DNA Methylation Profiling Defines Clinically Relevant Biological Subsets of Non−Small Cell Lung Cancer

Published OnlineFirst January 19, 2012; DOI: 10.1158/1078-0432.CCR-11-2635-T

Clinical Cancer Predictive Biomarkers and Personalized Medicine Research See commentary by Easwaran and Baylin, p. 2121

DNA Methylation Proﬁling Deﬁnes Clinically Relevant Biological Subsets of Non–Small Cell Lung Cancer

Kim Walter1, Thomas Holcomb1, Tom Januario1,2, Pan Du3, Marie Evangelista2, Nithya Kartha2, Leonardo Iniguez6, Robert Soriano4, Ling Huw1, Howard Stern5, Zora Modrusan4, Somasekar Seshagiri4, Garret M. Hampton1, Lukas C. Amler1, Richard Bourgon3, Robert L. Yauch1,2, and David S. Shames1

Abstract Purpose: Non–small cell lung cancers (NSCLC) comprise multiple distinct biologic groups with different prognoses. For example, patients with epithelial-like tumors have a better prognosis and exhibit greater sensitivity to inhibitors of the epidermal growth factor receptor (EGFR) pathway than patients with mesenchymal-like tumors. Here, we test the hypothesis that epithelial-like NSCLCs can be distinguished from mesenchymal-like NSCLCs on the basis of global DNA methylation patterns. Experimental Design: To determine whether phenotypic subsets of NSCLCs can be defined on the basis of their DNA methylation patterns, we combined microfluidics-based gene expression analysis and genome- wide methylation profiling. We derived robust classifiers for both gene expression and methylation in cell lines and tested these classifiers in surgically resected NSCLC tumors. We validate our approach using quantitative reverse transcriptase PCR and methylation-specific PCR in formalin-fixed biopsies from patients with NSCLC who went on to fail front-line chemotherapy. Results: We show that patterns of methylation divide NSCLCs into epithelial-like and mesenchymal-like subsets as defined by gene expression and that these signatures are similarly correlated in NSCLC cell lines and tumors. We identify multiple differentially methylated regions, including one in ERBB2 and one in ZEB2, whose methylation status is strongly associated with an epithelial phenotype in NSCLC cell lines, surgically resected tumors, and formalin-fixed biopsies from patients with NSCLC who went on to fail front- line chemotherapy. Conclusions: Our data show that patterns of DNA methylation can divide NSCLCs into two phenotypically distinct subtypes of tumors and provide proof of principle that differences in DNA methylation can be used as a platform for predictive biomarker discovery and development. Clin Cancer Res; 18(8); 1–14. 2012 AACR.

Introduction activity profile of some recently approved agents including Non–small cell lung cancer (NSCLC) accounts for the bevacizumab, erlotinib, and pemetrexed suggest that his- largest proportion of cancer-related deaths in the United tology may be an important variable in clinical decision States and worldwide (1). NSCLC is composed of multiple making (3–5). In addition, it is now clear that some molec- histologic subtypes including adenocarcinoma, squamous ularly targeted agents are more efficacious in specific, molec- cell carcinoma, large cell carcinoma, and others. Until ularly defined subsets of patients (6). The epidermal growth recently, histology has made little difference in terms of factor receptor (EGFR)-tyrosine kinase inhibitor, erlotinib, patient outcome on therapy (2). However, the safety and induces striking clinical responses in patients with activat- ing mutations in the EGFR kinase domain (7); however, there is evidence that a subset of patients with EGFR Authors' Affiliations: Departments of 1Oncology Biomarker Development, 2Molecular Diagnostics and Cancer Cell Biology, 3Bioinformatics and wild-type tumors also derive benefit from erlotinib therapy Computational Biology, 4Molecular Biology, and 5Pathology, Genentech (8–10). Recent efforts have therefore focused on identifying Inc., South San Francisco, California; and 6Roche Nimblegen, Madison, Wisconsin molecular biomarkers that identify further subsets of patients that may derive benefit from erlotinib. Note: Supplementary data for this article are available at Clinical Cancer Research Online (http://clincancerres.aacrjournals.org/). We previously reported on the identification of a gene expression signature that is associated with in vitro sensi- Corresponding Author: David S. Shames, Department of Oncology Biomarker Development, Genentech Inc., 1 DNA Way, South San tivity or resistance to erlotinib. This gene expression signa- Francisco, CA 94080. Phone: 650-225-7559; Fax: 650-225-5770; ture divides NSCLC cell lines into epithelial-like and mes- E-mail: [email protected] enchymal-like subsets (11). In multiple tumor types, an doi: 10.1158/1078-0432.CCR-11-2635-T epithelial-to-mesenchymal transition (EMT) induces an 2012 American Association for Cancer Research. aggressive phenotype characterized by increased motility

