Enhancing Cervical Cancer Screening: New Diagnostic Methodologies, Triage, and Risk Stratification in Prevention and Treatment
Abstract
:1. Introduction
2. Methods
2.1. Literature Search
2.2. Review Approach and Justification
3. Results and Discussion
3.1. Molecular Mechanisms of HPV-Driven Cancerogenesis
3.2. Prevalence of HPV in the World Regions
3.3. HPV and Cervico-Vaginal Microbiota
3.4. HPV and Premalignant Cervical Lesions: Modern Diagnostic Biomarkers
3.5. HPV and Cervical Cancer Screening: Updated Approach
3.6. Psychological Factors in HPV Infection
4. Strengths and Limitations
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Molecular Mechanism | HPV Type | Key Findings | References |
---|---|---|---|
E6 oncoprotein and p53 degradation | HPV-16, HPV-18, HPV-31, HPV-33, HPV-45 | E6 binds to E6-associated protein (E6-AP), leading to ubiquitin-mediated degradation of p53. This prevents apoptosis, disrupts DNA damage repair, and promotes cellular proliferation. | [4,35] |
E7 oncoprotein and Rb inactivation | HPV-16, HPV-18, HPV-31, HPV-33, HPV-45, HPV-52 | E7 binds and degrades the retinoblastoma (Rb) protein, releasing E2F transcription factors. This leads to uncontrolled cell cycle progression, increased proliferation, and chromosomal instability. | [23,32] |
HPV DNA integration into host genome | HPV-16, HPV-18, HPV-35, HPV-52 | Viral integration into fragile sites of the host genome disrupts tumor suppressor genes and leads to uncontrolled oncogene expression. HPV integration often occurs near oncogenes such as MYC, leading to increased tumor aggressiveness. | [23,26] |
Loss of E2 gene regulation | HPV-16, HPV-18, HPV-52, HPV-58 | HPV integration disrupts the viral E2 gene, which normally inhibits E6 and E7 expression. Loss of E2 leads to sustained overexpression of oncogenic proteins, increasing malignant potential. | [22,32] |
Epigenetic modifications (DNA methylation and histone changes) | HPV-16, HPV-18, HPV-31, HPV-58 | HPV induces hypermethylation of tumor suppressor genes (e.g., p16INK4a, RASSF1, CADM1, DAPK1) and histone modifications, silencing protective pathways and increasing oncogenesis. | [23,37] |
MicroRNA (miRNA) dysregulation | HPV-16, HPV-18, HPV-33, HPV-52, HPV-58 | HPV alters host miRNA expression: upregulation of oncogenic miRNAs (miR-21, miR-155) enhances proliferation and invasion, while downregulation of tumor-suppressive miRNAs (miR-375, miR-34a) promotes immune evasion and metastasis. | [25,37] |
Oxidative stress and inflammation | HPV-16, HPV-18, HPV-45, HPV-58 | HPV-induced chronic inflammation (elevated IL-6, TNF-α, and COX-2) leads to oxidative DNA damage, enhancing genomic instability and malignant transformation. | [23,24] |
Telomerase activation (hTERT overexpression) | HPV-16, HPV-18, HPV-33 | E6 upregulates human telomerase reverse transcriptase (hTERT), enabling indefinite cell replication, bypassing senescence, and promoting tumor progression. | [4,19] |
Cell adhesion and EMT (epithelial–mesenchymal transition) | HPV-16, HPV-18, HPV-45, HPV-58 | E6/E7 downregulates E-cadherin and upregulates N-cadherin, vimentin, and Snail, promoting invasion, metastasis, and resistance to therapy. | [23,24] |
Region | Most Common HPV Genotypes | HPV Prevalence in Cervical Cancer Cases | Reference |
---|---|---|---|
Sub-Saharan Africa | HPV-16, HPV-18, HPV-35, HPV-52 | 86.5% | [16,28] |
Middle East and North Africa (MENA) | HPV-16, HPV-18, HPV-51 | 81% | [16] |
Asia-Pacific | HPV-16, HPV-18, HPV-45, HPV-52, HPV-58 | 79.3% | [17,18] |
China | HPV-16, HPV-52, HPV-58 | High CIN1 prevalence | [18,19] |
Korea | HPV-16, HPV-58, HPV-52 | 85% in HSIL+ cases | [20] |
India | HPV-16, HPV-18 | 85% | [24] |
Saudi Arabia | HPV-16, HPV-18 | Significant correlation with cervical cancer | [25] |
Brazil | HPV-16, HPV-18 | 25% (cervix), 36% (penile cancer) | [26] |
Nigeria | HPV-16, HPV-18, HPV-35, HPV-52, HPV-58 | 25–76% (regional variation) | [27] |
Europe and North America | HPV-16, HPV-18, HPV-31, HPV-33 | Highest prevalence of squamous cell carcinoma | [23] |
Factor | HPV Type | Key Findings | References |
---|---|---|---|
Protective microbiota | HPV-16, HPV-18, HPV-58 | Lactobacillus crispatus dominance is associated with a lower risk of HPV infection and persistence, while its depletion increases susceptibility. | [20] |
Microbiota disruptions (dysbiosis) | HPV-16, HPV-18, HPV-52 | Increased vaginal microbiota diversity (alpha and beta diversity) correlates with HPV persistence and progression to high-grade lesions. | [15,28] |
