Mark W. Onaitis
David H. Harpole
Over the past decades, it has become recognized that cancer is a genetic disease. Therefore, the biology of lung and esophageal cancer must be considered from the perspective of genetic changes in the epithelial cells of these organs. In this chapter, we will highlight many of these known individual genetic changes as well as groups of genetic changes.
Oncogenes are genes that lead to increased proliferative capacity of cells. Because they are activating mutations, mutation or overexpression of only one of two normal protooncogenes per cell is required for transformation. Oncogenes may lead to increased proliferation through a variety of mechanisms, including augmented growth rate, increased mitotic rate, and decreased rate of apoptosis.
Ras is perhaps the best-known oncogene. The Ras family of proteins consists of three members, HRas, NRas, and KRas, the last of which is implicated in 30% to 40% of human lung adenocarcinoma.1Wild-type Ras is a membrane-associated G protein that serves as a link between tyrosine kinase receptors at the membrane and cytoplasmic second messenger molecules. These second messenger molecules participate in a proliferative signaling cascade that activates mitogen-activated protein kinase (MAPK) resulting in increased proliferation. This proliferation is caused by mutations in KRas codons 12, 13, and 61, all of which ablate KRas’ GTPase activity and constitutively activate KRas.
In both individual studies and a meta-analysis, the presence of mutated KRas in resected lung cancer portends a poor prognosis.2-4 Although the presence of these mutations may identify aggressive tumors, a portion of the prognostic impact may be explained by poor response to adjuvant chemotherapy. In the National Cancer Institute of Canada Clinical Trials Group (NCIC-CTG) North American intergroup study, the JBR.10 trial, the subgroup of patients with Ras mutations did not experience a survival advantage.5 Because localization of Ras to the membrane is dependent upon farnesylation, farnesyltransferase inhibitors may be more effective in patients with Ras mutation.
In addition to mutation of Ras, control of normal Ras protein levels may be important in lung cancer tumorigenesis. Recently, Ras was found to be an important target of the let-7 microRNA family. MicroRNAs are 22 nucleotide RNA molecules that negatively regulate gene expression by silencing messenger RNAs or by targeting microRNAs for destruction. Lung tumors exhibit lower levels of let-7 than normal lung,6 and low expression levels of let-7 have been demonstrated as predictive of poor survival.7-9
Interestingly, oncogenic Ras mutations occur almost exclusively in adenocarcinomas of smokers.10,11 This may relate to the effect of benzo-alpha-pyrenes on the bronchial epithelium.12 Perhaps smoking cessation efforts will eventually lead to fewer Ras-positive tumors in the future.
In esophageal cancer, Ras mutations have also been reported in patients with high-grade dysplasia and adenocarcinoma.9 These mutations are rarely found in Barrett metaplasia.
Epidermal Growth Factor Receptor (EGFR)
Unlike Ras, EGFR mutations most commonly occur in lung tumors of nonsmokers. They virtually never occur in the presence of Ras mutation and are most commonly present in adenocarcinomas of East Asian females.13,14 Along with Her2, Her3, and Her4, EGFR receptors comprise one of four types of ErbB receptors. Ligands of EGFR are varied, including both epidermal growth factor and transforming growth factor alpha.15 Ligand binding of the receptor leads to dimerization, phosphorylation, and activation of signaling pathways leading to proliferation.
Due to the availability of the EGFR-specific tyrosine kinase inhibitors, EGFR mutation has received much recent scrutiny. The majority of these mutations occur as either in-frame deletions of exon 19 or missense mutation in exon 21.13,16-21 Epithelial cells with mutant EGFR probably become physiologically dependent on the gene’s continued activity for maintenance of the transformed phenotypes.22 AsFigure 7–1 reveals, patients with tumors expressing EGFR and Her2-neu may have poorer postoperative survival than those with one or neither positive.
Figure 7–1. Unpublished data from the Harpole laboratory demonstrating diminished survival in Stage I patients with tumors staining positive for both EGFR and Her2-neu.
