Cancer genome sequencing and potential application in oncology

Abstract

Future OncologyVol. 6, No. 10 EditorialFree AccessCancer genome sequencing and potential application in oncologyChristos Katsios, Odysseas Zoras & Dimitrios H RoukosChristos KatsiosDepartment of Surgery, Ioannina University School of Medicine, Ioannina, Greece, Personalized Cancer Medicine, Biobank, Ioannina University, Ioannina TK 451 10, GreeceSearch for more papers by this author, Odysseas ZorasDepartment of General Surgery, Heraklion University Hospital, Crete, GreeceSearch for more papers by this author & Dimitrios H Roukos† Author for correspondenceSearch for more papers by this authorEmail the corresponding author at droukos@uoi.grPublished Online:9 Nov 2010https://doi.org/10.2217/fon.10.115AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinkedInRedditEmail Keywords: biological systemcancer genome sequencingdrug/biomarkergenetic interactiononcologystandard treatmentDespite modern systemic treatment with chemotherapy and targeted therapy, solid-cancer treatment failure and death rates are still alarmingly high. The first complete human genome sequencing 10 years ago created optimism for new strategies in the prevention and treatment of cancer and improved health. A decade later, where do we stand now, and what are the prospects for translating genome sequencing information into oncological practice by 2020?In an effort to link normal traits, such as height or weight, and diseases pathogenesis and evolution with genetics and genomics, recent genome-wide association studies (GWAS) [1,2] and, more recently, complete genome sequencing studies [3] have revealed that this genotype–phenotype relationship assessment is far more complicated than we thought [4,5]. Each cancer patient is unique and, among patients with the same clinicopathologic features, tumor stage and treatment, responses to therapy and oncological outcomes vary considerably [6]. Based on this assessment and the ability of next-generation sequencing (NGS) to identify faster and cheaper genetic alterations underlying cancer development and metastasis, new oncological strategies are being shaped. It would be ideal if these mutations could simply be linked to phenotypes. However, the genotype–phenotype map does not represent a linear relationship, and there are still major challenges [7,8].Standards in oncologyComparative-effectiveness research (CER) using randomized controlled trials (RCTs) and meta-analyses as tools for objective assessments [9,10] have established new diagnostics and therapeutics developed by advances in cancer biology and molecular oncology [11]. Several prevention and treatment strategies for the most common cancers have been standardized over the last few years, but the way for major clinical success continues to be a goal for the future.Risk prediction-based preventionScreening programs for the general population, including mammography for breast cancer, colonoscopy for colorectal cancer and prostate-specific antigen (PSA) levels screening for prostate cancer, have been standardized. These advances have substantially increased the rates of early cancer detection, so that more patients are diagnosed today than previously at early-stage cancer, saving the lives of thousands of patients. However, many low-risk individuals undergoing unnecessary screening, and often recieving false-positive results, leads to unnecessary biopsies. Moreover, for other patients, prognosis remains poor, either because of late diagnosis of interval cancer between two screenings or aggressive disease, even at early stages. Furthermore, recent evidence-based analyses raise valid concerns for new biomarkers. For example, the most popular and widely used PSA screening, as evidenced by the US Preventive Services Task Force, shows that PSA screening is associated with psychological harm, and its potential benefits remain uncertain [12]. The current lack of robust biomarkers in cancer true-risk prediction among individuals for the achievement of personalized medicine is not surprising if we consider emerging evidence from cancer genome sequencing, which reveals the high complexity and heterogeneity of cancer development [4–7,13,14].Heritable mutations contributing to cancer riskDuring evolutionary human history, a tremendous number of mutations ensuring diversity of human life have accumulated [15]. However, some of these genetic alterations are pathogenic, contributing to cancer risk. Recent GWAS have shown that these mutations are classified into two categories: rare mutations in the general population with a large effect on cancer risk, and common mutations with low cancer risk. However, only rare mutations with high cancer risk have clinical implications, whereas common low-risk mutations have minimal or no clinical implications [16]. For example, results of GWAS towards personalized medicine have revealed that very rare mutations increase the