Survival Of Cervical Cancer Patients Research Articles

MRI radiomics and nutritional-inflammatory biomarkers: a powerful combination for predicting progression-free survival in cervical cancer patients undergoing concurrent chemoradiotherapy

ObjectiveThis study aims to develop and validate a predictive model that integrates clinical features, MRI radiomics, and nutritional-inflammatory biomarkers to forecast progression-free survival (PFS) in cervical cancer (CC) patients undergoing concurrent chemoradiotherapy (CCRT). The goal is to identify high-risk patients and guide personalized treatment.MethodsWe performed a retrospective analysis of 188 patients from two centers, divided into training (132) and validation (56) sets. Clinical data, systemic inflammatory markers, and immune-nutritional indices were collected. Radiomic features from three MRI sequences were extracted and selected for predictive value. We developed and evaluated five models incorporating clinical features, nutritional-inflammatory indicators, and radiomics using C-index. The best-performing model was used to create a nomogram, which was validated through ROC curves, calibration plots, and decision curve analysis (DCA).ResultsModel 5, which integrates clinical features, Systemic Immune-Inflammation Index (SII), Prognostic Nutritional Index (PNI), and MRI radiomics, showed the highest performance. It achieved a C-index of 0.833 (95% CI: 0.792–0.874) in the training set and 0.789 (95% CI: 0.679–0.899) in the validation set. The nomogram derived from Model 5 effectively stratified patients into risk groups, with AUCs of 0.833, 0.941, and 0.973 for 1-year, 3-year, and 5-year PFS in the training set, and 0.812, 0.940, and 0.944 in the validation set.ConclusionsThe integrated model combining clinical features, nutritional-inflammatory biomarkers, and radiomics offers a robust tool for predicting PFS in CC patients undergoing CCRT. The nomogram provides precise predictions, supporting its application in personalized patient management.

Exploring MPC1 as a potential ferroptosis-linked biomarker in the cervical cancer tumor microenvironment: a comprehensive analysis

BackgroundThe increasing problems of drug and radiotherapy resistance in cervical cancer underscores the need for novel methods for its management. Reports indicate that the expression of MPC1 may be associated with the tumor microenvironment and the occurrence of ferroptosis in cervical cancer. The objective of this study was to visually illustrate the prognostic significance and immunological characterization of MPC1 in cervical cancer.MethodsThe expression profile and prognostic significance of MPC1 were analyzed using various databases, including UALCAN, TIMER2, GEPIA2, and Kaplan–Meier Plotter. TISIDB, TIMER2, and immunohistochemical analysis were used to investigate the correlation between MPC1 expression and immune infiltration. GO enrichment analysis, KEGG analysis, Reactome analysis, ConsensusPathDB, and GeneMANIA were used to visualize the functional enrichment of MPC1 and signaling pathways related to MPC1. The correlation analysis was carried out to examine the relationship between MPC1 and Ferroptosis gene in TIMER 2.0, ncFO, GEPIA Database and Kaplan–Meier Plotter.ResultsWe demonstrated that the expression levels of MPC1 in cervical cancer tissues were lower than those in normal cervical tissues. Kaplan–Meier survival curves showed shorter overall survival in cervical cancer patients with low levels of MPC1 expression. The expression of MPC1 was related to the infiltrating levels of tumor-infiltrating immune cells in cervical cancer. Moreover, MPC1 expression was associated with the iron-mediated cell death pathway, and several important ferroptosis genes were upregulated in cervical cancer cells. Furthermore, after knocking down MPC1 in HeLa cells, the expression of these genes decreased.ConclusionThese findings indicate that MPC1 functions as a prognostic indicator and plays a role in the regulation of the ferroptosis pathway in cervical cancer.

