Increasing evidence highlights the clinical significance of stromal cells and immune cells in the liver cancer microenvironment. However, reliable prognostic models have not been well established. This study aimed to develop a gene signature for liver cancer based on stromal and immune scores. Using the estimation of stromal and immune cells in malignant tumor tissues using expression data (ESTIMATE) algorithm, stromal and immune scores were estimated based on the transcriptome profile of The Cancer Genome Atlas (TCGA) liver cancer cohort. Stromal-/immune-related differentially expressed genes were identified, followed by functional enrichment analysis. The Cox regression model was used to select prognostic genes and construct a gene signature. Its predictive potential was evaluated by receiver operating characteristic (ROC). The correlation between the risk score and immune cell infiltration was analyzed using Tumor Immune Estimation Resource (TIMER). Three hundred sixty-four upregulated and 10 downregulated stromal-/immune-related genes were identified, were mainly enriched in immune-related processes and pathways. Through univariate and multivariate cox survival analysis, a five-gene risk score was constructed, composed of FABP3, HTRA3, OLFML2B, PDZD4 and SLAMF6. Patients with high score indicated a poorer prognosis than those with low risk score. The areas under the ROC curves of overall survival (OS), progression-free interval, 3-, 5-year, OS status were 0.68, 0.57, 0.72, 0.74 and 0.728, indicating its well performance on predicting patients' prognoses. Furthermore, the risk score and the five genes were significantly correlated with immune cell infiltration in the tumor microenvironment. In this study, we proposed a prognostic five-gene signature based on stromal/immune scores in the liver cancer microenvironment.

中文翻译：

---

在肿瘤微环境中基于基质/免疫评分的五基因签名及其对肝癌的临床意义。

越来越多的证据突出了肝癌微环境中基质细胞和免疫细胞的临床意义。但是，尚未建立可靠的预后模型。这项研究的目的是根据基质和免疫评分结果开发肝癌的基因标记。使用表达数据（ESTIMATE）算法估算恶性肿瘤组织中的基质细胞和免疫细胞，根据癌症基因组图谱（TCGA）肝癌队列的转录组图谱估算基质和免疫评分。鉴定基质/免疫相关的差异表达基因，然后进行功能富集分析。使用Cox回归模型选择预后基因并构建基因标记。通过接收器工作特性（ROC）评估了其预测潜力。使用肿瘤免疫估计资源（TIMER）分析了风险评分和免疫细胞浸润之间的相关性。鉴定到了364个与基质/免疫相关的基因上调和10个下调，这些基因主要集中在免疫相关的过程和途径中。通过单因素和多因素cox生存分析，建立了由FABP3，HTRA3，OLFML2B，PDZD4和SLAMF6组成的五基因风险评分。高分患者的预后较低风险患者低。总生存（OS），无进展间隔，3年，5年，OS状态的ROC曲线下面积分别为0.68、0.57、0.72、0.74和0.728，表明其在预测患者预后方面表现良好。此外，肿瘤微环境中的风险评分和五个基因与免疫细胞浸润显着相关。在这项研究中，我们基于肝癌微环境中的基质/免疫评分提出了预后的五基因签名。