In esophageal carcinoma, chromosome 7 (which contains EGFR) is frequently amplified in tumors that have metastasized to lymph nodes,23 and EGFR overexpression correlates with worse survival after induction treatment.24
A tumor suppressor is a gene whose absence allows neoplasia to progress. Because even a small amount of wild-type protein may suppress transformation, homozygous deletion of a tumor suppressor is thought necessary for oncogenesis. When a patient is heterozygous for a gene, the term loss of heterozygosity (LOH) is used to describe deletion or inactivation of the wild-type allele.
Perhaps the best-studied tumor suppressor gene is p53, which encodes a transcription factor with diverse biological functions, including the mediation of cell cycle arrest and cell death after DNA damage. The loss of wild-type (normal) p53 activity is the most common genetic abnormality in human cancer and can occur through allelic deletions or point mutations, or both, that result in amino acid substitutions that alter protein function. Abnormalities in p53 are also the most frequent genetic alterations in lung cancer, occurring in 90% of SCLCs and up to 60% of NSCLCs. These alterations primarily involve inactivating point mutations, but deletions, rearrangements, and splice mutations have also been described. As with Ras mutations, p53 mutations are more common in smokers: Denissenko and co-workers reported that benzo[a] pyrene, a major carcinogen in tobacco smoke, preferentially forms adducts at the guanine positions in p53 that are most frequently mutated in human lung cancer.25 In addition, Ahrendt and associates found that p53 mutations occur at a much higher frequency in lung cancers of patients with a history of significant alcohol and tobacco use.26
The prognostic significance of p53 abnormalities in lung cancer remains controversial. Since the half-life of mutant p53 protein is usually significantly longer than that of the wild-type protein, the detection of p53 by immunohistochemistry is considered a marker for p53 mutation, although Carbone and associates found that the concordance between positive p53 immunostaining and the presence of a p53 mutation was only 67%.27 Numerous studies have reported that p53 mutation or overexpression is predictive of poor prognosis, whereas others have found no association between p53 mutations and survival in either NSCLC or SCLC. Two recent meta-analyses concluded that the presence of p53 mutation or overexpression correlates with a poorer prognosis in patients with NSCLC.28,29 Data from the Harpole laboratory is in agreement with this (Figure 7–2).
Figure 7–2. Unpublished data from the Harpole laboratory revealing diminished survival in Stage I patients with Rb deficiency and p53 overexpression.
In esophageal cancer, p53 mutation is found in up to 80% of adenocarcinomas.30 LOH may also be important in risk stratification of patients with Barrett esophagus at risk for developing esophageal cancer.31
Cytogenetic studies have identified chromosomal region 9p21 as one of the most commonly affected loci in human cancers, including lung cancer. The p16 (INK4a, CDKN2A) gene, located at 9p21, has been characterized as a tumor suppressor gene based on the high frequency of p16 mutations and deletions present in a wide variety of human tumors and the presence of germline mutations in families with hereditary melanoma. The p16 protein is one of a family of cyclin-dependent kinase (cdk) inhibitors that regulate progression through the cell cycle by inactivating cdk4 or cdk6, thereby inhibiting the phosphorylation of Retinoblastoma 1 (RB1) by cyclin D:cdk4/6 complexes. Unphosphorylated Rb1 binds E2F with resultant cell cycle arrest at the G1/S boundary. Therefore, the loss of p16 function or the overexpression of cyclin D1 would have the same net effect as the loss of RB1 function: unregulated passage through the G1/S checkpoint with resultant neoplastic proliferation. At least one of these three abnormalities—loss of RB1, loss of p16, or overexpression of cyclin D1—occurs in most, if not all, human cancers, suggesting that dysregulation of the RB–cyclin D–cdk4/6–p16 pathway controlling the G1/S transition may be a necessary step during malignant transformation.
One of these cell cycle-altering pathways is active in over 90% of NSCLC tumors.32 Although p16 inactivation is common in all NSCLCs, the mechanism of inactivation may differ between smokers and nonsmokers, with deletions and mutations primarily responsible in the former and only promoter hypermethylation being noted in the latter.33 However, others have found hypermethylation of the gene in smokers.34
In esophageal cancer, alterations in p16 are common.35,36 As with p53, p16 alterations may portend higher risk of adenocarcinoma formation in Barrett’s patients.37,38
Inactivation of p16 may be associated with a poor outcome. Kratzke and colleagues and others have reported that the loss of p16 is associated with a poor prognosis,39 while Kinoshita and associates found that inactivation of p16 or RB1 was associated with an increased proliferative index in tumors lacking p53 activity.
