Status In Cervical Cancer Patients Research Articles

Identification of an inflammatory response-related gene prognostic signature and immune microenvironment for cervical cancer.

Background: Cervical cancer (CC) is the fourth most common cancer among women worldwide. As part of the brisk cross-talk between the host and the tumor, prognosis can be affected through inflammatory responses or the tumor microenvironment. However, further exploration of the inflammatory response-related genes that have prognostic value, microenvironment infiltration, and chemotherapeutic therapies in CC is needed. Methods: The clinical data and mRNA expression profiles of CC patients were downloaded from a public database for this study. In the TCGA cohort, a multigene prognostic signature was constructed by least absolute shrinkage and selection operator (LASSO) and Cox analyses. CC patients from the GEO cohort were used for validation. K‒M analysis was used to compare overall survival (OS) between the high- and low-risk groups. Univariate and multivariate Cox analyses were applied to determine the independent predictors of OS. The immune cell infiltration and immune-related functional score were calculated by single-sample gene set enrichment analysis (GSEA). Immunohistochemistry was utilized to validate the protein expression of prognostic genes in CC tissues. Results: A genetic signature model associated with the inflammatory response was built by LASSO Cox regression analysis. Patients in the high-risk group had a significantly lower OS rate. The predictive ability of the prognostic genes was evaluated by means of receiver operating characteristic (ROC) curve analysis. The risk score was confirmed to be an independent predictor of OS by univariate and multivariate Cox analyses. The immune status differed between the high-risk and low-risk groups, and the cancer-related pathways were enriched in the high-risk group according to functional analysis. The risk score was significantly related to tumor stage and immune infiltration type. The expression levels of five prognostic genes (LCK, GCH1, TNFRSF9, ITGA5, and SLC7A1) were positively related to sensitivity to antitumor drugs. Additionally, the expression of prognostic genes was significantly different between CC tissues and myoma patient cervix (non-tumorous) tissues in the separate sample cohort. Conclusion: A model consisting of 5 inflammation-related genes can be used to predict prognosis and influence immune status in CC patients. Furthermore, the inhibition or enhancement of these genes may become a novel alternative therapy.

Health related quality of life and its predictive factors on cervical cancer patients in two teaching hospitals, Addis Ababa, Ethiopia

BackgroundCervical cancer is the second most prevalent and the leading cause of cancer related deaths among Ethiopian women; and about three fourth are diagnosed at advanced stages. Cervical cancer can affect the health-related quality of life (HRQOL) in multiple ways. The main aim of this study was to describe the HRQOL of cervical cancer patients and the predictive factors using validated tools.MethodsInstitution based cross-sectional study was conducted among 264 cervical cancer patients using the validated Amharic version of European Organization for Research and Treatment of Cancer (EORTC) modules; QLQ-C30 and QLQ CX24. Descriptive statistics were used to summarize the raw data. One way ANOVA was used to determine the significance of mean differences between the dependent and independent variables. Binary and multivariable regression analysis were used to measure the association between Global Health Status and independent factors. The level of significance was set at p-value < 0.05.ResultsOn EORTC QLQ-C30 scales, the mean Global Health Status (GHS) was 42.57 ± 23.31. The least and highest affected functions were physical and social, mean (SD) = 76.39 ± 23.24 and 50.40 ± 32.19, respectively. The financial difficulty was the most affected among the symptom scales, 57.83 ± 35.34. Only physical function and financial difficulty have shown an independent association with GHS, (AOR = 0.21, 95% CI = 0.05–0.84), (AOR = 0.21 95% CI = 0.07–0.59), respectively. Illiterate, can read and write, were among the predictor factors that showed an independent association with the Global Health Status. Among the EORTC QLQ-CX24 symptom scales, the highest affected score was for sexual worry, mean (SD) = 51.81 + 32.197.ConclusionsIn an effort to improve the Global Health Status of cervical cancer patients in Ethiopia; physical function and financial difficulty should be the priority areas. The Illiterate and those who lack formal education need due attention in order to improve the health-related quality-of-life.

Significance of HIV status in cervical cancer patients receiving curative chemoradiation therapy, definitive radiation alone, or palliative radiation in Botswana.

