The most obvious source of dark matter is in Epi-driver genes. Human tumors contain large numbers of epigenetic changes affecting DNA or chromatin proteins. For example, a recent study of colorectal cancers showed that more than 10% of the protein-coding genes were differentially methylated when compared with normal colorectal epithelial cells (85). Some of these changes (i.e., those in Epi-driver genes) are likely to provide a selective growth advantage (86, 87). For example, epigenetic silencing of CDK2NA and MLH1 is much more common than mutational inactivation of either of these two well-recognized driver genes (85) However, there is a critical difference between a genetic and an epigenetic change in a gene. Unlike the sequence of a gene in a given individual, methylation is plastic, varying with cell type, developmental stage, and patient age (21). The methylation state of the normal precursor cells that initiate tumorigenesis is unknown; these cells, such as normal stem cells, may represent only a tiny fraction of the cells in a normal organ. This plasticity also means that methylation can change under microenvironmental cues, such as those associated with low nutrient concentrations or abnormal cell contacts. It is therefore difficult to know whether specific epigenetic changes observed in cancer cells reflect, rather than contribute to, the neoplastic state. Criteria for distinguishing epigenetic changes that exert a selective growth advantage from those that do not (passenger epigenetic changes) have not yet been formulated. Given that Epi-driver genes are likely to compose a major component of the dark matter, further research on this topic is essential (58).
Genetic Heterogeneity
The mutations depicted in Fig. 1 are clonal; that is, they are present in the majority of the neoplastic cells in the tumors. But additional, subclonal (i.e., heterogeneous within the tumor) mutations are important for understanding tumor evolution. Four types of genetic heterogeneity are relevant to tumorigenesis (Fig. 6):
Fig. 6
Four types of genetic heterogeneity in tumors, illustrated by a primary tumor in the pancreas and its metastatic lesions in the liver
Mutations introduced during primary tumor cell growth result in clonal heterogeneity. At the top left, a typical tumor is represented by cells with a large fraction of the total mutations (founder cells) from which subclones are derived. The differently colored regions in the subclones represent stages of evolution within a subclone. (A) Intratumoral: heterogeneity among the cells of the primary tumor. (B) Intermetastatic: heterogeneity among different metastatic lesions in the same patient. In the case illustrated here, each metastasis was derived from a different subclone. (C) Intrametastatic: heterogeneity among the cells of each metastasis develops as the metastases grow. (D) Interpatient: heterogeneity among the tumors of different patients. The mutations in the founder cells of the tumors of these two patients are almost completely distinct (see text).
Intratumoral: heterogeneity among the cells of one tumor. This type of heterogeneity has been recognized for decades. For example, it is rare to see a cytogenetic study of a solid tumor in which all of the tumor cells display the same karyotype (88). The same phenomenon has been noted for individual genes [e.g., (89)] and more recently has been observed throughout the genome (16, 90–96). This kind of heterogeneity must exist: Every time a normal (or tumor) cell divides, it acquires a few mutations, and the number of mutations that distinguish any two cells simply marks the time from their last common ancestor (their founder cell). Cells at the opposite ends of large tumors will be spatially distinct and, in general, will display more differences than neighboring cells (16). This phenomenon is analogous to speciation, wherein organisms on different islands are more likely to diverge from one another than are organisms on the same island.
In studies that have evaluated intratumoral heterogeneity by genome-wide sequencing, the majority of somatic mutations are present in all tumor cells. These mutations form the trunk of the somatic evolutionary tree. What is the importance of the mutations in the branches (i.e., those that are not shared by all tumor cells)? From a medical perspective, these mutations are often meaningless because the primary tumors are surgically removed. How much heterogeneity existed in the various branches before surgery is not important. However, this heterogeneity provides the seeds for intermetastastic heterogeneity, which is of great clinical importance.
Intermetastatic: heterogeneity among different metastatic lesions of the same patient. The vast majority of cancer patients die because their tumors were not removed before metastasis to surgically inaccessible sites, such as the liver, brain, lung, or bone. Patients who relapse with a single metastatic lesion can often still be cured by surgery or radiotherapy, but single metastases are the exception rather than the rule. A typical patient on a clinical trial has a dozen or more metastatic lesions large enough to be visualized by imaging, and many more that are smaller. If each of the metastatic lesions in a single patient was founded by a cell with a very different genetic constitution, then chemotherapeutic cures would be nearly impossible to achieve: Eradicating a subset of the metastatic lesions in a patient will not be adequate for long-term survival.