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DNA-based biomarkers can be used to infer the biologic Translational Relevance state of tumors and provide proof of principle that DNA Successful development of targeted therapeutics methylation differences can be used as a platform for now and in the future will hinge on defining patient predictive biomarker discovery and development. subsets that are most likely to benefit from new drug candidates. Here, we show that patterns of DNA methylation can divide NSCLC into two phenotypically Materials and Methods distinct subtypes of tumors and provide proof of Please see Supplementary Methods for description of cell principle that these kinds of differences in DNA meth- lines and tissues and for additional methods used in this ylation can be used as a platform for predictive bio- study. marker discovery and development. Fluidigm expression analysis EMT gene expression analysis was conducted on 82 NSCLC cell lines using the BioMark 96 96 gene expression and invasiveness and more recently has been implicated in platform (Fluidigm) and a 20-gene EMT expression panel DC resistance to chemotherapy and other drugs (12–17). While (Supplementary Table S1 and Methods). The t values the mechanisms responsible for maintaining an epithelial were used to cluster cell lines according to EMT gene or mesenchymal phenotype in cancer are not completely expression levels using Cluster v.3.0 and Treeview v.1.60 understood, recent evidence suggests that chromatin states, software (http://rana.lbl.gov/EisenSoftware.htm). and in particular DNA methylation, are involved. Promoter methylation and gene silencing of E-cadherin (CDH1), the Illumina Infinium analysis best-characterized epithelial marker, is frequently observed Microarray data were collected at Expression Analysis, Inc. in mesenchymal-like breast cancers (18, 19). Molecules that (www.expressionanalysis.com) using the IlluminaHuman- induce an EMT, such as TGFb1, lead to reduced CDH1 Methylation450 BeadChip (Illumina) as described (Supple- expression driven by transcriptional repressors that bind mentary Methods). Array data were analyzed and a methyl- directly to the CDH1 promoter and recruit histone deace- ation classifier was established using a "leave-one-out" cross- tylases and other chromatin remodeling proteins (20). validation strategy (Supplementary Methods; refs. 25, 26). Furthermore, downstream regulators of EMT including the Array data have been submitted to the Gene Expression miR-200 family of microRNAs are specifically silenced and Omnibus database (accession number GSE36216). gain promoter hypermethylation and repressive chromatin marks in some invasive and poorly differentiated tumors Results (21–23). Recent work describing an in vitro model system of Epithelial-like and mesenchymal-like expression EMT induction suggests that these DNA methylation signatures correlate with erlotinib sensitivity in vitro changes are acquired in a predictable, rather than stochastic We previously defined a gene expression signature that manner (20), suggesting that such patterns might be used as correlates with in vitro sensitivity of NSCLC cell lines to surrogate markers for cells in an epithelial versus a mesen- erlotinib (11). This gene set was highly enriched for genes chymal state. Taken together with evidence that genome- involved in EMT. From this work and other recent reports, wide reprogramming of chromatin domains occurs during we developed a quantitative reverse transcriptase PCR– EMT (24), these data suggest that specific epigenetic profiles based EMT expression panel on the Fluidigm nanofluidic may be associated with the epithelial-like and mesenchy- platform (Supplementary Table S1). A comparison of the mal-like phenotypes observed in NSCLCs. 100-probe set from the study of Yauch and colleagues and Here, we took an integrated genomics approach to the 20-gene EMT Fluidigm panel for 42 of the lines profiled determine whether DNA methylation patterns could clas- in the study of Yauch and colleagues shows that this 20-gene sify phenotypic subsets of NSCLC (see Supplementary expression panel is a representative classifier of EMT Methods; Fig. 1 for schematic of our experimental (ref. 11; Fig. 1A). approach). By combining microfluidics-based gene expres- To further evaluate whether our 20-gene panel was rep- sion analysis and genome-wide methylation profiling, we resentative of the phenotypic changes associated with an show that prognostic subsets of NSCLCs can be defined on EMT, we treated 2 cell lines with TGFb1. As shown in Fig. 1B, the basis of the differences in DNA methylation. Genome- TGFb1 induced morphologic changes associated with an wide DNA methylation profiling identified tumor-specific EMT. We then tested whether TGFb-induced gene expres- hyper- and hypomethylation patterns in the promoters and sion changes were consistent with an EMT in these cell lines. distal regulatory elements of genes involved in epithelial cell As expected, the genes associated with an epithelial pheno- differentiation and transformation. We identified 2 differ- type were downregulated and genes associated with a mes- entially methylated regions (DMR), one in ERBB2 and one enchymal phenotype were upregulated in these cell lines, in ZEB2, whose methylation status is strongly associated albeit to different degrees (Fig. 1C). with an epithelial phenotype in NSCLC cell lines, surgically To determine whether DNA methylation profiling could resected primary NSCLCs, and tumors from patients who be used to classify NSCLC cell lines into epithelial-like and had failed front-line chemotherapy. Our data suggest that mesenchymal-like groups, we used our 20-gene expression

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Figure 1. A Fluidigm-based EMT gene expression panel classifies NSCLC cell lines as epithelial-like or mesenchymal-like. A, comparison of hierarchical clustering of NSCLC cell lines using the 100-gene expression signature described in the study of Yauch and colleagues to the refined 20-gene EMT panel (reported in Supplementary Table S1). B, micrographs of H1975 and gBEC1 before and after chronic (4 weeks) exposure to TGFb (magnification, 100). C, quantitative PCR for the 20 EMT genes in H1975 and gBEC1. D, hierarchical clustering of 82 NSCLC cell lines using the 20 genes. 2DCt values were used for clustering. The expression data were normalized and median centered (samples and genes). Green indicates a low level or no mRNA expression for indicated genes; red indicates high expression. Hierarchical clustering characterizes 36 lines as epithelial-like and 34 lines as mesenchymal-like, with 12 forming a distinct intermediate group characterized by above median expression of genes from both the epithelial and mesenchymal gene sets.

panel to assign epithelial-like versus mesenchymal-like profiled that 89% could be classified clearly as epithelial or status to 82 cell lines. The NSCLC cell lines used in this mesenchymal. For the most part, this epithelial-like versus study include most of the lines profiled in the study of Yauch mesenchymal-like expression phenotype was mutually and colleagues and an additional 52 lines, which included 6 exclusive, possibly reflecting a distinct underlying biology, lines with EGFR mutations (summary of cell line descrip- which we hypothesized may be linked to distinct DNA tions including histology included in Supplementary Table methylation profiles. S2). Of the 82 cell lines, 36 were classified as epithelial-like and 34 were classified as mesenchymal-like on the basis of Genome-wide methylation profiles correlate with their expression of these markers (Fig. 1D). Twelve lines Fluidigm-based EMT signatures in NSCLC cell lines (indicated in the bottom cluster of Fig. 1D) were classified as We first evaluated the Illumina Infinium 450K array as a epithelial-like but express a combination of epithelial and platform for high-throughput methylation profiling by mesenchymal markers. Our interpretation is that these lines comparing the b-values for 52 probes and sodium bisulfite represent a distinct biology and, therefore, we designate sequencing data on a subset of cell lines (N ¼ 12). We them as intermediate. Thus, of the 82 NSCLC lines, we observed a highly significant, strong positive correlation

