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Liu X, Zhu X, Zhao Y, Shan Y, Gao Z, Yuan K. CDCA gene family promotes progression and prognosis in lung adenocarcinoma. Medicine (Baltimore) 2024; 103:e38581. [PMID: 38875380 PMCID: PMC11175971 DOI: 10.1097/md.0000000000038581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/16/2024] Open
Abstract
BACKGROUND The cell division cycle-associated (CDCA) family participates in the cell cycle, and the dysregulation of its expression is associated with the development of several types of cancers. However, the roles of CDCAs in lung adenocarcinomas (LUAD) have not been investigated in systematic research. METHODS Using data retrieved from The Cancer Genome Atlas (TCGA), the expression of CDCAs in LUAD and normal tissues was compared, and survival analysis was performed using the data. Also, the correlation between clinical characteristics and the expression of CDCAs was assessed. Using data from cBioPortal, we investigated genetic alterations in CDCAs and their prognostic implications. Immunohistochemical analyses were performed to validate our findings from TCGA data. Following this, we created a risk score model to develop a nomogram. We also performed gene set enrichment analyses (GSEA), gene ontology, and KEGG pathway analysis. We used Timer to analyze the correlation between immune cell infiltration, tumor purity, and expression data. RESULTS Our results indicated that all CDCAs were expressed at high levels in LUAD; this could be associated with poor overall survival, as indicated in TCGA data. Univariate and multivariate Cox analyses revealed that CDCA4/5 could serve as independent risk factors. The results of immunohistochemical analyses confirmed our results. Based on the estimation of expression levels, clinical characteristics, alterations, and immune infiltration, the low-risk group of CDCA4/5 had a better prognosis than the high-risk group. Immune therapy is also a potential treatment option. CONCLUSION In conclusion, our findings indicate that CDCAs play important roles in LUAD, and CDCA4/5 can serve as diagnostic and prognostic biomarkers and therapeutic targets in LUAD.
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Affiliation(s)
- XiangSen Liu
- Department of Thoracic Surgery, The Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University, Changzhou, China
| | - Xudong Zhu
- Department of Thoracic Surgery, The Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University, Changzhou, China
| | - Yi Zhao
- Department of Thoracic Surgery, The Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University, Changzhou, China
| | - Yuchen Shan
- Department of Thoracic Surgery, The Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University, Changzhou, China
| | - ZhaoJia Gao
- Department of Thoracic Surgery, The Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University, Changzhou, China
| | - Kai Yuan
- Department of Thoracic Surgery, The Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University, Changzhou, China
- Heart and Lung Disease Laboratory, The Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University, Changzhou, China
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Tuo Z, Lin Y, Zhang Y, Gao L, Yu D, Wang J, Sun C, Sun X, Wang J, Prasad A, Bheesham N, Meng M, Lv Z, Chen X. Prognostic significance and immune landscape of a cell cycle progression-related risk model in bladder cancer. Discov Oncol 2024; 15:160. [PMID: 38735911 PMCID: PMC11089032 DOI: 10.1007/s12672-024-01008-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Accepted: 05/03/2024] [Indexed: 05/14/2024] Open
Abstract
BACKGROUND A greater emphasis has been placed on the part of cell cycle progression (CCP) in cancer in recent years. Nevertheless, the precise connection between CCP-related genes and bladder cancer (BCa) has remained elusive. This study endeavors to establish and validate a reliable risk model incorporating CCP-related factors, aiming to predict both the prognosis and immune landscape of BCa. METHODS Clinical information and RNA sequencing data were collected from the GEO and TCGA databases. Univariate and multivariate Cox regression analyses were conducted to construct a risk model associated with CCP. The performance of the model was assessed using ROC and Kaplan-Meier survival analyses. Functional enrichment analysis was employed to investigate potential cellular functions and signaling pathways. The immune landscape was characterized using CIBERSORT algorithms. Integration of the risk model with various clinical variables led to the development of a nomogram. RESULTS To build the risk model, three CCP-related genes (RAD54B, KPNA2, and TPM1) were carefully chosen. ROC and Kaplan-Meier survival analysis confirm that our model has good performance. About immunological infiltration, the high-risk group showed decreased levels of regulatory T cells and dendritic cells coupled with increased levels of activated CD4 + memory T cells, M2 macrophages, and neutrophils. Furthermore, the nomogram showed impressive predictive power for OS at 1, 3, and 5 years. CONCLUSION This study provides new insights into the association between the CCP-related risk model and the prognosis of BCa, as well as its impact on the immune landscape.
