Prognosis Of Cervical Cancer Patients Research Articles

The predictive value of miR-29b-2-5p on the prognosis of cervical cancer and its inhibitory effect on cervical cancer progression.

The poor prognosis of cervical cancer patients leads to an annual increase in mortality, while microRNAs are involved in various cancers, including cervical cancer. This study aimed to investigate the clinical value and possible effect of miR-29b-2-5p on the progression of cervical cancer. The expression level of miR-29b-2-5p in cervical cancer tissues and cells was analyzed by polymerase chain reaction. The Kaplan-Meier curve was used to evaluate the role of miR-29b-2-5p in cervical cancer prognosis. The independent prognostic factors of cervical cancer were explored by the multivariate Cox regression analysis. The effect of miR-29b-2-5p on the proliferation, migration, and invasion of cervical cancer cells was determined by in vitro cell experiments. A significantly downregulated miR-29b-2-5p expression was observed in cervical cancer tumor tissues and cervical cancer cells compared with the adjacent tumor tissues (tissues of the negative surgical margin) and H8 cells, respectively. Higher miR-29b-2-5p expression correlated with a better 5-year progression-free survival of cervical cancer. MiR-29b-2-5p was also associated with the indicators (tumor size, tumor differentiation, FIGO (International Federation of Gynecology and Obstetrics) stage, and invasion depth) of the progression of cervical cancer tumors. And miR-29b-2-5p, along with tumor size, tumor differentiation, FIGO stage, histology type, and invasion depth, were independent prognostic factors for poor cervical cancer prognosis. MiR-29b-2-5p showed a suppressive effect on the proliferation, migration, and invasion of cervical cancer cells. MiR-29b-2-5p was downregulated in cervical cancer tumor tissues and could serve as an independent prognostic factor for cervical cancer. The overexpressed miR-29b-2-5p could be considered a tumor suppressor to inhibit the progression of cervical cancer.

Clinical and prognostic significance of Hec1 expression in patients with Cervical Cancer.

Hec1 is a component of the Ndc80 kinetochore complex and is frequently upregulated in various cancers. However, the clinical significance of Hec1 in cervical cancer remains largely unknown. This study aimed to investigate the expression patterns of Hec1 in cervical cancer and its relationship with the clinicopathological characteristics of patients diagnosed with the disease. Immunohistochemistry was used to assess the expression of Hec1 in 136 cervical cancer tissue samples and 82 normal cervical tissue samples. The relationship between Hec1 protein expression and the clinicopathological characteristics of cervical cancer patients was analyzed using the Chi-square test. Additionally, the association between Hec1 protein expression and patient survival was examined using Kaplan-Meier survival curves. Independent risk factors affecting the prognosis of cervical cancer patients were analyzed using the Cox proportional hazards regression model. The positive expression rate of Hec1 protein in cervical cancer tissues was 83.82%, significantly higher than the 7.31% in normal cervical tissues. Compared to patients with negative Hec1 expression, those with positive expression exhibited significantly higher FIGO staging, increased lymph node metastasis, greater depth of tumor stromal infiltration, and larger tumor diameter. Multivariable analysis using the Cox proportional hazards regression model indicated that Hec1 positive expression was an independent risk factor for both overall survival (HR = 2.79, 95% CI: 1.65-4.05, p = 0.012) and progression-free survival (HR = 1.81, 95% CI: 1.22-3.18, p = 0.002) in cervical cancer patients. Kaplan-Meier survival curve analysis showed that patients with positive Hec1 expression experienced a lower overall survival (HR: 2.72, 95% CI: 1.15-4.52, p = 0.004) and progression-free survival (HR: 3.12, 95% CI: 1.62-5.03, p = 0.002) when compared to those with negative Hec1 expression. Hec1 is significantly upregulated in cervical cancer tissues and associated with poor prognosis in cervical cancer patients. Therefore, Hec1 could be a novel biomarker, not only for the diagnosis and treatment evaluation of cervical cancer but also as an indicator for predicting the prognosis of cervical cancer patients.