How much heterogeneity is there among different metastatic lesions? In short, a lot. It is not uncommon for one metastatic lesion to have 20 clonal genetic alterations not shared by other metastases in the same patient (16, 97). Because they are clonal, these mutations occurred in the founder cell of the metastasis; that is, the cell that escaped from the primary tumor and multiplied to form the metastasis. The founder cell for each metastasis is present in different, geographically distinct areas of the primary tumors, as expected (16).
This potentially disastrous situation is tempered by the fact that the heterogeneity appears largely confined to passenger gene mutations. In most of the studies documenting heterogeneity in malignancies, the Mut-driver genes are present in the trunks of the trees, though exceptions have been noted (95). These findings are consistent with the idea, discussed above, that the genetic alterations required for metastasis were present (i.e., selected for) before metastasis actually occurred. The data are also consistent with the observation that in patients responsive to targeted agents, the response is often seen in all metastatic lesions rather than just a small subset (98).
Intrametastatic: heterogeneity among the cells of an individual metastasis. Each metastasis is established by a single cell (or small group of cells) with a set of founder mutations. As it grows, the metastasis acquires new mutations with each cell division. Though the founder mutations may make the lesion susceptible to antitumor agents, the new mutations provide the seeds for drug resistance. Unlike primary tumors, the metastatic lesions generally cannot be removed by surgery and must be treated with systemic therapies. Patients with complete responses to targeted therapies invariably relapse. Most of the initial lesions generally recur, and the time frame at which they recur is notably similar. This time course can be explained by the presence of resistance mutations that existed within each metastasis before the onset of the targeted therapy (99–102). Calculations show that any metastatic lesion of a size visible on medical imaging has thousands of cells (among the billions present) that are already resistant to virtually any drug that can be imagined (99, 101, 102). Thus, recurrence is simply a matter of time, entirely predictable on the basis of known mutation frequencies and tumor cell growth rates. This "fait accompli" can be circumvented, in principle, by treatment with multiple agents, as it is unlikely that a single tumor cell will be resistant to multiple drugs that act on different targets.
Interpatient: heterogeneity among the tumors of different patients. This type of heterogeneity has been observed by every oncologist; no two cancer patients have identical clinical courses, with or without therapy. Some of these differences could be related to host factors, such as germline variants that determine drug half-life or vascular permeability to drugs or cells, and some could be related to nongenetic factors (103). However, much of this interpatient heterogeneity is probably related to somatic mutations within tumors. Though several dozen somatic mutations may be present in the breast cancers from two patients, only a small number are in the same genes, and in the vast majority of cases, these are the Mut-driver genes (1, 104, 105). Even in these driver genes, the actual mutations are often different. Mutations altering different domains of a protein would certainly not be expected to have identical effects on cellular properties, as experimentally confirmed (106). Though it may seem that different mutations in adjacent codons would have identical effects, detailed studies of large numbers of patients have shown that this need not be the case. For example, a Gly12→Asp12 (G12D) mutation of KRAS does not have the same clinical implications as a G13D mutation of the same gene (107). Interpatient heterogeneity has always been one of the major obstacles to designing uniformly effective treatments for cancer. Efforts to individualize treatments based on knowledge of the genomes of cancer patients are largely based on an appreciation of this heterogeneity.
Signaling Pathways in Tumors
The immense complexity of cancer genomes that could be inferred from the data described above is somewhat misleading. After all, even advanced tumors are not completely out of control, as evidenced by the dramatic responses to agents that target mutant BRAF in melanomas (108) or mutant ALK in lung cancers (109). Albeit transient, these responses mean that interference with even a single mutant gene product is sufficient to stop cancer in its tracks, at least transiently. How can the genomic complexity of cancer be reconciled with these clinical observations?
