Prognostic value and immune-infiltration pattern of FOXD3-AS1 in patients with glioma

Chen, Zhenhua; Zhang, Yi; Feng, Sujuan; Yuan, Jiaqi; Shi, Dongliang; Wang, Yong; Dong, Jun

doi:10.3389/fphar.2023.1162309

Cited by 3 publications

(1 citation statement)

References 28 publications

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“…Given the above, our study emphasizes the urgency to unravel speci c molecular and microenvironmental properties and identify key biomarkers impacting GBM and LGG metabolism. By doing so, we aim to pave the way for more targeted potential therapies [14,15]. To this end, we have developed a prognostic predictive nomogram speci c for brain glioma (GBMLGG) centered around disul dptosis-associated genes.…”

Section: Introductionmentioning

confidence: 99%

Exploring the Role of Disulfidptosis-Related Genes in GBMLGG Prognosis: A Comprehensive Pan-Cancer Study

Shen,

Li,

et al. 2024

Preprint

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Background Disulfidptosis, a novel programmed cell death (PCD) driven by disulfide stress, has emerged as a potential player in various cancer dynamics. However, its implications in Glioma (GBMLGG) prognosis and immunotherapy response remain an uncharted territory. Results An extensive analysis on 15 disulfidptosis-associated genes across multiple cancers highlighted their diverse prognostic values. Specifically for GBMLGG, these genes offered unique non-clustered grouping with profound significance in prognosis differentiation. Out of these, seven pivotal genes were pinpointed using a robust machine learning framework encompassing 101 algorithm combinations. Their prognostic reliability was underscored through receiver operating characteristic curves and Kaplan-Meier (KM) analyses, both presenting highly satisfactory outcomes. The culmination of this work led to the formulation of a predictive nomogram. In-depth correlations were established between these target genes and key tumor-immunity factors, with 13 types of immune cells and 19 immune checkpoint genes showcasing significant ties. Single-cell analysis provided further validation to these findings. Conclusions This study underscores the intricate relationship between disulfidptosis-associated genes and GBMLGG prognosis. The derived nomogram, based on meticulously selected target genes through machine learning, exhibited remarkable accuracy across different datasets, offering promising avenues for GBMLGG prognostic strategies. Trial registration: Not applicable

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Section: Introductionmentioning

confidence: 99%

Exploring the Role of Disulfidptosis-Related Genes in GBMLGG Prognosis: A Comprehensive Pan-Cancer Study

Shen,

Li,

et al. 2024

Preprint

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Prognostic model construction of disulfidptosis-associated genes in brain glioma and their relevance in immune checkpoints

Shen,

Xu,

Wang

2023

Preprint

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Background: Disulfidptosis is a novel form of programmed cell death (PCD) triggered by disulfide stress and is implicated to have a potential role in various cancers. Although the role of disulfidptosis has been assessed in various cancers, its role in Glioma (GBMLGG) prognosis and immunotherapy response remains unexplored. Results: A prognostic analysis of 15 disulfidptosis-associated genes in a pan-cancer dataset revealed significant differences in their prognostic performance in several cancer types. An analysis of GBMLGG revealed that the prognosis of GBMLGG predicted by the 15 disulfidptosis-associated genes had grouped without any clusters, and the difference in the prognosis among the subgroups was highly significant. Subsequently, seven target genes were identified using 10 machine learning algorithms including 101 algorithm combinations, and their prognostic prediction was validated by constructing receiver operating characteristic curves and conducting Kaplan-Meier (KM) analyses, which showed very satisfactory results. The complete predictive nomogram was then constructed. Furthermore, we analyzed the correlation between the target genes and immune cells, tumor mutational burden, and immune checkpoints, and the results showed that 13 cell lines and 19 immune checkpoint–associated genes were significantly correlated with the target genes. These results were also verified through single-cell analysis. Conclusions: An in-depth analysis of GBMLGG confirmed the strong correlation between the target genes of disulfidptosis-associated cell death and GBMLGG prognosis in multiple ways. The prognostic predictive nomogram was constructed using powerful machine learning algorithms to screen for the final target genes, which demonstrated excellent results when tested using several datasets. Trial registration: Not applicable

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The Role of Disulfidptosis in Gliomas: Insights from Mendelian Randomization and Machine Learning

Pang,

Li,

et al. 2024

Preprint

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This study introduces a novel prognostic model for glioma outcomes based on disulfidptosis, a unique programmed cell death pathway, highlighting its potential in cancer progression. Analyzing 15 disulfidptosis genes across various cancers, significant prognostic disparities were observed in GBMLGG, ACC, LIHC, KIRC, and others. A detailed investigation in GBMLGG utilized one training and two testing groups to identify seven target genes (ACTN4, IQGAP1, DSTN, MYH9, PDLIM1, FLNB, ACTB) using 101 machine learning approaches across 10 models. Their predictive accuracy for patient prognosis was confirmed through ROC and KM analyses across three datasets. A comprehensive nomogram prediction model incorporating clinical data was developed and independently validated. The study also explored correlations between target genes, immune cells, tumor mutational burden (TMB), and 19 immune checkpoints, uncovering significant associations with 13 cell lines and 19 immune checkpoint-related genes. Validation techniques included single-cell analysis, PCR, immunohistochemistry, and summary data-based Mendelian randomization. The research underscores the importance of disulfidptosis in cancer development and its strong correlation with GBMLGG prognosis, facilitated by immune microenvironment interactions and specific immune checkpoint inhibitors. This multifaceted analysis not only affirms disulfidptosis's role in prognostic predictions for GBMLGG but also its broader impact on cancer research, offering a deep dive into the molecular mechanisms of tumor heterogeneity and the immune landscape.

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Prognostic value and immune-infiltration pattern of FOXD3-AS1 in patients with glioma

Cited by 3 publications

References 28 publications

Exploring the Role of Disulfidptosis-Related Genes in GBMLGG Prognosis: A Comprehensive Pan-Cancer Study

Exploring the Role of Disulfidptosis-Related Genes in GBMLGG Prognosis: A Comprehensive Pan-Cancer Study

Prognostic model construction of disulfidptosis-associated genes in brain glioma and their relevance in immune checkpoints

The Role of Disulfidptosis in Gliomas: Insights from Mendelian Randomization and Machine Learning

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