Paraptosis-related classification and risk signature for prognosis prediction and immunotherapy assessment in gastric cancer
Abstract Background Gastric cancer (GC) poses a significant health threat due to its prevalence and poor prognosis. To improve outcomes, there is an urgent need for novel biomarkers. Paraptosis, a recently discovered form of programmed cell death, remains uninvestigated in GC, and understanding its...
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Springer
2025-06-01
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| Series: | Discover Oncology |
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| Online Access: | https://doi.org/10.1007/s12672-025-02996-0 |
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| author | Kai Zhou Ruyue Chen |
| author_facet | Kai Zhou Ruyue Chen |
| author_sort | Kai Zhou |
| collection | DOAJ |
| description | Abstract Background Gastric cancer (GC) poses a significant health threat due to its prevalence and poor prognosis. To improve outcomes, there is an urgent need for novel biomarkers. Paraptosis, a recently discovered form of programmed cell death, remains uninvestigated in GC, and understanding its mechanisms could offer new insights. Materials and methods In our study, we utilized the TCGA-STAD dataset as the training cohort and GSE84433 as the validation cohort to explore the association between paraptosis-related genes and the clinical risk of gastric cancer (GC). Our goals were to analyze the prognostic value and potential biological mechanisms of these genes. We conducted various analyses, including consistent clustering, differential gene expression analysis, enrichment analysis, and immune infiltration analysis. Ultimately, we developed a paraptosis-related risk signature (PRRS) to assess survival prognosis, drug sensitivity, and immune infiltration based on risk classification. The reliability of our findings was further verified through immunohistochemical staining. Results Our results revealed distinct subgroups (C1, C2, and C3) among gastric cancer patients through consensus clustering based on 65 paraptosis-related genes. These subgroups exhibited significant variations in survival rates, immunity scores, and immune cell infiltration. We then developed the Paraptosis-Related Risk Score (PRRS) using cox-lasso regression analysis, incorporating genes such as SLCO2A1, VCAN, RAMP1, and MANEAL. The PRRS effectively distinguished between high-risk and low-risk populations. Validation in an independent dataset and immunohistochemical staining confirmed the accuracy of the PRRS. These findings highlight the close relationship between paraptosis and the immune microenvironment of gastric cancer tumors, and demonstrate the PRRS’s robust performance in predicting patient survival. Conclusion This study underscores the link between paraptosis subtypes and changes in the gastric cancer immunotumour microenvironment. We developed and validated the Paraptosis-Related Risk Score (PRRS), which effectively predicts survival, immune infiltration, and drug sensitivity in gastric cancer patients. Our findings enhance the understanding of paraptosis and suggest potential new therapeutic strategies for gastric cancer. |
| format | Article |
| id | doaj-art-08bd4e50c8c84f20ad5ca0dbeae3672b |
| institution | Kabale University |
| issn | 2730-6011 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Springer |
| record_format | Article |
| series | Discover Oncology |
| spelling | doaj-art-08bd4e50c8c84f20ad5ca0dbeae3672b2025-08-20T03:47:14ZengSpringerDiscover Oncology2730-60112025-06-0116111610.1007/s12672-025-02996-0Paraptosis-related classification and risk signature for prognosis prediction and immunotherapy assessment in gastric cancerKai Zhou0Ruyue Chen1Department of Oncology, The Second Affiliated Hospital of Shandong First Medical UniversityQingdao Medical College, Qingdao UniversityAbstract Background Gastric cancer (GC) poses a significant health threat due to its prevalence and poor prognosis. To improve outcomes, there is an urgent need for novel biomarkers. Paraptosis, a recently discovered form of programmed cell death, remains uninvestigated in GC, and understanding its mechanisms could offer new insights. Materials and methods In our study, we utilized the TCGA-STAD dataset as the training cohort and GSE84433 as the validation cohort to explore the association between paraptosis-related genes and the clinical risk of gastric cancer (GC). Our goals were to analyze the prognostic value and potential biological mechanisms of these genes. We conducted various analyses, including consistent clustering, differential gene expression analysis, enrichment analysis, and immune infiltration analysis. Ultimately, we developed a paraptosis-related risk signature (PRRS) to assess survival prognosis, drug sensitivity, and immune infiltration based on risk classification. The reliability of our findings was further verified through immunohistochemical staining. Results Our results revealed distinct subgroups (C1, C2, and C3) among gastric cancer patients through consensus clustering based on 65 paraptosis-related genes. These subgroups exhibited significant variations in survival rates, immunity scores, and immune cell infiltration. We then developed the Paraptosis-Related Risk Score (PRRS) using cox-lasso regression analysis, incorporating genes such as SLCO2A1, VCAN, RAMP1, and MANEAL. The PRRS effectively distinguished between high-risk and low-risk populations. Validation in an independent dataset and immunohistochemical staining confirmed the accuracy of the PRRS. These findings highlight the close relationship between paraptosis and the immune microenvironment of gastric cancer tumors, and demonstrate the PRRS’s robust performance in predicting patient survival. Conclusion This study underscores the link between paraptosis subtypes and changes in the gastric cancer immunotumour microenvironment. We developed and validated the Paraptosis-Related Risk Score (PRRS), which effectively predicts survival, immune infiltration, and drug sensitivity in gastric cancer patients. Our findings enhance the understanding of paraptosis and suggest potential new therapeutic strategies for gastric cancer.https://doi.org/10.1007/s12672-025-02996-0ParaptosisGastric CancerClassificationImmunotherapyPrognosis |
| spellingShingle | Kai Zhou Ruyue Chen Paraptosis-related classification and risk signature for prognosis prediction and immunotherapy assessment in gastric cancer Discover Oncology Paraptosis Gastric Cancer Classification Immunotherapy Prognosis |
| title | Paraptosis-related classification and risk signature for prognosis prediction and immunotherapy assessment in gastric cancer |
| title_full | Paraptosis-related classification and risk signature for prognosis prediction and immunotherapy assessment in gastric cancer |
| title_fullStr | Paraptosis-related classification and risk signature for prognosis prediction and immunotherapy assessment in gastric cancer |
| title_full_unstemmed | Paraptosis-related classification and risk signature for prognosis prediction and immunotherapy assessment in gastric cancer |
| title_short | Paraptosis-related classification and risk signature for prognosis prediction and immunotherapy assessment in gastric cancer |
| title_sort | paraptosis related classification and risk signature for prognosis prediction and immunotherapy assessment in gastric cancer |
| topic | Paraptosis Gastric Cancer Classification Immunotherapy Prognosis |
| url | https://doi.org/10.1007/s12672-025-02996-0 |
| work_keys_str_mv | AT kaizhou paraptosisrelatedclassificationandrisksignatureforprognosispredictionandimmunotherapyassessmentingastriccancer AT ruyuechen paraptosisrelatedclassificationandrisksignatureforprognosispredictionandimmunotherapyassessmentingastriccancer |