Two concepts bear on this point. The first, mentioned above, is that >99.9% of the alterations in tumors (including point mutations, copy-number alterations, translocations, and epigenetic changes distributed throughout the genome, not just in the coding regions) are immaterial to neoplasia. They are simply passenger changes that mark the time that has elapsed between successive clonal expansions. Normal cells also undergo genetic alterations as they divide, both at the nucleotide and chromosomal levels. However, normal cells are programmed to undergo cell death in response to such alterations, perhaps as a protective mechanism against cancer. In contrast, cancer cells have evolved to tolerate genome complexity by acquiring mutations in genes such as TP53 (110). Thus, genomic complexity is, in part, the result of cancer, rather than the cause.
To appreciate the second concept, one must take the 30,000-foot view. A jungle might look chaotic at ground level, but the aerial view shows a clear order, with all the animals gathering at the streams at certain points in the day, and all the streams converging at a river. There is order in cancer, too. Mutations in all of the 138 driver genes listed in table S2 do one thing: cause a selective growth advantage, either directly or indirectly. Moreover, there appears to be only a limited number of cellular signaling pathways through which a growth advantage can be incurred (Fig. 7 and table S5).
All of the known driver genes can be classified into one or more of 12 pathways (Fig. 7). The discovery of the molecular components of these pathways is one of the greatest achievements of biomedical research, a tribute to investigators working in fields that encompass biochemistry, cell biology, and development, as well as cancer. These pathways can themselves be further organized into three core cellular processes:
Cell fate: Numerous studies have demonstrated the opposing relationship between cell division and differentiation, the arbiters of cell fate. Dividing cells that are responsible for populating normal tissues (stem cells) do not differentiate, and vice versa. Regenerative medicine is based on this distinction, predicated on ways to get differentiated cells to de-differentiate into stem cells, then forcing the stem cells to differentiate into useful cell types for transplantation back into the patient. Many of the genetic alterations in cancer abrogate the precise balance between differentiation and division, favoring the latter. This causes a selective growth advantage, because differentiating cells eventually die or become quiescent. Pathways that function through this process include APC, HH, and NOTCH, all of which are well known to control cell fate in organisms ranging from worms to mammals (111). Genes encoding chromatin-modifying enzymes can also be included in this category. In normal development, the heritable switch from division to differentiation is not determined by mutation, as it is in cancer, but rather by epigenetic alterations affecting DNA and chromatin proteins. What better way to subvert this normal mechanism for controlling tissue architecture than to debilitate the epigenetic modifying apparatus itself?
Cell survival: Though cancer cells divide abnormally because of cell-autonomous alterations, such as those controlling cell fate, their surrounding stromal cells are perfectly normal and do not keep pace. The most obvious ramification of this asymmetry is the abnormal vasculature of tumors. As opposed to the well-ordered network of arteries, veins, and lymphatics that control nutrient concentrations in normal tissues, the vascular system in cancers is tortuous and lacks uniformity of structure (112, 113). Normal cells are always within 100 μm of a capillary, but this is not true for cancer cells (114). As a result, a cancer cell acquiring a mutation that allows it to proliferate under limiting nutrient concentrations will have a selective growth advantage, thriving in environments in which its sister cells cannot. Mutations of this sort occur, for example, in the EGFR, HER2, FGFR2, PDGFR, TGFbR2, MET, KIT, RAS, RAF, PIK3CA, and PTEN genes (table S2A). Some of these genes encode receptors for the growth factors themselves, whereas others relay the signal from the growth factor to the interior of the cell, stimulating growth when activated (115, 116). For instance, mutations in KRAS or BRAF genes confer on cancer cells the ability to grow in glucose concentrations that are lower than those required for the growth of normal cells or of cancer cells that do not have mutations in these genes (117, 118). Progression through the cell cycle (and its antithesis, apoptosis) can be directly controlled by intracellular metabolites, and driver genes that directly regulate the cell cycle or apoptosis, such as CDKN2A, MYC, and BCL2, are often mutated in cancers. Another gene whose mutations enhance cell survival is VHL, the product of which stimulates angiogenesis through the secretion of vascular endothelial growth factor. What better way to provision growth factors to a rogue tumor than to lure the unsuspecting vasculature to its hideout?
