|Year : 2017 | Volume
| Issue : 4 | Page : 651-659
Kinesin superfamily protein expression and its association with progression and prognosis in hepatocellular carcinoma
Jianliang Chen1, Shu Li2, Shu Zhou2, Shouji Cao2, Yun Lou2, Haiyuan Shen2, Jie Yin3, Guoqiang Li2
1 Department of General Surgery, People' Hospital, Jingjiang 214500; Department of Liver Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210009; Department of Liver Surgery, Key Laboratory of Living Donor Liver Transplantation of Ministry of Public Health, Nanjing 210009, China
2 Department of Liver Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210009; Department of Liver Surgery, Key Laboratory of Living Donor Liver Transplantation of Ministry of Public Health, Nanjing 210009, China
3 Department of Respiratory Medicine, Jinling Hospital, Nanjing 210002, Jiangsu Province, China
|Date of Web Publication||13-Sep-2017|
Department of General Surgery, First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing 210029, Jiangsu Province
Source of Support: None, Conflict of Interest: None
Objectives: In this study, we characterized the expression of 32 other kinesin superfamily proteins (KIFs) and analyzed their association with the progression and prognosis of hepatocellular carcinoma (HCC).
Materials and Methods: The data from 295 HCC patients from The Cancer Genome Atlas were included in the study. An independent t-test was used to compare the KIF levels in HCC and adjacent tissues. Pearson's Chi-square test was used to assess the relationships of KIF expression with tumor biomarkers and clinicopathological parameters. Kaplan–Meier plots and log-rank tests were used to analyze survival, and univariate and multivariate analyses were used to identify independent prognostic factors.
Results: The expressions of 32 KIFs were compared between HCC and adjacent nontumor tissues. Among them, 12 KIFs showed no statistical significance, 17 KIFs were upregulated, and three KIFs were downregulated in tumor tissues. The levels of some KIFs were markedly correlated with that of biomarkers for the S phase and proliferation. KIF2A and KIFC3 expression was positively associated with biomarkers for cell invasion and migration. Some KIF overexpression was significantly associated with neoplastic pathological grade and tumor-node-metastasis staging. Furthermore, KIF2C, KIF4A, and KIF11 overexpression were significantly associated with shorter relapse-free survival times. KIF2A, KIF2C, KIF3A, KIF4B, KIF11, KIF15, KIFC1, and KIFC3 overexpression was associated with shorter overall survival (OS) times, whereas higher expression of KIF19 was associated with a longer OS time. Further multivariate analyses suggested that only KIF4B was an independent prognostic factor for HCC.
Conclusions: Most overexpressions of abnormal KIFs were significantly associated with HCC progression and prognosis, indicating that KIFs could be prognostic and therapeutic biomarkers for HCC. However, it is necessary to further study the function of KIFs and their mechanisms involved in HCC.
Keywords: Biomarker, hepatocellular carcinoma, kinesin superfamily proteins, prognosis
|How to cite this article:|
Chen J, Li S, Zhou S, Cao S, Lou Y, Shen H, Yin J, Li G. Kinesin superfamily protein expression and its association with progression and prognosis in hepatocellular carcinoma. J Can Res Ther 2017;13:651-9
|How to cite this URL:|
Chen J, Li S, Zhou S, Cao S, Lou Y, Shen H, Yin J, Li G. Kinesin superfamily protein expression and its association with progression and prognosis in hepatocellular carcinoma. J Can Res Ther [serial online] 2017 [cited 2018 May 22];13:651-9. Available from: http://www.cancerjournal.net/text.asp?2017/13/4/651/214477
| > Introduction|| |
Hepatocellular carcinoma (HCC) is the fifth most frequent cancer worldwide, with 782,500 new cases diagnosed annually, and it is the second most life-threatening cancer worldwide with 745,500 deaths during 2012. At present, the treatments for HCC include surgical resection, transplantation, and percutaneous ablation., Over the past decade, the postoperative survival rate of HCC patients has improved. However, due to the frequency of HCC, the prognosis of HCC is still not optimal, with a low 5-year survival rate (approximately 26%) in the United States. It is therefore important to identify more useful molecular biomarkers for the diagnosis and prognosis of this disorder.
