KIF22 promotes bladder cancer progression by activating the expression of CDCA3

Li, Kai; Li, Song; Tang, Shuai; Zhang, Minghao; Ma, Zhiyi; Wang, Qi; Chen, Fangmin

doi:10.3892/ijmm.2021.5044

Cited by 5 publications

(4 citation statements)

References 38 publications

(49 reference statements)

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“…In BC, specific types of transcription factors can activate the expression of CDCA3, which then promotes the proliferation of BC cells, such as kinesin family member 22 (KIF22) and KIF4A. Similarly, research has shown that CDCA3 promotes cell cycle progression, accelerates cell growth, and promotes BC cell migration (11,18,19). Moreover, CDCA3 is a biomarker of chemosensitivity in NSCLC.…”

Section: Discussionmentioning

confidence: 99%

Pan-cancer analysis identifies CDCA3 as a novel prognostic marker associated with immune infiltration in lung adenocarcinoma through bioinformatics analysis

Yang¹,

Wei²,

Zhang³

et al. 2022

Transl Cancer Res TCR

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Background: Lung adenocarcinoma (LUAD) is the most common subtype of lung malignancy. However, the expression of cell division cycle-associated protein-3 (CDCA3) and its significance in LUAD remain unclear. In this study, we investigated the functional role of CDCA3 in LUAD through bioinformatics analysis and expected to provide a new direction for clinical treatment.Methods: The expression of CDCA3 was analyzed by online database. The association between the expression of CDCA3 and clinical parameters with LUAD was explored in TCGA. Survival and independent prognostic analysis were performed by TCGA database and the GSE30219 and GSE31210 datasets. Furthermore, Enrichment analyses were conducted to analyze the functions of CDCA3. Afterward, the relationship between CDCA3 and immune infiltration was investigated. Additionally, a competing endogenous RNA (ceRNA) regulatory network related to CDCA3 was constructed. Finally, CDCA3 expression was validated in clinical tissues by immunohistochemistry (IHC), real-time quantitative reverse transcriptase polymerase chain reaction (qRT-PCR), and western blotting (WB).Results: CDCA3 expression was upregulated in 20 tumors and was significantly higher in LUAD compared with normal tissues in3 datasets. In addition, CDCA3 was significantly correlated with age, gender, stage, N, and smoking status. Kaplan-Meier survival curves showed that LUAD samples with higher CDCA3 expression were associated with poorer overall survival (OS) and disease-free survival (DFS). Univariate Cox regression analysis showed that the p value of CDCA3 expression was less than 0.05 (P<0.05) and it appeared in the results of multivariate Cox regression analysis (HR ≥1), indicating that CDCA3 can be used as an independent prognostic factor for LUAD. Intriguingly, Gene Set Enrichment Analysis (GSEA) suggested that CDCA3 was correlated with DNA-related terms and metabolic-related pathways in LUAD. CDCA3 expression was correlated with four immune scores and 14 immune cells in different groups. Next, a ceRNA network was constructed with CDCA3, and the experimental results of IHC, qRT-PCR, and WB were consistent with the bioinformatic analysis.Conclusions: CDCA3 could serve as a prognostic biomarker for LUAD.

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Section: Discussionmentioning

confidence: 99%

Pan-cancer analysis identifies CDCA3 as a novel prognostic marker associated with immune infiltration in lung adenocarcinoma through bioinformatics analysis

Yang¹,

Wei²,

Zhang³

et al. 2022

Transl Cancer Res TCR

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“…CDCA3 is another protein-coding gene. KIF22 promotes bladder cancer further development by activating CDCA3 [20]. CDCA4 is a protein-coding gene.…”

Section: Introductionmentioning

confidence: 99%

Integrated bioinformatics analysis and experimental validation identified CDCA families as prognostic biomarkers and sensitive indicators for rapamycin treatment of glioma

Li,

Chen,

Yang

et al. 2024

PLoS ONE

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The cell division cycle associated (CDCA) genes regulate the cell cycle; however, their relationship with prognosis in glioma has been poorly reported in the literature. The Cancer Genome Atlas (TCGA) was utilized to probe the CDCA family in relation to the adverse clinical features of glioma. Glioma single-cell atlas reveals specific expression of CDCA3, 4, 5, 8 in malignant cells and CDCA7 in neural progenitor cells (NPC)-like malignant cells. Glioma data from TCGA, the China Glioma Genome Atlas Project (CGGA) and the gene expression omnibus (GEO) database all demonstrated that CDCA2, 3, 4, 5, 7 and 8 are prognostic markers for glioma. Further analysis identified CDCA2, 5 and 8 as independent prognostic factors for glioma. Lasso regression-based risk models for CDCA families demonstrated that high-risk patients were characterized by high tumor mutational burden (TMB), low levels of microsatellite instability (MSI), and low tumor immune dysfunction and rejection (TIDE) scores. These pointed to immunotherapy for glioma as a potentially viable treatment option Further CDCA clustering suggested that the high CDCA subtype exhibited a high macrophage phenotype and was associated with a higher antigen presentation capacity and high levels of immune escape. In addition, hsa-mir-15b-5p was predicted to be common regulator of CDCA3 and CDCA4, which was validated in U87 and U251 cells. Importantly, we found that CDCAs may indicate response to drug treatment, especially rapamycin, in glioma. In summary, our results suggest that CDCAs have potential applications in clinical diagnosis and as drug sensitivity markers in glioma.

