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Global DNA methylation reflects spatial heterogeneity and molecular evolution of lung adenocarcinomas

ABSTRACT: Lung adenocarcinoma (ADC) is the most prevalent subtype of lung cancer and characterized by considerable morphological and mutational heterogeneity. However, little is known about the epigenomic intratumor variability between spatially separated histological growth patterns of ADC. In order to reconstruct the clonal evolution of histomorphological growth patterns, we performed global DNA methylation profiling of 27 primary tumor regions, seven matched normal tissues, and six lymph node metastases from seven ADC cases. Additionally, we investigated the methylation data from 369 samples of the TCGA ADC cohort. All regions showed varying degrees of methylation changes between segments of different, but also of the same growth patterns. Similarly, copy number variations were seen between spatially distinct segments of each patient. Hierarchical clustering of promoter methylation revealed extensive heterogeneity within and between the cases. Intra-tumor DNA methylation heterogeneity demonstrated a branched clonal evolution of ADC regions driven by genomic instability with subclonal copy number changes. Notably, methylation profiles within tumors were not more similar to each other than to those from other individuals. In two cases, different tumor regions of the same individuals were represented in distant clusters of the TCGA cohort, illustrating the extensive epigenomic intratumor heterogeneity of ADCs. Importantly, we found no evidence for the lymph node metastases to be derived from a common growth pattern. Instead, they had evolved early and separately from a particular pattern in each individual primary tumor. In summary, our results suggest that extensive variation of epigenomic features contributes to the molecular and phenotypic heterogeneity of primary ADCs and lymph node metastases.

ORGANISM(S): Homo sapiens

PROVIDER: GSE114989 | GEO | 2019/05/15

REPOSITORIES: GEO

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Project description: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.

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Global DNA methylation reflects spatial heterogeneity and molecular evolution of lung adenocarcinomas

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