Cervical cancer associated with human papillomavirus has the highest cancer incidence and mortality for women in Botswana because of a high HIV prevalence and limited screening. This study investigates the significance of HIV on the overall survival (OS) of patients with locally advanced cervical cancer by various treatment categories (curative chemoradiation, definitive radiation [RT] alone, or palliative RT alone). This study included patients diagnosed with cervical cancer between 2013 and 2020, prospectively enrolled in the Botswana Prospective Cancer Cohort. OS based on HIV status and completion of planned treatment regimen was estimated by the Kaplan-Meier method. Comparisons of 2-year OS by HIV status was performed by the log-rank test, univariate and multivariable Cox analyses adjusting for cancer stage, RT dose, number of chemotherapy cycles, and baseline hemoglobin levels. Of 1131 patients diagnosed with stage IB-IVB cervical cancer, 69.8% were women living with HIV (n=789). For patients receiving curative chemoradiation, HIV status was not significantly associated with OS in unadjusted (p=.987) and adjusted (p=.578) analyses. For RT only treatment and definitive (high-dose) RT alone, HIV status was significantly associated with OS in unadjusted analysis (HR=1.77, p=.002; HR=1.95, p=.014), but not in adjusted analysis (p=.227, p=.73). For patients receiving palliative (low-dose) RT, HIV status was not associated with OS in unadjusted (p=.835) or adjusted analysis (p=.359). In Botswana, a resource-limited setting, HIV status had no significant effect on 2-year OS in patients with cervical cancer with well-managed HIV receiving chemoradiation, RT alone, or palliative RT. This demonstrates that patients living with HIV receiving antiretroviral treatment can receive clinically appropriate treatment with no evidence that HIV may lead to poorer outcomes.

Hematological indicator-based machine learning models for preoperative prediction of lymph node metastasis in cervical cancer.

Lymph node metastasis (LNM) is an important prognostic factor for cervical cancer (CC) and determines the treatment strategy. Hematological indicators have been reported as being useful biomarkers for the prognosis of a variety of cancers. This study aimed to evaluate the feasibility of machine learning models characterized by preoperative hematological indicators to predict the LNM status of CC patients before surgery. The clinical data of 236 patients with pathologically confirmed CC were retrospectively analyzed at the Gynecology Oncology Department of the First Affiliated Hospital of Bengbu Medical University from November 2020 to August 2022. The least absolute shrinkage and selection operator (LASSO) was used to select 21 features from 35 hematological indicators and for the construction of 6 machine learning predictive models, including Adaptive Boosting (AdaBoost), Gaussian Naive Bayes (GNB), and Logistic Regression (LR), as well as Random Forest (RF), Support Vector Machines (SVM), and Extreme Gradient Boosting (XGBoost). Evaluation metrics of predictive models included the area under the receiver operating characteristic curve (AUC), accuracy, specificity, sensitivity, and F1-score. RF has the best overall predictive performance for ten-fold cross-validation in the training set. The specific performance indicators of RF were AUC (0.910, 95% confidence interval [CI]: 0.820-1.000), accuracy (0.831, 95% CI: 0.702-0.960), specificity (0.835, 95% CI: 0.708-0.962), sensitivity (0.831, 95% CI: 0.702-0.960), and F1-score (0.829, 95% CI: 0.696-0.962). RF had the highest AUC in the testing set (AUC = 0.854). RF based on preoperative hematological indicators that are easily available in clinical practice showed superior performance in the preoperative prediction of CC LNM. However, investigations on larger external cohorts of patients are required for further validation of our findings.

Sodium deoxyribonucleate effects on the status of cervical cancer patients after radiotherapy