GENOMICS AND PROTEOMICS
As technology has evolved and the human genome has been sequenced, the ability to screen samples for expression/mutation across large numbers of genes has become both possible and affordable. These techniques involve isolating either RNA (in the case of transcriptome profiling) or DNA (in the case of single nucleotide polymorphism [SNP] arrays), fluorescently labeling them, and hybridizing them to chips to which are immobilized short DNA sequences (probes) from thousands of genes of interest. After reading and analysis, an expression value for each probe is obtained. Commercially available chips now contain all known genes in the genome of humans and almost any other organism under study.
The vast amount of information obtained from these arrays has necessitated the explosion of the field of bioinformatics in that complex, computerized statistical algorithms have been developed to identify important significant differences between samples. In the case of the Affymetrix (www.affymetrix.com) human genome U133 2.0 Plus chips, expression data for over 54,000 probes is provided for each sample.
As these fields have advanced, these approaches have been applied to human lung cancer. Several groups including ours have demonstrated that squamous cell carcinoma and adenocarcinoma have markedly different transcriptome profiles.40-43 Within these broad histologic classes, these studies have also identified subgroups that have poor prognosis. These types of studies may eventually lead to personalized treatment.
In contrast to the transcriptome array studies discussed thus far, sequencing of the human genome has led to the accumulation of single nucleotide polymorphism data. These polymorphisms represent single base pair differences between individuals and may either cause disease (if the change causes differences in protein expression) or be used as markers of disease (if a SNP is very close to a gene contributing to a disease phenotype such that recombination happens between the gene and the SNP only rarely). Large SNP arrays are now commercially available. The protocol for their use is similar to that of transcriptome arrays except that genomic DNA is hybridized to the chips. Because this technology is relatively new, less lung cancer-specific data has been published. However, recent studies have demonstrated increased lung cancer risk with specific polymorphisms.44-47 As the technology becomes more affordable and easier to use, more of these studies will undoubtedly be published over the next several years. Because these studies identify genetic markers in genomic DNA which can be isolated and analyzed at any time from a blood sample, a myriad of ethical considerations will inevitably arise concerning testing of healthy people for increased lung cancer susceptibility.
Proteomics involves study of the set of proteins in a selected group of cells and tissue. Because the protein profile represents a snapshot of the activities of a cell at any given time, proteomic study is extremely powerful. However, because of the complexity of the proteome caused by multiple amino acids comprising each protein (as opposed to just 4 bases in DNA and RNA) and extensive posttranslational modifications (glycosylation, phosphorylation, etc), methods of isolating and studying proteins lag behind those of genomics.
Despite this, proteomic analysis has proven an important tool in analysis of human cancer. The foundation of most proteomic studies is two-dimensional gel electrophoresis, in which proteins are separated on the basis of size and charge. Spots of differential expression (between differentially-labeled normal and tumor samples, for instance) are dissected from the gel and the proteins isolated. These are then analyzed by various forms of mass spectroscopy (MS) in order to sequence and identify the proteins. Such approaches have identified proteins which not only differentiate lung cancer from normal specimens48-51 but also predict survival.52,53
In addition to standard 2D-gel/MS approaches, new developments in proteomic analysis have been described. Recently, proteomic microarrays have also been used in two ways. In a forward phase array, multiple protein-specific antibodies are immobilized on a glass slide and the protein sample is added to it.54 In a reverse phase array, protein extracts are hybridized to a slide, and either antibodies or candidates for drug development are used to probe it.55 As proteomic microar-rays continue to evolve, so too does mass spectroscopy. Using surface-enhanced laser desorption/ionization mass spectroscopy (SELDI-MS), solutions of proteins are directly analyzed, allowing differentiation of cancer from normal. In addition, typical matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF), may be used to create protein profiles able to distinguish between histologic types of lung cancer and between primary and metastatic tumors.56
An exciting new area of inquiry into the molecular biology of lung cancer is mouse modeling. Modern transgenic and knockout genetic technologies have allowed manipulation of the mouse genome in order to study effects of mutation/overexpression/deletion of specific genes. This section will briefly describe two of the present models.
