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MUC16overexpression induced by gene mutations promotes lung cancer cell growth and invasion

Overview of attention for article published in Oncotarget, January 2018
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MUC16overexpression induced by gene mutations promotes lung cancer cell growth and invasion
Published in
Oncotarget, January 2018
DOI 10.18632/oncotarget.24203
Pubmed ID

Madiha Kanwal, Xiao-Jie Ding, Xin Song, Guang-Biao Zhou, Yi Cao


Air pollution is one of the leading causes of lung cancer. Air pollution-related lung cancer is a deteriorating public health problem, particularly in developing countries. The MUC16 gene is one of the most frequently mutated genes in air pollution-related lung cancer. In the present study, MUC16 mRNA expression was increased in ∼50% of air pollution-related lung cancer samples obtained from patients residing in air-polluted regions (Xuanwei and Fuyuan, Yunnan, China), and MUC16 mRNA levels were correlated with the degree of air pollution. Furthermore, sequencing of the captured MUC16 gene identified 561 mutation sites within the MUC16 gene in the air pollution-related lung cancer tissues. Interestingly, some mutations at specific sites and one region were associated with MUC16 mRNA up-regulation. Therefore, we further investigated the impacts of gene mutation on MUC16 expressions and cell behaviors in cultured cells by inducing certain mutations within the MUC16 gene using CRISPER/Cas9 genome editing technology. Certain mutations within the MUC16 gene induced MUC16 overexpression at both the mRNA and the protein level in the cultured cells. Additionally, MUC16 overexpression induced by gene mutations had functional effects on the behavior of lung cancer cells, including increasing their resistance to cisplatin, promoting their growth, and enhancing their migration and invasion capabilities. Based on the data, we suggest that MUC16 mutations potentially associated with air pollution may participate in the development and progression of air pollution-related lung cancer. In addition to ovarian cancer, MUC16 may be a candidate biomarker for lung cancer.

Mendeley readers

The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 30 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 23%
Researcher 4 13%
Student > Bachelor 3 10%
Student > Doctoral Student 3 10%
Professor > Associate Professor 2 7%
Other 2 7%
Unknown 9 30%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 11 37%
Medicine and Dentistry 4 13%
Business, Management and Accounting 1 3%
Nursing and Health Professions 1 3%
Social Sciences 1 3%
Other 1 3%
Unknown 11 37%