[Retracted] Identification of Hub Genes for Early Diagnosis and Predicting Prognosis in Colon Adenocarcinoma

Xu, Shuo; Liu, Dingsheng; Cui, Mingming; Zhang, Yao; Zhang, Yu; Guo, Shiwei; Zhang, Hong

doi:10.1155/2022/1893351

Cited by 5 publications

(5 citation statements)

References 80 publications

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“…There have been some CRC hub gene studies based on bioinformatics analyses, but very few studies targeting mitophagy ( 33 , 34 ). The role of mitophagy in inflammation, immunity, and tumor progression has gained widespread attention from researchers.…”

Section: Discussionmentioning

confidence: 99%

Identification and validation of mitophagy-related signatures as a novel prognostic model for colorectal cancer

Ke,

Wang,

Deng

et al. 2024

Transl Cancer Res

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Background Colorectal cancer (CRC) is one of the most commonly diagnosed cancers in the world. Mitophagy is associated with tumorigenesis and development of malignancy. However, the specific role of mitophagy has yet not been systematically explored in CRC. Methods The RNA-sequencing dataset of CRC from The Cancer Genome Atlas (TCGA) and microarray data of gene expression profiles of CRC from Gene Expression Omnibus (GEO) were downloaded. Mitophagy-related gene sets were obtained from the Pathway Unification database. The package “limma” was used for differential gene expression analysis. Kaplan-Meier (KM) survival analyses were utilized to evaluate the prognostic value of the mitophagy regulators. Single-sample gene set enrichment analysis (ssGSEA) was used to estimate the infiltrating immune cells and the activity of immune response. The ConsensusClusterPlus algorithm was used to determine mitophagy-related subtypes. Principal component analysis (PCA) was used to create composite measurement of mitophagy scores. The R packages “survminer” and “ReGlot” were used to plot the nomogram and calibration curves. Results Integrated analysis of the GEO and TCGA databases revealed some common differentially expressed genes (DEGs) in CRC. MFN2 , UBB , PINK1 , and PRKN were significantly downregulated in CRC samples as compared to normal samples, and other genes were significantly upregulated in CRC samples. KM survival analyses showed that high expression of ATG12 and MAP1LC3B predicted a poor prognosis, whereas high expression of TOMM22 and TOMM40 predicted a better prognosis. Mitophagy showed significant correlation with immune-related pathways in CRC samples. We identified 2 distinct CRC subtypes with different mitophagy accumulation, of which subtype B had better prognosis and immune activity. The mitophagy score may be employed as a new and efficient clinical predictor in conjunction with other clinical indicators to predict the prognosis of CRC patients. Conclusions We systematically investigated the CRC heterogeneity with reference to mitophagy based on bioinformatics analyses, and the findings of this study might provide some guidance for future research into potential biomarkers for diagnosis and prognosis prediction of CRC patients.

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Section: Discussionmentioning

confidence: 99%

Identification and validation of mitophagy-related signatures as a novel prognostic model for colorectal cancer

Ke,

Wang,

Deng

et al. 2024

Transl Cancer Res

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“…The “pROC” and “ggplot2” packages of R language were used to analyze and visualize the hub gene's ROC curve and compare the hub gene's diagnostic efficiency in patients with AUVP ( 26 ). The area value (AUC) under the ROC curve is 0.5–1.…”

Section: Methodsmentioning

confidence: 99%

Identification of hub genes and pathophysiological mechanism related to acute unilateral vestibulopathy by integrated bioinformatics analysis

Cheng

Zheng²,

Yu³

et al. 2022

Front. Neurol.

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BackgroundAlthough many pathological mechanisms and etiological hypotheses of acute unilateral vestibulopathy (AUVP) have been reported, but the actual etiology remains to be elucidated.ObjectiveThis study was based on comprehensive bioinformatics to identify the critical genes of AUVP and explore its pathological mechanism.MethodsGene expression profiles of AUVP and normal samples were collected from GSE146230 datasets of the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was constructed, and the WGCNA R-package extracted significant modules. The limma R-package was applied to identify differentially expressed genes (DEGs). The common genes of practical modules and DEGs were screened for GO and KEGG pathways analysis. The protein–protein interaction (PPI) layout and hub genes validation was created by Cytoscape software using the link from the STRING database. The functions of hub genes were predicted through the CTD (comparative genetics database).ResultsA total of 332 common genes were screened from practical modules and DEGs. Functional enrichment analysis revealed that these genes were predominantly associated with inflammation and infection. After construction of PPI, expressions of hub genes, and drawing ROC curves, LILRB2, FPR1, AQP9, and LILRA1 are highly expressed in AUVP (p < 0.05) and have a certain diagnostic efficacy for AUVP (AUC > 0.7), so they were selected as hub genes. The functions of hub genes suggested that the occurrence of AUVP may be related to inflammation, necrosis, hepatomegaly, and other conditions in CTD.ConclusionLILRB2, FPR1, AQP9, and LILRA1 may play essential roles in developing AUVP, providing new ideas for diagnosing and treating AUVP.

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“…Hub genes in the network tend to cluster densely and represent the likely control points of the study condition 6 , 7 . Studies have established that hub genes can serve as diagnostic, predictive, or prognostic biomarkers in colon adenocarcinoma 8 . In bovines, hub genes involved in mastitis development 9 , intramuscular fat content of Nellore cattle 10 and in vivo pre-implantation development 11 are identified.…”

Section: Introductionmentioning

confidence: 99%

Identification of hub genes and their expression profiling for predicting buffalo (Bubalus bubalis) semen quality and fertility

Swathi,

Ramya,

Archana

et al. 2023

Sci Rep

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Sperm transcriptomics provide insights into subtle differences in sperm fertilization competence. For predicting the success of complex traits like male fertility, identification of hub genes involved in various sperm functions are essential. The bulls from the transcriptome profiled samples (n = 21), were grouped into good and poor progressive motility (PM), acrosome integrity (AI), functional membrane integrity (FMI) and fertility rate (FR) groups. The up-regulated genes identified in each group were 87, 470, 1715 and 36, respectively. Gene networks were constructed using up- and down-regulated genes from each group. The top clusters from the upregulated gene networks of the PM, AI, FMI and FR groups were involved in tyrosine kinase (FDR = 1.61E−11), apoptosis (FDR = 1.65E−8), translation (FDR = 2.2E−16) and ribosomal pathway (FDR = 1.98E−21), respectively. From the clusters, the hub genes were identified and validated in a fresh set of semen samples (n = 12) using RT-qPCR. Importantly, the genes (fold change) RPL36AL (14.99) in AI, EIF5A (54.32) in FMI, and RPLP0 (8.55) and RPS28 (13.42) in FR were significantly (p < 0.05) up-regulated. The study suggests that the expression levels of MAPK3 (PM), RPL36AL + RPS27A or RPL36AL + EXT2 (AI), RPL36AL or RPS27A (FMI) and RPS18 + RPS28 (FR) are potential markers for diagnosing the semen quality and fertility status of bulls which can be used for the breeding program.

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[Retracted] Identification of Hub Genes for Early Diagnosis and Predicting Prognosis in Colon Adenocarcinoma

Cited by 5 publications

References 80 publications

Identification and validation of mitophagy-related signatures as a novel prognostic model for colorectal cancer

Identification and validation of mitophagy-related signatures as a novel prognostic model for colorectal cancer

Identification of hub genes and pathophysiological mechanism related to acute unilateral vestibulopathy by integrated bioinformatics analysis

Identification of hub genes and their expression profiling for predicting buffalo (Bubalus bubalis) semen quality and fertility

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