This first of these models was made in Tyler Jacks’ laboratory at MIT by knocking a mutant codon 12 KRas gene into the Ras locus in an inducible fashion. This mutant gene is preceded by a stop codon flanked by a certain DNA sequence termed a loxP site. These loxP sites are recognized by the Cre recombinase enzyme, which proceeds to excise the DNA between them. When Cre recombinase is delivered to specific cells of this transgenic mouse line, the stop codon is excised, and the oncogenic KRas mutant is over expressed. In order to direct recombination and oncogene expression to the bronchial epithelium in these mice, Cre recombinase was delivered via inhaled adenovirus. After the adenovirus was administered, these mice developed first atypical adenomatous hyperplasia and epithelial hyperplasia. These lesions progressed to adenomas and then to adenocarcinoma.57 By gradually decreasing the dose of virus administered, hyperplasia was found to initiate at cells positive for both the Clara cell marker Clara Cell antigen 10 (CC10) and the alveolar Type II cell marker surfactant protein C (SPC). In a subsequent study, these “dual-positive” cells were isolated and found to exhibit stem cell properties of self-renewal and ability to differentiate into multiple lineages. These cells were termed bronchoalveolar stem cells (BASCs) and were demonstrated to proliferate after Cre-induced Ras activation in the bronchial epithelium of the above mice.58 Thus, this inducible oncogenic Ras mouse model may have led to identification of a normal tissue stem cell in the lung. If this normal tissue stem cell is truly the cell of origin for adenocarcinoma, this would constitute proof of the cancer stem cell hypothesis, which states that tumors arise from transformed normal tissue stem cells.59
This mouse model also has shed light upon importance of other signaling molecules in lung cancer tumorigenesis and progression. Although the oncogenic Ras mutant produced adenocarcinomas, they did not metastasize. However, when this mouse line was crossed with an inducible knockout of p53, administration of adenoviral Cre recombinase led to adenocarcinomas which are invasive, desmo-plastic, and metastatic.60 Using the same Ras mutant in a doxycycline-inducible mouse line, the Varmus laboratory obtained the same result.61 Another group of investigators using the same inducible Ras mutant found that inducible deletion of the Lkb1 gene, deficiency of which contributes to Peutz-Jeghers syndrome, leads to metastatic adenocarcinomas as well as a proportion of tumors which exhibit squamous histology.62 This result indicates that, at least in a subset of lung cancers, histologic subtype may be the result of a “switch” involving Lkb1. Finally, downstream effectors of Ras may be important in tumorigenesis, as induction of oncogenic KRas in a mouse line which is null for the Ras downstream effector Rac1, leads to a markedly decreased number of tumors.63
Inducible mutant epidermal growth factor receptor mice also lead to adeno-carcinoma. Transgenic mouse lines were made in the Varmus laboratory by injecting tetracycline-inducible oncogenic EGFR mutants driven by the Clara Cell secretory protein (CCSP) promoter. Both a point mutant at position 858 (L858R) and a deletion mutant (L747-S752) were made. When doxycycline is administered to these mice, they form tumors with histologic features similar to bronchoalveolar carcinoma (BAC). Interestingly, when doxycycline was withdrawn from these mice, the tumors regressed. The tumors also regressed upon treatment with the EGFR tyrosine kinase inhibitor erlotinib.64 Finally, the downstream molecules in these mice were compared to those of the doxycycline-inducible mutant KRas adenocarcinoma-forming mice. In both cases, phosphorylated Erk, Akt, and Stat3 were present by immunostaining. This suggests that both models involve activation of the mitogen activated protein kinase (MAPK), phosphoinositol-3-kinase (PI3K), and signal transducer and activator of transcription-3 (STAT3) pathways.
CANCER STEM CELLS
The theory that cancers arise from small populations of cells with ability to self-renew and differentiate into multiple lineages has become very popular.59 According to this model, stem cells may be transformed and thus become proliferative or proliferative non-stem cells may acquire the properties of stem cells. Either way, the theory holds that these cells should be targeted in order for anticancer treatments to be effective.