The effect of one-room CT guided brachytherapy on procedure time and cost in the treatment of cervical cancer

IntroductionBrachytherapy is associated with improved overall survival in cervical cancer patients, but the utilization seems hindered by high costs and relatively low reimbursement, particularly in the US. A one-room brachytherapy suite with CT (ORBT) could optimize the treatment workflow. By eliminating transport and waiting times, limiting applicator movement, and providing real-time applicator placement feedback, treatment time and costs could potentially be reduced. This study assesses the potential value of implementing ORBT in cervical cancer treatment. MethodsA variable cost model was developed to compare current (multi-room) brachytherapy workflows (MBRT) to ORBT, taking into account staff utilization, staff, equipment and consumables costs and room expenses. Two current care scenarios were simulated; applicator placement performed in the operating room (S1), and applicator placement performed in a brachytherapy suite (S2). For both scenarios literature reported fraction times of MBRT were compared to a range of ORBT times. Sensitivity analyses were performed to determine the influence of input parameters. ResultsIn scenario one, the results showed yearly savings of $45,572 up to $339,439 (USD), assuming a 5% and 20% reduction in fraction duration, respectively, in ORBT compared to MRBT. In scenario two, ORBT does not result in costs savings at 5% to 15% improvement. Therefore, only when ORBT results in a >20% improvement of fraction time, cost will be saved. DiscussionThe results indicate that reducing procedure time (using ORBT) can lead to cost savings, depending on the current workflow. Savings appear to depend mostly on applicator placement location, number of patients per year, and involved personnel.

Upregulation of long non-coding RNA ENSG00000267838 is related to the high risk of progression and non-response to chemoradiotherapy treatment for cervical cancer

Cervical cancer (CC) is a global public health concern, primarily caused by persistent infection with oncogenic types of human papillomavirus (HPV). The World Health Organization (WHO) has established a plan to eliminate CC as a public health issue by the year 2100. However, the implementation of the HPV vaccine is impeded by vaccine restrictions and misinformation despite its demonstrated effectiveness. The CC treatment is influenced by the disease stage, with an unfavorable prognosis for those in advanced stages. This study aimed to investigate the potential of long non-coding RNAs (lncRNAs) in CC by identifying and characterizing related lncRNAs, elucidating their regulatory mechanisms and molecular interactions, and analyzing their expression patterns in patients with diverse responses to chemoradiotherapy. Non-stem cells from CC were isolated using flow cytometry sorting and used for total RNA extraction. The RNA was used to build libraries that were subsequently sequenced using the Illumina Nextseq 550.417 lncRNAs that showed differentially expressed between CC patients who responded or not to treatment. Further analysis demonstrated that these lncRNAs significantly interact with several molecules, which play crucial roles in CC progression and therapeutic resistance. Statistical analysis correlated the expression profile of these lncRNAs with treatment efficacy. Three lncRNAs, ENSG00000267838, ENSG00000266340, and FRMD6-AS1, were identified with positive expression related to non-response to chemoradiotherapy and worse progression-free survival in CC patients. Specifically, lncRNA ENSG00000267838 has its up-regulation related to non-response and down-regulation to response to chemoradiotherapy treatment.

Association of MORC2 expression with progression-free survival in cervical cancer patients treated with concurrent chemoradiotherapy.

MORC family CW-type zinc finger 2 (MORC2) is a newly identified chromatin remodeling protein, and has been proposed as a prognostic biomarker associated with survival in some types of human cancer, but the role of MORC2 in cervical cancer remains unknown. Here, we investigated the role of MORC2 expression in predicting the survival outcomes of locally advanced cervical cancer patients treated with cisplatin-based concurrent chemoradiotherapy (CCRT). In this retrospectively study, we detected MORC2 immunohistochemical expression on 55 biopsies from patients who underwent CCRT. The association between the MORC2 expression and various clinicopathological characteristics were analyzed, as were association between MORC2 expression and locoregional failure and progression-free survival (PFS) of cervical cancer patients. MORC2 expression was positively associated with pelvic node metastasis and locoregional failure. Higher MORC2 expression was a significant indicator of worse PFS. Our results suggest that MORC2 expression may be a prognostic indicator in patients with locally advanced cervical cancer undergoing CCRT.

Immunoprognostic analysis of indoleamine 2,3-dioxygenase 1 in patients with cervical cancer.

