Cervical Squamous Cell Carcinoma And Endocervical Adenocarcinoma Research Articles

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.

The cuproptosis-related gene UBE2D2 functions as an immunotherapeutic and prognostic biomarker in pan-cancer.

Cuproptosis, as a unique modality of regulated cell death, requires the involvement of ubiquitin-binding enzyme UBE2D2. However, the prognostic and immunotherapeutic values of UBE2D2 in pan-cancer remain largely unknown. Using UCSC Xena, TIMER, Clinical Proteomic Tumor Analysis Consortium (CPTAC), and Human Protein Atlas (HPA) databases, we aimed to explore the differential expression pattern of UBE2D2 across multiple cancer types and to evaluate its association with patient prognosis, clinical features, and genetic variations. The association between UBE2D2 and immunotherapy response was assessed by gene set enrichment analysis, tumor microenvironment, immune gene co-expression and drug half maximal inhibitory concentration (IC50) analysis. The mRNA and protein levels of UBE2D2 were markedly elevated in most cancer types, and UBE2D2 exhibited prognostic significance in liver hepatocellular carcinoma (LIHC), kidney chromophobe (KICH), uveal melanomas (UVM), cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), and kidney renal papillary cell carcinoma (KIRP). UBE2D2 expression was correlated with clinical features, tumor mutation burden, microsatellite instability, and anti-tumor drug resistance in several tumor types. Gene enrichment analysis showed that UBE2D2 was significantly associated with immune-related pathways. The expression level of UBE2D2 was correlated with immune cell infiltration, including CD4 + T cells、Macrophages M2、CD8 + T cells in pan-cancer. PDCD1, CD274 and CTLA4 expression levels were positively correlated with UBE2D2 level in multiple cancers. We comprehensively investigated the potential value of UBE2D2 as a prognostic and immunotherapeutic predictor for pan-cancer, providing a novel insight for cancer immunotherapy.

Development and validation of a prognostic prediction model for cervical cancer patients treated with radical radiotherapy: a study based on TCGA database.

Radiotherapy or concurrent chemoradiotherapy is the standard treatment for patients with locally advanced or inoperable cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC). However, treatment failure for CESC patients treated with radical radiotherapy still occurs due to local recurrence and distant metastasis. The previous prediction models were focused on all CESC patients, neglecting the prognostic differences under different treatment modalities. Therefore, there is a pressing demand to explore novel biomarkers for the prognosis and sensitivity of radiotherapy in CESC patients treated with radical radiotherapy. As a single biomarker has limited effect in stratifying these patients, our objective was to identify radioresponse-related mRNAs to ameliorate forecast of the prognosis for CESC patients treated with radical radiotherapy. Sample data on CESC patients treated with radical radiotherapy were obtained from The Cancer Genome Atlas (TCGA) database. We randomly separated these patients into a training and test cohorts using a 1:1 ratio. Differential expression analysis was carried out to identify radioresponse-related mRNA sets that were significantly dysregulated between complete response (CR) and radiographic progressive disease (RPD) groups, and univariate Cox regression analyses, least absolute shrinkage and selection operator (LASSO) method and multivariate Cox regression were performed to identify the radioresponse-related signature in the training cohort. we adopted survival analysis to measure the predictive value of the radioresponse-related signature both in the test and entire cohorts. Moreover, we developed a novel nomogram to predict the overall survival (OS) of CESC patients treated with radical radiotherapy. In addition, immune infiltration analysis and Gene Set Enrichment Analysis (GSEA) were conducted to preliminarily explore possible mechanisms. This study included a total of 92 CESC patients subjected to radical radiotherapy. We developed and verified a risk score model based on radioresponse-related mRNA. The radioresponse-related mRNA signature and International Federation of Gynecology and Obstetrics (FIGO) stage were served as independent prognostic factors for CESC patients treated with radical radiotherapy. Moreover, a nomogram integrating radioresponse-related mRNA signature with FIGO stage was established to perform better for predicting 1-, 3-, and 5-year survival rates. Mechanically, the low-risk group under the risk score of this model had a better survival status, and the distribution of CD4 T cells was potentially involved in the regulation of radiotherapy response in CESC, leading to a better survival outcome in the low-risk group. This study presents a new radioresponse-related mRNA signature that shows promising clinical efficacy in predicting the prognosis of CESC patients treated with radical radiotherapy.

