Establishment and Validation of an Individualized Cell Cycle Process-Related Gene Signature to Predict Cancer-Specific Survival in Patients with Bladder Cancer

Shi, Run; Bao, Xuanwen; Rogowski, Paul; Schäfer, Christian; Schmidt-Hegemann, Nina-Sophie; Unger, Kristian; Lü, Shun; Sun, Jing; Büchner, Alexander; Stief, Christian G.; Belka, C.; Li, Minglun

doi:10.3390/cancers12051146

Cited by 10 publications

(9 citation statements)

References 37 publications

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“…40 Recent studies indicate that cell cycle gene signatures show strong capacities of prognostication in many malignancies and have the potential of evaluating immunogenicity of tumors and their responses to ICIs. [41][42][43] However, such relationship between cell cycle signatures and tumor immune microenvironment (TIME) in ccRCC was not reported before. In present study, we built a gene signature included two cell cycle genes (FOXM1&TOP2A) adopting DEGs from GEO database.…”

Section: Discussionmentioning

confidence: 96%

Development of a novel gene signature to predict prognosis and response to PD-1 blockade in clear cell renal cell carcinoma

Yin

Wang

et al. 2021

OncoImmunology

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Clear cell renal cell carcinoma (ccRCC) is the most common kidney malignancy characterized by a poor prognosis. The treatment efficacy of immune checkpoint inhibitors (ICIs) also varies widely in advanced ccRCC. We aim to construct a robust gene signature to improve the prognostic discrimination and prediction of ICIs for ccRCC patients. In this study, adopting differentially expressed genes from seven ccRCC datasets in GEO (Gene Expression Omnibus), a novel signature (FOXM1&TOP2A) was constructed in TCGA (The Cancer Genome Atlas) database by LASSO and Cox regression. Survival and time-dependent ROC analysis revealed the strong predictive ability of our signature in discovery set, two online validation sets and one tissue microarray (TMA) from our institution. High-risk group based on the signature comprises more high-grade (G3&G4) and advanced pathologic stage (stageIII/IV) tumors and presents hyperactivation of cell cycle process according to the functional analysis. Meanwhile, high-risk tumors demonstrate an immunosuppressive phenotype with more infiltrations of regulatory T cells (Tregs), macrophages and high expressions of genes negatively regulating anti-tumor immunity. Low-risk tumors have an improved response to anti-PD-1 therapy and the predictive ability of our signature is better than other recognized biomarkers in ccRCC. A nomogram containing this signature showed a high predictive accuracy with AUCs of 0.90 and 0.84 at 3 and 5 years. Overall, this robust signature could predict prognosis, evaluate immune microenvironment and response to anti-PD-1 therapy in ccRCC, which is very promising in clinical promotion.

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Section: Discussionmentioning

confidence: 96%

Development of a novel gene signature to predict prognosis and response to PD-1 blockade in clear cell renal cell carcinoma

Yin

Wang

et al. 2021

OncoImmunology

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“…Advances in high-throughput techniques, such as microarray and RNA-sequencing (RNA-seq), together with well-established databases, such as the Cancer Genome Atlas (TCGA) and the public genomic data repository Gene Expression Omnibus (GEO), have uncovered new transcriptional landscapes, encouraging researchers to identify molecular markers for cancer diagnosis and prognosis [ 17 ]. Here, we performed RNA-seq analysis and identified BUB1 as a differentially expressed gene in NMIBC and normal adjacent tissue (NAT).…”

Section: Introductionmentioning

confidence: 99%

Prognostic Value of BUB1 for Predicting Non-Muscle-Invasive Bladder Cancer Progression