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between methylation calls by the Infinium array and direct lines H1435, HCC4017, H647, H2228, H1755, and HCC15 bisulfite sequencing (r ¼ 0.926; Supplementary Fig. S1). clustered with the epithelial-like group (Fig. 2, indicated by To identify DMRs that distinguished between epithelial- Sample Type in the top). Interestingly, 5 of these 6 lines like and mesenchymal-like cell lines, we used a cross-val- clustered closely together into a distinct subset of the idation strategy which simultaneously constructed a meth- mesenchymal-like lines by EMT gene expression analysis ylation-based classifier and assessed its prediction accuracy (Fig. 1D), suggesting that this gene expression phenotype (see Supplementary Methods). When applied to our 69 cell associates with a somewhat distinct underlying methylation line training set, this analysis yielded 549 DMRs represent- signature. Importantly, the mesenchymal-like phenotype ing 915 individual CpG sites that were selected as defining harbors a larger proportion of hypermethylated sites than epithelial-like versus mesenchymal-like NSCLC cell lines the epithelial phenotype. This suggests that changes in with a false discovery rate–adjusted P value below 0.01 in methylation may be required to stabilize the phenotypic 100% of the cross-validation iterations (Supplementary alterations acquired during an EMT in NSCLCs. Table S3). The cross-validation estimated accuracy of the EGFR-mutant NSCLCs typically present as well-differen- methylation-based classifier was 88.0% (2.4%, 95% con- tiated adenocarcinomas in the peripheral lung. As antici- fidence interval). pated, based on their epithelial-like expression phenotype Next, we used the CpG sites included in our methylation- and their characteristic histology, the EGFR-mutant cell based EMT classifier to cluster the 69 NSCLC cell lines lines behaved more similarly to epithelial-like lines than (including 6 EGFR-mutant, erlotinib-sensitive lines) and to mesenchymal-like lines. We also noted the segregation 2 primary normal lung cell strains and their immortalized pattern of the cell lines based on in vitro sensitivity to counterparts. This analysis revealed a striking segregation erlotinib (Fig. 2, indicated by Sensitivity in the middle). As of epithelial-like, mesenchymal-like, and normal lines anticipated, based on prior studies (11), nearly all erlotinib- (Fig. 2). Notably, the methylation signal from these CpG sensitive lines were associated with an epithelial-like phe- sites clustered the epithelial-like and mesenchymal-like cell notype whereas nearly all mesenchymal-like lines were lines into their respective epithelial-like and mesenchymal- resistant to erlotinib. However, not all epithelial-like lines like groups with only 6 exceptions: the mesenchymal-like were sensitive to erlotinib. Ten of the erlotinib-resistant

Figure 2. DNA methylation profiling delineates epithelial-like (E) and mesenchymal-like (M) NSCLC cell lines. Seventy-two NSCLC cell lines and normal lung epithelial cells were profiled using the Illumina Infinium 450K Methylation array platform. Supervised hierarchical clustering was conducted using 915 probes that were significantly differentially methylated between epithelial-like and mesenchymal-like cell lines (false discovery rate ¼ 0.01; Supplementary Methods). Annotated probes sets used for the cluster analysis are listed (Supplementary Table S3). Each row represents an individual probe on the Infinium 450K array and each column represents a cell line. Regions shaded blue in the heat map represent unmethylated regions, regions shaded red represent methylated regions. The top color bar shows columns representing the epithelial-like or mesenchymal-like status of each cell line as determined by Fluidigm EMT gene expression analysis. Green indicates epithelial-like and black indicates mesenchymal-like cell lines. The bottom color bar indicates the erlotinib response phenotype of each cell line. Red indicates erlotinib-sensitive lines; black indicates erlotinib-resistant lines; gray indicates lines with intermediate sensitivity to erlotinib. A Euclidian distance metric was used for clustering without centering; the color scheme represents absolute methylation differences.

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Downloaded from clincancerres.aacrjournals.org on September 27, 2021. © 2012 American Association for Cancer Research. www.aacrjournals.org Table 1. Annotation of DMRs selected for sodium bisulﬁte sequencing or qMSP and pyrosequencing array design Downloaded from Gene Chromosomal 5-aza-dC Normal Epithelial/ symbol Gene name location Regulatory element induction PBMCs lung mesenchymal P (E vs. M) P (S vs. R)

ZEB2 Zinc ﬁnger E-box chr2: 144,989,352- Conserved regulatory Yes Unmethylated No E 0.0012 0.3432 binding homeobox 2 144,989,168 potential Published OnlineFirstJanuary19,2012;DOI:10.1158/1078-0432.CCR-11-2635-T NKX6.2 Homeobox protein chr10: 134,448,826- CpG island NE Partially No E 0.0568 0.8353 Nkx-6.2 134,449,879 methylated clincancerres.aacrjournals.org PEX5L Peroxisomal biogenesis chr3: 181,236,933- CpG island No Unmethylated No E 0.0084 0.6566 factor 5-like 181,237,780 GALR1 Galanin receptor 1 chr18: 73,090,412- CpG island NE Unmethylated No E NE NE 73,090,797 PTPRM Protein tyrosine chr18: 7,932,674- Conserved Yes Methylated Yes E NE NE phosphatase, 7,933,993 regulatory receptor type, M potential ME3 NADP-dependent chr11: 86,060,344- CpG island Some Unmethylated No E 0.0295 0.5771 malic enzyme 3 86,061,158

Cancer Research. SYK Spleen tyrosine chr9: 92,631,210- None deﬁned Yes Methylated Yes E NE NE kinase 92,632,740

on September 27, 2021. © 2012American Association for PCDH8 Protocadherin 8 chr13: 52,321,012- CpG island Yes Unmethylated No E 0.0656 0.5107 52,321,485 HOXC5 Homeobox C5 chr12: 52,712,688- CpG island NE Unmethylated No M 0.7493 0.0008

52,7l3,529 Subsets Biologic NSCLC Underlie Patterns Methylation DNA miR200C microRNA 200c chr12: 6,942,800- None deﬁned NE Methylated No M NE NE 6,943,200 SERPINB5 Serine (or cysteine) chr18: 59,294,906- Conserved regulatory Yes Methylated Yes M NE NE proteinase inhibitor, 59,295,319 potential clade B, member 5; Maspin BCAR3 Breast cancer chr1: 93,852,868- Conserved regulatory Some Methylated Yes M 0.001 0.2071

lnCne e;1()Arl1,2012 15, April 18(8) Res; Cancer Clin antiestrogen 93,853,418 potential resistance 3 FAM110A Family with sequence chr20: 822, None deﬁned Some Methylated No M <0.0001 0.0007 similarity 110, 480-822,120 member A CLDN7 Claudin 7 chr17: 7,103, CpG island Yes Partially No M <0.0001 0.0011 446-7,106,446 methylated ESRP1 Epithelial splicing chr8: 95,653,500- Yes Yes Unmethylated No M <0.0001 0.0043 regulatory protein 95,654,240 (Continued on the following page) OF5 Published OnlineFirst January 19, 2012; DOI: 10.1158/1078-0432.CCR-11-2635-T

