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Risk Stratification of Pancreatic Neuroendocrine Neoplasms Based on Clinical, Pathological, and Molecular Characteristics.

Young Hoon ChoiWoo Hyun Paik
Published in: Journal of clinical medicine (2022)
Pancreatic neuroendocrine neoplasms consist of heterogeneous diseases. Depending on the novel features detected by various modern technologies, their classification and related prognosis predictions continue to change and develop. The role of traditional clinicopathological prognostic factors, including classification systems, is also being refined, and several attempts have been made to predict a more accurate prognosis through novel serum biomarkers, genetic factors, and epigenetic factors that have been identified through various state-of-the-art molecular techniques with multiomics sequencing. In this review article, the latest research results including the traditional approach to prognostic factors and recent advanced strategies for risk stratification of pancreatic neuroendocrine neoplasms based on clinical, pathological, and molecular characteristics are summarized. Predicting prognosis through multi-factorial assessments seems to be more efficacious, and prognostic factors through noninvasive methods are expected to develop further advances in liquid biopsy in the future.
Keyphrases
  • prognostic factors
  • machine learning
  • deep learning
  • dna methylation
  • gene expression
  • single molecule
  • genome wide
  • high resolution
  • ionic liquid
  • mass spectrometry