| Literature DB >> 30537941 |
Yibing Chen1, Jingjing Zhao2, Zhihui Jiao1, Weiwei Wang3, Dandan Wang4, Xiaohe Yu5, Zhiyong Shi5, Naijian Ge5, Qiuzhong Pan2, Jianchuan Xia2, Wancheng Niu6, Ruihua Zhao7, Xiaofei Zhang8, Wei Du9.
Abstract
BACKGROUND: SKA1, an important mitosis protein, has been indicated in the initiation and progression of several malignancies. However, its clinical significance in hepatocellular carcinoma (HCC) remain to be elucidated.Entities:
Keywords: Gene profiling; Hepatocellular carcinoma; Oncofetal gene; Prognosis; SKA1
Mesh:
Substances:
Year: 2018 PMID: 30537941 PMCID: PMC6288885 DOI: 10.1186/s12885-018-5119-6
Source DB: PubMed Journal: BMC Cancer ISSN: 1471-2407 Impact factor: 4.430
Association of SKA1 expression in tumor tissues with characteristics of HCC patients
| Variables |
| SKA1 expression | ||
|---|---|---|---|---|
| Positive Negative | ||||
| All cases | 126 | 65 | 61 | |
| Gender | 0.317 | |||
| Female | 13 | 5 | 8 | |
| Male | 113 | 60 | 53 | |
| Age (year) | 0.457 | |||
| < 53 | 60 | 33 | 27 | |
| ≥ 53 | 66 | 32 | 34 | |
| Tumor size (cm) | 0.002 | |||
| < 5 | 63 | 24 | 39 | |
| ≥ 5 | 63 | 41 | 22 | |
| Differentiation | 0.155 | |||
| Well to moderate | 34 | 14 | 20 | |
| Poor | 92 | 51 | 41 | |
| HBsAg | 0.272 | |||
| Positive | 114 | 57 | 57 | |
| Negative | 12 | 8 | 4 | |
| Serum AFP (μg/L) | 0.035 | |||
| ≥ 200 | 74 | 44 | 30 | |
| < 200 | 52 | 21 | 31 | |
| TNM stage | 0.009 | |||
| I + II | 92 | 41 | 51 | |
| III + IV | 34 | 24 | 10 | |
AFP, α-fetoprotein; HBsAg, hepatitis B virus surface antigen; HCC, hepatocellular carcinoma
Fig. 1Elevated SKA1 mRNA level in HCC tissues. a, Relative mRNA expression levels in 126 paired HCC and pericancer tissues determined by real-time PCR in our study. b, mRNA expressions determined by RNA profiling in TCGA database
Fig. 2SKA1 expression in HCC tissues by IHC staining. a, intensive SKA1 staining in tumor tissues. b: moderate SKA1 staining in tumor staining. c, negative SKA1 staining in non-neoplastic liver tissues. d, proportion of different SKA1 staining in tumor and non-neoplastic tissues
Fig. 3Kaplan-Meier survival curves of HCC patients by SKA expression in tumor tissues. a, OS curves stratified by SKA1 expression. b, RFS curves stratified by SKA1 expression
Cox regression analysis of prognostic factors for HCC patients
| Variables | OS | RFS | ||||||
|---|---|---|---|---|---|---|---|---|
| Univariate analysis | Multivariate analysis | Univariate analysis | Multivariate analysis | |||||
| HR (95% CI) |
| HR (95% CI) |
| HR (95% CI) |
| HR (95% CI) |
| |
| Gender(male/female) | 1.355 (0.537–3.416) | 0.520 | 1.621 (0.652–4.031) | 0.299 | ||||
| Age (> 53/≤53 years) | 1.446 (0.827–2.527) | 0.195 | 1.990 (1.970–2.011) | 0.454 | ||||
| Tumor size (> 5/≤5 cm) | 2.275 (1.296–3.994) | 0.004 | 2.603 (1.583–4.281) | 0.001 | ||||
| Differentiation (poor/well to moderate) | 1.835 (0.954–3.530) | 0.069 | 1.213 (0.721–2.040) | 0.466 | ||||
| HBsAg (positive/negative) | 1.323 (0.526–3.328) | 0.552 | 1.147 (0.524–2.509) | 0.731 | ||||
| AFP (≥200/< 200 μg/L) | 1.000 (1.081–3.281) | 0.025 | 1.395 (0.782–2.489) | 0.260 | 1.912 (1.183–3.090) | 0.008 | 1.449 (0.857–2.450) | 0.167 |
| TNM stage (III + IV/I + II) | 1.516 (1.156–1.987) | 0.003 | 1.962 (1.196–3.684) | 0.031 | 1.688 (1.337–3.131) | 0.001 | 1.472 (1.131–1.916) | 0.004 |
| SKA1 expression (positive/negative) | 2.497 (1.380–4.516) | 0.002 | 2.133 (1.145–3.974) | 0.017 | 1.974 (1.208–3.224) | 0.007 | 1.750 (1.064–2.878) | 0.028 |
AFP, α-fetoprotein; CI, confidence interval, HBsAg; hepatitis B virus surface antigen; HCC, hepatocellular carcinoma; HR, hazard ratio; OS, overall survival; RFS, relapse-free survival
Fig. 4Gene profiling analysis of four types of sample including high SKA1, low SKA1, fetal liver and hepatocytes (adult liver) based on microarray data. The dendrogram and heatmap (a) show the hierarchical cluster analysis of gene-expression data from human specimens of hepatocytes, fetal liver and HCC tissues. Columns represent individual samples, and rows represent individual genes. Each cell in the matrix represents the expression level of a gene in an individual sample. The scale bar indicates the level of expression, red indicates a high level of expression, and green a low level of expression. GSEA analysis showed that genes upregulated in high SKA1 HCC enriched in the cell cycle pathway (b), while genes down-regulated in the high SKA1 HCC were enriched in the apoptosis pathway (c). NES denotes normalized enrichment score in gene set enrichment analysis. The ranked list metric was generated by calculating the signal-to-noise ratio which is based on the difference of means scaled according to the standard deviation. The larger the signal-to-noise ratio, the more distinct the gene expression is in each phenotype and the more the gene acts as a “class marker.” The bar codes stand for genes in the pathway. The Broad Institute Gene Set Enrichment Analysis website (http://software.broadinstitute.org/gsea/index.jsp) provides detailed information about the computational method