Piao

You

Byun

et al. 2021

IJMS

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Non-muscle-invasive bladder cancer (NMIBC) is a common disease with a high recurrence rate requiring lifetime surveillance. Although NMIBC is not life-threatening, it can progress to muscle-invasive bladder cancer (MIBC), a lethal form of the disease. The management of the two diseases differs, and patients with MIBC require aggressive treatments such as chemotherapy and radical cystectomy. NMIBC patients at a high risk of progression benefit from early immediate cystectomy. Thus, identifying concordant markers for accurate risk stratification is critical to predict the prognosis of NMIBC. Candidate genetic biomarkers associated with NMIBC prognosis were screened by RNA-sequencing of 24 tissue samples, including 16 NMIBC and eight normal controls, and by microarray analysis (GSE13507). Lastly, we selected and investigated a mitotic checkpoint serine/threonine kinase, BUB1, that regulates chromosome segregation during the cell cycle. BUB1 gene expression was tested in 86 NMIBC samples and 15 controls by real-time qPCR. The performance of BUB1 as a prognostic biomarker for NMIBC was validated in the internal Chungbuk cohort (GSE13507) and the external UROMOL cohort (E-MTAB-4321). BUB1 expression was higher in NMIBC patients than in normal controls (p < 0.05), and the overexpression of BUB1 was correlated with NMIBC progression (log-rank test, p = 0.007). In in vitro analyses, BUB1 promoted the proliferation of bladder cancer cells by accelerating the G2/M transition of the cell cycle. Conclusively, BUB1 modulates the G2/M transition to promote the proliferation of bladder cancer cells, suggesting that it could serve as a prognostic marker in NMIBC.

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“…In recent years, numerous previous studies indicated that cell cycle gene signatures have the potential for evaluating immune cell infiltration, immune evasion, and immune responses (23)(24)(25). However, the relationship between cell cycle-related signatures and tumor immune situation in PRAD was not explored before.…”

Section: Discussionmentioning

confidence: 99%

Comprehensive Analysis of Cell Cycle-Related Genes in Patients With Prostate Cancer

Liu

Pan

et al. 2022

Front. Oncol.

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This study aimed to identify critical cell cycle-related genes (CCRGs) in prostate cancer (PRAD) and to evaluate the clinical prognostic value of the gene panel selected. Gene set variation analysis (GSVA) of dysregulated genes between PRAD and normal tissues demonstrated that the cell cycle-related pathways played vital roles in PRAD. Patients were classified into four clusters, which were associated with recurrence-free survival (RFS). Moreover, 200 prognostic-related genes were selected using the Kaplan–Meier (KM) survival analysis and univariable Cox regression. The prognostic CCRG risk score was constructed using random forest survival and multivariate regression Cox methods, and their efficiency was validated in Memorial Sloan Kettering Cancer Center (MSKCC) and GSE70770. We identified nine survival-related genes: CCNL2, CDCA5, KAT2A, CHTF18, SPC24, EME2, CDK5RAP3, CDC20, and PTTG1. Based on the median risk score, the patients were divided into two groups. Then the functional enrichment analyses, mutational profiles, immune components, estimated half-maximal inhibitory concentration (IC50), and candidate drugs were screened of these two groups. In addition, the characteristics of nine hub CCRGs were explored in Oncomine, cBioPortal, and the Human Protein Atlas (HPA) datasets. Finally, the expression profiles of these hub CCRGs were validated in RWPE-1 and three PRAD cell lines (PC-3, C4-2, and DU-145). In conclusion, our study systematically explored the role of CCRGs in PRAD and constructed a risk model that can predict the clinical prognosis and immunotherapeutic benefits.

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Establishment and Validation of an Individualized Cell Cycle Process-Related Gene Signature to Predict Cancer-Specific Survival in Patients with Bladder Cancer

Cited by 10 publications

References 37 publications

Development of a novel gene signature to predict prognosis and response to PD-1 blockade in clear cell renal cell carcinoma

Development of a novel gene signature to predict prognosis and response to PD-1 blockade in clear cell renal cell carcinoma

Prognostic Value of BUB1 for Predicting Non-Muscle-Invasive Bladder Cancer Progression

Comprehensive Analysis of Cell Cycle-Related Genes in Patients With Prostate Cancer

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