Prognostic and immune implications of a novel ferroptosis-related ten-gene signature in lung adenocarcinoma

Ma, Chi; Li, Feng; Luo, Huan

doi:10.21037/atm-20-7936

Cited by 17 publications

(18 citation statements)

References 67 publications

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“…ROC analysis was used to evaluate the diagnostic values of gene expression levels in cancer tissues. The diagnostic values were better when the area under the curve (AUC) was closer to 1 [ 11 , 15 ]. In LAC, the diagnostic values of oxidative stress-related DEGs (CCNA2, ERO1A, CDK1, PLK1, CDC25C, ITGB4, and GJB2) were investigated through the ROC analysis.…”

Section: Methodsmentioning

confidence: 99%

The Risk Model Based on the Three Oxidative Stress-Related Genes Evaluates the Prognosis of LAC Patients

Guo

Liu

et al. 2022

Oxidative Medicine and Cellular Longevity

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Background. Oxidative stress plays a role in carcinogenesis. This study explores the roles of oxidative stress-related genes (OSRGs) in lung adenocarcinoma (LAC). Besides, we construct a risk score model of OSRGs that evaluates the prognosis of LAC patients. Methods. OSRGs were downloaded from the Gene Set Enrichment Analysis (GSEA) website. The expression levels of OSRGs were confirmed in LAC tissues of the TCGA database. GO and KEGG analyses were used to evaluate the roles and mechanisms of oxidative stress-related differentially expressed genes (DEGs). Survival, ROC, Cox analysis, and AIC method were used to screen the prognostic DEGs in LAC patients. Subsequently, we constructed a risk score model of OSRGs and a nomogram. Further, this work investigated the values of the risk score model in LAC progression and the relationship between the risk score model and immune infiltration. Results. We discovered 163 oxidative stress-related DEGs in LAC, involving cellular response to oxidative stress and reactive oxygen species. Besides, the areas under the curve of CCNA2, CDC25C, ERO1A, CDK1, PLK1, ITGB4, and GJB2 were 0.970, 0.984, 0.984, 0.945, 0.984, 0.771, and 0.959, respectively. This indicates that these OSRGs have diagnosis values of LAC and are significantly related to the overall survival of LAC patients. ERO1A, CDC25C, and ITGB4 overexpressions were independent risk factors for the poor prognosis of LAC patients and were associated with risk scores in the risk model. High-risk score levels affected the poor prognosis of LAC patients. Notably, a high-risk score may be implicated in LAC progression via cell cycle, DNA replication, mismatch repair, and other mechanisms. Further, ERO1A, CDC25C, and ITGB4 expression levels were related to the immune infiltrating cells of LAC, including mast cells, NK cells, and CD8 T cells. Conclusion. In summary, ERO1A, CDC25C, and ITGB4 of OSRGs are associated with poor prognosis of LAC patients. We confirmed that the risk model based on the ERO1A, CDC25C, and ITGB4 is expected to assess the prognosis of LAC patients.

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Section: Methodsmentioning

confidence: 99%

The Risk Model Based on the Three Oxidative Stress-Related Genes Evaluates the Prognosis of LAC Patients

Guo

Liu

et al. 2022

Oxidative Medicine and Cellular Longevity

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“…Szymon Zmorzyński et al 117 showed that the changes in the activity of the GPX2 isoform might be associated with other cancers development. In another study, Chao Ma et al 118 reported that ALOX12B could predict lung adenocarcinoma accurately.…”

Section: Discussionmentioning

confidence: 95%

Drug repositioning in non-small cell lung cancer (NSCLC) using gene co-expression and drug–gene interaction networks analysis