The incidence of cervical cancer is increasing. Immunotherapies show better patient outcomes than monotherapies; however, the mainstay treatment for cervical cancer remains surgery and chemotherapy. Indoleamine 2,3-dioxygenase 1 (IDO1) acts on multiple tryptophan substrates, exhibiting antitumor, immunomodulatory, and antioxidant activities. Despite the association of elevated IDO1 expression with unfavorable outcomes in various cancers, its precise function in cervical cancer remains ambiguous. Here, we explored the prognostic significance of IDO1 in cervical carcinoma. Gene expression datasets were obtained from The Cancer Genome Atlas. Gene Expression Omnibus datasets were used for differential expression and functional correlation analyses. Using Human Protein Atlas alongside Tumor-Immune System Interaction Database, we assessed the association of IDO1 with survival rates. Given the link between cervical cancer prognosis and immune invasion, CIBERSORT was used to assess the connection between immune cells and IDO1, while the percentage of tumor-penetrating immune cells based on IDO1 expression in cervical cancer patients was analyzed using Tumor-Immune System Interaction Database. Incorporating a clinicopathological characteristic-based risk score model with IDO1 risk score, we devised a nomogram to predict cervical cancer patient survival. The effects of IDO1 in immune regulation and its prognostic significance were validated using data from patients with cervical cancer obtained from The Cancer Imaging Archive database. Compared with that in normal cervical tissues, IDO1 expression was significantly upregulated in cervical cancer tissues and significantly correlated with cervical cancer progression and prognosis. IDO1 expression showed a positive association with monocyte and macrophage abundance, while exhibiting a negative correlation with that of endothelial cells and eosinophils. Cox regression analyses highlighted IDO1 as the core immune gene implicated in cervical cancer. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses revealed an association of IDO1 with the metabolic pathways of tryptophan, phenylalanine, and tyrosine. Univariate and multivariate analyses revealed that elevated IDO1 expression correlates markedly with cervical cancer outcomes, suggesting it as a promising therapeutic target. The Cancer Imaging Archive data analysis revealed that the impact of anti-PD1 and CTLA4 therapy is more pronounced in cervical cancer patients exhibiting elevated IDO1 expression. IDO1 is a potential target for immunotherapy for cervical cancer.

Predictors of Clinical Hematological Toxicities under Radiotherapy in Patients with Cervical Cancer-A Risk Analysis.

Cervical cancer ranks third in frequency among female cancers globally and causes high mortality worldwide. Concurrent chemoradiotherapy improves the overall survival in cervical cancer patients by 6% but it can cause significant acute and late toxicities affecting patient quality of life. Whole pelvis radiotherapy doses of 10-20 Gy can lead to myelosuppression and to subsequent hematological toxicities since pelvic bones contain half of bone marrow tissue. A total of 69 patients with IB-IVB-staged cervical cancer have been included in this retrospective cohort study. We analyzed clinical adverse events and changes in blood cell counts (hemoglobin, neutrophils, leukocytes, and platelets) during radiation or chemoradiotherapy received at the Oncological Institute of Bucharest from 2018 to 2021. Decreases in hemoglobin levels of over 2.30 g/dL during treatment were associated with BMI > 23.2 kg/m2 (OR = 8.68, 95%CI = [1.01, 75.01]), age over 53 years (OR = 4.60 95%CI = [1.10, 19.22]), with conformational 3D irradiation (OR = 4.78, 95%CI = [1.31, 17.40]) and with total EQD2 of over 66.1 Gy (OR = 3.67, 95%CI = [1.02, 13.14]). The hemoglobin decrease rate of 0.07 g/dL/day was related to 95% isodose volume (OR = 18.00). Neutropenia is associated frequently with gastrointestinal side effects and with the bowel and rectal V45 isodoses (OR = 16.5 and OR = 18.0, respectively). Associations of total external and internal radiation dose with the time durations calculated from the initiation of treatment to the onset of hematological adverse reactions were also obtained. The maximum drop in leukocytes was observed before day 35 from the RT initiation in patients who underwent treatment with 3D conformal radiotherapy (OR = 4.44, 95%CI = [1.25, 15.82]). Neutrophil levels under 2.2 × 103/μL and thrombocyte levels under 131 × 103/μL during the follow-up period were associated with a total planned dose of 54 Gy to the pelvic region volume (OR = 6.82 and OR = 6.67, respectively). This study shows the existence of clinical and blood predictors of hematological adverse reactions in cervical cancer patients. Thus, patients who are in a precarious clinical situation, with low hematological values (but not yet abnormal), should be monitored during days 29-35 after the initiation of RT, especially if they are obese or over 53 years of age.