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lines clustered with the epithelial-like lines, and 4 erlotinib- sensitive lines, H838, H2030, RERF-LC-MS, and SK-MES-1, clustered with the mesenchymal-like lines. Notably, H838 (S vs. R)

P and SK-MES-1 behaved as outliers with regard to erlotinib sensitivity when clustered by gene expression using our previously defined EMT expression signature (11). Some of the other outliers with respect to erlotinib sensitivity have (E vs. M) 0.0001 0.0004 0.0001 0.0004 mutations that explain their apparent resistance. For exam- < P 0.0001 0.0023 < NE NE 0.0009 0.0028 ple, the epithelial-like line H1975 harbors a T790M mutation in EGFR and H1993 harbors an MET amplification. These genetic alterations confer resistance to erlotinib specifically, suggesting that the epigenetic signatures we observed are surrogates for the biologic state of the cell line rather than for erlotinib sensitivity, per se. Epithelial/ mesenchymal Sodium bisulfite sequencing of selected DMRs validates Infinium methylation profiling

Normal lung Yes M We selected 17 DMRs identified by Infinium (Table 1) that were spatially associated with genes (in the 50 CpG island or intragenic) and examined their methylation status by direct sequencing of cloned fragments of sodium bisulfite–converted DNA. We randomly selected 5 epithelial-like methylated lines, 4 mesenchymal-like lines, and one intermediate line for sequencing validation. As shown in Fig. 3A and B, bisulfite sequencing of approximately 10 clones per cell line for 10 loci revealed that nearly all of these markers were almost completely methylated in at least 4 of the mesen- 5-aza-dC induction PBMCs Yes Unmethylated Some M NoNE Partially Methylated Yes M No Methylated No M chymal-like cell lines and in the intermediate line H522. In contrast, these loci were completely unmethylated in all 5 of the epithelial-like lines. Four of 10 markers that were methylated in mesenchymal-like lines, ESRP1 and CP2L3/ GRHL2, miR200C, and MST1R/RON, are involved in

ned ESRP1

ﬁ epithelial differentiation (2, 27, 28). is an epithelial-speciﬁc regulator of alternative splicing that is down- te sequencing or qMSP and pyrosequencing array design (Cont'd )

ﬁ CP2L3/GRHL2

enhancer regulated in mesenchymal cells and is a CpG island Yes Unmethylated No M CpG island CpG island None de Putative transcriptional regulator of the apical junctional complex (27, 28); miR200C is a known negative regulator of the EMT inducer ZEB1 (29). ESRP1 and GRHL2 expression was downregulated in a larger panel of mesenchymal-like lines relative to all of the epithelial-like lines (Supplementary Fig. S2), consistent with the known absence of ESRP proteins in mesenchymal cells and the ability of these proteins to regulate epithelial transcripts that switch splicing during 102,575,793 49,916,545 129,869,427 78,440,951 37,863,650 EMT. Pyrosequencing analysis indicated that GRHL2 was chr3: 49,916,089- Chromosomal location Regulatory element chr17: 78,440,425- chr12: 129,868,924- chr17: 37,861,100- also hypermethylated in this broader panel of mesenchymal-like lines relative to epithelial-like lines (Supplemen- tary Fig. S3).

c In addition to identifying methylation markers associat- fi ed with a mesenchymal phenotype, we also found several DMRs that defined epithelial-like cell lines by Infinium and bisulfite sequencing (Fig. 3B). Not surprisingly, 2 of these stimulating 1 receptor chaperone D leukemia viral oncogene homolog 2 epithelial-specific markers were associated with genes Grainyhead-like 2Macrophage chr8: 102,575,373- 5yntaxin 2 Tubulin-speci v-erb-b2 erythroblastic involved in cellular adhesion functions or have been impli- Annotation of DMRs selected for sodium bisul cated in the regulation of EMT (PCDH8 and ZEB2). Inter- estingly, the epithelial-like lines were methylated in the first intronic region of ZEB2, a known inducer of EMT that has GRHL2 RON STX2 Table 1. Gene symbol Gene name TBCD ERBB2 NOTE: 5-aza-dC expression: NE, not evaluated. been negatively correlated with an epithelial gene signature in NSCLC lines. Collectively, these data establish distinct