N6-methyladenosine (m6A) reader HNRNPA2B1 accelerates the cervical cancer cells aerobic glycolysis.

N6-methyladenosine (m6A) modification is, a more common epigenetic modification, mainly found in mRNA. More and more researches have shown the important functions of m6A on human cancers. This study seeks to explore the role of hnRNPA2B1 and m6A-dependent mechanism in cervical cancer. Elevated hnRNPA2B1 indicated the poor prognosis of cervical cancer patients. Enforced hnRNPA2B1 reduced the apoptosis, and accelerated the proliferation and migration of cervical cancer cells in vitro. Besides, hnRNPA2B1 promoted the aerobic glycolysis of cervical cancer cells, including the lactate secretion, glucose uptake, ATP production, extracellular acidification rate (ECAR) and oxygen consumption rate (OCR). LDHA was found as the downstream target of hnRNPA2B1 by m6A site. Moreover, hnRNPA2B1 enhanced the mRNA stability of LDHA through m6A-dependent manner. LDHA inhibitor (FX-11) could reverse the effect of hnRNPA2B1. Taken together, the data revealed that hnRNPA2B1 promoted the proliferation, migration and aerobic glycolysis of cervical cancer cells by m6A/LDHA-dependent manner. These findings might bring a new idea for cervical cancer treatment.

Preoperative scoring system for the prediction of risk of lymph node metastasis in cervical cancer

The study aimed to develop and validate a preoperative scoring system to predict the risk of lymph node metastasis (LNM) in cervical cancer (CC). A total of 426 stage IB1–IIA1 CC patients were randomly divided into two sets. A logistic regression model was used to determine independent factors that contribute to LNM. A preoperative scoring system was developed based on beta (β) coefficients. An area under the receiver operating curve (AUC) was used to test for model discrimination. Five-year overall survival (OS) rate was 91.7%. Multivariable logistic regression analysis showed that FIGO stage, tumor size, depth of invasion on MRI, and squamous cell carcinoma antigen levels were independent risk factors in the development set (all P < 0.05). The AUCs of the scoring system for the development and validation sets were 0.833 (95% CI = 0.757–0.909) and 0.767 (95% CI = 0.634–0.891), respectively. Patients who scored 0–2, 3–5, and 6–8 were classified into low-risk, medium-risk, and high-risk groups. Predicted rates were in accord with observed rates in both sets. The 5-year OS rates of the new groups were also significantly different for the entire group, development set, and validation set (all P < 0.05). LNM affects the prognosis of CC patients. The scoring system can be used to assist in evaluating the risk of LNM in CC patients preoperatively. It is easy to obtain and can provide reference for clinical treatment decision-making.

A novel strategy to enhance inhibition of Hela cervical cancer by combining Lentinus β-glucan and autophagic flux blockage

Lentinus β-D-glucan (LNT), derived from artificially cultured mushrooms of Lentinus edodes, shows an important yet incompletely understood biological functions in cancer. In this work, the chemical structure of the refined LNT comprising a β-D-(1, 6)-branched β-D-(1,3)-glucan was further clarified via 1D- and 2D-NMR with high resolution, and its drug resistance resulted from autophagy in human cervical cancer (CC) Hela cells besides its anti-cancer function were revealed in vitro and in vivo. In detail, LNT destroyed cellular homeostasis by significantly increasing the intracellular Ca2+ levels and promoted autophagic flux in vitro Hela cells, which was found to at least partially depend on the PI3K/Akt/mTOR-mediated pathway by up-regulating LC3-II levels and down-regulating the expression of p62, PI3K, p-Akt, and mTOR in Hela cells-transplanted BALB/c nude mice. In particular, LNT-induced autophagy led to a drug resistance against LNT-induced proliferation inhibition and apoptosis in Hela cells, and the co-treatment of autophagy inhibitors and LNT significantly enhanced the inhibition of Hela cells and tumor growth in vitro and in vivo. Therefore, the combination of LNT and autophagy inhibitors will be a novel therapeutic strategy to reduce the resistance and improve the prognosis of CC patients in the clinical.