Kinesin superfamily proteins (KIFs) were first identified by Vale et al. in 1985. There are >45 human KIFs. The KIFs facilitate the transport of mRNAs, protein complexes, and organelles in an ATP-and microtubule-dependent manner., They are essential for cell mitosis and meiosis., Any abnormalities in mitosis cause cell death, gene deletion, and even carcinogenesis.,, KIF3B and KIF14 overexpression has been associated with the poor prognosis of HCC patients, and the suppression of KIF3B and KIF14 decreases HCC cell growth., Liao et al. reported that KIF18A was a biomarker for HCC diagnosis and prognosis. Itzel et al. showed that KIF18B interfered with cell cycle regulation and was a key regulator of carcinogenesis. KIF20A has been reported as an important risk factor for HCC recurrence and survival. HCC patients with expression of KIF23 splice variant 1 have a longer 5-year survival. Liu et al. reported that suppression of KIF20B expression significantly increased the cytotoxic effect of Taxol against HCC. KIF1B was negatively associated with disease-free survival and overall survival (OS) in HCC patients. However, the expression of many other KIFs and their relationship with HCC progression and prognosis are unclear.
In the present study, we first determined the expression of 32 other KIFs in 295 HCC tissues and 50 adjacent tissues, using data provided by The Cancer Genome Atlas More Details (TCGA), which showed that the expression of 20 KIFs were significantly different between HCC and adjacent tissues. Furthermore, we assessed the relationships between KIF levels and tumor biomarkers, clinicopathological parameters, and their predictive value for HCC prognosis. Together, our results showed that some KIFs were associated with the progression and prognosis of HCC, but only KIF4B could independently predict the OS of HCC patients.
| > Materials and Methods|| |
Clinicopathological features and kinesin superfamily protein expression
KIF expression and clinicopathological features of HCC patients were downloaded from TCGA portal (http://cancergenome.nih.gov/, last accessed on February 24, 2015). A total of 295 HCC patients, from 1995 to 2013, were finally included in our study, while other patients were excluded due to a lack of critical information such as histological grade and tumor-node-metastasis (TNM) grade. In the TCGA data set there were insufficient data for the mRNA expression of KIF2B, KIF5A, and KIF25. Therefore, only 32 KIFs were finally analyzed in our study. The main clinicopathological characteristics of 295 HCC patients are shown in [Table 1]. All patients were divided into low and high expression groups based on the median expression of each gene.
|Table 1: Clinicopathologic features of the hepatocellular carcinoma patients (n=295)|
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The independent t-test was used to compare the expression of KIFs in HCC tissues and adjacent tissues. The different expression groups (high versus low) were distinguished by the median value of the KIF expression. The association of KIF expression with clinicopathological indicators was accessed using the Pearson's Chi-square test. The associations between KIF expression and the relapse-free survival (RFS) time and OS were determined using Kaplan–Meier plots and log-rank tests. The Cox regression model was used for univariate and multivariate analyses. The age, sex, histological grade, TNM stage, new tumor events, cancer status, family cancer history, and vascular tumor invasion of 20 KIFs were included in the multivariate analyses. Statistical analyses, using SPSS statistical software for Windows, version 23.0 (SPSS, Chicago, IL, USA), were two-sided, and P ≤ 0.05 was considered statistically significant.
| > Results|| |
Expression of 32 kinesin superfamily proteins in HCC tissues and adjacent tissues
A total of 295 HCC tissues and 50 adjacent tissues were used from the TCGA data set. Compared with adjacent tissues from HCC patients, 17 KIFs (KIF2A, KIF2C, KIF3A, KIF4A, KIF4B, KIF5B, KIF7, KIF9, KIF11, KIF15, KIF21B, KIF22, KIF24, KIFAP3, KIFC1, KIFC2, and KIFC3) were upregulated and three KIFs (KIF13B, KIF19, and KIF26A) were down-regulated in HCC tissues (all, P < 0.05). In addition, the expression of 12 other KIFs (KIF1A, KIF1C, KIF3C, KIF5C, KIF6, KIF12, KIF13A, KIF16B, KIF17, KIF21A, KIF26B, and KIF27) in HCC and adjacent tissues had no statistical significance [Figure 1]; P > 0.05].
