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Comprehensive integration of single-cell RNA and transcriptome RNA sequencing to establish a pyroptosis-related signature for improving prognostic prediction of gastric cancer

转录组 上睑下垂 肿瘤科 癌症 癌症研究 医学 生物 计算生物学 内科学 炎症体 基因 基因表达 受体 生物化学
作者
Jie Li,Yu Tian,Juan Sun,Mingwei Ma,Zicheng Zheng,Weiming Kang,Xin Ye
出处
期刊:Computational and structural biotechnology journal [Elsevier BV]
卷期号:23: 990-1004 被引量:1
标识
DOI:10.1016/j.csbj.2024.02.002
摘要

Cell pyroptosis, a Gasdermin-dependent programmed cell death characterized by inflammasome, plays a complex and dynamic role in Gastric cancer (GC), a serious threat to human health. Therefore, the value of pyroptosis-related genes (PRGs) as prognostic biomarkers and therapeutic indicators for patients needs to be exploited in GC. This study integrates single-cell RNA sequencing (scRNA-seq) dataset GSE183904 with GC transcriptome data from the TCGA database, focusing on the expression and distribution of PRGs in GC at the single-cell level. The prognostic signature of PRGs was established by using Cox and LASSO analyses. The differences in long-term prognosis, immune infiltration, mutation profile, CD274 and response to chemotherapeutic drugs between the two groups were analyzed and evaluated. A tissue array was used to verify the expression of six PRGs, CD274, CD163 and FoxP3. C12orf75, VCAN, RGS2, MKNK2, SOCS3 and TNFAIP2 were successfully screened out to establish a signature to potently predict the survival time of GC patients. A webserver (https://pumc.shinyapps.io/GastricCancer/) for prognostic prediction in GC patients was developed based on this signature. High-risk score patients typically had worse prognoses, resistance to classical chemotherapy, and a more immunosuppressive tumor microenvironment. VCAN, TNFAIP2 and SOCS3 were greatly elevated in the GC while RGS2 and MKNK2 were decreased in the tumor samples. Further, VCAN was positively related to the infiltrations of Tregs and M2 TAMs in GC TME and the CD274 in tumor cells. In summary, a potent pyroptosis-related signature was established to accurately forecast the survival time and treatment responsiveness of GC patients.

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