scholarly journals Artificial intelligence, molecular subtyping, biomarkers, and precision oncology

Author(s):  
John Paul Shen

A targeted cancer therapy is only useful if there is a way to accurately identify the tumors that are susceptible to that therapy. Thus rapid expansion in the number of available targeted cancer treatments has been accompanied by a robust effort to subdivide the traditional histological and anatomical tumor classifications into molecularly defined subtypes. This review highlights the history of the paired evolution of targeted therapies and biomarkers, reviews currently used methods for subtype identification, and discusses challenges to the implementation of precision oncology as well as possible solutions.

Author(s):  
Zhen Luo ◽  
Yujuan Gao ◽  
Zhongyu Duan ◽  
Yu Yi ◽  
Hao Wang

Mitochondria are well known to serve as the powerhouse for cells and also the initiator for some vital signaling pathways. A variety of diseases are discovered to be associated with the abnormalities of mitochondria, including cancers. Thus, targeting mitochondria and their metabolisms are recognized to be promising for cancer therapy. In recent years, great efforts have been devoted to developing mitochondria-targeted pharmaceuticals, including small molecular drugs, peptides, proteins, and genes, with several molecular drugs and peptides enrolled in clinical trials. Along with the advances of nanotechnology, self-assembled peptide-nanomaterials that integrate the biomarker-targeting, stimuli-response, self-assembly, and therapeutic effect, have been attracted increasing interest in the fields of biotechnology and nanomedicine. Particularly, in situ mitochondria-targeted self-assembling peptides that can assemble on the surface or inside mitochondria have opened another dimension for the mitochondria-targeted cancer therapy. Here, we highlight the recent progress of mitochondria-targeted peptide-nanomaterials, especially those in situ self-assembly systems in mitochondria, and their applications in cancer treatments.


Cancers ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 940 ◽  
Author(s):  
So Yun Lee ◽  
Moon Sung Kang ◽  
Woo Yeup Jeong ◽  
Dong-Wook Han ◽  
Ki Su Kim

Hyaluronic acid (HA) is a natural mucopolysaccharide and has many useful advantages, including biocompatibility, non-immunogenicity, chemical versatility, non-toxicity, biodegradability, and high hydrophilicity. Numerous tumor cells overexpress several receptors that have a high binding affinity for HA, while these receptors are poorly expressed in normal body cells. HA-based drug delivery carriers can offer improved solubility and stability of anticancer drugs in biological environments and allow for the targeting of cancer treatments. Based on these benefits, HA has been widely investigated as a promising material for developing the advanced clinical cancer therapies in various formulations, including nanoparticles, micelles, liposomes, and hydrogels, combined with other materials. We describe various approaches and findings showing the feasibility of improvement in theragnosis probes through the application of HA.


2021 ◽  
Vol 12 ◽  
Author(s):  
Meng Sun ◽  
Ting Wang ◽  
Leijiao Li ◽  
Xiangyang Li ◽  
Yutong Zhai ◽  
...  

Epidermal growth factor receptor (EGFR) is an anticancer drug target for a number of cancers, such as non-small cell lung cancer. However, unsatisfying treatment effects, terrible side-effects, and development of drug resistance are current insurmountable challenges of EGFR targeting treatments for cancers. With the advancement of nanotechnology, an increasing number of inorganic nanomaterials are applied in EGFR-mediated therapy to improve those limitations and further potentiate the efficacy of molecular targeted cancer therapy. Given their facile preparation, easy modification, and biosecurity, inorganic nanoparticles (iNPs) have been extensively explored in cancer treatments to date. This review presents an overview of the application of some typical metal nanoparticles and nonmetallic nanoparticles in EGFR-targeted therapy, then discusses and summarizes the relevant advantages. Moreover, we also highlight future perspectives regarding their remaining issues. We hope these discussions inspire future research on EGFR-targeted iNPs.


2015 ◽  
Vol 22 (11) ◽  
pp. 1335-1347 ◽  
Author(s):  
Yan Gao ◽  
Jacson Shen ◽  
Lara Milane ◽  
Francis Hornicek ◽  
Mansoor Amiji ◽  
...  

2014 ◽  
Vol 20 (32) ◽  
pp. 5218-5244 ◽  
Author(s):  
A. Aerts ◽  
N.R.E.N. Impens ◽  
M. Gijs ◽  
M. D'Huyvetter ◽  
H. Vanmarcke ◽  
...  

2011 ◽  
Vol 11 (10) ◽  
pp. 983-992 ◽  
Author(s):  
Arthur E. Frankel ◽  
Carol Carter ◽  
Shu-Ru Kuo ◽  
Jung-Hee Woo ◽  
Jeremy Mauldin ◽  
...  

2014 ◽  
Vol 3 (2) ◽  
pp. 83-88 ◽  
Author(s):  
Maria Gazouli ◽  
Nikolitsa Nomikou ◽  
John F Callan ◽  
Efstathios P. Efstathopoulos

Author(s):  
Stephen R. Barley

The four chapters of this book summarize the results of thirty-five years dedicated to studying how technologies change work and organizations. The first chapter places current developments in artificial intelligence into the historical context of previous technological revolutions by drawing on William Faunce’s argument that the history of technology is one of progressive automation of the four components of any production system: energy, transformation, and transfer and control technologies. The second chapter lays out a role-based theory of how technologies occasion changes in organizations. The third chapter tackles the issue of how to conceptualize a more thorough approach to assessing how intelligent technologies, such as artificial intelligence, can shape work and employment. The fourth chapter discusses what has been learned over the years about the fears that arise when one sets out to study technical work and technical workers and methods for controlling those fears.


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