Background. Apart from surgery and medications, radiation therapy is one of the main treatment methods for malignant tumors of the cervix. However, its use is associated with high incidence of urological complications. In addition, the need for long-term treatment, reduced level of patients’ quality of life promote the necessity to minimize the frequency of urological complications and justify search and study of the most adequate methods of their prevention.Aim. To evaluate the effect of radioprotector sodium deoxyribonucleate on clinical characteristics and quality of life of patients with cervical cancer after radiation treatment.Materials and methods. 80 patients with cervical cancer treated in A.I. Kryzhanovsky Krasnoyarsk Regional Clinical Oncology Dispensary. Patients received chemoand radiotherapy with the 3D conformal radiotherapy method in combination with intracavity gamma therapy sources of high dose with subsequent application of radioprotector and without it.Results. On the 3rd visit it was found that in patients with cervical cancer using a radioprotector, reduced red blood cells and flat epithelium cells content in the urine sediment, it may be due to the reparative and cytoprotective sodium deoxyribonucleate properties. In the assessment of the life quality after combined therapy completion with radioprotector, 60 % of patients’ responses to the health assessment questions of the last week differed from the comparison group. Undesirable phenomena associated with sodium deoxyribonucleate therapy not observed in cervical cancer patients during radiotherapy and subsequent observation period.Conclusion. Conformal external beam radiation therapy in combination with long-term intramuscular administration of a radioprotector has advantages compared to 3D conformal radiation therapy. This method reduces the severity of post-radiation side effects, increases time to development of hematological toxicity in the context of combination chemoradiotherapy, and reduces urothelial damage caused by chemoradiotherapy.

A 5-year survival status prognosis of nonmetastatic cervical cancer patients through machine learning algorithms.

Prediction models with high accuracy rates for nonmetastatic cervical cancer (CC) patients are limited. This study aimed to construct and compare predictive models on the basis of machine learning (ML) algorithms for predicting the 5-year survival status of CC patients through using the Surveillance, Epidemiology, and End Results public database of the National Cancer Institute. The data registered from 2004 to 2016 were extracted and randomly divided into training and validation cohorts (8:2). The least absolute shrinkage and selection operator (LASSO) regression was employed to identify significant factors. Then, four predictive models were constructed, including logistic regression (LR), random forest (RF), support vector machine (SVM), and extreme gradient boosting (XGBoost). The predictive models were evaluated and compared using Receiver-operating characteristics with areas under the curves (AUCs) and decision curve analysis (DCA), respectively. A total of 13,802 patients were involved and classified into training (N=11,041) and validation (N=2761) cohorts. By using the LASSO regression method, seven factors were identified. In the training cohort, the XGBoost model showed the best performance (AUC=0.8400) compared to the other three models (all p < 0.05 by Delong's test). In the validation cohort, the XGBoost model also demonstrated a superior prediction ability (AUC=0.8365) than LR and SVM models (both p < 0.05 by Delong's test), although the difference was not statistically significant between the XGBoost and the RF models (p=0.4251 by Delong's test). Based on the DCA results, the XGBoost model was also superior, and feature importance analysis indicated that the tumor stage was the most important variable among the seven factors. The XGBoost model proved to be an effective algorithm with better prediction abilities. This model is proposed to support better decision-making for nonmetastatic CC patients in the future.

Assessment of alterations in histone modification function and guidance for death risk prediction in cervical cancer patients.

Background: Cervical cancer is the second most lethal malignancy among women, and histone modification plays a fundamental role in most biological processes, but the prognostic value of histone modification in cervical cancer has not been evaluated. Methods: A total of 594 cervical cancer patients from TCGA-CESC, GSE44001, and GSE52903 cohorts were enrolled in the current study, along with the corresponding clinicopathological features. Patients with a follow-up time less than one month were removed. A total of 122 histone modification-associated signaling pathways were obtained from the MSigDB. The activation scores of these pathways were evaluated using the “GSVA” package, differentially expressed genes were identified by the “limma” package, and pathway enrichment was conducted using the “clusterProfiler 4.0” package. The subsequent least absolute shrinkage and selection operator (LASSO) regression analysis was performed using the “glmnet” package, and a prognostic nomogram was established using the “regplot” package. For the prediction of potential therapeutic drugs, we used the data from GDSC2016 and visualized them via “MOVICS”. Results: Nine of 23 histone modification-associated prognostic genes were identified to construct the prognostic signature by LASSO analysis, named the histone modification-associated gene (HMAG) signature. Cervical patients with HMAG-H in TCGA-CESC cohort showed a 2.68-fold change of death risk, with the 95% CI from 1.533 to 4.671 (p < 0.001), as well as the increased death risk of HMAG-H in the GSE44001 cohort (HR: 2.83, 95% CI: 1.370–5.849, p = 0.005) and GSE44001 cohort (HR: 4.59, 95% CI: 1.658–12.697, p = 0.003). We observed the preferable AUC values of the HMAG signature in TCGA-CESC cohort (1-year: 0.719, 3-year: 0.741, and 5-year: 0.731) and GSE44001 cohort (1-year: 0.850, 3-year: 0.781, and 5-year: 0.755). The C-index of the nomogram showed a prognostic value as high as 0.890, while the C-index for age was only 0.562, and that for grade was only 0.542. Patients with high HMAG scores were more suitable for the treatment of CHIR-99021, embelin, FTI-277, JNK-9L, JQ12, midostaurin, PF-562271, pyrimethamine, and thapsigargin, and patients with low HMAG scores were more suitable for the treatment of BMS-536924, CP466722, crizotinib, PHA-665752, rapamycin, and TAE684. Conclusion: We comprehensively evaluated the histone modification status in cervical cancer patients and revealed histone modification-associated prognostic genes to construct the HMAG signature, aiming to provide a new insight into prognosis prediction and precise clinical treatment.

