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Integrated Transcriptome Analysis Reveals KLK5 and L1CAM Predict Response to Anlotinib in NSCLC at 3rd Line.


ABSTRACT: The oral multi-targeted tyrosine kinase inhibitor (TKI) anlotinib is effective for non-small cell lung cancer (NSCLC) in clinical trials at 3rd line. However, a fraction of patients remains non-responsive, raising the need of how to identify anlotinib-responsive patients. In the present study, we aimed to screen potential biomarkers for anlotinib-responsive stratification via integrated transcriptome analysis. Comparing with the anlotinib-sensitive lung cancer cell NCI-H1975, we found 1,315 genes were differentially expressed in anlotinib-resistant NCI-H1975 cells. Among the enriched angiogenesis-related genes, we observed high expression of KLK5 and L1CAM was mostly associated with poor clinical outcomes in NSCLC patients through Kaplan-Meier survival analysis in a TCGA cohort. Moreover, an independent validation in a cohort of ALTER0303 (NCT02388919) indicated that high serum levels of KLK5 and L1CAM were also associated with poor anlotinib response in NSCLC patients at 3rd line. Lastly, we demonstrated that knockdown of KLK5 and L1CAM increases anlotinib-induced cytotoxicity in anlotinib-resistant NCI-H1975 cells. Collectively, our study suggested serum levels of KLK5 and L1CAM potentially serve as biomarkers for anlotinib-responsive stratification in NSCLC patients at 3rd line.

SUBMITTER: Lu J 

PROVIDER: S-EPMC6749025 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Integrated Transcriptome Analysis Reveals KLK5 and L1CAM Predict Response to Anlotinib in NSCLC at 3rd Line.

Lu Jun J   Shi Qin Q   Zhang Lele L   Wu Jun J   Lou Yuqing Y   Qian Jie J   Zhang Bo B   Wang Shuyuan S   Wang Huimin H   Zhao Xiaodong X   Han Baohui B  

Frontiers in oncology 20190911


The oral multi-targeted tyrosine kinase inhibitor (TKI) anlotinib is effective for non-small cell lung cancer (NSCLC) in clinical trials at 3rd line. However, a fraction of patients remains non-responsive, raising the need of how to identify anlotinib-responsive patients. In the present study, we aimed to screen potential biomarkers for anlotinib-responsive stratification via integrated transcriptome analysis. Comparing with the anlotinib-sensitive lung cancer cell NCI-H1975, we found 1,315 gene  ...[more]

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