Monocomponent Nanodots with Dichromatic Output Regulated by Synergistic Dual-Stimuli for Cervical Cancer Tissue Imaging and Photodynamic Tumor Therapy

2021 ◽  
Author(s):  
Yujia Liu ◽  
Yibing Li ◽  
Le Yu ◽  
Zhaoyi Yang ◽  
Ju Ding ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Tumor Therapy ◽  
Tissue Imaging ◽  
Cancer Tissue ◽  
Cervical Cancer Tissue

scholarly journals IL-10, IL-15, IL-17, and GMCSF levels in cervical cancer tissue of Tanzanian women infected with HPV16/18 vs. non-HPV16/18 genotypes

2015 ◽  
Vol 10 (1) ◽  
Author(s):  
Adriana C Vidal ◽  
David Skaar ◽  
Rachel Maguire ◽  
Seyram Dodor ◽  
Laura W Musselwhite ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Cancer Tissue ◽  
Cervical Cancer Tissue

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 Diagnostic Availability of Estrogen Receptor Alpha mRNA on Cervical Cancer Tissue

2018 ◽  
Vol 50 (4) ◽  
pp. 449-456
Author(s):  
Geehyuk Kim ◽  
Kwangmin Yu ◽  
Jungho Kim ◽  
Seoyong Kim ◽  
Sunyoung Park ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Estrogen Receptor ◽  
Estrogen Receptor Alpha ◽  
Cancer Tissue ◽  
Receptor Alpha ◽  
Cervical Cancer Tissue

scholarly journals A high yield gold nanoparticle-based DNA isolation method for human papillomaviruses genotypes from cervical cancer tissue samples

2019 ◽  
Author(s):  
Noorossadat Seyyedi ◽  
Fatemeh Farjadian ◽  
Ali Farhadi ◽  
Gholamreza Rafiei Dehbidi ◽  
Reza Ranjbaran ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Dna Sequences ◽  
Hpv Infection ◽  
Human Papillomaviruses ◽  
High Yield ◽  
Cancer Tissue ◽  
Purification Method ◽  
Tissue Samples ◽  
Hpv Dna ◽  
Cervical Cancer Tissue

Gold nanoparticles (AuNPs) are commonly used in biosensors of various kinds. The purification of DNA from cancer tissues is an important step in diagnostic and therapeutic development, but current methods are not optimal. Many cervical cancer patients are also susceptible to high-risk human papillomavirus (HR-HPV) infection. Accurate viral diagnosis has so far relied on the extraction of adequate amounts of DNA from formalin-fixed, paraffin-embedded (FFPE) tissue samples. Since the sensitivity and specificity of commercially available purification kits are not optimal, we designed a DNA purification method based on AuNPs to purify sufficient amounts of HR-HPV DNA from cervical cancer tissue samples. AuNPs were coated with a series of oligonucleotide probes to hybridize to specific DNA sequences of HR-HPV genotypes. With this method, we recovered 733 out of 800 copies of type-specific HPV DNA with complete specificity, compared to 36 copies with a standard commercial kit (Qiagen FFPE).

Quantitative Analysis of Heparanase Gene Expression in Normal Cervical, Cervical Intraepithelial Neoplastic, and Cervical Carcinoma Tissues

2009 ◽  
Vol 19 (9) ◽  
pp. 1614-1619 ◽  
Author(s):  
Eugene Varchalama ◽  
Alexander Rodolakis ◽  
Areti Strati ◽  
Theocharis Papageorgiou ◽  
Christos Valavanis ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cervical Cancer ◽  
Heparan Sulfate ◽  
Mrna Expression ◽  
Tumor Size ◽  
Invasive Cervical Cancer ◽  
Cancer Tissue ◽  
Low Grade ◽  
Tissue Samples ◽  
Cervical Cancer Tissue

Heparanase is an endoglycosidase that specifically cleaves heparan sulfate side chains of heparan sulfate proteoglycans, the major proteoglycans in the extracellular matrix and cell surfaces. Traditionally, heparanase activity was implicated in cellular invasion associated with angiogenesis, inflammation, and cancer metastasis. More recently, heparanase up-regulation was documented in an increasing number of primary human tumors. Ιn this study, we sought to investigate the expression of heparanase messenger RNA (mRNA) in normal cervical tissue and intraepithelial cervical lesion and its clinicopathologic importance in invasive cervical cancer. Gene expression of heparanase was assessed by quantitative real-time reverse transcriptase polymerase chain reaction in 28 normal cervical, 26 intraepithelial neoplastic, and 48 cervical cancer tissue samples. Heparanase mRNA expression was different between the 3 groups and lower in normal cervical specimens in relationship with intraepithelial cervical lesions and invasive cervical cancer tissue samples (P = 0.048). Gradually increasing expression of heparanase was evident as the cells progressed from low-grade to high-grade squamous intraepithelial lesions (P = 0.002). In invasive cervical cancer cases, there was a direct correlation between heparanase expression and tumor size (P = 0.002). In cases treated with radical hysterectomy and pelvic lymphadenectomy, the heparanase mRNA expression was significantly higher in tumors exhibiting lymph vascular space invasion (P = 0.044) and in cases with big tumor size (P = 0.005). In our study, we did not find any significant correlation between disease-free and overall survival rates and expression of heparanase (P = 0.396 and P = 0.712, respectively). The results of this study suggest that the gene expression of heparanase in cervical cancer enhances growth, invasion, and angiogenesis of the tumor and may have therapeutic applications.

Development of Image Processing Algorithm for Cytological Diagnosis of Uterine Cervical Cancer Tissue Examination

2013 ◽  
Vol 694-697 ◽  
pp. 2027-2031
Author(s):  
Han Yeong Oh ◽  
Ha Ju So ◽  
Seong Hyun Kim ◽  
Dong Wook Kim ◽  
Hyun Chang Kim
Keyword(s):  
Image Processing ◽  
Cervical Cancer ◽  
Uterine Cervical Cancer ◽  
Cancer Tissue ◽  
Cytological Diagnosis ◽  
Process Automation ◽  
Image Processing Algorithm ◽  
Cell Image ◽  
Cervical Cancer Tissue ◽  
Cellular Domain

In this study is relevant to cell area extraction for cytological diagnosis of liquid-based cell examination being used for early diagnosis of uterine cervical cancer by utilizing image processing. As existing cytological diagnosis process has been performed manually by cytotechnologist, the amount of cell image that could be processed was limited. Therefore, in this study, cellular domain extraction through which automatic processing of cytological diagnosis process is enabled was performed and its condition was established depending on the size of cell nucleus based on cytological diagnosis standard of uterine cervical cancer cell. Obtained cell image was processed by hough transform matching with cell image by using matlab through preprocessing phase. As a result, 28 sample images among total 30 sample images were succeeded in finding out target cell and two sample images failed to find it. In the future, modification and verification for such failure case may be required to be performed. It is expected that the result of this study could be utilized for diagnosis process automation of liquid-based cell examination.

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