Clinical Significance of Detection of Human Papilloma Virus DNA and E6/E7 mRNA for Cervical Cancer Patients

Yu, Tingting; Wang, Chunyan

doi:10.14715/cmb/2021.67.6.21

Cited by 2 publications

(3 citation statements)

References 7 publications

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“…For instance, Valença et al, reported in their study that out of 111 women who underwent biopsy and an E6/E7 test, the positivity rate of the E6/E7 test was 84.7% in women with cervical intraepithelial neoplasia (CIN) grade 2 or higher lesions [26]. In addition, Yu and Wang 2022 reported that the presence of HPV DNA and HPV E6/E7 mRNA were significantly higher in cases of CIN and cervical cancer than in cases of inflammation of the cervix [32]. Yu and Wang also reported that the specificity of HPV E6/E7 mRNA was lower than that of HPV DNA in detecting low-grade intraepithelial neoplasia, but it performed better in detecting high-grade intraepithelial neoplasia and cervical cancer [32].…”

Section: Hr-hpv Frequency (%)mentioning

confidence: 99%

“…In addition, Yu and Wang 2022 reported that the presence of HPV DNA and HPV E6/E7 mRNA were significantly higher in cases of CIN and cervical cancer than in cases of inflammation of the cervix [32]. Yu and Wang also reported that the specificity of HPV E6/E7 mRNA was lower than that of HPV DNA in detecting low-grade intraepithelial neoplasia, but it performed better in detecting high-grade intraepithelial neoplasia and cervical cancer [32]. Furthermore, Cao et al reported that the total E6/E7 mRNA positivity rate was 67.27%…”

Section: Hr-hpv Frequency (%)mentioning

confidence: 99%

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Detection of Human Papillomavirus DNA and E6/E7 mRNA from HPV Genotypes 16, 18, 31 and 33 in Histologically Confirmed Cases of Cervical Cancer and Precancerous Lesions in Burkina Faso

Zohoncon,

Bello,

Bado

et al. 2023

AJMB

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Introduction: Cervical cancer, caused by persistent high-risk human papillomavirus (HPV) infection, remains a global public health problem. The cellular transformation and maintenance of the malignant phenotype of these HPVs are attributed to the viral oncoproteins E6 and E7. Objective: This study aims to detect the presence of human papillomavirus DNA and E6/E7 oncoprotein mRNA of HPV genotypes 16, 18, 31 and 33 in cases of cervical cancer and precancerous lesions, histologically confirmed in Burkina Faso. Methods: This descriptive cross-sectional study focused on cases of cervical cancer and high-grade intraepithelial neoplasia (CIN) and was conducted from June to December 2022. One hundred (100) samples of fixed and paraffin-embedded tissues were collected from the pathological anatomy and cytology laboratories of hospitals in the capital of Burkina Faso. High-risk human papillomavirus (HR-HPV) DNA was detected using multiplex real-time PCR, while the presence of E6 and E7 mRNA in cervical cancer and highgrade CIN samples was determined using real-time Reverse Transcriptase-PCR (RT-PCR) with TaqMan probes. Results: The mean age of women diagnosed with cervical cancer and high-grade CIN was 50.

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Section: Hr-hpv Frequency (%)mentioning

confidence: 99%

Section: Hr-hpv Frequency (%)mentioning

confidence: 99%

Detection of Human Papillomavirus DNA and E6/E7 mRNA from HPV Genotypes 16, 18, 31 and 33 in Histologically Confirmed Cases of Cervical Cancer and Precancerous Lesions in Burkina Faso

Zohoncon,

Bello,

Bado

et al. 2023

AJMB

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“…Despite being a deadly disease, CC can be cured if it can be detected in the early stages [12,13]. For clinical initiative, it is a very crucial task to identify the cancerous cell which is known as a cyst [14]. Detecting cyst from cervix images ensures clinicians for patients regarding CC.…”

Section: Introductionmentioning

confidence: 99%

Early-Stage Cervical Cancerous Cell Detection from Cervix Images Using YOLOv5

Ontor¹,

Ali²,

Ahmed³

et al. 2023

Computers, Materials &Amp; Continua

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Cervical Cancer (CC) is a rapidly growing disease among women throughout the world, especially in developed and developing countries. For this many women have died. Fortunately, it is curable if it can be diagnosed and detected at an early stage and taken proper treatment. But the high cost, awareness, highly equipped diagnosis environment, and availability of screening tests is a major barrier to participating in screening or clinical test diagnoses to detect CC at an early stage. To solve this issue, the study focuses on building a deep learning-based automated system to diagnose CC in the early stage using cervix cell images. The system is designed using the YOLOv5 (You Only Look Once Version 5) model, which is a deep learning method. To build the model, cervical cancer pap-smear test image datasets were collected from an open-source repository and these were labeled and preprocessed. Then the YOLOv5 models were applied to the labeled dataset to train the model. Four versions of the YOLOv5 model were applied in this study to find the best fit model for building the automated system to diagnose CC at an early stage. All of the model's variations performed admirably. The model can effectively detect cervical cancerous cell, according to the findings of the experiments. In the medical field, our study will be quite useful. It can be a good option for radiologists and help them make the best selections possible.

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Clinical Significance of Detection of Human Papilloma Virus DNA and E6/E7 mRNA for Cervical Cancer Patients

Cited by 2 publications

References 7 publications

Detection of Human Papillomavirus DNA and E6/E7 mRNA from HPV Genotypes 16, 18, 31 and 33 in Histologically Confirmed Cases of Cervical Cancer and Precancerous Lesions in Burkina Faso

Detection of Human Papillomavirus DNA and E6/E7 mRNA from HPV Genotypes 16, 18, 31 and 33 in Histologically Confirmed Cases of Cervical Cancer and Precancerous Lesions in Burkina Faso

Early-Stage Cervical Cancerous Cell Detection from Cervix Images Using YOLOv5

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