The Comprehensive Analysis Identified an Autophagy Signature for the Prognosis and the Immunotherapy Efficiency Prediction in Lung Adenocarcinoma

Li, Xizhe; Dai, Ziyu; Wu, Xianning; Zhang, Nan; Zhang, Hao; Wang, Zeyu; Zhang, Xun; Liang, Xisong; Luo, Peng; Zhang, Jian; Liu, Zaoqu; Zhou, Yanwu; Cheng, Quan; Chang, Ruimin

doi:10.3389/fimmu.2022.749241

Cited by 28 publications

(27 citation statements)

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“…Many LUAD-associated prognostic models have been made available previously; for example, an immune-related prognostic signature constructed by Yi et al (2021) , a ferroptosis-associated prognostic signature introduced by Wang et al (2021) , an autophagy-related prognostic signature developed by Li et al (2022) , and an inflammatory-associated prognostic signature identified by Zhai et al (2021) have identified. Compared with these models, our study reported a prognostic model based on neddylation-associated genes which shows promising prognostic accuracy.…”

Section: Discussionmentioning

confidence: 99%

Neddylation pattern indicates tumor microenvironment characterization and predicts prognosis in lung adenocarcinoma

Cui

Chen

Pan

et al. 2022

Front. Cell Dev. Biol.

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Background: Lung adenocarcinoma (LUAD) is the most common type of lung cancer with a complex tumor microenvironment. Neddylation, as a type of post-translational modification, plays a vital role in the development of LUAD. To date, no study has explored the potential of neddylation-associated genes for LUAD classification, prognosis prediction, and treatment response evaluation.Methods: Seventy-six neddylation-associated prognostic genes were identified by Univariate Cox analysis. Patients with LUAD were classified into two patterns based on unsupervised consensus clustering analysis. In addition, a 10-gene prognostic signature was constructed using LASSO-Cox and a multivariate stepwise regression approach.Results: Substantial differences were observed between the two patterns of LUAD in terms of prognosis. Compared with neddylation cluster2, neddylation cluster1 exhibited low levels of immune infiltration that promote tumor progression. Additionally, the neddylation-related risk score correlated with clinical parameters and it can be a good predictor of patient outcomes, gene mutation levels, and chemotherapeutic responses.Conclusion: Neddylation patterns can distinguish tumor microenvironment and prognosis in patients with LUAD. Prognostic signatures based on neddylation-associated genes can predict patient outcomes and guide personalized treatment.

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Section: Discussionmentioning

confidence: 99%

Neddylation pattern indicates tumor microenvironment characterization and predicts prognosis in lung adenocarcinoma

Cui

Chen

Pan

et al. 2022

Front. Cell Dev. Biol.

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“…Therefore, it is of great significance to identify and characterize phagocytosis regulatory factors and clarify their roles in LUAD prognosis and immunotherapy response for the prognosis and treatment of LUAD patients. Gene signature is a biological function model constructed from the expression data of multiple genes, which can be used to predict the prognosis and progression of many types of malignant tumors (17). Yi et al constructed a prognostic model of 17-immune-related genes signature to predict survival and response to ICI (immune checkpoint inhibitors) in LUAD patients and the result showed that patients with a lowrisk score had a better prognosis and predicted benefit from ICI treatment (18).…”

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Identification and validation of a novel phagocytosis regulators-related signature with potential prognostic and immunotherapeutic value in patients with lung adenocarcinoma

Sun

et al. 2022

Front. Oncol.

