R Ghosh, I Dhande, V Kadam
genomic technologies, molecular classification, novel molecular targets, oncogenes
R Ghosh, I Dhande, V Kadam. Oncogenomics: The Future Of Cancer Therapy. The Internet Journal of Pharmacology. 2007 Volume 5 Number 2.
At present, cancer accounts for 12% of the 56 million deaths occurring annually, making it one of the leading causes for death. The primary obstacle clinicians face today is that they are not adequately equipped to tackle this imminent threat. However, with the recent developments in the field of oncogenomics, our knowledge of exactly where, why and how tumorigenesis occurs has increased manifold. Genomic technologies such as 'comparative genomic hybridization' and cDNA microarrays have helped to improve our understanding of the genetic basis of cancer. Researchers are presently looking towards developing new anticancer drugs based on the discovery of novel molecular targets. The success stories of agents like Trastuzumab and Gleevec®)used in the therapy of HER-2 positive breast cancers and chronic myelegenous leukemia (CML) respectively, give us hope that not too long from now, oncogenomics will no longer remain a mere research modality, but will be used in clinical practice for the effective therapy of cancer. This article reviews some of the more recent developments in the field of cancer genomics and discusses the current status as well as the future trends.
Despite the advances in medical research, cancer is still one of the leading causes for death. Recently, the International Agency for Research on Cancer (IARC), a branch of the World Health Organization (WHO), published the World Cancer Report, which states that in the year 2000 alone, there were 10 million new cases of cancer reported globally. This figure is predicted to rise by a staggering 50% by the year 2020, due to steadily ageing populations, current trends in smoking prevalence, and unhealthy lifestyles. As per the American Cancer Society estimates, in India alone, at any given time, there are 2.5 million cases of cancer.
Table 1 shows the global incidence of cancer in the year 2002. The figures are compiled from the American Cancer Society publications (Parkin et al, 2005).
Surgery and radiation, the primary curative therapies for cancer, are usually only successful if the cancer is found while it is in an early localized stage. Once the disease has progressed to locally advanced or metastatic forms, these therapies are not as effective. Chemotherapy offers mainly palliative solutions, complete cure of the malignancy is not guaranteed. Additionally, most chemotherapeutic agents have severe dose-limiting toxicities and work within an extremely narrow therapeutic window. Clearly, new therapeutic options are necessary as the current trends in the treatment of cancer leave much to be desired.
The discovery of oncogenic defects in cancer coupled with the completion of the Human Genome Project has made it possible to translate the knowledge of the genetic basis of tumorigenesis into therapeutics that could selectively destroy tumors without the severe systemic side effects commonly associated with traditional chemotherapeutic agents. This has paved the way for new treatment options, like “Personalized Medicine”, a combination of pharmacology and genomics, a study of how variations in an individual's genes affect his response to different therapeutic regimens.
As our knowledge of biochemical processes and genetic information increases, so does our understanding of the underlying causes for cancer and as a consequence, the field of oncogenomics, or cancer genomics, has been born. Oncogenomics involves the study of oncogenes and how their genetic alteration ultimately culminates in tumorigenesis.
A greater understanding of oncogenes helps to classify and diagnose cancers. It may also help in predicting the clinical outcome of the disease. Knowledge of the mechanisms through which they act will present novel targets for anticancer therapy. This information may eventually help to prevent the occurrence of the disease itself, using techniques like gene therapy.
The Genetic Basis of Cancer
Cancer is a complex, highly variable disease of multiple accumulating mutations and is characterized by several genetic and epigenetic changes. These changes allow the cell to bypass the cell-cycle checkpoints and thus exhibit uncontrolled growth. Apart from this, cancer cells also have the ability to metastasize and generate their own vasculature (angiogenesis).
Broadly, the cancer-causing genes can be categorized into oncogenes and tumor-supressor genes. Comparative oncogenomics is a powerful tool to identify oncogenes, which uses animal models to predict the importance of the homologues of these genes in human cancers.
These are the genes capable of causing cancer. Mutations in proto-oncogenes, (i.e. the dormant form of oncogenes) may upset the normal cell-cycle regulation leading to uncontrolled growth and tumor formation.
No one oncogene itself results in cancer - cancer requires several mutations. But one oncogene can increase cell division, and consequently, increase the probability of other mutations occurring, which can eventually culminate in cancer.
