Necroptosis Identifies Novel Molecular Phenotypes and Influences Tumor Immune Microenvironment of Lung Adenocarcinoma

Zhao, Chen; Xiong, Kewei; Adam, Abdalla; Ji, Zhiqiang; Li, Xiangpan

doi:10.3389/fimmu.2022.934494

Cited by 11 publications

(8 citation statements)

References 45 publications

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“…Recent studies have demonstrated that NRGs play a crucial role in prompting the progression of cardiac and neurological diseases and can serve as a biomarker for prognosis and treatment in patients with multiple diseases (35)(36)(37)(38). Furthermore, bioinformatics analysis elucidated the key role of necrosis-based prognostic models in the diagnosis and treatment of patients with various cancers (39)(40)(41). However, whether necroptosis is implicated in ASD progression has not been reported so far.…”

Section: Discussionmentioning

confidence: 99%

Combination of machine learning-based bulk and single-cell genomics reveals necroptosis-related molecular subtypes and immunological features in autism spectrum disorder

Liu

Ding

et al. 2023

Front. Immunol.

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BackgroundNecroptosis is a novel form of controlled cell death that contributes to the progression of various illnesses. Nonetheless, the function and significance of necroptosis in autism spectrum disorders (ASD) remain unknown and require further investigation.MethodsWe utilized single-nucleus RNA sequencing (snRNA-seq) data to assess the expression patterns of necroptosis in children with autism spectrum disorder (ASD) based on 159 necroptosis-related genes. We identified differentially expressed NRGs and used an unsupervised clustering approach to divide ASD children into distinct molecular subgroups. We also evaluated immunological infiltrations and immune checkpoints using the CIBERSORT algorithm. Characteristic NRGs, identified by the LASSO, RF, and SVM-RFE algorithms, were utilized to construct a risk model. Moreover, functional enrichment, immune infiltration, and CMap analysis were further explored. Additionally, external validation was performed using RT-PCR analysis.ResultsBoth snRNA-seq and bulk transcriptome data demonstrated a greater necroptosis score in ASD children. Among these cell subtypes, excitatory neurons, inhibitory neurons, and endothelials displayed the highest activity of necroptosis. Children with ASD were categorized into two subtypes of necroptosis, and subtype2 exhibited higher immune activity. Four characteristic NRGs (TICAM1, CASP1, CAPN1, and CHMP4A) identified using three machine learning algorithms could predict the onset of ASD. Nomograms, calibration curves, and decision curve analysis (DCA) based on 3-NRG have been shown to have clinical benefit in children with ASD. Furthermore, necroptosis-based riskScore was found to be positively associated with immune activation. Finally, RT-PCR demonstrated differentially expressed of these four NRGs in human peripheral blood samples.ConclusionA comprehensive identification of necroptosis may shed light on the underlying pathogenic process driving ASD onset. The classification of necroptosis subtypes and construction of a necroptosis-related risk model may yield significant insights for the individualized treatment of children with ASD.

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Section: Discussionmentioning

confidence: 99%

Combination of machine learning-based bulk and single-cell genomics reveals necroptosis-related molecular subtypes and immunological features in autism spectrum disorder

Liu

Ding

et al. 2023

Front. Immunol.

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“…Therefore, demethylation treatments could improve the anticancer efficacy of chemotherapy [84]. A further study investigating the epigenetic landscape of necroptosis in lung adenocarcinoma (LUAD) did not identify any correlation between the levels of methylation in the RIPK3 promoter and its mRNA expression [85].…”

Section: Epigenetic Regulation In Necroptosismentioning

confidence: 94%

Epi-Regulation of Cell Death in Cancer

Beato¹,

Torre²,

Capone³

et al. 2023

Biochemistry

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How do organisms regulate the correct balance between the production of “new” cells and the elimination of the “old” ones, remains an important biology issue under investigation. Cell(s) death represents a fundamental process involved in organism development and cell homeostasis, whose alteration is considered one hallmark of cancer and lead to drug resistance and consequently treatment failure. The recent re-classification of cell death has identified new molecular programs in which several proteins have a pivotal role. Several studies have highlighted a direct link between epigenetic modifications and cell death mechanisms. Different epi-modifications have been described, capable of regulating diverse key players implicated in cell death, leading to uncontrolled proliferation of cancer cells. Scientific efforts are focused on the understanding the epigenetic regulation of cell death mechanisms by developing tools and/or new epi-molecules able to overcome cell death resistance. The development of new epi-molecular tools can overcome cell death deregulation thus potentially improving the sensitivity to the anti-tumor therapies. This chapter focuses on the main epigenetic deregulations in cell death mechanisms in cancer.