Comprehensive Expression Profiling and Molecular Basis of CDC28 Protein Kinase Regulatory Subunit 2 in Cervical Cancer.

More and more evidence suggests the oncogenic function of overexpressed CDC28 protein kinase regulatory subunit 2 (CKS2) in various human cancers. However, CKS2 has rarely been studied in cervical cancer. Herein, taking advantage of massive genetics data from multicenter RNA-seq and microarrays, we were the first group to perform tissue microarrays for CKS2 in cervical cancer. We were also the first to evaluate the clinical significance of CKS2 with large samples (980 cervical cancer cases and 422 noncancer cases). We further excavated the mechanism of the tumor-promoting activities of CKS2 in cervical cancer through analysis of genetic mutation profiles, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) significant enrichment of genes coexpressed with CKS2. According to the results, expression data from multilevels unanimously supported the overexpression of CKS2 in cervical cancer. Patients with cervical cancer in stage II from inhouse microarrays had significantly higher expression of CKS2, and CKS2 overexpression had an adverse impact on the disease-free survival status of cervical cancer patients in GSE44001. Both mutation types of mRNA high and mRNA low appeared in cervical cancer cases from the TCGA Firehose project. Gene coexpressed with CKS2 participated in pathways including the cell cycle, estrogen signaling pathway, and DNA replication. In summary, upregulated CKS2 is closely associated with the malignant clinical development of cervical cancer and might serve as a valuable therapeutic target in cervical cancer.

Evaluation of Survival Rate and Associated Factors in Patients with Cervical Cancer: A Retrospective Cohort Study.

Cervical cancer, the most common gynecological cancer, is a matter of concern, especially in developing countries. The present study investigates survival rates, associated factors, and post-treatment follow-up status in cervical cancer patients. A retrospective cohort study. This study was conducted on 187 patients referred to an academic referral cancer center in Iran from 2014-2020. Overall survival (OS) and event-free survival (EFS) were evaluated using Kaplan Meyer analysis. The event was defined as recurrence, metastasis, or death. The patients came for post-treatment visits for a median of 36 months (interquartile range [IQR]: 18-51). The median OS and EFS were 24 and 18 months, respectively. The 1- and 3- year OS rates were 90% and 72%, respectively. The 1- and 3- year EFS rates were 76% and 61%, respectively. Stage ≥ III (hazard ratio [HR]: 3.1, 95% confidence interval [CI]: 1.5, 6.5, P &lt; 0.001) and tumor size &gt; 4 cm (HR: 2.5, 95% CI: 1.2, 4.9, P = 0.006) predicted lower OS. The most common histopathology was squamous cell carcinoma (SCC) (71.1%) with non-significant higher 3- year OS (HR: 0.62, 95% CI: 0.33, 1.16, P = 0.13). No significant difference in OS was found between adjuvant and definitive radiotherapy in both early and advance-staged patients (Log-rank = 0.7 P = 0.4, log-rank = 1.6, P = 0.2, respectively). As evidenced by the obtained results, the survival of patients was lower compared to that in developed countries. Higher stage and tumor size led to shorter survival. The histopathology and type of treatment in comparable stages did not have any significant impact on survival.

Construction of a hypoxia-immune-related prognostic model and targeted therapeutic strategies for cervical cancer.