HPV-ferroptosis related genes as biomarkers to predict the prognosis of cervical cancer

BackgroundFerroptosis can be used as a powerful predictor of cancer prognosis. HPV persistent infection is the main cause of cervical cancer, so it is very important to improve the prognosis of patients. Therefore, it is necessary to explore the value of HPV-ferroptosis related genes as prognostic biomarkers of cervical cancer patients.MethodsIn this study, differentially expressed HPV-ferroptosis related genes were obtained from GSE7410, HPV gene set crossed with iron death genes. Five HPV-ferroptosis related genes with prognostic features were finally identified: CYBB, VEGFA, CKB, EFNA1 and HELLS. Multifactorial Cox regression was applied to establish and validate the prognostic model, and drug susceptibility and immune infiltration analyses were also performed.ResultsThe prognostic model was validated in the training set (TCGA) and validation set (GSE44001). Kaplan–Meier curves reveal significant differences in overall survival (OS) between high-risk and low-risk groups. Receiver operating characteristic (ROC) curve reflects the stability and accuracy of the prognostic model established in this study. In terms of immune function, T cell costimulation was better in the low-risk group than in the high-risk group (P < 0.01). The therapeutic effects of cisplatin, paclitaxel, docetaxel and cyclophosphamide, commonly used chemotherapy drugs for cervical cancer, are better in the high-risk group than in the low-risk group (P < 0.001).ConclusionHPV-ferroptosis related gene prognostic model not only has good stability and accuracy in predicting the prognosis of cervical cancer patients, but also has certain guiding value for clinicians in terms of drug sensitivity and immune microenvironment.

Study on serum miR-182 as a marker for diagnosis and prognosis of cervical cancer.

Cervical cancer (CC) is a common female malignancy, with a global incidence rate second only to breast cancer. To propose a new idea for early treatment and auxiliary diagnosis of CC by exploring the diagnostic and prognostic implications of serum miR-182 in CC. We enrolled 70 CC patients, 35 cervical intraepithelial neoplasia (CIN) patients and 35 healthy controls (HCs), who visited The First Affiliated Hospital of Hainan Medical College Hospital between January 2015 and April 2016. miR-182 expression was quantified by real-time quantitative PCR and compared among the three groups. The correlation of serum miR-182 expression with patients' clinical features was evaluated. The receiver operating characteristic curve (ROC) and the Kaplan-Meier method were used to evaluate the early diagnostic value and prognostic value of serum miR-182. Cox regression analysis was performed to determine serum miR-182 expression and its important role in predicting CC patients' prognosis. Serum miR-182 expression was determined to be 0.345 ± 0.094, 0.369 ± 0.076, and 0.586 ± 0.157 in CC patients, CIN patients, and HCs, respectively (P< 0.001). Serum miR-182 expression had an obvious association with lymph node metastasis and pathological differentiation (P< 0.05). The area under the ROC curve (AUC) of serum miR-182 was 0.709 (95% CI: 0.622-0.795), the critical value was 0.456, the sensitivity was 81.4%, and the specificity was 52.9%. CC patients were grouped as either the low- (miR-182 < 0.3) or high-level group (miR-182 ⩾ 0.03) based on serum miR-182 levels, and a Cox regression model of OS was established. Serum miR-182 expression was identified as a factor independently influencing CC patients' OS (P= 0.028); the death risk of the high-level group was 3.246 times that of the low-level group. Serum miR-182 expression is not only a biomarker for early diagnosis of CC, but also one of the independent factors influencing the survival and prognosis of CC patients.

Activation of the G Protein-Coupled Bile Acid Receptor TGR5 Modulates the HCP5/miR-139-5p/DDIT4 Axis to Antagonize Cervical Cancer Progression.