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“…The immune infiltrating levels were conducted using ssGSEA https://github.com/GSEA-MSigDB/ssGSEA-gpmodule ), MCPcounter https://github.com/ebecht/MCPcounter ), xCell https://xcell.ucsf.edu/ ), ABIS https://github.com/giannimonaco/ABIS ) and ESTIMATE ( https://cibersortx.stanford.edu/ ) algorithms according to previously described ( 38 ). Briefly, the proportions of a variety of immune cells in each sample were assessed using global marker genes, and the above algorithms were applied for calculating fractional enrichment or relative abundance for each immune cell subset.…”

Section: Methodsmentioning

confidence: 99%

Integration of bulk RNA sequencing and single-cell analysis reveals a global landscape of DNA damage response in the immune environment of Alzheimer’s disease

Lai

Lin²,

Chen³

et al. 2023

Front. Immunol.

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BackgroundWe developed a novel system for quantifying DNA damage response (DDR) to help diagnose and predict the risk of Alzheimer’s disease (AD).MethodsWe thoroughly estimated the DDR patterns in AD patients Using 179 DDR regulators. Single-cell techniques were conducted to validate the DDR levels and intercellular communications in cognitively impaired patients. The consensus clustering algorithm was utilized to group 167 AD patients into diverse subgroups after a WGCNA approach was employed to discover DDR-related lncRNAs. The distinctions between the categories in terms of clinical characteristics, DDR levels, biological behaviors, and immunological characteristics were evaluated. For the purpose of choosing distinctive lncRNAs associated with DDR, four machine learning algorithms, including LASSO, SVM-RFE, RF, and XGBoost, were utilized. A risk model was established based on the characteristic lncRNAs.ResultsThe progression of AD was highly correlated with DDR levels. Single-cell studies confirmed that DDR activity was lower in cognitively impaired patients and was mainly enriched in T cells and B cells. DDR-related lncRNAs were discovered based on gene expression, and two different heterogeneous subtypes (C1 and C2) were identified. DDR C1 belonged to the non-immune phenotype, while DDR C2 was regarded as the immune phenotype. Based on various machine learning techniques, four distinctive lncRNAs associated with DDR, including FBXO30-DT, TBX2-AS1, ADAMTS9-AS2, and MEG3 were discovered. The 4-lncRNA based riskScore demonstrated acceptable efficacy in the diagnosis of AD and offered significant clinical advantages to AD patients. The riskScore ultimately divided AD patients into low- and high-risk categories. In comparison to the low-risk group, high-risk patients showed lower DDR activity, accompanied by higher levels of immune infiltration and immunological score. The prospective medications for the treatment of AD patients with low and high risk also included arachidonyltrifluoromethane and TTNPB, respectively,ConclusionsIn conclusion, immunological microenvironment and disease progression in AD patients were significantly predicted by DDR-associated genes and lncRNAs. A theoretical underpinning for the individualized treatment of AD patients was provided by the suggested genetic subtypes and risk model based on DDR.

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Necroptosis Identifies Novel Molecular Phenotypes and Influences Tumor Immune Microenvironment of Lung Adenocarcinoma

Cited by 11 publications

References 45 publications

Combination of machine learning-based bulk and single-cell genomics reveals necroptosis-related molecular subtypes and immunological features in autism spectrum disorder

Combination of machine learning-based bulk and single-cell genomics reveals necroptosis-related molecular subtypes and immunological features in autism spectrum disorder

Epi-Regulation of Cell Death in Cancer

Integration of bulk RNA sequencing and single-cell analysis reveals a global landscape of DNA damage response in the immune environment of Alzheimer’s disease

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