HPV-associated bacteria | HPV-16, HPV-18, HPV-58, HPV-52 | Lactobacillus iners, Gardnerella vaginalis, Atopobium, Prevotella, Fusobacterium, and Sneathia are frequently found in HPV-infected women and those with cervical dysplasia. | [16,19] |
Impact on immune response | HPV-16, HPV-31, HPV-33, HPV-45 | Dysbiosis weakens the host immune response, facilitating HPV persistence and carcinogenesis. Chronic inflammation caused by Sneathia and Fusobacterium promotes oncogenic progression. | [23,37] |
Mechanisms of HPV persistence | HPV-16, HPV-18, HPV-35, HPV-52 | Anaerobic bacteria disrupt cervical mucus, produce carcinogenic metabolites (e.g., nitrosamines), and damage epithelial integrity, aiding HPV integration. | [4,26] |
Probiotics and microbiota restoration | HPV-16, HPV-18, HPV-58, HPV-52 | Probiotic therapies (e.g., Lactobacillus crispatus supplementation) may prevent HPV persistence, modulate the immune response, and restore vaginal microbiota homeostasis. | [25,32] |
Ethnic and regional variations | HPV-16, HPV-18, HPV-52, HPV-58, HPV-35 | Latina and Afro-Caribbean women have distinct microbiome patterns that may influence HPV infection outcomes. Higher prevalence of L. iners and anaerobes correlates with persistent HPV in these populations. | [23,24] |
Biomarker | Diagnostic Role | Sensitivity/Specificity | Reference |
---|---|---|---|
HPV DNA testing | Detects presence of high-risk HPV | High sensitivity, lower specificity | [38] |
E6/E7 oncoprotein test | Identifies active HPV-driven oncogenesis | Sensitivity: 82%, specificity: high | [39] |
p16/Ki-67 dual staining | Detects high-risk lesions (CIN2+) | Sensitivity: 93%, specificity: 60% | [43] |
hTERC gene amplification | Predicts lesion progression | Sensitivity: 100%, specificity: 98.11% | [44] |
DNA methylation (FAM19A4/miR-124-2 test) | Identifies CIN2+/CC lesions | High specificity (98%) | [43] |
MicroRNA panels (miR-9, miR-21, miR-375) | Prognostic indicators for CIN and CC | Sensitivity: 52.9–67.3%, specificity: 76.4–94.4% | [58] |
Screening Method | HPV Type | Key Findings | References |
---|---|---|---|
HPV DNA testing (primary screening) | HPV-16, HPV-18, HPV-31, HPV-33, HPV-52 | The WHO recommends HPV DNA testing as the most effective primary screening tool due to its high sensitivity. It detects high-risk HPV (hrHPV) before cytological abnormalities appear. | [28,38] |
E6/E7 oncoprotein testing | HPV-16, HPV-18 | E6/E7 mRNA tests have higher specificity than DNA tests, reducing false positives and unnecessary colposcopies. Studies confirm over 82% specificity across all patient groups. | [39,40] |
p16/Ki-67 dual staining | HPV-16, HPV-18, HPV-31, HPV-33 | Used for triaging HPV-positive women, this test improves specificity in detecting CIN2+ lesions. It is particularly valuable in ASC-US/LSIL cases, reducing unnecessary colposcopies. | [23,43] |
hTERC gene amplification | HPV-16, HPV-18, HPV-33 | A predictor of precancerous lesion progression. Combining hTERC with cytology and HPV testing improves sensitivity (up to 100%) and specificity (98.11%) for CIN2+. | [42,44] |
DNA methylation biomarkers | HPV-16, HPV-18, HPV-52, HPV-58 | FAM19A4/miR124-2 and ZNF582 methylation tests show high specificity (~98%) for detecting CIN2+/CIN3 lesions and are effective for triaging HPV-positive women. | [23,42] |
Self-sampling for HPV testing | HPV-16, HPV-18, HPV-31, HPV-52 | Self-sampling increases screening participation, particularly in low-resource settings. Devices such as Evalyn® Brush, FLOQSwabs®, and Delphi Screener demonstrate diagnostic accuracy comparable to clinician-collected samples. | [23,24] |
Urine-based HPV testing | HPV-16, HPV-18, HPV-58 | PCR-based urine tests (GP5+/6+, SPF10) detect ≥79% of CIN2+ cases. While useful, they have 21% lower sensitivity in primary screening compared to cervical samples. | [15,19] |
Menstrual blood-based HPV testing | HPV-16, HPV-18, HPV-33, HPV-52 | Testing menstrual blood for HPV provides a cost-effective alternative with sensitivity ranging from 82.8% to 97.7%. Diagnostic accuracy is highest when collected on the first day of menstruation. | [23,26] |
AI-assisted cervical cytology | HPV-16, HPV-18, HPV-31, HPV-33 | AI-based Pap test analysis improves detection of precancerous lesions, reducing false negatives and human errors. Digital cytology aids in early cancer diagnosis. | [24,42] |
