Cutaneous squamous cell carcinoma (cSCC) is the most common lethal malignancy, with most deaths caused by metastasis or local progression. Despite this high disease burden, there are no biomarkers to predict disease progression and no established therapeutic molecular targets. This is reflective of the high genomic complexity of cSCC, which possesses the highest tumour mutational burden of all cancers (~240 mutations/Mb), dominated by a UV signature of C>T transitions across both coding and non-coding regions.
However, our understanding of the cSCC genome to date is derived only from data obtained using short-read, PCR-dependent sequencing technologies. While these are highly sensitive in identifying single nucleotide polymorphisms, short-read sequencing is limited in its ability to elucidate larger scale structural variations and alterations in repetitive regions. Given there is increasing evidence supporting the role of these large structural variations in driving progression and predicting prognosis in other cancers including prostate and renal carcinomas, the use of long-read sequencing technologies capable of capturing such alterations is a glaring deficiency in the study of high risk and metastatic cSCC.
To this end, we directly compared the whole genome of metastatic cSCC specimens obtained from short-read (NGS, Illumina) and long-read (Oxford Nanopore Technologies, PromethION) tumour-normal sequencing platforms. We describe, for the first time, a long-read characterisation of a metastatic cSCC genome taken from 150 Gb reads with an N50 greater than 15 kb, with a focus on structural variation. In addition, long-read sequencing of the novel cell line we derived from this same tumour illustrates retention of structural variation in vitro, which validates the genomic recapitulative value of our novel cell model. Together, our results demonstrate the potential of long-read sequencing in further understanding the complexity of metastatic cSCC. This emphasises the importance of selecting appropriate and diverse sequencing technologies to comprehensive characterise whole cancer genomes.