Transcriptional signatures underlying dynamic phenotypic switching and novel disease biomarkers in a linear cellular model of melanoma progression.

Despite advances in therapeutics, the progression of melanoma to metastasis still confers a poor outcome to patients. Nevertheless, there is a scarcity of biological models to understand cellular and molecular changes taking place along disease progression. Here, we characterized the transcriptome profiles of a multi-stage murine model of melanoma progression comprising a nontumorigenic melanocyte lineage (melan-a), premalignant melanocytes (4C), nonmetastatic (4C11-) and metastasis-prone (4C11+) melanoma cells. Clustering analyses have grouped the 4 cell lines according to their differentiated (melan-a and 4C11+) or undifferentiated/"mesenchymal-like" (4C and 4C11-) morphologies, suggesting dynamic gene expression patterns associated with the transition between these phenotypes. The cell plasticity observed in the murine melanoma progression model was corroborated by molecular markers described during stepwise human melanoma differentiation, as the differentiated cell lines in our model exhibit upregulation of transitory and melanocytic markers, whereas "mesenchymal-like" cells show increased expression of undifferentiated and neural crest-like markers. Sets of differentially expressed genes (DEGs) were detected at each transition step of tumor progression, and transcriptional signatures related to malignancy, metastasis and epithelial-to-mesenchymal transition were identified. Finally, DEGs were mapped to their human orthologs and evaluated in uni- and multivariate survival analyses using gene expression and clinical data of 703 drug-naïve primary melanoma patients, revealing several independent candidate prognostic markers. Altogether, these results provide novel insights into the molecular mechanisms underlying the phenotypic switch taking place during melanoma progression, reveal potential drug targets and prognostic biomarkers, and corroborate the translational relevance of this unique sequential model of melanoma progression.

A Distinct DNA Methylation Shift in a Subset of Glioma CpG Island Methylator Phenotypes during Tumor Recurrence.

Glioma diagnosis is based on histomorphology and grading; however, such classification does not have predictive clinical outcome after glioblastomas have developed. To date, no bona fide biomarkers that significantly translate into a survival benefit to glioblastoma patients have been identified. We previously reported that the IDH mutant G-CIMP-high subtype would be a predecessor to the G-CIMP-low subtype. Here, we performed a comprehensive DNA methylation longitudinal analysis of diffuse gliomas from 77 patients (200 tumors) to enlighten the epigenome-based malignant transformation of initially lower-grade gliomas. Intra-subtype heterogeneity among G-CIMP-high primary tumors allowed us to identify predictive biomarkers for assessing the risk of malignant recurrence at early stages of disease. G-CIMP-low recurrence appeared in 9.5% of all gliomas, and these resembled IDH-wild-type primary glioblastoma. G-CIMP-low recurrence can be characterized by distinct epigenetic changes at candidate functional tissue enhancers with AP-1/SOX binding elements, mesenchymal stem cell-like epigenomic phenotype, and genomic instability. Molecular abnormalities of longitudinal G-CIMP offer possibilities to defy glioblastoma progression.

Crosstalk between B16 melanoma cells and B-1 lymphocytes induces global changes in tumor cell gene expression.

The analysis of gene expression patterns in cancers has improved the understanding of the mechanisms underlying the process of metastatic progression. However, the acquisition of invasive behavior in melanoma is poorly understood. In melanoma, components of the immune system can contribute to tumor progression, and inflammatory cells can influence almost all aspects of cancer progression, including metastasis. Recent studies have attributed an important role to B-1 cells, a subset of B lymphocytes, in melanoma progression. In vitro interactions between B16 melanoma cells and B-1 lymphocytes lead to increased B16 cell metastatic potential, but the molecular changes induced by B-1 lymphocytes on B16 cells have not yet been elucidated. In this study, we used a microarray approach to assess the gene expression profile of B16 melanoma cells following contact with B-1 lymphocytes (B16B1). The microarray analysis identified upregulation in genes involved with metastatic progression, such as ctss, ccl5, cxcl2 and stat3. RT-qPCR confirmed this increase in mRNA expression in B16B1 samples. As previous studies have indicated that the ERK1/2 MAPK cascade is activated in melanoma cells following contact with B-1 lymphocytes, RT-qPCR was performed with RNA from melanoma cells before and after contacting B-1 cells and untreated or treated with ERK phosphorylation inhibitors. The results showed that the expression of stat3, ctss and cxcl2 increased in B16B1 but decreased following ERK1/2 MAPK inhibition. Ccl5 gene expression increased after contacting B-1 cells and was maintained at the same level following inhibitor treatment. Stat3 was verified and validated at the protein level by Western blot analysis. STAT3 expression was also significantly increased in B16B1, suggesting that this pathway can also contribute to the increased metastatic phenotype observed in our model. These results indicated that B-1 cells induce important global gene expression changes in B16 melanoma cells. We also evaluated the relationship of some of the genes identified as differentially expressed and the ERK1/2 MAPK cascade. This work may have important implications for understanding the role of B-1 lymphocytes and the ERK/MAPK cascade in the metastatic process.