Tumor suppressor genes code for anti-proliferation signals and proteins that suppress mitosis and cell growth. Generally, tumor suppressors are transcription factors that are activated by cellular stress or DNA damage. The p53 nuclear phospho-protein (coded by the tumor supressor gene TP53), one of the most important studied tumor suppressor proteins, is a transcription factor activated by many cellular stressors including hypoxia and ultraviolet radiation damage.
Despite nearly half of all cancers possibly involving alterations in p53, its tumor suppressor function is poorly understood. p53 clearly has two functions: one a nuclear role as a transcription factor, and the other a cytoplasmic role in regulating the cell cycle, cell division, and apoptosis.
Other tumor supressor genes implicated in commonly studied cancers include APC (adenomatosis polyposis coli), BRCA1 ( breast cancer type 1 - implicated in several hereditary cancers, especially those of the breast, ovaries and the prostate), BRCA2 (breast cancer type 2 – associated with carcinomas of the breast in both, females and males, pancereas, prostate, gall bladder and the renal tract.), RB1 (retinoblastoma 1 gene), WT1 (Wilm's tumor 1 gene), STIM1 (stromal interaction molecule 1 – implicated in Beckwith-Wiedemann syndrome, Wilms tumor, rhabdomyosarcoma, adrenocrotical carcinoma, and lung, ovarian, and breast cancer) etc. Deletions in one of the alleles of the KLF6 (Kruppel-like factor 6) have been implicated in nearly 77% of primary prostatic cancers ( Narla et al. 2001). Aberrant methylation and silencing of the TCF21 tumor suppressor gene has been shown to be associated with head and neck squamous cell carcinomas (HNSCC) and non small-cell lung cancer (NSCLC) (Smith, Lin, Brena et al. 2006). The Gprc5a gene has been found to play an important role as a tumor suppressor for lung cancer in mice and it is predicted that the GPRC5A gene in humans may share this property (Tao, Fujimoto, Ye et al. 2007). More recently, the cyclin dependent kinase inhibitor CDKN1C is being studied as a candidate tumor suppressor gene in human breast cancers (Larson, Schletler, Yang et al. 2008).
Details of the other tumor supressor genes are available online at the tumor supressor gene database (TSGDB).
The Molecular Classification of Cancers
At present, there is no single comprehensive, robust modern tumor classification available. The traditional classifications, such as the World Health Organization (WHO) classification, group the neoplasms according to the organ sites where they occur (Berman, 2004). A major drawback of this system is that a single organ may contain several organ-specific and organ non-specific cell types. So, tumors of the brain may affect the connective tissue system or the lymphoid tissue system, both of which are very different in many aspects (Kleihues, Burger, Scheithauer, 1993). In view of this, the WHO has now included in the classification, information regarding the molecular genetics of the cancer in addition to the histopathologic data (Kleihues, Sobin, 2000).
In January 1999, the U.S. National Cancer Institute (NCI) issued a challenge to the scientific community “to harness the power of comprehensive molecular analysis technologies to make the classification of tumors vastly more informative”. Presently, researchers are attempting to develop a new system of cancer classification, one that no longer phenotypically based but rather focuses on the genotypic aspects of the tumor (Berman, 2005).
Studies on the different molecular signatures of acute myeloid leukaemia (AML) and acute lymphoblastic leukaemia (ALL) have shown that gene expression alone can suffice for the molecular classification of cancers (Gloub et al. 1999). Data continue to accumulate on the genetic signature of dozens of malignancies (Zhang et al. 2001). For example, hereditary breast cancers have been studied in terms of their differing expression levels of certain genes, such as the keratin 8 gene, which was differentially expressed between the mutation-positive and mutation-negative breast cancer groups (Hedenfalk et al. 2000). Similarly, thyroid carcinomas have been profiled, and the degree of differentiation of cells in normal, differentiated, and undifferentiated tissue has been correlated with the expression levels of genes such as osteonectin, -tubulin, and glutathione peroxidase (Takano et al. 2000).
A more comprehensive system of classification may translate into better therapeutic approaches. For example, encouraging results have been obtained with drugs like Gleevec (a small molecule tyrosine kinase inhibitor) for the treatment of gastrointestinal stromal tumors (GIST) and chronic myeloid leukaemia (CML), both of which are of non-endodermal/ectodermal origin. Patients having acute promyelocytic leukemia who present a specific chromosomal translocation [t(15,17)] selectively respond to treatment with all-
However, the classification approaches have limitations as well. According to Quackenbush (2006), a majority of the studies conducted have not involved a sufficiently large number of patients; as a result, it is difficult to predict how the results obtained can be applied to large clinical populations. Also, the correlation of the molecular signatures and results of the DNA microarray studies is difficult. Having said that, it is evident that these signatures may serve as potential ‘biomarkers' that aid in the diagnosis and prognosis of the disease, as in the case of HER2 positive breast cancers.
