Predictive Biomarkers and Molecular Subtypes in DLBCL: Insights from PCD Gene Expression and Machine Learning

The data consists of gene expression profiles from five DLBCL patient cohorts (GSE132929, GSE43677, GSE156309, GSE190847, and GSE12453) and 18 programmed cell death (PCD)-related genes. The data include results from consensus clustering that divided the patients into two subgroups (C1 and C2), with C2 representing a higher-risk group. The dataset also includes immune infiltration data, gene set variation analysis (GSVA) of relevant pathways, and predictive models built using 12 different machine learning algorithms. Validation through transcriptome sequencing of DLBCL cell lines and normal B-lymphocyte cell lines was also conducted.

本数据集包含来自5个弥漫性大B细胞淋巴瘤（diffuse large B-cell lymphoma, DLBCL）患者队列（GSE132929、GSE43677、GSE156309、GSE190847及GSE12453）的基因表达谱，以及18个程序性细胞死亡（programmed cell death, PCD）相关基因。数据集包含通过一致性聚类将患者划分为两个亚组（C1与C2）的分析结果，其中C2为高风险亚组。本数据集还涵盖免疫浸润数据、相关通路的基因集变异分析（gene set variation analysis, GSVA）结果，以及基于12种不同机器学习算法构建的预测模型。此外，通过弥漫性大B细胞淋巴瘤细胞系与正常B淋巴细胞系的转录组测序完成的验证数据亦已纳入本数据集。