Login / Signup

Molecular Classifiers in Skin Cancers: Challenges and Promises.

Ali AzimiPablo Fernandez-Penas
Published in: Cancers (2023)
Skin cancers are common and heterogenous malignancies affecting up to two in three Australians before age 70. Despite recent developments in diagnosis and therapeutic strategies, the mortality rate and costs associated with managing patients with skin cancers remain high. The lack of well-defined clinical and histopathological features makes their diagnosis and classification difficult in some cases and the prognostication difficult in most skin cancers. Recent advancements in large-scale "omics" studies, including genomics, transcriptomics, proteomics, metabolomics and imaging-omics, have provided invaluable information about the molecular and visual landscape of skin cancers. On many occasions, it has refined tumor classification and has improved prognostication and therapeutic stratification, leading to improved patient outcomes. Therefore, this paper reviews the recent advancements in omics approaches and appraises their limitations and potential for better classification and stratification of skin cancers.
Keyphrases
  • single cell
  • soft tissue
  • wound healing
  • machine learning
  • deep learning
  • mass spectrometry
  • high resolution
  • risk factors
  • climate change
  • risk assessment
  • human health