A novel mitochondria-related core gene signature to predict the prognosis and evaluate tumour microenvironment in CESC single-cell validation.

Mitochondria and their related genes (MTRGs) are pivotal in the tumour microenvironment (TME) of cervical cancer, influencing prognosis and treatment response. This study developed a prognostic model using MTRGs to predict overall survival (OS) in cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), aiming for personalized therapy. Analysing 14 MTRGs like ISCU and NDUFA11 through techniques such as univariate Cox regression, we found that a low mitochondrial (MT) score is associated with better survival, while a high MT score predicts poorer outcomes. The TME score, particularly influenced by CD8 T cells, also correlates with prognosis, with a high score indicating favourable outcomes. The interplay between MT and TME subtypes revealed that the best prognosis is seen in patients with a low MT and high TME score. Our findings highlight the role of MTRGs as potential biomarkers and therapeutic targets in cervical cancer, offering a novel approach to improving patient outcomes through a more nuanced understanding of mitochondrial function and immune interactions within the TME. This model presents a promising avenue for enhancing the precision of prognostic assessments in CESC.

Abstract 4930: Identification of CBX7 and PCDHB18 as novel prognostic biomarkers of cervical cancer: RNA-sequencing and machine learning analysis

Abstract Background- Cervical cancer, ranking fourth in prevalence among women worldwide, is highly preventable when diagnosed early. The advent of innovative technologies including bioinformatics and machine learning, is revolutionizing the discovery and development of novel biomarkers for cancer. Our study uniquely integrates artificial neural networks with RNA-sequencing data of cervical cancer patients. This combination enhances the accuracy and reliability of biomarker predictions, providing a better understanding of the potential clinical utility of the identified biomarkers. Methods- RNA-sequencing data and clinicopathological details of 304 Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (CESC) were obtained from the GDAC database (https://gdac.broadinstitute.org/). Differentially expressed genes (DEGs) were identified (P<0.05, |log2 fold change (FC)| > 1.5, false discovery rate (FDR) < 0.05). Pathway enrichment analysis was performed and protein-protein interactions of DEGs were constructed using the STRING database. Prognostic biomarkers were identified using Kaplan-Meier and Cox proportional hazard methods adjusted for potential confounders such as age, disease stage, and comorbidities (HR<1, p<0.05). Deep learning algorithms were applied for predictive marker identification, utilizing Weight by Correlation feature selection. The model used AUC (Area Under the Curve), accuracy, MSE (Mean Squared Error), and R2 (R-squared) as evaluation metrics in a 70-30 training-test split. A combined ROC curve assessed diagnostic biomarkers, validated externally with a GEO dataset on cervical cancer patients. Results- In our study, 4153 DEGs were identified. Pathway analysis revealed that key dysregulated genes play a pivotal role in extracellular matrix organization. The survival analysis identified that six upregulated genes (CT62, SLC7A5P1, C10orf110, FDPSL2A, TNFSF15, and TTLL13) and seven downregulated genes (BAI3, CBX7, DKFZp566F0947, PCDHB18, GRAPL, PCDHB19P, and C4orf38) decreased the overall survival in patients. The machine learning model demonstrated high predictive accuracy (AUC=1, accuracy=99.02%, R2=0.99), identifying twenty genes with a positive correlation to cervical cancer risk. Notably, CBX7 emerged as a prognostic and diagnostic biomarker (AUC=0.99, sensitivity=0.93, specificity=1.00). Conclusion- Our study uncovers the prognostic significance of two novel genes in cervical cancer: CBX7, a vital regulator of tumor suppression, and PCDHB18, a member of the protocadherin beta gene cluster functioning as a cell adhesion molecule. Downregulation of these genes is associated with decreased overall survival. Further functional analyses and validation of these candidate biomarkers are crucial to fully assess their potential clinical value in cervical cancer. Citation Format: Ghazaleh Pourali, Mohsen Zeinali, Mahshid Arastonejad, Nima Khalili-Tanha, Elham Nazari, Ghazaleh Khalili-Tanha, Adetunji T. Toriola. Identification of CBX7 and PCDHB18 as novel prognostic biomarkers of cervical cancer: RNA-sequencing and machine learning analysis [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 4930.

