白细胞群体的变化可能会混淆癌症患者血液中与疾病相关的 miRNA 信号。我们的目标是开发一种方法来检测肺癌全血样本中差异表达的 miRNA，且不受白细胞比例变化的影响。 Ref-miREO 方法通过比较健康白细胞亚型和肺癌血液样本中 miRNA 的样本内相对表达顺序 (REO)，识别不受白细胞群体变化影响的差异 miRNA。在肺癌和健康血液样本之间观察到的差异 miRNA 中，超过 77% 与骨髓源性白细胞和淋巴源性白细胞之间的差异 miRNA 重叠，这表明白细胞群体的变化对 miRNA 谱的潜在影响。 Ref-miREO 鉴定了 16 个差异 miRNA，这些 miRNA 靶向先前与白细胞相关的 19 个肺腺癌相关基因。这些 miRNA 在癌症相关通路中表现出富集，并显示出作为诊断生物标志物的巨大潜力，LASSO 回归模型可以有效区分健康和肺癌血液或血清样本（所有 AUC > 0.85）。此外，其中 12 个 miRNA 表现出显着的预后相关性。 Ref-miREO 方法为不受白细胞群体变化影响的癌症循环生物标志物检测提供了有价值的候选方法。

Changes in leukocyte populations may confound the disease-associated miRNA signals in the blood of cancer patients. We aimed to develop a method to detect differentially expressed miRNAs from lung cancer whole blood samples that are not influenced by variations in leukocyte proportions. The Ref-miREO method identifies differential miRNAs unaffected by changes in leukocyte populations by comparing the within-sample relative expression orderings (REOs) of miRNAs from healthy leukocyte subtypes and those from lung cancer blood samples. Over 77% of the differential miRNAs observed between lung cancer and healthy blood samples overlapped with those between myeloid-derived and lymphoid-derived leukocytes, suggesting the potential impact of changes in leukocyte populations on miRNA profile. Ref-miREO identified 16 differential miRNAs that target 19 lung adenocarcinoma-related genes previously linked to leukocytes. These miRNAs showed enrichment in cancer-related pathways and demonstrated high potential as diagnostic biomarkers, with the LASSO regression models effectively distinguishing between healthy and lung cancer blood or serum samples (all AUC > 0.85). Additionally, 12 of these miRNAs exhibited significant prognostic correlations. The Ref-miREO method offers valuable candidates for circulating biomarker detection in cancer that are not affected by changes in leukocyte populations.