Construction of a novel MPT-driven necrosis-related lncRNAs signature for prognosis prediction in laryngeal squamous cell carcinoma

Jian, Liu; Zhang, Min; Sun, Qing; Qin, Xuemei; Gao, Tianle; Xu, Yinwei; Han, Shuhui; Zhang, Yinhuo

doi:10.1007/s11356-023-26996-1

Cited by 9 publications

(7 citation statements)

References 50 publications

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“…A lncRNA‒mRNA co-expression network was established utilizing Cytoscape software (version 3.7.2, http://www.cytoscape.org/ ) [ 12 ]. The network was constructed to enable an examination of the relationship between SRGs and SRlncRNAs with Pearson correlation coefficients (with a significance threshold of P < 0.001 and |R|> 0.4).…”

Section: Methodsmentioning

confidence: 99%

“…cytos cape. org/) [12]. The network was constructed to enable an examination of the relationship between SRGs and SRlncRNAs with Pearson correlation coefficients (with a significance threshold of P < 0.001 and |R|> 0.4).…”

Section: Construction Of the Lncrna-mrna Co-expression Networkmentioning

confidence: 99%

“…Long non-coding RNAs (lncRNAs), despite their lack of coding capacity [11][12][13][14], play significant roles in various cellular processes, including the regulation of gene expression, facilitation of subcellular transport, modulation of protein degradation, and promotion of organelle biogenesis [15]. Research indicates that abnormal expression of lncRNAs significantly influences TNBC cell behavior, impacting proliferation, migration, metastasis, and tumorigenicity [16][17][18].…”

Section: Introductionmentioning

confidence: 99%

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Comprehensive characterization of stemness-related lncRNAs in triple-negative breast cancer identified a novel prognostic signature related to treatment outcomes, immune landscape analysis and therapeutic guidance: a silico analysis with in vivo experiments

Zhang,

Wang

et al. 2024

J Transl Med

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Background Cancer stem cells (CSCs) and long non-coding RNAs (lncRNAs) are known to play a crucial role in the growth, migration, recurrence, and drug resistance of tumor cells, particularly in triple-negative breast cancer (TNBC). This study aims to investigate stemness-related lncRNAs (SRlncRNAs) as potential prognostic indicators for TNBC patients. Methods Utilizing RNA sequencing data and corresponding clinical information from the TCGA database, and employing Weighted Gene Co-expression Network Analysis (WGCNA) on TNBC mRNAsi sourced from an online database, stemness-related genes (SRGs) and SRlncRNAs were identified. A prognostic model was developed using univariate Cox and LASSO-Cox analysis based on SRlncRNAs. The performance of the model was evaluated using Kaplan–Meier analysis, ROC curves, and ROC-AUC. Additionally, the study delved into the underlying signaling pathways and immune status associated with the divergent prognoses of TNBC patients. Results The research identified a signature of six SRlncRNAs (AC245100.6, LINC02511, AC092431.1, FRGCA, EMSLR, and MIR193BHG) for TNBC. Risk scores derived from this signature were found to correlate with the abundance of plasma cells. Furthermore, the nominated chemotherapy drugs for TNBC exhibited considerable variability between different risk score groups. RT-qPCR validation confirmed abnormal expression patterns of these SRlncRNAs in TNBC stem cells, affirming the potential of the SRlncRNAs signature as a prognostic biomarker. Conclusion The identified signature not only demonstrates predictive power in terms of patient outcomes but also provides insights into the underlying biology, signaling pathways, and immune status associated with TNBC prognosis. The findings suggest the possibility of guiding personalized treatments, including immune checkpoint gene therapy and chemotherapy strategies, based on the risk scores derived from the SRlncRNA signature. Overall, this research contributes valuable knowledge towards advancing precision medicine in the context of TNBC.

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Section: Methodsmentioning

confidence: 99%

Section: Construction Of the Lncrna-mrna Co-expression Networkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Comprehensive characterization of stemness-related lncRNAs in triple-negative breast cancer identified a novel prognostic signature related to treatment outcomes, immune landscape analysis and therapeutic guidance: a silico analysis with in vivo experiments

Zhang,

Wang

et al. 2024

J Transl Med

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“…The transcriptomic data and corresponding clinical information of ccRCC patients were acquired from the TCGA database (https:// portal.gdc.cancer.gov/). Drawing from pertinent literature, the gene set associated with mitochondrial permeability transition-driven necrosis (MPTDN) was identified (19). Patients were then randomly stratified into a training set and a test set at a proportion of 7:3, specifically focusing on genes implicated in MPTDN for ensuing analyses.…”

Section: Data Sourcesmentioning

confidence: 99%

Elucidating the Influence of MPT-driven necrosis-linked LncRNAs on immunotherapy outcomes, sensitivity to chemotherapy, and mechanisms of cell death in clear cell renal carcinoma

Huang,

Liu,

Chen

et al. 2023

Front. Oncol.