The Prognostic and Immune Significance of BZW2 in Pan-Cancer and its Relationship with Proliferation and Apoptosis of Cervical Cancer.

Basic leucine zipper and W2 domains 2 (BZW2), a member of the basic domain leucine zipper superfamily of transcription factors, has been implicated in the development and progression of various cancers. However, the precise biological role of BZW2 in pan-cancer datasets remains to be explored. This study aimed to assess the prognostic significance of BZW2 and its immune-related signatures in various tumors. Our study investigated the expression, epigenetic modifications, and clinical prognostic relevance of BZW2 using multi-omics data in different cancer types. Additionally, the immunological characteristics, tumor stemness, drug sensitivity, and correlation of BZW2 with immunotherapy response were explored. Finally, in vitro experiments were conducted to assess the impact of BZW2 knockdown on Hela cells, a cell line derived from cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC). BZW2 exhibited elevated expression levels in various tumor tissues and significantly impacted the prognosis of different cancer types. BZW2 emerged as an independent prognostic factor in CESC. We found that copy number amplification and methylation levels of BZW2 were associated with its mRNA expression. Immunological analyses revealed that BZW2 shapes a non-inflamed immunosuppressive tumor microenvironment across multiple cancers. Furthermore, our cell experiments demonstrated that BZW2 knockdown reduced proliferation, migration, and apoptosis activities in CESC cells. BZW2 promotes cancer progression by shaping a non-inflamed immunosuppressive tumor microenvironment. Additionally, BZW2 was shown to significantly influence the proliferation, migration, and apoptosis of CESC cells.

ZNF695, A Potential Prognostic Biomarker, Correlates with Immune Infiltrates in Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma: Bioinformatic Analysis and Experimental Verification.

The role of Zinc Finger Protein 695 (ZNF695) is unclear in cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC). The objective of this study was to conduct a comprehensive analysis and experimental validation of ZNF695 in CESC. The study investigated the expression of ZNF695 in both pan-cancer and CESC, utilizing data from The Cancer Genome Atlas (TCGA) database to assess its diagnostic value. The present study investigated the association between ZNF695 expression levels and clinical characteristics, as well as prognosis, in patients with CESC. The study explored potential regulatory networks involving ZNF695, including its association with immune infiltration, immune score, stemness index based on mRNA expression (mRNAsi), and drug sensitivity in CESC. We explored the expression of ZNF695 in CESC single cells. ZNF695 expression was validated using GSE29570. ZNF695 was found to be aberrantly expressed in pan-cancer and CESC. There was a significant correlation observed between an elevated level of ZNF695 expression in patients with CESC and histological grade (p = 0.017). Furthermore, a strong association was found between high ZNF695 expression in CESC patients and poorer overall survival (OS) (HR: 1.87; 95% CI: 1.17-3.00; p = 0.009), Progression-free Survival (PFS) (HR: 1.86; 95% CI: 1.16-2.98; p = 0.010), and Disease-specific Survival (DSS) (HR: 1.98; 95% CI: 1.15-3.42; p = 0.014). The expression of ZNF695 in CESC patients (p = 0.006) was identified as an independent prognostic determinant. ZNF695 was associated with steroid hormone biosynthesis, oxidative phosphorylation, and so on. ZNF695 expression correlated with immune infiltration, immune score, and mRNAsi in CESC. ZNF695 expression significantly and negatively correlated with AICA ribonucleotide, BIX02189, QL-XI-92, STF-62247, and SNX-2112 in CESC. ZNF695 gene was upregulated in CESC tissues and cell lines. ZNF695 was significantly upregulated in the CESC cell lines. ZNF695 may be a potential prognostic biomarker and immunotherapeutic target for CESC patients.