|Figure 1: The relative expression of 32 kinesin superfamily proteins in 295 hepatocellular carcinoma tissues and 50 adjacent tissues. Seventeen kinesin superfamily proteins (KIF2A, KIF2C, KIF3A, KIF4A, KIF4B, KIF5B, KIF7, KIF9, KIF11, KIF15, KIF21B, KIF22, KIF24, KIFAP3, KIFC1, KIFC2, and KIFC3) were upregulated and three kinesin superfamily proteins (KIF13B, KIF19, and KIF26A) were downregulated in hepatocellular carcinoma tissues. In addition, the expression of 12 other kinesin superfamily proteins in hepatocellular carcinoma and adjacent tissues were not significant (P > 0.05). KIF=Kinesin superfamily protein|
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Association between kinesin superfamily protein expression and tumor markers
We first analyzed the possible association between KIFs and S phase markers and proliferation. The expressions of 12 KIFs (KIF2A, KIF2C, KIF4A, KIF4B, KIF5B, KIF7, KIF11, KIF15, KIF22, KIF24, KIFC1, and KIFC2) were positively associated with CDK1 and CCNB1 expression, which are important proteins in the S phase. In addition, 11 KIFs (KIF2A, KIF2C, KIF4A, KIF4B, KIF7, KIF11, KIF15, KIF22, KIF24, KIFC1, and KIFC2) were positively corrected with the proliferating cell nuclear antigen (PCNA) and Ki67 proliferation markers. To further show the functions of KIFs in cell invasion and migration, KIF2A and KIFC3 were positively associated with MMP2, MMP7, MMP9, CD24, and CD44 [Table 2].
|Table 2: Association between kinesin superfamily proteins and biomarkers for tumor biological behaviors|
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Association between kinesin superfamily protein expression and clinicopathological characteristics
KIF2A (P = 0.032), KIF2C (P = 0.002), KIF4A (P = 0.002), KIF4B (P = 0.004), KIF5B (P = 0.002), KIF7 (P = 0.032), KIF11 (P = 0.000), KIF15 (P = 0.000), KIF24 (P = 0.004), and KIFC1 (P = 0.002) were differentially expressed in neoplastic histological grades, and KIF2A (P = 0.027), KIF2C (P = 0.013), KIF4A (P = 0.027), KIF11 (P = 0.031), KIF15 (P = 0.027), KIF24 (P = 0.027), KIF27 (P = 0.027), and KIFC1 (P = 0.031) were differentially expressed in TNM stages. No other association between these gene expressions and clinicopathological variables was observed. Taken together, the results suggested that KIF2A, KIF2C, KIF4A, KIF4B, KIF5B, KIF7, KIF11, KIF15, KIF24, KIF27, and KIFC1 were biomarkers for HCC progression [Table 3].
|Table 3: Association between kinesin superfamily proteins expression and clinicopathologic variables|
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Survival outcomes and multivariate analyses
The influence of 20 KIFs on the RFS time was evaluated. The results showed that KIF2C (P = 0.041), KIF4A (P = 0.045), and KIF11 (P = 0.024) expressions were significantly associated with the RFS [Figure 2]a. Specifically, patients with lower KIF2C, KIF4A, and KIF11 levels had a longer RFS time. The association between KIF and OS was also assessed. Similar to the RFS, higher KIF2A (P = 0.026), KIF2C (P = 0.005), KIF3A (P = 0.049), KIF4B (P = 0.030), KIF11 (P = 0.044), KIF15 (P = 0.021), KIFC1 (P = 0.031), and KIFC3 (P = 0.006) expression was significantly associated with poorer OS, whereas higher KIF19 (P = 0.042) expression was significantly associated with a better OS [Figure 2]b. Other molecules did not show any correlation with OS in HCC patients. As shown in [Table 4], the expressions of KIF2A (hazard ratio [HR] =1.628; 95% confidence interval [CI], 1.056–2.508; P = 0.027), KIF2C (HR = 1.832; 95% CI, 1.188–2.824; P = 0.006), KIF4B (HR = 1.602; 95% CI, 1.042–2.463; P = 0.032), KIF11 (HR = 1.545; 95% CI, 1.008–2.370; P = 0.046), KIF15 (HR = 1.647; 95% CI, 1.073–2.529; P = 0.022), KIF19 (HR = 0.638; 95% CI, 0.412–0.987; P = 0.043), KIFC1 (HR = 1.598; 95% CI, 1.040–2.456; P = 0.032), and KIFC3 (HR = 1.840; 95% CI, 1.181–0.866; P = 0.007) were significant prognostic factors using univariate analyses, as well as age (HR = 1.028; 95% CI, 1.009–1.047; P = 0.003), TNM stage (HR = 1.752; 95% CI, 1.113–2.756; P = 0.015), and cancer status (HR = 764; 95% CI, 1.127–2.762; P = 0.013). However, multivariate Cox regression analyses showed that only KIF4B (HR = 2.827; 95% CI, 1.301–6.147; P = 0.009) could independently predict the OS of HCC patients [Table 4].
