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. 2019 Aug 19;39(8):BSR20190827.
doi: 10.1042/BSR20190827. Print 2019 Aug 30.

Prognostic roles of the transcriptional expression of exportins in hepatocellular carcinoma

Lubiao Chen  1 , Yanlin Huang  1   2 , Liang Zhou  3 , Yifan Lian  2 , Jialiang Wang  2 , Dongmei Chen  2 , Huan Wei  2 , Mingsheng Huang  4 , Yuehua Huang  5   2
Affiliations

Prognostic roles of the transcriptional expression of exportins in hepatocellular carcinoma

Lubiao Chen et al. Biosci Rep. .

Abstract

Aims: A large number of studies have suggested that exportins (XPOs) play a pivotal role in human cancers. In the present study, we analyzed XPO mRNA expression in cancer tissues and explored their prognostic value in hepatocellular carcinoma (HCC).Methods: Transcriptional and survival data related to XPO expression in HCC patients were obtained through the ONCOMINE and UALCAN databases. Survival analysis plots were drawn with Gene Expression Profiling Interactive Analysis (GEPIA). Sequence alteration data for XPOs were obtained from The Cancer Genome Atlas (TCGA) database and c-BioPortal. Gene functional enrichment analyses were performed with Database for Annotation, Visualization and Integrated Discovery (DAVID).Results: Compared with normal liver tissues, significant XPO mRNA overexpression was observed in HCC cancer tissues. There was a trend of higher XPO expression in more advanced clinical stages and lower differentiated pathological grades of HCC. In HCC patients, high expression of XPO1, CSE1L, XPOT, XPO4/5/6 was related to poor overall survival (OS), and XPO1, CSE1L and XPO5/6 were correlated with poor disease-free survival (DFS). The main genetic alterations in XPOs involved mRNA up-regulation, DNA amplification and deletion. General XPO mutations were remarkably associated with worse OS and mostly affected the pathways of RNA transport and oocyte meiosis.Conclusion: High expression of XPOs was associated with a poor prognosis in HCC patients. XPOs may be exploited as good prognostic biomarkers for survival in HCC patients.

Keywords: Exportin; GEPIA; Hepatocellular carcinoma; ONCOMINE; Prognosis.

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Conflict of interest statement

All datasets used in the present study were retrieved from published literature, and written informed consent was obtained. The study protocol was approved by the Ethics Committee of The Third Affiliated Hospital of Sun Yat-sen University for Human Study and conducted according to the principles of the Declaration of Helsinki.

The authors declare that there are no competing interests associated with the manuscript.

Figures

Figure 1
Figure 1. XPO gene expression in 20 different cancer types
XPOs mRNA expression (cancer tissue vs. normal tissue) was analyzed using the ONCOMINE database. The numbers in colored cells show the quantities of datasets with statistically significant mRNA overexpression (red) or underexpression (blue) of target genes. Cell colors were determined by the best gene rank percentile for the analysis within cells. Analysis conditions required the following thresholds: gene rank percentile (10%), P-value (0.05) and fold change (1.5).
Figure 2
Figure 2. Transcription levels of XPOs in HCC cancer tissues and normal liver tissues
Expression panels for XPO1 (A), CSE1L (B), XPOT (C), XPO4 (D), XPO5 (E), XPO6 (F), and XPO7 (G) comparing the data between 50 normal individuals and 371 HCC patients in the TCGA database. ***P<0.001.
Figure 3
Figure 3. Relationship between XPO mRNA expression and HCC clinical stage
Expression panels for XPO1 (A), CSE1L (B), XPOT (C), XPO4 (D), XPO5 (E), XPO6 (F), and XPO7 (G) based on HCC cancer clinical stage comparing the data between 50 normal individuals and 371 HCC patients in the TCGA database. *P<0.05; **P<0.01; ***P<0.001.
Figure 4
Figure 4. Relationship between XPO mRNA expression and HCC pathological grade
Expression panels for XPO1 (A), CSE1L (B), XPOT (C), XPO4 (D), XPO5 (E), XPO6 (F), and XPO7 (G) based on HCC tumor grade comparing the data between 50 normal individuals and 371 HCC patients in the TCGA database. Pathological grading: Grade 1, well-differentiated; grade 2, moderately differentiated; grade 3, poorly differentiated and grade 4: undifferentiated. *P<0.05; **P<0.01; ***P<0.001.
Figure 5
Figure 5. OS difference based on XPO mRNA levels in HCC patients
High XPO1, CSE1L, XPOT and XPO4/5/6 (A–F) mRNA expression levels were remarkably associated with poor OS in HCC patients, while that of XPO7 (G) was not (P=0.08, borderline significance).
Figure 6
Figure 6. DFS difference based on XPO mRNA levels in HCC patients
High XPO1, CSE1L and XPO/5/6 (A,B,E,F) mRNA expression levels were associated with poor DFS in HCC patients, while those of XPOT/4 (C,D) were not and that of XPO7 (G) was uncertain (P=0.052, borderline significance).
Figure 7
Figure 7. XPO expression and mutation analysis in HCC
(A) OncoPrint in c-BioPortal showed the distribution and proportion of samples with alterations in XPOs. (B) XPO alterations were associated with worse OS in HCC patients. (C) XPO alterations did not correlate with DFS in HCC patients.
Figure 8
Figure 8. GO enrichment and KEGG pathway analyses of XPOs
(A) Networks constructed in c-BioPortal showed the interaction relationship between XPO1, CSE1L and the 50 most frequently altered neighboring genes. GO functional enrichment analysis predicted three main functions of the target genes: (B) biological process, (C) cellular components and (D) molecular functions. (E) KEGG pathway analysis of XPO1, CSE1L and their 50 most frequently altered neighboring genes.
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