Mining gene expression signature for the detection of pre-malignant melanocytes and early melanomas with risk for metastasis.

BACKGROUND: Metastatic melanoma is a highly aggressive skin cancer and currently resistant to systemic therapy. Melanomas may involve genetic, epigenetic and metabolic abnormalities. Evidence is emerging that epigenetic changes might play a significant role in tumor cell plasticity and metastatic phenotype of melanoma cells. PRINCIPAL FINDINGS: In this study, we developed a systematic approach to identify genes implicated in melanoma progression. To do this, we used the Affymetrix GeneChip Arrays to screen 34,000 mouse transcripts in melan-a melanocytes, 4C pre-malignant melanocytes, 4C11- non-metastatic and 4C11+ metastatic melanoma cell lines. The genome-wide association studies revealed pathways commonly over-represented in the transition from immortalized to pre-malignant stage, and under-represented in the transition from non-metastatic to metastatic stage. Additionally, the treatment of cells with 10 µM 5-aza-2'-deoxycytidine (5AzaCdR) for 48 hours allowed us to identify genes differentially re-expressed at specific stages of melan-a malignant transformation. Treatment of human primary melanocytes with the demethylating agent 5AzaCdR in combination to the histone deacetylase inhibitor Trichostatin A (TSA) revealed changes on melanocyte morphology and gene expression which could be an indicator of epigenetic flexibility in normal melanocytes. Moreover, changes on gene expression recognized by affecting the melanocyte biology (NDRG2 and VDR), phenotype of metastatic melanoma cells (HSPB1 and SERPINE1) and response to cancer therapy (CTCF, NSD1 and SRC) were found when Mel-2 and/or Mel-3-derived patient metastases were exposed to 5AzaCdR plus TSA treatment. Hierarchical clustering and network analyses in a panel of five patient-derived metastatic melanoma cells showed gene interactions that have never been described in melanomas. SIGNIFICANCE: Despite the heterogeneity observed in melanomas, this study demonstrates the utility of our murine melanoma progression model to identify molecular markers commonly perturbed in metastasis. Additionally, the novel gene expression signature identified here may be useful in the future into a model more closely related to translational research.

Biomarkers as key contributors in treating malignant melanoma metastases.

Melanoma is a human neurocristopathy associated with developmental defects in the neural crest-derived epidermal melanocytes. At the present time, at least three hypotheses were identified that may explain melanoma aetiology, as follows: (1) a model of linear progression from differentiated melanocytes to metastatic cancer cells (2) a model involving the appearance of melanoma stem-like cells, and (3) an epigenetic progenitor model of cancer. Treating metastatic melanoma is one of the most serious challenges in the 21st century. This is justified because of a subpopulation of cells presenting a remarkable molecular heterogeneity, which is able to explain the drug resistance and the growing mortality rates worldwide. Fortunately, there are now evidences sustaining the importance of genetic, epigenetic, and metabolomic alterations as biomarkers for classification, staging, and better management of melanoma patients. To illustrate some fascinating insights in this field, the genes BRAF(V600E) and CTLA4 have been recognized as bona fide targets to benefit melanoma patients. Our research attempts to carefully evaluate data from the literature in order to highlight the link between a molecular disease model and the key contribution of biomarkers in treating malignant melanoma metastases.