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Liu B, He S, Li C, Li Z, Feng C, Wang H, Tu C, Li Z. Development of a prognostic Neutrophil Extracellular Traps related lncRNA signature for soft tissue sarcoma using machine learning. Front Immunol 2024; 14:1321616. [PMID: 38264665 PMCID: PMC10803471 DOI: 10.3389/fimmu.2023.1321616] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2023] [Accepted: 12/19/2023] [Indexed: 01/25/2024] Open
Abstract
Background Soft tissue sarcoma (STS) is a highly heterogeneous musculoskeletal tumor with a significant impact on human health due to its high incidence and malignancy. Long non-coding RNA (lncRNA) and Neutrophil Extracellular Traps (NETs) have crucial roles in tumors. Herein, we aimed to develop a novel NETsLnc-related signature using machine learning algorithms for clinical decision-making in STS. Methods We applied 96 combined frameworks based on 10 different machine learning algorithms to develop a consensus signature for prognosis and therapy response prediction. Clinical characteristics, univariate and multivariate analysis, and receiver operating characteristic curve (ROC) analysis were used to evaluate the predictive performance of our models. Additionally, we explored the biological behavior, genomic patterns, and immune landscape of distinct NETsLnc groups. For patients with different NETsLnc scores, we provided information on immunotherapy responses, chemotherapy, and potential therapeutic agents to enhance the precision medicine of STS. Finally, the gene expression was validated through real-time quantitative PCR (RT-qPCR). Results Using the weighted gene co-expression network analysis (WGCNA) algorithm, we identified NETsLncs. Subsequently, we constructed a prognostic NETsLnc signature with the highest mean c-index by combining machine learning algorithms. The NETsLnc-related features showed excellent and stable performance for survival prediction in STS. Patients in the low NETsLnc group, associated with improved prognosis, exhibited enhanced immune activity, immune infiltration, and tended toward an immunothermal phenotype with a potential immunotherapy response. Conversely, patients with a high NETsLnc score showed more frequent genomic alterations and demonstrated a better response to vincristine treatment. Furthermore, RT-qPCR confirmed abnormal expression of several signature lncRNAs in STS. Conclusion In conclusion, the NETsLnc signature shows promise as a powerful approach for predicting the prognosis of STS. which not only deepens our understanding of STS but also opens avenues for more targeted and effective treatment strategies.
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Affiliation(s)
- Binfeng Liu
- Department of Orthopaedics, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
- Hunan Key Laboratory of Tumor Models and Individualized Medicine of The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Shasha He
- Department of Oncology, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Chenbei Li
- Department of Orthopaedics, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
- Hunan Key Laboratory of Tumor Models and Individualized Medicine of The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Zhaoqi Li
- Department of Orthopaedics, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
- Hunan Key Laboratory of Tumor Models and Individualized Medicine of The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Chengyao Feng
- Department of Orthopaedics, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
- Hunan Key Laboratory of Tumor Models and Individualized Medicine of The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Hua Wang
- Department of Orthopaedics, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
- Hunan Key Laboratory of Tumor Models and Individualized Medicine of The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Chao Tu
- Department of Orthopaedics, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
- Hunan Key Laboratory of Tumor Models and Individualized Medicine of The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
- Shenzhen Research Institute of Central South University, Guangdong, China
| | - Zhihong Li
- Department of Orthopaedics, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
- Hunan Key Laboratory of Tumor Models and Individualized Medicine of The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
- Shenzhen Research Institute of Central South University, Guangdong, China
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Yang X, Du Y, Luo L, Xu X, Xiong S, Yang X, Guo L, Liang T. Deciphering the Enigmatic Influence: Non-Coding RNAs Orchestrating Wnt/β-Catenin Signaling Pathway in Tumor Progression. Int J Mol Sci 2023; 24:13909. [PMID: 37762212 PMCID: PMC10530696 DOI: 10.3390/ijms241813909] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 09/04/2023] [Accepted: 09/08/2023] [Indexed: 09/29/2023] Open
Abstract
Dysregulated expression of specific non-coding RNAs (ncRNAs) has been strongly linked to tumorigenesis, cancer progression, and therapeutic resistance. These ncRNAs can act as either oncogenes or tumor suppressors, thereby serving as valuable diagnostic and prognostic markers. Numerous studies have implicated the participation of ncRNAs in the regulation of diverse signaling pathways, including the pivotal Wnt/β-catenin signaling pathway that is widely acknowledged for its pivotal role in embryogenesis, cellular proliferation, and tumor biology control. Recent emerging evidence has shed light on the capacity of ncRNAs to interact with key components of the Wnt/β-catenin signaling pathway, thereby modulating the expression of Wnt target genes in cancer cells. Notably, the activity of this pathway can reciprocally influence the expression levels of ncRNAs. However, comprehensive analysis investigating the specific ncRNAs associated with the Wnt/β-catenin signaling pathway and their intricate interactions in cancer remains elusive. Based on these noteworthy findings, this review aims to unravel the intricate associations between ncRNAs and the Wnt/β-catenin signaling pathway during cancer initiation, progression, and their potential implications for therapeutic interventions. Additionally, we provide a comprehensive overview of the characteristics of ncRNAs and the Wnt/β-catenin signaling pathway, accompanied by a thorough discussion of their functional roles in tumor biology. Targeting ncRNAs and molecules associated with the Wnt/β-catenin signaling pathway may emerge as a promising and effective therapeutic strategy in future cancer treatments.
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Affiliation(s)
- Xinbing Yang
- Jiangsu Key Laboratory for Molecular and Medical Biotechnology, School of Life Science, Nanjing Normal University, Nanjing 210023, China; (X.Y.); (Y.D.); (L.L.); (X.X.)
| | - Yajing Du
- Jiangsu Key Laboratory for Molecular and Medical Biotechnology, School of Life Science, Nanjing Normal University, Nanjing 210023, China; (X.Y.); (Y.D.); (L.L.); (X.X.)
| | - Lulu Luo
- Jiangsu Key Laboratory for Molecular and Medical Biotechnology, School of Life Science, Nanjing Normal University, Nanjing 210023, China; (X.Y.); (Y.D.); (L.L.); (X.X.)
| | - Xinru Xu
- Jiangsu Key Laboratory for Molecular and Medical Biotechnology, School of Life Science, Nanjing Normal University, Nanjing 210023, China; (X.Y.); (Y.D.); (L.L.); (X.X.)
| | - Shizheng Xiong
- Department of Bioinformatics, Smart Health Big Data Analysis and Location Services Engineering Lab of Jiangsu Province, School of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing 210023, China; (S.X.); (X.Y.)
| | - Xueni Yang
- Department of Bioinformatics, Smart Health Big Data Analysis and Location Services Engineering Lab of Jiangsu Province, School of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing 210023, China; (S.X.); (X.Y.)
| | - Li Guo
- Department of Bioinformatics, Smart Health Big Data Analysis and Location Services Engineering Lab of Jiangsu Province, School of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing 210023, China; (S.X.); (X.Y.)
| | - Tingming Liang
- Jiangsu Key Laboratory for Molecular and Medical Biotechnology, School of Life Science, Nanjing Normal University, Nanjing 210023, China; (X.Y.); (Y.D.); (L.L.); (X.X.)
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