RNA-binding proteins signature is a favorable biomarker of prognosis, immunotherapy and chemotherapy response for cervical cancer

Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) still present a huge threaten to women’s health, especially the local advanced patients. Hence, developing more effectiveness prognostic signatures is urgently needed. This study constructed and verified a robust RNA-binding proteins (RBPs) related signature through a series of bioinformatics methods and explored the biological function of hub RBP in vitro experiments. As a result, the 10 RBPs signature was successfully established and could act as an independent prognostic biomarker in CESC patients, which displayed the highest sensitivity and specificity in prognosis prediction compared with other clinicopathological parameters. The risk model also presented good performance in risk stratification among CESC patients. Besides, a nomogram was constructed based on pathological stage and the risk signature and exhibited satisfactory accuracy in prognosis prediction. Functional enrichment indicated that the risk signature mainly participated in immune-related pathways and cancer-related pathways, and the infiltration level of immune cells and immune checkpoints showed a significantly higher degree in low-risk patients compared with high-risk patients. Notably, the 10 RBPs signature act as a novel biomarker in immunotherapy and chemotherapy response. In addition, PRPF40B was selected as hub RBP and its transcription and translation levels were obviously increased in CESC tissues, as well as Hela and Siha cells. Knockdown of PRPF40B inhibits the proliferation, migration and invasion of Hela and Siha cells in vitro. In conclusion, our research provides a noticeable strategy in prognostic prediction among CESC patients, which may illuminate the prospect of CESC patients’ clinical outcome.

Unraveling the role of the circadian clock genes in cervical squamous cell carcinoma and endocervical adenocarcinoma: A prognostic indicator for prognostic, immunotherapy response, and chemotherapy sensitivity.

Background: Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) account for a significant proportion of gynecological malignancies and represent a major global health concern. Globally, CESC is ranked as the fourth most common cancer among women. Conventional treatment of this disease has a less favorable prognosis for most patients. However, the discovery of early molecular biomarkers is therefore important for the diagnosis of CESC, as well as for slowing down their progression process. Methods: To identify differentially expressed genes strongly associated with prognosis, univariate Cox proportional hazard analysis and least absolute shrinkage and selection operator (LASSO) regression analysis were used. Using multiple Cox proportional hazard regression, a multifactorial model for prognostic risk assessment was then created. Results: The expression of biological clock-related genes, which varied considerably among distinct subtypes and were associated with significantly diverse prognoses, was used to categorize CESC patients. These findings demonstrate how the nomogram developed based on the 7-CRGs signature may assist physicians in creating more precise, accurate, and successful treatment plans that can aid CESC patients at 1, 3, and 5 years. Conclusions: By using machine learning techniques, we thoroughly investigated the impact of CRGs on the prognosis of CESC patients in this study. By creating a unique nomogram, we were able to accurately predict patient prognosis. At the same time, we showed new perspectives on the development of CESC and its treatment by analyzing the associations of the prognostic model with immunity, enrichment pathways, chemotherapy sensitivity, and so on. This research provides a new direction for clinical treatment.

Angiogenesis-related lncRNAs index: A predictor for CESC prognosis, immunotherapy efficacy, and chemosensitivity.

Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) is a common gynecologic tumor and patients with advanced and recurrent disease usually have a poor clinical outcome. Angiogenesis is involved in the biological processes of tumors and can promote tumor growth and invasion. In this paper, we created a signature for predicting prognosis based on angiogenesis-related lncRNAs (ARLs). This provides a prospective direction for enhancing the efficacy of immunotherapy in CESC patients. We screened seven OS-related ARLs by univariate and multivariate regression analyses and Lasso analysis and developed a prognostic signature at the same time. Then, we performed an internal validation in the TCGA-CESC cohort to increase the precision of the study. In addition, we performed a series of analyses based on ARLs, including immune cell infiltration, immune function, immune checkpoint, tumor mutation load, and drug sensitivity analysis. Our created signature based on ARLs can effectively predict the prognosis of CESC patients. To strengthen the prediction accuracy of the signature, we built a nomogram by combining signature and clinical features.

EGLN1: A Biomarker of Poor Prognosis of Cervical Cancer and a Target of Treatment.

