Abstract
Melanoma researchers utilize cell lines to model many tumour phenomena. It is thus important to understand similarities and differences between cell lines and the tumours that they represent, so that the optimal models can be chosen to answer specific research questions. Herein, we compared the transcriptomes of 42 melanoma cell lines to hundreds of tumours from The Cancer Genome Atlas and thousands of single melanoma cells. Tumour purity was accounted for using the ESTIMATE algorithm, so that differences likely resulting from non-tumour cells could be accounted for. In addition, UV mutational signatures and the expression of skin-associated genes were analyzed in order to identify the putative origin of various cell lines. We found the transcriptional and mutational characteristics of melanoma cell lines to mirror those of the tumours, with the exception of immune-associated transcripts, which were absent in cell culture. We also determined cell lines that highly or poorly recapitulate melanomas and have identified colon (COLO 741) and lung (COLO 699) cancer cell lines that may actually be melanoma. In summary, this study represents a comprehensive comparison of melanoma cell lines and tumours that can be used as a guide for researchers when selecting melanoma cell line models.
Highlights
Human malignant melanoma is the most deadly form of skin cancer
Transcriptional profiles of melanoma cell lines generally resemble that of tumours, with a correlation coefficient of 0.91 for the mean expression of 20,460 coding genes (Figure 1a, Supplementary Figure 1)
This is in line with previous work that has recognized the high representation of amelanotic melanoma cell lines [16]
Summary
Human malignant melanoma is the most deadly form of skin cancer. It accounts for only 2% of skin cancer cases, it causes the majority of skin cancer deaths [1]. While highly treatable if detected early, metastatic melanoma has a five year survival rate of only 10-20% and it remains a aggressive form of cancer [4]. New targeted therapies, such as BRAF and immune checkpoint inhibitors, have achieved success in extending patient survival, innate or acquired therapy resistance and tumour recurrence is almost unavoidable [5, 6]. Modeling melanoma is paramount to understanding the molecular mechanisms behind melanoma tumourigenicity and therapy resistance
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