Emerging evidence indicates that hypoxia and immunity play important roles in tumorigenesis and development. However, the hypoxia-immune-related prognostic risk model has not been established in cervical cancer (CC). We aimed to construct a hypoxia-immune-related prognostic risk model, which has potential application in predicting the prognosis of CC patients and the response to targeted therapy. The RNA-seq data and corresponding clinical information were retrieved from The Cancer Genome Atlas (TCGA) database. The hypoxia status and immune status of CC patients were evaluated using the Consensus Clustering method and single-sample gene set enrichment analysis (ssGSEA), respectively. The univariate Cox regression, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression were applied to establish the prognostic risk model of CC. The chemotherapy response for six chemotherapeutic agents of each CC patient was calculated according to the Genomics of Drug Sensitivity in Cancer (GDSC). And the Connectivity Map (CMap) database was performed to screen candidate small-molecule drugs. In this study, we identified seven gene signatures (P4HA2, MSMO1, EGLN1, ZNF316, IKZF3, ISCU and MYO1B) with prognostic values. And the survival time of patients with low risk was significantly longer than those with high risk. Meanwhile, CC patients in the high-risk group yielded higher sensitivity to five chemotherapeutic agents. And we listed 10 candidate small-molecule drugs that exhibited a high correlation with the prognosis of CC. Thus, the prognostic model can accurately predict the prognosis of patients with CC and may be helpful for the development of new hypoxia-immune prognostic markers and therapeutic strategies for CC.

Predicting 3D Structure, Cross Talks, and Prognostic Significance of KLF9 in Cervical Cancer.

Our study aimed to identify the new blood-based biomarkers for the diagnosis and prognosis of cervical cancer. Moreover, the three-dimensional (3D) structure of Kruppel-like factor 9 (KLF9) was also determined in order to better understand its function, and a signaling pathway was constructed to identity its upstream and downstream targets. In the current study, the co-expressions of tumor protein D52 (TPD52), KLF9, microRNA 223 (miR-223), and protein kinase C epsilon (PKCϵ) were evaluated in cervical cancer patients and a possible relation with disease outcome was revealed. The expressions of TPD52, KLF9, miR-223, and PKCϵ were studied in the blood of 100 cervical cancer patients and 100 healthy controls using real-time PCR. The 3D structure of KLF9 was determined through homology modeling via the SWISS-MODEL and assessed using the Ramachandran plot. The predicted 3D structure of KLF9 had a similarity index of 62% with its template (KLF4) with no bad bonds in it. In order to construct a genetic pathway, depicting the crosstalk between understudied genes, STRING analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG), and DAVID software were used. The constructed genetic pathway showed that all the understudied genes are linked to each other and involved in the PI3K/Akt signaling pathway. There was a 23-fold increase in TPD52 expression, a 2-fold increase in miR-223 expression, a 0.14-fold decrease in KLF9 expression, and a 0.05-fold decrease of PKCϵ expression in cervical cancer. In the present study, we observed an association of the expressions of TPD52, KLF9, miR-223, and PKCϵ with tumor stage, metastasis, and treatment status of cervical cancer patients. Elevated expressions of TPD52 and miR-223 and reduced expressions of KLF9 and PKCϵ in peripheral blood of cervical cancer patients may serve as predictors of disease diagnosis and prognosis. Nevertheless, further in vitro and tissue-level studies are required to strengthen their role as potential diagnostic and prognostic biomarkers.

An immune-associated ten-long noncoding RNA signature for predicting overall survival in cervical cancer.