Objective: To conduct bioinformatics analysis on the prognostic effect, mechanism of action, and drug sensitivity of Egl-9 family hypoxia-inducible factor 1 (EGLN1) expression on cervical cancer. Methods: Bioinformatics were obtained from Gene Expression Profiling Interactive Analysis (GEPIA), Tumor Immune Estimation Resource (TIMER), and the human cancer metastasis database (HCMDB), and the effect of EGLN1 expression level on the prognosis of cervical cancer was comprehensively analyzed. The protein-protein interaction network was constructed by Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), and the possible mechanism of EGLN1 affecting the prognosis of cervical cancer was discussed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. In addition, Gene Set Cancer Analysis (GSCALite) was used to predict sensitive drugs online. Results: The higher the expression level of EGLN1, the shorter the tumor-free survival time and overall survival time of cervical cancer. The higher the stage of cervical cancer, the higher the expression level of EGLN1. The expression of EGLN1 affects the degree of immune infiltration, the variation of somatic copy number, and the level of N6-methyladenosine (m6A) modification in cervical cancer. COX regression model suggested that EGLN1 was an independent prognostic factor of cervical cancer. Conclusions: The high expression of EGLN1 in cervical cancer is an independent risk factor for the prognosis of cervical cancer, which affects the prognosis of cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) through different signal pathways. It is expected to be used to predict the sensitive anticancer drugs for the treatment of cervical cancer.

Zinc Transporters Serve as Prognostic Predictors and their Expression Correlates with Immune Cell Infiltration in Specific Cancer: A Pan-cancer Analysis.

The disruption of zinc (Zn) homeostasis has been implicated in cancer development and progression through various signaling pathways. Maintaining intracellular zinc balance is crucial in the context of cancer. Human cells rely on two families of transmembrane transporters, SLC30A/ZNT and SLC39A/ZIP, to coordinate zinc homeostasis. While some ZNTs and ZIPs have been linked to cancer progression, limited information is available regarding the expression patterns of zinc homeostasis-related genes and their potential roles in predicting prognosis and developing therapeutic strategies for specific cancers. In this study, a systematic analysis was conducted to examine the expression of all genes from the SLC30A and SLC39A families at both mRNA and protein levels across different cancers. As a result, three SLC39A genes (SLC39A1, SLC39A4, and SLC39A8) were found to be significantly dysregulated in specific cancers, including cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), liver hepatocellular carcinoma (LIHC), pancreatic adenocarcinoma (PAAD), and kidney renal papillary cell carcinoma (KIRP). Moreover, the dysregulation of these genes was tightly associated with the prognosis of patients with those cancers. Furthermore, we found that the gene SLC39A8 exhibited the lowest mutation frequency in KIRP, whereas mutations in SLC39A4 were found to significantly impact overall survival (OS), disease-free (DF), and progress-free survival (PFS) in cancer patients, particularly in those with PAAD. Additionally, immune infiltration analysis revealed that SLC39A1, SLC39A4, and SLC39A8 may function as immune regulators in cancers. This provides new insights into understanding the complex relationship between zinc homeostasis and cancer progression.

TGFA expression is associated with poor prognosis and promotes the development of cervical cancer.

Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) are the second most common cancers in women aged 20-39. While HPV screening can help with early detection of cervical cancer, many patients are already in the medium to late stages when they are identified. As a result, searching for novel biomarkers to predict CESC prognosis and propose molecular treatment targets is critical. TGFA is a polypeptide growth factor with a high affinity for the epidermal growth factor receptor. Several studies have shown that TGFA can improve cancer growth and progression, but data on its impact on the occurrence and advancement of CESC is limited. In this study, we used clinical data analysis and bioinformatics techniques to explore the relationship between TGFA and CESC. The results showed that TGFA was highly expressed in cervical cancer tissues and cells. TGFA knockdown can inhibit the proliferation, migration and invasion of cervical cancer cells. In addition, after TGFA knockout, the expression of IL family and MMP family proteins in CESC cell lines was significantly reduced. In conclusion, TGFA plays an important role in the occurrence and development of cervical cancer. Therefore, TGFA may become a new target for cervical cancer treatment.

A novel immune-related risk-scoring system associated with the prognosis and response of cervical cancer patients treated with radiation therapy.

