NRN1 interacts with Notch to increase oncogenic STAT3 signaling in melanoma.

BACKGROUND: Melanoma is a highly heterogeneous cancer, in which frequent changes in activation of signaling pathways lead to a high adaptability to ever changing tumor microenvironments. The elucidation of cancer specific signaling pathways is of great importance, as demonstrated by the inhibitor of the common BrafV600E mutation PLX4032 in melanoma treatment. We therefore investigated signaling pathways that were influenced by neurotrophin NRN1, which has been shown to be upregulated in melanoma. METHODS: Using a cell culture model system with an NRN1 overexpression, we investigated the influence of NRN1 on melanoma cells' functionality and signaling. We employed real time cell analysis and spheroid formation assays, while for investigation of molecular mechanisms we used a kinase phosphorylation kit as well as promotor activity analysis followed by mRNA and protein analysis. RESULTS: We revealed that NRN1 interacts directly with the cleaved intracellular domain (NICD) of Notch1 and Notch3, causing a potential retention of NICD in the cytoplasm and thereby reducing the expression of its direct downstream target Hes1. This leads to decreased sequestration of JAK and STAT3 in a Hes1-driven phosphorylation complex. Consequently, our data shows less phosphorylation of STAT3 while presenting an accumulation of total protein levels of STAT3 in association with NRN1 overexpression. The potential of the STAT3 signaling pathway to act in both a tumor suppressive and oncogenic manner led us to investigate specific downstream targets - namely Vegf A, Mdr1, cMet - which were found to be upregulated under oncogenic levels of NRN1. CONCLUSIONS: In summary, we were able to show that NRN1 links oncogenic signaling events between Notch and STAT3 in melanoma. We also suggest that in future research more attention should be payed to cellular regulation of signaling molecules outside of the classically known phosphorylation events.

Gene expression profiling in porocarcinoma indicates heterogeneous tumor development and substantiates poromas as precursor lesions.

BACKGROUND AND OBJECTIVES: Malignant sweat gland tumors are rare, with the most common being eccrine porocarcinoma (EP). Approximately 18% of benign eccrine poroma (EPO) transit to EP. Previous research has provided first insights into the mutational landscape of EP. However, only few studies have performed gene expression analyses. This leaves a gap in the understanding of EP biology and potential drivers of malignant transformation from EPO to EP. METHODS: Transcriptome profiling of 23 samples of primary EP and normal skin (NS). Findings from the EP samples were then tested in 17 samples of EPO. RESULTS: Transcriptome profiling revealed diversity in gene expression and indicated biologically heterogeneous sub-entities as well as widespread gene downregulation in EP. Downregulated genes included CD74, NDGR1, SRRM2, CDC42, ANXA2, KFL9 and NOP53. Expression levels of CD74, NDGR1, SRRM2, ANXA2, and NOP53 showed a stepwise-reduction in expression from NS via EPO to EP, thus supporting the hypothesis that EPO represents a transitional state in EP development. CONCLUSIONS: We demonstrated that EP is molecularly complex and that evolutionary trajectories correspond to tumor initiation and progression. Our results provide further evidence implicating the p53 axis and the EGFR pathway. Larger samples are warranted to confirm our findings.

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.

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.