A supervised subtype differentiation learning for building invariant features of non-small cell lung cancer in a latent space of a Variational Autoencoder

2021 ◽  
Author(s):  
Fabian Cano ◽  
Charlens Alvarez-Jimenez ◽  
David Becerra ◽  
Andres Siabatto ◽  
Angel Cruz-Roa ◽  
...  
2016 ◽  
Vol 11 ◽  
pp. S123-S130
Author(s):  
Dujuan Yu ◽  
Ping Tan ◽  
Min Yu ◽  
Shaomin Shi ◽  
Xue Wang

The purpose of this study was to investigate the incidence and clinical significance of alterations in EGFR, IGF1R and the cell signaling pathway activities induced by them, as well as EGR1 expression in resected non-small cell lung cancer (NSCLC). The protein expressions of  biomarker were evaluated by Western blotting in tissues from 19 surgically resected NSCLCs. High expressions of EGR1, EGFR and  IGF1R were detected in more than 30% tumor tissues. High expressions of pErk and pAkt were detected in more than 50% paracancer tissues. There were significant correlations between the NSCLC target factors detected (p<0.05). Alterations of protein expressions of target factor detected in NSCLC were significantly associated with alterations in pathological subtype, differentiation, pathological stage, and smoking history. Positive EGR1 might be  associated with good survival, while positive pErk might be associated with poor prognosis. 


2016 ◽  
Vol 22 ◽  
pp. 176
Author(s):  
Genevieve Streb ◽  
Narjust Duma ◽  
Natasha Piracha ◽  
Sejal Kothadia ◽  
Komal Patel ◽  
...  

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