A growing body of evidence indicates that the G protein-coupled bile acid receptor, TGR5, plays a critical role in multiple physiological processes ranging from metabolic disorders to cancers. However, the biological functions of TGR5 in cervical cancer (CC) have not been elucidated. Here, using TGR5 knockout mice, we found that a deficiency of TGR5 leads to greater sensitivity to the progression of cervical inflammation. Activation of TGR5 by its specific ligands significantly attenuated the malignant behavior of CC cells. In addition, we found that TGR5 can negatively modulate the expression of lncRNA HCP5 by blocking its transcription activation when mediated by p65. HCP5 was highly expressed in CC tissues, which was positively correlated with the poor prognosis of CC patients. HCP5 knockdown notably restrained CC cell proliferation, colony formation, and migration in vitro, and inhibited tumor growth in vivo. Furthermore, HCP5 can function as the molecular sponge for miR-139-5p to upregulate DNA damage-induced transcript 4 (DDIT4) in CC cells. Murine xenograft studies demonstrated that TGR5 suppressed the tumor formation of CC cells and downregulated HCP5 and DDIT4 while increasing miR-139-5p in the xenografts. Taken together, these findings, for the first time, indicate that TGR5 inhibits CC progression by regulating the HCP5/miR-139-5p/DDIT4 axis, suggesting that it may represent a novel and potent target for CC treatment.

91 Effect of cisplatin cycles on prognosis for cervical cancer patients treated with chemoradiotherapy

91 Effect of cisplatin cycles on prognosis for cervical cancer patients treated with chemoradiotherapy

Clinical changes in serum intercellular adhesion molecule 1 in cervical cancer patients receiving radiotherapy.

The levels of soluble intracellular adhesion molecule-1 (sICAM-1) increased in cervical cancer patients and those patients with recurrence. However, the pattern of change in sICAM-1 and its association with prognosis in cervical cancer patients after radiotherapy remain unknown. sICAM-1 level was detected using enzyme-linked immunosorbent assay in different patient groups. The predictive value of sICAM-1 for cervical cancer occurrence was evaluated using receiver operating characteristics analysis. The association of sICAM-1 with clinical pathology was analyzed using Fisher's exact test. Association of sICAM-1 with prognosis was evaluated by alteration of sICAM-1 level in cervical cancer patients with or without complete remission at pre-radiotherapy, post-radiotherapy, and post-follow-up. The survival rate of cervical cancer patients with low or high sICAM-1 was plotted using the Kaplan-Meier curve. sICAM-1 level significantly increased in cervical cancer patients and could predict the occurrence of cervical cancer. sICAM-1 was closely associated with tumor size, differentiation, and radiotherapy effect. Importantly, the level of sICAM-1 gradually decreased in patients with complete remission after radiotherapy, while it remained unchanged in those without complete remission. Furthermore, the cervical cancer patients with high expression of sICAM-1 had a shorter survival time. The level of sICAM-1 could predict the occurrence of cervical cancer and is closely related to the prognosis of cervical cancer patients after radiotherapy.

Relationships between nine neuropsychiatric disorders and cervical cancer: insights from genetics, causality and shared gene expression patterns