Genome maintenance: As a result of the exotic microenvironments in which they reside, cancer cells are exposed to a variety of toxic substances, such as reactive oxygen species. Even without microenvironmental poisons, cells make mistakes while replicating their DNA or during division (119, 120), and checkpoints exist to either slow down such cells or make them commit suicide (apoptosis) under such circumstances (110, 121, 122). Although it is good for the organism to remove these damaged cells, tumor cells that can survive the damage will, by definition, have a selective growth advantage. Therefore, it is not surprising that genes whose mutations abrogate these checkpoints, such as TP53 and ATM, are mutated in cancers (123). Defects in these genes can also indirectly confer a selective growth advantage by allowing cells that have a gross chromosomal change favoring growth, such as a translocation or an extra chromosome, to survive and divide. Analogously, genes that control point mutation rates, such as MLH1 or MSH2, are mutated in cancers (table S2A) or in the germ line of patients predisposed to cancers (table S4) because they accelerate the acquisition of mutations that function through processes that regulate cell fate or survival. What better way to promote cancer than by increasing the rate of occurrence of the mutations that drive the process?
Because the protein products of genes regulating cell fate, cell survival, and genome maintenance often interact with one another, the pathways within them overlap; they are not as discrete as might be inferred from the description above. However, grouping genes into pathways makes perfect sense from a genetics standpoint. Given that cancer is a genetic disease, the principles of genetics should apply to its pathogenesis. When performing a conventional mutagenesis screen in bacteria, yeast, fruit flies, or worms, one expects to discover mutations in several different genes that confer similar phenotypes. The products of these genes often interact with one another and define a biochemical or developmental pathway. Therefore, it should not be surprising that several different genes can result in the same selective growth advantage for cancer cells and that the products of these genes interact. The analogy between cancer pathways and biochemical or developmental pathways in other organisms goes even deeper: The vast majority of our knowledge of the function of driver genes has been derived from the study of the pathways through which their homologs work in nonhuman organisms. Though the functions are not identical to those in human cells, they are highly related and have provided the starting point for analogous studies in human cells.
Recognition of these pathways also has important ramifications for our ability to understand interpatient heterogeneity. One lung cancer might have an activating mutation in a receptor for a stimulatory growth factor, making it able to grow in low concentrations of epidermal growth factor (EGF). A second lung cancer might have an activating mutation in KRAS, whose protein product normally transmits the signal from the epidermal growth factor receptor (EGFR) to other cell signaling molecules. A third lung cancer might have an inactivating mutation in NF1, a regulatory protein that normally inactivates the KRAS protein. Finally, a fourth lung cancer might have a mutation in BRAF, which transmits the signal from KRAS to downstream kinases (Fig. 8). One would predict that mutations in the various components of a single pathway would be mutually exclusive-that is, not occurring in the same tumor-and this has been experimentally confirmed (124, 125). Apart from being intellectually satisfying, knowledge of these pathways has implications for cancer therapy, as discussed in the next section.
A Perspective on Genome-Based Medicine in Oncology
Opportunities
Though cancer genome sequencing is a relatively new endeavor, it has already had an impact on the clinical care of cancer patients. The recognition that certain tumors contain activating mutations in driver genes encoding protein kinases has led to the development of small-molecule inhibitor drugs targeting those kinases.
Representative examples of this type of genome-based medicine include the use of EGFR kinase inhibitors to treat cancers with EGFR gene mutations (126), the aforementioned ana-plastic lymphoma kinase (ALK) inhibitors to treat cancers with ALK gene translocations (109), and specific inhibitors of mutant BRAF to treat cancers with BRAF mutations (108). Before instituting treatment with such agents, it is imperative to determine whether the cancer harbors the mutations that the drug targets. Only a small fraction of lung cancer patients have EGFR gene mutations or ALK gene translocations, and only these patients will respond to the drugs. Treating lung cancer patients without these particular genetic alterations would be detrimental, as such patients would develop the toxic side effects of the drugs while their tumors progressed.
