Guo Chunguang, Liu Zaoqu, Yu Yin, Liu Shirui, Ma Ke, Ge Xiaoyong, Xing Zhe, Lu Taoyuan, Weng Siyuan, Wang Libo, Liu Long, Hua Zhaohui, Han Xinwei, Li Zhen
Department of Endovascular Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Front Cell Dev Biol. 2022 Feb 25;10:816153. doi: 10.3389/fcell.2022.816153. eCollection 2022.
Recent evidence demonstrates that pyroptosis-derived long non-coding RNAs (lncRNAs) have profound impacts on the initiation, progression, and microenvironment of tumors. However, the roles of pyroptosis-derived lncRNAs (PDLs) in gastric cancer (GC) remain elusive. We comprehensively analyzed the multi-omics data of 839 GC patients from three independent cohorts. The previous gene set enrichment analysis embedding algorithm was utilized to identify PDLs. A gene pair pipeline was developed to facilitate clinical translation qualitative relative expression orders. The LASSO algorithm was used to construct and validate a pyroptosis-derived lncRNA pair prognostics signature (PLPPS). The associations between PLPPS and multi-omics alteration, immune profile, and pharmacological landscape were further investigated. A total of 350 PDLs and 61,075 PDL pairs in the training set were generated. Cox regression revealed 15 PDL pairs associated with overall survival, which were utilized to construct the PLPPS model the LASSO algorithm. The high-risk group demonstrated adverse prognosis relative to the low-risk group. Remarkably, genomic analysis suggested that the lower tumor mutation burden and gene mutation frequency (e.g., , , and ) were found in the high-risk group patients. The copy number variants were not significantly different between the two groups. Additionally, the high-risk group possessed lower immune cell infiltration abundance and might be resistant to a few chemotherapeutic drugs (including cisplatin, paclitaxel, and gemcitabine). PDLs were closely implicated in the biological process and prognosis of GC, and our PLPPS model could serve as a promising tool to advance prognostic management and personalized treatment of GC patients.
近期证据表明，焦亡衍生的长链非编码RNA（lncRNA）对肿瘤的发生、发展及微环境具有深远影响。然而，焦亡衍生的lncRNA（PDL）在胃癌（GC）中的作用仍不清楚。我们全面分析了来自三个独立队列的839例GC患者的多组学数据。利用先前的基因集富集分析嵌入算法来识别PDL。开发了一个基因对管道以促进临床转化——定性相对表达顺序。使用LASSO算法构建并验证焦亡衍生的lncRNA对预后特征（PLPPS）。进一步研究了PLPPS与多组学改变、免疫图谱和药理格局之间的关联。在训练集中共生成了350个PDL和61,075个PDL对。Cox回归显示15个与总生存相关的PDL对，利用这些对通过LASSO算法构建PLPPS模型。高风险组相对于低风险组显示出不良预后。值得注意的是，基因组分析表明，在高风险组患者中发现较低的肿瘤突变负担和基因突变频率（例如， 、 和 ）。两组之间的拷贝数变异无显著差异。此外，高风险组的免疫细胞浸润丰度较低，并且可能对几种化疗药物（包括顺铂、紫杉醇和吉西他滨）耐药。PDL与GC的生物学过程和预后密切相关，我们的PLPPS模型可作为推进GC患者预后管理和个性化治疗的有前景的工具。