BackgroundNeuropsychiatric disorders and cervical cancer exert substantial influences on women’s health. Furthermore, neuropsychiatric disorders frequently manifest as common symptoms in cancer patients, potentially increasing the risk of malignant neoplasms. This study aimed to identify neuropsychiatric disorders that are genetically and causally related to cervical cancer and to investigate the molecular mechanisms underlying these associations.MethodsGWAS data related to nine neuropsychiatric disorders, namely, schizophrenia, bipolar disorder, autism spectrum disorder, Parkinson’s disease, anxiety, Alzheimer’s disease, mood disorders, depression, and alcohol dependence, were obtained to calculate heritability (h2) and genetic correlation (rg) with cervical cancer using linkage disequilibrium score regression (LDSC). Mendelian randomization (MR) analysis of the two cohorts was employed to assess the causal effects. Shared gene expression pattern analysis was subsequently conducted to investigate the molecular mechanism underlying these significant associations.ResultsAnxiety, mood disorders, depression, and alcohol dependence were genetically correlated with cervical cancer (all adjusted P < 0.05). Only depression was causally related to cervical cancer in both the discovery (ORIVW: 1.41, PIVW = 0.02) and replication cohorts (ORIVW: 1.80, PIVW = 0.03) in the MR analysis. Gene expression pattern analysis revealed that 270 genes related to depression and cervical cancer, including tumour necrosis factor (TNF), were significantly upregulated in cervical cancer patients, while vascular endothelial growth factor A (VEGFA), transcription factor AP-1 (JUN), and insulin-like growth factor I (IGF-I) were associated with prognosis in cervical cancer patients (all P < 0.05). These overlapping genes implicated the involvement of multiple biological mechanisms, such as neuron death, the PI3K-Akt signalling pathway, and human papillomavirus infection.ConclusionsGenetic, causal and molecular evidence indicates that depression increases the risk of cervical cancer. The TNF, VEGFA, JUN, and IGF-1 genes and the neuron death, PI3K-Akt, and human papillomavirus infection signalling pathways may possibly explain this association.

Endothelial cell specific molecule 1 promotes epithelial-mesenchymal transition of cervical cancer via the E-box binding homeobox 1.

To investigate the mechanism of endothelial cell specific molecule 1 (ESM1) promoting cervical cancer cell proliferation and EMT characteristics through zinc finger E-box binding homeobox 1 (ZEB1)/EMT pathway. The correlation between ESM1 expression and prognosis of cervical cancer patients was analyzed by bioinformatics. SiHa, HeLa cell lines and corresponding control cell lines with stable ESM1 expression were obtained. Cell proliferation ability was detected by CCK-8 assay. The invasion and migration ability of Hela and SiHa cells were detected by Transwell assay and scratch closure assay. Expressions of EMT-related markers E-cadherin and Vimentin were detected by real-time PCR. The ability of silenced ESM1 to tumor formation in vivo was detected by tumor formation in nude mice. The effects of aloe-emodin on inhibit ESM1 expression and its inhibitory effect on cervical cancer cells in vitro and in vivo were analyzed by the same method. ESM1 was highly expressed in cervical cancer, and the high expression of ESM1 was associated with poor prognosis of cervical cancer patients. CCK-8 results showed that the proliferation, invasion and migration of Hela and SiHa cells were significantly reduced after siRNA interfered with ESM1 expression. Overexpression of ESM1 promoted the proliferation and migration of cervical cancer cells. Mechanism studies have shown that the oncogenic effect of ESM1 is realized through the ZEB1/PI3K/AKT pathway. High throughput drug screening found that aloe-emodin can target ESM1. Inhibitory effect of aloe emodin on ESM1/ZEB1/EMT signaling pathway and cervical cancer cells. The silencing of ESM1 expression may inhibit the proliferation, invasion, metastasis and epithelial-mesenchymal transformation of cervical cancer cells by inhibiting ZEB1/PI3K/AKT. Aloe-emodin is a potential treatment for cervical cancer, which can play an anti-tumor role by inhibiting ESM1/ZEB1.

Vitamin D-Regulated miR-589-3p in Patients with Cervical Cancer Predicts Patient Prognosis and is Involved in Tumor Progression

The study aims to evaluate the performance of Vitamin D/calcitriol-induced miR-589-3p in predicting the prognosis of cervical cancer patients and its role in cancer cell function. To identify differentially expressed miRNAs (DEMs) related to calcitriol treatment, the GSE61829 dataset was analyzed. MiR-589-3p expression levels were verified in cervical cancer patients. The association of miR-589-3p with overall survival was investigated using Kaplan-Meier survival analyses and the multi-variate Cox proportional hazards model analysis. The effects of miR-589-3p on cervical cancer cells and calcitriol-treated cells were examined using the MTT assay and Transwell migration/invasion assay. From GSE61829 dataset, a total of eleven DEMs were identified, including miR-589-3p. MiR-589-3p was found to be decreased in cervical cancer but increased after one-year intake of Vitamin D. Low miR-589-3p after one-year intake of Vitamin D was identified as a predictive factor for low survival probability (p = 0.0059) with a significant impact on the death risk (HR: 3.04; 95%CI: 1.47-6.29; p = 0.003). MiR-589-3p overexpression inhibited the proliferation and migration/invasion of cervical cancer cells and calcitriol-treated cervical cancer cells. In conclusion, miR-589-3p can be induced by Vitamin D/calcitriol treatment and inhibit cervical cancer progression. MiR-589-3p has the potential to predict overall survival in patients with cervical cancer.