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BackgroundLung adenocarcinoma (LUAD) is a malignant tumor that seriously affects the prognosis of patients. Tumor-associated macrophages (TAMs) play a vital role in the tumor microenvironment and can be used as a potential target for tumor therapy, and phagocytosis regulators (PRs) are particularly important in this process. However, the PRs-related signature that can predict the potential prognostic and immunotherapeutic value in patients with LUAD has not been discovered.MethodsIn this study, we mainly analyzed the effect of phagocytosis regulators on the prognosis of LUAD, and based on multiple screening analyses including differential analysis, univariate Cox analysis, and Lasso analysis, we constructed a prognostic risk model consisting of five genes. To verify the stability of the model, survival analysis and ROC curve verification were carried out through multiple data sets. In addition, we also combined many factors, such as immune infiltrating cells, clinical grouping characteristics, immune examination sites, pro-inflammatory factors, and other factors as well as in vitro cell experiments and clinical tissue samples for further validation analysis.ResultsAfter identifying 29 differentially expressed PRs in LUAD samples, we further constructed a prognostic model consisting of five prognostic signatures (FURIN, KIF23, SASH3, GNPNAT1, and ITGAL). Further survival analysis tests, ROC verification, as well as univariate and multivariate Cox regression analysis showed that the risk score of the model could well predict the prognosis of LUAD patients and could be used as an independent prognostic factor. In addition, we further found that these phagocytic regulators-related signatures were closely related to the immune microenvironment and immunotherapy in LUAD patients, and could well predict the efficacy of immunotherapy in patients. In vitro cell experiments and Immunohistochemistry of clinical tissues showed that the expressions of FURIN, KIF23, SASH3, GNPNAT1 and ITGAL in normal lung cells/tissues and LUAD cells/tissues were consistent with bioinformatics results, and 3 of them had significant differences.ConclusionOur study identified a novel PRs-related signature that has potential application value in predicting the prognosis of LUAD patients and predicting the efficacy of immunotherapy. This provides a new basis for the prognosis assessment of LUAD patients and provides a novel target for immunotherapy of LUAD patients.

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“…Consistently, how to evaluate the efficacy of ICP therapy is a problem faced by the majority of oncologists (59)(60)(61). On the one hand, "magic drugs" will bring a resurrection effect to some patients, but on the other hand, improper use is likely to cause various side effects (62).…”

Section: Discussionmentioning

confidence: 99%

LncRNA profiles from Notch signaling: Implications for clinical management and tumor microenvironment of colorectal cancer

et al. 2022

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The interplay between long non-coding RNAs (lncRNAs) and the Notch pathway involves a variety of malignancies. However, Notch-derived lncRNAs and their latent clinical significance remain elusive in colorectal cancer (CRC). In this study, we introduced a framework that could screen Notch-derived lncRNAs (named “NLncer”) and ultimately identified 24 NLncers. To further explore the clinical significance of these NLncers, we performed LASSO and Cox regression in TCGA-CRC cohort (n = 584) and then retained six lncRNAs tightly associated with prognosis. The final model (termed “NLncS”) was subsequently tested in GSE38832 (n = 122), GSE39582 (n = 573), and an in-house clinical cohort (n = 115). Ultimately, our NLncS model could serve as an independent risk factor and afford a robust performance for assessing the prognosis of CRC patients. Additionally, patients with high NLncS risk scores were characterized by upregulation of immune pathways, strong immunogenicity, abundant CD8 + T-cell infiltration, and potentially higher response rates to CTLA4 blockers, which turned out to be suitable for immunotherapy. Aiming at globally observing the characteristics of high-risk patients, somatic mutation and methylation modification analysis provide us with evidence at the genomic and transcriptomic levels. To facilitate the clinical transformability, we mined deeply into the sensitive compounds targeting high-risk individuals and identified dasatinib as a candidate agent for patients with a high Notch risk score. In conclusion, our NLncS model is a promising biomarker for optimizing the clinical management of CRC patients.

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The Comprehensive Analysis Identified an Autophagy Signature for the Prognosis and the Immunotherapy Efficiency Prediction in Lung Adenocarcinoma

Cited by 28 publications

References 50 publications

Neddylation pattern indicates tumor microenvironment characterization and predicts prognosis in lung adenocarcinoma

Neddylation pattern indicates tumor microenvironment characterization and predicts prognosis in lung adenocarcinoma

Identification and validation of a novel phagocytosis regulators-related signature with potential prognostic and immunotherapeutic value in patients with lung adenocarcinoma

LncRNA profiles from Notch signaling: Implications for clinical management and tumor microenvironment of colorectal cancer

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