Objective: The tumor microenvironment plays a critical role in the radiotherapy and immunotherapy response of cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC). Radioresistance is a key factor in treatment failure among patients who receive radical radiotherapy. Thus, new immune-related biomarkers associated with radiotherapy response in CESC are needed. Methods: In this study, the CIBERSORT and ESTIMATE methods were applied to determine the percentage of tumor-infiltrating cells and the number of immune components in 103 CESCs treated with radiotherapy from The Cancer Genome Atlas (TCGA) database. The main dysregulated genes were subjected to multivariate and univariate analyses. The prognostic value of this system was studied via receiver operating characteristic curve and survival analysis. For further confirmation, the biomarkers' expression levels and predictive value were validated by immunohistochemistry (IHC) and qRT-PCR. The CIBERSORT algorithm was used to calculate the compositional patterns of 22 types of immune cells in cervical cancer patients treated with radiation therapy. Results: Data for 17 radioresistant and 86 radiosensitive tumors were obtained from the The Cancer Genome Atlas database. 53 immune-related DEGs were identified. GO and KEGG analyses revealed that the DEGs were enriched in protein kinase B signaling, growth factors in cytokines, the MAPK pathway and the PI3K-Akt pathway. Then, 14 key immune-related genes built a risk scoring model were deemed prognostic in CESC with radiotherapy. The area under the curve (AUC) of the model was 0.723, and the high-risk group presented worse outcomes than the low-risk group. In addition, the high-risk group tended to have persistent tumors (p = 0.001). The high expression of WT1 and SPOUYT4 were associated with relapse, the high expression of Angiotensinogen and MIEN1 were associated with nonrelapse. Analysis of the immune microenvironment indicated that M0 macrophages, M2 macrophages, activated mast cells and resting memory CD4+ T cells were positively correlated with the risk score (p < 0.05). Conclusion: The novel immune-related risk scoring system has some advantages in predicting the prognosis and treatment response of cervical cancer patients treated with radiotherapy. Moreover, it might provide novel clues for providing targeted immune therapy to these patients.

MiR-1299 is regulated by KCNQ1OT1 and inhibits cervical cancer progression.

Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) is the most common malignancy of the female genital tract. MiR-1299 serves as a tumor suppressor, while KCNQ1OT1 acts as an oncogene in multiple malignancies. This research was designed to investigate the impacts of miR-1299 and KCNQ1OT1 on CESC progression. The downstream target of miR-1299 and the underlying regulatory mechanism of KCNQ1OT1 action on miR-1299 were explored. RT-qPCR was applied for RNA expression detection in CESC tissues and cells. RNA immunoprecipitation, RNA pulldown and luciferase reporter assays were applied to evaluate the binding between molecules in CESC cells. Cell Counting Kit-8 and colony formation assays were used for the measurement of CESC cell viability and proliferation. Western blotting was utilized to measure levels of apoptosis-related in CESC cells. MiR-1299 was downregulated in CESC tissues and presented a negative correlation with KCNQ1OT1 expression. KCNQ1OT1 was directly bound to miR-1299 to negatively modulate miR-1299 expression in CESC cells. The proliferative ability of CESC cells was suppressed by miR-1299 overexpression and was facilitated by KCNQ1OT1 overexpression. CESC cells apoptosis was promoted by miR-1299 mimics and inhibited by KCNQ1OT1 overexpression. In addition, in in vivo studies, miR-1299 overexpression rescued the effects of KCNQ1OT1 overexpression on CESC xenograft tumor growth. Finally, KCNQ1OT1 was bound to miR-1299 to upregulate PDPK1 expression in CESC cells. Collectively, miR-1299 was regulated by KCNQ1OT1 and inhibited CESC progression in vivo and in vitro, suggesting the tumor-suppressor role of miR-1299 for CESC.

Metabolism-associated molecular classification of cervical cancer

ObjectiveThis study aimed to explore metabolic abnormalities in cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) for metabolism-related genes.MethodsWe downloaded expression data for metabolism-related genes, performed differential expression analysis, and applied weighted gene co-expression network analysis (WGCNA) to identify metabolism-related functional modules. We obtained normalised miRNA expression data and identified master methylation regulators for metabolism-related genes. Cox regression of data on metabolism-related genes was performed to screen for genes that affect the prognosis of patients with CESC. Furthermore, we selected key genes for validation.ResultsOur results identified 3620 metabolism-related genes in CESC, 2493 of which contained related mutations. The co-occurrence of CUBN, KALRN, and HERC1 was related to the prognosis of CESC. The fraction of genome altered (FGA) closely correlated with overall survival. In expression analysis, 374 genes were related to the occurrence and prognosis of CESC. We then identified four metabolic pathway modules in WGCNA. Further analysis revealed that glycolysis/gluconeogenesis was related to endothelial cells and that arachidonic acid metabolism was related to cell proliferation. These four modules were also related to the prognosis of CESC. Among CESC-related metabolic genes, two genes were found to be regulated by microRNAs (miRNAs) and methylation, whereas another two genes were coregulated by miRNAs and mutations.ConclusionsAmong metabolism-related genes, 15 genes were related to the prognosis of CESC. The co-occurrence of CUBN/KALRN/HERC1 was associated with CESC prognosis. Glycolysis/gluconeogenesis was related to endothelial cells, and arachidonic acid metabolism was related to cell proliferation.

