Xu Rong, Du Ashuai, Li Jianbo, Yang Qinglong
Department of Pathology, Changde Hospital, Xiangya School of Medicine, Central South University (The First People's Hospital of Changde City) Changde 415000, Hunan, China.
Department of Infectious Diseases, Guizhou Provincial People's Hospital Guiyang 550002, Guizhou, China.
Am J Cancer Res. 2024 Nov 15;14(11):5116-5132. doi: 10.62347/MJTA2660. eCollection 2024.
Acute myeloid leukemia (AML) is a malignant blood disorder and the most common type of acute leukemia in adults. Notwithstanding the plethora of therapeutic modalities, a significant cohort of patients fail to respond to treatment and experience relapse. Anoikis, a distinct modality of programmed cell death, has been linked to cancer progression. However, the prognostic significance of anoikis in AML remains unclear. In this study, a non-negative matrix factorization algorithm was utilized to efficiently reduce the dimensions of merged datasets. We used differential analysis, weighted gene co-expression network analysis (WGCNA), univariate Cox regression, and least absolute shrinkage and selection operator (LASSO) regression to identify genes associated with prognosis and develop a risk scoring model. Immunohistochemistry was conducted to assess the expression levels of key genes in clinical samples. The association between risk score and the tumor microenvironment (TME), stemness, clinical characteristics, and immunotherapy was evaluated. We identified 41 AML anoikis-related genes (ANRGs) related to survival, and seven genes were chosen to develop prognostic models. The prognostic risk score combined with the clinical and pathological features of AML was used to develop a nomogram, and decision curve analysis demonstrated the net clinical benefit of the model. Furthermore, analysis of ANRGs revealed that PDGFRB inhibition significantly reduced the proliferation of AML cells, promoted apoptosis, and inhibited AML progression both in vitro and in vivo, indicating that PDGFRB plays a crucial role in AML development.
急性髓系白血病（AML）是一种恶性血液疾病，也是成人中最常见的急性白血病类型。尽管有大量的治疗方式，但仍有相当一部分患者对治疗无反应并经历复发。失巢凋亡是一种独特的程序性细胞死亡方式，与癌症进展有关。然而，失巢凋亡在AML中的预后意义仍不清楚。在本研究中，我们利用非负矩阵分解算法有效地降低了合并数据集的维度。我们使用差异分析、加权基因共表达网络分析（WGCNA）、单变量Cox回归和最小绝对收缩和选择算子（LASSO）回归来识别与预后相关的基因并建立风险评分模型。通过免疫组织化学评估临床样本中关键基因的表达水平。评估了风险评分与肿瘤微环境（TME）、干性、临床特征和免疫治疗之间的关联。我们鉴定出41个与AML失巢凋亡相关的生存基因（ANRGs），并选择了7个基因来建立预后模型。将预后风险评分与AML的临床和病理特征相结合，绘制了列线图，决策曲线分析证明了该模型的净临床获益。此外，对ANRGs的分析表明，抑制血小板衍生生长因子受体B（PDGFRB）可显著降低AML细胞的增殖，促进细胞凋亡，并在体外和体内抑制AML进展，这表明PDGFRB在AML发展中起关键作用。
