Status of Anti-Lung Cancer Drug Patents Applications in China from 2003 to 2012

2014 ◽  
Vol 9 (2) ◽  
pp. 221-240 ◽  
Author(s):  
Da-ming Chen ◽  
Kai-yun Mao ◽  
Lu Yang ◽  
Hong-bo Jiang
Keyword(s):  
2021 ◽  
Vol 11 ◽  
pp. 100151
Author(s):  
Qiaofeng Zhong ◽  
Yunxia Tao ◽  
Haizhu Chen ◽  
Yu Zhou ◽  
Liling Huang ◽  
...  

Micromachines ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 624
Author(s):  
Qiang Liu ◽  
Tian Zhao ◽  
Xianning Wang ◽  
Zhongyao Chen ◽  
Yawei Hu ◽  
...  

Three-dimensional cultured patient-derived cancer organoids (PDOs) represent a powerful tool for anti-cancer drug development due to their similarity to the in vivo tumor tissues. However, the culture and manipulation of PDOs is more difficult than 2D cultured cell lines due to the presence of the culture matrix and the 3D feature of the organoids. In our other study, we established a method for lung cancer organoid (LCO)-based drug sensitivity tests on the superhydrophobic microwell array chip (SMAR-chip). Here, we describe a novel in situ cryopreservation technology on the SMAR-chip to preserve the viability of the organoids for future drug sensitivity tests. We compared two cryopreservation approaches (slow freezing and vitrification) and demonstrated that vitrification performed better at preserving the viability of LCOs. Next, we developed a simple procedure for in situ cryopreservation and thawing of the LCOs on the SMAR-chip. We proved that the on-chip cryopreserved organoids can be recovered successfully and, more importantly, showing similar responses to anti-cancer drugs as the unfrozen controls. This in situ vitrification technology eliminated the harvesting and centrifugation steps in conventional cryopreservation, making the whole freeze–thaw process easier to perform and the preserved LCOs ready to be used for the subsequent drug sensitivity test.


1980 ◽  
Vol 64 (6) ◽  
pp. 1337-1343 ◽  
Author(s):  
Seth A. Rudnick ◽  
Alvan R. Feinstein
Keyword(s):  

Author(s):  
Mariana Magalhães ◽  
Francisco Veiga ◽  
Ana Figueiras ◽  
Ana Cláudia Santos

2021 ◽  
Author(s):  
Rizwan Qureshi

This is a review paper for the analysis and prediction of lung cancer drug resistance. We explore several computational methods, that can provide, biological insights for the analysis, visualization and prediction of lung cancer drug resistance.


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