scholarly journals Identification of candidate biomarkers correlated with the diagnosis and prognosis of cervical cancer via integrated bioinformatics analysis

2019 ◽  
Vol Volume 12 ◽  
pp. 4517-4532 ◽  
Author(s):  
Fangfang Dai ◽  
Gantao Chen ◽  
Yanqing Wang ◽  
Li Zhang ◽  
Youmei Long ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Bioinformatics Analysis ◽  
Diagnosis And Prognosis

scholarly journals Small Non-Coding-RNA in Gynecological Malignancies

Cancers ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 1085
Author(s):  
Shailendra Kumar Dhar Dwivedi ◽  
Geeta Rao ◽  
Anindya Dey ◽  
Priyabrata Mukherjee ◽  
Jonathan D. Wren ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Noncoding Rna ◽  
Molecular Mechanisms ◽  
P Element ◽  
Gynecologic Malignancies ◽  
Diagnosis And Prognosis ◽  
Gynecological Malignancies ◽  
Non Coding Rna ◽  
Therapeutic Research ◽  
Regulatory Functions

Gynecologic malignancies, which include cancers of the cervix, ovary, uterus, vulva, vagina, and fallopian tube, are among the leading causes of female mortality worldwide, with the most prevalent being endometrial, ovarian, and cervical cancer. Gynecologic malignancies are complex, heterogeneous diseases, and despite extensive research efforts, the molecular mechanisms underlying their development and pathology remain largely unclear. Currently, mechanistic and therapeutic research in cancer is largely focused on protein targets that are encoded by about 1% of the human genome. Our current understanding of 99% of the genome, which includes noncoding RNA, is limited. The discovery of tens of thousands of noncoding RNAs (ncRNAs), possessing either structural or regulatory functions, has fundamentally altered our understanding of genetics, physiology, pathophysiology, and disease treatment as they relate to gynecologic malignancies. In recent years, it has become clear that ncRNAs are relatively stable, and can serve as biomarkers for cancer diagnosis and prognosis, as well as guide therapy choices. Here we discuss the role of small non-coding RNAs, i.e., microRNAs (miRs), P-Element induced wimpy testis interacting (PIWI) RNAs (piRNAs), and tRNA-derived small RNAs in gynecological malignancies, specifically focusing on ovarian, endometrial, and cervical cancer.

Identification of diagnosis and prognosis gene markers in B-ALL with ETV6-RUNX1 fusion by Integrated Bioinformatics Analysis

Gene ◽  
2022 ◽  
pp. 146132
Author(s):  
Hongkai Zhu ◽  
Rong Zhang ◽  
Ruijuan Li ◽  
Zhihua Wang ◽  
Heng Li ◽  
...  
Keyword(s):  
Bioinformatics Analysis ◽  
Gene Markers ◽  
Diagnosis And Prognosis

scholarly journals Investigation of differentially-expressed microRNAs and genes in cervical cancer using an integrated bioinformatics analysis

2017 ◽  
Vol 13 (4) ◽  
pp. 2784-2790 ◽  
Author(s):  
Zhanzhan Xu ◽  
Yu Zhou ◽  
Fang Shi ◽  
Yexuan Cao ◽  
Thi Lan Anh Dinh ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Bioinformatics Analysis ◽  
Differentially Expressed

scholarly journals Identification of key pathways and genes in the progression of cervical cancer using bioinformatics analysis

2018 ◽  
Author(s):  
Kejia Wu ◽  
Yuexiong Yi ◽  
Fulin Liu ◽  
Wanrong Wu ◽  
Yurou Chen ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Bioinformatics Analysis ◽  
Key Pathways

scholarly journals The effect of HMGB1 on the clinicopathological and prognostic features of cervical cancer

2019 ◽  
Vol 39 (5) ◽  
Author(s):  
Pan Li ◽  
Mengfei Xu ◽  
Hongbing Cai ◽  
Niresh Thapa ◽  
Can He ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Molecular Mechanisms ◽  
Bioinformatics Analysis ◽  
Immunohistochemical Analysis ◽  
Figo Stage ◽  
P Value ◽  
Prognostic Features ◽  
Potential Biomarker ◽  
Hmgb1 Expression

Abstract Cervical cancer is the third leading cause of cancer death among women in less-developed regions. Because of the poor survivorship of patients with advanced disease, finding new biomarkers for prognostic prediction is of great importance. In the current study, mRNA datasets (GSE9750 and GSE63514) were retrieved from Gene Expression Omnibus and was used to identify differentially expressed genes. The underlying molecular mechanisms associated with high-mobility group box 1 protein (HMGB1) were investigated using bioinformatics analysis. Immunohistochemical analysis of HMGB1 was performed on 239 cases of cervical cancer samples to investigate its possible correlation with clinicopathological characteristics and outcomes. A preliminary validation has been made to explore the possible correlation factors with HMGB1 that promote migration of cervical cancer cells. Bioinformatics analysis showed that adherens junction was significant for both P-value and enrichment scores, which was consistent with the clinical study. The underlying molecular mechanisms might be the interaction among HMGB1, RAC1, and CDC42. HMGB1 expression was significantly associated with tumor size, parametrial infiltration, the depth of cervical stromal invasion, and FIGO stage (P=0.003, 0.019, 0.013, and 0.003, respectively). FIGO stage, lymph mode metastasis, and HMGB1 expression were independent predictors of a poorer prognosis of patients with cervical cancer. Knockdown of HMGB1 inhibits migration of Siha and C33A cells in vitro. Western blot and quantitative real-time PCR (qRT-PCR) showed that the expression of RAC1 and CDC42 was positively correlated with HMGB1. HMGB1 is a useful prognostic indicator and a potential biomarker of cervical cancer. RAC1 and CDC42 may be involved in the progression of cervical cancer migration induced by HMGB1.

