Identification and experimental validation of mitochondria-related genes biomarkers associated with immune infiltration for sepsis

Shen, Qi; She, Han; Chen, Xi; Zhong, Like; Zhu, Junfeng; Luo, Fa

doi:10.3389/fimmu.2023.1184126

Cited by 14 publications

(6 citation statements)

References 54 publications

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“…On the other hand, RF is a predictive algorithm that does not impose restrictions on variable conditions, making it capable of providing predictions without apparent variations [ 35 ]. The intersection of the two results can serve as the candidate feature genes for diagnosis [ 36 , 37 ]. Using the LASSO regression algorithm, we identified a subset of 14 feature genes (Fig.…”

Section: Resultsmentioning

confidence: 99%

Analysis and experimental validation of necroptosis-related molecular classification, immune signature and feature genes in Alzheimer’s disease

Lian,

Cai,

Yang

et al. 2024

Apoptosis

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Necroptosis, a programmed cell death pathway, has been demonstrated to be activated in Alzheimer’s disease (AD). However, the precise role of necroptosis and its correlation with immune cell infiltration in AD remains unclear. In this study, we conducted non-negative matrix factorization clustering analysis to identify three subtypes of AD based on necroptosis-relevant genes. Notably, these subtypes exhibited varying necroptosis scores, clinical characteristics and immune infiltration signatures. Cluster B, characterized by high necroptosis scores, showed higher immune cell infiltration and was associated with a more severe pathology, potentially representing a high-risk subgroup. To identify potential biomarkers for AD within cluster B, we employed two machine learning algorithms: the least absolute shrinkage and selection operator regression and Random Forest. Subsequently, we identified eight feature genes (CARTPT, KLHL35, NRN1, NT5DC3, PCYOX1L, RHOQ, SLC6A12, and SLC38A2) that were utilized to develop a diagnosis model with remarkable predictive capacity for AD. Moreover, we conducted validation using bulk RNA-seq, single-nucleus RNA-seq, and in vivo experiments to confirm the expression of these feature genes. In summary, our study identified a novel necroptosis-related subtype of AD and eight diagnostic biomarkers, explored the roles of necroptosis in AD progression and shed new light for the clinical diagnosis and treatment of this disease.

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Section: Resultsmentioning

confidence: 99%

Analysis and experimental validation of necroptosis-related molecular classification, immune signature and feature genes in Alzheimer’s disease

Lian,

Cai,

Yang

et al. 2024

Apoptosis

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“…GSE179285 (GPL6480, Agilent-014850 Whole Human Genome Microarray 4x44K G4112F (Probe Name version)) and GSE107499 (GPL15207, (PrimeView) Affymetrix Human Gene Expression Array) (31 HC and 175 UC samples) were combined as the validation cohort. To remove the batch effect of each GEO dataset, we utilized the “SVA” package to standardize processing the transcriptome data [ 19 , 20 ].…”

Section: Methodsmentioning

confidence: 99%

Machine learning-based B cell-related diagnostic biomarker signature and molecular subtypes characteristic of ulcerative colitis

Wu,

Li,

Chen

et al. 2024

Aging

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As an inflammatory bowel disease, ulcerative colitis (UC) does not respond well to current treatments. It is of positive clinical significance to further study the pathogenesis of UC and find new therapeutic targets. B lymphocytes play an important role in the pathogenesis of UC. The effect of anti-CD20 therapy on UC also provides new evidence for the involvement of B cells in UC process additionally, suggesting the important role and potential therapeutic value of B cells in UC. In this study, we screened the most critical immune cell-related gene modules associated with UC and found that activated B cells were closely related to the gene modules. Subsequently, key activated B cell-associated gene (BRG) signatures were obtained based on WGCNA and differential expression analysis, and three overlapping BRG-associated genes were obtained by RF and LASSO algorithms as BRG-related diagnostic biomarkers for UC. Nomogram model was further performed to evaluate the diagnostic ability of BRG-related diagnostic biomarkers, subsequently followed by UC molecular subsets identification and immunoinfiltration analysis. We also further verified the expressions of the three screened BRGs in vitro by using an LPS-induced NCM460 cell line model. Our results provide new evidence and potential intervention targets for the role of B cells in UC from a new perspective.

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“…Thereafter, the ROC curve was plotted and the area under curve (AUC) values were calculated. The ‘rms’ package [ 19 ] was used to display the nomograms and calibration curves of the multifactorial model, and the C-index was calculated to predict survival…”

Section: Methodsmentioning

confidence: 99%

Construction of a Novel Mitochondria-Associated Gene Model for Assessing ESCC Immune Microenvironment and Predicting Survival

Wang,

Zhang,

Shi

et al. 2024

J. Microbiol. Biotechnol.

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Esophageal squamous cell carcinoma (ESCC) is among the most common malignant tumors of the digestive tract, with the sixth highest fatality rate worldwide. The ESCC-related dataset, GSE20347, was downloaded from the Gene Expression Omnibus (GEO) database, and weighted gene co-expression network analysis was performed to identify genes that are highly correlated with ESCC. A total of 91 transcriptome expression profiles and their corresponding clinical information were obtained from The Cancer Genome Atlas database. A mitochondria-associated risk (MAR) model was constructed using the least absolute shrinkage and selection operator Cox regression analysis and validated using GSE161533. The tumor microenvironment and drug sensitivity were explored using the MAR model. Finally, in vitro experiments were performed to analyze the effects of hub genes on the proliferation and invasion abilities of ESCC cells. To confirm the predictive ability of the MAR model, we constructed a prognostic model and assessed its predictive accuracy. The MAR model revealed substantial differences in immune infiltration and tumor microenvironment characteristics between high- and low-risk populations and a substantial correlation between the risk scores and some common immunological checkpoints. AZD1332 and AZD7762 were more effective for patients in the low-risk group, whereas Entinostat, Nilotinib, Ruxolutinib, and Wnt.c59 were more effective for patients in the high-risk group. Knockdown of TYMS significantly inhibited the proliferation and invasive ability of ESCC cells in vitro. Overall, our MAR model provides stable and reliable results and may be used as a prognostic biomarker for personalized treatment of patients with ESCC.

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Identification and experimental validation of mitochondria-related genes biomarkers associated with immune infiltration for sepsis

Cited by 14 publications

References 54 publications

Analysis and experimental validation of necroptosis-related molecular classification, immune signature and feature genes in Alzheimer’s disease

Analysis and experimental validation of necroptosis-related molecular classification, immune signature and feature genes in Alzheimer’s disease

Machine learning-based B cell-related diagnostic biomarker signature and molecular subtypes characteristic of ulcerative colitis

Construction of a Novel Mitochondria-Associated Gene Model for Assessing ESCC Immune Microenvironment and Predicting Survival

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