Cultural influences on HPV screening uptake | HPV-16, HPV-18, HPV-31, HPV-52 | Religious and cultural beliefs influence self-sampling acceptance. In Muslim communities, self-collection is preferred due to privacy concerns, improving screening uptake. | [23,25] |
Strategies to increase screening accessibility | HPV-16, HPV-18, HPV-33, HPV-45 | Self-sampling and mobile health workers improve coverage in low-income areas. WHO aims for 70% screening coverage by 2030 to eliminate cervical cancer. | [24,42] |
Psychological Factor | Description | Impact on HPV Infection | References |
---|---|---|---|
Stigma and shame | Negative emotions and social stigma related to sexually transmitted infections (STIs), particularly HPV. | Stigmatization can lead to avoidance of diagnosis and treatment, increasing the risk of HPV-related complications like cervical cancer. It also reduces open communication about prevention and treatment. | [75,76] |
Fear and anxiety | Emotional responses such as fear of infection and anxiety about potential health risks related to HPV. | Fear and anxiety may lead individuals to delay or avoid necessary screenings and medical consultations, raising the risk of undiagnosed or untreated HPV-related diseases. | [76,77] |
Self-esteem and body image | The perception of one’s body and self-worth, particularly in relation to the diagnosis of an STI like HPV. | Lower self-esteem due to the stigma of having an STI may result in poor engagement with medical care, hinder discussions about preventive behaviors, and contribute to further emotional distress. | [76,78] |
Depression | Feelings of sadness, loss of interest in activities, and a lack of motivation to address health needs. | Depression can lead to neglect of health behaviors such as regular screenings, vaccination, and treatment adherence, resulting in worse health outcomes for individuals with HPV. | [76] |
Perceived control | Belief in one’s ability to manage the course of an illness like HPV. | Individuals who feel they lack control over their health may be less likely to engage in preventive measures, follow treatment guidelines, or seek medical help, leading to worsened health outcomes. | [79,80] |
Social support | Emotional, informational, and practical assistance provided by friends, family, and others. | Strong social support promotes better mental health, encourages positive health behaviors like vaccination and screenings, and leads to improved health outcomes in individuals with HPV. | [81] |
Health literacy | Knowledge and understanding of health information, particularly regarding HPV transmission, prevention, and treatment. | Higher health literacy leads to better adherence to prevention methods (e.g., vaccination), more frequent screenings, and better management of HPV-related risks. | [76,82] |
Coping mechanisms | Psychological strategies employed to deal with the stress or adversity caused by an HPV diagnosis. | Effective coping strategies (e.g., problem-solving, seeking social support) can result in healthier responses to HPV-related stress, adherence to treatment plans, and better overall health outcomes. | [83,84] |
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Kamzayeva, N.; Bapayeva, G.; Terzic, M.; Primbetov, B.; Imankulova, B.; Kim, Y.; Sultanova, A.; Kongrtay, K.; Kadroldinova, N.; Ukybassova, T. Enhancing Cervical Cancer Screening: New Diagnostic Methodologies, Triage, and Risk Stratification in Prevention and Treatment. Life 2025, 15, 367. https://doi.org/10.3390/life15030367
Kamzayeva N, Bapayeva G, Terzic M, Primbetov B, Imankulova B, Kim Y, Sultanova A, Kongrtay K, Kadroldinova N, Ukybassova T. Enhancing Cervical Cancer Screening: New Diagnostic Methodologies, Triage, and Risk Stratification in Prevention and Treatment. Life. 2025; 15(3):367. https://doi.org/10.3390/life15030367
Chicago/Turabian StyleKamzayeva, Nazira, Gauri Bapayeva, Milan Terzic, Berik Primbetov, Balkenzhe Imankulova, Yevgeniy Kim, Arailym Sultanova, Kuralay Kongrtay, Nazira Kadroldinova, and Talshyn Ukybassova. 2025. "Enhancing Cervical Cancer Screening: New Diagnostic Methodologies, Triage, and Risk Stratification in Prevention and Treatment" Life 15, no. 3: 367. https://doi.org/10.3390/life15030367
APA StyleKamzayeva, N., Bapayeva, G., Terzic, M., Primbetov, B., Imankulova, B., Kim, Y., Sultanova, A., Kongrtay, K., Kadroldinova, N., & Ukybassova, T. (2025). Enhancing Cervical Cancer Screening: New Diagnostic Methodologies, Triage, and Risk Stratification in Prevention and Treatment. Life, 15(3), 367. https://doi.org/10.3390/life15030367