BackgroundSeveral immune-associated long non-coding RNA (lncRNA) signatures have been reported as prognostic models in different types of cancers; however, the immune-associated lncRNA signature for predicting overall survival (OS) in cervical cancer is unknown.MethodsThe lncRNA expression profiles and clinical data of cervical cancer were acquired from The Cancer Genome Atlas (TCGA) dataset. Immune-associated genes were extracted from the Molecular Signatures Database (MSigDB), and the immune-associated lncRNAs were extracted for Cox regression analysis. Principal component analysis (PCA) was used to distinguish the high and low risk status of cervical cancer patients. Gene Set Enrichment Analysis (GSEA) was used for functional analyses.ResultsCox regression analyses and the least absolute shrinkage and selection operator (LASSO) Cox regression model were used to construct an immune-associated ten-lncRNA signature (containing AL021807.1, AL109976.1, LINC02446, MIR4458HG, AC004540.2, AC009065.8, AC083809.1, AC055822.1, AP000904.1, and FBXL19-AS1) for predicting OS in cervical cancer. The signature segregated the cervical cancer patients into 2 groups (high-risk group and low-risk group). The Kaplan-Meier survival curves of AL021807.1, AL109976.1, LINC02446, and MIR4458HG were statistically significant (P<0.05) and the others (including AC004540.2, AC009065.8, AC083809.1, AC055822.1, AP000904.1, and FBXL19-AS1) were not statistically significant (P>0.05). The Kaplan-Meier survival curves of the signature were statistically significant (P=1.134e-10), and the 5-year survival rate was 0.444 in the high-risk group [95% confidence interval (CI): 0.334 to 0.590] and 0.884 in the low-risk group (95% CI: 0.807 to 0.969). The area under curve (AUC) of the receiver operating characteristic (ROC) curve of the signature was 0.833. The concordance index (C-index) of the signature was 0.788 (95% CI: 0.730 to 0.846, P=1.884778e-22). The PCA successfully distinguished the high-risk group and low-risk group based on the signature. The GSEA showed that the signature-related protein coding genes (PCGs) may participate in immunologic biological processes and pathways.ConclusionsThis study revealed that the immune-associated ten-lncRNA signature is an independent factor for cervical cancer prognosis prediction, providing a bright future for immunotherapy of cervical cancer patients.

Predicting Tumor Budding Status in Cervical Cancer Using MRI Radiomics: Linking Imaging Biomarkers to Histologic Characteristics.

Simple SummaryTumor budding is a histopathologic characteristic which has led to a growing interest in the prognosis prediction of cancers of various sites. We aimed to evaluate whether imaging biomarkers could predict tumor budding status. Preoperative MRI radiomic features were used as imaging biomarkers. Four machine learning classifiers were applied to build prediction models using a training dataset. Internal validation was performed to validate the built models. As a result, radiomics-based models predicted tumor budding status with a mean area under the receiver operating characteristic value of 0.816 and a mean accuracy of 0.779 in the independent test dataset. Final selected features were mostly from filtered images, implying the importance of filtering methods in radiomics. Preoperative prediction of tumor budding status may help personalize treatment in cervical cancer patients.Background: Our previous study demonstrated that tumor budding (TB) status was associated with inferior overall survival in cervical cancer. The purpose of this study is to evaluate whether radiomic features can predict TB status in cervical cancer patients. Methods: Seventy-four patients with cervical cancer who underwent preoperative MRI and radical hysterectomy from 2011 to 2015 at our institution were enrolled. The patients were randomly allocated to the training dataset (n = 48) and test dataset (n = 26). Tumors were segmented on axial gadolinium-enhanced T1- and T2-weighted images. A total of 2074 radiomic features were extracted. Four machine learning classifiers, including logistic regression (LR), random forest (RF), support vector machine (SVM), and neural network (NN), were used. The trained models were validated on the test dataset. Results: Twenty radiomic features were selected; all were features from filtered-images and 85% were texture-related features. The area under the curve values and accuracy of the models by LR, RF, SVM and NN were 0.742 and 0.769, 0.782 and 0.731, 0.849 and 0.885, and 0.891 and 0.731, respectively, in the test dataset. Conclusion: MRI-based radiomic features could predict TB status in patients with cervical cancer.

Total Antioxidant Capacity and Lipid Peroxidation Status in Cervical Cancer Patients Compared with Women Without Cervical Cancer in Bangladesh