Circ_0000337 Promotes the Progression of Cervical Cancer by miR-155-5p/RAB3B Axis.

Current study aims to investigate the biological function of circular RNA (circRNA, circ_0000337) in cervical cancer (CC). Bioinformatic analyses were used to predict targets for circ_0000337 and miR-155-5p, and analyze the gene expression differences between cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) tissues and normal tissues. Quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot were applied to assess mRNA and protein expressions of circ_0000337, microRNA-155-5p (miR-155-5p) and member RAS oncogene family (RAB3B), respectively. Following the establishment of gain/loss-of-function models, CCK-8 was performed to evaluate cell proliferation. Bioinformatics analysis, dual-luciferase reporter assay and RNA immunoprecipitation (RIP) were used to identify the interaction in circ_0000337, miR-155-5p, and RAB3B. Circ_0000337 and RAB3B were upregulated, while miR-155-5p was downregulated in CC tissues and cell lines. circ_0000337 overexpression promoted cell proliferation, circ_0000337 knock down inhibited cell proliferation by sponging miR-155-5p. RAB3B was a target of miR-155-5p which was positively regulated by circ_0000337. In the collected CC tissues, there was a negative correlation between miR-155-5p and circ_0000337 or RAB3B, and a positive correlation between circ_0000337 and RAB3B. miR-155-5p was positively, while RAB3B was negatively correlated with OS in patients with CC, and they were negatively correlated. In conclusion, circ_0000337 upregulates RAB3B by sponging miR-155-5p to promote CC cell proliferation.

Dedifferentiated Schwann cells promote perineural invasion mediated by the PACAP paracrine signalling in cervical cancer.

Perineural invasion (PNI) has emerged as a key pathological feature and be considered as a poor prognostic factor in cervical cancer. However, the underlying molecular mechanisms are largely unknown. Here, PNI status of 269 cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) samples were quantified by using whole-slide diagnostic images obtained from The Cancer Genome Atlas. Integrated analyses revealed that PNI was an indicative marker of poorer disease-free survival for CESC patients. Among the differentially expressed genes, ADCYAP1 were identified. Clinical specimens supported that high expression of PACAP (encoded by ADCYAP1) contributed to PNI in CESC. Mechanistically, PACAP, secreted from cervical cancer cells, reversed myelin differentiation of Schwann cells (SCs). Then, dedifferentiated SCs promoted PNI by producing chemokine FGF17 and by degrading extracellular matrix through secretion of Cathepsin S and MMP-12. In conclusion, this study identified PACAP was associated with PNI in cervical cancer and suggested that tumour-derived PACAP reversed myelin differentiation of SCs to aid PNI.

Functional analysis of tumor-derived immunoglobulin lambda and its interacting proteins in cervical cancer