risk of conditions such as schizophrenia, epilepsy or autism by up to 20-fold. On the other hand, common mutations, such as nine and ten single-nucleotide polymorphisms (SNPs) identified by GWAS that may be involved in cardiovascular disease and breast cancer, respectively, did not seem to improve disease risk-prediction [17,18].Earlier findings using conventional single-gene molecular research have identified inherited rare mutations that cause hereditary breast/ovarian cancer, colorectal cancer (Lynch syndrome) and diffuse gastric cancer for individuals who test positive for heritable mutations in BRCA1/BRCA2, mismatch-repair genes and CDH1 gene, respectively. However, although genetic testing is currently widely used and prophylactic surgery for mutation carriers protects from cancer development, there are serious limitations. Prophylactic surgery has negative effects on quality of life; approximately 25% of mutation carriers never develop cancer in their life and, thus, experience an unnecessary surgery. In addition, these hereditary syndromes are rare, and the vast majority of individuals who will develop cancer cannot be identified and predicted [11].Targeted treatment: advances & limitationsOver the last 10 years, the advent of biologically targeted agents has created an overenthusiasm for improving oncological outcomes. The potential ability of druggable targets to block the function of cancer cells but not healthy cells has contributed to a rapidly growing list of approved drugs, and many others are undergoing clinical evaluation. The present generation of drugs includes two major groups: monoclonal antibodies and small-molecule tyrosine kinase inhibitors. Trastuzumab is the most popular antibody for the treatment of breast cancer and gastric cancer [19–21], the anti-EGF receptor cetuximab and panitumumab for treatment of KRAS wild-type colorectal cancer [22,23] and the tyrosine kinase inhibitors erlotinib or gefitinib for non-small-cell lung cancer (NSCLC) [23].Recent Phase III RCTs have demonstrated some efficacy in the advanced or metastatic setting in selected patients, measured by progression-free survival (PFS) without any overall survival (OS) benefit. For example, cetuximab or panitumumab added to chemotherapy has improved PFS in KRAS wild-type-only metastatic colorectal cancer, and gefitinib added to chemotherapy improved NSCLC in a small proportion of patients with EGF receptor mutations [20]. This absence of OS benefit, even in genotype-based selection of patients, raises serious questions and concerns regarding whether the current-generation biologic agents will have the capacity to improve long-term survival and cure rates in the adjuvant setting. Trastuzumab provided an OS benefit for HER2-positive metastatic breast cancer and gastric cancer and in an adjuvant setting for breast cancer represents an isolated success. However, there is scepticism, since the net response rate of trastuzumab is approximately 10%, and longer follow-up is needed to conclude whether this monoclonal antibody can provide a cure or if it only has a recurrence-delaying effect.Limited efficacy of targeted drugs drives current research towards understanding drugs resistanceIdentifying the causes of treatment failure and highlighting the molecular mechanisms underlying nonresponsiveness to biologically targeted agents is fundamental for innovation design of the next generation of more effective biologic agents. What are the future perspectives?Cancer complexity & heterogeneityEmerging evidence reveals that the landscape of mutations and deregulated signaling pathways underlying cancer development, progression and metastasis of solid cancers is much more complicated than we imagined. Beyond the known point mutations, such as SNPs, genomic rearrangements and copy number changes are also involved in cancer, and should be explored [4,5,24]. Although the costs for full-genome sequence may drop to approximately US$1000 in the next few years, allowing thousands of cancer genomes to be completely sequenced, major challenges raise uncertainty. The discrimination between causal (driver) and noncausal (passengers) mutations still remains a challenge. However, the next big problem will be to explore and understand the functional role of mutations in the nonprotein-coding genome [4,5,24]. An even greater problem is how to understand the complex gene–gene, protein–protein, gene–environment and intratumoral cell–cell interactions in a timely dynamic process. It is thought that the ultimate oncological outcome, namely tumorigenesis or metastatic recurrence, is driven by complex molecular networks rather than a simple linear relationship between genetic alterations and phenotype [7,8,25,26].Cancer genome sequencingAt the end of the first postgenome decade, we are now facing an explosion in DNA sequencing technology. As the costs drop dramatically and the sequencing data quality is improved, 24 complete