The m6A-Related Long Noncoding RNA Signature Predicts Prognosis and Indicates Tumor Immune Infiltration in Ovarian Cancer

<b>Background:</b> OV is the most lethal gynecological malignancy. M6A and lncRNAs have a great impact on OV development and patient immunotherapy response. In this paper, we decided to establish a reliable signature of mRLs. <b>Method:</b> The lncRNAs associated with m6A in...

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Main Authors: Rui Geng, Tian Chen, Zihang Zhong, Senmiao Ni, Jianling Bai, Jinhui Liu
Format: Article
Language:English
Published: MDPI AG 2022-08-01
Series:Cancers
Subjects:
Online Access:https://www.mdpi.com/2072-6694/14/16/4056
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author Rui Geng
Tian Chen
Zihang Zhong
Senmiao Ni
Jianling Bai
Jinhui Liu
author_facet Rui Geng
Tian Chen
Zihang Zhong
Senmiao Ni
Jianling Bai
Jinhui Liu
author_sort Rui Geng
collection DOAJ
description <b>Background:</b> OV is the most lethal gynecological malignancy. M6A and lncRNAs have a great impact on OV development and patient immunotherapy response. In this paper, we decided to establish a reliable signature of mRLs. <b>Method:</b> The lncRNAs associated with m6A in OV were analyzed and obtained by co-expression analysis of the TCGA-OV database. Univariate, LASSO and multivariate Cox regression analyses were employed to establish the model of mRLs. K-M analysis, PCA, GSEA and nomogram based on the TCGA-OV and GEO database were conducted to prove the predictive value and independence of the model. The underlying relationship between the model and TME and cancer stemness properties were further investigated through immune feature comparison, consensus clustering analysis and pan-cancer analysis. <b>Results:</b> A prognostic signature comprising four mRLs, WAC-AS1, LINC00997, DNM3OS and FOXN3-AS1, was constructed and verified for OV according to the TCGA and GEO database. The expressions of the four mRLs were confirmed by qRT-PCR in clinical samples. Applying this signature, one can identify patients more effectively. The samples were divided into two clusters, and the clusters had different overall survival rates, clinical features and tumor microenvironments. Finally, pan-cancer analysis further demonstrated that the four mRLs were significantly related to immune infiltration, TME and cancer stemness properties in various cancer types. <b>Conclusions:</b> This study provided an accurate prognostic signature for patients with OV and elucidated the potential mechanism of the mRLs in immune modulation and treatment response, giving new insights into identifying new therapeutic targets.
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spelling doaj.art-6decf0cd179043e3a16051ad837837662023-12-01T23:32:37ZengMDPI AGCancers2072-66942022-08-011416405610.3390/cancers14164056The m6A-Related Long Noncoding RNA Signature Predicts Prognosis and Indicates Tumor Immune Infiltration in Ovarian CancerRui Geng0Tian Chen1Zihang Zhong2Senmiao Ni3Jianling Bai4Jinhui Liu5Department of Biostatistics, School of Public Heath, Nanjing Medical University, 101 Longmian Avenue, Jiangning District, Nanjing 211166, ChinaDepartment of Gynecology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, ChinaDepartment of Biostatistics, School of Public Heath, Nanjing Medical University, 101 Longmian Avenue, Jiangning District, Nanjing 211166, ChinaDepartment of Biostatistics, School of Public Heath, Nanjing Medical University, 101 Longmian Avenue, Jiangning District, Nanjing 211166, ChinaDepartment of Biostatistics, School of Public Heath, Nanjing Medical University, 101 Longmian Avenue, Jiangning District, Nanjing 211166, ChinaDepartment of Gynecology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China<b>Background:</b> OV is the most lethal gynecological malignancy. M6A and lncRNAs have a great impact on OV development and patient immunotherapy response. In this paper, we decided to establish a reliable signature of mRLs. <b>Method:</b> The lncRNAs associated with m6A in OV were analyzed and obtained by co-expression analysis of the TCGA-OV database. Univariate, LASSO and multivariate Cox regression analyses were employed to establish the model of mRLs. K-M analysis, PCA, GSEA and nomogram based on the TCGA-OV and GEO database were conducted to prove the predictive value and independence of the model. The underlying relationship between the model and TME and cancer stemness properties were further investigated through immune feature comparison, consensus clustering analysis and pan-cancer analysis. <b>Results:</b> A prognostic signature comprising four mRLs, WAC-AS1, LINC00997, DNM3OS and FOXN3-AS1, was constructed and verified for OV according to the TCGA and GEO database. The expressions of the four mRLs were confirmed by qRT-PCR in clinical samples. Applying this signature, one can identify patients more effectively. The samples were divided into two clusters, and the clusters had different overall survival rates, clinical features and tumor microenvironments. Finally, pan-cancer analysis further demonstrated that the four mRLs were significantly related to immune infiltration, TME and cancer stemness properties in various cancer types. <b>Conclusions:</b> This study provided an accurate prognostic signature for patients with OV and elucidated the potential mechanism of the mRLs in immune modulation and treatment response, giving new insights into identifying new therapeutic targets.https://www.mdpi.com/2072-6694/14/16/4056ovarian serous cystadenocarcinomaN6-methyladenosinelong noncoding RNAsprognosistumor microenvironment
spellingShingle Rui Geng
Tian Chen
Zihang Zhong
Senmiao Ni
Jianling Bai
Jinhui Liu
The m6A-Related Long Noncoding RNA Signature Predicts Prognosis and Indicates Tumor Immune Infiltration in Ovarian Cancer
Cancers
ovarian serous cystadenocarcinoma
N6-methyladenosine
long noncoding RNAs
prognosis
tumor microenvironment
title The m6A-Related Long Noncoding RNA Signature Predicts Prognosis and Indicates Tumor Immune Infiltration in Ovarian Cancer
title_full The m6A-Related Long Noncoding RNA Signature Predicts Prognosis and Indicates Tumor Immune Infiltration in Ovarian Cancer
title_fullStr The m6A-Related Long Noncoding RNA Signature Predicts Prognosis and Indicates Tumor Immune Infiltration in Ovarian Cancer
title_full_unstemmed The m6A-Related Long Noncoding RNA Signature Predicts Prognosis and Indicates Tumor Immune Infiltration in Ovarian Cancer
title_short The m6A-Related Long Noncoding RNA Signature Predicts Prognosis and Indicates Tumor Immune Infiltration in Ovarian Cancer
title_sort m6a related long noncoding rna signature predicts prognosis and indicates tumor immune infiltration in ovarian cancer
topic ovarian serous cystadenocarcinoma
N6-methyladenosine
long noncoding RNAs
prognosis
tumor microenvironment
url https://www.mdpi.com/2072-6694/14/16/4056
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