A second type of genome-based medicine focuses on the side effects and metabolism of the therapeutic agents, rather than the genetic alterations they target. At present, the dose of cancer drugs given to patients is based on the patients' size (body weight or surface area). But the therapeutic ratio of cancer drugs (ratio of the concentration that causes side effects to the concentration required to kill tumor cells) is generally low, particularly for conventional (nontargeted) therapeutic agents. Small changes in circulating concentrations of these drugs can make the difference between substantial tumor regression and intolerable side effects. Interrogation of the germline status of the genes encoding drug-metabolizing enzymes could substantially improve the outcomes of treatment by informing drug dosing (127). Optimally, this genome interrogation would be accompanied by pharmacokinetic measurements of drug concentrations in each patient. The additional cost of such analyses would be small compared with the exorbitant costs of new cancer therapies-for recently approved drugs, the cost is estimated to be $200,000 to $300,000 per quality life year produced (128).
Challenges
One challenge of genome-based medicine in oncology is already apparent from the opportunities described above: All of the clinically approved drugs that target the products of genetically altered genes are directed against kinases. One reason for this is that kinases are relatively easy to target with small molecules and have been extensively studied at the biochemical, structural, and physiologic levels (129). But another reason has far deeper ramifications. The vast majority of drugs on the market today, for cancer or other diseases, inhibit the actions of their protein targets. This inhibition occurs because the drugs interfere with the protein's enzymatic activity (such as the phosphorylation catalyzed by kinases) or with the binding of the protein to a small ligand (such as with G protein–coupled receptors). Only 31 of the oncogenes listed in tables S2 and S3 have enzymatic activities that are targetable in this manner. Many others participate in protein complexes, involving large interfaces and numerous weak interactions. Inhibiting the function of such proteins with small drugs is notoriously difficult because small compounds can only inhibit one of these interactions (130, 131).
Though one can at least imagine the development of drugs that inhibit nonenzymatic protein functions, the second challenge evident from table S2 poses even greater difficulties: A large fraction of the Mut-driver genes encode tumor suppressors. Drugs generally interfere with protein function; they cannot, in general, replace the function of defective genes such as those resulting from mutations in tumor suppressor genes. Unfortunately, tumor suppressor gene–inactivating mutations predominate over oncogene-activating mutations in the most common solid tumors: Few individual tumors contain more than one oncogene mutation (Fig. 5).
The relatively small number of oncogene mutations in tumors is important in light of the intrametastatic heterogeneity described earlier. To circumvent the inevitable development of resistance to targeted therapies, it will likely be necessary to treat patients with two or more drugs. The probability that a single cancer cell within a large metastatic lesion will be resistant to two agents that target two independent pathways is exponentially less than the probability that the cell will be resistant to a single agent. However, if the cancer cell does not contain more than one targetable genetic alteration (i.e., an oncogene mutation), then this combination strategy is not feasible.
Given the paucity of oncogene alterations in common solid tumors and these principles, can targeted therapeutic approaches ever be expected to induce long-term remissions, even cures, rather than the short-term remissions now being achieved? The saviors are pathways; every tumor suppressor gene inactivation is expected to result in the activation of some growth-promoting signal downstream of the pathway. An example is provided by PTEN mutations: Inactivation of the tumor suppressor gene PTEN results in activation of the AKT kinase (Fig. 8). Similarly, inactivation of the tumor suppressor gene CDKN2A results in activation of kinases, such as cyclin-dependent kinase 4, that promote cell cycle traverse (132). Furthermore, inactivation of tumor suppressor gene APC results in constitutive activity of oncogenes such as CTNNB1 and CMYC (133–135).
We believe that greater knowledge of these pathways and the ways in which they function is the most pressing need in basic cancer research. Successful research on this topic should allow the development of agents that target, albeit indirectly, defective tumor suppressor genes. Indeed, there are already examples of such indirect targeting. Inactivating mutations of the tumor suppressor genes BRCA1 or BRCA2 lead to activation of downstream pathways required to repair DNA damage in the absence of BRCA function. Thus, cancer cells with defects in BRCA1 or BRCA2 are more susceptible to DNA damaging agents or to drugs that inhibit enzymes that facilitate the repair of DNA damage such as PARP [poly(adenosine diphosphate–ribose) polymerase] (136). PARP inhibitors have shown encouraging results in clinical trials when used in patients whose tumors have inactivating mutations of BRCA genes (137).