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DNA methylation patterns in epithelial-like and mesenchy- the presence or absence of methylation, which obviates the mal-like cell lines that directly underlie differential gene need for defining cutoff points. expression patterns in known mediators of EMT. Importantly, several of our most specific markers with regard to epithelial-like versus mesenchymal-like status Biologic relevance of DMRs were heavily methylated in peripheral blood mononuclear To evaluate the role of methylation in regulating expres- cell (PBMC) DNA, obviating their clinical use (Table 1; sion of the genes associated with select DMRs, we carried out Supplementary Fig. S5). These experiments illustrate that a quantitative PCR in a panel of 34 5-aza-2’-deoxycytidine major hurdle to using qMSP or methylation assays for either (5-aza-dC) and dimethyl sulfoxide–treated NSCLC cell early detection screening or predictive diagnostics is con- lines. Not all DMRs were associated with obvious gene tamination by PBMCs or other types of immune cells. Thus, expression changes following 5-aza-dC treatment (see it is critical to test any new set of assays on multiple samples ERBB2, Table 1), but we noted significant induction of of PBMC DNA if the intent is to develop them for clinical GRHL2, ESRP1, and CLDN7 transcripts in mesenchymal- applications. like versus epithelial-like lines (Supplementary Fig. S4). We first determined whether these assays differentiated From this group of genes, we selected CLDN7 as a repre- epithelial-like from mesenchymal-like cell lines based on sentative marker of EMT and quantified its methylation our EMT gene expression classification. Thirteen candidate status by pyrosequencing in an extended panel of 42 cell markers of epithelial (E) or mesenchymal (M) status were lines. Nearly all of the mesenchymal-like lines were meth- tested, including RON/MST1R (M), STX2 (M), HOXC5 (M), ylated at the CLDN7 promoter region and exhibited dra- PEX5L (E), FAM110A (M), ZEB2 (E), ESRP1 (M), BCAR3 matic induction of CLDN7 expression (>10-fold) in (E), CLDN7 (M), PCDH8 (E), NKX6.2 (M), ME3 (E), and response to 5-aza-dC treatment (Fig. 3C and D). In contrast, GRHL2 (M). Ten of 13 markers were significantly associated CLDN7 was expressed in the majority of the epithelial-like with epithelial-like or mesenchymal-like status in using a cell lines and was not induced further by 5-aza-dC treat- P < 0.05 cutoff value (Fig. 4; Table 1). We next examined ment. These data show a direct link between locus-specific whether these same markers were predictive of erlotinib DNA hypermethylation and transcriptional silencing in a sensitivity in vitro. Seven of 13 DMRs were strongly predic- subset of genes associated with epithelial-like and mesen- tive of erlotinib resistance (individual P < 0.005; Supple- chymal-like states in NSCLC cell lines. mentary Fig. S7) and 3 of 13 DMRs, PEX5L, ME3, and ZEB2, were significantly associated with an epithelial phenotype Quantitative MSP classifies NSCLC cell lines into but were not predictive of erlotinib sensitivity. epithelial and mesenchymal subtypes and predicts for erlotinib sensitivity Hypomethylation of the ERBB2 DMR correlates with Following independent validation of the methylation ERBB2 expression and an epithelial-like phenotype in status of 17 markers by direct sequencing analysis, we NSCLC cell lines and primary tumors expanded our discovery set to 70 NSCLC cell lines to While many of the DMRs were associated with CpG determine whether these markers could correctly classify islands, a significant minority were located within genes. epithelial-like and mesenchymal-like phenotypes. On the In some cases, the intragenic DMRs appeared to be basis of sodium bisulfite sequencing analyses, we selected hypomethylated relative to normal adjacent tissue (Supple- methylated regions that best distinguished the epithelial- mentary Fig. S8). One such DMR, which was part of the like lines from mesenchymal-like lines and designed quan- methylation classifier, included a CpG site near exon 4 of titative methylation-specific PCR (qMSP) assays based on the ERBB2 proto-oncogene. ERBB2 is a clinically validated TaqMan technology (Supplementary Fig. S5). We used drug target whose amplification and overexpression are qMSP as an assay platform because previous work showed associated with sensitivity to erlotinib and other inhibitors its use in detecting tumor-specific promoter hypermethyla- of HER signaling (34, 35). For these reasons, we further tion in specimens obtained from patients with cancer. This evaluated the relationship between ERBB2 expression and method is highly sensitive and specific for quantifying DNA methylation status in this region. methylated alleles and is readily adaptable to high-through- In silico analysis of this region using the UCSC genome put formats, making it suitable for clinical applications (30– browser suggested that the differentially methylated CpG 33). TaqMan technology is superior to SYBR-based designs site corresponding to probe cg00459816 overlapped with a for MSP due to the increased specificity of the assay potential regulatory element. Because this region was not imparted by the fluorescent probe, which does not act as within a CpG island and was not particularly GC rich, we a primer. To normalize samples for DNA input, we designed designed pyrosequencing primers flanking this region to a bisulfite-modified RNase P reference assay to amplify determine its methylation status in a panel of epithelial-like input DNA independent of its methylation status. We con- and mesenchymal-like cell lines. We observed a remarkable ducted titration curves using control methylated DNA, DNA pattern of hypomethylation (mean methylation of 6 CpG derived from peripheral blood monocytes (N ¼ 20), and sites 20%) in 13 of 16 epithelial-like lines relative to DNA from cell lines with known methylation status for each mesenchymal-like lines (mean methylation 70% in 20 DMR (Supplementary Fig. S5). Of note, nearly all of the of 21 mesenchymal-like lines; P < 0.001; Fig. 5A). Only one assays we developed result in essentially binary outputs for mesenchymal-like line, H1435, was hypomethylated at this

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Figure 3. Sodium bisulfite sequencing of selected DMRs validates Infinium methylation profiling. A, sodium bisulfite sequencing confirms regions of differential methylation between epithelial-like and mesenchymal-like NSCLC cell lines. Candidate regions identified by Infinium methylation profiling were selected for sodiumbisulfite sequencing analysis. Ten regions associatedwith the indicated genes are differentially methylatedin mesenchymal-likeNSCLC lines. Methylation status was determined at individual CpG sites for 10 to 12 clones per cell line for the target region of each indicated gene. A green bar indicates epithelial-like, a black bar indicates mesenchymal-like, and a blue bar indicates intermediate-like NSCLC lines. Each row represents one clone and each column represents an individual CpG site. Open boxes represent unmethylated CpG sites; filled boxes represent methylated sites; shaded boxes are undetermined. Four loci (CLDN7, LAMB3, STX2,andGJB3) from the 20 gene panel that were also part of the 915-probe classifier were included in this analysis. DMRs associated with 2 additional genes, NKX6.2 and STX2, were evaluated by qMSP (Table 1, Supplementary Figs. S6 and S7). B, seven candidate regions associated with the indicated genes are differentially methylated in epithelial-like NSCLC lines. The DMR associated with ERBB2 was evaluated by pyrosequencing (Table 1; Fig. 5). C, pyrosequencing of the CLDN7 promoter region differentiates 42 NSCLC cell lines on the basis of epithelial-like/mesenchymal-like phenotype. Quantitative methylation was determined at 7 CpG sites by PyroMark analysis software using the equation: % methylation ¼ (C peak height 100/C peak height þ Tpeakheight).Dataare represented as the mean SD percentage of methylation at 7 CpG sites. D, relative expression of CLDN7 mRNA was determined using a standard DCt method in 42 (n ¼ 20 epithelial-like, 19 mesenchymal-like, 3 intermediate) DMSO-treated and 5-aza-dC–treated NSCLC cell lines. Expression values were calculated as a fold change in 5-aza-dC–treated relative to DMSO-treated control cells. Data are normalized to the housekeeping gene GAPDH and represented as the mean of 2 replicates. DMSO, dimethyl sulfoxide; GAPDH, glyceraldehyde-3-phosphate dehydrogenase.