Across many cancer types, researchers have identified cells surface markers that differentiate cancer stem cells from the rest of the tumor.65-69 Relevant markers include CD133, CD24, and CD44. One group has identified CD133 as identifying cancer stem cells in small cell and non-small cell lung cancer. In this study, CD133-positive cells self-renew and differentiate into all cell types in the tumor both in vitro (in sphere-forming assays) and in vivo (in immunodeficient mice) much more efficiently than CD133-negative tumor cells.70
However, controversy exists concerning these studies. Some have made mathematical arguments demonstrating the implausibility of these approaches71 while others have provided direct experimental evidence that the apparent stem-like abilities of tumor subpopulations may be recapitulated by many more cells in the tumor given the correct conditions.72,73 Thus, the cancer stem cell theory will await further confirmatory studies.
As our understanding of molecular biology increases, we will know more about both lung cancer and esophageal cancer. This may allow rapid clinical advances in the future.
1. Rodenhuis S, Slebos RJ. Clinical significance of Ras oncogene activation in human lung cancer. Cancer Res. 1992;52(9 Suppl):2665s-2669s.
2. Slebos RJ, Kibbelaar RE, Dalesio O, et al. KRas oncogene activation as a prognostic marker in adenocarcinoma of the lung. N Engl J Med. 1990;323(9):561-565.
3. Sugio K, Ishida T, Yokoyama H, Inoue T, Sugimachi K, Sasazuki T. Ras gene mutations as a prognostic marker in adenocarcinoma of the human lung without lymph node metastasis. Cancer Res. 1992;52(10):2903-2906.
4. Mascaux C, Iannino N, Martin B, et al. The role of Ras oncogene in survival of patients with lung cancer: a systematic review of the literature with meta-analysis. Br J Cancer. 2005;92(1):131-139.
5. Winton T, Livingston R, Johnson D, et al. Vinorelbine plus cisplatin vs. observation in resected non-small-cell lung cancer. N Engl J Med. 2005;352(25):2589-2597.
6. Johnson SM, Grosshans H, Shingara J, et al. Ras is regulated by the let-7 microRNA family. Cell. 2005;120:635-647.
7. Yanaihara N, Caplen N, Bowman E, et al. Unique microRNA molecular profiles in lung cancer diagnosis and prognosis. Cancer Cell. 2006;9:189-198.
8. Yu SL, Chen HY, Chang GC, et al. MicroRNA signature predicts survival and relapse in lung cancer. Cancer Cell. 2008;13(1):48-57.
9. Lord RV, O’Grady R, Sheehan C, Field AF, Ward RL. K-ras codon 12 mutations in Barrett’s oesophagus and adenocarcinomas of the oesophagus and oesophagogastric junction. J Gastroenterol Hepatol. 2000;15(7):730-736.
10. Ahrendt SA, Decker PA, Alawi EA, et al. Cigarette smoking is strongly associated with mutation of the K-ras gene in patients with primary adenocarcinoma of the lung. Cancer. 2001;92(6):1525-1530.
11. Slebos RJ, Hruban RH, Dalesio O, Mooi WJ, Offerhaus GJ, Rodenhuis S. Relationship between K-ras oncogene activation and smoking in adenocarcinoma of the human lung. J Natl Cancer Inst. 1991;83(14):1024-107.
12. Feng Z, Hu W, Chen JX, et al. Preferential DNA damage and poor repair determine ras gene mutational hotspot in human cancer. J Natl Cancer Inst. 2002;94(20):1527-1536.
13. Shigematsu H, Lin L, Takahashi T, et al. Clinical and biological features associated with epidermal growth factor receptor gene mutations in lung cancers. J Natl Cancer Inst. 2005;97(5):339-346.
14. Shigematsu H, Gazdar AF. Somatic mutations of epidermal growth factor receptor signaling pathway in lung cancers. Int J Cancer. 2006;118(2):257-262.
15. Harris RC, Chung E, Coffey RJ. EGF receptor ligands. Exp Cell Res. 2003;284(1):2-13.
16. Kosaka T, Yatabe Y, Endoh H, Kuwano H, Takahashi T, Mitsudomi T. Mutations of the epidermal growth factor receptor gene in lung cancer: biological and clinical implications. Cancer Res. 2004;64(24):8919-8923.
