Dataset Information

Overexpression of kinesin superfamily members as prognostic biomarkers of breast cancer.

ABSTRACT:

Background

Kinesin superfamily (KIFs) has a long-reported significant influence on the initiation, development, and progress of breast cancer. However, the prognostic value of whole family members was poorly done. Our study intends to demonstrate the value of kinesin superfamily members as prognostic biomarkers as well as a therapeutic target of breast cancer.

Methods

Comprehensive bioinformatics analyses were done using data from TCGA, GEO, METABRIC, and GTEx. LASSO regression was done to select tumor-related members. Nomogram was constructed to predict the overall survival (OS) of breast cancer patients. Expression profiles were testified by quantitative RT-PCR and immunohistochemistry. Transcription factor, GO and KEGG enrichments were done to explore regulatory mechanism and functions.

Results

A total of 20 differentially expressed KIFs were identified between breast cancer and normal tissue with 4 (KIF17, KIF26A, KIF7, KIFC3) downregulated and 16 (KIF10, KIF11, KIF14, KIF15, KIF18A, KIF18B, KIF20A, KIF20B, KIF22, KIF23, KIF24, KIF26B, KIF2C, KIF3B, KIF4A, KIFC1) overexpressed. Among which, 11 overexpressed KIFs (KIF10, KIF11, KIF14, KIF15, KIF18A, KIF18B, KIF20A, KIF23, KIF2C, KIF4A, KIFC1) significantly correlated with worse OS, relapse-free survival (RFS) and distant metastasis-free survival (DMFS) of breast cancer. A 6-KIFs-based risk score (KIF10, KIF15, KIF18A, KIF18B, KIF20A, KIF4A) was generated by LASSO regression with a nomogram validated an accurate predictive efficacy. Both mRNA and protein expression of KIFs are experimentally demonstrated upregulated in breast cancer patients. Msh Homeobox 1 (MSX1) was identified as transcription factors of KIFs in breast cancer. GO and KEGG enrichments revealed functions and pathways affected in breast cancer.

Conclusion

Overexpression of tumor-related KIFs correlate with worse outcomes of breast cancer patients and can work as potential prognostic biomarkers.

SUBMITTER: Li TF

PROVIDER: S-EPMC7161125 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

Overexpression of kinesin superfamily members as prognostic biomarkers of breast cancer.

Li Tian-Fu TF Zeng Hui-Juan HJ Shan Zhen Z Ye Run-Yi RY Cheang Tuck-Yun TY Zhang Yun-Jian YJ Lu Si-Hong SH Zhang Qi Q Shao Nan N Lin Ying Y

Cancer cell international 20200415

<h4>Background</h4>Kinesin superfamily (KIFs) has a long-reported significant influence on the initiation, development, and progress of breast cancer. However, the prognostic value of whole family members was poorly done. Our study intends to demonstrate the value of kinesin superfamily members as prognostic biomarkers as well as a therapeutic target of breast cancer.<h4>Methods</h4>Comprehensive bioinformatics analyses were done using data from TCGA, GEO, METABRIC, and GTEx. LASSO regression wa ...[more]