The impact of diabetes, hypercholesterolemia, and low-density lipoprotein (LDL) on the survival of cervical cancer patients

BackgroundCervical cancer is a prevalent malignancy and an important health concern worldwide. Recent research has highlighted the potential impact of metabolic factors, such as hyperlipidemia and diabetes, on cancer progression, increased mortality, and patient outcomes. However, insufficient data have been reported regarding their relationship with cervical cancer. This study aimed to investigate the relationships between metabolic disorders, including dyslipidemia, dysglycemia, and metabolic syndrome, and survival in patients with cervical cancer.MethodsWe retrospectively analyzed demographic information, clinical characteristics, and metabolic health indicators of patients with cervical cancer. Patients were categorized into groups based on specific metabolic conditions: high triglyceride, high low-density lipoprotein, high cholesterol, and diabetes groups. Additionally, the presence of metabolic syndrome and other metabolic comorbidities was recorded. The log-rank test was used to compare survival rates between different patient groups and identify associated risk factors. Survival curves generated via the Cox proportional hazards model were used to evaluate the associations between metabolic parameters and survival.ResultsThe Cox proportional hazards model was used to analyze data from 840 patients with cervical cancer between 28 and 72 years old who underwent surgery. The hazard ratio (HR) of mortality was 1.804 (95% CI 1.394–2.333, p < 0.001) in the high-density lipoprotein group, 0.758 (95% CI 0.558 to 1.030, p < 0.001) in the high-triglyceride group, 1.794 (95% CI 1.304–2.470, p < 0.001) in the high low-density lipoprotein group, and 0.011 (95% CI 0.005–0.025, p < 0.001) in the diabetes group. These factors were significantly associated with reduced survival in patients with cervical cancer, and these associations persisted after adjusting for age, cancer stage, treatment type, and the presence of metabolic syndrome or other comorbidities.ConclusionThis study highlights the importance of metabolic health and the significance of controlling metabolic disorders, including hyperlipidemia, diabetes, and metabolic syndrome, to improve survival outcomes in patients with cervical cancer. Future research should explore the impact of managing multiple metabolic conditions on the prognosis of these patients.

Long-term analysis of hematological parameters as predictors of recurrence patterns and treatment outcomes in cervical cancer patients undergoing definitive chemoradiotherapy

PurposeThis study sought to determine the predictive and prognostic value of clinicopathological parameters and neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and hemoglobin (Hgb) level in predicting recurrence patterns and locoregional relapse-free survival (LRFS) and distant metastasis-free survival (DMFS) in cervical cancer patients receiving definitive chemoradiotherapy (ChRT).MethodsThis study included 261 cervical cancer patients treated with ChRT. The primary endpoints were the predictors of local recurrence (LR) and distant metastasis (DM), whereas the secondary endpoints were LRFS and DMFS. The association of survival with potential prognostic factors was analyzed using Cox regression analysis, and the predictors of LR and DM were identified using logistic regression analysis.ResultsThe median follow-up time was 10.9 years. Recurrences occurred in 132 patients (50.6%) within a median of 11.2 months after definitive ChRT. NLR and PLR values were significantly higher in patients with LR and DM than in those without, with no significant differences in Hgb levels in patients with or without LR and DM. In the multivariable logistic regression analysis, lymph node metastasis, elevated NLR, and low Hgb level were significantly correlated with LR and DM. In the multivariable analysis, large tumor size, presence of lymph node metastasis, and elevated NLR were the independent predictors for poor LRFS and DMFS, and Hgb level was an additional prognostic factor for DMFS.ConclusionHematological markers, particularly NLR and Hgb, may serve as cost-effective and readily accessible indicators for predicting recurrence and survival in cervical cancer patients, contributing to their practical use in routine assessments.

