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Developmental Pathways Are Epigenetically Reprogrammed during Lung Cancer Brain Metastasis

ABSTRACT: Non-small cell lung cancer (NSCLC) is one of the most commonly diagnosed and deadliest cancers worldwide, owing in large part to roughly half of all patients initially presenting with both primary and metastatic disease. While the major events in the metastatic cascade have been identified, a mechanistic understanding of how NSCLC routinely, successfully colonizes the brain is largely unknown. Recent studies have begun demonstrating the role of epigenetic mis-regulation within tumorigenesis as well as in the metastatic process, including widespread changes in DNA methylation and histone modifications. To better understand the role of DNA methylation alterations in NSCLC metastasis to brain, we measured DNA methylation during disease progression for 12 patients, globally profiling the methylation of their normal lung, primary lung tumor, and brain metastasis. We found that the variation in methylation is just as great; albeit less coordinated across genomic features, during metastatic spread as compared to primary tumorigenesis. The greatest recurrent methylation changes during metastatic progression occurred over DNA methylation valleys (DMVs) harboring H3K9me3 as well as bivalent marks H3K27me3 and H3K4me1 enrichment in normal lung. Mapping EZH2, the catalytic subunit of polycomb repressive complex 2 (PCR2), binding locations in H1299, a lymph node-derived lung cancer cell line, revealed a loss of EZH2 binding within DMVs accompanied by an increase in DNA methylation, exemplifying epigenetic switching. The vast majority of these differentially methylated region-associated DMVs harbor developmental genes, suggesting that altered epigenetic regulation of developmentally important genes may confer a selective advantage during metastatic progression.

ORGANISM(S): Homo sapiens

PROVIDER: GSE203216 | GEO | 2022/07/01

REPOSITORIES: GEO

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Project description:Background: There is a paucity of non-invasive markers for early detection of brain metastasis (BM) in patients with non-small cell lung cancer (NSCLC). Secretory proteomic approach based on quantitative tandem mass tag is believed to offer bright prospects for screening potential serum biomarkers for diseases. Methods: We used the secretory proteomics to identify up-regulated proteins in the highly brain metastatic cell line compared to the parental lung cancer cell line. Enzyme linked immunoassay and immunohistochemistry were performed on non-small cell lung cancer patients with brain metastasis and control samples from each cohort to verify the expression levels of candidate proteins. A logistic regression model was used to develop a biomarker panel composed of Cathepsin F (CTSF) and Fibulin-1 (FBLN1), and then an independent validation data set was used for verification. The diagnostic accuracy was evaluated by receiver operating characteristic (ROC) curve analysis. Changes in serum CTSF levels of patients were tracked to monitor the effect of treatment, and progression-free survival (PFS) and overall survival (OS) were analyzed to assess their prognostic relevance. Results: CTSF and FBLN1 levels were specifically upregulated in sera and tissues of patients with NSCLC BM. Importantly, the combined diagnostic performance of CTSF and FBLN1 was superior to their individual diagnostic performance (sensitivity and specificity). CTSF serum changes were found to reflect the therapeutic response of patients with NSCLC BM and the trends of resistance and progression were detected earlier than the MRI changes. Elevated expression of CTSF in NSCLC BM tissues was associated with poor PFS. Moreover, CTSF tissue expression was found to be an independent prognostic factor. Conclusions: CTSF and FBLN1 are potential novel and specific serum markers for early diagnosis of BM in patients with NSCLC. CTSF can also be used as a biomarker for monitoring therapeutic efficacy and prognostic assessment.

Project description:Non-small cell lung cancer (NSCLC) is a very common solid tumor where only small advances in the reduction of relapse-free survival and overall survival have been accomplished. The issue is particularly critical for stage I patients where there are not available biomarkers, in the absence of detectable nodal or other metastatic involvement, that might indicate which high-risk patients should receive the beneficially proved adjuvant chemotherapy. We aimed to find DNA methylation markers with prognostic value that could be helpful in this regard and complement the conventional staging. A DNA methylation microarray that analyzes 450,000 CpG sites in the human genome was used to study primary tumoral DNA obtained from a multicenter cohort of 490 patients with NSCLC, corresponding to 339 adenocarcinomas, 133 squamous carcinomas and 18 large cell carcinomas, in addition to 25 normal lung epithelium samples. The obtained prognostic DNA methylation markers were validated by the development of a single methylation-pyrosequencing assay in an independent cohort of 143 patients with stage I NSCLC. The unsupervised clustering of the studied primary NSCLC distinguished two branches with distinct clinical outcomes. Those CpG sites that were the best predictors of recurrence in stage I NSCLC patients were further confirmed in the described independent cohort. Both the global DNA methylation classifier and the highly-ranked aberrantly methylated single genes improved prognostic accuracy beyond standard stagings. DNA was quantified by Quant-iT PicoGreen dsDNA Reagent (Invitrogen) and the integrity was analyzed in a 1.3% agarose gel. Bisulfite conversion of 600 ng of each sample was performed according to the manufacturer's recommendations for the Illumina Infinium Assay. Effective bisulfite conversion was checked for three controls that were converted simultaneously with the samples. 4 ul of bisulfite-converted DNA were used to hybridize on an Infinium HumanMethylation 450 BeadChip, following the Illumina Infinium HD Methylation protocol. Chip analysis was performed using the Illumina HiScan SQ fluorescent scanner. The intensities of the images were extracted using GenomeStudio (2011.2) Methylation module (1.8.5) software. The methylation score of each CpG is represented as a beta value. This dataset includes 444 patient samples.

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Developmental Pathways Are Epigenetically Reprogrammed during Lung Cancer Brain Metastasis

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