REDE：用于九大队列和三种癌症的差异表达可重复性及诊断迁移的定量框架
REDE: A Quantitative Framework for Differential-Expression Reproducibility and Diagnostic Transfer Across Nine Cohorts and Three Cancers
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中文总结 AI 辅助
本研究针对三种癌症的九大队列，提出REDE定量框架及REDE-2Fold程序，评估差异表达可重复性，发现紧凑基因集的诊断性能高但操作点不稳定，定义了相关证据层级。
中文摘要 AI 辅助
差异表达分析常将队列特异性的显著性转化为稳定基因特征或诊断生物标志物的结论。本研究评估了哪些证据层级可在独立数据集间重复，以及由发现阶段衍生的基因集是否能保持肿瘤与非肿瘤的锁定分类性能。研究将九个公共微阵列队列组织成固定的发现集、验证集和外部测试集，涉及胰腺导管腺癌、乳腺癌和肺癌。对差异表达基因（DEG）负担、精确成员身份、排名前位重叠、符号效应、预设基因确认及Hallmark通路的可重复性进行了评估。还引入了REDE-2Fold：每个发现队列在患者层面拆分一次，在两个拆分组中独立进行差异表达分析，仅保留在两个拆分组中均为同向的基因。随后评估了四个仅用于训练的基因集及对应的锁定逻辑模型和阈值：所有发现阶段的DEG、排名前19的发现阶段DEG、所有REDE-2Fold基因、排名前19的REDE-2Fold基因。在两个独立队列中，DEG列表的广泛确认率为15.5%至39.5%，大效应的确认率升至50.1%至84.3%；通路复制率为52.2%至88.9%。紧凑的19基因集保留了较高的外部ROC-AUC，但锁定的操作点常不稳定：部分ROC-AUC接近1.0的模型显示零特异性或极低敏感性。这些结果定义了从阈值化成员身份到效应、通路、区分度及操作点迁移的层级。REDE提供了一个七级定量框架，用于将转录组学结论与实际测试的证据匹配；而REDE-2Fold提供了一种最小内部特征稳定性程序，可强化但不替代独立验证。
英文摘要
Differential-expression analyses often turn cohort-specific significance into claims of stable gene signatures or diagnostic biomarkers. We evaluated which layers of evidence reproduce across independent datasets and whether discovery-derived panels retain locked tumor-versus-non-tumor classification performance. Nine public microarray cohorts were organized into fixed discovery, validation, and external-test experiments for pancreatic ductal adenocarcinoma, breast cancer, and lung cancer. Reproducibility was assessed for DEG burden, exact membership, top-rank overlap, signed effects, prespecified gene confirmation, and Hallmark pathways. We also introduced REDE-2Fold, in which each discovery cohort is split once at patient level, differential expression is performed independently in both folds, and only same-direction genes selected in both are retained. Four training-only panels were then evaluated with locked logistic models and thresholds: all discovery DEGs, the top 19 discovery DEGs, all REDE-2Fold genes, and the top 19 REDE-2Fold genes. Broad DEG-list confirmation in both independent cohorts ranged from 15.5% to 39.5%, rising to 50.1% to 84.3% for large effects. Pathway replication ranged from 52.2% to 88.9%. Compact 19-gene panels retained high external ROC-AUC, but locked operating points were often unstable: some models with ROC-AUC near 1.0 showed zero specificity or very low sensitivity. These results define a hierarchy from thresholded membership through effect, pathway, discrimination, and operating-point transfer. REDE provides a seven-level quantitative framework for matching transcriptomic claims to the evidence actually tested, while REDE-2Fold offers a minimum internal feature-stability procedure that strengthens but does not replace independent validation.
