HUMAN MUTATION
·
2025
·Vol. 2025
·期 1
·5319444
·
IF 3.7
Xin Wu,Linde Sun,Peifa Liu,Qiong Wang,Yu Wang
Background PANoptosis, as an inflammatory programmed cell death, is involved in tumor development. This study set out to discover novel PANoptosis-correlated prognostic signatures in stomach adenocarcinoma (STAD), a prevalent malignancy of the digestive system. Methods STAD samples were derived from a public database, and PANoptosis-related genes (PRGs) were acquired from existing reports. Prognosis-related PRGs were screened by univariate Cox regression analysis. Molecular subtypes of STAD were identified by the “ConsensusClusterPlus” package. The “Limma” package was employed to filter differentially expressed genes (DEGs) between different subtypes. PANoptosis-related prognostic signatures in STAD were identified to establish the RiskScore model. The RiskScore and some of the clinical features were integrated to establish a nomogram. Immune cell infiltration and TIDE score in different risk groups were compared. Correlation between immune checkpoint genes, drug sensitivity, and RiskScore was analyzed by the Spearman method. The biological function of PANoptosis-related signature genes in STAD was preliminarily explored by in vitro cell experiments. Results Based on 18 prognosis-related PRGs, two molecular subtypes of STAD were recognized, and the C1 subtype showed a lower overall survival (OS) rate than the C2 subtype. Further, three PANoptosis-related signature genes ( APOD , GPC3 , and SERPINE1 ) were determined to establish a RiskScore model that could accurately assess the prognostic outcomes for STAD patients. Then, by integrating RiskScore with clinical features, a nomogram was established. The high-risk group had higher immune cell infiltration and TIDE score and lower OS rate than those with a low risk. RiskScore was positively correlated with nine immune checkpoint genes. Besides, we screened 23 drugs that significantly correlated with RiskScore. In vitro cell experiments showed that the mRNA and protein levels of APOD , GPC3 , and SERPINE1 were upregulated in the STAD cell line and that APOD knockout significantly reduced cancer cell proliferation, migration, and invasion levels and increased the apoptotic capacity of the STAD cell line. Conclusion This study established a PANoptosis-related RiskScore model for assessing STAD patient prognosis, which could contribute to the personalized treatment of STAD.
研究领域:
肿瘤学
·
分子生物学
·
生物信息学
·
免疫治疗
·
精准医学
✓ 已验证
DOI
PubMed
高影响因子
Scientific Reports
·
2025
·Vol. 15
·期 1
·1-18
·
IF 3.9
Su Rishun,Chen Jia,Dai Chen,Yin Songcheng,Chen Haoming,Sun Xuezeng,Fang Zhaoxin,Zhang Changhua,Chen Jingyao,Gu Liang
G2/M checkpoint and P53 pathway are essential in regulating the cell cycle and proliferation of cells, which is related to the progress of tumors. Here, we carried out an integrative analysis of the prognostic genes of these pathways in gastric cancer (GC) and thus developed a molecular subtype. We identified prognostic differential expression genes (PDEGs) of G2/M checkpoint and P53 pathways between normal and tumor tissue in TCGA-STAD and developed a molecular subtype based on PDEGs. Meanwhile, the clinical significance of the molecular subtype was further explored. In addition, a comprehensive model and nomogram based on PDEGs score were constructed and validated by GSE26901 and GSE13861. Gastric cancer cell lines and patients’ specimens were used to validate the expression of selected genes.19 PDEGs were identified from these pathways in TCGA-STAD. Ulteriorly, a PDEGs score model consisting of 4 genes (PVT1, F2R, INCENP, IRAK1) was generated to classify patients into high- and low- PDEGs score subgroups. Patients in low PDEGs score groups had a better prognosis and a higher tumor mutational burden and may be more sensitive to chemotherapy and immunotherapy. Notably, the combination of PDEGs score and clinical features showed a pleasing survival prediction ability. In the GSE13861 cohort, the PDEGs score and its derivative model were confirmed with significant predictive effects in overall survival. Furthermore, these genes were significantly upregulated in both GC cell lines and tumor tissues and F2R was the hub gene resulting in poor survival. This paper has provided a distinct insight for tumor classification predicting prognosis more accurately and having the potential to instruct the use of chemotherapy and immunotherapy for patients with GC.
研究领域:
癌症研究
·
分子生物学
·
生物信息学
·
基因组学
·
肿瘤学
·
计算生物学
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医学遗传学
✓ 已验证
产品关联
DOI
PubMed
高影响因子
Heliyon
·
2024
·
IF 3.4
Zhihao Zhang,Feng Liu,Xin Lan,Fuhai Wang,Jiahao Sun,Honglong Wei
Objective This study explores the impact of pyroptosis-related genes (PRG) on the prognosis of liver cancer (LC). Methods 421 samples (371 tumor samples and 50 normal samples) from the Cancer Genome Atlas (TCGA) were included in this study. GSE14520 dataset (data of RNA expression and relevant clinicopathological features), GSE125449 dataset (single-cell data in LC) and HCCDB18 dataset (validation on the reliability of the model) were downloaded as appropriate. Download the PRG and its corresponding pathway information from the gene set enrichment analysis (GSEA) website. The consensus clustering was performed by ConsensusClusterPlus package. Differentially expressed genes (DEGs) were identified using limma package, and prognostic features were constructed using un/multivariate and Lasso Cox regression. Pathway enrichment analysis was conducted by ssGSEA method. Receiver Operating Characteristic and the survival analysis were conducted by timeROC and Survminer packages. The Seurat package was used for single-cell RNA sequencing (scRNA-seq) analysis. For cellular validation, following the quantification on the key genes via reverse-transcription quantitative PCR, the Transwell and scratch assays were applied to evaluate the in-vitro invasion and migration of LC cells Huh-7. Results 12 prognosis-related genes were identified to be related to the progression of LC. Three subtypes including C1, C2 and C3 were categorized using the 12 prognosis-related genes and PRGs significantly related to the prognosis of LC patients. The worst and best prognosis was seen in C3 subtype and C2 subtype, respectively. Hallmark pathway enrichment analysis has shown the concurrent immunoactivation and immune escape in C3 subtype. A RiskScore model was constructed using 8 key genes (KPNA2, UCK2, FTCD, CBX2, RAB32, HMMR, S100A9 and ANXA10) from the DEGs of three subtypes. The RiskScore system as an independent prognostic factor dividing the patients into high and low risk groups, and patients of the high-risk group had poor prognosis in both test set and validation set. A nomogram model combining the risk score had the extreme higher benefit. Further, 6 subclusters were identified from scRNA-seq analysis, where the highest PYROPTOSIS score was seen in Monocytic-Macrophages. The quantification on the key genes has suggested the high expressions of KPNA2, UCK2, CBX2, RAB32, HMMR and S100A9 and the low expressions of FTCD and ANXA10 in LC cells Huh-7. Particularly, UCK2 knockdown evidently diminished the number of invaded and migrated LC cells in vitro . Conclusion The risk model associated with pyproptosis is crucial for the tumor immunity of LC and may serve as a prognostic indicator for patients suffering from LC. Our findings will offer new perspectives for immunotherapies targeting LC.
研究领域:
肿瘤学
·
分子生物学
·
生物信息学
·
癌症基因组学
·
细胞免疫学
✓ 已验证
产品关联
DOI
PubMed
高影响因子
危险品化学品经营许可证（带存储）