PurposeOver the past several decades, research has suggested reactive oxygen species act as cofactors for cervical cancer development. The aim of this study is to evaluate the antioxidant and lipid peroxidation status in cervical cancer patients in Bangladesh.MethodsFrom December 2017 to 2018, a cross-sectional observational study was conducted on 50 cervical cancer patients and 50 controls. Plasma levels of lipid peroxidation and total antioxidant capacity were measured. The Student’s t test was used for statistical analysis. P values less than 0.05 were taken as a level of significance.ResultsThere was a significant reduction in total antioxidant levels in patients with cervical cancer, 972.77 ± 244.22 SD µmol equivalent to ascorbic acid/L, compared to normal controls, 1720.13 ± 150.81 SD µmol equivalent to ascorbic acid/L (P < 0.001). Levels of lipid peroxidation were found to be significantly higher in cervical cancer, 7.49 ± 2.13 SD µmol/L, than in women without cervical cancer, 3.28 ± 0.58 SD µmol/L (P < 0.001). The cervical cancer patients had significantly higher levels of oxidative stress index (0.83 ± 0.31) in comparison to controls (0.19 ± 0.04) (P < 0.001).ConclusionThere was an increased oxidative stress index due to imbalance between lipid peroxidation generation and total antioxidant capacity in cervical cancer patients. Further studies are needed to explore the role of oxidative stress as a cofactor for cervical carcinogenesis.

Employment status of cervical cancer patients and characteristics of workers

Employment status of cervical cancer patients and characteristics of workers

A Prognostic Model Based on Immune-Related Long Non-Coding RNAs for Patients With Cervical Cancer.

Objectives: The study is performed to analyze the relationship between immune-related long non-coding RNAs (lncRNAs) and the prognosis of cervical cancer patients. We constructed a prognostic model and explored the immune characteristics of different risk groups.Methods: We downloaded the gene expression profiles and clinical data of 227 patients from The Cancer Genome Atlas database and extracted immune-related lncRNAs. Cox regression analysis was used to pick out the predictive lncRNAs. The risk score of each patient was calculated based on the expression level of lncRNAs and regression coefficient (β), and a prognostic model was constructed. The overall survival (OS) of different risk groups was analyzed and compared by the Kaplan–Meier method. To analyze the distribution of immune-related genes in each group, principal component analysis and Gene set enrichment analysis were carried out. Estimation of STromal and Immune cells in MAlignant Tumors using Expression data was performed to explore the immune microenvironment.Results: Patients were divided into training set and validation set. Five immune-related lncRNAs (H1FX-AS1, AL441992.1, USP30-AS1, AP001527.2, and AL031123.2) were selected for the construction of the prognostic model. Patients in the training set were divided into high-risk group with shorter OS and low-risk group with longer OS (p = 0.004); meanwhile, similar result were found in validation set (p = 0.013), combination set (p < 0.001) and patients with different tumor stages. This model was further confirmed in 56 cervical cancer tissues by Q-PCR. The distribution of immune-related genes was significantly different in each group. In addition, the immune score and the programmed death-ligand 1 expression of the low-risk group was higher.Conclusions: The prognostic model based on immune-related lncRNAs could predict the prognosis and immune status of cervical cancer patients which is conducive to clinical prognosis judgment and individual treatment.

Serum vitamin A, E and C status in cervical cancer patients undergoing Concurrent Chemo-Radiotherapy, an institutional study

Vitamin A, E, and C are powerful non enzymatic antioxidants responsible for capturing free radicals, and thus, they prevent oxidative chain reactions. Persistent oxidative stress may cause resistance to apoptosis, which promotes cell proliferation and leads to the tumor and its angiogenesis. Serum level of Vitamin A, E, and C were estimated in carcinoma cervix patients at different phases of treatment and compared it with healthy controls. Ninety-seven histopathologically diagnosed Cervical Carcinoma patients, and thirty age-matched healthy controls were included in this study. Blood samples were taken once from the controls. From each patient undergoing Radiotherapy, four samples were collected i.e., before, during, immediately after and at three months follow-up of treatment. The serum was separated and stored at −20 °C until examination. Statistical analysis was done with the commercial SPSS 21.0 package for Windows (SPSS, IBM Bangalore). P-value < 0.05 was considered statistically significant. Vitamin A, E, and C levels were lower in carcinoma cervix patients of all FIGO (International Federation of Gynecology and Obstetrics) stages compared to controls. Patient serum levels of vitamins decreased again during Concurrent Chemo-Radiotherapy and immediately after the therapy. There is an elevation shown by these vitamins after three months of follow up. The results indicate that the lower serum vitamin A, E, and C levels before treatment could be a cause or an effect of cancer. Further decrease in vitamin levels during and immediately after therapy shows the high oxidative stress during the treatment period, which is beneficial for the patient. These altered vitamin levels were normalized during the time of follow-up.