Targeted proteomics-determined multi-biomarker profiles developed classifier for prognosis and immunotherapy responses of advanced cervical cancer.

Cervical cancer (CC) poses a global health challenge, with a particularly poor prognosis in cases of recurrence, metastasis, or advanced stages. A single biomarker is inadequate to predict CC prognosis or identify CC patients likely to benefit from immunotherapy, presumably owing to tumor complexity and heterogeneity. Using advanced Olink proteomics, we analyzed 92 oncology-related proteins in plasma from CC patients receiving immunotherapy, based upon the comparison of protein expression levels of pre-therapy with those of therapy-Cycle 6 in the partial response (PR) group and progressive disease (PD) group, respectively. 55 proteins were identified to exhibit differential expression trends across pre-therapy and post-therapy in both PR and PD groups. Enriched GO terms and KEGG pathways were associated with vital oncological and immunological processes. A logistic regression model, using 5 proteins (ITGB5, TGF-α, TLR3, WIF-1, and ERBB3) with highest AUC values, demonstrated good predictive performance for prognosis of CC patients undergoing immunotherapy and showed potential across different cancer types. The effectiveness of these proteins in prognosis prediction was further validated using TCGA-CESC datasets. A negative correlation and previously unidentified roles of WIF-1 in CC immunotherapy was also first determined. Our findings reveal multi-biomarker profiles effectively predicting CC prognosis and identifying patients benefitting most from immunotherapy, especially for those with limited treatment options and traditionally poor prognosis, paving the way for personalized immunotherapeutic treatments and improved clinical strategies.

Development and assessment of an RNA editing-based risk model for the prognosis of cervical cancer patients.

RNA editing, as an epigenetic mechanism, exhibits a strong correlation with the occurrence and development of cancers. Nevertheless, few studies have been conducted to investigate the impact of RNA editing on cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC). In order to study the connection between RNA editing and CESC patients' prognoses, we obtained CESC-related information from The Cancer Genome Atlas (TCGA) database and randomly allocated the patients into the training group or testing group. An RNA editing-based risk model for CESC patients was established by Cox regression analysis and least absolute shrinkage and selection operator (LASSO). According to the median score generated by this RNA editing-based risk model, patients were categorized into subgroups with high and low risks. We further constructed the nomogram by risk scores and clinical characteristics and analyzed the impact of RNA editing levels on host gene expression levels and adenosine deaminase acting on RNA. Finally, we also compared the biological functions and pathways of differentially expressed genes (DEGs) between different subgroups by enrichment analysis. In this risk model, we screened out 6 RNA editing sites with significant prognostic value. The constructed nomogram performed well in forecasting patients' prognoses. Furthermore, the level of RNA editing at the prognostic site exhibited a strong correlation with host gene expression. In the high-risk subgroup, we observed multiple biological functions and pathways associated with immune response, cell proliferation, and tumor progression. This study establishes an RNA editing-based risk model that helps forecast patients' prognoses and offers a new understanding of the underlying mechanism of RNA editing in CESC.

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.