Comprehensive assessment of postoperative recurrence and survival in patients with cervical cancer

BackgroundThe prediction of postoperative recurrence and survival in cervical cancer patients has been a major clinical challenge. The combination of clinical parameters, inflammatory markers, intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI), and MRI-derived radiomics is expected to support the prediction of recurrence-free survival (RFS), disease-free survival (DFS), tumor-specific survival (CSS), and overall survival (OS) of cervical cancer patients after surgery. MethodsA retrospective analysis of 181 cervical cancer patients with continuous follow-up was completed. The parameters of IVIM-DWI and radiomics were measured, analyzed, and screened. The LASSO regularization was used to calculate the radiomics score (Rad-score). Multivariate Cox regression analysis was used to construct nomogram models for predicting postoperative RFS, DFS, CSS, and OS in cervical cancer patients, with internal and external validation. ResultsClinical stage, parametrial infiltration, internal irradiation, D-value, and Rad-score were independent prognostic factors for RFS; Squamous cell carcinoma antigen, internal irradiation, D-value, f-value and Rad-score were independent prognostic factors for DFS; Maximum tumor diameter, lymph node metastasis, platelets, D-value and Rad-score were independent prognostic factors for CSS; Lymph node metastasis, systemic inflammation response index, D-value and Rad-score were independent prognostic factors for OS. The AUCs of each model predicting RFS, DFS, CSS, and OS at 1, 3, and 5 years were 0.985, 0.929, 0.910 and 0.833, 0.818, 0.816 and 0.832, 0.863, 0.891 and 0.804, 0.812, 0.870, respectively. ConclusionsNomograms based on clinical and imaging parameters showed high clinical value in predicting postoperative RFS, DFS, CSS, and OS of cervical cancer patients and can be used as prognostic markers.

Analysis of miR-497/195 cluster identifies new therapeutic targets in cervical cancer

ObjectivemiR-497/195, located at 17p13.1, is a highly conserved miRNA cluster whose abnormal expression is a key regulator of carcinogenesis. We performed a comprehensive analysis of the miR-497/195 cluster to determine its prognostic utility and role in cervical cancer (CC) using publicly available datasets.ResultsIn silico analysis and validation revealed that this cluster is downregulated in CC. A total of 60 target genes of miR-497/195 cluster were identified as differentially expressed between normal and CC samples. ShinyGO, STRING, CytoHubba, Timer 2.0, HPA, and HCMBD were used for functional enrichment, PPIN network construction, hub gene identification, immune infiltration correlation, histopathological expression, and determination of the metastatic potential of miR-497/195 cluster and their target genes. PPIN analysis identified CCNE1, CCNE2, ANLN, RACGAP1, KIF23, CHEK1, CDC25A, E2F7, CDK1, and CEP55 as the top 10 hub genes (HGs). Furthermore, the upregulation of RECK, ATD5, and BCL2, downregulation of OSBPL3, RCAN3, and HIST1H3H effected overall survival of CC patients. We identified 6 targets (TFAP2A, CLSPN, RASEF, HIST1H3H, AKT3, and ITPR1) of miR-497/195 cluster to influence metastasis. In addition, 8 druggable genes and 38 potential drugs were also identified. Our study identified miR-497/195 cluster target genes and pathways that could be used for prognostic and therapeutic applications in CC.

DSG2 and c-MYC Interact to Regulate the Expression of ADAM17 and Promote the Development of Cervical Cancer.

To explore the effect of DSG2 on the growth of cervical cancer cells and its possible regulatory mechanism. The expression levels and survival prognosis of DSG2 and ADAM17 in cervical squamous cell carcinoma tissues and adjacent normal tissues were analyzed by bioinformatics. CCK-8 assay, colony formation assay and Transwell assay were used to detect the effects of DSG2 on the proliferative activity, colony formation ability and migration ability of SiHa and Hela cells. The effect of DSG 2 on the level of ADAM17 transcription and translation was detected by qPCR and Western blot experiments. The interaction between DSG2 and c-MYC was detected by immunocoprecipitation. c-MYC inhibitors were used in HeLa cells overexpressing DSG2 to analyze the effects of DSG2 and c-MYC on proliferation, colony formation and migration of Hela cells, as well as the regulation of ADAM17 expression. DSG2 was highly expressed in cervical squamous cell carcinoma compared with normal tissues (P<0.05), and high DSG2 expression suggested poor overall survival (P<0.05). After DSG2 knockdown, the proliferative activity, colony formation and migration ability of SiHa and Hela cells were significantly decreased (P<0.05). Compared with adjacent normal tissues, ADAM17 was highly expressed in cervical squamous cell carcinoma (P<0.05), and high ADAM17 expression suggested poor overall survival in cervical cancer patients (P<0.05). The results of immunocoprecipitation showed the interaction between DSG2 and c-MYC. Compared with DSG2 overexpression group, DSG2 overexpression combined with c-MYC inhibition group significantly decreased cell proliferation, migration and ADAM17 expression (P < 0.05). DSG2 is highly expressed in cervical cancer, and inhibition of DSG2 expression can reduce the proliferation and migration ability of cervical cancer cells, which may be related to the regulation of ADAM17 expression through c-MYC interaction.