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locus. This exception was not surprising given our previous observation that H1435 was identified as a mesenchymal- like line by EMT expression analysis (Fig. 1D). Interestingly, epithelial-like lines exhibited significantly higher levels of ERBB2 expression (P < 0.001) than mesenchymal-like lines (Fig. 5B), although we did not observe induction of ERBB2 in these lines upon 5-aza-dC treatment (data not shown). We also observed that ERBB2 hypomethylation was strongly correlated with erlotinib sensitivity in vitro, suggesting its potential use as a predictive clinical biomarker of erlotinib response (Fig. 5C). Fresh-frozen samples are not typically obtained during diagnosis of NSCLCs or as part of lung cancer clinical trials. Therefore, to be amenable to clinical applications, a pyrosequencing assay must be able to amplify limited, degrad- ed DNA from formalin-fixed, paraffin-embedded (FFPE) tissue (commonly <150 bp). Because of the high concor- dance between the methylation states of 6 adjacent CpG sites within the ERBB2 DMR using a 228-bp pyrosequencing assay (Supplementary Fig. S9), we redesigned the assay to examine just 2 CpG sites. We evaluated the methylation status of ERBB2 in 42 late-stage (stage IIIb/IV) FFPE NSCLC tumors for which gene expression data were also available. Hypomethylation of the ERBB2 enhancer correlated strongly with expression of HER2 in biopsies obtained from patients who later went on to fail front-line chemotherapy (P < 0.011), recapitulating the pattern that we observed in cell lines (Fig. 5D).

Methylation status of ERBB2 and ZEB2 are associated with an epithelial-like phenotype in NSCLC primary tumors Although the loss of CDH1 expression is the best-established marker of the EMT, it is a suboptimal classiﬁer because CDH1 is only expressed when the cells are epithelial; a negative outcome could mean that the tissue is mesenchymal or it could be an artifact of tissue processing or staining. In addition, there are the confounding vari- ables of tumor heterogeneity and the sometimes transient nature of an EMT. On the basis of these facts and our own observations (Fig. 1C and D), we reasoned that a combination of several markers would enable a more accurate representation of epithelial-like or mesenchymal-like biologic phenotypes. To determine how robust our expression panel was in tumors, we took CDH1 expression as an EMT

Figure 4. qMSP assays differentiate epithelial-like from mesenchymal-like anchor and then selected genes (13 in total) whose corre- NSCLC cell lines. TaqMan-based methylation detection assays specific lation with CDH1 showed the same sign in both cell lines for DMRs associated with the genes (A) MST1R/RON,(C)FAM110A,(E) and tumor samples (inverse correlation for mesenchymal CP2L3/GRHL2, and (G) ESRP1 are presented. qMSP assays were used markers; positive correlation for epithelial markers). The 31 ¼ to determine methylation in epithelial-like (n 36) and mesenchymal-like tumors were then assigned an EMT score according to (n ¼ 34) NSCLC cell lines. Total input DNA was normalized using a bisulfite-specific RNase P TaqMan probe. Methylation levels are plotted expression levels of these 13 genes (see Supplementary as DCt (indicated target gene- RNase P) for each sample on the y-axis. Table S4 and Methods). The tumors were also scored D An increasing Ct value indicates increasing methylation. Cell lines are according to the methylation-based classifier described grouped by epithelial-like/mesenchymal-like status on the x-axis. above. Remarkably, methylation scores correlated strongly P values were determined using a 2-tailed, unpaired Student t test. r ¼ Receiver operating characteristic (ROC) plots for (B) RON,(D)FAM110A, with the expression-based EMT score in both cell lines ( (F) GRHL2, and (H) ESRP1 are presented. Additional ROC plots are also 0.880, P < 0.0001) and in surgically resected primary presented (Supplementary Figs. S6 and S7). P values were determined tumors (r ¼0.668, P < 0.0001; Fig. 6B). These data using a Wilcoxon rank-sum test. indicate that, similar to cell lines, NSCLC primary tumors

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Figure 5. Hypomethylation of the ERBB2 correlates with ERBB2 expression and an epithelial-like phenotype in NSCLC cell lines and primary tumors. A, pyrosequencing determines quantitative methylation of the ERBB2 in epithelial-like and mesenchymal-like NSCLC cell lines. Data are represented as mean SD percentage of methylation at 6 consecutive CpG sites in the sequenced region. Percentages of methylation at each of the 6 individual CpG sites are also presented (Supplementary Fig. S9). P value was determined using a 2-tailed, unpaired Student t test. B, relative expression of ERBB2 mRNA was determined in NSCLC cell lines using TaqMan-based Fluidigm gene expression analysis (see Materials and Methods for detailed description). Data are represented as 2DCt (ERBB2-reference genes) values. P value was determined using a 2-tailed, unpaired Student t test. C, ERBB2 pyrosequencing analysis of NSCLC cell lines correlates ERBB2 hypomethylation with erlotinib sensitivity. Data are plotted as the mean SD percentage of methylation of 6 CpG cites against erlotinib IC50 values (described in Materials and Methods). D, methylation status and relative expression of ERBB2 mRNA was determined in 42 NSCLC primary tumors derived from FFPE tissue using pyrosequencing and TaqMan-based Fluidigm gene expression analysis (see Materials and Methods for detailed description). Percentage of methylation is represented as the mean of 2 CpG sites. ERBB2 expression data are represented as 2DCt (ERBB2-reference genes) values. A median cutoff point was used to dichotomize ERBB2-high and ERBB2-low tumors. P value was determined using a one-tailed Mann–Whitney U test.