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Affiliation(s)
- Zhouting Tuo
- Department of Urology, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Yuan Lin
- Department of Urology, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Ying Zhang
- Department of Urology, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Liang Gao
- Center for Clinical Medicine, Huatuo Institute of Medical Innovation (HTIMI), Berlin, Germany
| | - Dexin Yu
- Department of Urology, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Jiani Wang
- Institute for Social Medicine, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Zu Berlin; Berlin Institute of Health, Epidemiology and Health Economics, Berlin, Germany
| | - Chenyu Sun
- Department of General Surgery, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Xianchao Sun
- Department of Urology, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Jinyou Wang
- Department of Urology, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Apurwa Prasad
- Parkview Regional Medical Center, 11109 Parkview Plaza Dr, Fort Wayne, IN, 46845, USA
| | - Nimarta Bheesham
- Internal Medicine, University of Illinois College of Medicine, One Illini Drive, Peoria, IL, 61605, USA
| | - Muzi Meng
- UK Program Site, American University of the Caribbean School of Medicine, Vernon Building Room 64, Sizer St, Preston, PR1 1JQ, UK
- Bronxcare Health System, 1650 Grand Concourse, The Bronx, NY, 10457, USA
| | - Zhengmei Lv
- Department of Histology and Embryology, School of Basic Medical Sciences, Anhui Medical University, Anhui, China.
| | - Xin Chen
- Department of Urology, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
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Han C, Liu S, Ji Y, Hu Y, Zhang J. CDCA3 is a potential biomarker for glioma malignancy and targeted therapy. Medicine (Baltimore) 2024; 103:e38066. [PMID: 38728485 PMCID: PMC11081570 DOI: 10.1097/md.0000000000038066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/02/2023] [Accepted: 04/09/2024] [Indexed: 05/12/2024] Open
Abstract
CDCA3, a cell cycle regulator gene that plays a catalytic role in many tumors, was initially identified as a regulator of cell cycle progression, specifically facilitating the transition from the G2 phase to mitosis. However, its role in glioma remains unknown. In this study, bioinformatics analyses (TCGA, CGGA, Rembrandt) shed light on the upregulation and prognostic value of CDCA3 in gliomas. It can also be included in a column chart as a parameter predicting 3- and 5-year survival risk (C index = 0.86). According to Gene Set Enrichment Analysis and gene ontology analysis, the biological processes of CDCA3 are mainly concentrated in the biological activities related to cell cycle such as DNA replication and nuclear division. CDCA3 is closely associated with many classic glioma biomarkers (CDK4, CDK6), and inhibitors of CDK4 and CDK6 have been shown to be effective in tumor therapy. We have demonstrated that high expression of CDCA3 indicates a higher malignancy and poorer prognosis in gliomas.
