The value of a metabolic and immune-related gene signature and adjuvant therapeutic response in pancreatic cancer
BackgroundPancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy characterized by a dismal prognosis. Treatment outcomes exhibit substantial variability across patients, underscoring the urgent need for robust predictive models to effectively estimate survival probabilities and th...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Genetics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2024.1475378/full |
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| author | Danlei Ni Jiayi Wu Jingjing Pan Yajing Liang Zihui Xu Zhiying Yan Kequn Xu Feifei Wei |
| author_facet | Danlei Ni Jiayi Wu Jingjing Pan Yajing Liang Zihui Xu Zhiying Yan Kequn Xu Feifei Wei |
| author_sort | Danlei Ni |
| collection | DOAJ |
| description | BackgroundPancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy characterized by a dismal prognosis. Treatment outcomes exhibit substantial variability across patients, underscoring the urgent need for robust predictive models to effectively estimate survival probabilities and therapeutic responses in PDAC.MethodsMetabolic and immune-related genes exhibiting differential expression were identified using the TCGA-PDAC and GTEx datasets. A genetic prognostic model was developed via univariable Cox regression analysis on a training cohort. Predictive accuracy was assessed using Kaplan-Meier (K-M) curves, calibration plots, and ROC curves. Additional analyses, including GSAE and immune cell infiltration studies, were conducted to explore relevant biological mechanisms and predict therapeutic efficacy.ResultsAn 8-gene prognostic model (AK2, CXCL11, TYK2, ANGPT4, IL20RA, MET, ENPP6, and CA12) was established. Three genes (AK2, ENPP6, and CA12) were associated with metabolism, while the others were immune-related. Most genes correlated with poor prognosis. Validation in TCGA-PDAC and GSE57495 datasets demonstrated robust performance, with AUC values for 1-, 3-, and 5-year OS exceeding 0.7. The model also effectively predicted responses to adjuvant therapy.ConclusionThis 8-gene signature enhances prognostic accuracy and therapeutic decision-making in PDAC, offering valuable insights for clinical applications and personalized treatment strategies. |
| format | Article |
| id | doaj-art-258ec8aed66942c683a842c59e22c4ff |
| institution | Kabale University |
| issn | 1664-8021 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Genetics |
| spelling | doaj-art-258ec8aed66942c683a842c59e22c4ff2025-01-23T16:31:22ZengFrontiers Media S.A.Frontiers in Genetics1664-80212025-01-011510.3389/fgene.2024.14753781475378The value of a metabolic and immune-related gene signature and adjuvant therapeutic response in pancreatic cancerDanlei NiJiayi WuJingjing PanYajing LiangZihui XuZhiying YanKequn XuFeifei WeiBackgroundPancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy characterized by a dismal prognosis. Treatment outcomes exhibit substantial variability across patients, underscoring the urgent need for robust predictive models to effectively estimate survival probabilities and therapeutic responses in PDAC.MethodsMetabolic and immune-related genes exhibiting differential expression were identified using the TCGA-PDAC and GTEx datasets. A genetic prognostic model was developed via univariable Cox regression analysis on a training cohort. Predictive accuracy was assessed using Kaplan-Meier (K-M) curves, calibration plots, and ROC curves. Additional analyses, including GSAE and immune cell infiltration studies, were conducted to explore relevant biological mechanisms and predict therapeutic efficacy.ResultsAn 8-gene prognostic model (AK2, CXCL11, TYK2, ANGPT4, IL20RA, MET, ENPP6, and CA12) was established. Three genes (AK2, ENPP6, and CA12) were associated with metabolism, while the others were immune-related. Most genes correlated with poor prognosis. Validation in TCGA-PDAC and GSE57495 datasets demonstrated robust performance, with AUC values for 1-, 3-, and 5-year OS exceeding 0.7. The model also effectively predicted responses to adjuvant therapy.ConclusionThis 8-gene signature enhances prognostic accuracy and therapeutic decision-making in PDAC, offering valuable insights for clinical applications and personalized treatment strategies.https://www.frontiersin.org/articles/10.3389/fgene.2024.1475378/fullmetabolism and immune-related genevaluePDACprognosisadjuvant therapy |
| spellingShingle | Danlei Ni Jiayi Wu Jingjing Pan Yajing Liang Zihui Xu Zhiying Yan Kequn Xu Feifei Wei The value of a metabolic and immune-related gene signature and adjuvant therapeutic response in pancreatic cancer Frontiers in Genetics metabolism and immune-related gene value PDAC prognosis adjuvant therapy |
| title | The value of a metabolic and immune-related gene signature and adjuvant therapeutic response in pancreatic cancer |
| title_full | The value of a metabolic and immune-related gene signature and adjuvant therapeutic response in pancreatic cancer |
| title_fullStr | The value of a metabolic and immune-related gene signature and adjuvant therapeutic response in pancreatic cancer |
| title_full_unstemmed | The value of a metabolic and immune-related gene signature and adjuvant therapeutic response in pancreatic cancer |
| title_short | The value of a metabolic and immune-related gene signature and adjuvant therapeutic response in pancreatic cancer |
| title_sort | value of a metabolic and immune related gene signature and adjuvant therapeutic response in pancreatic cancer |
| topic | metabolism and immune-related gene value PDAC prognosis adjuvant therapy |
| url | https://www.frontiersin.org/articles/10.3389/fgene.2024.1475378/full |
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