Nuclear transport proteins are secreted by cancer cells and identified as potential novel cancer biomarkers

癌症 宫颈癌 癌症生物标志物 癌细胞 免疫印迹 癌症研究 生物 内科学 病理 医学 分子生物学 肿瘤科 免疫学 生物化学 基因
作者
Pauline J. van der Watt,Michael Okpara,Andrew Wishart,M. Iqbal Parker,Nelson C. Soares,Jonathan M. Blackburn,Virna D. Leaner
出处
期刊:International Journal of Cancer [Wiley]
卷期号:150 (2): 347-361 被引量:20
标识
DOI:10.1002/ijc.33832
摘要

Abstract Previous studies have identified increased expression of members of the nuclear transport protein family in cancer cells. Recently, certain nuclear transport proteins have been reported to be secreted by cells and found in the serum. The aims of our study were to investigate the levels of multiple nuclear transport proteins secreted from cancer cells, and to determine their potential as diagnostic markers for cervical and oesophageal cancer. Mass spectrometry identified 10 nuclear transport proteins in the secretome and exosomes of cultured cancer cells, and Western blot analysis confirmed increased secreted levels in cancer cells compared to normal. To investigate their presence in patient serum, enzyme‐linked immunosorbent assays were performed and revealed significantly increased levels of KPNβ1, CRM1, CAS, IPO5 and TNPO1 in cervical and oesophageal cancer patient serum compared to non‐cancer controls. Significantly elevated KPNα2 and RAN levels were also identified in oesophageal cancer serum samples. Logistics regression analyses revealed IPO5 and TNPO1 to be the best performing individual candidate biomarkers in discriminating between cancer cases and controls. The combination of KPNβ1, CRM1, KPNα2, CAS, RAN, IPO5 and TNPO1 as a panel of biomarkers had the highest diagnostic capacity with an area under the curve of 0.944 and 0.963, for cervical cancer and oesophageal cancer, and sensitivity of 92.5% at 86.8% specificity and 95.3% sensitivity at 87.5% specificity, respectively. These results suggest that nuclear transport proteins have potential as diagnostic biomarkers for cervical and oesophageal cancers, with a combination of protein family members being the best predictor.
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