17. Pao W, Miller V, Zakowski M, et al. EGF receptor gene mutations are common in lung cancers from “never smokers” and are associated with sensitivity of tumors to gefitinib and erlotinib. Proc Natl Acad Sci U S A. 2004;101(36):13306-13311.
18. Huang SF, Liu HP, Li LH, et al. High frequency of epidermal growth factor receptor mutations with complex patterns in non-small cell lung cancers related to gefitinib responsiveness in Taiwan. Clin Cancer Res. 2004;10(24):8195-8203.
19. Tokumo M, Toyooka S, Kiura K, et al. The relationship between epidermal growth factor receptor mutations and clinicopathologic features in non-small cell lung cancers. Clin Cancer Res. 2005;11(3):1167-1173.
20. Paez JG, Jänne PA, Lee JC, et al. EGFR mutations in lung cancer: correlation with clinical response to gefitinib therapy. Science. 2004;304(5676):1497-1500.
21. Lynch TJ, Bell DW, Sordella R, et al. Activating mutations in the epidermal growth factor receptor underlying responsiveness of non-small-cell lung cancer to gefitinib. N Engl J Med. 2004;350(21):2129-2139.
22. Gazdar AF, Shigematsu H, Herz J, Minna JD. Mutations and addiction to EGFR: the Achilles ‘heal’ of lung cancers. Trends Mol Med. 2004;10:481-486.
23. Vissers KJ, Riegman PH, Alers JC, Tilanus HW, van Dekken H. Involvement of cancer-activating genes on chromosomes 7 and 8 in esophageal (Barrett’s) and gastric cardia adenocarcinoma.Anticancer Res. 2001;21(6A):3813-3820.
24. Gibson MK, Abraham SC, Wu TT, et al. Epidermal growth factor receptor, p53 mutation, and pathological response predict survival in patients with locally advanced esophageal cancer treated with preoperative chemoradiotherapy. Clin Cancer Res. 2003;9(17):6461-6468.
25. Denissenko MF, Pao A, Tang M, Pfeifer GP. Preferential formation of benzo[a]pyrene adducts at lung cancer mutational hotspots in P53. Science. 1996;274(5286):430-432.
26. Ahrendt SA, Chow JT, Yang SC, et al. Alcohol consumption and cigarette smoking increase the frequency of p53 mutations in non-small cell lung cancer. Cancer Res. 2000; 60(12):3155-3159.
27. Carbone DP, Mitsudomi T, Chiba I, et al. p53 immunostaining positivity is associated with reduced survival and is imperfectly correlated with gene mutations in resected non-small cell lung cancer. A preliminary report of LCSG 871. Chest. 1994;106(6 Suppl):377S-381S.
28. Mitsudomi T, Hamajima N, Ogawa M, Takahashi T. et al. Prognostic significance of p53 alterations in patients with non-small cell lung cancer: a meta-analysis. Clin Cancer Res. 2000;6(10): 4055-4063.
29. Steels E, Paesmans M, Berghmans T, et al. Role of p53 as a prognostic factor for survival in lung cancer: a systematic review of the literature with a meta-analysis. Eur Respir J. 2001;18(4):705-719.
30. Wu TT, Watanabe T, Heitmiller R, Zahurak M, Forastiere AA, Hamilton SR. Genetic alterations in Barrett esophagus and adenocarcinomas of the esophagus and esophagogastric junction region. Am J Pathol; 1998;153(1):287-294.
31. Dolan K, Morris AI, Gosney JR, Field JK, Sutton R. Loss of heterozygosity on chromosome 17p predicts neoplastic progression in Barrett’s esophagus. J Gastroenterol Hepatol. 2003;18(6):683-689.
32. Tanaka H, Fujii Y, Hirabayashi H, et al. Disruption of the RB pathway and cell-proliferative activity in non-small-cell lung cancers. Int J Cancer. 1998;79(2):111-115.
33. Sanchez-Cespedes M, Decker PA, Doffek KM, et al. Increased loss of chromosome 9p21 but not p16 inactivation in primary non-small cell lung cancer from smokers. Cancer Res. 2001;61(5):2092-2096.