|Figure 2: Survival analyses of hepatocellular carcinoma patients related to kinesin superfamily protein expression. (a) The correlation between kinesin superfamily protein expression and relapse free survival time. The higher expressions of KIF2C, KIF4A, and KIF11 were significantly associated with shorter relapse free survival times. (b) The association between KIF expression and overall survival time. The lower levels of KIF2A, KIF2C, KIF3A, KIF4B, KIF11, KIF15, KIFC1, and KIFC3 were significantly associated with better overall survival, while a lower level of KIF19 was significantly associated with a poorer prognosis. KIF=Kinesin superfamily protein|
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| > Discussion|| |
HCC is a malignancy that has continued to increase over several years. Like most cancers, HCC is more effectively treated when it is diagnosed at an early stage. Identifying useful biomarkers with prognostic value would therefore increase the efficacy of HCC therapies. Previous studies have reported that some KIFs are associated with the progression and prognosis of HCC.,,,,,,, In this study, we determined the expression of KIFs, and assessed the predictive and prognostic value of these KIFs in HCC.
We found that the levels of 12 KIFs (KIF1A, KIF1C, KIF3C, KIF5C, KIF6, KIF12, KIF13A, KIF16B, KIF17, KIF21A, KIF26B, and KIF27) in HCC and adjacent tissues had no statistical significance. Then we characterized the other 20 KIFs, and found that most of them, in addition to four KIFs (KIF9, KIF13B, KIF21B, and KIFAP3), were associated with HCC progression, aggressive tumor behaviors, and poor survival.
KIFs are motors for anterograde transport of mitochondria that are involved in cell cycle regulation. CCNB1/CDK1 complexes take part in the regulation of mitochondrial functions  and specifically regulate the entry into mitosis at the G2/M interface. KIFs could affect cell cycle arrest and malignant growth by facilitating the mitochondrial fission/fusion events. This study showed that the expressions of 12 KIFs (KIF2A, KIF2C, KIF4A, KIF4B, KIF5B, KIF7, KIF11, KIF15, KIF22, KIF24, KIFC1, and KIFC2) were positively associated with S phase biomarkers (CDK1 and CCNB1). PCNA , and Ki67 are widely recognized cell proliferation markers for a variety of tumors. The levels of 11 KIFs (KIF2A, KIF2C, KIF4A, KIF4B, KIF7, KIF11, KIF15, KIF22, KIF24, KIFC1, and KIFC2) were positively associated with the PCNA and Ki67 proliferative biomarkers. Thus, decreased KIF (KIF2A, KIF2C, KIF4A, KIF4B, KIF7, KIF11, KIF15, KIF22, KIF24, KIFC1, and KIFC2) expression may ameliorate HCC progression by inhibiting proliferation and the tumor cell cycle. KIF2A and KIFC3 were positively associated with cancer cell migration and invasion biomarkers (MMP2, MMP7, MMP9, CD24, and CD44), indicating that KIF2A and KIFC3 could play important roles in HCC invasion and metastasis.
