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The PI3K/Akt/mTOR axis in colorectal cancer: Oncogenic alterations, non-coding RNAs, therapeutic opportunities, and the emerging role of nanoparticles.

Mohammad-Javad SanaeiAyda Baghery Saghchy KhorasaniAtieh Pourbagheri-SigaroodiShabnam ShahrokhMohammad Reza ZaliSoroush Sadeghi
Published in: Journal of cellular physiology (2021)
Colorectal cancer (CRC) is one of the deadliest human malignancies worldwide. Several molecular pathways have been demonstrated to be involved in the initiation and development of CRC which among them, the overactivation of the phosphatidyl-inositol 3-kinase (PI3K)/Akt/mTOR axis is of importance. The current review aims to unravel the mechanisms by which the PI3K/Akt/mTOR pathway affects CRC progression; and also, to summarize the original data obtained from international research laboratories on the oncogenic alterations and polymorphisms affecting this pathway in CRC. Besides, we provide a special focus on the regulatory role of noncoding RNAs targeting the PI3K/Akt/mTOR pathway in this malignancy. Questions on how this axis is involved in the inhibition of apoptosis, in the induction of drug resistance, and the angiogenesis, epithelial to mesenchymal transition, and metastasis are also responded. We also discussed the PI3K/Akt pathway-associated prognostic and predictive biomarkers in CRC. In addition, we provide a general overview of PI3K/Akt/mTOR pathway inhibition whether by chemical-based drugs or by natural-based medications in the context of CRC, either as monotherapy or in combination with other therapeutic agents; however, those treatments might have life-threatening side effects and toxicities. To the best of our knowledge, the current review is one of the first ones highlighting the emerging roles of nanotechnology to overcome challenges related to CRC therapy in the hope that providing a promising platform for the treatment of CRC.
Keyphrases
  • endothelial cells
  • transcription factor
  • healthcare
  • oxidative stress
  • cell death
  • stem cells
  • high throughput
  • combination therapy
  • cell proliferation
  • machine learning
  • big data
  • protein kinase