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BackgroundClear cell renal carcinoma (ccRCC) stands as the prevailing subtype among kidney cancers, making it one of the most prevalent malignancies characterized by significant mortality rates. Notably,mitochondrial permeability transition drives necrosis (MPT-Driven Necrosis) emerges as a form of cell death triggered by alterations in the intracellular microenvironment. MPT-Driven Necrosis, recognized as a distinctive type of programmed cell death. Despite the association of MPT-Driven Necrosis programmed-cell-death-related lncRNAs (MPTDNLs) with ccRCC, their precise functions within the tumor microenvironment and prognostic implications remain poorly understood. Therefore, this study aimed to develop a novel prognostic model that enhances prognostic predictions for ccRCC.MethodsEmploying both univariate Cox proportional hazards and Lasso regression methodologies, this investigation distinguished genes with differential expression that are intimately linked to prognosis.Furthermore, a comprehensive prognostic risk assessment model was established using multiple Cox proportional hazards regression. Additionally, a thorough evaluation was conducted to explore the associations between the characteristics of MPTDNLs and clinicopathological features, tumor microenvironment, and chemotherapy sensitivity, thereby providing insights into their interconnectedness.The model constructed based on the signatures of MPTDNLs was verified to exhibit excellent prediction performance by Cell Culture and Transient Transfection, Transwell and other experiments.ResultsBy analyzing relevant studies, we identified risk scores derived from MPTDNLs as an independent prognostic determinant for ccRCC, and subsequently we developed a Nomogram prediction model that combines clinical features and associated risk assessment. Finally, the application of experimental techniques such as qRT-PCR helped to compare the expression of MPTDNLs in healthy tissues and tumor samples, as well as their role in the proliferation and migration of renal clear cell carcinoma cells. It was found that there was a significant correlation between CDK6-AS1 and ccRCC results, and CDK6-AS1 plays a key role in the proliferation and migration of ccRCC cells. Impressive predictive results were generated using marker constructs based on these MPTDNLs.ConclusionsIn this research, we formulated a new prognostic framework for ccRCC, integrating mitochondrial permeability transition-induced necrosis. This model holds significant potential for enhancing prognostic predictions in ccRCC patients and establishing a foundation for optimizing therapeutic strategies.

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“…Mounting evidence suggests that lncRNAs significantly influenced diverse cancer-related processes, including tumor initiation, proliferation, metastasis, drug resistance, and programmed cell death [ [15] , [16] , [17] ]. Currently, research investigating the modes of cell death in LSCC or HNSCC has identified immunity-related lncRNA [ 18 ], ferroptosis-related lncRNAs [ 19 ], MPT-driven necrosis-related [ 20 ], and stemness-related lncRNAs [ 21 ] as valuable prognostic biomarkers and therapeutic targets for LSCC or HNSCC. However, the role of DRlncRNAs remains unclear.…”

Section: Introductionmentioning

confidence: 99%

Construction of a novel disulfidptosis-related lncRNAs signature for prognosis prediction and anti-tumor immunity in laryngeal squamous cell carcinoma

Zhang,

Sun,

Han

et al. 2024

Heliyon

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Construction of a novel MPT-driven necrosis-related lncRNAs signature for prognosis prediction in laryngeal squamous cell carcinoma

Cited by 9 publications

References 50 publications

Comprehensive characterization of stemness-related lncRNAs in triple-negative breast cancer identified a novel prognostic signature related to treatment outcomes, immune landscape analysis and therapeutic guidance: a silico analysis with in vivo experiments

Comprehensive characterization of stemness-related lncRNAs in triple-negative breast cancer identified a novel prognostic signature related to treatment outcomes, immune landscape analysis and therapeutic guidance: a silico analysis with in vivo experiments

Elucidating the Influence of MPT-driven necrosis-linked LncRNAs on immunotherapy outcomes, sensitivity to chemotherapy, and mechanisms of cell death in clear cell renal carcinoma

Construction of a novel disulfidptosis-related lncRNAs signature for prognosis prediction and anti-tumor immunity in laryngeal squamous cell carcinoma

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