34. Kim DH, Nelson HH, Wiencke JK, et al. p16(INK4a) and histology-specific methylation of CpG islands by exposure to tobacco smoke in non-small cell lung cancer. Cancer Res. 2001;61(8):3419-3424.
35. Barrett MT, Galipeau PC, Sanchez CA, Emond MJ, Reid BJ. Determination of the frequency of loss of heterozygosity in esophageal adenocarcinoma by cell sorting, whole genome amplification and microsatellite polymorphisms. Oncogene. 1996;12(9):1873-188.
36. Tarmin L, Yin J, Zhou X, et al. Frequent loss of heterozygosity on chromosome 9 in adenocarcinoma and squamous cell carcinoma of the esophagus. Cancer Res. 1994;54(23):6094-6096.
37. Galipeau PC, Prevo LJ, Sanchez CA, et al. Clonal expansion and loss of heterozygosity at chromosomes 9p and 17p in premalignant esophageal (Barrett’s) tissue. J Natl Cancer Inst. 1999;91(24):2087-2095.
38. Maley CC, Galipeau PC, Li X, Sanchez CA, Paulson TG, Reid BJ. Selectively advantageous mutations and hitchhikers in neoplasms: p16 lesions are selected in Barrett’s esophagus. Cancer Res. 2004;64(10):3414-3427.
39. Kratzke RA, Greatens TM, Rubins JB, et al. Rb and p16INK4a expression in resected non-small cell lung tumors. Cancer Res. 1996;56(15):3415-3420.
40. Beer DG, Kardia SL, Huang CC, et al. Gene-expression profiles predict survival of patients with lung adenocarcinoma. Nat Med. 2002;8(8):816-824.
41. Bhattacharjee A, Richards WG, Staunton J, et al. Classification of human lung adenocarcinomas by mRNA expression profiling reveals distinct adenocarcinoma subclasses. PNAS. 2001;98(24):13790-13795.
42. Garber ME, Troyanskaya OG, Schluens K, et al. Diversity of gene expression in adenocarcinoma of the lung. PNAS. 2002;98(24):13784-13789.
43. Raponi M, Zhang Y, Yu J, et al. Gene expression signatures for predicting prognosis of squamous cell and adenocarcinomas of the lung. Cancer Res. 2006;66(15):7466-7472.
44. Cao G, Lu H, Feng J, Shu J, Zheng D, Hou Y. Lung cancer risk associated with Thr495Pro polymorphism of GHR in Chinese population. Jpn J Clin Oncol. 2008; Apr;38(4):308-316.
45. Kiyohara C, Yoshimasu K. Genetic polymorphisms in the nucleotide excision repair pathway and lung cancer risk: a meta-analysis. Int J Med Sci. 2007;4(2):59-71.
46. Nomura M, Shigematsu H, Li L, et al. Polymorphisms, mutations, and amplification of the EGFR gene in non-small cell lung cancers. PLoS Med. 2007;4(4):e125.
47. Oh JJ, Koegel AK, Phan DT, Razfar A, Slamon DJ. The two single nucleotide polymorphisms in the H37/RBM5 tumour suppressor gene at 3p21.3 correlated with different subtypes of non-small cell lung cancers. Lung Cancer. 2007;58(1):7-14.
48. Bergman AC, Benjamin T, Alaiya A, et al. Identification of gel-separated tumor marker proteins by mass spectrometry. Electrophoresis. 2000;21(3):679-686.
49. Chen G, Gharib TG, Huang CC, et al. Proteomic analysis of lung adenocarcinoma: identification of a highly expressed set of proteins in tumors. Clin Cancer Res. 2002;8(7):2298-2305.
50. Hanash S, Brichory F, Beer D. A proteomic approach to the identification of lung cancer markers. Dis Markers. 2001;17(4):295-300.
51. Hirano T, Franzén B, Uryu K, et al. Detection of polypeptides associated with the histopathological differentiation of primary lung carcinoma. Br J Cancer. 1995;72(4):840-848.
52. Chen G, Gharib TG, Wang H, et al. Protein profiles associated with survival in lung adenocarcinoma. Proc Natl Acad Sci U S A. 2003;100(23):13537-13542.