MotieGhader

Tabrizi-Nezhadi

Paskeh

et al. 2022

Sci Rep

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Lung cancer is the most common cancer in men and women. This cancer is divided into two main types, namely non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC). Around 85 to 90 percent of lung cancers are NSCLC. Repositioning potent candidate drugs in NSCLC treatment is one of the important topics in cancer studies. Drug repositioning (DR) or drug repurposing is a method for identifying new therapeutic uses of existing drugs. The current study applies a computational drug repositioning method to identify candidate drugs to treat NSCLC patients. To this end, at first, the transcriptomics profile of NSCLC and healthy (control) samples was obtained from the GEO database with the accession number GSE21933. Then, the gene co-expression network was reconstructed for NSCLC samples using the WGCNA, and two significant purple and magenta gene modules were extracted. Next, a list of transcription factor genes that regulate purple and magenta modules' genes was extracted from the TRRUST V2.0 online database, and the TF–TG (transcription factors–target genes) network was drawn. Afterward, a list of drugs targeting TF–TG genes was obtained from the DGIdb V4.0 database, and two drug–gene interaction networks, including drug-TG and drug-TF, were drawn. After analyzing gene co-expression TF–TG, and drug–gene interaction networks, 16 drugs were selected as potent candidates for NSCLC treatment. Out of 16 selected drugs, nine drugs, namely Methotrexate, Olanzapine, Haloperidol, Fluorouracil, Nifedipine, Paclitaxel, Verapamil, Dexamethasone, and Docetaxel, were chosen from the drug-TG sub-network. In addition, nine drugs, including Cisplatin, Daunorubicin, Dexamethasone, Methotrexate, Hydrocortisone, Doxorubicin, Azacitidine, Vorinostat, and Doxorubicin Hydrochloride, were selected from the drug-TF sub-network. Methotrexate and Dexamethasone are common in drug-TG and drug-TF sub-networks. In conclusion, this study proposed 16 drugs as potent candidates for NSCLC treatment through analyzing gene co-expression, TF–TG, and drug–gene interaction networks.

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Section: Discussionmentioning

confidence: 99%

“…Dendritic cell is a professional antigen-presenting immune cell and contributes to a powerful anticancer immune response ( van der Hoorn et al, 2021 ). However, the dendritic cell function is often suppressed in patients with lung cancer ( Ma et al, 2021 ). Hence, some clinical trials are investigating neoantigen-targeted dendritic cell vaccines to promote antitumor immunity ( Stevens et al, 2020 ).…”

Section: Discussionmentioning

confidence: 99%

Development and Validation of a 7-Gene Inflammatory Signature Forecasts Prognosis and Diverse Immune Landscape in Lung Adenocarcinoma

Nai

et al. 2022

Front. Mol. Biosci.

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Background: Inflammatory responses are strongly linked with tumorigenesis and cancer development. This research aimed to construct and validate a novel inflammation response–related risk predictive signature for forecasting the prognosis of patients with LUAD.Methods: Differential expression analysis, univariate Cox, LASSO, and multivariate Cox regression analyses of 200 inflammatory response–related genes (IRRG) were performed to establish a risk predictive model in the TCGA training cohort. The performance of the IRRG model was verified in eight GEO datasets. GSEA analysis, ESTIMATE algorithms, and ssGSEA analysis were applied to elucidate the possible mechanisms. Furthermore, the relationship analysis between risk score, model genes, and chemosensitivity was performed. Last, we verified the protein expression of seven model genes by immunohistochemical staining or Western blotting.Results: We constructed a novel inflammatory response–related 7-gene signature (MMP14, BTG2, LAMP3, CCL20, TLR2, IL7R, and PCDH7). Patients in the high-risk group presented markedly decreased survival time in the TCGA cohort and eight GEO cohorts than the low-risk group. Interestingly, multiple pathways related to immune response were suppressed in high-risk groups. The low infiltration levels of B cell, dendritic cell, natural killer cell, and eosinophil can significantly affect the unsatisfactory prognosis of the high-risk group in LUAD. Moreover, the tumor cells’ sensitivity to anticancer drugs was markedly related to risk scores and model genes. The protein expression of seven model genes was consistent with the mRNA expression.Conclusion: Our IRRG prognostic model can effectively forecast LUAD prognosis and is tightly related to immune infiltration.

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Prognostic and immune implications of a novel ferroptosis-related ten-gene signature in lung adenocarcinoma

Cited by 17 publications

References 67 publications

The Risk Model Based on the Three Oxidative Stress-Related Genes Evaluates the Prognosis of LAC Patients

The Risk Model Based on the Three Oxidative Stress-Related Genes Evaluates the Prognosis of LAC Patients

Drug repositioning in non-small cell lung cancer (NSCLC) using gene co-expression and drug–gene interaction networks analysis

Development and Validation of a 7-Gene Inflammatory Signature Forecasts Prognosis and Diverse Immune Landscape in Lung Adenocarcinoma

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