Lin Jiayu, Liu Pengyi, Sun Keyan, Jiang Lingxi, Liu Yang, Huang Yishu, Liu Jia, Shi Minmin, Zhang Jun, Wang Ting, Shen Baiyong
Department of General Surgery, Pancreatic Disease Center, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
Shanghai Key Laboratory of Pancreatic Neoplasms Translational Medicine, Shanghai, China.
Cancer Cell Int. 2024 May 21;24(1):177. doi: 10.1186/s12935-024-03369-3.
Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest tumors worldwide, with extremely aggressive and complicated biology. Krüppel-like factors (KLFs) encode a series of transcriptional regulatory proteins and play crucial roles in a variety of processes, including tumor cell differentiation and proliferation. However, the potential biological functions and possible pathways of KLFs in the progression of PDAC remain elusive.
We systematically evaluated the transcriptional variations and expression patterns of KLFs in pancreatic cancer from the UCSC Xena. Based on difference analysis, the non-negative matrix factorization (NMF) algorithm was utilized to identify the immune characteristics and clinical significance of two different subtypes. The multivariate Cox regression was used to construct the risk model and then explore the differences in tumor immune microenvironment (TIME) and drug sensitivity between high and low groups. Through single-cell RNA sequencing (scRNA-seq) analysis, we screened KLF6 and further investigated its biological functions in pancreatic cancer and pan-cancer.
The KLFs exhibited differential expression and mutations in the transcriptomic profile of PDAC. According to the expression of KLFs, patients were classified into two distinct subtypes, each exhibiting significant differences in prognosis and TIME. Moreover, the KLF signature was developed using univariate Cox and Lasso regression, which proved to be a reliable and effective prognostic model. Furthermore, the KLF_Score was closely associated with immune infiltration, response to immunotherapy, and drug sensitivity and we screened small molecule compounds targeting prognostic genes separately. Through scRNA-seq analysis, KLF6 was selected to further demonstrate its role in the malignance of PC in vitro. Finally, pan-cancer analysis emphasized the biological significance of KLF6 in multiple types of tumors and its clinical utility in assessing cancer prognosis.
This study elucidated the pivotal role of KLF family genes in the malignant development of PC through comprehensive analysis and revealed that KLF6 would be a novel diagnostic biomolecule marker and potential therapeutic target for PDAC.
胰腺导管腺癌（PDAC）是全球最致命的肿瘤之一，具有极其侵袭性和复杂的生物学特性。Krüppel样因子（KLFs）编码一系列转录调节蛋白，在包括肿瘤细胞分化和增殖在内的多种过程中发挥关键作用。然而，KLFs在PDAC进展中的潜在生物学功能和可能途径仍不清楚。
我们从UCSC Xena系统评估了胰腺癌中KLFs的转录变化和表达模式。基于差异分析，利用非负矩阵分解（NMF）算法识别两种不同亚型的免疫特征和临床意义。采用多变量Cox回归构建风险模型，然后探讨高低分组之间肿瘤免疫微环境（TIME）和药物敏感性的差异。通过单细胞RNA测序（scRNA-seq）分析，我们筛选出KLF6，并进一步研究其在胰腺癌和泛癌中的生物学功能。
KLFs在PDAC的转录组图谱中表现出差异表达和突变。根据KLFs的表达，患者被分为两种不同的亚型，每种亚型在预后和TIME方面都表现出显著差异。此外，使用单变量Cox和Lasso回归建立了KLF特征，证明是一种可靠有效的预后模型。此外，KLF_Score与免疫浸润、免疫治疗反应和药物敏感性密切相关，我们分别筛选了靶向预后基因的小分子化合物。通过scRNA-seq分析，选择KLF6进一步证明其在体外PC恶性肿瘤中的作用。最后，泛癌分析强调了KLF6在多种肿瘤类型中的生物学意义及其在评估癌症预后中的临床应用。
本研究通过综合分析阐明了KLF家族基因在PC恶性发展中的关键作用，并揭示KLF6将是PDAC的一种新型诊断生物分子标志物和潜在治疗靶点。
