Prognostic Significance and Immune Landscape of a Cuproptosis-Related LncRNA Signature in Ovarian Cancer

<b>Background:</b> Cuproptosis is a copper-induced mitochondrial cell death, and regulating cuproptosis is becoming a rising cancer treatment modality. Here, we attempted to establish a cuproptosis-associated lncRNAs (CRLs) signature (CRlncSig) to predict the survival, immune landscape, and treatment response in ovarian cancer (OC) patients. <b>Methods:</b> A series of statistical analyses were used to identify the key CRLs that are closely related to the prognosis, and a prognostic CRlncSig was constructed. The predictive accuracy of the CRlncSig was further validated in an independent Gene Expression Omnibus (GEO) set. Then, we compared the immune cell infiltration, immune checkpoints, tumor microenvironment (TME), tumor mutational burden (TMB), drug sensitivity, and efficacy of immunotherapy between the two subgroups. We further built a nomogram integrating the CRlncSig and different clinical traits to enhance the clinical application of the CRlncSig. <b>Results:</b> Nine hub CRLs, namely RGMB-AS1, TYMSOS, DANCR, LINC00702, LINC00240, LINC00996, DNM1P35, LINC00892, and TMEM254-AS1, were correlated with the overall survival (OS) of OC and a prognostic CRlncSig was established. The CRlncSig classified OC patients into two risk groups with strikingly different survival probabilities. The time-dependent ROC (tdROC) curves demonstrated good predictive ability in both the training cohort and an independent validation cohort. Multivariate analysis confirmed the independent predictive performance of the CRlncSig. We constructed a nomogram based on the CRlncSig, which can predict the prognosis of OC patients. The high-risk score was characterized by decreased immune cell infiltration and activation of stroma, while activation of immunity was observed in the low-risk subgroup. Moreover, patients in low-risk subgroups had more Immunophenoscore (IPS) and fewer immune escapes compared to high-risk subgroups. Finally, an immunotherapeutic cohort confirmed the value of the CRlncSig in predicting immunotherapy outcomes. <b>Conclusions:</b> The developed CRlncSig may be promising for the clinical prediction of OC patient outcomes and immunotherapeutic responses.

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Publication Details

Journal
Biomedicines
Published
2024-11-19
DOI
https://doi.org/10.3390/biomedicines12112640
Citations
2
Primary Topic
Cancer-related molecular mechanisms research
Type
article
Field-Weighted Citation Impact
0.57

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article

Prognostic Significance and Immune Landscape of a Cuproptosis-Related LncRNA Signature in Ovarian Cancer

Guotao Huang, Jianming Tang, Min Zhou, Hong Li
2 citations
Biomedicines
Cancer-related molecular mechanisms research
0.57
article

Prognostic Significance and Immune Landscape of a Cuproptosis-Related LncRNA Signature in Ovarian Cancer

Guotao Huang, Jianming Tang, Min Zhou, Hong Li
article en
2 citations

Abstract

<b>Background:</b> Cuproptosis is a copper-induced mitochondrial cell death, and regulating cuproptosis is becoming a rising cancer treatment modality. Here, we attempted to establish a cuproptosis-associated lncRNAs (CRLs) signature (CRlncSig) to predict the survival, immune landscape, and treatment response in ovarian cancer (OC) patients. <b>Methods:</b> A series of statistical analyses were used to identify the key CRLs that are closely related to the prognosis, and a prognostic CRlncSig was constructed. The predictive accuracy of the CRlncSig was further validated in an independent Gene Expression Omnibus (GEO) set. Then, we compared the immune cell infiltration, immune checkpoints, tumor microenvironment (TME), tumor mutational burden (TMB), drug sensitivity, and efficacy of immunotherapy between the two subgroups. We further built a nomogram integrating the CRlncSig and different clinical traits to enhance the clinical application of the CRlncSig. <b>Results:</b> Nine hub CRLs, namely RGMB-AS1, TYMSOS, DANCR, LINC00702, LINC00240, LINC00996, DNM1P35, LINC00892, and TMEM254-AS1, were correlated with the overall survival (OS) of OC and a prognostic CRlncSig was established. The CRlncSig classified OC patients into two risk groups with strikingly different survival probabilities. The time-dependent ROC (tdROC) curves demonstrated good predictive ability in both the training cohort and an independent validation cohort. Multivariate analysis confirmed the independent predictive performance of the CRlncSig. We constructed a nomogram based on the CRlncSig, which can predict the prognosis of OC patients. The high-risk score was characterized by decreased immune cell infiltration and activation of stroma, while activation of immunity was observed in the low-risk subgroup. Moreover, patients in low-risk subgroups had more Immunophenoscore (IPS) and fewer immune escapes compared to high-risk subgroups. Finally, an immunotherapeutic cohort confirmed the value of the CRlncSig in predicting immunotherapy outcomes. <b>Conclusions:</b> The developed CRlncSig may be promising for the clinical prediction of OC patient outcomes and immunotherapeutic responses.

BiomedicinesVol. 12(11)
Wuhan University (CN), Renmin Hospital of Wuhan University (CN)
Fundamental Research Funds for the Central Universities
Good health and well-being
Openalex Percentile: Top 30%
Cancer-related molecular mechanisms research
0.57
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