harbor DNA methylation patterns representative of their and overall gene expression phenotype (Fig. 6C). Having gene expression profiles and suggest that these methylation established that the DMR associated with the known EMT patterns can be used to classify tumors into epithelial-like regulator ZEB2 was also a marker of an epithelial pheno- and mesenchymal-like biologic subsets. type in NSCLC cell lines, we evaluated its association Because of tissue limitations and the process of formalin with epithelial-like/mesenchymal-like status in 60 late- fixation, we were unable to conduct genome-wide analysis stage NSCLCs—less material was required for qMSP com- in the second cohort of tissue samples (FFPE, chemotherapy pared with pyrosequencing, thus the difference in sample failure). For the same reasons, we were unable to amplify number between here and above. We determined ZEB2 sufficient product from the tumor samples used in Fig. 6 to methylation status using a qMSP preamplification method show similar data on CLDN7 as presented for cell lines that we developed (described in Materials and Methods). in Fig. 3. As a result, we investigated whether ERBB2 could qMSP analysis indicated that epithelial-like tumors were serve as a marker of an epithelial-like or mesenchymal-like significantly hypermethylated at the ZEB2 locus relative to phenotype in these tumor samples. We used a median cutoff mesenchymal-like tumors (P < 0.008), again recapitulating point to classify tumors as epithelial-like or mesenchymal- the pattern that we observed in NSCLC cell lines (Fig. 6D). like. Tumors that were classified as epithelial-like were These data show that both ERBB2 and ZEB2 methylation hypomethylated at the ERBB2 enhancer relative to tumors status are predictive of an epithelial phenotype in NSCLC classified as mesenchymal-like (P < 0.046), indicating a cell lines, surgically resected tumors, and formalin-fixed strong association between ERBB2 methylation status biopsies from patients with NSCLCs who went on to fail

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DNA Methylation Patterns Underlie NSCLC Biologic Subsets

Figure 6. DNA methylation profiles and DNA methylation of ERBB2 and ZEB2 predict epithelial/mesenchymal phenotypes in late-stage NSCLC tumors. A, scoring systems were established to determine epithelial-like/mesenchymal-like status based on Infinium methylation profiling and Fluidigm gene expression analysis (see Supplementary Methods). Epithelial-like/mesenchymal-like status as determined by methylation score was correlated with epithelial-like/ mesenchymal-like status as determined by gene expression score for 34 NSCLC cell lines. A methylation score (y-axis) for each cell line was computed on the basis of the methylation status at 915 CpG sites. A gene expression score (x-axis) was computed as described (Supplementary Methods). An increasing methylation score indicates an increasingly mesenchymal phenotype, whereas an increasing mRNA expression score indicates an increasingly epithelial gene expression phenotype. B, thirty-one NSCLC primary tumors profiled on the Infinium 450K array were clustered using the 915 EMT probe signature and their methylation scores were correlated with Fluidigm EMT gene expression scores. C, analysis of methylation of ERBB2 and epithelial/mesenchymal status in 47 NSCLC primary tumor samples derived from archival FFPE slides. Methylation status of ERBB2 was determined using pyrosequencing analysis (see Materials and Methods for detailed description). Data are represented as the mean of 2 CpG cites. Epithelial-like/mesenchymal-like status was determined using scores derived from TaqMan-based Fluidigm gene expression analysis (see Materials and Methods for detailed description). A median cutoff point was used to dichotomize epithelial-like/mesenchymal-like expression scores. P value was determined using a Student t test. D, analysis of methylation of ZEB2 and epithelial-like/mesenchymal-like expression score in 60 samples derived from archival FFPE slides. ZEB2 methylation status was determined using qMSP (see Materials and Methods for detailed description). An increasing DCt value indicates increasing methylation. Data were normalized to the gene MeRNAse P. Epithelial-like/mesenchymal-like scores were determined using TaqMan-based Fluidigm gene expression (see Materials and Methods for detailed description). A median cutoff point was used to dichotomize epithelial-like/mesenchymal-like expression scores. P value was determined using a 2-tailed, unpaired Student t test. front-line chemotherapy. Furthermore, they establish that ylation patterns are associated with distinct biologic and pyrosequencing and qMSP assays can quantify methylation clinically relevant subsets of NSCLCs. DNA- and RNA-based differences in patient DNA derived from FFPE tissue, show- microarray analyses, such as those used in our study to ing that DNA methylation analysis may be a suitable plat- classify phenotypic subsets of NSCLC, require adequate form for predictive biomarker development. tissue quantity and quality, which cannot always be obtained in routine clinical samples. Here, we show that Discussion by refining the genome-wide analyses of both gene expres- In this report, we used an integrated genomics approach sion profiles and DNA methylation profiles in cell lines, we combining gene expression analysis with whole genome capture a representative signature of markers that can be methylation profiling to show that methylation biomarkers translated into a classification system applicable to clinical are capable of classifying epithelial and mesenchymal phe- samples where tissue is limited. notypes in NSCLCs. To our knowledge, this is the first A major challenge in the development of predictive demonstration that genome-wide differences in DNA meth- biomarkers is the need to establish a robust "cut-point" for

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Walter et al.