sequences of the human genome have been published and close to 200 unpublished ones have finished [3]. At least three fully sequenced cancer genomes, including breast, lung and melanoma cancer, have been published [3–5]. All these data consistently change our understanding of the genetic background and molecular mechanisms underlying malignant disease. Cancer is much more complex and heterogeneous than we have supposed [27]. A huge number of mutations are involved in tumorigenesis and metastasis [24], and it is likely that, in most cases, complex gene–gene, gene–environment and intratumoral cell–cell interactions drive the oncological outcome, rather than a simple linear genotype–phenotype relationship [28]. Although Collins [13] and Venter [14] agree that this genomic revolution has not yet changed medical practice, it is important to note that the new genomics-based current knowledge shapes more rational innovation strategies to successfully prevent and treat cancer in the future.Both genotype and phenotype complete data are crucial in the effort to predict risk of recurrence and survival. Several studies have already identified a large number of mutations and genes involved in cancer development and metastasis. Using cheaper and refined NGS technology, it is expected that, in the next decade, the catalogue of driver mutations, including point mutations, rearrangements and copy-number changes, may be completed, at least for major cancers. The importance of phenotype data is emphasized by Venter [14], who believes that more powerful computers will be required to consider the tremendous number of high-quality clinical, pathological, therapeutic and follow-up data (phenotype) that should be integrated into complex network modeling.However, the understanding of the nonlinear complex relationship between genotypes and phenotypes is a major problem. Yet rapid progress and collaboration between researchers in biomedical and mathematical sciences may overcome current challenges. Bionetwork modeling represents one of the most fascinating fields aiming towards a genotype–phenotype-based personalized medicine [11]. Efforts are underway to integrate genotyping and molecular data into molecular network modeling to predict outcomes [7,8]. Biological systems approaches shape a new way to understand complex biological systems, such as individual tumors, hosts and environments [27–33]. The goal is to link genomics data with clinical data for understanding why some patients respond to therapy and are cured whereas others do not respond to therapy, experiencing fatal metastatic recurrence.ConclusionTo improve OS in a metastatic setting, and cure rates in the adjuvant setting, a new generation of targeted drugs should be added to modern systemic chemotherapy. Selection of patients based on novel biomarkers is also crucial for improving oncological outcomes. For both drug and biomarker development, NGS-based completion of driver mutations and cancer biological systems approaches provide the most rational promises. The time required for translating this innovation into clinical oncological practice is hard to predict, given the multiple challenges.Future perspectiveCurrent state-of-the-art treatment of cancer has been developed by exciting conventional single-gene molecular and cancer biology research and validated by large-scale randomized clinical trials. This standardized multimodal treatment consisted of complete tumor resection (R0) surgery, adjuvant radiotherapy and systemic chemotherapy, and recently, targeted therapy has improved survival and reduced death rates from cancer. However, treatment failures and mortality rates still remain high, even in high-income countries, as demonstrated by the current cancer facts and statistics data in the USA. There is a need for developing and validating novel robust biomarkers in order to tailor a combination of available cytotoxic and new biologic agents. In relation to such an effective and safe treatment, the latest genome sequencing technology provides exciting perspectives for an in-depth understanding of cancer initiation, progression and metastasis. This NGS can reveal most or even all genetic variants underlying cancer. Assessing the causal mutations involved in cancer has opened new directions for the development of robust biomarkers and more active biotherapeutics. However, beyond cancer genome sequencing, a lot of challenges should be overcome, such as how to improve our understanding of genetic regulation, intracellular signalling pathway networks and biological systems interactions, in order to achieve more effective and less toxic therapeutics.Financial & competing interests disclosureThe authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. 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This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.No writing assistance was utilized in the production of this manuscript.PDF download