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Affiliation(s)
- Chengxi Han
- Department of Neurosurgery, The Second Hospital of Hebei Medical University, Hebei, China
| | - Shuo Liu
- Department of Neurosurgery, The Second Hospital of Hebei Medical University, Hebei, China
| | - Yunfeng Ji
- Department of Neurosurgery, The Second Hospital of Hebei Medical University, Hebei, China
| | - Yuhua Hu
- Department of Neurosurgery, The Second Hospital of Hebei Medical University, Hebei, China
| | - Jingwen Zhang
- Department of Neurosurgery, The Second Hospital of Hebei Medical University, Hebei, China
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Li T, Wang L, Yu N, Zeng A, Huang J, Long X. CDCA3 is a prognostic biomarker for cutaneous melanoma and is connected with immune infiltration. Front Oncol 2023; 12:1055308. [PMID: 36713580 PMCID: PMC9876620 DOI: 10.3389/fonc.2022.1055308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Accepted: 12/21/2022] [Indexed: 01/12/2023] Open
Abstract
Introduction Dysregulation of cell cycle progression (CCP) is a trait that distinguishes cancer from other diseases. In several cancer types, CCP-related genes serve as the primary risk factor for prognosis, but their role in cutaneous melanoma remains unclear. Methods Data from cutaneous melanoma patients were acquired from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Using a Wilcoxon test, the level of CCP-related gene expression in cutaneous melanoma patient tissues was compared to that in normal skin tissues. Logistic analysis was then utilized to calculate the connection between the CCP-related genes and clinicopathological variables. The important functions of the CCP-related genes were further investigated using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and single-sample Gene Set Enrichment Analysis (ssGSEA). Univariate and multivariate Cox analyses and Kaplan-Meier analysis were used to estimate the association between CCP-related genes and prognosis. In addition, using Cox multivariate analysis, a nomogram was constructed to forecast the influence of CCP-related genes on survival rates. Results High expression of CCP-related genes was associated with TNM stage, age, pathological grade, and Breslow depth (P < 0.05). Multivariate analysis demonstrated that CCP-related genes were an independent factor in overall survival and disease-specific survival. High levels of gene expression originating from CCP were shown by GSEA to trigger DNA replication, the G1-S specific transcription factor, the mitotic spindle checkpoint, and the cell cycle. There was a negative association between CCP-related genes and the abundance of innate immune cells. Finally, we revealed that knockdown of cell division cycle-associated gene 3 (CDCA3) significantly suppressed the proliferation and migration ability of cutaneous melanoma cells. Conclusion According to this study, CCP-related genes could serve as potential biomarkers to assess the prognosis of cutaneous melanoma patients and are crucial immune response regulators.
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Affiliation(s)
| | | | | | | | | | - Xiao Long
- *Correspondence: Jiuzuo Huang, ; Xiao Long,
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Li S, Ran MY, Qiao H. A cell cycle-related lncRNA signature predicts the progression-free interval in papillary thyroid carcinoma. Front Endocrinol (Lausanne) 2023; 14:1110987. [PMID: 36923215 PMCID: PMC10009218 DOI: 10.3389/fendo.2023.1110987] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 02/14/2023] [Indexed: 03/02/2023] Open
Abstract
The cell cycle plays a vital role in tumorigenesis and progression. Long non-coding RNAs (lncRNAs) are key regulators of cell cycle processes. Therefore, understanding cell cycle-related lncRNAs (CCR-lncRNAs) is crucial for determining the prognosis of papillary thyroid carcinoma (PTC). RNA-seq and clinical data of PTC were acquired from The Cancer Genome Atlas, and CCR-lncRNAs were selected based on Pearson's correlation coefficients. According to univariate Cox regression, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses, a five-CCR-lncRNA signature (FOXD2-AS1, LOC100507156, BSG-AS1, EGOT, and TMEM105) was established to predict the progression-free interval (PFI) in PTC. Kaplan-Meier survival, time-dependent receiver operating characteristic curve, and multivariate Cox regression analyses proved that the signature had a reliable prognostic capability. A nomogram consisting of the risk signature and clinical characteristics was constructed that effectively predicted the PFI in PTC. Functional enrichment analyses indicted that the signature was involved in cell cycle- and immune-related pathways. Furthermore, we also analyzed the correlation between the signature and immune cell infiltration. Finally, we verified the differential expression of CCR-lncRNAs in vitro using quantitative real-time polymerase chain reaction. Overall, the newly developed prognostic risk signature based on five CCR-lncRNAs may become a marker for predicting the PFI in PTC.
