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Normal growth of MGRN1-null human melanoma cells. (A) Phase-contrast images of control (HBL-CTR) and MGRN1-KO cells (HBL MGRN1-KO) in 2D cultures. The smaller images on the top right corners show a magnification of a representative region of the micrograph. Scale bar, 50 μm. (B) Changes in the morphology of HBL cells depleted of MGRN1 by siRNA transfection and stimulated with NDP-MSH, as specified in the upper scheme depicting the experimental design. Representative phase-contrast micrographs are shown below. (C) Efficient repression of MGRN1 expression by the siRNA transfection employed above. The upper graph represents the levels of MGRN1 mRNA as estimated by real-time RT-PCR, normalized to the expression in cells treated with control, non-targeting siRNA. ACTB mRNA was used as a loading control. Further details concerning primer sequences are provided under Material and Methods. A representative Western blot of detergent-solubilized cell extracts, stained for MGRN1 and GAPDH as loading control, is shown below, along with the quantification of 3 independent blots. (D) Western blot analysis of MITF expression in cells treated as in panel B, immunostained for MITF and GAPDH (as loading control). A representative blot out of 3 independent experiments and the quantification of the fold change of the normalized MITF signal relative to control unstimulated cells is shown below. (E) Comparable expression of MITF in control HBL cells and MGRN1-KO clones obtained by permanent knockdown of MGRN1. Detergent-solubilized, cell-free extracts were analyzed for MGRN1 by Western blot. A representative blot out of 3 independent experiments and the corresponding quantification are shown. The numbers on top of the MGRN1-KO lanes refer to the individual clone analyzed. GAPDH was used as a loading control. The numbers below these lanes correspond to the normalized MITF signal relative to the control lane (mean of 2 independent experiments). (F) Cell cycle progression in human melanoma cells lacking MGRN1. Control HBL cells and MGRN1-KO cells (clone 3.7) were stained with propidium iodide and analyzed in an FACScanto cytometer. The graph shows the percentage of cells in the G0/G1, S, and G2/M phases (mean ± sem, n = 5 for control and n = 2 for MGRN1-KO cells). (G) Comparable proliferation rates of control and MGRN1-KO cells. The proliferation of control and MGRN1-KO cells was compared with 3 independent methods: metabolic activity measured with MTT (left), metabolic labeling of DNA with BrdU (right), and counting viable cells over 72 h (graph on the bottom). In this last case, doubling times of roughly 23 h were obtained upon nonlinear regression, without statistically significant differences.
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Mahogunin Ring Finger 1 (MGRN1), a ubiquitin ligase expressed in melanocytes, interacts with the α melanocyte-stimulating hormone receptor, a well-known melanoma susceptibility gene. Previous studies showed that MGRN1 modulates the phenotype of mouse melanocytes and melanoma cells, with effects on pigmentation, shape, and motility. Moreover, MGRN1...
Citations
... We previously reported that Mgrn1-null mouse melanocytes displayed a differentiated phenotype with numerous highly melanized melanosomes [36]. MGRN1-deficient melanoma cells also displayed differentiated and less aggressive phenotypes, with induction of intercellular contacts and matrix adhesion, reduced motility, migration, and invasion capabilities, and aberrant cell cycle progression with significant accumulation of cells in the S and G2/M phases [37][38][39]. Based on these observations and on the recent report that genes whose expressions correlate with adverse outcomes across cancer types often encode for housekeeping genes with roles in cell cycle progression [20], we hypothesized that the level of expression of MGRN1 in MM might provide useful prognostic information. ...
... We found higher mutational burden and chromosome number alterations in MGRN1-Low compared with MGRN1-High tumors, and a similar trend for the weighted genome instability index (wGII) (Figure 3d). These data were consistent with preliminary previous data suggesting a role of MGRN1 in genomic stability in mouse [39] and human MM cells [37]. ...
... We next validated the transcriptomic data using functional assays and explored a causal relationship between MGRN1 deficit and the transcriptomic differences in MGRN1-Low and -High MM (Figure 4). To this end, we obtained independent MGRN1-KO clones of HBL human MM cells knocked out for MGRN1 with CRISPR-Cas9, as previously described [37] (clones 2.1, 3.7, and 4.9). MGRN1 knockout was confirmed by analysis of the edited sequences and Western blot [38]. ...
With ever-increasing incidence and high metastatic potential, cutaneous melanoma is the deadliest skin cancer. Risk prediction based on the Tumor-Node-Metastasis (TNM) staging system has medium accuracy with intermediate IIB-IIIB stages, as roughly 25% of patients with low-medium-grade TNM, and hence a favorable prognostic, undergo an aggressive disease with short survival and around 15% of deaths arise from metastases of thin, low-risk lesions. Therefore, reliable prognostic biomarkers are required. We used genomic and clinical information of melanoma patients from the TCGA-SKCM cohort and two GEO studies for discovery and validation of potential biomarkers, respectively. Neither mutation nor overexpression of major melanoma driver genes provided significant prognostic information. Conversely, expression of MGRN1 and the melanocyte-specific genes MLANA, PMEL, and TYRP1 provided a simple 4-gene signature identifying with high-sensitivity (>80%), low-medium TNM patients with adverse outcomes. Transcriptomic analysis of tumors with this signature, or from low-medium-grade TNM patients with poor outcomes, revealed comparable dysregulation of an inflammatory response, cell cycle progression, and DNA damage/repair programs. A functional analysis of MGRN1-knockout cells confirmed these molecular features. Therefore, the simple MGRN1-MLANA-PMEL-TYRP1 combination of biomarkers complemented TNM staging prognostic accuracy and pointed to the dysregulation of immunological responses and genomic stability as determinants of a melanoma outcome.
Posthitis is an incurable lethal disease of males of the European bison (Bison bonasus), regarded to be one of the major threats to the survival of the iconic species. Multiple attempts have been undertaken over the last 30 years to identify a source of infection and a primary pathogen. Studies indicated the disease could have a genetic background after tools developed for cattle (Bos taurus) revealed genomic regions that could be associated with its occurrence. In this study, we applied deep coverage targeted sequencing to 74 regions on 10 of the bison’s chromosomes (1, 9, 12, 13, 15, 23, 25, 26, 29, and X) in search for species-specific single nucleotide polymorphism (SNP) markers that could help to explain the mechanism of the disease and be used to test for posthitis susceptibility. The association results were ranked based on p-values lower than 0.005 and odds ratios (OR) higher than 1. We obtained 30 SNP markers that met these requirements, all located on chromosome 25. However, none of the SNPs found in the study was significantly associated with posthitis occurrence after Bonferroni correction. The conditional nature of posthitis and ‘false negative’ sampling represent major difficulties in investigating this disease, and we recommend a complex genomic and environmental factors association assay that could eventually explain the puzzling etiology of posthitis and help mitigate this threat to the European bison.