scholarly journals LncRNA PVT1 promotes proliferation and invasion through enhancing Smad3 expression by sponging miR-140-5p in cervical cancer

2019 ◽  
Vol 53 (4) ◽  
pp. 443-452 ◽  
Author(s):  
Qing-Qing Chang ◽  
Chun-Yan Chen ◽  
Zhao Chen ◽  
Shuai Chang
Keyword(s):  
Cervical Cancer ◽  
Cancer Cells ◽  
Bioinformatics Analysis ◽  
Downstream Target ◽  
Cervical Cancer Cells ◽  
Proliferation And Metastasis ◽  
Underlying Mechanisms ◽  
Smad3 Expression ◽  
Proliferation And Invasion ◽  
Variant Translocation

Abstract Background Cervical cancer is one of the most frequent malignancies among females worldwide. Increasing evidence have indicated the participation of long noncoding RNAs (lncRNAs) in the progression and metastasis of cervical cancer. Our present study was conducted to explore the effects of lncRNA plasmacytoma variant translocation 1 (PVT1) on the progression of cervical cancer and the underlying mechanisms. Materials and methods Expressions of PVT1, miR-140-5p and Smad3 in cervical cancer cell lines were detected by qRT-PCR and western blotting. Bioinformatics analysis and luciferase assays were used to elucidate the potential correlations between PVT1, miR-140-5p and Smad3. The roles of PVT1 on the progression of cervical cancer cells were determined by transfecting sh-RNA through series function assays such as colony formation assay, wound healing assay, transwell assay. Results PVT1 and Smad3 were upregulated, and miR-140-5p was downregulated in cervical cancer cells. PVT1 could bind directly with miR-140-5p, and Smad3 was a downstream target of miR-140-5p. Inhibition of PVT1 could enhance expression of miR-140-5p, inhibit the expression of Smad3, significantly inhibited the proliferation, migration, invasion in cervical cancer cells. While transfection of miR-140-5p inhibitor could partially reverse the above changes in cervical cancer cells. Conclusions The results revealed that PVT1 could promote the proliferation and metastasis via increasing the Smad3 expression by sponging miR-140-5p, which might be a promising prognostic and therapeutic target for cervical cancer.

scholarly journals The E545 Mutation of PIK3CA in Cervical Cancer Promotes the Survival by Several Different Pathways

2021 ◽  
Author(s):  
Yan Chen ◽  
Ma-Chi Yuan ◽  
Jia-Zhen Shi ◽  
Xia Zhao ◽  
Nan He ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Differential Expression ◽  
Bioinformatics Analysis ◽  
Cancer Tissue ◽  
Ppi Network ◽  
Tissue Samples ◽  
Cervical Cancer Tissue ◽  
Differential Expression Genes ◽  
High Degree

Abstract Backgroud: The E545 mutation of PIK3CA in Cervical cancer is frequently happened. But the role of E545 mutation of PIK3CA in Cervical cancer is not clear.Methods: In this study, we analysised the molecular signatures of E545 mutation Cervical cancer by bioinformatics methods.Results: We collected transcriptome sequencing results of 227 no mutation cervical cancer tissue samples and 36 mutation cervical cancer tissue samples, then analyzed the data combining bioinformatics methods. A total of 5 differential expression miRNAs were obtained, including 3 up-regulated miRNAs, 1 down-rugulated miRNA. A total of 174 differential expression genes were obtained, including 132 up-regulated genes, 40 down-rugulated genes. GO analysis suggested that the up-regulated DEGs were mainly enriched in transcription factor activity, leukotriene signaling pathway and so on. Besides, we constructed a PPI network with DEGs to screen the top hub genes with a relatively high degree of connectivity. Among them CAV1, KRT20, FOS, had a degree of connectivity larger than 5 and functioned as hub module genes to promote the survival of E545 mutation cervical cancer. We also identified different miRNA-DEG axis, including hsa-mir-449a-AXL, hsa-mir-508-CGA, COL15A1, NNMT, hsa-mir-552-CHST6, NWD1. These axis regulated the survival of E545 mutation cervical cancer togetherly. Conclusions: In conclusion, this study identified DEGs and screened the key genes and pathways closely related to E545 mutation in Cervical cancer by bioinformatics analysis, These results might hold promise for finding potential therapeutic targets of cervical cancer harboring E545 mutation of PI3KCA.

scholarly journals Bioinformatics analysis shows that TOP2A functions as a key candidate gene in the progression of cervical cancer

2020 ◽  
Author(s):  
Qinfei Zhao ◽  
Huaying Li ◽  
Longyu Zhu ◽  
Suping Hu ◽  
Xuxiang Xi ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Candidate Gene ◽  
Bioinformatics Analysis
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