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Updated: Jun 2, 2026
A Robust Discovery Platform for the Identification of Novel Mediators of Melanoma Metastasis
Published on: March 8, 2022
Network-guided analysis of genes with altered somatic copy number and gene expression reveals pathways commonly
Armand Valsesia1, Donata Rimoldi, Danielle Martinet
1Ludwig Institute for Cancer Research, Lausanne, Switzerland.
Abstract:
Cancer genomes frequently contain somatic copy number alterations (SCNA) that can significantly perturb the expression level of affected genes and thus disrupt pathways controlling normal growth. In melanoma, many studies have focussed on the copy number and gene expression levels of the BRAF, PTEN and MITF genes, but little has been done to identify new genes using these parameters at the genome-wide scale. Using karyotyping, SNP and CGH arrays, and RNA-seq, we have identified SCNA affecting gene expression ('SCNA-genes') in seven human metastatic melanoma cell lines. We showed that the combination of these techniques is useful to identify candidate genes potentially involved in tumorigenesis. Since few of these alterations were recurrent across our samples, we used a protein network-guided approach to determine whether any pathways were enriched in SCNA-genes in one or more samples. From this unbiased genome-wide analysis, we identified 28 significantly enriched pathway modules. Comparison with two large, independent melanoma SCNA datasets showed less than 10% overlap at the individual gene level, but network-guided analysis revealed 66% shared pathways, including all but three of the pathways identified in our data. Frequently altered pathways included WNT, cadherin signalling, angiogenesis and melanogenesis. Additionally, our results emphasize the potential of the EPHA3 and FRS2 gene products, involved in angiogenesis and migration, as possible therapeutic targets in melanoma. Our study demonstrates the utility of network-guided approaches, for both large and small datasets, to identify pathways recurrently perturbed in cancer.
Insights
This study identifies novel cancer genes by analyzing genome-wide copy number alterations in melanoma. A network-guided approach revealed enriched pathways, highlighting potential therapeutic targets like EPHA3 and FRS2.
Area of Science:
- Genomics
- Cancer Biology
- Bioinformatics
Background:
- Somatic copy number alterations (SCNA) disrupt gene expression and cellular pathways in cancer.
- Previous melanoma research focused on specific genes (BRAF, PTEN, MITF), neglecting genome-wide SCNA-gene identification.
Purpose of the Study:
- To identify novel genes affected by SCNA and altered gene expression in melanoma.
- To explore genome-wide SCNA-gene profiles using a network-guided approach.
- To identify recurrently perturbed pathways in melanoma.
Main Methods:
- Integrated karyotyping, SNP arrays, CGH arrays, and RNA-seq to identify SCNA-genes in seven metastatic melanoma cell lines.
- Applied a protein network-guided analysis to identify enriched pathways.
- Compared findings with two independent melanoma SCNA datasets.
Main Results:
- Identified 28 significantly enriched pathway modules in melanoma cell lines.
- Demonstrated high overlap (66%) in enriched pathways between datasets using network analysis, despite low gene-level overlap (<10%).
- Frequently altered pathways included WNT, cadherin signaling, angiogenesis, and melanogenesis. EPHA3 and FRS2 were highlighted as potential therapeutic targets.
Conclusions:
- A network-guided approach effectively identifies perturbed pathways in cancer, even with small datasets.
- This unbiased genome-wide analysis reveals key pathways and potential therapeutic targets in melanoma.
- The study underscores the importance of integrating SCNA and gene expression data with network analysis for cancer research.
