Oral Presentation Australasian Society for Dermatology Research 2022 Annual Scientific Meeting

Use spatial transcriptomics to study tumor predictors in patients with early invasive melanoma (#105)

Chenhao Zhou 1 , Samuel X Tan 1 , Yung-Ching Kao 1 , Magdalena Claeson 2 , Susan Brown 1 , Duncan Lambie 3 , David C Whiteman 2 , H Peter Soyer 1 , Mitchell S Stark 1 , Quan Nguyen 4 , Kiarash Khosrotehrani 1
  1. The University of Queensland Diamantina Institute, Translational Research Institute, Woolloongabba, QLD, Australia
  2. QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
  3. Princess Alexandra Hospital, Brisbane, QLD, Australia
  4. Institute for Molecular Bioscience, The University of Queensland, St Lucia, QLD, Australia

Early invasive melanomas, despite their excellent prognosis, account for the majority of melanoma deaths. There is currently a lack of accurate clinical and pathological predictors to identify which patients, with early invasive melanomas, are at the highest risk of disease progression. The recent advances in spatial transcriptomic technologies allow unbiased discovery of key gene and spatial biomarkers controlling the fate of tumorigenesis. Using the 10x Genomics Visium platform, we examined spatially resolved transcriptome profiles of archived FFPE tissues derived from 40 locally invasive thin (<1mm) melanoma patients (20 pairs of fatal cases and nonfatal controls matched for age, sex, year of diagnosis, length of follow-up and tumour thickness) in a well-established and annotated QLD Cancer Registry population cohort. We identified a list of differentially expressed genes associated with patient survival. In particular, case tumours show increased expression of EMT and TNFα signalling-associated genes and decreased expression of antigen processing and presentation (APP)-related genes when compared to control tumours. Interestingly, EMThi tumours and APPhi tumours were located in close proximity to fibroblast and myeloid cell infiltrate respectively, implying that different cross-talks between tumour cells and non-tumour cells could be one major contributor to modulate tumour microenvironment and determine the fate of tumour progression. Further analysis will focus on integrating multiple candidate features and validating them to identify best predictive scenarios for patient survival that can progress into the clinic.