The levels of KIF2A and KIF2C (members of the kinesin-13 family) have been associated with poor prognoses of human gastric cancer and gliomas.,,, Our results showed that KIF2A and KIF2C were associated with HCC aggressiveness, as measured by both histological grade and TNM stage. Our survival analyses also showed that KIF2C was significantly associated with RFS, and KIF2A and KIF2C were significantly associated with OS in HCC patients. KIF4A and KIF4B (members of the kinesin-4 family) play a role in anaphase spindle dynamics. High levels of KIF4A many times associate with tumor cell growth and poor prognoses in several cancers, such as breast cancer, oral cancer, and lung cancer.,, Our results showed that KIF4A and KIF4B could predict HCC progression (KIF4A for histological grade and TNM stage, and KIF4B for histological grade). Our survival analyses also suggested that KIF4A was significantly associated with RFS, and KIF4B was significantly associated with OS in HCC patients. Multivariate analyses showed that KIF4B could independently predict the OS of HCC. KIFC1, KIFC2, and KIFC3 (members of the kinesin-14 family) are C-terminal kinesins with special minus end motility on microtubules. KIFC1 is abundantly expressed in various cancers, such as ovarian cancer, breast cancer, lung cancer, and kidney cancer. Our results suggested that KIFC1 could predict HCC progression (KIFC1 for histological grade and TNM stage), and our survival analyses showed that KIFC1 and KIFC3 were associated with OS in HCC patients. KIF11 (also known as EG5 or kinesin-5), is a driver of invasion, proliferation, and self-renewal in glioblastomas. Moreover, our results suggested that KIF11 could predict HCC progression (KIF11 for histological grade and TNM stage), and our survival analyses showed that KIF11 was significantly correlated with RFS and OS in HCC patients. High levels of KIF15 many times associated with tumor cell growth and poor prognosis in breast cancer. Our results suggested that KIF15 could predict HCC progression (KIF15 for histological grade and TNM stage), and our survival analyses showed that KIF15 was associated with OS in HCC patients. Taken together, these results suggested that KIF2A, KIF2C, KIF4A, KIF4B, KIF11, KIF15, and KIFC1 could be useful biomarkers for the progression and prognosis of HCC.
Furthermore, KIF5B, KIF7, KIF24, and KIF27 predicted the HCC progression (KIF5B, KIF7, and KIF24 for the histological grade, and KIF24 and KIF27 for the TNM stage), and KIF3A and KIF19 were significantly associated with the OS of HCC patients. However, in the future, it will be necessary to perform more clinical and experimental studies to confirm the role of KIFs and their mechanism involved in HCC.
| > Conclusions|| |
Expressions of most KIFs were abnormally upregulated in HCC and were significantly associated with tumor progression and poor outcomes. The results suggested that KIFs are biomarkers for HCC progression and prognosis and that KIFs could be used as targets for the treatment of HCC.
The results shown here are in whole or part based on data generated by the TCGA Research Network: http://cancergenome.nih.gov/.
Financial support and sponsorship
The study is supported by the Scientific Research Program of Ministry of Health (201302009).
Conflicts of interest
There are no conflicts of interest.
| > References|| |
Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J, Jemal A. Global cancer statistics, 2012. CA Cancer J Clin 2015;65:87-108.
Maluccio M, Covey A. Recent progress in understanding, diagnosing, and treating hepatocellular carcinoma. CA Cancer J Clin 2012;62:394-9.
Li W, Man W, Guo H, Yang P. Clinical study of transcatheter arterial chemoembolization combined with microwave ablation in the treatment of advanced hepatocellular carcinoma. J Cancer Res Ther 2016;12 Suppl:C217-20.
Simard EP, Ward EM, Siegel R, Jemal A. Cancers with increasing incidence trends in the United States: 1999 through 2008. CA Cancer J Clin 2012;62:118-28.
Vale RD, Reese TS, Sheetz MP. Identification of a novel force-generating protein, kinesin, involved in microtubule-based motility. Cell 1985;42:39-50.
Miki H, Setou M, Kaneshiro K, Hirokawa N. All kinesin superfamily protein, KIF, genes in mouse and human. Proc Natl Acad Sci U S A 2001;98:7004-11.
