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. 2022 Jan 27:13:806995.
doi: 10.3389/fphar.2022.806995. eCollection 2022.

Prognostic Implications of Pyroptosis-Related Gene Signatures in Lung Squamous Cell Carcinoma

Tingting Li  1 , Huanqing Liu  2 , Chunsheng Dong  3 , Jun Lyu  2
Affiliations

Prognostic Implications of Pyroptosis-Related Gene Signatures in Lung Squamous Cell Carcinoma

Tingting Li et al. Front Pharmacol. .

Abstract

Background: Lung squamous cell carcinoma (LUSC) has been a highly malignant tumor with very poor prognosis. It is confirmed that pyroptosis refers to the deaths of cells in a programmed and inflammatory manner. Nevertheless, the correlation between expression of genes related with pyroptosis and their prognosis remains uncertain in LUSC. Methods: Utilization of The Cancer Genome Atlas (TCGA) cohort has been done for evaluating the prognostics of pyroptosis-related genes for survival and constructing a signature with multiple genes. The least absolute shrinkage and selection operator (LASSO) Cox regression was performed for establishing such pyroptosis-related gene signature. Results: Eventually, identification of 28 genes in relation to pyroptosis was made in LUSC and healthy lung tissues. Upon the basis of these differentially-expressed genes (DEGs), the patients of LUSC can be divided into two subtypes. Nine gene signatures were established using LASSO. The surviving rate for low-risk group was apparently greater in contrast with the high-risk group (p < .001). According to our finding, risk score worked as an independent predictive factor of OS among LUSC sufferers in combination with clinical characteristics. In line with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, the enrichment of immunity-related genes and decreasing immunity status among the high-risk group. Conclusion: Genes in relation with pyroptosis played an essential role in tumor immunity, which is capable of predicting the prognosis for LUSCs.

Keywords: TCGA; immune microenvironment; lung squamous cell carcinoma; prognosis; pyroptosis.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Expression and interaction of DEGs. (A) Heatmap of DEGs amid normal tissue (N, bright blue) and tumor tissue (T, red) (green: low expression level; Red: high expression levels). **p < .01; ***p < .001. (B) PPI network showed the interaction of DEGs (interaction score = 0.4). (C) DEGs correlation network (red line: positively correlated; blue line: negatively correlated. The depth of the color gives a reflection on the strength of the correlation).
FIGURE 2
FIGURE 2
Tumor classification upon the basis of pyroptosis-related DEGs. (A) Total of 491 LUSC patients were clustered in line with the consensus clustering matrix (B) Heatmap and clinicopathological features of the two clusters according to these DEGs (StageⅠ, StageⅡ, StageⅢ and Stage Ⅳ are the degree of tumour differentiation). (C) Kaplan–Meier OS curves for the two clusters.
FIGURE 3
FIGURE 3
Establishment of risk signature in the TCGA cohort. (A) Univariate Cox regression analysis was carried out for the OS of all the pyroptosis-related genes, nine of which were p < .05 (B) LASSO performed regression analysis on nine OS-associated genes. (C) Patients distribution upon the basis of risk score (D) PCA plot for LUSC upon the basis of risk score. (E) Surviving state of all patients (low-risk population: dashed line left; High-risk group: right of dotted line). (F) Kaplan–Meier curves for the OS of patients in the high- and low-risk group (G) ROC curves manifested the prediction effect of the risk score.
FIGURE 4
FIGURE 4
Univariate and multivariate Cox regression analysis for the risk score. (A) Univariate analysis for the TCGA cohort (pathologic stage: the degree of tumour differentiation, Ⅰ to Ⅳ). (B) Multivariate analysis for the TCGA cohort. (C) Heatmap (green: low expression; red: high expression) to connect clinical pathologic characteristics with the risk groups.
FIGURE 5
FIGURE 5
Functional analysis of genes that differed amid the two risk groups in the TCGA cohort. (A) Bubble diagram of GO enrichment (the larger the bubble is, the greater number of genes are enriched; the deeper the red depth is, the obviously greater the difference is). (B) KEGG pathway Barplot (the longer the bar is, the greater number of genes are enriched, and the deeper the red is, the obviously greater the difference is).
FIGURE 6
FIGURE 6
Contrast of ssGSEA scores of immune cells with immune pathways. (A) Contrast was made of the enrichment scores for 16 immunity cells in the low (green box) group and the high risk (red box) group in the TCGA cohort. (B) Contrast of enrichment scores of 13 immune-associated pathways in low (blue box) and high risk (red box) groups in the TCGA cohort.
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References

    1. Abe J., Morrell C. (2016). Pyroptosis as a Regulated Form of Necrosis: PI+/Annexin V-/High Caspase 1/Low Caspase 9 Activity in Cells = Pyroptosis. Circ. Res. 118 (10), 1457–1460. 10.1161/CIRCRESAHA.116.308699 - DOI - PMC - PubMed
    1. Baker P. J., Boucher D., Bierschenk D., Tebartz C., Whitney P. G., D'Silva D. B., et al. (2015). NLRP3 Inflammasome Activation Downstream of Cytoplasmic LPS Recognition by Both Caspase-4 and Caspase-5. Eur. J. Immunol. 45 (10), 2918–2926. 10.1002/eji.201545655 - DOI - PubMed
    1. Corrales L., McWhirter S. M., Dubensky T. W., Jr, Gajewski T. F. (2016). The Host STING Pathway at the Interface of Cancer and Immunity. J. Clin. Invest. 126 (7), 2404–2411. 10.1172/JCI86892 - DOI - PMC - PubMed
    1. Correa R. G., Milutinovic S., Reed J. C. (2012). Roles of NOD1 (NLRC1) and NOD2 (NLRC2) in Innate Immunity and Inflammatory Diseases. Biosci. Rep. 32 (6), 597–608. 10.1042/BSR20120055 - DOI - PMC - PubMed
    1. Cotterchio M., Lowcock E., Bider-Canfield Z., Lemire M., Greenwood C., Gallinger S., et al. (2015). Association between Variants in Atopy-Related Immunologic Candidate Genes and Pancreatic Cancer Risk. PloS one 10 (5), e0125273. 10.1371/journal.pone.0125273 - DOI - PMC - PubMed

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