髓系细胞在生理上与先天免疫和炎症相关。肿瘤相关的骨髓细胞由于其在人类恶性肿瘤的肿瘤进展和抗癌免疫应答中的关键作用而获得了越来越多的兴趣。然而,肿瘤相关骨髓细胞相关基因与肝细胞癌之间的关联尚待揭示.这里,通过对公共肝癌样本的批量和单细胞RNA(scRNA)测序的整合分析,我们开发了一个基因标签来研究HCC特异性髓系标签基因在HCC患者中的作用.我们首先通过分析GEO数据集中HCC的scRNA数据,定义了317个骨髓细胞标记基因。选择差异表达的基因后,11个基因也被证明具有预后性。然后,我们从TCGA队列中构建了基因签名,并通过应用LASSOCox方法进一步验证了ICGC数据集。八个基因签名(FABP5,C15orf48,PABPC1,TUBA1B,最终获得AKR1C3、NQO1、AKR1B10、SPP1)。与低危组患者相比,高危组患者的肿瘤分期较高,生存率较低。风险评分被证明是预后的独立危险因素。高风险组的树突状细胞浸润较高,巨噬细胞和Tregs。APC共抑制,T细胞共抑制途径也被激活。此外,风险评分与多药耐药蛋白呈正相关。总之,我们的骨髓细胞标记基因相关的签名可以预测患者的生存,也可能表明免疫浸润和耐药性的水平。
Myeloid cells are physiologically related to innate immunity and inflammation. Tumor-associated myeloid cells gained increasing interest because of their critical roles in tumor progression and anticancer immune responses in human malignancies. However, the associations between tumor-associated myeloid cell-related genes and hepatocellular carcinoma have yet to be revealed. Here, through the integrating analysis of bulk and single-cell RNA (scRNA) sequencing of public HCC samples, we developed a gene signature to investigate the role of HCC-specific myeloid signature genes in HCC patients. We firstly defined 317 myeloid cell marker genes through analyzing scRNA data of HCC from the GEO dataset. After selecting the differentially expressed genes, eleven genes were also proved prognostic. Then we built a gene signature from the TCGA cohort and verified further with the ICGC dataset by applying the LASSO Cox method. An eight genes signature (FABP5, C15orf48, PABPC1, TUBA1B, AKR1C3, NQO1, AKR1B10, SPP1) was achieved finally. Patients in the high risk group correlated with higher tumor stages and poor survival than those in the low-risk group. The risk score was proved to be an independent risk factor for prognosis. The high risk group had higher infiltrations of dendritic cells, macrophages and Tregs. And the APC co-inhibition, T cell co-inhibition pathways were also activated. Besides, the risk score positively correlated with multidrug resistance proteins. In conclusion, our myeloid cell marker genes related signature can predict patients\' survival and may also indicate the levels of immune infiltration and drug resistance.