Overview of the signaling pathways involved in metastasis: An intriguing story-tale of the metastatic journey of ovarian cancer cells

Cell Mol Biol (Noisy-le-grand). 2021 Nov 25;67(3):212-223. doi: 10.14715/cmb/2021.67.3.34.

Abstract

Wealth of information has revolutionized our understanding related to the genetics and functional genomics of this heterogeneous disease. Keeping in view the heterogeneity of ovarian cancer, long-term survival might be achieved by translation of recently emerging mechanistic insights at the cellular and molecular levels to personalize individual strategies for treatment and to identify biomarkers for early detection. Importantly, the motility and invasive properties of ovarian cancer cells are driven by a repertoire of signaling cascades, many components of which have been experimentally verified as therapeutic targets in preclinical models as well as in clinical trials. Scientific evidence garnered over decades of research has deconvoluted the highly intricate intertwined network of intracellular signaling pathways which played fundamental role in carcinogenesis and metastasis. In this review we have provided a compendium of myriad of signaling cascades which have been documented to play critical role in the progression and metastasis of ovarian cancer. We have partitioned this multi-component review into different sections to individually discuss and summarize the roles of TGF/SMAD, JAK/STAT, Wnt/β-Catenin, NOTCH, SHH/GLI, mTORC1/mTORC2, VEGFR and Hippo/YAP pathways in ovarian cancer metastasis.

Publication types

  • Review

MeSH terms

  • Animals
  • Apoptosis / genetics
  • Biomarkers, Tumor / genetics*
  • Carcinogenesis / genetics
  • Disease Models, Animal
  • Female
  • Gene Expression Regulation, Neoplastic*
  • Gene Regulatory Networks / genetics*
  • Genomics / methods*
  • Humans
  • Models, Genetic
  • Neoplasm Metastasis
  • Ovarian Neoplasms / genetics*
  • Ovarian Neoplasms / pathology
  • Ovarian Neoplasms / therapy
  • Signal Transduction / genetics*

Substances

  • Biomarkers, Tumor