The association of increased lung resistance protein expression with acquired etoposide resistance in human H460 lung cancer cell lines

2006 ◽  
Vol 29 (11) ◽  
pp. 1018-1023 ◽  
Author(s):  
Eunmyong Lee ◽  
Soo-Jeong Lim
2016 ◽  
Vol 10 (1) ◽  
pp. 151-165 ◽  
Author(s):  
Zeineb Farhane ◽  
Franck Bonnier ◽  
Marcus Alexander Maher ◽  
Jane Bryant ◽  
Alan Casey ◽  
...  

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e14525-e14525
Author(s):  
Hui Yu ◽  
Maya Amar ◽  
Christopher J Rivard ◽  
Kim Ellison ◽  
Leslie Rozeboom ◽  
...  

e14525 Background: Immunotherapy has shown promising results in multiple forms of cancer including lung cancer patients. Treatment targeting alternative immune checkpoints may demonstrate value for specific cancers or in combination therapy with other immunotherapies or chemotherapeutic agents. While adenosine has physiological importance in preventing excess inflammatory reactions and inhibiting autoimmunity, it is generated through an enzymatic cascade in the tumor microenvironment whereby AMP is ultimately dephosphorylated to adenosine by CD73 on tumor cells. Previous studies have shown that increased tumor CD73 expression correlated with increased metastasis, worse prognosis and chemotherapy resistance. Methods: Genomic data from the CCLE and TCGA database were evaluated for CD73 expression in lung cancer. The specificity of an anti-CD73 antibody (Cell Signaling) was confirmed by Western blotting in lung cancer cell lines. Immunohistochemistry (IHC) was performed for FFPE lung cancer cell lines and a NSCLC patient cohort. CD73 expression data was correlated with patient demographic data including outcomes. Results: CD73 mRNA was expressed in lung cancer cell lines (70/126, 55.6%) and did not correlate with other immune checkpoint ligands including PD-L1, GAL-9, and B7H4 in NSCLC. Review of the TCGA database identified CD73 expression is highest in thyroid carcinoma and significant in lung cancer. The prevalence of CD73 protein expression by IHC in NSCLC cell lines was 84.8% (39/46) and 15.4% (6/39) in SCLC cell lines. We also evaluated CD73 protein expression in a NSCLC cohort with a prevalence of 32.1% (36/112), with no significant correlation to patient clinical characteristics or outcomes. Conclusions: We evaluated the expression of the immune checkpoint, CD73, in lung cancer cell lines and tissues. Both genomic data and protein expression by IHC demonstrated CD73 was significantly expressed. However, there was no correlation with other immune biomarkers or patient demographics or outcomes. CD73 is a new target for immunotherapy and current clinical studies with CD73 inhibitors may prove beneficial to lung cancer patients.


2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Yuan Chen ◽  
Kai Leonie Schnitzler ◽  
Yunxia Ma ◽  
Miljana Nenkov ◽  
Bernhard Theis ◽  
...  

Exploitation of autophagy might potentially improve therapeutic strategy. Here, we analyzed the protein expression of autophagy-associated genes including LC3A, LC3B, Beclin-1, p62, and Atg5 in 88–131 primary lung tumors by immunohistochemistry (IHC) on tissue-microarrays (TMAs). Additionally, the DNA methylation pattern of LC3A was investigated by bisulfite sequencing (BS) and methylation-specific-PCR (MSP). It turned out that the higher expression of LC3A protein was associated with adenocarcinoma compared to squamous cell carcinoma of lung (p=0.008), positive staining of LC3B was significantly related to tumor grade (p=0.006), and the protein expression of Beclin-1 was significantly correlated to pN stage (p=0.041). The expression of p62 and Atg5 was however not significantly associated with any clinicopathological parameters. Downregulation of LC3A was related to DNA methylation in lung cancer cell lines, while in primary lung tumor samples, protein expression of LC3A was not significantly correlated with DNA methylation, and the methylation status of LC3A was not related to clinicopathological features. Taken together, our results suggest that autophagy-associated proteins such as LC3A, LC3B, and Beclin-1 might be potential biomarkers for subclassification, differentiation, and local metastasis in primary lung tumor, and epigenetic mechanism is partially responsible for gene silencing of LC3A in lung cancer cell lines.


2017 ◽  
Vol 2017 ◽  
pp. 1-7 ◽  
Author(s):  
Kenichi Suda ◽  
Leslie Rozeboom ◽  
Koh Furugaki ◽  
Hui Yu ◽  
Mary Ann C. Melnick ◽  
...  

Despite the recent development of immunotherapies that target programmed death-1 (PD-1) or programmed death ligand-1 (PD-L1) in non-small cell lung cancer (NSCLC) treatment, these therapies are less effective in NSCLC patients with epidermal growth factor receptor (EGFR) mutations. However, the molecular mechanisms underlying this lower efficacy of immunotherapies in EGFR mutant lung cancers are still unclear. In this study, we analyzed PD-L1 protein expression in lung cancer cell lines with EGFR mutations prior to and after acquisition of resistance to EGFR tyrosine kinase inhibitors (TKIs). We found that parental lung cancer cell lines harboring EGFR mutations showed negative (PC9 and H3255 cells) and positive (HCC827 cells) staining for PD-L1 by immunohistochemistry. Comparing PD-L1 expression between EGFR-TKI resistant cell lines and their parental cells, we found that increased phosphorylation of EGFR was related to increased expression of PD-L1. Increased phosphorylation of EGFR was accompanied by the T790M secondary mutation. Acquired resistance cells with MET amplification or EGFR loss both showed decreased phosphorylation of EGFR and decreased PD-L1 expression. Our results indicate that lung cancer cell lines with EGFR mutations (parental cells) do not harbor high PD-L1 protein expression. In addition, EGFR phosphorylation affects PD-L1 expression after acquisition of resistance to EGFR-TKIs.


10.1038/87074 ◽  
2001 ◽  
Vol 27 (S4) ◽  
pp. 53-53
Author(s):  
Priya Dayananth ◽  
Terri McClanahan ◽  
Ferdous Gheyas ◽  
Marco Hernandez ◽  
Wei Ding ◽  
...  

Author(s):  
Angela Gradilone ◽  
Ida Silvestri ◽  
Susanna Scarpa ◽  
Stefania Morrone ◽  
Orietta Gandini ◽  
...  

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