Construction of an Excellent 7 mRNAsi-Related Gene Model Based on Cancer Stem Cells for Predicting Survival Outcome of Cervical Cancer

Background. Cervical cancer (CC) is one of the most frequent female malignancy. Cancer stem cells (CSCs) positively affect survival outcomes in cancer patients, but in cervical cancer, the mechanism of tumor stem cells is still uncertain. Methods. RNA-seq data and related clinical follow-up of patie...

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Main Authors: Yang Liu, Lin Yang, Hao Liang, Jianhua Zeng, Yuanyuan Hua, Huan Wu
Format: Article
Language:English
Published: Wiley 2023-01-01
Series:Stem Cells International
Online Access:http://dx.doi.org/10.1155/2023/8383058
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author Yang Liu
Lin Yang
Hao Liang
Jianhua Zeng
Yuanyuan Hua
Huan Wu
author_facet Yang Liu
Lin Yang
Hao Liang
Jianhua Zeng
Yuanyuan Hua
Huan Wu
author_sort Yang Liu
collection DOAJ
description Background. Cervical cancer (CC) is one of the most frequent female malignancy. Cancer stem cells (CSCs) positively affect survival outcomes in cancer patients, but in cervical cancer, the mechanism of tumor stem cells is still uncertain. Methods. RNA-seq data and related clinical follow-up of patients suffering from CC were from TCGA. Consensus clustering screened prognostic mRNAsi-related genes and identified molecular subtypes for CC. Based on the overlapping differentially expressed genes (DEGs) in subtypes, we employed LASSO and multivariate Cox regression to screen prognostic-related genes and established the RiskScore system. The patients were grouped by RiskScore, the prognosis was analyzed by the Kaplan-Meier (K-M) curve among the various groups, and the precision of the RiskScore was assessed by the ROC curve. Finally, the potential worth of RiskScore in immunotherapy/chemotherapy response was assessed by evaluating TIDE scores and chemotherapy drug IC50 values. Results. We noticed that patients with low mRNAsi had a shorter survival and then identified three molecular subtypes (C1-3), with the C1 having the worst prognosis and the lowest mRNAsi. Finally, we identified 7 prognostic-related genes (SPRY4, PPP1R14A, MT1A, DES, SEZ6L2, SLC22A3, and CXCL8) via LASSO and Cox regression analysis. We established a 7-gene model defined RiskScore to predict the prognosis of CC patients. K-M curve indicated that low RiskScore patients had improved prognosis, and ROC curves indicated that RiskScore could precisely direct the prognostic evaluation for those suffering from the cancer. This was also confirmed in the GSE44001 and GSE52903 external cohorts. Patients were more sensitive to immunotherapy if with low RiskScore, and RiskScore exhibited precise assessment ability in predicting response to immunological therapy in CC patients. Conclusion. CC stemness is associated with patient prognosis, and the RiskScore constructed based on stemness characteristics is an independent prognostic index, which is expected to be a guide for immunotherapy, providing a new idea for CC clinical practice.
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spelling doaj-art-d784c2c3ca0148229cc1d316bba6665c2025-08-20T02:20:58ZengWileyStem Cells International1687-96782023-01-01202310.1155/2023/8383058Construction of an Excellent 7 mRNAsi-Related Gene Model Based on Cancer Stem Cells for Predicting Survival Outcome of Cervical CancerYang Liu0Lin Yang1Hao Liang2Jianhua Zeng3Yuanyuan Hua4Huan Wu5Department of Obstetrics and GynecologyDepartment of GynecologyDepartment of Obstetrics and GynecologyDepartment of Obstetrics and GynecologyDepartment of Obstetrics and GynecologyDepartment of Obstetrics and GynecologyBackground. Cervical cancer (CC) is one of the most frequent female malignancy. Cancer stem cells (CSCs) positively affect survival outcomes in cancer patients, but in cervical cancer, the mechanism of tumor stem cells is still uncertain. Methods. RNA-seq data and related clinical follow-up of patients suffering from CC were from TCGA. Consensus clustering screened prognostic mRNAsi-related genes and identified molecular subtypes for CC. Based on the overlapping differentially expressed genes (DEGs) in subtypes, we employed LASSO and multivariate Cox regression to screen prognostic-related genes and established the RiskScore system. The patients were grouped by RiskScore, the prognosis was analyzed by the Kaplan-Meier (K-M) curve among the various groups, and the precision of the RiskScore was assessed by the ROC curve. Finally, the potential worth of RiskScore in immunotherapy/chemotherapy response was assessed by evaluating TIDE scores and chemotherapy drug IC50 values. Results. We noticed that patients with low mRNAsi had a shorter survival and then identified three molecular subtypes (C1-3), with the C1 having the worst prognosis and the lowest mRNAsi. Finally, we identified 7 prognostic-related genes (SPRY4, PPP1R14A, MT1A, DES, SEZ6L2, SLC22A3, and CXCL8) via LASSO and Cox regression analysis. We established a 7-gene model defined RiskScore to predict the prognosis of CC patients. K-M curve indicated that low RiskScore patients had improved prognosis, and ROC curves indicated that RiskScore could precisely direct the prognostic evaluation for those suffering from the cancer. This was also confirmed in the GSE44001 and GSE52903 external cohorts. Patients were more sensitive to immunotherapy if with low RiskScore, and RiskScore exhibited precise assessment ability in predicting response to immunological therapy in CC patients. Conclusion. CC stemness is associated with patient prognosis, and the RiskScore constructed based on stemness characteristics is an independent prognostic index, which is expected to be a guide for immunotherapy, providing a new idea for CC clinical practice.http://dx.doi.org/10.1155/2023/8383058
spellingShingle Yang Liu
Lin Yang
Hao Liang
Jianhua Zeng
Yuanyuan Hua
Huan Wu
Construction of an Excellent 7 mRNAsi-Related Gene Model Based on Cancer Stem Cells for Predicting Survival Outcome of Cervical Cancer
Stem Cells International
title Construction of an Excellent 7 mRNAsi-Related Gene Model Based on Cancer Stem Cells for Predicting Survival Outcome of Cervical Cancer
title_full Construction of an Excellent 7 mRNAsi-Related Gene Model Based on Cancer Stem Cells for Predicting Survival Outcome of Cervical Cancer
title_fullStr Construction of an Excellent 7 mRNAsi-Related Gene Model Based on Cancer Stem Cells for Predicting Survival Outcome of Cervical Cancer
title_full_unstemmed Construction of an Excellent 7 mRNAsi-Related Gene Model Based on Cancer Stem Cells for Predicting Survival Outcome of Cervical Cancer
title_short Construction of an Excellent 7 mRNAsi-Related Gene Model Based on Cancer Stem Cells for Predicting Survival Outcome of Cervical Cancer
title_sort construction of an excellent 7 mrnasi related gene model based on cancer stem cells for predicting survival outcome of cervical cancer
url http://dx.doi.org/10.1155/2023/8383058
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