胰腺癌缺氧和乳酸代谢相关的预后和治疗特征。

IF 2.9 4区 医学 Q3 ENDOCRINOLOGY & METABOLISM
Chen-Hui Zhang, An-Qi Huang, Cang-Chang Shi, Zhi-Jia Jiang, Hao Yao, Jin-Jin Sun
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引用次数: 0

摘要

背景:缺氧和乳酸代谢产物是胰腺癌(PC)肿瘤微环境的关键组成部分,影响肿瘤的侵袭、转移和治疗抵抗。本研究旨在探讨缺氧和乳酸代谢相关基因(HLRGs)在预测PC患者总生存和指导治疗中的作用。方法:通过TCGA、ICGC和GEO三种方法获取PC患者的基因表达和临床资料。正常胰腺组织数据来源于GTEx。对合并的TCGA-PAAD和GTEx队列进行差异表达分析,以鉴定差异表达基因(DEGs)。我们对从MsigDB数据库中获得的deg和HLRGs进行了交叉分析,以确定与PC缺氧和乳酸代谢相关的deg。在TCGA-PAAD队列中采用随机生存森林、Cox回归和LASSO分析建立预后模型。该模型在ICGC-PACA和GSE85916队列中进行了外部验证。进行风险分层,分析亚组间肿瘤突变负担、免疫微环境和药物反应的差异。RT-qPCR验证了关键基因的表达差异。结果:建立了基于HLRGs (SLC7A7、PYGL、HS3ST1、DDIT4、CYP27A1、ANKZF1、COL5A1)的预后模型。高危患者预后较差,肿瘤突变负担较高,抗pd - l1治疗反应较好,而低危患者免疫浸润较高,化疗敏感性增高。RT-qPCR证实,SLC7A7和COL5A1在PC中上调,ANKZF1下调。结论:我们开发了一种基于hlrgs的预后模型,可以预测总生存期并指导治疗策略,有助于精确治疗PC。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hypoxia- and lactate metabolism-associated prognostic and therapeutic signature in pancreatic cancer.

Background: Hypoxia and lactate metabolism products are critical components of the tumor microenvironment in pancreatic cancer (PC), influencing tumor invasiveness, metastasis, and treatment resistance. This study aims to explore the role of hypoxia- and lactate metabolism-related genes (HLRGs) in predicting overall survival and guiding treatment for PC patients.

Methods: Gene expression and clinical data from PC patients were obtained from TCGA, ICGC, and GEO. Normal pancreatic tissue data were sourced from GTEx. Differential expression analysis was performed on the merged TCGA-PAAD and GTEx cohorts to identify differentially expressed genes (DEGs). We performed an intersection analysis between the DEGs and the HLRGs obtained from the MsigDB database to identify the DEGs associated with hypoxia and lactate metabolism in PC. A prognostic model was developed using random survival forests, Cox regression, and LASSO analysis in the TCGA-PAAD cohort. The model was externally validated in the ICGC-PACA and GSE85916 cohorts. Risk stratification was performed, and the differences between subgroups in tumor mutational burden, immune microenvironment, and drug response were analyzed. RT-qPCR validated the key genes expression differences.

Results: A prognostic model based on HLRGs (SLC7A7, PYGL, HS3ST1, DDIT4, CYP27A1, ANKZF1, COL5A1) was established. High-risk patients exhibited worse prognosis, higher tumor mutational burden, and better response to anti-PD-L1 therapy, while low-risk patients exhibited higher immune infiltration and increased chemotherapy sensitivity. RT-qPCR confirmed that SLC7A7 and COL5A1 were upregulated, while ANKZF1 was downregulated in PC.

Conclusions: We developed an HLRGs-based prognostic model that predicts overall survival and guides treatment strategies, contributing to precision therapy in PC.

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来源期刊
Discover. Oncology
Discover. Oncology Medicine-Endocrinology, Diabetes and Metabolism
CiteScore
2.40
自引率
9.10%
发文量
122
审稿时长
5 weeks
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