Patient-specific identification of genome-wide DNA-methylation differences between intracranial and extracranial melanoma metastases

Abstract

Melanomas frequently metastasize to distant organs and especially intracranial metastases still represent a major clinical challenge. Epigenetic reprogramming of intracranial metastases is thought to be involved in therapy failure, but so far only little is known about patient-specific DNA-methylation differences between intra- and extracranial melanoma metastases. Hierarchical clustering of the methylomes of 24 patient-matched intra- and extracranial melanoma metastases pairs revealed that intra- and extracranial metastases of individual patients were more similar to each other than to metastases in the same tissue from other patients. Therefore, a personalized analysis of each metastases pair was done by a Hidden Markov Model to classify methylation levels of individual CpGs as decreased, unchanged or increased in the intra- compared to the extracranial metastasis. The predicted DNA-methylation alterations were highly patient-specific differing in the number and methylation states of altered CpGs. Nevertheless, four important general observations were made: (i) intracranial metastases of most patients mainly showed a reduction of DNA-methylation, (ii) cytokine signaling was most frequently affected by differential methylation in individual metastases pairs, but also MAPK, PI3K/Akt and ECM signaling were often altered, (iii) frequently affected genes were mainly involved in signaling, growth, adhesion or apoptosis, and (iv) an enrichment of functional terms related to channel and transporter activities supports previous findings for a brain-like phenotype. In addition, the derived set of 17 signaling pathway genes that distinguished intra- from extracranial metastases in more than 50% of patients included well-known oncogenes (e.g. PRKCA, DUSP6, BMP4) and several other genes known from neuronal disorders (e.g. EIF4B, SGK1, CACNG8). Moreover, associations of gene body methylation alterations with corresponding gene expression changes revealed that especially the three signaling pathway genes JAK3, MECOM, and TNXB differ strongly in their expression between patient-matched intra- and extracranial metastases. Our analysis contributes to an in-depth characterization of DNA-methylation differences between patient-matched intra- and extracranial melanoma metastases and may provide a basis for future experimental studies to identify targets for new therapeutic approaches.

Personalized identification and characterization of genome-wide gene expression differences between patient-matched intracranial and extracranial melanoma metastasis pairs

“…However, melanoma metastases in different organs from a patient are more similar to each other than to metastases from other patients in the same organs. This patient-specific heterogeneity of molecular data from melanoma metastases has been observed in other studies before [18,24,25]. Therefore, such differences between individual patients should be included in the data analysis to further improve the identification of molecular differences between intra-and extracranial melanoma metastases.…”

“…Fischer et al [26] performed RNA sequencing and multiple immune-relevant sequencing analyses and identified a significant immunosuppression and enrichment of oxidative phosphorylation in intracranial melanoma metastases. We have recently performed a personalized analysis of genome-wide DNA-methylation profiles and revealed a global decrease of DNA-methylation intracranially [25]. These DNA-methylation changes between patient-matched intra-and extracranial melanoma metastases affected many genes involved in cellular signaling, growth, adhesion and apoptosis and further supported the presence of a neuronal phenotype.…”

“…To realize this, each patient-matched metastasis pair was analyzed by a Hidden-Markov Model (HMM) approach to identify differentially expressed genes for each pair. This was done by transferring the recently used HMM-approach for the personalized analysis of DNA-methylation profiles by [25] to the analysis of gene expression profiles. The predicted differentially expressed genes were further used to identify frequently affected cellular pathways and to derive a set of genes that was altered in the same manner in the majority of patients.…”

5-Methylcytosine immunohistochemistry for predicting cutaneous melanoma prognosis

“…According to the literature review, there is no difference in methylation between methylation level and location 31 , 42 , 43 . Some papers found that previous therapy had no effect on methylation levels 31 , 44 , and in our analysis, we recruited a melanoma patient who had not previously received treatment. Finally, the study's results were unaffected by age, tumour location, or treatment experience.…”

Epigenomic profiling of active regulatory elements by enrichment of unmodified CpG dinucleotides

“…This facet of the technology is unique amongst epigenetic profiling approaches and particularly aligns Active-Seq with recent work highlighting the significance of unmethylated enhancer DNA as a signature of cell biology 12 . Enhancers are partially (10-60%) methylated in healthy cells and their differential methylation is, in fact, the prevalent perturbation to methylation of DNA at 'functional' genomic elements [62][63][64] . In cancer, hypomethylation of enhancers is more common, being approximately twice as prevalent, in broad range of cancers, as enhancer hypermethylation 62 .…”