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Molecular Pathology of Pancreatic Cystic Lesions with a Focus on Malignant Progression.

Yan HuDan JonesAshwini Kumar EsnakulaSomashekar G KrishnaHui-Zi Chen
Published in: Cancers (2024)
The malignant progression of pancreatic cystic lesions (PCLs) remains understudied with a knowledge gap, yet its exploration is pivotal for effectively stratifying patient risk and detecting cancer at its earliest stages. Within this review, we delve into the latest discoveries on the molecular level, revealing insights into the IPMN molecular landscape and revised progression model, associated histologic subtypes, and the role of inflammation in the pathogenesis and malignant progression of IPMN. Low-grade PCLs, particularly IPMNs, can develop into high-grade lesions or invasive carcinoma, underscoring the need for long-term surveillance of these lesions if they are not resected. Although KRAS and GNAS remain the primary oncogenic drivers of neoplastic development in IPMNs, additional genes that are important in tumorigenesis have been recently identified by whole exome sequencing. A more complete understanding of the genes involved in the molecular progression of IPMN is critical for effective monitoring to minimize the risk of malignant progression. Complicating these strategies, IPMNs are also frequently multifocal and multiclonal, as demonstrated by comparative molecular analysis. Algorithms for preoperative cyst sampling and improved radiomic techniques are emerging to model this spatial and temporal genetic heterogeneity better. Here, we review the molecular pathology of PCLs, focusing on changes associated with malignant progression. Developing models of molecular risk stratification in PCLs which can complement radiologic and clinical features, facilitate the early detection of pancreatic cancer, and enable the development of more personalized surveillance and management strategies are summarized.
Keyphrases
  • high grade
  • low grade
  • public health
  • single molecule
  • oxidative stress
  • healthcare
  • gene expression
  • squamous cell carcinoma
  • single cell
  • deep learning
  • case report
  • lymph node
  • copy number
  • prognostic factors
  • dna methylation