Fan Yang, Na Jiang, Xiao-Yu Li, Xing-Si Qi, Zi-Bin Tian, Ying-Jie Guo
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This study aims to develop a prognostic model based on key hypoxia-related molecules to enhance prediction accuracy for patient outcomes and to guide more effective treatment strategies in pancreatic cancer.</p><p><strong>Aim: </strong>To develop and validate a prognostic model for predicting outcomes in patients with pancreatic cancer using key hypoxia-related molecules.</p><p><strong>Methods: </strong>This pancreatic cancer prognostic model was developed based on the expression levels of the hypoxia-associated genes <i>CAPN2</i>, <i>PLAU</i>, and <i>CCNA2</i>. The results were validated in an independent dataset. This study also examined the correlations between the model risk score and various clinical features, components of the immune microenvironment, chemotherapeutic drug sensitivity, and metabolism-related pathways. Real-time quantitative PCR verification was conducted to confirm the differential expression of the target genes in hypoxic and normal pancreatic cancer cell lines.</p><p><strong>Results: </strong>The prognostic model demonstrated significant predictive value, with the risk score showing a strong correlation with clinical features: It was significantly associated with tumor grade (G) (<sup>b</sup> <i>P</i> < 0.01), moderately associated with tumor stage (T) (<sup>a</sup> <i>P</i> < 0.05), and significantly correlated with residual tumor (R) status (<sup>b</sup> <i>P</i> < 0.01). There was also a significant negative correlation between the risk score and the half-maximal inhibitory concentration of some chemotherapeutic drugs. Furthermore, the risk score was linked to the enrichment of metabolism-related pathways in pancreatic cancer.</p><p><strong>Conclusion: </strong>The prognostic model based on hypoxia-related genes effectively predicts pancreatic cancer outcomes with improved accuracy over traditional factors and can guide treatment selection based on risk assessment.</p>","PeriodicalId":23778,"journal":{"name":"World Journal of Gastroenterology","volume":"30 36","pages":"4057-4070"},"PeriodicalIF":4.3000,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11439118/pdf/","citationCount":"0","resultStr":"{\"title\":\"Construction and validation of a pancreatic cancer prognostic model based on genes related to the hypoxic tumor microenvironment.\",\"authors\":\"Fan Yang, Na Jiang, Xiao-Yu Li, Xing-Si Qi, Zi-Bin Tian, Ying-Jie Guo\",\"doi\":\"10.3748/wjg.v30.i36.4057\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Pancreatic cancer is one of the most lethal malignancies, characterized by poor prognosis and low survival rates. Traditional prognostic factors for pancreatic cancer offer inadequate predictive accuracy, often failing to capture the complexity of the disease. The hypoxic tumor microenvironment has been recognized as a significant factor influencing cancer progression and resistance to treatment. This study aims to develop a prognostic model based on key hypoxia-related molecules to enhance prediction accuracy for patient outcomes and to guide more effective treatment strategies in pancreatic cancer.</p><p><strong>Aim: </strong>To develop and validate a prognostic model for predicting outcomes in patients with pancreatic cancer using key hypoxia-related molecules.</p><p><strong>Methods: </strong>This pancreatic cancer prognostic model was developed based on the expression levels of the hypoxia-associated genes <i>CAPN2</i>, <i>PLAU</i>, and <i>CCNA2</i>. The results were validated in an independent dataset. This study also examined the correlations between the model risk score and various clinical features, components of the immune microenvironment, chemotherapeutic drug sensitivity, and metabolism-related pathways. Real-time quantitative PCR verification was conducted to confirm the differential expression of the target genes in hypoxic and normal pancreatic cancer cell lines.</p><p><strong>Results: </strong>The prognostic model demonstrated significant predictive value, with the risk score showing a strong correlation with clinical features: It was significantly associated with tumor grade (G) (<sup>b</sup> <i>P</i> < 0.01), moderately associated with tumor stage (T) (<sup>a</sup> <i>P</i> < 0.05), and significantly correlated with residual tumor (R) status (<sup>b</sup> <i>P</i> < 0.01). There was also a significant negative correlation between the risk score and the half-maximal inhibitory concentration of some chemotherapeutic drugs. 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引用次数: 0
摘要
背景:胰腺癌是最致命的恶性肿瘤之一,其特点是预后差、生存率低。传统的胰腺癌预后因素预测准确性不足,往往不能反映疾病的复杂性。缺氧的肿瘤微环境已被认为是影响癌症进展和耐药性的重要因素。本研究旨在开发一种基于关键缺氧相关分子的预后模型,以提高对患者预后的预测准确性,并指导胰腺癌患者采用更有效的治疗策略:该胰腺癌预后模型是根据缺氧相关基因CAPN2、PLAU和CCNA2的表达水平建立的。研究结果在一个独立数据集中得到了验证。本研究还考察了模型风险评分与各种临床特征、免疫微环境成分、化疗药物敏感性和代谢相关通路之间的相关性。研究还进行了实时定量 PCR 验证,以确认缺氧和正常胰腺癌细胞系中靶基因的差异表达:预后模型具有显著的预测价值,风险评分与临床特征密切相关:它与肿瘤分级(G)明显相关(b P < 0.01),与肿瘤分期(T)中度相关(a P < 0.05),与残留肿瘤(R)状态明显相关(b P < 0.01)。风险评分与某些化疗药物的半数最大抑制浓度之间也存在明显的负相关。此外,风险评分还与胰腺癌代谢相关通路的富集有关:结论:与传统因素相比,基于缺氧相关基因的预后模型能有效预测胰腺癌的预后,并能根据风险评估指导治疗选择。
Construction and validation of a pancreatic cancer prognostic model based on genes related to the hypoxic tumor microenvironment.
Background: Pancreatic cancer is one of the most lethal malignancies, characterized by poor prognosis and low survival rates. Traditional prognostic factors for pancreatic cancer offer inadequate predictive accuracy, often failing to capture the complexity of the disease. The hypoxic tumor microenvironment has been recognized as a significant factor influencing cancer progression and resistance to treatment. This study aims to develop a prognostic model based on key hypoxia-related molecules to enhance prediction accuracy for patient outcomes and to guide more effective treatment strategies in pancreatic cancer.
Aim: To develop and validate a prognostic model for predicting outcomes in patients with pancreatic cancer using key hypoxia-related molecules.
Methods: This pancreatic cancer prognostic model was developed based on the expression levels of the hypoxia-associated genes CAPN2, PLAU, and CCNA2. The results were validated in an independent dataset. This study also examined the correlations between the model risk score and various clinical features, components of the immune microenvironment, chemotherapeutic drug sensitivity, and metabolism-related pathways. Real-time quantitative PCR verification was conducted to confirm the differential expression of the target genes in hypoxic and normal pancreatic cancer cell lines.
Results: The prognostic model demonstrated significant predictive value, with the risk score showing a strong correlation with clinical features: It was significantly associated with tumor grade (G) (bP < 0.01), moderately associated with tumor stage (T) (aP < 0.05), and significantly correlated with residual tumor (R) status (bP < 0.01). There was also a significant negative correlation between the risk score and the half-maximal inhibitory concentration of some chemotherapeutic drugs. Furthermore, the risk score was linked to the enrichment of metabolism-related pathways in pancreatic cancer.
Conclusion: The prognostic model based on hypoxia-related genes effectively predicts pancreatic cancer outcomes with improved accuracy over traditional factors and can guide treatment selection based on risk assessment.
期刊介绍:
The primary aims of the WJG are to improve diagnostic, therapeutic and preventive modalities and the skills of clinicians and to guide clinical practice in gastroenterology and hepatology.