A novel prognostic prediction model based on seven immune-related RNAs for predicting overall survival of patients in early cervical squamous cell carcinoma

Qin, Rui; Cao, Lu; Ye, Cong; Wang, Junrong; Sun, Ziqian

doi:10.1186/s12920-021-00885-3

Cited by 8 publications

(6 citation statements)

References 39 publications

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“…Interestingly, in a previous analysis, we showed that the high expression of VCAM1 indicates a good prognosis in cervical cancer patients, which is in line with the results of a previous study ( 39 ). To examine the aberrant expression of VCAM1 in cervical tumor tissues and further explore the relationship between miR-95-3p and VCAM1 , we collected clinical cervical tumor tissue samples and downregulated the expression of miR-95-3p with an inhibitor in the HeLa cells.…”

Section: Resultssupporting

confidence: 92%

MiR-95-3p acts as a prognostic marker and promotes cervical cancer progression by targeting VCAM1

Feng¹,

Lu²,

Sun³

et al. 2022

Ann Transl Med

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Background: Cervical cancer patients have a high risk of metastasis and a poor prognosis with shorter disease-free survival. Thus, novel biomarkers and feasible therapies urgently need to be discovered. Previous studies have shown that miR-95-3p plays crucial roles in several cancer types. However, the roles of miR-95-3p in cervical cancer remain unknown. Methods: The micro ribonucleic acid (miRNA) expression data and clinical characteristics of cervical cancer samples were downloaded from The Cancer Genome Atlas (TCGA) database. Univariate and multivariate Cox regression analyses were conducted to identify the prognostic-related miRNAs. The potential target genes of miR-95-3p were predicted by the TargetScan database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted to explore the target gene of miR-95-3p. The effects of miR-95-3p inhibition and overexpression on cell proliferation were inspected by cell counting kit-8 (CCK-8) assays and cell colony formation assays. Woundhealing assays and transwell assays were also used to examine cell migration ability in HeLa and SiHa cells. Results: MiR-95-3p was the only miRNA significantly associated with the poor prognosis of cervical squamous cell carcinoma. A further analysis suggested that vascular cell adhesion molecule 1 (VCAM1) is a target gene of miR-95-3p in cervical cancer, and miR-95-3p promotes the malignant behavior of cervical cancer cells by inhibiting the expression of VCAM1. The CCK-8 and cell colony assays showed that miR-95-3p downregulation significantly suppressed cell proliferation in the HeLa and SiHa cells. The transwell and wound-healing assays showed that miR-95-3p inhibition suppressed cell migration in the HeLa and SiHa cells. Further the Western blot analysis and the quantitative real-time-polymerase chain reaction (qRT-PCR) showed that the knockdown of miR-95-3p in HeLa cells resulted in increased VCAM1 expression. And VCAM1 was highly expressed in the paired adjacent normal cervical epithelium tissue samples, but lowly expressed in the cervical tumor tissue samples. Conclusions: Our study was the first to show that miR-95-3p could serve as a prognostic biomarker of cervical cancer. Mechanistically, we discovered that miR-95-3p inhibited the expression of the cell adhesion molecule VCAM1 and thus promoted further tumor progression.

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Section: Resultssupporting

confidence: 92%

MiR-95-3p acts as a prognostic marker and promotes cervical cancer progression by targeting VCAM1

Feng¹,

Lu²,

Sun³

et al. 2022

Ann Transl Med

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“…Recent years the net reclassification index (NRI), integrated discrimination improvement (IDI) have become the two popularity alternatives assessment in risk evaluation or prediction between different models (21,22). We searched ten recently published CESC prognostic signatures, and used NRI, IDI method in "survIDINRI" package to compare the clinical benefits of our signature and published signatures (23)(24)(25)(26)(27)(28)(29)(30)(31)(32).…”

Section: Clinical Benefits Evaluation Of Cesc Os Signaturesmentioning

confidence: 99%

A Novel Prognostic Risk Model for Cervical Cancer Based on Immune Checkpoint HLA-G-Driven Differentially Expressed Genes

Wang

Xing

et al. 2022

Front. Immunol.

