Prognostic Significance of Disulfidptosis-Related Gene DSTN in Kidney Renal Clear Cell Carcinoma: Correlation with Immune Cell Infiltration and Cancer Stemness
Abstract Backgrounds Kidney renal clear cell carcinoma (KIRC) is a highly metastatic cancer that shows resistance to traditional chemoradiotherapy. Disulfidptosis, a newly discovered mechanism of cell death in malignancies, involves the accumulation of intracellular disulfides, leading to rapid cell demise. Identifying disulfidptosis-related genes (DRGs) in KIRC can provide novel treatment strategies for patients with this disease. Methods The 15 DRGs and differentially expressed genes (DEGs) obtained from the KIRC-TCGA database were intersected to identify overlapping genes, and a prognostic model was constructed using Lasso regression analysis. Univariate and multivariate Cox regression analysis were conducted to identify independent prognostic factors associated with disulfidptosis. Kaplan-Meier (KM) survival curve was used for prognostic analysis. Co-expression analysis was performed between the screened DRGs and other DRGs to investigate their correlation. The samples in KIRC-TCGA were grouped based on the selected DRGs, and Gene Set Enrichment Analysis (GSEA) as well as immune infiltration analysis were performed. Tumor stemness analysis was conducted using the OCLR algorithm, and correlation analysis between the independent prognostic DRGs and the inhibitory concentration 50% (IC50) of Pazopanib and Sorafenib was performed using ridge regression. Results Univariate and multivariate regression analysis indicated that DSTN and FLNA may serve as independent prognostic DRGs for KIRC. In the KIRC-TCGA, FLNA expression was higher in tumor tissues compared with adjacent tissues, whereas DSTN expression was lower in tumor tissues than in adjacent tissues (P < 0.05). KM survival curve demonstrated that high expression of DSTN and FLNA correlated with a higher survival rate. Co-expression analysis revealed positive correlations between DSTN and the expression of FLNA, MYH9, TLN1, MYL6, MYH10, IQGAP1, and CD2AP. Immune infiltration analysis showed that DSTN was positively correlated with endothelial cell infiltration. High expression of DSTN and endothelial cell marker genes were associated with a longer survival period. Correlation analysis revealed a negative correlation between DSTN expression and stemness scores. Additionally, the IC50 values of Pazopanib and Sorafenib showed a high negative correlation with DSTN expression (0.5≤|ρSpearman|<0.8). Conclusions DSTN, as a DRG, had been identified as an independent prognostic biomarker in patients with KIRC. Its expression was closely linked to tumor cell stemness and also correlated with the IC50 of commonly used chemotherapy drugs in KIRC. DSTN holded promise as a meaningful prognostic marker and potential therapeutic target for KIRC..
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Preprint| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
ResearchSquare.com - (2024) vom: 28. März Zur Gesamtaufnahme - year:2024 |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
Shangguan, Zuifei [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| doi: |
10.21203/rs.3.rs-3908062/v1 |
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| PPN (Katalog-ID): |
XRA042608260 |
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| 245 | 1 | 0 | |a Prognostic Significance of Disulfidptosis-Related Gene DSTN in Kidney Renal Clear Cell Carcinoma: Correlation with Immune Cell Infiltration and Cancer Stemness |
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| 520 | |a Abstract Backgrounds Kidney renal clear cell carcinoma (KIRC) is a highly metastatic cancer that shows resistance to traditional chemoradiotherapy. Disulfidptosis, a newly discovered mechanism of cell death in malignancies, involves the accumulation of intracellular disulfides, leading to rapid cell demise. Identifying disulfidptosis-related genes (DRGs) in KIRC can provide novel treatment strategies for patients with this disease. Methods The 15 DRGs and differentially expressed genes (DEGs) obtained from the KIRC-TCGA database were intersected to identify overlapping genes, and a prognostic model was constructed using Lasso regression analysis. Univariate and multivariate Cox regression analysis were conducted to identify independent prognostic factors associated with disulfidptosis. Kaplan-Meier (KM) survival curve was used for prognostic analysis. Co-expression analysis was performed between the screened DRGs and other DRGs to investigate their correlation. The samples in KIRC-TCGA were grouped based on the selected DRGs, and Gene Set Enrichment Analysis (GSEA) as well as immune infiltration analysis were performed. Tumor stemness analysis was conducted using the OCLR algorithm, and correlation analysis between the independent prognostic DRGs and the inhibitory concentration 50% (IC50) of Pazopanib and Sorafenib was performed using ridge regression. Results Univariate and multivariate regression analysis indicated that DSTN and FLNA may serve as independent prognostic DRGs for KIRC. In the KIRC-TCGA, FLNA expression was higher in tumor tissues compared with adjacent tissues, whereas DSTN expression was lower in tumor tissues than in adjacent tissues (P < 0.05). KM survival curve demonstrated that high expression of DSTN and FLNA correlated with a higher survival rate. Co-expression analysis revealed positive correlations between DSTN and the expression of FLNA, MYH9, TLN1, MYL6, MYH10, IQGAP1, and CD2AP. Immune infiltration analysis showed that DSTN was positively correlated with endothelial cell infiltration. High expression of DSTN and endothelial cell marker genes were associated with a longer survival period. Correlation analysis revealed a negative correlation between DSTN expression and stemness scores. Additionally, the IC50 values of Pazopanib and Sorafenib showed a high negative correlation with DSTN expression (0.5≤|ρSpearman|<0.8). Conclusions DSTN, as a DRG, had been identified as an independent prognostic biomarker in patients with KIRC. Its expression was closely linked to tumor cell stemness and also correlated with the IC50 of commonly used chemotherapy drugs in KIRC. DSTN holded promise as a meaningful prognostic marker and potential therapeutic target for KIRC. | ||
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| 700 | 1 | |a Shi, Na |4 aut | |
| 700 | 1 | |a Ying, Xue |4 aut | |
| 700 | 1 | |a Chen, Tingting |4 aut | |
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