Immune-related LncRNAs scores predicts chemotherapeutic responses and prognosis in cervical cancer patients

BackgroundLong non-coding RNAs (LncRNAs) regulating the immune microenvironment of cancer is a hot spot. But little is known about the influence of the immune-related lncRNA (IRlncRs) on the chemotherapeutic responses and prognosis of cervical cancer (CC) patients. The purpose of the study was to identify an immune-related lncRNAs (IRlncRs)-based model for the prospective prediction of clinical outcomes in CC patients.MethodsCC patients’ relevant data was acquired from The Cancer Genome Atlas (TCGA). Correlation analysis and Cox regression analyses were applied. A risk score formula was formulated. Prognostic factors were combined into a nomogram, while sensitivity for chemotherapy drugs was analyzed using the OncoPredict algorithm.ResultsEight optimal IRlncRs(ATP2A1-AS1, LINC01943, AL158166.1, LINC00963, AC009065.8, LIPE-AS1, AC105277.1, AC098613.1.) were incorporated in the IRlncRs model. The overall survival (OS) of the high-risk group of the model was inferior to those in the low-risk group. Further analysis demonstrated this eight-IRlncRs model as a useful prognostic marker. The Nomogram had a concordance index of survival prediction of 0.763(95% CI 0.746–0.780) and more robust predictive accuracy. Furthermore, patients in the low-risk group were found to be more sensitive to chemotherapy, including Paclitaxel, Rapamycin, Epirubicin, Vincristine, Docetaxel and Vinorelbine.ConclusionsAn eight-IRlncRs-based prediction model was identified that has the potential to be an important tool to predict chemotherapeutic responses and prognosis for CC patients.

The differential expression of AFF3 in cervical cancer and its correlation with clinicopathological features and prognosis

Background Cervical cancer (CC) is the second most common malignancy in women, and identifying biomarkers of CC is crucial for prognosis prediction. Here, we investigated the expression of AF4/FMR2 Family Member 3 (AFF3) in CC and its association with clinicopathological features and prognosis. Methods Tumour and adjacent tissues, along with clinicopathological features and follow-up information, were collected from 78 patients. AFF3 expression was assessed using quantitative real-time polymerase chain reaction and Western blotting. The correlation between AFF3 expression and CC symptoms was using chi-square test. The 5-year overall survival (OS) was analysed using the Kaplan-Meier method. The Univariate analysis of prognostic risk factors was conducted using the COX proportional hazards model, followed by multivariate COX regression analysis including variables with p < 0.01. Results AFF3 expression was downregulated in CC, and its levels were correlated with lymph node metastasis (LNM) and International Federation of Gynaecology and Obstetrics (FIGO) stage. Patients with low AFF3 expression had a lower 5-year OS rate (52.78%, 19/36). Postoperative survival was reduced in patients with histological grade 3 (G3), myometrial invasion (depth ≥ 1/2), lymphovascular space invasion, LNM, and advanced FIGO stage. Low expression of AFF3 (HR: 2.848, 95% CI: 1.144–7.090) and histological grade G3 (HR: 4.393, 95% CI: 1.663–11.607) were identified as independent prognostic risk factors in CC patients. Conclusion Low expression of AFF3 and histological G3 are independent predictors of poor prognosis in CC patients, suggesting that AFF3 could serve as a potential biomarker for prognostic assessment in CC.

Abstract 3672: Development of liquid biopsy HPV (Human Papilloma Virus) cell free DNA (cfDNA) based approach for prognosis of cervical cancer