Genomic Technologies in Cancer Research
Genomic technologies have found several applications in cancer research. By profiling and comparing gene expression of tumors of different grades or primary and metastatic tumors, the molecular signatures of several neoplasms have been discovered, making it possible to classify them into groups that were not possible using conventional approaches. These classification paradigms may predict disease outcome or response to specific molecular or chemotherapeutic agents. Genomic technologies may also allow clinicians to more accurately diagnose cancers based on its genotype rather than its histopathological characters alone. In fact, recently, these technologies have helped researchers identify a robust cancer gene expression signature common to almost all major human cancer types (Xu
Comparative Genomic Hybridization (CGH)
Comparative genomic hybridization is a technique that can be used to screen the entire genome for copy number aberrations in chromosomal material. This helps to identify amplifications and deletions that can act as molecular signatures for specific cancers (Kallionemi et al, 1992). Recurrent deletions in chromosomal material may indicate the presence of tumor suppressor genes, while amplifications act as markers for proto-oncogenes.
In this technique, genomic DNA of the test sample is labelled in red fluorescent dye while that of the reference sample is labelled with green fluorescent dye. Next, these DNAs are allowed to undergo metaphase hybridization. The chromosomal regions involved in amplifications appear green, while those involved in deletions are red. The regions equally represented in test and reference samples appear yellow (Cheng, Tanyi and Mills, 2002). To obtain higher resolution capabilities, the test DNA may be hybridized to DNA microarrays (Pinkel and Albertson, 2005).
Genome-wide studies using array-based CGH have already helped to identify copy number aberrations associated with several cancers and they also serve as useful diagnostic tools, as demonstrated by Golub
The relationship between the copy number aberrations and prognosis has been established for several cancers including prostate cancer (Paris
The potential of the comparative genomic hybridization technique was demonstrated by Albertson and colleagues, who used this approach to map the recurrent breast-cancer amplicon at chromosome 20q12.3 (Albertson DG, Ylstra B, Segraves R, et al. Quantitative mapping of amplicon structure by array CGH identifies CYP24 as a candidate oncogene. Nat Genet 2000;25:144-146). This approach clearly demonstrated that what had previously been described as a single amplicon was, in fact, two distinct amplicons, one containing the putative oncogene
Complementary DNA (cDNA) microarrays or DNA-chips are a collection of microscopic DNA ‘spots' on glass slides coated with a suitable adhesive substance such as silanes or polysilanes. Each spot has defined characteristics and is spotted with one selected gene having a known DNA sequence. These can either be a large probe of cDNA of the gene of interest, or short synthetic DNA sequences – oligonucleotides. Qualitative as well as quantitative measurements of DNA are based on the principles of selective DNA-DNA or DNA-RNA hybridization, detected by fluorophore-based techniques. Being relatively easy to use, less expensive and suitable for high-throughput applications, cDNA microarrays have become the method of choice for the assay of the total genetic activity in cells. Expression of oncogenes, tumor suppressor genes and drug resistance genes can be simultaneously studied enabling this method to find several applications in cancer research (Lander 1999). DNA microarrays are commonly employed to study gene expression or in comparative genomic hybridization (CGH).
Golub and colleagues (1999) used DNA microarrays to develop a systematic approach to classify cancers based on their molecular signatures. DNA-chips have already been used to differentiate between different types of leukemias as well as to identify previously unrecognized subgroups of leukemias that are morphologically indistinguishable (Gloub et al. 1999; Yeoh et al. 2002). Holleman et al. (2004) used this tool to predict the outcomes of acute lymphoblastic leukaemia (ALL) and help select the most effective therapy regimens. Similar studies have been carried out for colorectal (McLeod and Murray, 1999; Wang, Jatkoe, Zhang et al. 2004) and ovarian cancers (Kraggerud et al. 2000; Shridhar et al. 2001; Shayesteh et al. 1999) to predict patient responses to specific drugs. cDNA micro arrays have been used in examining 8000 genes in 60 cell lines from the central nervous system, renal, ovarian, leukemia, coloncancers, and melanomas (Ross et al. 2000). The results established the ability of the genomic approach to differentiate tumor subtypes and also to predict patient outcomes (Cheng, Tanyi and Mills, 2002).
