| Summary: | 博士 === 長庚大學 === 生物醫學研究所 === 100 === Lung cancer is one of the most prominent causes of cancer death over the world. It is emergent to find a good biomarkers for diagnosis and prognosis for lung cancer. Herein, we identified karyopherin subunit alpha-2 (KPNA2) was a potential biomarker for non-small cell lung cancer (NSCLC) by integration of the cancer cell secretome and tissue transcriptome datasets. Immunohistochemical staining revealed overexpression of KPNA2 in the nuclei of tumor cells, compared with adjacent normal cells. A sandwich ELISA assay developed to detect KPNA2 levels in serum samples showed significantly higher serum KPNA2 in NSCLC patients than in healthy controls. Knockdown of KPNA2 suppressed the proliferation and migration abilities of lung cancer cells. However, the precise molecular mechanisms underlying KPNA2 activity in cancer remain to be established. Therefore, we applied gene knockdown, subcellular fractionation and stable isotope labeling by amino acids in cell culture (SILAC)-based quantitative proteomic strategies to systematically analyze the KPNA2-regulating protein profiles in an adenocarcinoma cell line. Interaction network analysis revealed that several KPNA2-regulating proteins are involved in the cell cycle, DNA metabolic process, cellular component movements and cell migration. Importantly, E2F1 was identified as a potential novel cargo of KNAP2 in the nuclear proteome. The mRNA levels of potential effectors of E2F1 measured using quantitative PCR indicated that E2F1 is one of the "master molecule" responses to KPNA2 knockdown. Immunofluorescence staining and immunoprecipitation assays disclosed co-localization and association between E2F1 and KPNA2. An in vitro protein binding assay further demonstrated that E2F1 interacts directly with KPNA2. Moreover, knockdown of KPNA2 led to subcellular redistribution of E2F1 in lung cancer cells. Our results collectively suggest that integration of the cancer cell secretome and transcriptome datasets provides an efficient means of identifying novel accessible biomarkers for NSCLC, such as KPNA2 and we demonstrate the utility of quantitative proteomic approaches and provide a fundamental platform to further explore the biological roles of KPNA2 in NSCLC.
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