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

Melanoma is the most serious type of skin cancer that frequently spreads to other organs of the human body. Especially melanoma metastases to the brain (intracranial metastases) are hard to treat and a major cause of death of melanoma patients. Little is known about molecular alterations and altered mechanisms that distinguish intra- from extracranial melanoma metastases. So far, almost all existing studies compared intracranial metastases from one set of patients to extracranial metastases of an another set of melanoma patients. This neglects the important facts that each melanoma is highly individual and that intra- and extracranial melanoma metastases from the same patient are more similar to each other than to melanoma metastases from other patients in the same organ. To overcome this, we compared the gene expression profiles of 16 intracranial metastases to their corresponding 21 patient-matched extracranial metastases in a personalized way using a three-state Hidden Markov Model (HMM) to identify altered genes for each individual metastasis pair. This enabled three major findings by considering the predicted gene expression alterations across all patients: (i) most frequently altered pathways include cytokine-receptor interaction, calcium signaling, ECM-receptor interaction, cAMP signaling, Jak-STAT and PI3K/Akt signaling, (ii) immune-relevant signaling pathway genes were downregulated in intracranial metastases, and (iii) intracranial metastases were associated with a brain-like phenotype gene expression program. Further, the integration of all differentially expressed genes across the patient-matched melanoma metastasis pairs led to a set of 103 genes that were consistently down- or up-regulated in at least 11 of the 16 of the patients. This set of genes contained many genes involved in the regulation of immune responses, cell growth, cellular signaling and transport processes. An analysis of these genes in the TCGA melanoma cohort showed that the expression behavior of 11 genes was significantly associated with survival. Moreover, a comparison of the 103 genes to three closely related melanoma metastasis studies revealed a core set of eight genes that were consistently down- or upregulated in intra- compared to extracranial metastases in at least two of the three related studies (down: CILP, DPT, FGF7, LAMP3, MEOX2, TMEM119; up: GLDN, PMP2) including FGF7 that was also significantly associated with survival. Our findings contribute to a better characterization of genes and pathways that distinguish intra- from extracranial melanoma metastasis and provide important hints for future experimental studies to identify potential targets for new therapeutic approaches.

Network-based analysis of heterogeneous patient-matched brain and extracranial melanoma metastasis pairs reveals three homogeneous subgroups.

Melanoma, the deadliest form of skin cancer, can metastasize to different organs. Molecular differences between brain and extracranial melanoma metastases are poorly understood. Here, promoter methylation and gene expression of 11 heterogeneous patient-matched pairs of brain and extracranial metastases were analyzed using melanoma-specific gene regulatory networks learned from public transcriptome and methylome data followed by network-based impact propagation of patient-specific alterations. This innovative data analysis strategy allowed to predict potential impacts of patient-specific driver candidate genes on other genes and pathways. The patient-matched metastasis pairs clustered into three robust subgroups with specific downstream targets with known roles in cancer, including melanoma (SG1: RBM38, BCL11B, SG2: GATA3, FES, SG3: SLAMF6, PYCARD). Patient subgroups and ranking of target gene candidates were confirmed in a validation cohort. Summarizing, computational network-based impact analyses of heterogeneous metastasis pairs predicted individual regulatory differences in melanoma brain metastases, cumulating into three consistent subgroups with specific downstream target genes.

Screen time and sleep among medical students in Germany.

Medical students are a vulnerable group for harmful health behaviours due to academic stress. Increased screen time is associated with adverse health behaviour, particularly delayed bedtime, shorter sleep duration and poorer sleep quality. This possible relationship has not yet been examined among medical students in Europe. Medical students at the Technical University of Dresden were invited to participate in an online questionnaire based cross-sectional study. To analyse correlations between screen time and sleep parameters, correlation coefficients, linear regression and mixed-model analysis were calculated. 415 students (average age 24 years, 70% female) were included in the analysis. The students reported an average of 7 h screen time per day and 7.25 h sleep duration per night. Approximately 23% (n = 97) reported sleeping less than 7 h per night and 25% (n = 105) reported fairly to very poor sleep quality. Students who reported more screen time for leisure went to bed significantly later (r = 0.213, p < 0.001). Students who spent more screen time for study/work tended to sleep shorter (r = - 0.108, p < 0.015). There was no significant association between screen time and sleep quality (p = 0.103). The results show a need for educational interventions to promote healthy sleep behaviour and to limit screen time.

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

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.