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Affiliation(s)
- Shuang Li
- Department of Endocrinology, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Ming-Yu Ran
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Hong Qiao
- Department of Endocrinology, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
- *Correspondence: Hong Qiao,
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Sarafidis M, Lambrou GI, Zoumpourlis V, Koutsouris D. An Integrated Bioinformatics Analysis towards the Identification of Diagnostic, Prognostic, and Predictive Key Biomarkers for Urinary Bladder Cancer. Cancers (Basel) 2022; 14:cancers14143358. [PMID: 35884419 PMCID: PMC9319344 DOI: 10.3390/cancers14143358] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 07/03/2022] [Accepted: 07/06/2022] [Indexed: 02/04/2023] Open
Abstract
Simple Summary Bladder cancer is evidently a challenge as far as its prognosis and treatment are concerned. The investigation of potential biomarkers and therapeutic targets is indispensable and still in progress. Most studies attempt to identify differential signatures between distinct molecular tumor subtypes. Therefore, keeping in mind the heterogeneity of urinary bladder tumors, we attempted to identify a consensus gene-related signature between the common expression profile of bladder cancer and control samples. In the quest for substantive features, we were able to identify key hub genes, whose signatures could hold diagnostic, prognostic, or therapeutic significance, but, primarily, could contribute to a better understanding of urinary bladder cancer biology. Abstract Bladder cancer (BCa) is one of the most prevalent cancers worldwide and accounts for high morbidity and mortality. This study intended to elucidate potential key biomarkers related to the occurrence, development, and prognosis of BCa through an integrated bioinformatics analysis. In this context, a systematic meta-analysis, integrating 18 microarray gene expression datasets from the GEO repository into a merged meta-dataset, identified 815 robust differentially expressed genes (DEGs). The key hub genes resulted from DEG-based protein–protein interaction and weighted gene co-expression network analyses were screened for their differential expression in urine and blood plasma samples of BCa patients. Subsequently, they were tested for their prognostic value, and a three-gene signature model, including COL3A1, FOXM1, and PLK4, was built. In addition, they were tested for their predictive value regarding muscle-invasive BCa patients’ response to neoadjuvant chemotherapy. A six-gene signature model, including ANXA5, CD44, NCAM1, SPP1, CDCA8, and KIF14, was developed. In conclusion, this study identified nine key biomarker genes, namely ANXA5, CDT1, COL3A1, SPP1, VEGFA, CDCA8, HJURP, TOP2A, and COL6A1, which were differentially expressed in urine or blood of BCa patients, held a prognostic or predictive value, and were immunohistochemically validated. These biomarkers may be of significance as prognostic and therapeutic targets for BCa.
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Affiliation(s)
- Michail Sarafidis
- Biomedical Engineering Laboratory, School of Electrical and Computer Engineering, National Technical University of Athens, 9 Iroon Polytechniou Str., 15780 Athens, Greece;
- Correspondence: ; Tel.: +30-210-772-2430
| | - George I. Lambrou
- Choremeio Research Laboratory, First Department of Pediatrics, National and Kapodistrian University of Athens, 8 Thivon & Levadeias Str., 11527 Athens, Greece;
- University Research Institute of Maternal and Child Health and Precision Medicine, National and Kapodistrian University of Athens, 8 Thivon & Levadeias Str., 11527 Athens, Greece
| | - Vassilis Zoumpourlis
- Biomedical Applications Unit, Institute of Chemical Biology, National Hellenic Research Foundation, 48 Vas. Konstantinou Ave., 11635 Athens, Greece;
| | - Dimitrios Koutsouris
- Biomedical Engineering Laboratory, School of Electrical and Computer Engineering, National Technical University of Athens, 9 Iroon Polytechniou Str., 15780 Athens, Greece;
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