Overview of genetic and epigenetic regulation of human papillomavirus and apoptosis in cervical cancer

Yadav, Chetna; Yadav, Ritu; Chabbra, Ravindresh; Nanda, Smiti; Ranga, Shalu; Kadian, Lokesh; Ahuja, Parul

doi:10.1007/s10495-023-01812-w

Cited by 4 publications

(2 citation statements)

References 153 publications

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“…HPV E6 targets BAX as well as p53 tumor suppressor to inhibit apoptosis in cervical cancer 33 . In addition, HPV E7 attenuates apoptosis by suppressing the binding of pro‐apoptotic cellular factor SIVA‐1 to anti‐apoptotic factor BCL‐X(L) in human immortalized keratinocytes 34 .…”

Section: Discussionmentioning

confidence: 99%

“…HPV E6 targets BAX as well as p53 tumor suppressor to inhibit apoptosis in cervical cancer. 33 In addition, HPV E7 attenuates apoptosis by suppressing the binding of pro-apoptotic cellular factor SIVA-1 to anti-apoptotic factor BCL-X(L) in human immortalized keratinocytes. 34 Expression of c-IAP2 (encoded by BIRC3) is associated with resistance to apoptosis in an NF-κB dependent manner in HPV16 E6/E7-immortalized human oral keratinocytes, and BIRC3 knockdown caused cell death in HPV18-positive cervical carcinoma cells.…”

Section: Impact Of Autophagy Inhibitor On 5-fuinduced Cell Death In H...mentioning

confidence: 99%

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HPV16 E6 and E7 are involved in inhibition of autophagy and maintenance of cancer stem cell properties in HPV16‐positive oral squamous cell carcinoma cells

Shigeishi

Sugiyama

Akagi

et al. 2023

Oral Science International

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AimThe involvement of human papillomavirus (HPV) E6/E7 in autophagy has not been fully elucidated in oral squamous cell carcinoma (OSCC) cells. The objective of this study was to clarify the association between HPV E6/E7 and autophagy and cancer stem cell properties such as self‐renewal ability and chemotherapy resistance in HPV16‐positive OSCC cells.MethodsUM‐SCC‐104 HPV16‐positive OSCC cells were cultured on laminin 332‐coated silicone gel. The impact of HPV16 E6 or E7 siRNA transfection on cell proliferation, spheroid formation, 5‐fluorouracil (5‐FU)‐induced cell death, and autophagy was investigated. After treatment with rapamycin, DAPGreen was used to detect autophagosome formation.ResultsHPV16 E6 or E7 siRNA transfection resulted in knockdown of both E6 and E7 in UM‐SCC‐104 cells. HPV16 E6/E7 knockdown inhibited cell proliferation, mRNA expression of stem cell markers (i.e., CD44, ALDH1, BMI1, OCT4, and NANOG), and spheroid formation. Furthermore, HPV16 E6/E7 knockdown enhanced 5‐FU‐induced cell death. Additionally, mRNA expression of autophagy‐related genes such as ATG5 and BECN1 was significantly increased after HPV16 E6/E7 knockdown. Furthermore, HPV16 E6/E7 knockdown augmented rapamycin‐induced autophagy. Next, we found that miR‐30a‐5p is indicated to interact with the 3′‐untranslated region of ATG5 and BECN1 using TargetScan. However, significant induction of autophagy was not found after miR‐30a‐5p inhibitor transfection. Importantly, 5‐FU‐induced cell death was significantly attenuated by chloroquine autophagy inhibitor in HPV16 E6/E7 knockdown cells.ConclusionHPV16 E6/E7 is involved in autophagy regulation as well as in the maintenance of cancer stem cell features in OSCC cells.

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Section: Discussionmentioning

confidence: 99%

Section: Impact Of Autophagy Inhibitor On 5-fuinduced Cell Death In H...mentioning

confidence: 99%

HPV16 E6 and E7 are involved in inhibition of autophagy and maintenance of cancer stem cell properties in HPV16‐positive oral squamous cell carcinoma cells

Shigeishi

Sugiyama

Akagi

et al. 2023

Oral Science International

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Enhancing cervical cancer diagnosis with graph convolution network: AI-powered segmentation, feature analysis, and classification for early detection

Fahad,

Azam,

Montaha

et al. 2024

Multimed Tools Appl

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Cervical cancer is a prevalent disease affecting the cervix cells in women and is one of the leading causes of mortality for women globally. The Pap smear test determines the risk of cervical cancer by detecting abnormal cervix cells. Early detection and diagnosis of this cancer can effectively increase the patient’s survival rate. The advent of artificial intelligence facilitates the development of automated computer-assisted cervical cancer diagnostic systems, which are widely used to enhance cancer screening. This study emphasizes the segmentation and classification of various cervical cancer cell types. An intuitive but effective segmentation technique is used to segment the nucleus and cytoplasm from histopathological cell images. Additionally, handcrafted features include different properties of the cells generated from the distinct cervical cytoplasm and nucleus area. Two feature rankings techniques are conducted to evaluate this study’s significant feature set. Feature analysis identifies the critical pathological properties of cervical cells and then divides them into 30, 40, and 50 sets of diagnostic features. Furthermore, a graph dataset is constructed using the strongest correlated features, prioritizes the relationship between the features, and a robust graph convolution network (GCN) is introduced to efficiently predict the cervical cell types. The proposed model obtains a sublime accuracy of 99.11% for the 40-feature set of the SipakMed dataset. This study outperforms the existing study, performing both segmentation and classification simultaneously, conducting an in-depth feature analysis, attaining maximum accuracy efficiently, and ensuring the interpretability of the proposed model. To validate the model’s outcome, we tested it on the Herlev dataset and highlighted its robustness by attaining an accuracy of 98.18%. The results of this proposed methodology demonstrate the dependability of this study effectively, detecting cervical cancer in its early stages and upholding the significance of the lives of women.

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The role of long non-coding RNAs and circular RNAs in cervical cancer: modulating miRNA function

Heidari-Ezzati,

Moeinian,

Ahmadian-Nejad

et al. 2024

Front. Cell Dev. Biol.

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Overview of genetic and epigenetic regulation of human papillomavirus and apoptosis in cervical cancer

Cited by 4 publications

References 153 publications

HPV16 E6 and E7 are involved in inhibition of autophagy and maintenance of cancer stem cell properties in HPV16‐positive oral squamous cell carcinoma cells

HPV16 E6 and E7 are involved in inhibition of autophagy and maintenance of cancer stem cell properties in HPV16‐positive oral squamous cell carcinoma cells

Enhancing cervical cancer diagnosis with graph convolution network: AI-powered segmentation, feature analysis, and classification for early detection

The role of long non-coding RNAs and circular RNAs in cervical cancer: modulating miRNA function

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