A novel prognostic signature and immune microenvironment characteristics associated with disulfidptosis in papillary thyroid carcinoma based on single-cell RNA sequencing

Abstract

Background: Disulfidptosis is a newly discovered form of regulated cell death. The research on disulfidptosis and tumor progression remains unclear. Our research aims to explore the relationship between disulfidptosis-related genes (DRGs) and the clinical outcomes of papillary thyroid carcinoma (PTC), and its interaction on the tumor microenvironment.Methods: The single-cell RNA seq data of PTC was collected from GEO dataset GSE191288. We illustrated the expression patterns of disulfidptosis-related genes in different cellular components in thyroid cancer. LASSO analyses were performed to construct a disulfidptosis associated risk model in TCGA-THCA database. GO and KEGG analyses were used for functional analyses. CIBERSORT and ESTIMATE algorithm helped with the immune infiltration estimation. qRT‒PCR and flow cytometry was performed to validate the hub gene expression and immune infiltration in clinical samples.Results: We clustered PTC scRNA seq data into 8 annotated cell types. With further DRGs based scoring analyses, we found endothelial cells exhibited the most relationship with disulfidptosis. A 4-gene risk model was established based on the expression pattern of DRGs related endothelial cell subset. The risk model showed good independent prognostic value in both training and validation dataset. Functional enrichment and genomic feature analysis exhibited the significant correlation between tumor immune infiltration and the signature. The results of flow cytometry and immune infiltration estimation showed the higher risk scores was related to immuno-suppressive tumor microenvironment in PTC.Conclusion: Our study exhibited the role of disulfidptosis based signature in the regulation of tumor immune microenvironment and the survival of PTC patients. A 4-gene prognostic signature (including SNAI1, STC1, PKHD1L1 and ANKRD37) was built on the basis of disulfidptosis related endothelial cells. The significance of clinical outcome and immune infiltration pattern was validated robustly.

A disulfidptosis-related lncRNAs cluster to forecast the prognosis and immune landscapes of ovarian cancer

“…The study utilized the CIBERSORT algorithm to analyze the composition of tumor-infiltrating immune cells and compare the differences in immune cell proportions between high-risk and low-risk groups ( Newman et al, 2015 ). Additionally, the ESTIMATE algorithm was employed to assess differences in immune, stromal, and tumor purity scores between the two risk groups ( Liao et al, 2023 ). Single-Sample Gene Set Enrichment Analysis (ssGSEA) in the GSVA R package was used to quantify the infiltration levels and functions of 28 immune cell types based on established gene signatures ( Hänzelmann et al, 2013 ; Xia et al, 2023 ).…”

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“…The study utilized the CIBERSORT algorithm to analyze the composition of tumor-infiltrating immune cells and compare the differences in immune cell proportions between high-risk and lowrisk groups (Newman et al, 2015). Additionally, the ESTIMATE algorithm was employed to assess differences in immune, stromal, and tumor purity scores between the two risk groups (Liao et al, 2023). Single-Sample Gene Set Enrichment Analysis (ssGSEA) in the GSVA R package was used to quantify the infiltration levels and functions of 28 immune cell types based on established gene signatures (Hänzelmann et al, 2013;Xia et al, 2023).…”