genotyping, rather than determining the specific nucleotide sequence of DNA, it involves looking at an individual’s differences in genetic variations that may be present in a population (1). Genotyping techniques may reveal the inherited alleles of an individual and determine variations in single nucleotide polymorphisms (SNPs), copy number variants (CNVs), microsatellites or insertion/deletion polymorphisms (13). It has been an important tool in the discovery of associations between genes of interest and their variants—particularly in genetic studies of diseases (1).

 

As the realm of cancer research rapidly evolves, advancements in clinical practices have quickly followed suit. This has been quite evident with the development of novel cancer diagnostics. In the past decade, diagnosing cancer has gone from a pathology-centered approach towards a multi-disciplinary focus (7). The latter includes the combination of microscopy with the detection of molecular biomarkers either present in the blood or genetically expressed from a sample of tumour tissue (7).

 

In addition to novel diagnostic methods, personalized cancer therapy permits treatment be tailored towards the individual. Thus, the field of pharmacogenomics has emerged as a means to optimize treatment efficacy and minimize drug toxicity (8). Pharmacogenomics takes into account an individual’s genotype and how that may influence their response to treatment (8). Since cancer treatments such as chemotherapy have narrow therapeutic windows, this knowledge is particularly useful for preventing adverse drug reactions (ADR) whcih can sometimes be fatal (8). 

 

Although diagnostic and pharmacogenetic assessments are essential for personalizing a patient’s treatment, they also require prognostic assessments that ultimately define a patient’s outcome. Until recently, prognostics were highly dependent upon the tumour-node-metastasis (TNM) staging system since its early development in the 1950’s (9). In this approach, the progression of an individual’s cancer is described by assessing tumour size, nodular involvement, and metastatic events (3). Despite its widespread use it has been criticized for inaccurate results as it only assesses physical characteristics (3). In response to obtaining prognostic assessments with higher accuracy, researchers have taken advantage of tissue and serum-based markers, as they are easily accessible (5).

 

To conclude, a few examples of personalized cancer treatments that have shown great success in the clinic will be highlighted. These include treatments such as Trastuzumab for breast cancer, Imatinib for chronic myelogenous leukemia, EGFR inhibitors, and cancer immunotherapy. In addition, some of the key ethical issues regarding personalized cancer therapy including incidental findings from genetic tests, genetic discrimination, and inequality in pharmacogenomics will be explored (2).

 

With the advent of rapid improvements in genomic sequencing, tumor profiling has steadily become a routine task that has paved its way as a contributor to personalized medicine. However, it should be noted that the technical proficiency in acquiring these genomic variations within a tumor is not sufficient enough in developing a genomic-based medicine (12). A series of scientific, logistical, and regulatory hurdles must be surmounted in order to bridge the gap between clinical science and medicine. The first and foremost of these bottleneck doors is the need to crucially understand the downstream contributions of the discovered genomic variations to the biology of the tumor. These contributions include the effects on the tumor’s proclivity to metastasize and behavior in response to certain chemotherapeutic agents (12).

 

Concurrently, stagnation of the transition from genome sciences to personalized cancer therapies is attributed to the incomplete log of genomic variations in the wide selection of cancers. As a result, it is crucial that a reference cancer genome be established in order determine the adequate biomarkers and thus drugs required to be administered.

 

 

References

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  2. Christenhusz, G. M., Devriendt, K., & Dierickx, K. (2013). To tell or not to tell? A systematic review of ethical reflections on incidental findings arising in genetics contexts. European journal of human genetics : EJHG21(3), 248–55. doi:10.1038/ejhg.2012.130
     
  3. Hodul, P., & Yeatman, T. (2007). TNM staging is obsolete. Journal of surgical oncology, (May 2006), 8–9. doi:10.1002/jso
     
  4. Hutchison, C. a. (2007). DNA sequencing: bench to bedside and beyond. Nucleic acids research35(18), 6227–37. doi:10.1093/nar/gkm688
     
  5. Menéndez, P., Villarejo, P., Padilla, D., Menéndez, J. M., & Montes, J. a R. (2013). Diagnostic and prognostic significance of serum microRNAs in colorectal cancer. Journal of surgical oncology107(2), 217–20. doi:10.1002/jso.23245
     
  6. Mukherjee, Siddhartha. The Emperor of All Maladies: A Biography of Cancer. New York: Scribner, 2010. Print.
     
  7. Ramaswamy, S., Tamayo, P., Rifkin, R., Mukherjee, S., Yeang, C. H., Angelo, M., Ladd, C., et al. (2001). Multiclass cancer diagnosis using tumor gene expression signatures. Proceedings of the National Academy of Sciences of the United States of America98(26), 15149–54. doi:10.1073/pnas.211566398
     
  8. Ross, C. J. D., Visscher, H., Sistonen, J., Brunham, L. R., Pussegoda, K., Loo, T. T., Rieder, M. J., et al. (2010). The Canadian Pharmacogenomics Network for Drug Safety: a model for safety pharmacology. Thyroid : official journal of the American Thyroid Association20(7), 681–7. doi:10.1089/thy.2010.1642
     
  9. Saitta, N., & Samuel, D. (2012). Efficacy of a Physician ’ s Words of Empathy : An Overview of State Apology Laws, 112(7), 7–12.
     
  10. Visvader, J. E., & Lindeman, G. J. (2008). Cancer stem cells in solid tumours: accumulating evidence and unresolved questions. Nature reviews. Cancer8(10), 755–68. doi:10.1038/nrc2499
     
  11. Wei, Q. (2012). Personalized medicine at a prime time for cancer medicine - Introducing Cancer Medicine. Cancer medicine1(1), 1. doi:10.1002/cam4.1
     
  12. Chin, L., Anderson, J.N., & Futreal, P.A. (2011). Cancer genomics: from discovery science to personalized medicine. Nature medicine, 17(3): 297-303. doi:10.1038/nm.2323
  13. Shi, M. M. (2001). Enabling Large-Scale Pharmacogenetic Studies by High-Throughput Mutation Detection and Genotyping Technologies. Clinical Chemistry, 47(2), 164-172.