TPP1 is associated with risk of advanced precursors and cervical cancer survival.

It is unclear how telomere-binding protein TPP1 interacts with human telomerase reverse transcriptase (hTERT) and influences cervical cancer development and progression. This study included all eligible 156 cervical cancers diagnosed during 2003-2008 and followed up through 2014, 102 cervical intraepithelial neoplasia (CIN) patients, and 16 participants with normal cervix identified at the same period. Correlation of expression of TPP1 and hTERT in these lesions was assessed using Kappa statistics. TPP1 was knocked down by siRNA in three cervical cancer cell lines. We assessed mRNA expression using quantitative real-time polymerase chain reaction and protein expression using tissue microarray-based immunohistochemical staining. We further analyzed the impact of TPP1 expression on the overall survival of cervical cancer patients by calculating the hazard ratio (HR) with 95% confidence intervals (CIs) using the multivariable-adjusted Cox regression model. Compared to the normal cervix, high TPP1expression was significantly associated with CIN 3 and cervical cancers (P<0.001 for both). Expressions of TPP1 and hTERT were highly correlated in CIN 3 (Kappa statistics = 0.50, P = 0.005), squamous cell carcinoma (Kappa statistics = 0.22, P = 0.011), and adenocarcinoma/adenosquamous carcinoma (Kappa statistics = 0.77, P = 0.001). Mechanistically, knockdown of TPP1 inhibited the expression of hTERT in both mRNA and protein levels. High expression of TPP1 (HR = 2.61, 95% CI 1.23-5.51) and co-high expression of TPP1 and hTERT (HR = 2.38, 95% CI 1.28-4.43) were independently associated with worse survival in cervical cancer patients. TPP1 and hTERT expression was correlated and high expression of TPP1 was associated with high risk of CIN 3 and cervical cancer and could predict a worse survival in cervical cancer.

Construction and validation of an innovative prognostic nomogram for overall survival in cervical cancer patients with lung metastasis: an analysis utilizing the SEER database.

To facilitate patient consultation and assist in clinical decision-making, we developed a predictive model to analyze the overall survival (OS) rate of cervical cancer patients with concurrent lung metastasis for 6 months, 1 year, or 2 years. We extracted data on patients diagnosed with cervical cancer and concurrent lung metastasis between 2010 and 2020 from the Surveillance, Epidemiology, and End Results (SEER) database. Through a random assignment process, these patients were allocated to either a training cohort or a validation cohort, maintaining a 7:3 ratio. Utilizing both univariate and multivariate Cox regression analyses, we determined the independent prognostic factors influencing OS. To enhance predictive accuracy, we developed a nomogram model incorporating these identified independent prognostic variables. Model effectiveness was subsequently assessed using various metrics, including receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). We gathered data on 1330 patients diagnosed with cervical cancer with lung metastases. An OS nomogram was developed, accounting for factors such as histological type, presence of metastases in other organs (brain, liver), surgical interventions, radiation therapy, and chemotherapy. The ROC curves, calibration plots, and DCA curves demonstrated the commendable predictive performance of the nomogram in assessing the prognosis of cervical cancer patients with lung metastases in both the training and validation cohorts. By utilizing clinical data from the SEER database, we have effectively devised a nomogram capable of predicting the 6-month, 1-year, and 2-year survival rates of cervical cancer patients with lung metastases. The nomogram boasts high accuracy, offering precise prognostic predictions. Its implementation can guide the formulation of individualized follow-up and treatment plans for enhanced patient care.

