KIF11 Functions as an Oncogene and Is Associated with Poor Outcomes from Breast Cancer

Zhou, Juan; Chen, Weirong; Yang, Lichao; Wang, Jun; Sun, Jiayuan; Zhang, Wen; He, Zhen-Yu; Wu, San‐Gang

doi:10.4143/crt.2018.460

Cited by 54 publications

(57 citation statements)

References 37 publications

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“…Similar study was also performed and reported by Song et al, showing the relationship between high expression of KIF15, KIF20A, KIF23, KIF2C, KIF4A and poor prognosis [27]. Moreover, KIF11 was identified as an oncogene in breast cancer through prompting cell proliferation, colony formation, cell migration while inhibiting cell apoptosis [28]. Li et al reported that KIF23 is able to promote the development of gastric cancer through stimulating the expression of Ki-67 and PCNA, thus accelerating cell proliferation [29].…”

Section: Agingsupporting

confidence: 84%

GSG2 (Haspin) promotes development and progression of bladder cancer through targeting KIF15 (Kinase-12)

Chen

Zhao

et al. 2020

Aging

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Bladder cancer is the most commonly diagnosed malignant tumor in urological system worldwide. The relationship between GSG2 and bladder cancer has not been demonstrated and remains unclear. In this study, it was demonstrated that GSG2 was up-regulated in bladder cancer tissues compared with the normal tissues and its high expression was correlated with more advanced malignant grade and lower survival rate. Further investigations indicated that the overexpression/knockdown of GSG2 could promote/inhibit proliferation, colony formation and migration of bladder cancer cells, while inhibiting/promoting cell apoptosis. Moreover, knockdown of GSG2 could also suppress tumorigenicity of bladder cancer cells in vivo. RNA-sequencing followed by Ingenuity pathway analysis (IPA) was performed for exploring downstream of GSG2 and identified KIF15 as the potential target. Furthermore, our study revealed that knockdown of KIF15 could inhibit development of bladder cancer in vitro, and alleviate the GSG2 overexpression induced promotion of bladder cancer. In conclusion, our study showed, as the first time, GSG2 as a prognostic indicator and tumor promotor for bladder cancer, whose function was carried out probably through the regulation of KIF15.

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Section: Agingsupporting

confidence: 84%

GSG2 (Haspin) promotes development and progression of bladder cancer through targeting KIF15 (Kinase-12)

Chen

Zhao

et al. 2020

Aging

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“…CEP55 acts as a tumor promoter in cancers of the lung, breast and pancreas, and it has been reported to be associated with metastasis in renal cell carcinoma . Kinesin family member 11 (KIF11) acts as an oncogene in meningioma and is also associated with poor outcomes in meningioma, breast and oral cancer . In our study, using the LASSO Cox regression model, we succeeded in integrating multiple genomic and protein markers into one model with high prognostic accuracy.…”

Section: Discussionmentioning

confidence: 99%

Development and validation of a five‐gene model to predict postoperative brain metastasis in operable lung adenocarcinoma

Zhang

Gao

et al. 2020

Intl Journal of Cancer

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One of the most common sites of extra-thoracic distant metastasis of nonsmall-cell lung cancer is the brain. Our study was performed to discover genes associated with postoperative brain metastasis in operable lung adenocarcinoma (LUAD). RNA seq was performed in specimens of primary LUAD from seven patients with brain metastases and 45 patients without recurrence. Immunohistochemical (IHC) assays of the differentially expressed genes were conducted in 272 surgical-resected LUAD specimens. LASSO Cox regression was used to filter genes related to brain metastasis and construct brain metastasis score (BMS). GSE31210 and GSE50081 were used as validation datasets of the model. Gene Set Enrichment Analysis was performed in patients stratified by risk of brain metastasis in the TCGA database. Through the initial screening, eight genes (CDK1, KPNA2, KIF11, ASPM, CEP55, HJURP, TYMS and TTK) were selected for IHC analyses. The BMS based on protein expression levels of five genes (TYMS, CDK1, HJURP, CEP55 and KIF11) was highly predictive of brain metastasis in our cohort (12-month AUC: 0.791, 36-month AUC: 0.766, 60-month AUC: 0.812). The validation of BMS on overall survival of GSE31210 and GSE50081 also showed excellent predictive value (GSE31210, 12-month AUC: 0.682, 36-month AUC: 0.713, 60-month AUC: 0.762; GSE50081, 12-month AUC: 0.706, 36-month AUC: 0.700, 60-month AUC: 0.724). Further analyses showed high BMS was associated with pathways of cell cycle and DNA repair. A five-gene predictive model exhibits potential clinical utility for the prediction of postoperative brain metastasis and the individual management of patients with LUAD after radical resection.F.F. and Y.Z. contributed equally to this work. Additional Supporting Information may be found in the online version of this article.

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“…Jin et al found high expression of KIF11 predicted a unfavorable prognosis in clear cell renal cell carcinoma [ 25 ]. Zhou et al also found KIF11 functioned as an oncogene and was associated with poor outcomes in breast cancer patients [ 26 ]. Chen et al found KIF11 overexpression was significantly associated with shorter relapse-free survival times in HCC [ 27 ].…”

Section: Discussionmentioning

confidence: 99%

Exploration and validation of a novel prognostic signature based on comprehensive bioinformatics analysis in hepatocellular carcinoma

2020

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This study aimed to construct a novel signature for indicating the prognostic outcomes of hepatocellular carcinoma (HCC). Gene expression profiles were downloaded from Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) databases. The prognosis-related genes with differential expression were identified with Weighted gene co-expression network analysis (WGCNA), univariate analysis, the least absolute shrinkage and selection operator (LASSO). With the stepwise regression analysis, a risk score was constructed based on the expression levels of five genes: Risk score = (−0.7736* CCNB2) + (1.0083* DYNC1LI1) + (−0.6755* KIF11) + (0.9588* SPC25) + (1.5237* KIF18A), which can be applied as a signature for predicting the prognosis of HCC patients. The prediction capacity of the risk score for overall survival was validated with both TCGA and ICGC cohorts. The 1-, 3- and 5-year ROC curves were plotted, in which the AUC was 0.842, 0.726 and 0.699 in TCGA cohort and 0.734, 0.691 and 0.700 in ICGC cohort, respectively. Moreover, the expression levels of the five genes were determined in clinical tumor and normal specimens with immunohistochemistry. The novel signature has exhibited good prediction efficacy for the overall survival of HCC patients.

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KIF11 Functions as an Oncogene and Is Associated with Poor Outcomes from Breast Cancer

Cited by 54 publications

References 37 publications

GSG2 (Haspin) promotes development and progression of bladder cancer through targeting KIF15 (Kinase-12)

GSG2 (Haspin) promotes development and progression of bladder cancer through targeting KIF15 (Kinase-12)

Development and validation of a five‐gene model to predict postoperative brain metastasis in operable lung adenocarcinoma

Exploration and validation of a novel prognostic signature based on comprehensive bioinformatics analysis in hepatocellular carcinoma

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