Further progress in this area will require more detailed information about the signaling pathways through which cancer genes function in human cancer cells, as well as in model organisms. One of the lessons of molecular biology over the past two decades is that pathway functions are different, depending on the organism, cell type, and precise genetic alterations in that cell (138). A pertinent example of this principle is provided by results of treatment with drugs inhibiting mutant BRAF kinase activity. In the majority of patients with melanomas harboring (V600E; V, Val; E, Glu) mutations in the BRAF gene, these drugs induce dramatic (though transient) remissions (108). But the same drugs have no therapeutic effect in colorectal cancer patients harboring the identical BRAF mutations (139). This observation has been attributed to the expression of EGFR, which occurs in some colorectal cancers but not in melanoma and is thought to circumvent the growth-inhibitory effects of the BRAF inhibitors. With this example in mind, no one should be surprised that a new drug that works well in an engineered tumor in mice fails in human trials; the organism is different, the cell type is usually different, and the precise genetic constitutions are always different. The converse of this statement-that a drug that fails in animal trials will not necessarily fail in human trials-has important practical consequences. In our view, if the biochemical and conceptual bases for a drug's actions are solid and the drug is shown to be safe in animals, then a human trial may be warranted, even if it does not shrink tumors in mice.
Genome-Based Medicines of the Future
Cancer genomes can also be exploited for the development of more effective immunotherapies. As noted above, typical solid tumors contain 30 to 70 mutations that alter the amino acid sequences of the proteins encoded by the affected genes. Each of these alterations is foreign to the immune system, as none have been encountered during embryonic or postnatal life. Therefore, these alterations, in principle, provide a "holy grail" for tumor immunology: truly tumor-specific antigens. These antigens could be incorporated into any of the numerous platforms that already exist for the immunotherapy of cancer. These include administration of vaccines containing the mutant peptide, viruses encoding the mutant peptides on their surfaces, dendritic cells presenting the mutated peptide, and antibodies or T cells with reactivity directed against the mutant peptides (140).
To realize these sorts of therapeutics, several conditions must be met. First, the mutant protein must be expressed. As cancer cells generally express about half of the proteins that are encoded by the human genome (141), this condition is not limiting. Second, as most proteins affected by mutations are intracellular, these mutations will not be visible to the immune system unless the mutant residue is presented in the context of a human leukocyte antigen (HLA) protein. Based on in silico analyses of binding affinities, it has been estimated that a typical breast or colorectal cancer contains 7 to 10 mutant proteins that can bind to an individual patient's HLA type (142). These theoretical predictions have recently gained experimental support. Studies of mouse tumors have identified mutant genes and shown that the corresponding peptides can induce antitumor immunity when administered as vaccines (143). Moreover, clinical trials of brain cancer patients immunized against a mutant peptide have yielded encouraging results (144).
As with all cancer therapies that are attractive in concept, obstacles abound in practice. If a tumor expresses a mutant protein that is recognizable as foreign, why has the host immune system not eradicated that tumor already? Indeed, immunoediting in cancers has been shown to exist, resulting in the down-regulation or absence of mutant epitopes that should have, and perhaps did, elicit an immune response during tumor development (145, 146). Additionally, tumors can lose immunogenicity through a variety of genetic alterations, thereby precluding the presentation of epitopes that would otherwise be recognized as foreign (147). Though these theoretical limitations are disheartening, recent studies on immune regulation in humans portend cautious optimism (148, 149).
Other Ways to Reduce Morbidity and Mortality Through Knowledge of Cancer Genomics
When we think about eradicating cancer, we generally think about curing advanced cases-those that cannot be cured by surgery alone because they have already metastasized. This is a curious way of thinking about this disease. When we think of cardiovascular or infectious diseases, we first consider ways to prevent them rather than drugs to cure their most advanced forms. Today, we are in no better position to cure polio or massive myocardial infarctions than we were a thousand years ago. But we can prevent these diseases entirely (vaccines), reduce incidence (dietary changes, statins), or mitigate severity (stents, thrombolytic agents) and thereby make a major impact on morbidity and mortality.
