Ji Hongchen, Zhang Qiong, Wang Xiang-Xu, Li Junjie, Wang Xiaowen, Pan Wei, Zhang Zhuochao, Ma Ben, Zhang Hong-Mei
Department of Oncology, Xijing Hospital, Fourth Military Medical University, No. 127 West Changle Road, Xi'an, 710032, China.
Faculty of Hepatopancreatobiliary Surgery, Chinese PLA General Hospital, No. 28 Fuxing Road, Beijing, China.
Discov Oncol. 2022 Aug 25;13(1):83. doi: 10.1007/s12672-022-00532-y.
Pancreatic cancer is one of the deadliest cancers worldwide. The extracellular matrix (ECM) microenvironment affects the drug sensitivity and prognosis of pancreatic cancer patients. This study constructed an 8-genes pancreatic ECM scoring (PECMS) model, to classify the ECM features of pancreatic cancer, analyze the impact of ECM features on survival and drug sensitivity, and mine key molecules that influence ECM features in pancreatic cancer.
GSVA score calculation and clustering were performed in TCGA-PAAD patients. Lasso regression was used to construct the PECMS model. The association between PECMS and patient survival was analyzed and validated in the CPTAC-3 dataset of TCGA and our single-center retrospective cohort. The relationships between PECMS and features of the matrix microenvironment were analyzed. Finally, PECMS feature genes were screened and verified in pancreatic cancer specimens to select key genes associated with the ECM microenvironment.
The survival of the PECMS-high group was significantly worse. The PECMS-high group showed higher oxidative stress levels, lower levels of antigen presentation- and MHC-I molecule-related pathways, and less immune effector cell infiltration. Data from IMvigor-210 cohort suggested that PECMS-low group patients were more sensitive to immune checkpoint blockers. The PECMS score was negatively correlated with chemotherapy drug sensitivity. The negative association of PECMS with survival and drug sensitivity was validated in our retrospective cohort. KLHL32 expression predicted lower oxidative stress level and more immune cells infiltrate in pancreatic cancer.
PECMS is an effective predictor of prognosis and drug sensitivity in pancreatic cancer patients. KLHL32 may play an important role in the construction of ECM, and the mechanism is worth further study.
胰腺癌是全球最致命的癌症之一。细胞外基质（ECM）微环境影响胰腺癌患者的药物敏感性和预后。本研究构建了一个8基因的胰腺ECM评分（PECMS）模型，以分类胰腺癌的ECM特征，分析ECM特征对生存和药物敏感性的影响，并挖掘影响胰腺癌ECM特征的关键分子。
对TCGA-PAAD患者进行基因集变异分析（GSVA）评分计算和聚类。采用套索回归构建PECMS模型。在TCGA的CPTAC-3数据集和我们的单中心回顾性队列中分析并验证PECMS与患者生存之间的关联。分析PECMS与基质微环境特征之间的关系。最后，在胰腺癌标本中筛选并验证PECMS特征基因，以选择与ECM微环境相关的关键基因。
PECMS高分组的生存情况明显更差。PECMS高分组显示出更高的氧化应激水平、更低的抗原呈递和MHC-I分子相关途径水平以及更少的免疫效应细胞浸润。来自IMvigor-210队列的数据表明，PECMS低分组患者对免疫检查点阻断剂更敏感。PECMS评分与化疗药物敏感性呈负相关。PECMS与生存和药物敏感性的负相关在我们的回顾性队列中得到了验证。KLHL32表达预测胰腺癌中氧化应激水平较低且免疫细胞浸润较多。
PECMS是胰腺癌患者预后和药物敏感性的有效预测指标。KLHL32可能在ECM构建中发挥重要作用，其机制值得进一步研究。