Abstract Introduction: Recent progress in the analysis of blood samples for circulating tumor cells or cell-free circulating tumor DNA (ctDNA) has shown that liquid biopsies may have potential applications in the detection and monitoring of cancer. Human papillomavirus (HPV) circulating cell-free (ccf) DNA may act as a unique marker for the prognosis of high-risk HPV-related cancers. However, detection of circulating markers for cervical cancer (CC) requires extremely sensitive techniques that can measure circulating human papillomavirus DNA. Here, we used the sensitive droplet digital PCR (dd PCR) based approach for the detection and quantification of circulating human papillomavirus DNA in plasma from patients diagnosed with cervical cancer at baseline and subsequent follow up with intention of validating its utility as a prognostic marker in CC. Method: Blood sera form 34 Patients diagnosed with cervical cancer (Stage 1-1V) at AIIMS Delhi was collected at baseline and after 3 months of the treatment. 10 healthy controls were also recruited in the study after due approval from AIIMS IEC. Plasma samples were stored at -80°C. ccf DNA was isolated from 1 ml of plasma and further processed to detect the presence of circulating high risk Human papilloma virus (HPV) i.e., HPV-16 and HPV18 cf DNA using dd PCR. Result: The median cf DNA concentration was 9.3 ng/uL (range 3-26.6) for all patients while median cf DNA concentration was 7.2 ng/uL (Range 3-57.3) for healthy controls (n=10). Furthermore, the levels of cfDNA decreases post 3 months of treatment with average concentration of 8.07 ng/uL (Range 4.6-19.3). We further processed our samples for dd PCR based screening to detect low copy no HPV cf DNA and ddPCR detection yielded a positive rate of 51% (18/35) for circulating HPV18 DNA while a positivity of 88.5% (31/35) was seen for the circulating HPV16 DNA in the sera of CC patients. By comparing HPV16 and HPV18 genotypes, we observed detection of circulating HPV 16 DNA more frequently than circulating HPV18 DNA in CC patients coming at our center. Furthermore, we found that copies of circulating viral DNA (HPV18 and HPV16) decreased post induction therapy in CC patients indicating progression ability of thid marker. Conclusion: In the current studies we provide evidence that cell free DNA concentration in CC patient can predict tumor burden and detection of low copy no of circulating HPV DNA could be a promising indicator for prognosis in cervical cancer patients and can predict recurrence of the disease. Citation Format: Gunjan Dagar, Ashna Gupta, Ravi Chauhan, Abhishek Shankar, Daya Nand Sharma, Muzafar A. Macha, Ajaz A. Bhat, Rajeev Goyal, Vaishali Suri, Mayank Singh. Development of liquid biopsy HPV (Human Papilloma Virus) cell free DNA (cfDNA) based approach for prognosis of cervical cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3672.

Incidence, prognostic factors, and a nomogram of cervical cancer with lung metastasis: A SEER-based study

AimsThe purpose of this study was to investigate the incidence, survival and prognostic factors of cervical cancer with lung metastasis at the initial diagnosis and to develop a visual nomogram to predict the prognosis of these patients. MethodsWe used the Surveillance, Epidemiology and End Results (SEER) database to screen patients diagnosed with cervical cancer from 2010 to 2015. After strict inclusion and exclusion, the chi-square test was used to evaluate the differences in the clinical characteristics of patients with cervical cancer, and then we used Kaplan–Meier method to perform survival analysis among cervical cancer patients with lung metastasis. Next, univariate and multivariate Cox proportional hazard regression models were used to estimate prognostic factors of these patients and we developed a visualized and novel nomogram to judge the prognosis. Results476 patients with lung metastasis and 12,016 patients without lung metastasis were included in this study. The incidence of lung metastasis was higher in unmarried white cervical cancer patients between the ages of 40 and 60, and grade III cervical squamous cell carcinoma patients were more likely to have lung metastasis. In addition, grade, surgery, radiotherapy, sequence of surgery and radiotherapy and chemotherapy were significantly related to the outcomes of cervical cancer patients with lung metastasis. Furthermore, our nomogram could predict the 3-year and 5-year overall survival (OS) of these patients. Finally, the AUC of 3-year OS and 5-year OS were confirmed to be 0.969 and 0.939 respectively by ROC curves, with good consistency. ConclusionsAge at diagnosis, race, marital status, and characteristics of the tumor can influence the incidence of lung metastasis in cervical cancer patients. Besides, grade, surgery, radiotherapy, sequence of surgery and radiotherapy and chemotherapy may deeply affect the prognosis of cervical cancer patients with lung metastasis. The nomogram built in this study may help clinicians to formulate individualized treatment strategies and encourage the development of more and more comprehensive and accurate predictive models.