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. 2023 Mar 24;160(1):13.
doi: 10.1186/s41065-023-00273-0.

CCNE1 is a predictive and immunotherapeutic indicator in various cancers including UCEC: a pan-cancer analysis

Xingyu Zheng #  1   2 , Lingli Chen #  1   2 , Wenlu Liu #  1   2 , Shuangshuang Zhao  1   2 , Ye Yan  1   2 , Jianzhen Zhao  1   2 , Wenyan Tian  1   2 , Yingmei Wang  3   4
Affiliations

CCNE1 is a predictive and immunotherapeutic indicator in various cancers including UCEC: a pan-cancer analysis

Xingyu Zheng et al. Hereditas. .

Abstract

Background: CCNE1 plays an important oncogenic role in several tumors, especially high-stage serous ovarian cancer and endometrial cancer. Nevertheless, the fundamental function of CCNE1 has not been explored in multiple cancers. Therefore, bioinformatics analyses of pan-cancer datasets were carried out to explore how CCNE1 regulates tumorigenesis.

Methods: A variety of online tools and cancer databases, including GEPIA2, SangerBox, LinkedOmics and cBioPortal, were applied to investigate the expression of CCNE1 across cancers. The pan-cancer datasets were used to search for links between CCNE1 expression and prognosis, DNA methylation, m6A level, genetic alterations, CCNE1-related genes, and tumor immunity. We verified that CCNE1 has biological functions in UCEC cell lines using CCK-8, EdU, and Transwell assays.

Results: In patients with different tumor types, a high mRNA expression level of CCNE1 was related to a poor prognosis. Genes related to CCNE1 were connected to the cell cycle, metabolism, and DNA damage repair, according to GO and KEGG enrichment analyses. Genetic alterations of CCNE1, including duplications and deep mutations, have been observed in various cancers. Immune analysis revealed that CCNE1 had a strong correlation with TMB, MSI, neoantigen, and ICP in a variety of tumor types, and this correlation may have an impact on the sensitivity of various cancers to immunotherapy. CCK-8, EdU and Transwell assays suggested that CCNE1 knockdown can suppress UCEC cell proliferation, migration and invasion.

Conclusion: Our study demonstrated that CCNE1 is upregulated in multiple cancers in the TCGA database and may be a promising predictive biomarker for the immunotherapy response in some types of cancers. Moreover, CCNE1 knockdown can suppress the proliferation, migration and invasion of UCEC cells.

Keywords: CCNE1; Immune; Pancancer; Prognosis; UCEC.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
CCNE1 expression levels in normal tissues and tumors including UCEC. A CCNE1 expression levels in 27 tumor tissues and normal tissues in TCGA combined with GTEx database via SangerBox. B CCNE1 expression levels in UCEC tissues and normal tissues in TCGA. C The correlation between CCNE1 expression and UCEC stages (I, II, II and IV) in TCGA datasets. D The correlation between CCNE1 expression and tumor stages in various tumors by TCGA cohort. *P < 0.05, ***P < 0.001, ****P < 0.0001
Fig. 2
Fig. 2
The correlation between CCNE1 expression and overall survival (OS) in various cancers in TCGA database
Fig. 3
Fig. 3
DNA promotor methylation levels of CCNE1 in pan-cancers. A The DNA promotor methylation levels of CCNE1 in various cancers and normal tissues in TCGA database. B The DNA promotor methylation levels of CCNE1 in UCEC cell lines
Fig. 4
Fig. 4
Distinct genomic profiles associated with CCNE1 expression. Detection of differential somatic mutations in UCEC, including 25% CCNE1low group (A) and 25% ALKBH5high group (B). C The CNAs profile analysis about 25% CCNE1low group and 25% CCNE1.high group in TCGA dataset by GISTIC2.0. (D-E) Frequency of amplifications and deletions in UCEC with CCNE1 low or high expression (red, amplification, Blue, deletion)
Fig. 5
Fig. 5
The interactions between CCNE1 and its binding proteins. The interacting proteins of CCNE1 in the Genemania (A) and STRING (B) portals. C The intersection of CCNE1 binding proteins in Genemania, STRING and Hitpredict portals, including CDK2, CDK1, FBXW7, E2F1, FOXM1 and BRCA1
Fig. 6
Fig. 6
The m6A modification of CCNE1 mRNA via SRAMP portal
Fig. 7
Fig. 7
The analyses of CCNE1-related genes in UCEC. Heatmaps showing the enrichment patterns of the top 100 genes positively (50) (A) or negatively (50) (B) correlated with CCNE1 expression of UCEC in TCGA database. The GO-BP enrichment analysis were applied with the top 50 CCNE1 positive (C) or negative (D) related genes. The KEGG enrichment analysis were used to analyze the top 50 CCNE1 positive (E) or negative (F) related genes
Fig. 8
Fig. 8
Correlations between CCNE1 mRNA expression and immune infiltration. A The correlations between CCNE1 expression and immune cell infiltration levels in various tumors through Sangerbox. B The correlations between ESTIMATE scores (ESTIMATE Score, Immune Score, and Stromal Score) and CCNE1 expression in various tumors via Sangerbox portal. The relationships between ccne1 mRNA expression and TMB (C), MSI (D), neoantigen (E) and ICP-gene (F) in multiple cancers. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001
Fig. 9
Fig. 9
The biological functions of CCNE1 inUCEC. Verification of knockdown efficiency of CCNE1 in HEC-1A (A) and HEC-1B (C) cell lines via RT-qPCR and western blot. The biological functions of CCNE1 on UCEC cell lines were verified by CCK-8 (B and D), EdU (E–F) and Transwell (G-H) experiments. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001
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References

    1. Patch AM, Christie EL, Etemadmoghadam D, Garsed DW, George J, Fereday S, Nones K, Cowin P, Alsop K, Bailey PJ, et al. Whole-genome characterization of chemoresistant ovarian cancer. Nature. 2015;521:489–494. doi: 10.1038/nature14410. - DOI - PubMed
    1. Rosen DG, Yang G, Deavers MT, Malpica A, Kavanagh JJ, Mills GB, Liu J. Cyclin E expression is correlated with tumor progression and predicts a poor prognosis in patients with ovarian carcinoma. Cancer-Am Cancer Soc. 2006;106:1925–1932. - PubMed
    1. Nakayama K, Rahman MT, Rahman M, Nakamura K, Ishikawa M, Katagiri H, Sato E, Ishibashi T, Iida K, Ishikawa N, Kyo S. CCNE1 amplification is associated with aggressive potential in endometrioid endometrial carcinomas. Int J Oncol. 2016;48:506–516. doi: 10.3892/ijo.2015.3268. - DOI - PMC - PubMed
    1. Cherniack AD, Shen H, Walter V, Stewart C, Murray BA, Bowlby R, Hu X, Ling S, Soslow RA, Broaddus RR, et al. Integrated Molecular Characterization of Uterine Carcinosarcoma. Cancer Cell. 2017;31:411–423. doi: 10.1016/j.ccell.2017.02.010. - DOI - PMC - PubMed
    1. Zhao S, Choi M, Overton JD, Bellone S, Roque DM, Cocco E, Guzzo F, English DP, Varughese J, Gasparrini S, et al. Landscape of somatic single-nucleotide and copy-number mutations in uterine serous carcinoma. Proc Natl Acad Sci U S A. 2013;110:2916–2921. doi: 10.1073/pnas.1222577110. - DOI - PMC - PubMed

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