Immunis.AI, Royal Oak, MI 48067, USA.
Infinia ML, Duke University, Durham, NC 27708, USA.
Cells. 2021 Sep 28;10(10):2567. doi: 10.3390/cells10102567.
The primary objective of this study is to detect biomarkers and develop models that enable the identification of clinically significant prostate cancer and to understand the biologic implications of the genes involved. Peripheral blood samples (1018 patients) were split chronologically into independent training ( = 713) and validation ( = 305) sets. Whole transcriptome RNA sequencing was performed on isolated phagocytic CD14+ and non-phagocytic CD2+ cells and their gene expression levels were used to develop predictive models that correlate to adverse pathologic features. The immune-transcriptomic model with the highest performance for predicting adverse pathology, based on a subtraction of the log-transformed expression signals of the two cell types, displayed an area under the curve (AUC) of the receiver operating characteristic of 0.70. The addition of biomarkers in combination with traditional clinical risk factors (age, serum prostate-specific antigen (PSA), PSA density, race, digital rectal examination (DRE), and family history) enhanced the AUC to 0.91 and 0.83 for the training and validation sets, respectively. The markers identified by this approach uncovered specific pathway associations relevant to (prostate) cancer biology. Increased phagocytic activity in conjunction with cancer-associated (mis-)regulation is also represented by these markers. Differential gene expression of circulating immune cells gives insight into the cellular immune response to early tumor development and immune surveillance.
本研究的主要目的是检测生物标志物并建立模型,以识别临床上有意义的前列腺癌,并了解相关基因的生物学意义。外周血样本(1018 例患者)按时间顺序分为独立的训练集(=713)和验证集(=305)。对分离的吞噬性 CD14+和非吞噬性 CD2+细胞进行全转录组 RNA 测序,并利用其基因表达水平建立预测模型,以关联不良病理特征。基于两种细胞类型的对数转换表达信号相减,该免疫转录组模型在预测不良病理方面表现出最高的性能,其受试者工作特征曲线下面积(AUC)为 0.70。将生物标志物与传统临床危险因素(年龄、血清前列腺特异性抗原(PSA)、PSA 密度、种族、直肠指检(DRE)和家族史)相结合进行添加,可将训练集和验证集的 AUC 分别提高到 0.91 和 0.83。该方法识别的标志物揭示了与(前列腺)癌症生物学相关的特定途径关联。这些标志物还代表了吞噬活性的增加以及与癌症相关的(错误)调节。循环免疫细胞的差异基因表达可深入了解细胞免疫对早期肿瘤发展和免疫监视的反应。