Elevated Expression of HMGA1 Correlates with the Malignant Status and Prognosis of Non-small Cell Lung Cancer

Overview

Journal Tumour Biol

Publisher Sage Publications

Specialty Oncology

Date 2014 Oct 26

PMID 25344216

Citations 26

Authors

Ze Zhang

Quan Wang

Feng Chen

Jun Liu

Affiliations

Soon will be listed here.

Abstract

High-mobility group A1 (HMGA1) has been suggested to play a significant role in tumor progression, but little is known about the accurate significance of HMGA1 in non-small cell lung cancer (NSCLC) patients. The aim of this study was to identify the role of HMGA1 in NSCLC. The expression status of HMGA1 was observed initially in NSCLC by Gene Expression Omnibus (GEO). The expression of HMGA1 messenger RNA (mRNA) and protein was examined in NSCLC and adjacent normal lung tissues through real-time PCR and immunohistochemistry. Meanwhile, the relationship of HMGA1 expression levels with clinical features and prognosis of NSCLC patients was analyzed. In our results, HMGA1 was overexpressed in NSCLC tissues compared with adjacent normal lung tissues in microarray data (GSE19804). HMGA1 mRNA and protein expressions were markedly higher in NSCLC tissues than in normal lung tissues (P < 0.001 and P = 0.010, respectively). Using immunohistochemistry, high levels of HMGA1 protein were positively correlated with the status of clinical stage (I-II vs. III-IV, P < 0.001), T classification (T1-T vs. T3-T4, P = 0.003), N classification (N0N1 vs. N2-N3, P < 0.001), M classification (M0 vs. M1, P = 0.002), and differentiated degree (high or middle vs. low or undifferentiated, P = 0.003) in NSCLC. Patients with higher HMGA1 expression had a significantly shorter overall survival time than did patients with low HMGA1 expression. Multivariate analysis indicated that the level of HMGA1 expression was an independent prognostic factor (P < 0.001) for the survival of patients with NSCLC. In conclusion, HMGA1 plays an important role on NSCLC progression and prognosis and may act as a convictive biomarker for prognostic prediction.

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