Deterioration of nutritional status of patients with locally advanced cervical cancer during treatment with concomitant chemoradiotherapy.

In Mexico, 80% women with cervical cancer are diagnosed at locally advanced stages and are treated with concomitant chemoradiotherapy. The treatment modality and catabolic state confer a nutritional risk. The present study aimed to thoroughly evaluate the nutritional status and change in body composition of locally advanced cervical cancer (LACC) patients throughout treatment. An observational prospective study, carried out at the Mexican National Cancer Institute, included 55 LACC patients. Nutritional status was evaluated before, during and after treatment, using anthropometric, dietary and biochemical measurements. Body composition was analysed using computed tomography images obtained at the time of diagnosis and approximately 4months after treatment completion. Clinical outcomes were associated with changes in body composition. At the time of diagnosis, no patients were clinically malnourished, although 33.3% presented sarcopenia and most were overweight; by the end of treatment, 69% became clinically malnourished and 58% were sarcopenic. Average weight loss was 7.4kg (P=0.001). Adequacy of energy intake was reduced to 54%, obtained predominantly from carbohydrates. By the week 9, 62.8% patients became anemic and 34.5% had low albumin levels. Body composition analysis revealed that patients lost both, muscle and adipose tissues, although 27% patients were muscle depleted by the end of treatment. Patients who lost ≥10% skeletal muscle presented a higher tumour recurrence (hazard ratio=2.957, P=0.006) and a tendency towards diminished overall survival (hazard ratio=2.572, not significant). The nutritional status of cervical cancer patients deteriorates during treatment with concomitant chemoradiotherapy and, most importantly, muscle loss impacts the clinical outcome of patients.

Identification of CD28 and PTEN as novel prognostic markers for cervical cancer.

Cervical cancer (CC) is the most common malignant tumor with poor clinical outcome among women. Identification of novel biomarkers could be beneficial for the clinical diagnosis and treatment of CC. This study aimed to identify prognostic biomarkers for the prediction of prognostic status of CC patients, and explore the effect of the corresponding methylated genes in the occurrence and development of CC. The methylation microarray data of CC was extracted from The Cancer Genome Atlas (TCGA) dataset. The methylation genes associated with the prognostic status were identified based on the information of the relapse-free survival (RFS) of the CC patients. The prognostic gene pairs were further identified. Then, the prognostic signature was identified by the forward search algorithm based on the C-index method. The results were validated by independent dataset. Finally, the functional analysis was performed on the methylation genes. A total of 276 methylation genes and 2508 gene pairs associated with the prognostic status of the CC were identified. A signature composed of eight methylation gene pairs was obtained to predict the prognostic status of cervical patients. A series of genes that played an important role in the occurrence and development of CC were obtained by the functional enrichment analysis. To summary, a prognostic signature consisting of eight methylation gene pairs was obtained. Of note, the CD28 and PTEN gene pair were found to play important roles in the occurrence and development of CC.

The interaction between antioxidant status and cervical cancer: a case control study.

To compare the antioxidant status of cervical cancer patients with healthy controls and to assess the antioxidant levels before and after radiotherapy or radiochemotherapy. Antioxidant levels (glutathione, glutathione peroxidase, superoxide dismutase, and malondialdehyde) were measured in 35 patients with cervical cancer and 35 age-matched healthy controls. Blood samples were collected twice (before and after treatment) from cervical cancer patients and once from healthy control subjects. In the patient group, pre-radiotherapy glutathione and glutathione peroxidase levels were significantly lower (P <0.01 and P <0.0001, respectively) than the control group. Pre-radiotherapy levels of superoxide dismutase were significantly higher in cancer patients (P <0.01). In general, no difference was observed between pre- and post-radiotherapy antioxidant levels in cancer patients. However, when post-radiotherapy glutathione levels were analyzed, patients who did not respond to treatment had significantly higher levels than those who did respond (P <0.01). Levels of antioxidants significantly differed between the patients with cervical cancer and the controls, and no change in antioxidant levels was observed after treatment. Moreover, further studies evaluating the predictive value of glutathione levels on treatment response are warranted.