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Human leukocyte antigen G (HLA-G) is a potential checkpoint molecule that plays a key role in cervical carcinogenesis. The purpose of this study was to construct and validate a prognostic risk model to predict the overall survival (OS) of cervical cancer patients, providing a reference for individualized clinical treatment that may lead to better clinical outcomes. HLA-G-driven differentially expressed genes (DEGs) were obtained from two cervical carcinoma cell lines, namely, SiHa and HeLa, with stable overexpression of HLA-G by RNA sequencing (RNA-seq). The biological functions of these HLA-G-driven DEGs were analysed by GO enrichment and KEGG pathway using the “clusterProfiler” package. The protein-protein interactions (PPIs) were assessed using the STRING database. The prognostic relevance of each DEG was evaluated by univariate Cox regression using the TCGA-CESC dataset. After the TCGA-CESC cohort was randomly divided into training set and testing set, and a prognostic risk model was constructed by LASSO and stepwise multivariate Cox regression analysis in training set and validated in testing set or in different types of cervical cancer set. The predictive ability of the prognostic risk model or nomogram was evaluated by a series of bioinformatics methods. A total of 1108 candidate HLA-G-driven DEGs, including 391 upregulated and 717 downregulated genes, were obtained and were enriched mostly in the ErbB pathway, steroid biosynthesis, and MAPK pathway. Then, an HLA-G-driven DEG signature consisting of the eight most important prognostic genes CD46, LGALS9, PGM1, SPRY4, CACNB3, PLIN2, MSMO1, and DAGLB was identified as a key predictor of cervical cancer. Multivariate Cox regression analysis showed that this signature is an independent risk factor for the overall survival of CESC patients. Kaplan-Meier survival analysis showed that the 5-year overall survival rate is 23.0% and 84.6% for the high-risk and low-risk patients, respectively (P<0.001). The receiver operating characteristic (ROC) curve of this prognostic model with an area under the curve (AUC) was 0.896 for 5 years, which was better than that of other clinical traits. This prognostic risk model was also successfully validated in different subtypes of cervical cancer, including the keratinizing squamous cell carcinoma, non-keratinizing squamous cell carcinoma, squamous cell neoplasms, non-squamous cell neoplasms set. Single-sample gene set enrichment (ssGSEA) algorithm and Tumor Immune Dysfunction and Exclusion (TIDE) analysis confirmed that this signature influence tumour microenvironment and immune checkpoint blockade. A nomogram that integrated risk score, age, clinical stage, histological grade, and pathological type was then built to predict the overall survival of CESC patients and evaluated by calibration curves, AUC, concordance index (C-index) and decision curve analysis (DCA). To summarize, we developed and validated a novel prognostic risk model for cervical cancer based on HLA-G-driven DEGs, and the prognostic signature showed great ability in predicting the overall survival of patients with cervical cancer.

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“…In another study, an autophagy-related gene prognostic risk model was applied to provide a reference for CC patients to make precise treatment strategy, and the AUCs for prognostic accuracy reached 0.772 for the training set and 0.889 for the verification set. Other gene sets for establishing prognostic model in CC included immune-related genes [ 15 ], DNA methylation [ 16 ], and lymph node metastasis [ 17 ].…”

Section: Discussionmentioning

confidence: 99%

A cellular senescence-related genes model allows for prognosis and treatment stratification of cervical cancer: a bioinformatics analysis and external verification

Yang,

An,

et al. 2023

Aging

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Background: Cervical cancer (CC) is highly lethal and aggressive with an increasing trend of mortality for females. Molecular characterization-based methods hold great promise for improving the diagnostic accuracy and for predicting treatment response. Methods: The mRNAs expression data of CC patients and cellular senescence-related genes were obtained from the Cancer Genome Atlas (TCGA) and CellAge databases, respectively. Differentially expressed genes (DEGs) of senescence related genes between tumor and normal tissues were used for Least absolute shrinkage and selection operator (LASSO) regression to construct a prognostic model. Univariate and LASSO regression analyses were applied to establish a predictive nomogram. The performance of the nomogram were evaluated by Kaplan-Meier curve, receiver operating characteristic (ROC), Harrell's concordance index (C-index), and calibration curve. GSE44001 and GSE52903 were used for external validation. Results: We established a cellular senescence-related genes-based stratified model, and a multivariable-based nomogram, which could accurately predict the prognosis of CC patients in the TCGA database. The Kaplan-Meier curve indicated that patients in the low-risk group had considerably better overall survival (OS, P =2.021e-05). The area under the ROC curve (AUC) of this model was 0.743 for OS. Multivariate analysis found that the 6-gene risk signature (HR=3.166, 95%CI: 1.660-6.041, P<0.001) was an independent risk factor for CC patients. We then designed an OS-associated nomogram that included the risk signature and clinicopathological factors. The AUC reached 0.860 for predicting 5-year OS. The nomogram showed excellent consistency between the predictions and actual survival observations. Two external GEO validations were corresponding to the gene expression pattern in TCGA. Conclusions: Our results suggested a six-senescence related signature and established a prognostic nomogram that reliably predicted the overall survival for CC. These findings may be beneficial to personalized treatment and medical decision-making.

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A novel prognostic prediction model based on seven immune-related RNAs for predicting overall survival of patients in early cervical squamous cell carcinoma

Cited by 8 publications

References 39 publications

MiR-95-3p acts as a prognostic marker and promotes cervical cancer progression by targeting VCAM1

MiR-95-3p acts as a prognostic marker and promotes cervical cancer progression by targeting VCAM1

A Novel Prognostic Risk Model for Cervical Cancer Based on Immune Checkpoint HLA-G-Driven Differentially Expressed Genes

A cellular senescence-related genes model allows for prognosis and treatment stratification of cervical cancer: a bioinformatics analysis and external verification

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