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“…Bladder cancer (BLCA) is a common cancer with high morbidity and mortality rates worldwide. Most BLCA patients are often diagnosed in the late stages and lack effective treatments ( 1 , 2 ). There were about 81,400 new BLCA cases and 17,980 BLCA deaths in the United States in 2020 alone.…”

Section: Introductionmentioning

confidence: 99%

Identification of a novel defined inflammation-related long noncoding RNA signature contributes to predicting prognosis and distinction between the cold and hot tumors in bladder cancer

Xiong

Chen

et al. 2023

Front. Oncol.

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PurposeBladder cancer (BLCA) is one of the most frequently diagnosed urological malignancies and is the 4th most common cancer in men worldwide. Molecular targets expressed in bladder cancer (BLCA) are usually used for developing targeted drug treatments. However, poor prognosis and poor immunotherapy efficacy remain major challenges for BLCA. Numerous studies have shown that long non-coding RNAs (LncRNAs) play an important role in the development of cancer. However, the role of lncRNAs related to inflammation in BLCA and their prognostic value remain unclear. Therefore, this study is aimed to explore new potential biomarkers that can predict cancer prognosis.MethodsWe downloaded BLCA-related RNA sequencing data from The Cancer Genome Atlas (TCGA) and searched for inflammation-related prognostic long non-coding RNAs (lncRNAs) by univariate Cox (uniCox) regression and co-expression analysis. We used the least absolute shrinkage and selection operator (LASSO) analysis to construct an inflammation-related lncRNA prognosis risk model. Samples were divided into high-risk score (HRS) group and low-risk score (LRS) group based on the median value of risk scores. The independent variable factors were identified by univariate Cox (uni-Cox) and multivariate Cox (multi-Cox) regression analyses, and receiver operating characteristic (ROC) curves were used to compare the role of different factors in predicting outcomes. Nomogram and Calibration Plot were generated by the R package rms to analyze whether the prediction results are correct and show good consistency. Correlation coefficients were calculated by Pearson analysis. The Kaplan-Meier method was used to assess the prognostic value. The expression of 7 lncRNAs related with inflammation was also confirmed by qRT-PCR in BLCA cell lines. Kyoto Encyclopedia of Gene and Genome (KEGG) pathways that were significantly enriched (P < 0.05) in each risk group were identified by the GSEA software. The R package pRRophetic was used to predict the IC50 of common chemotherapeutic agents. TIMER, XCELL, QUANTISEQ, MCPCOUNTER, EPIC and CIBERSORT were applied to quantify the relative proportions of infiltrating immune cells. We also used package ggpubr to evaluate TME scores and immune checkpoint activation in LRS and HRS populations. R package GSEABase was used to analyze the activity of immune cells or immune function. Different clusters of principal component analysis (PCA), t-distribution random neighborhood embedding (t-SNE), and Kaplan-Meier survival were analyzed using R package Rtsne’s. The R package ConsensesClusterPlus was used to class the inflammation-related lncRNAs.ResultsIn this study, a model containing 7 inflammation-related lncRNAs was constructed. The calibration plot of the model was consistent with the prognosis prediction outcomes. The 1-, 3-, and 5-year ROC curve (AUC) were 0.699, 0.689, and 0.699, respectively. High-risk patients were enriched in lncRNAs related with tumor invasion and immunity, and had higher levels of immune cell infiltration and immune checkpoint activation. Hot tumors and cold tumors were effectively distinguished by clusters 2 and 3 and cluster 1, respectively, which indicated that hot tumors are more susceptible to immunotherapy.ConclusionOur study showed that inflammation-related LncRNAs are closely related with BLCA, and inflammation-related lncRNA can accurately predict patient prognosis and effectively differentiate between hot and cold tumors, thus improving individualized immunotherapy for BLCA patients. Therefore, this study provides an effective predictive model and a new therapeutic target for the prognosis and clinical treatment of BLCA, thus facilitating the development of individualized tumor therapy.

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KIF22 promotes bladder cancer progression by activating the expression of CDCA3

Cited by 5 publications

References 38 publications

Pan-cancer analysis identifies CDCA3 as a novel prognostic marker associated with immune infiltration in lung adenocarcinoma through bioinformatics analysis

Pan-cancer analysis identifies CDCA3 as a novel prognostic marker associated with immune infiltration in lung adenocarcinoma through bioinformatics analysis

Integrated bioinformatics analysis and experimental validation identified CDCA families as prognostic biomarkers and sensitive indicators for rapamycin treatment of glioma

Identification of a novel defined inflammation-related long noncoding RNA signature contributes to predicting prognosis and distinction between the cold and hot tumors in bladder cancer

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