Integrated In-Silico and In Vitro analysis to Decipher the contribution of bisphenol-A in cervical cancer

Bisphenol A (BPA) is a synthetic chemical widely used as a monomer for producing polycarbonate plastics. The present investigation employed an in-silico approach to identify BPA-responsive genes and comprehend the biological functions affected using in vitro studies. A Comparative Toxicogenomics Database search identified 29 BPA-responsive genes in cervical cancer (CC). Twenty-nine genes were screened using published datasets, and thirteen of those showed differential expression between normal and CC samples. Protein-Protein Interaction Networks (PPIN) analysis identified BIRC5, CASP8, CCND1, EGFR, FGFR3, MTOR, VEGFA, DOC2B, WNT5A, and YY1 as hub genes. KM-based survival analysis identified that CCND, EGFR, VEGFA, FGFR3, DOC2B, and YY1 might affect CC patient survival. SiHa and CaSki cell proliferation, migration, and invasion were all considerably accelerated by BPA exposure. Changes in cell morphology, remodeling of the actin cytoskeleton, increased number and length of filopodia, elevated intracellular reactive oxygen species and calcium, and lipid droplet accumulation were noted upon BPA exposure. BPA treatment upregulated the expression of epithelial to mesenchymal transition pathway members and enhanced the nuclear translocation of CTNNB1. We showed that the enhanced migration and nuclear translocation of CTNNB1 upon BPA exposure is a calcium-dependent process. The present study identified potential BPA-responsive genes and provided novel insights into the biological effects and mechanisms affected by BPA in CC. Our study raises concern over the use of BPA.

Common predictors of cervical cancer related mortality in Ethiopia. A systematic review and meta-analysis

BackgroundCervical cancer accounts for 7.5% of all female cancer related deaths worldwide; peaking between the ages of 35 and 65, and not only kills young women but also destroys families with young children.ObjectiveThis review was intended to measure national level magnitude and the most common predictors of cervical cancer related mortality in Ethiopia.MethodsCommon Public databases like Science Direct, Embase, the Cochrane Library, and PubMed were thoroughly searched. The STATA 14 and Rev-Manager 5.3 statistical software packages were used for analysis, as well as a standardized data abstraction tool created in Microsoft Excel. The Cochrane Q-test statistics and the I2 test were used to assess non-uniformity. The pooled magnitude and predictors of cervical cancer related mortality were estimated using fixed-effect and random-effect models, respectively.ResultThe pooled mortality among cervical cancer patients was estimated that 16.39% at 95% confidence level fall in 13.89–18.88% in Ethiopia. The most common predictors of cervical cancer related mortality were late diagnosed, radiation therapy alone, and Being anemic were identified by this review. Among cervical cancer treatment modalities effectiveness of surgery with adjuvant therapy was also approved in this meta-analysis.Conclusion and recommendationIn this study high cervical cancer-related mortality was reported as compared to national strategies to alleviate cervical cancer related mortality. Advanced implementation of cervical cancer screening at the national level for early diagnosis, anaemia detection, and combination anticancer therapy during initiation, as well as combination therapy, is critical to improve cervical cancer patient survival and decreasing mortality rates.

DDOST is associated with tumor immunosuppressive microenvironment in cervical cancer

Evidence has revealed that DDOST plays an important role in cancer development and progression. However, there are no reports on functions of DDOST in cervical tumorigenesis. Hence, we investigated the relationship of DDOST with prognosis, mutation, promoter methylation, immune cell infiltration, and drug sensitivity using bioinformatics techniques. Our results demonstrated that DDOST was significantly upregulated in a variety of tumor types and correlated with poor prognosis, including cervical cancer. Cox regression analysis dissected that high DDOST expression was associated with poor survival in cervical cancer patients. Immune infiltration analysis defined that DDOST was negatively correlated with CD8 T cells and NK cells. Strikingly, the sensitivity to multiple drugs was negatively correlated with the expression of DDOST. Therefore, our findings uncovered that DDOST could play an essential role in the tumor microenvironment and tumor immune regulation in cervical cancer, which indicated that DDOST could be a useful biomarker for prognosis and a potential therapeutic target for cancer treatment.

