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DNA methylation signature reliably distinguishes pulmonary enteric adenocarcinoma from metastatic colorectal cancer

ABSTRACT: Pulmonary enteric adenocarcinoma (PEAD) is a rare non-small cell lung cancer subtype. It is poorly characterized and cannot be distinguished from metastatic colorectal or upper gastrointestinal adenocarcinomas (ADCs) by means of routine pathological methods. As DNA methylation patterns are known to be highly tissue specific, we aimed to develop a methylation-based algorithm to differentiate these entities. To this end, genome wide methylation profiles of 600 primary pulmonary, colorectal and upper gastrointestinal ADCs obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database were used as a reference cohort to train a machine learning algorithm. The resulting classifier correctly classified all samples from a validation cohort consisting of 680 primary pulmonary, colorectal and upper gastrointestinal ADCs from TCGA and the GEO database, demonstrating the ability of the algorithm to reliably distinguish these three entities. We then analyzed DNA methylation data of 15 PEADs as well as four pulmonary metastases and four primary colorectal ADCs with the algorithm. All 15 PEADs were reliably classified as primary pulmonary tumors and all four metastases as well as all four primary colorectal ADC samples were identified as primary colorectal ADCs. In a t-distributed stochastic neighbor embedding analysis, the PEAD samples did not form a separate methylation subclass but rather diffusely intermixed with other pulmonary ADCs. Additional characterization of the PEAD series using fluorescence in-situ hybridization, next generation sequencing and copy number analysis revealed KRAS mutations in nine of 15 samples (60%) and a high number of structural chromosomal changes. Except for an unusually high rate of chromosome 20 gain (66.7%) the molecular data was mostly reminiscent of standard pulmonary ADCs. In conclusion, we provide sound evidence of the pulmonary origin of PEAD and in addition provide a publicly available machine learning based algorithm to reliably distinguish PEAD from metastatic colorectal cancer and upper gastrointestinal adenocarcinomas.

ORGANISM(S): Homo sapiens

PROVIDER: GSE116699 | GEO | 2019/01/04

REPOSITORIES: GEO

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Project description:Using data from high-density genomic profiling arrays, we describe the profiles of somatic copy-number aberrations (SCNAs) in 486 adenocarcinomas across all three major digestive organs, including 296 gastric and esophageal cancers. This analysis revealed that although patterns of broad, chromosome arm-level alterations are similar across the three types of adenocarcinoma, focal genomic amplifications are substantially more prevalent in gastric/esophageal adenocarcinoma. A statistical analysis identified 64 regions of significantly recurrent amplification and deletion, including those shared across these tumors and those uniquely significant in adenocarcinomas from a single organ. Among significantly amplified genes are those encoding therapeutically targetable kinases such as ERBB2, FGFR1, FGFR2, EGFR, and MET, events noted in 14% of colorectal adenocarcinomas and 37% of gastric/esophageal tumors suggesting that analysis of genomic amplification will be a critical source of biomarkers to guide therapies in upper gastrointestinal adenocarcinomas. While many of the other significant loci of amplifications implicate genes recognized to play roles in gastrointestinal and other cancers, other loci point to regions that may harbor novel genes contributing to these cancers. One such event is a recurrent focal deletion present in 15% of esophageal adenocarcinomas, which we narrow to a single likely target, the Runt transcription factor subunit RUNX1. Indeed, reintroduction of RUNX1 into a cell model with this deletion inhibited anchorage-independent growth. Overall, these results demonstrate genomic features common to these tumors and identify key differences that reflect distinctive biology and potential opportunities for therapeutic intervention. Affymetrix SNP arrays were performed according to the manufacturer's directions on DNA extracted from 87 cancer DNAs derived from primary tumor tissues, as well as from DNA obtained from 1,480 normal DNA samples. Signal intensities were normalized to raw copy number estimates using the tangent normalization method, as described in Beroukhim et al., In Press and Mermel et al., In preparation. The 250K Sty data from this submission were combined with data for 128 colon adenocarcinomas (Firestein et al, Nature 2008) and segmented using GLAD. These segmented data were then combined with segmented SNP 6.0 data for 62 colon, 97 gastric and 112 esophageal adenocarcinomas using common markers to anchor the segments. Data analysis across samples was performed using this GISTIC 2.0 algorithm (Mermel C et al, Genome Biology 2011).

Project description:Using data from high-density genomic profiling arrays, we describe the profiles of somatic copy-number aberrations (SCNAs) in 486 adenocarcinomas across all three major digestive organs, including 296 gastric and esophageal cancers. This analysis revealed that although patterns of broad, chromosome arm-level alterations are similar across the three types of adenocarcinoma, focal genomic amplifications are substantially more prevalent in gastric/esophageal adenocarcinoma. A statistical analysis identified 64 regions of significantly recurrent amplification and deletion, including those shared across these tumors and those uniquely significant in adenocarcinomas from a single organ. Among significantly amplified genes are those encoding therapeutically targetable kinases such as ERBB2, FGFR1, FGFR2, EGFR, and MET, events noted in 14% of colorectal adenocarcinomas and 37% of gastric/esophageal tumors suggesting that analysis of genomic amplification will be a critical source of biomarkers to guide therapies in upper gastrointestinal adenocarcinomas. While many of the other significant loci of amplifications implicate genes recognized to play roles in gastrointestinal and other cancers, other loci point to regions that may harbor novel genes contributing to these cancers. One such event is a recurrent focal deletion present in 15% of esophageal adenocarcinomas, which we narrow to a single likely target, the Runt transcription factor subunit RUNX1. Indeed, reintroduction of RUNX1 into a cell model with this deletion inhibited anchorage-independent growth. Overall, these results demonstrate genomic features common to these tumors and identify key differences that reflect distinctive biology and potential opportunities for therapeutic intervention. Affymetrix SNP arrays were performed according to the manufacturer's directions on DNA extracted from 271 cancer DNAs derived from primary tissues, as well as from DNA obtained from 60 normal DNA samples. Signal intensities were normalized to raw copy number estimates using the tangent normalization method, as described in Beroukhim et al., In Press and Mermel et al., In preparation. The SNP 6.0 data from this submission were segmented using CBS. These segmented data were then combined with segmented Affymetrix 250K Sty data for 128 colon, 13 gastric and 74 esophageal adenocarcinomas using common markers to anchor the segments. Data analysis across samples was performed using this GISTIC 2.0 algorithm (Mermel C et al, Genome Biology 2011).

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DNA methylation signature reliably distinguishes pulmonary enteric adenocarcinoma from metastatic colorectal cancer

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