Oncogenomics: A Tool For Targeted Therapeutics
Over the last 20 years, there has been a shift in the way target identification in cancer is approached. Advances in molecular biology now allow us to identify genes that become dysfunctional in cancer, and understand the molecular mechanisms underlying the disease. Presently, many genes are known to affect tumorigenesis and tumor growth, and the need of the hour is to decide which ones to exploit in the areas of signal transduction, cell-cycle regulation, apoptosis, telomere biology, and angiogenesis. The new approaches in targeted therapeutics include recombinant proteins, monoclonal antibodies, peptides, and small organic molecules as drug candidates.
Knowledge of the mutated gene (such as
The application of oncogenomics and cellular pathways can also be helpful for exploiting rational targets that prove difficult to inhibit because, as in the case of tumor suppressor genes, the protein target is no longer present in the tumor. For example, inhibition of specific cyclin dependent kinases by
Current and Investigational Molecular-Based Agents
One of the most commonly studied families of drugs based on ‘targeted therapeutics' are the protein kinase inhibitors. ST571 (Gleevec), a tyrosine kinase inhibitor and specifically targets bcr-abl tyrosine kinase, has been successfully used for the treatment of chronic myelegenous leukaemia (CML).
In some cancers, especially those of the lungs, oral cavity and the colon epidermal growth factor receptors (EGFR) are found to be overexpressed. The autocrine activation of EGFR can be inhibited by EGFR kinase inhibitors such as ZD-1839 (Gefitinib-Iressa®), which have shown favourable clinical results, particularly in non small-cell lung cancer (NSCLC). C225 (Cetuximab) is a monoclonal antibody that targets EGFR and is found to be useful in metastatic colorectal cancer. Cetuximab has been approved for the treatment of squamous cell carcinoma of the head and neck. Another monoclonal antibody is Trastuzumab (Herceptin®) that targets the HER2/neu protein (a receptor tyrosine kinase) and has been used to treat HER2 positive breast cancers.
Farnesyl transferase (FTase) inhibitors did not show significant anti-tumor activity in phase I trials, they are now being tested in combination with other therapies (Gibbs, 2000). Cyclin dependent kinases (cdk) play an important role in regulation of the cell-cycle events may also serve as potential targets for anti-cancer drugs (Shapiro and Harper, 1999).
Studies have shown that upregulation of IAPs, or inhibitors of apoptosis, particularly XIAP, and survivin is associated with several malignancies, including certain cervical cancers and adenocarcinomas (Espinosa et al. 2006). Survivin antagonists have shown promising results in preclinical trials as novel targets (Blanc-Brude et al. 2003). Mutations in the BRAF gene have been reported to be mutated in nearly 70% of malignant melanomas, and targeting this oncogene may provide effective therapies (Davies et al. 2002).
Recently, sphingosine kinase 2 (SphK2) has been shown to be a mediator in cytostasis and apoptosis in tumor cells (Sankala et al. 2007). It is predicted that this may prove to be a candidate for targeted therapy of colon and breast cancer.
Lehner et al. (2007) have demonstrated that the hepatocyte nuclear factor 6 (HNF6) and FOXA2 are key regulators in colorectal liver metastases and may possibly serve as useful targets in such cases.
The number of new cancer cases is growing at a staggering rate, and it has been predicted that by the year 2030 there will be an estimated 15 million new cases of this disease. Furthermore, close to two-thirds of the cancer cases predicted for 2050 will occur in low-income countries.At the same time, the medical treatment available at present provides mainly palliative care, complete cure of the malignancy is not guaranteed. Scientists in the field of cancer research are now attempting to go to the root cause of the problem to find effective solutions. Everyday, molecular signatures for various malignancies are being identified, new molecular classification paradigms are being established and novel anti-cancer agents that target specific pathways based on the tumor's histopathological features are being developed. The regulatory approval of Trastuzumab, Bevacizumab, Erlotinib, Gefitinib, Imantinib etc. have already demonstrated the impact of genomic technologies on the field of cancer research. Oncogenomics provides us with a valuable tool to diagnose cancers early, as well as determine an individual's response to a therapeutic regimen. We are now moving from an era of empirical therapy into one of ‘personalized medicine'. The key is to translate our knowledge of the genetic basis of cancer into the clinical setting and it is envisioned that not too long from now, there will be a time we will be able to cure cancer safely and effectively.