MiR-218-5p, miR-124-3p and miR-23b-3p act synergistically to modulate the expression of NACC1, proliferation, and apoptosis in C-33A and CaSki cells

BackgroundIn cervical cancer (CC), miR-218-5p, -124-3p, and −23b-3p act as tumor suppressors. These miRNAs have specific and common target genes that modulate apoptosis, proliferation, invasion, and migration; biological processes involved in cancer. MethodsmiR-218-5p, -124-3p, and −23b-3p mimics were transfected into C-33A and CaSki cells, and RT-qPCR was used to quantify the level of each miRNA and NACC1. Proliferation was assessed by BrdU and apoptosis by Annexin V/PI. In the TCGA and The Human Protein Atlas databases, the level of NACC1 mRNA and protein (putative target of the three miRNAs) was analyzed in CC and normal tissue. The relationship of NACC1 with the overall survival in CC was analyzed in GEPIA2. NACC1 mRNA and protein levels were higher in CC tissues compared with cervical tissue without injury. ResultsAn increased expression of NACC1 was associated with lower overall survival in CC patients. The levels of miR-218-5p, -124-3p, and −23b-3p were lower, and NACC1 was higher in C-33A and CaSki cells compared to HaCaT cells. The increase of miR-218-5p, -124-3p, and −23b-3p induced a significant decrease in NACC1 mRNA. The transfection of the three miRNAs together caused more drastic changes in the level of NACC1, in the proliferation, and in the apoptosis with respect to the individual transfections of each miRNA. ConclusionThe results indicate that miR-218-5p, -124-3p, and −23b-3p act synergistically to decrease NACC1 expression and proliferation while promoting apoptosis in C-33A and CaSki cells. The levels of NACC1, miR-218-5p, -124-3p, and −23b-3p may be a potential prognostic indicator in CC.

Survival rate of cervical cancer: a five year review at a Major Teaching Hospital in Ghana, West Africa.

Cervical cancer (CC) is one of the leading causes of cancer-related deaths among females in Ghana. Despite the magnitude of the public health challenge posed by CC in Ghana, survival data as well as reported incidence and mortality rates are primarily based on studies conducted in the capital city of the country. Even though age at diagnosis is known to affect the overall survival of CC patients, the role of this factor in the prognosis of CC patients in Ghana has not been sufficiently explored. The aim of this study was to determine the 5-year survival rate of Ghanaian woman treated for CC at a large tertiary healthcare facility in Ghana. This research was a single-institution-based quantitative retrospective cohort study conducted among patients with histopathologically confirmed CC. Clinical and socio-demographic data were retrieved from patients' medical records. Data analysis was done using the Statistical Package for the Social Sciences software version 23. Kaplan Meier curves were used to present the survival rates and median survival time. The peak age at diagnosis was between 45 and 80 years with the modal age group of patients between 75 and 80 years. The mean age at diagnosis was 63.3 ± 15.7 years ranging from 27 to 104 years. The overall survival rates at 1, 3 and 5 years were 76.5%, 51.5% and 32.4%, respectively. The median survival time was 65.8 months. Age < 50 years was associated with higher survival estimates than age >50 years. The 5-year overall survival rate of CC patients reported in this study (32.4%) is relatively low compared with countries in the developed world but like previous reports at other healthcare facilities in Ghana as well as in other underdeveloped countries.

Prediction of Cervical Cancer Patients' Survival Period with Machine Learning Techniques.

The objective of this research is to apply machine learning (ML) algorithms to predict the survival of cervical cancer patients. The aim was to address the limitations of traditional statistical methods, which often fail to provide accurate answers due to the complexity of the problem. This research employed visualization techniques for initial data understanding. Subsequently, ML algorithms were used to develop both classification and regression models for survival prediction. In the classification models, we trained the algorithms to predict the time interval between the initial diagnosis and the patient's death. The intervals were categorized as "<6 months," "6 months to 3 years," "3 years to 5 years," and ">5 years." The regression model aimed to predict survival time (in months). We used attribute weights to gain insights into the model, highlighting features with a significant impact on predictions and offering valuable insights into the model's behavior and decision-making process. The gradient boosting trees algorithm achieved an 81.55% accuracy in the classification model, while the random forest algorithm excelled in the regression model, with a root mean square error of 22.432. Notably, radiation doses around the affected areas significantly influenced survival duration. Machine learning demonstrated the ability to provide high-accuracy predictions of survival periods in both classification and regression problems. This suggests its potential use as a decision-support tool in the process of treatment planning and resource allocation for each patient.