BackgroundImmunoglobulin lambda (Igλ) has been reported to be expressed in many normal and tumor tissues and cells. However, the function and clinical significance of tumor-derived Igλ remain unclear.MethodsThe differential expressions of Immunoglobulin Lambda Constants (IGLCs) in cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) were examined with The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Human Protein Atlas (HPA) databases. The effects of IGLCs on patient clinical phenotypes and prognosis were explored via bioinformatics analyses based on the TCGA databases. We used the bioinformatics analyses based on the TCGA and GTEx databases to elucidate the correlations among IGLC expressions, immunomodulator expressions, tumor stemness, and infiltration scores of tumor infiltrating immune cells. Co-immunoprecipitation (Co-IP) and silver staining combined with liquid chromatography-tandem mass spectrometry (LC–MS/MS) were used to obtain potential tumor-derived Igλ-interacting proteins. Functional annotation of candidate proteins identified by LC–MS/MS was performed in Database for Annotation, Visualization and Integrated Discovery (DAVID). The bioinformatics analyses of 7 IGLCs in CESC and normal cervical tissues were performed based on TCGA, GTEx, and Gene Expression Profiling Interactive Analysis 2 (GEPIA2) databases. Protein–protein interaction (PPI) network was analyzed based on tumor-derived Igλ-interacting proteins in Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. Immunohistochemistry (IHC) was used to validate the expressions of IGLCs in CESC.ResultsWe found that the expressions of the majority of IGLCs (IGLC1, IGLC2, IGLC3, IGLC4, IGLC5, IGLC6, and IGLC7) were upregulated in CESC tissues, compared with those in normal cervical tissues. The expressions of IGLC5 and IGLC7 had significant difference in different pathologic metastasis (M), one of tumor, node, and metastasis (TNM) staging system, categories of CESC. Except for disease-free interval (DFI), 4 IGLC (IGLC1, IGLC2, IGLC3, and IGLC7) expression levels were positively associated with patient overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) respectively in CESC tissues. 5 IGLC (IGLC1, IGLC2, IGLC3, IGLC6, and IGLC7) expressions were positively correlated with the expressions of a majority of immunomodulators respectively in CESC tissues. Tumor stemness was negatively correlated with the expressions of 4 IGLCs (IGLC1, IGLC2, IGLC3, and IGLC7) respectively in CESC tissues. Except for IGLC4, IGLC5, and IGLC7, 4 IGLC (IGLC1, IGLC2, IGLC3, and IGLC6) expressions were positively correlated with infiltration scores of 6 tumor-infiltrating immune cells (B cell, T cell CD4, T cell CD8, neutrophil, macrophage, and DC). After analyses of the above bioinformatics data of tumor-derived Igλ, Co-IP and LC–MS/MS were used to confirm that 4 proteins (RPL7, RPS3, H1-5, and H1-6) might interact with tumor-derived Igλ in cervical cancer cells. Functional analyses of these candidate proteins showed that they interacted with many proteins and were involved in various cellular biological processes. Finally, IHC was used to further confirm the above bioinformatics results, it was indicated that the expression level of Igλ in cervical adenocarcinoma and cervical squamous cell carcinoma was higher than that in normal cervical tissue.ConclusionThis study comprehensively investigated the functions of tumor-derived Igλ and its interacting proteins based on bioinformatics analysis and the potential value of Igλ as a prognostic and therapeutic marker for CESC, providing new direction and evidence for CESC therapy.

A Novel Eight-Gene Signature for Lipid Metabolism Predicts the Progression of Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma.

Recently, studies on the mechanisms underlying lipid metabolic reprogramming in cancer have increased. However, its significance in cervical cancer remains unclear. In the present study, a prognostic signature was constructed for patients with cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) using the expression profiles of lipid metabolism-related genes (LMRGs). Furthermore, using various bioinformatics methods, a prognostic gene signature was developed for progression-free survival (PFS). This signature was externally validated using a cervical cancer dataset (GSE44001). The characteristics of the molecular subgroups of LMRGs were analyzed, and target LMRGs were identified via differential gene analysis of the expression profiles and weighted gene correlation network analysis. Thereafter, the identified target genes were used to develop the prognostic gene signature using univariate, least absolute shrinkage and selection operator, and multivariate Cox regression analyses. The performance of the LMRG signature was evaluated using Kaplan-Meier curves, time-dependent receiver operating characteristic curves, decision curve analysis, mutation landscapes, gene set enrichment analysis, and immune score calculation. As a result, a novel eight-LMRG signature comprising ALDH3B2, CERS3, FA2H, GLTP, NR1H3, PLIN3, SLC44A3, and SQLE was constructed. Using this gene signature, patients with CESC and significantly distinguished PFS were divided. This eight-LMRG signature exhibited independent prognostic potential and superior predictive performance compared with a previously developed 12-gene signature. Our findings suggest that our novel eight-LMRG signature contributes to the implementation of precision medicine strategies for managing patients with cervical cancer by facilitating CESC prognosis.