The prognostic value of proliferating cell nuclear antigen expression in colorectal cancer

Zhou, He; Huang, Tao; Xiong, Yong; Peng, Linglong; Wang, Rong; Zhang, Guang jun

doi:10.1097/md.0000000000013752

Cited by 21 publications

(11 citation statements)

References 41 publications

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“…Furthermore, the expression level of PCNA was found to be related to clinicopathological features and prognosis of EC patients (Hareyama, 1994). Additionally, many studies have demonstrated that it is a poor survival biomarker in osteosarcoma, gastric, and colorectal cancer (Wang et al, 2017; Yin et al, 2017; Zhou et al, 2018). BIRC5 which encodes for survivin protein, is a member of inhibitor of apoptosis gene family and regulates apoptosis, while cell cycle studies suggest that BIRC5 is overexpressed both in EC and in EC cell lines (Pallares et al, 2005; Nabilsi et al, 2009).…”

Section: Discussionmentioning

confidence: 99%

Identification of Potential Crucial Genes Associated With the Pathogenesis and Prognosis of Endometrial Cancer

Liu

Lin

2019

Front. Genet.

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Background and Objective: Endometrial cancer (EC) is a common gynecological malignancy worldwide. Despite advances in the development of strategies for treating EC, prognosis of the disease remains unsatisfactory, especially for advanced EC. The aim of this study was to identify novel genes that can be used as potential biomarkers for identifying the prognosis of EC and to construct a novel risk stratification using these genes. Methods and Results: An mRNA sequencing dataset, corresponding survival data and expression profiling of an array of EC patients were obtained from The Cancer Genome Atlas and Gene Expression Omnibus, respectively. Common differentially expressed genes (DEGs) were identified based on sequencing and expression as given in the profiling dataset. Pathway enrichment analysis of the DEGs was performed using the Database for Annotation, Visualization, and Integrated Discovery. The protein-protein interaction network was established using the string online database in order to identify hub genes. Univariate and multivariable Cox regression analyses were used to screen prognostic DEGs and to construct a prognostic signature. Survival analysis based on the prognostic signature was performed on TCGA EC dataset. A total of 255 common DEGs were found and 11 hub genes (TOP2A, CDK1, CCNB1, CCNB2, AURKA, PCNA, CCNA2, BIRC5, NDC80, CDC20, and BUB1BA) that may be closely related to the pathogenesis of EC were identified. A panel of 7 DEG signatures consisting of PHLDA2, GGH, ESPL1, FAM184A, KIAA1644, ESPL1, and TRPM4 were constructed. The signature performed well for prognosis prediction (p < 0.001) and time-dependent receiver-operating characteristic (ROC) analysis displayed an area under the curve (AUC) of 0.797, 0.734, 0.729, and 0.647 for 1, 3, 5, and 10-year overall survival (OS) prediction, respectively. Conclusion: This study identified potential genes that may be involved in the pathophysiology of EC and constructed a novel gene expression signature for EC risk stratification and prognosis prediction.

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Section: Discussionmentioning

confidence: 99%

Identification of Potential Crucial Genes Associated With the Pathogenesis and Prognosis of Endometrial Cancer

Liu

Lin

2019

Front. Genet.

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“…Finally, epigenetic alterations can also influence clinical outcome of CRC patients. Hypermethylation in MLH1 or MGMT predicts good prognosis, whereas hypermethylation in p16 or hypomethylation in the promoters of LINE-1 and IGF-2 are related to poor prognosis [19,113,189,190,191].…”

Section: Clinical Relevance Of Molecular Alterations In the Serratmentioning

confidence: 99%

The Molecular Hallmarks of the Serrated Pathway in Colorectal Cancer

Palma

D’Argenio

Pol

et al. 2019

Cancers

139

102

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Colorectal cancer (CRC) is a leading cause of cancer death worldwide. It includes different subtypes that differ in their clinical and prognostic features. In the past decade, in addition to the conventional adenoma-carcinoma model, an alternative multistep mechanism of carcinogenesis, namely the “serrated pathway”, has been described. Approximately, 15 to 30% of all CRCs arise from neoplastic serrated polyps, a heterogeneous group of lesions that are histologically classified into three morphologic categories: hyperplastic polyps, sessile serrated adenomas/polyps, and the traditional serrated adenomas/polyps. Serrated polyps are characterized by genetic (BRAF or KRAS mutations) and epigenetic (CpG island methylator phenotype (CIMP)) alterations that cooperate to initiate and drive malignant transformation from normal colon mucosa to polyps, and then to CRC. The high heterogeneity of the serrated lesions renders their diagnostic and pathological interpretation difficult. Hence, novel genetic and epigenetic biomarkers are required for better classification and management of CRCs. To date, several molecular alterations have been associated with the serrated polyp-CRC sequence. In addition, the gut microbiota is emerging as a contributor to/modulator of the serrated pathway. This review summarizes the state of the art of the genetic, epigenetic and microbiota signatures associated with serrated CRCs, together with their clinical implications.

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“…PCNA has been identified as a proliferating cell nuclear antigen that can serve a role in DNA replication and repair (21). Furthermore, previous studies have identified PCNA as a cell growth marker and a predictive indicator of various types of cancer, including colorectal cancer, gastric carcinoma and parotid gland cancer (22)(23)(24). In addition, it has been reported that upregulated PCNA is associated with poor survival in patients with esophagus squamous cell cancer (25), which is consistent with the results from our previous study on ESCA.…”

Section: Discussionmentioning

confidence: 99%

Bioinformatics analysis of esophageal cancer unveils an integrated mRNA‑lncRNA signature for predicting prognosis

et al. 2019

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Esophageal cancer (ESCA) carries a poor prognosis among gastrointestinal malignancies. The present study developed a signature based on mRNAs and long non-coding RNAs (lncRNAs) to predict prognosis in ESCA by using The Cancer Genome Atlas database. By using least absolute shrinkage and selection operator penalized regression, a set of RNAs (three mRNAs and two lncRNAs) was identified and used to build a risk score system of ESCA prognosis, which was used to stratify patients having considerable diverse survival in the training set [hazard ratio (HR), 3.932; 95% CI, 1.555-9.944; P<0.002] into high-and low-risk groups. The authentication of the results was achieved through the test set (HR, 3.150; 95% CI, 1.113-8.918; P<0.02) and the entire set (HR, 3.181; 95% CI, 1.686-6.006; P<0.0002). The results from multivariate Cox proportional hazard regression analysis in the entire set suggested that the prognostic significance of this signature may be independent of patients' clinicopathological characteristics. Furthermore, this signature was associated with several molecular signaling pathways of cancer according to Gene Set Enrichment Analysis. In addition, a nomogram was built and the risk score and TNM stage were integrated to estimate the 1-and 3-year overall survival rates. The results from the present study demonstrated that the integrated mRNA-lncRNA signature may be considered as a novel biomarker for the prognosis of ESCA.

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The prognostic value of proliferating cell nuclear antigen expression in colorectal cancer

Cited by 21 publications

References 41 publications

Identification of Potential Crucial Genes Associated With the Pathogenesis and Prognosis of Endometrial Cancer

Identification of Potential Crucial Genes Associated With the Pathogenesis and Prognosis of Endometrial Cancer

The Molecular Hallmarks of the Serrated Pathway in Colorectal Cancer

Bioinformatics analysis of esophageal cancer unveils an integrated mRNA‑lncRNA signature for predicting prognosis

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