Introduction

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).

Figure 1

Table 1: Incidence of cancer in developing countries compared with that in developed countries.

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.

Oncogenes

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.

Figure 2

Table 2: Examples of some oncogenes

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

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-trans retinoic acid and arsenic trioxide (Zhang et al. 2001; Chen Z, 1996; Chen G, 1997). This suggests that such stratification of patients into subgroups based on the molecular nature of tumors may also help to identify more viable targets for more effective therapeutics.

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 et al. 2007). Several proteomic and genomic technologies, are in use, such as array comparative genomic hybridization (CGH), cDNA microarrays, tissue microarrays (TMA), serial analysis of gene expression (SAGE), high-throughput DNA sequencing, RT-PCR assays and digital karyotyping, however, the most widely used techniques have been discussed here.

Comparative Genomic Hybridization (CGH)

DNA Microarrays

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 ras, p53, RB, p16, myc, and bcr-abl etc) associated with the cancer generally determines the choice of the target. Overexpression of specific gene products, such as HER-2, epidermal growth factor (EGF) and insulin-like growth factor receptors, and cyclins, has also been correlated as a causative factor in some cancers (Sherr, 1996). Alternatively, a normal gene product may be closely correlated with cancer progression. For example, elevated telomerase activity is observed in essentially all human cancers and increased serum vascular endothelial growth factor (VEGF) has been reported to be a prognostic clinical factor correlated with decreased survival in breast, ovarian, lung, gastric, and colon cancer patients. Many molecular tools are available for target validation, including antisense oligonucleotides, ribozymes, dominant negative mutants, and neutralizing antibodies. The use of several of these tools has led to the recognition that the telomerase enzyme and the KDR receptor of VEGF are good targets for drug development (Neufeld et al. 1999). Telomerase regulates the immortalization properties of tumors, that is, it delays senescence by inactivation of the tumor suppressor gene and KDR is expressed in normal vasculature endothelial cells that would not be expected to have the genomic instability problems of the surrounding tumor cells.

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 p16 indicates that protein kinase inhibitors to these targets may inhibit tumors having defective p16 (Sherr, 1996). Alternatively, there may be new approaches to find pharmaceutically tractable targets that might not be identified by our current knowledge of cancer genomics (Table 3.).

Figure 3

Table 3: Novel anti-cancer targets

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.

Figure 4

Table 4: Tyrosine Kinase Inhibitors

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.

Conclusion

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.