PMID: 32322170

Similar Datasets

Project description:BackgroundKinesin superfamily of proteins (KIFs) has been broadly reported to play an indispensable role in the biological process. Recently, emerging evidence reveals its oncogenic role in various cancers. However, the prognostic, oncological, and immunological values of KIFs have not been comprehensively explored in pancreatic ductal adenocarcinoma (PDAC) patients. We aimed to illustrate the relationship between KIFs and pancreatic ductal adenocarcinoma by using bioinformatical analysis.MethodsWe use GEPIA, Oncomine datasets, cBioPortal, LOGpc, TIMER, and STRING bioinformatics tools and web servers to investigate the aberrant expression, prognostic values, and oncogenic role of KIFs. The two-gene prognostic model and the correlation between KIFs and KRAS and TP53 mutation were performed using an R-based computational framework.ResultsOur results demonstrated that KIFC1/2C/4A/11/14/15/18A/18B/20B/23 (we name it prognosis-related KIFs) were upregulated and associated with unfavorable clinical outcome in pancreatic cancer patients. KIF21B overexpression is associated with better clinical outcome. The KIFC1/2C/4A/11/14/15/18A/18B/20B/23 profiles were significantly increased compared to grade 1 and grade 2/3. Besides, KIFC1/2C/4A/11/14/15/18A/18B/20B/23 was significantly associated with the mutation status of KRAS and TP53.Notably, most prognosis-related KIFs have strong correlations with tumor growth and myeloid-derived suppressor cells infiltration (MDSCs). A prognostic signature based on KIF20B and KIF21B showed a reliable predictive performance. Receiver operating characteristic (ROC) curve was employed to assess the predictive power of two-gene signature. Consequently, the gene set enrichment analysis (GSEA) showed that KIF20B and KIF21B's overexpression was associated with the immunological and oncogenic pathway activation in pancreatic cancer. Finally, real-time quantitative PCR (RT-qPCR) was utilized to investigate the expression pattern of KIF20B and KIF21B in pancreatic cancer cell lines and normal pancreatic cell.ConclusionsKnowledge of the expression level of the KIFs may provide novel therapeutic molecular targets and potential prognostic biomarkers to pancreatic cancer patients.

Project description:BackgroundMatrix metalloproteinases (MMPs) are regarded to be relevant to the prognosis of breast cancer. Numerous studies have confirmed the association between MMPs and tumor growth, invasion and metastasis in breast cancer. However, their prognostic values for survival in patients with breast cancer remain controversial. Hence, a meta-analysis was performed to clarify a more accurate estimation of the role of MMPs on prognosis of breast cancer patients.MethodA systemic electronic search was conducted in PubMed, Embase and Web of science databases to identify eligible studies, which were associated with the relationship between MMPs and prognosis of breast cancer. The correlation in random-effect model was evaluated by using the hazard ratios (HRs) and 95% confidence intervals (CIs).ResultsA total of 28 studies covering 4944 patients were included for meta-analysis. A summary hazard ratio (HR) of all studies was calculated, as well as the sub-group HRs. The combined HRs calculated by either univariate or multivariate analysis both suggested that overexpression of MMPs had an unfavorable impact on overall survival (OS) (HR = 1.694, 95%CI: 1.347-2.129, P < 0.001; HR = 1.611, 95%CI: 1.419-1.830, P < 0.001, respectively). And the univariate analysis showed that patients with overexpression of MMPs had worse relapse-free survival (RFS) (HR = 1.969, 95%CI: 1.460-2.655, P < 0.001) in all eligible studies. In the sub-group analyses, HRs of MMP-9 positivity with poor OS were 1.794 (95%CI: 1.330-2.420, P < 0.001) and 1.709 (95%CI: 1.157-2.526, P = 0.007) which were separately evaluated by univariate and multivariate analysis. A small number of articles demonstrated that MMP-2 overexpression was not related with shorter OS (HR = 1.400, 95%CI: 0.610-3.029, P = 0.427). Four studies included in the OS analysis of MMPs expression in serum suggested that positive expression of serum MMPs may be an unfavorable factor (HR = 1.630, 95%CI: 1.065-2.494) for breast cancer patients. No publication bias was observed in the current meta-analysis.ConclusionsOur findings suggested that MMPs overexpression (especially MMP-9, MMP-2, MMPs overexpression in serum) might indicate a higher risk of poor prognosis in breast cancer. Larger prospective studies are further needed to estimate the prognostic values of MMPs overexpression.

Dataset Information

Overexpression of kinesin superfamily members as prognostic biomarkers of breast cancer.

Background

Methods

Results

Conclusion

Publications

Overexpression of kinesin superfamily members as prognostic biomarkers of breast cancer.

Similar Datasets

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