53. Gharib TG, Chen G, Wang H, et al. Proteomic analysis of cytokeratin isoforms uncovers association with survival in lung adenocarcinoma. Neoplasia. 2002;4(5):440-448.
54. Liotta LA, Espina V, Mehta AI, et al. Protein microarrays: meeting analytical challenges for clinical applications. Cancer Cell. 2003;3(4):317-325.
55. Huang J, Zhu H, Haggarty SJ, et al. Finding new components of the target of rapamycin (TOR) signaling network through chemical genetics and proteome chips. Proc Natl Acad Sci U S A. 2004;101(47):16594-16599.
56. Yanagisawa K, Shyr Y, Xu BJ, et al. Proteomic patterns of tumour subsets in non-small-cell lung cancer. Lancet. 2003;362(9382):433-439.
57. Jackson EL, Willis N, Mercer K, et al. Analysis of lung tumor initiation and progression using conditional expression of oncogenic K-ras. Genes Dev. 2001;15:3243-3248.
58. Kim CF, Jackson EL, Woolfenden AE, et al. Identification of bronchioalveolar stem cells in normal lung and lung cancer. Cell. 2005;121(6):823-835.
59. Reya T, Morrison SJ, Clarke MF, Weissman IL. Stem cells, cancer, and cancer stem cells. Nature. 2001;414:105-111.
60. Jackson EL, Olive KP, Tuveson DA et al. The differential effects of mutant p53 alleles on advanced murine lung cancer. Cancer Res. 2005;65(22):10280-10288.
61. Fisher GH, Wellen SL, Klimstra D, et al. Induction and apoptotic regression of lung adenocarcinomas by regulation of a K-Ras transgene in the presence and absence of tumor suppressor genes. Genes Dev. 2001;15(24):3249-3262.
62. Ji H, Ramsey MR, Hayes DN, et al. LKB1 modulates lung cancer differentiation and metastasis. Nature. 2007;448(7155):807-810.
63. Kissil JL, Walmsley MJ, Hanlon L, et al. Requirement for Rac1 in a K-ras-induced lung cancer in the mouse. Cancer Res. 2007;67(17):8089-894.
64. Politi K, Zakowski MF, Fan PD, Schonfeld EA, Pao W, Varmus HE. Lung adenocarcinomas induced in mice by mutant EGF receptors found in human lung cancers respond to a tyrosine kinase inhibitor or to down-regulation of the receptors. Genes Dev. 2006;20(11):1496-1510.
65. Al-Hajj M, Wicha MS, Benito-Hernandez A, Morrison SJ, Clarke MF. Prospective identification of tumorigenic breast cancer cells. PNAS. 2003;100(7):3983-3988.
66. Lawson DA, Xin L, Lukacs RU, Cheng D, Witte ON. Isolation and functional characterization of murine prostate stem cells. PNAS. 2007;104(1):181-186.
67. Prince ME, Sivanandan R, Kaczorowski A, et al. Identification of a subpopulation of cells with cancer stem cell properties in head and neck squamous cell carcinoma. PNAS. 2007;104(3):973-978.
68. Ricci-Vitiani L, Lombardi DG, Pilozzi E, et al. Identification and expansion of human colon-cancer-initiating cells. Nature. 2007;445(4):111-115.
69. Singh SK, Hawkins C, Clarke ID, et al. Identification of human brain tumour initiating cells. Nature. 2004;432:396-401.
70. Eramo A, Lotti F, Sette G, et al. Identification and expansion of the tumorigenic lung cancer stem cell population. Cell Death Differ. 2008;15(3):504-514.
71. Kern SE, Shibata D. The fuzzy math of solid tumor stem cells: a perspective. Cancer Res. 2007;67(19):8985-8988.
72. Kelly PN, Dakic A, Adams JM, Nutt SL, Strasser A. Tumor growth need not be driven by rare cancer stem cells. Science. 2007;317(5836):337.
73. Quintana E, Shackleton M, Sabel MS, Fullen DR, Johnson TM, Morrison SJ. Efficient tumour formation by single human melanoma cells. Nature. 2008;456(7222):593-598.