This focus on curing advanced cancers might have been reasonable 50 years ago, when the molecular pathogenesis of cancers was mysterious and when chemotherapeutic agents against advanced cancers were showing promise. But this mindset is no longer acceptable. We now know precisely what causes cancer: a sequential series of alterations in well-defined genes that alter the function of a limited number of pathways. Moreover, we know that this process takes decades to develop and that the incurable stage, metastasis, occurs only a few years before death. In other words, of the one million people that will die from cancer this year, the vast majority will die only because their cancers were not detected in the first 90% of the cancers' lifetimes, when they were amenable to the surgeons' scalpel.
This new knowledge of cancer (Box 2) has reinvigorated the search for cures for advanced cancers, but has not yet permeated other fields of applied cancer research. A common and limited set of driver genes and pathways is responsible for most common forms of cancer (table S2); these genes and pathways offer distinct potential for early diagnosis. The genes themselves, the proteins encoded by these genes, and the end products of their pathways are, in principle, detectable in many ways, including analyses of relevant body fluids, such as urine for genitourinary cancers, sputum for lung cancers, and stool for gastrointestinal cancers (150). Equally exciting are the possibilities afforded by molecular imaging, which not only indicate the presence of a cancer but also reveal its precise location and extent. Additionally, research into the relationship between particular environmental influences (diet and lifestyle) and the genetic alterations in cancer is sparse, despite its potential for preventative measures.
Box 2
Highlights
Most human cancers are caused by two to eight sequential alterations that develop over the course of 20 to 30 years.
Each of these alterations directly or indirectly increases the ratio of cell birth to cell death; that is, each alteration causes a selective growth advantage to the cell in which it resides.
The evidence to date suggests that there are ~140 genes whose intragenic mutations contribute to cancer (so-called Mut-driver genes). There are probably other genes (Epi-driver genes) that are altered by epigenetic mechanisms and cause a selective growth advantage, but the definitive identification of these genes has been challenging.
The known driver genes function through a dozen signaling pathways that regulate three core cellular processes: cell fate determination, cell survival, and genome maintenance.
Every individual tumor, even of the same histopathologic subtype as another tumor, is distinct with respect to its genetic alterations, but the pathways affected in different tumors are similar.
Genetic heterogeneity among the cells of an individual tumor always exists and can impact the response to therapeutics.
In the future, the most appropriate management plan for a patient with cancer will be informed by an assessment of the components of the patient's germline genome and the genome of his or her tumor.
The information from cancer genome studies can also be exploited to improve methods for prevention and early detection of cancer, which will be essential to reduce cancer morbidity and mortality.
The reasons that society invests so much more in research on cures for advanced cancers than on prevention or early detection are complex. Economic issues play a part: New drugs are far more lucrative for industry than new tests, and large individual costs for treating patients with advanced disease have become acceptable, even in developing countries (151). From a technical standpoint, the development of new and improved methods for early detection and prevention will not be easy, but there is no reason to assume that it will be more difficult than the development of new therapies aimed at treating widely metastatic disease.
Our point is not that strenuous efforts to develop new therapies for advanced cancer patients should be abandoned. These will always be required, no matter our arsenal of early detection or preventative measures. Instead, we are suggesting that "plan A" should be prevention and early detection, and "plan B" (therapy for advanced cancers) should be necessary only when plan A fails. To make plan A viable, government and philanthropic organizations must dedicate a much greater fraction of their resources to this cause, with long-term considerations in mind. We believe that cancer deaths can be reduced by more than 75% in the coming decades (152), but that this reduction will only come about if greater efforts are made toward early detection and prevention.
Acknowledgments
We thank M. Nowak and I. Bozic for critical reading of the manuscript, S. Gabelli for assisting with the production of Fig. 8, and A. Dixon, V. Ferranta, and E. Cook for artwork. This work was supported by The Virginia and D.K. Ludwig Fund for Cancer Research; The Lustgarten Foundation for Pancreatic Cancer Research; and NIH grants CA 43460, CA 47345, CA 62924, and CA 121113. All authors are Founding Scientific Advisors of Personal Genome Diagnostics (PGDx), a company focused on the identification of genetic alterations in human cancer for diagnostic and therapeutic purposes. All authors are also members of the Scientific Advisory Board of Inostics, a company that is developing technologies for the molecular diagnosis of cancer. All authors own stock in PGDx and Inostics. The terms of these arrangements are being managed by Johns Hopkins University, in accordance with their conflict-of-interest policies.
