■胰腺癌(PC),其特点是其侵略性和低患者生存率,仍然是一个具有挑战性的恶性肿瘤。Anoikis,抑制转移性癌细胞扩散的过程,通过失巢凋亡相关基因与癌症进展和转移密切相关。尽管如此,这些基因在PC中的确切作用机制尚不清楚。
■研究数据来自癌症基因组图谱(TCGA)数据库,在基因表达综合(GEO)数据库中访问验证数据。进行差异表达分析和单变量Cox分析以确定与失巢凋亡相关的预后相关差异表达基因(DEGs)。然后采用无监督聚类分析对癌症样品进行分类。随后,对确定的DEGs进行了最小绝对收缩和选择算子(LASSO)Cox回归分析,以建立临床预后基因标签.使用此签名得出的风险评分,癌症患者被分为高风险和低风险组,通过生存分析进行进一步评估,免疫浸润分析,和突变分析。外部验证数据用于确认结果,Westernblot和免疫组织化学用于验证临床预后基因标记的风险基因。
■共获得20个与失巢凋亡相关的预后相关的DEGs。TCGA数据集揭示了两个不同的子组:簇1和簇2。利用20个DEG,构建了包含两个风险基因(CDKN3和LAMA3)的临床预后基因标签.胰腺腺癌(PAAD)患者根据其风险评分分为高风险和低风险组,后者表现出优越的存活率。在两组之间的免疫浸润和突变水平之间注意到统计学上的显着差异。验证队列结果与最初的发现一致。此外,实验验证证实了CDKN3和LAMA3在肿瘤样品中的高表达。
■我们的研究解决了在理解与失巢凋亡相关的基因在PAAD中的参与方面的差距。本文开发的临床预后基因标签准确地对PAAD患者进行分层,有助于为这些患者提供精准医疗。
UNASSIGNED: Pancreatic cancer (PC), characterized by its aggressive nature and low patient survival rate, remains a challenging malignancy. Anoikis, a process inhibiting the spread of metastatic cancer cells, is closely linked to cancer progression and metastasis through anoikis-related genes. Nonetheless, the precise mechanism of action of these genes in PC remains unclear.
UNASSIGNED: Study data were acquired from the Cancer Genome Atlas (TCGA) database, with validation data accessed at the Gene Expression Omnibus (GEO) database. Differential expression analysis and univariate Cox analysis were performed to determine prognostically relevant differentially expressed genes (DEGs) associated with anoikis. Unsupervised cluster analysis was then employed to categorize cancer samples. Subsequently, a least absolute shrinkage and selection operator (LASSO) Cox regression analysis was conducted on the identified DEGs to establish a clinical prognostic gene signature. Using risk scores derived from this signature, patients with cancer were stratified into high-risk and low-risk groups, with further assessment conducted via survival analysis, immune infiltration analysis, and mutation analysis. External validation data were employed to confirm the findings, and Western blot and immunohistochemistry were utilized to validate risk genes for the clinical prognostic gene signature.
UNASSIGNED: A total of 20 prognostic-related DEGs associated with anoikis were obtained. The TCGA dataset revealed two distinct subgroups: cluster 1 and cluster 2. Utilizing the 20 DEGs, a clinical prognostic gene signature comprising two risk genes (CDKN3 and LAMA3) was constructed. Patients with pancreatic adenocarcinoma (PAAD) were classified into high-risk and low-risk groups per their risk scores, with the latter exhibiting a superior survival rate. Statistically significant variation was noted across immune infiltration and mutation levels between the two groups. Validation cohort results were consistent with the initial findings. Additionally, experimental verification confirmed the high expression of CDKN3 and LAMA3 in tumor samples.
UNASSIGNED: Our study addresses the gap in understanding the involvement of genes linked to anoikis in PAAD. The clinical prognostic gene signature developed herein accurately stratifies patients with PAAD, contributing to the advancement of precision medicine for these patients.