prospective evaluation. This is particularly problematic for with an epithelial-like phenotype. Therefore, we favor an protein-based assays such as immunohistochemistry. While alternative interpretation whereby the increase in overall widely used, immunohistochemistry is subject to a number methylation observed in mesenchymal-like cells that of technical challenges that limit its use in the context of accompanies an EMT occurs because the cells are changing predictive biomarker development. These limitations from an epigenetic state acquired during normal differen- include antibody specificity and sensitivity, epitope avail- tiation into a fundamentally different state. We propose ability and stability, and the inherent subjectivity of data that tumor cells may undergo a malignant form of differ- interpretation by different pathologists (24, 25). Molecular entiation during an EMT that becomes heritable over time assays that can leverage the dynamic range and specificity of through changes in DNA methylation. This interpretation is PCR are much more desirable. However, there are also consistent with a recent observation by Dumont and col- limitations with PCR-based assays: RNA is highly unstable leagues in that methylation changes associated with EMT and requires that a cutoff point be defined prospectively. appear to occur in a deterministic rather than a stochastic Mutation detection assays, while potentially binary, are manner (20). Indeed, we identified consistent hypermethy- limited by the availability of high prevalence mutation hot lation events that also correlate with the transcriptional spots and target sequences. As we have shown, PCR-based activity of multiple genes previously described as function- methylation assays potentially address many of these issues ally relevant to EMT. because they have many of the properties of mutation One unexpected finding was that of a DMR within the assays, including a broad dynamic range and an essentially ERBB2 proto-oncogene locus. In contrast to many of the loci binary readout with similar sensitivity to mutation assays, discussed above, the DMR in the ERBB2 locus was hypo- yet due to the locally correlated behavior of CpG methyl- methylated relative to adjacent normal tissue. Tumor-spe- ation states, the target regions for assay design can be quite cific differential methylation is ordinarily viewed in the large. Most importantly, DNA methylation can be used to context of tumor-acquired hypermethylation. However, infer the biologic state of tumors in much the same way as tumor-specific differences in DNA methylation were first gene expression has been used in the past. described by Feinberg and Vogelstein as tumor acquired The use of genomic and transcriptional profiling in the hypomethylation events involving both the HRAS and identification of molecular features that are predictive of KRAS promoters (40). In addition, a number of recent tumor response to targeted therapeutics is well established studies have observed loss of imprinting whereby allele- (36, 37). A perceived limitation of using DNA methylation specific expression is lost as a result of changes in methyl- as biomarker is that it is by definition, indirect; DNA ation of the target gene (39). Thus, the DMR in the ERBB2 methylation does not necessarily cause gene silencing but locus could undergo some form of demethylation during rather is likely a marker of the transcriptional state of a gene. oncogenesis to support high-level expression of ERBB2. However, recent work has shown that epigenetic profiles However, an alternative explanation might be that differ- are prognostic of clinical outcome in patients with glioblas- ential methylation of this locus occurs during normal lung toma and breast cancer (38, 39) Here, we have shown that development. In this case, epithelial-like tumors harboring DNA methylation profiles are at least as informative as gene a hypomethylated ERBB2 pattern arise from a specific cell expression profiling in terms of defining biologically and lineage within the lung (6). Additional studies analyzing the clinically relevant differences between NSCLC subtypes. methylation status of ERBB2 in epithelial subtypes in the Indeed, when viewed on a gene-by-gene basis across many normal lung will be required to address this question. While samples using quantitative PCR–based methods, methyla- the DMR we identified is not located within a CpG island, its tion has a larger quantitative range than gene expression. association with known regulatory factors suggests a puta- Previous studies have shown that loss of E-cadherin tive enhancer function. Of note, hypomethylation of the expression, indicative of an EMT, is correlated with poor ERBB2 locus was highly correlated with both higher expres- prognosis in patients with NSCLC (11). With respect to the sion of HER2 in cell lines and with an epithelial phenotype predictive value of E-cadherin expression in patients receiv- as evidenced by our gene expression panel. Our finding that ing erlotinib, further analysis in TRIBUTE patients has ERBB2 hypomethylation is associated with erlotinib sensi- indicated a significantly longer time to progression for E- tivity raises the possibility that differential methylation of cadherin–positive patients receiving erlotinib and chemo- this region could serve as a predictive biomarker for inhi- therapy versus chemotherapy alone (bib11). To show the bitors of EGFR or HER2 signaling. Similarly, the clinical clinical relevance of our approach, we sought to identify significance of ZEB2 methylation in NSCLCs warrants fur- biomarkers of epithelial and mesenchymal phenotypes that ther study, given the known role of ZEB2 expression in might also serve as surrogate markers of erlotinib sensitivity. mediating EMT and the clinical association of EMT with Interestingly, more DMRs were predictive of a mesenchymal chemoresistance. state and of erlotinib resistance than of erlotinib sensitivity. One interesting possibility raised by these findings is that This finding may imply that a mesenchymal-like state is the markers identified here could subset NSCLC tumors that generally indicative of a more advanced tumor stage (19) are amenable to treatment with epigenetic modifying drugs and may represent tumors that have undergone more including histone deacetylase inhibitors and demethylating hypermethylation events than less advanced tumors. Con- agents, administered alone or in combination with other versely, some advanced tumors remain well differentiated targeted therapeutics. The relationship between genetic and

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DNA Methylation Patterns Underlie NSCLC Biologic Subsets

epigenetic mechanisms of drug response is not well under- implications for identifying subsets of patients who may stood; however, an emerging role for nonmutational benefit from molecularly targeted therapy. Importantly, mechanisms of drug response exists (41). Indeed, recent DNA-based methylation markers of epithelial and mesen- work by Sharma and colleagues identifies a transiently chymal phenotypes and other clinically relevant tumor acquired epigenetically mediated drug-tolerant phenotype subtypes will be useful in settings where patient biopsy in NSCLC cells, and ongoing clinical trials are evaluating the material is limited or material for expression-based analyses use of a chromatin-modifying agent in combination with is unavailable. Further studies evaluating the use of DNA erlotinib in patients with NSCLC (42). Furthermore, methylation-based assays as predictive biomarkers in Sequist and colleagues describe a histologic transformation NSCLC and other tumor types are warranted. consistent with EMT in tumors of 2 patients with NSCLC who developed acquired resistance against EGFR-tyrosine Disclosure of Potential Conflicts of Interest kinase inhibitors in the absence of other known resistance No potential conflicts of interests were disclosed. mutations in components of the EGFR signaling pathway (13), suggesting a possible epigenetic mechanism of resis- Acknowledgments The authors thank Joe Muller for constructing the tricistronic vector used tance in these tumors. Considered together with our find- for immortalization of gBECs and gSACs and David Davis for generating the ings, these studies indicate that the development of epige- recombinant virus and carrying out the viral transduction of the gBEC and netic-based molecular assays for identifying these poten- gSAC cultures. They also thank Adi Gazdar and John Minna for providing NSCLC cell lines used in the study; Ashi Malekafzali for procuring the tissue tially responsive or resistant patient populations and mon- specimens; Expression Analysis for conducting the Illumina Infinium 450K itoring tumor epigenetic states will be useful. methylation array profiling; and Jeff Settleman, Chana Davis, David Dornan, and Mark Lackner for critically reviewing the manuscript. Finally, the authors In summary, we have shown that genome-wide differ- thank Zach Boyd and An Do for their contributions to this article. ences in DNA methylation are fundamentally associated The costs of publication of this article were defrayed in part by the pay- with gene expression patterns that distinguish NSCLC bio- ment of page charges. This article must therefore be hereby marked advertise- ment in accordance with 18 U.S.C. Section 1734 solely to indicate this fact. logic subtypes. These methylation profiles may underlie therapeutically relevant tumor subtypes and may serve as Received October 13, 2011; revised December 7, 2011; accepted January 8, a surrogate for gene expression profiles, a finding with broad 2012; published OnlineFirst January 19, 2012.

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DNA Methylation Profiling Defines Clinically Relevant Biological Subsets of Non−Small Cell Lung Cancer

Kim Walter, Thomas Holcomb, Tom Januario, et al.

Clin Cancer Res Published OnlineFirst January 19, 2012.

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