The increased skin cancer incidence in organ transplant recipients is well-known, but the skin cancer burden at any one time is unknown. Our objective was to estimate the period prevalence of untreated skin malignancy and actinic keratoses in high-risk kidney and liver transplant recipients and to assess associated factors. Organ transplant recipients underwent full skin examinations by dermatologically trained physicians. The proportion of examined organ transplant recipients with histopathologically confirmed skin cancer in the 3-month baseline period was estimated. Prevalence ratios with 95% confidence intervals indicated significant associations. Of 495 high-risk organ transplant recipients (average age = 54 years, time immunosuppressed = 8.9 years), 135 (27%) had basal cell carcinoma, squamous cell carcinoma or Bowen's disease (intraepidermal carcinoma) present and confirmed in the baseline period, with respective prevalence proportions of 10%, 11%, and 18% in kidney transplant recipients and 10%, 9%, and 13% in liver transplant recipients. Over 80% had actinic keratosis present, with approximately 30% having 5 or more actinic keratoses. Organ transplant recipients with the highest skin cancer burden were Australian born, were fair skinned (prevalence ratio = 1.61, 95% confidence interval = [1.07, 2.43]), reported past skin cancer (prevalence ratio =3.39, 95% confidence interval = [1.93, 5.95]), and were receiving the most frequent skin checks (prevalence ratio = 1.76, 95% confidence interval = [1.15, 2.70]). In conclusion, high-risk organ transplant recipients carry a substantial measurable skin cancer burden at any given time and require frequent review through easily accessible, specialized services.

Identification of appropriate reference genes (RGs) is critical to accurate data interpretation in quantitative real-time PCR (qPCR) experiments. In this study, we have utilised next generation RNA sequencing (RNA-seq) to analyse the transcriptome of a panel of non-melanoma skin cancer lesions, identifying genes that are consistently expressed across all samples. Genes encoding ribosomal proteins were amongst the most stable in this dataset. Validation of this RNA-seq data was examined using qPCR to confirm the suitability of a set of highly stable genes for use as qPCR RGs. These genes will provide a valuable resource for the normalisation of qPCR data for the analysis of non-melanoma skin cancer.