Brendza RP, Serbus LR, Duffy JB, Saxton WM. A function for kinesin I in the posterior transport of oskar mRNA and Staufen protein. Science 2000;289:2120-2.
Hirokawa N. Kinesin and dynein superfamily proteins and the mechanism of organelle transport. Science 1998;279:519-26.
Vicente JJ, Wordeman L. Mitosis, microtubule dynamics and the evolution of kinesins. Exp Cell Res 2015;334:61-9.
Sharp DJ, Rogers GC, Scholey JM. Microtubule motors in mitosis. Nature 2000;407:41-7.
Miki H, Okada Y, Hirokawa N. Analysis of the kinesin superfamily: Insights into structure and function. Trends Cell Biol 2005;15:467-76.
Yu Y, Feng YM. The role of kinesin family proteins in tumorigenesis and progression: Potential biomarkers and molecular targets for cancer therapy. Cancer 2010;116:5150-60.
Zhu X, Mei J, Wang Z. Aurora-A kinase: Potential tumor marker of osteosarcoma. J Cancer Res Ther 2014;10 Suppl:C102-7.
Huang X, Liu F, Zhu C, Cai J, Wang H, Wang X, et al.
Suppression of KIF3B expression inhibits human hepatocellular carcinoma proliferation. Dig Dis Sci 2014;59:795-806.
Yang T, Zhang XB, Zheng ZM. Suppression of KIF14 expression inhibits hepatocellular carcinoma progression and predicts favorable outcome. Cancer Sci 2013;104:552-7.
Liao W, Huang G, Liao Y, Yang J, Chen Q, Xiao S, et al.
High KIF18A expression correlates with unfavorable prognosis in primary hepatocellular carcinoma. Oncotarget 2014;5:10271-9.
Itzel T, Scholz P, Maass T, Krupp M, Marquardt JU, Strand S, et al.
Translating bioinformatics in oncology: Guilt-by-profiling analysis and identification of KIF18B and CDCA3 as novel driver genes in carcinogenesis. Bioinformatics 2015;31:216-24.
Shi C, Huang D, Lu N, Chen D, Zhang M, Yan Y, et al.
Aberrantly activated Gli2-KIF20A axis is crucial for growth of hepatocellular carcinoma and predicts poor prognosis. Oncotarget 2016;7:26206-19.
Sun X, Jin Z, Song X, Wang J, Li Y, Qian X, et al.
Evaluation of KIF23 variant 1 expression and relevance as a novel prognostic factor in patients with hepatocellular carcinoma. BMC Cancer 2015;15:961.
Liu X, Zhou Y, Liu X, Peng A, Gong H, Huang L, et al.
MPHOSPH1: A potential therapeutic target for hepatocellular carcinoma. Cancer Res 2014;74:6623-34.
Yang SZ, Wang JT, Yu WW, Liu Q, Wu YF, Chen SG. Downregulation of KIF1B mRNA in hepatocellular carcinoma tissues correlates with poor prognosis. World J Gastroenterol 2015;21:8418-24.
Wang X, Yarmohammadi H, Cao G, Ji X, Hu J, Yarmohammadi H, et al.
Dual phase cone-beam computed tomography in detecting <3 cm hepatocellular carcinomas during transarterial chemoembolization. J Cancer Res Ther 2017;13:38-43.
Schlisio S, Kenchappa RS, Vredeveld LC, George RE, Stewart R, Greulich H, et al.
The kinesin KIF1Bbeta acts downstream from EglN3 to induce apoptosis and is a potential 1p36 tumor suppressor. Genes Dev 2008;22:884-93.
Alexandrou AT, Li JJ. Cell cycle regulators guide mitochondrial activity in radiation-induced adaptive response. Antioxid Redox Signal 2014;20:1463-80.
Doxsey S, Zimmerman W, Mikule K. Centrosome control of the cell cycle. Trends Cell Biol 2005;15:303-11.
Horbay R, Bilyy R. Mitochondrial dynamics during cell cycling. Apoptosis 2016;21:1327-35.
Li J, Li H, Liu J, Feng B, Feng M, Lv B, et al.
The clinical implications of human telomerase reverse transcriptase expression in grade and prognosis of gliomas: A systematic review and meta-analysis. Mol Neurobiol 2016;53:2887-93.
Celis JE, Madsen P, Nielsen S, Celis A. Nuclear patterns of cyclin (PCNA) antigen distribution subdivide S-phase in cultured cells – Some applications of PCNA antibodies. Leuk Res 1986;10:237-49.
Niewiadomska H, Jeziorski A, Olborski B. The expression of the proliferating antigen Ki67, PCNA and products of suppressor gene p53 in primary invasive ductal breast carcinoma. J Exp Clin Cancer Res 1998;17:503-10.
Nakamura Y, Tanaka F, Haraguchi N, Mimori K, Matsumoto T, Inoue H, et al.
Clinicopathological and biological significance of mitotic centromere-associated kinesin overexpression in human gastric cancer. Br J Cancer 2007;97:543-9.
Bie L, Zhao G, Wang YP, Zhang B. Kinesin family member 2C (KIF2C/MCAK) is a novel marker for prognosis in human gliomas. Clin Neurol Neurosurg 2012;114:356-60.
Zhang S, Huang F, Wang Y, Song Q, Yang X, Wu H. KIF2A overexpression and its association with clinicopathologic characteristics and poor prognoses in patients with gastric cancer. Dis Markers 2016;2016:7484516.
Zhang X, Ma C, Wang Q, Liu J, Tian M, Yuan Y, et al.
Role of KIF2A in the progression and metastasis of human glioma. Mol Med Rep 2016;13:1781-7.
Zhu C, Zhao J, Bibikova M, Leverson JD, Bossy-Wetzel E, Fan JB, et al.
Functional analysis of human microtubule-based motor proteins, the kinesins and dyneins, in mitosis/cytokinesis using RNA interference. Mol Biol Cell 2005;16:3187-99.
Zou JX, Duan Z, Wang J, Sokolov A, Xu J, Chen CZ, et al.
Kinesin family deregulation coordinated by bromodomain protein ANCCA and histone methyltransferase MLL for breast cancer cell growth, survival, and tamoxifen resistance. Mol Cancer Res 2014;12:539-49.
Minakawa Y, Kasamatsu A, Koike H, Higo M, Nakashima D, Kouzu Y, et al.
Kinesin family member 4A: A potential predictor for progression of human oral cancer. PLoS One 2013;8:e85951.
Taniwaki M, Takano A, Ishikawa N, Yasui W, Inai K, Nishimura H, et al.
Activation of KIF4A as a prognostic biomarker and therapeutic target for lung cancer. Clin Cancer Res 2007;13(22 Pt 1):6624-31.
Verhey KJ, Hammond JW. Traffic control: Regulation of kinesin motors. Nat Rev Mol Cell Biol 2009;10:765-77.
Pawar S, Donthamsetty S, Pannu V, Rida P, Ogden A, Bowen N, et al.
KIFCI, a novel putative prognostic biomarker for ovarian adenocarcinomas: Delineating protein interaction networks and signaling circuitries. J Ovarian Res 2014;7:53.
Pannu V, Rida PC, Ogden A, Turaga RC, Donthamsetty S, Bowen NJ, et al.
HSET overexpression fuels tumor progression via centrosome clustering-independent mechanisms in breast cancer patients. Oncotarget 2015;6:6076-91.
Grinberg-Rashi H, Ofek E, Perelman M, Skarda J, Yaron P, Hajdúch M, et al.
The expression of three genes in primary non-small cell lung cancer is associated with metastatic spread to the brain. Clin Cancer Res 2009;15:1755-61.
Chan JY. A clinical overview of centrosome amplification in human cancers. Int J Biol Sci 2011;7:1122-44.
Venere M, Horbinski C, Crish JF, Jin X, Vasanji A, Major J, et al.
The mitotic kinesin KIF11 is a driver of invasion, proliferation, and self-renewal in glioblastoma. Sci Transl Med 2015;7:304ra143.
[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3], [Table 4]