CELL INTELLIGENCE · 肿瘤细胞治疗研究
肿瘤细胞治疗研究
英文原题：Identification and experimental validation of a tumor-infiltrating lymphocytes-related long noncoding RNA signature for prognosis of clear cell renal cell carcinoma.
Identification and experimental validation of a tumor-infiltrating lymphocytes-related long noncoding RNA signature for prognosis of clear cell renal cell carcinoma.
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透明细胞肾细胞癌（ccRCC）是泌尿系统中常见的侵袭性恶性肿瘤。鉴于肿瘤微环境的异质性，免疫治疗在晚期患者中可能无法充分发挥作用。长链非编码RNA（lncRNA）已被报道与TIL（肿瘤浸润淋巴细胞）（TILs）的分化和成熟密切相关，而TILs具有对抗肿瘤细胞的作用。
在本研究中，我们基于癌症基因组图谱（TCGA）数据库，通过Pearson相关分析、单因素Cox回归、Lasso回归和多因素Cox回归，鉴定了10个与TIL相关的lncRNA（AL590094.1、LINC02027、LINC00460、AC147651.1、AC026401.3、LINC00944、LINC01615、AP000439.2、AL162586.1和AC084876.1）。基于这些lncRNA建立了风险评分模型。接下来，构建了列线图以预测总生存期。通过利用高、低风险评分组之间的差异表达基因（DEGs），进行了基因本体论（GO）富集分析，以鉴定与免疫DEGs相关的主要生物学过程（BP）。
我们分析了各组的突变数据，并证明SETD2和BAP1在高风险组中具有最高的突变频率。使用“CIBERSORT”R包检测各组中TILs的丰度。比较了淋巴细胞标志物的表达。
我们还检测了ccRCC患者肾组织中两个lncRNA（AC084876.1和AC026401.3）的表达及其与淋巴细胞标志物的关系，结果显示AC084876.1与FoxP3之间存在正相关。AC084876.1下调的ccRCC细胞系的增殖、迁移和侵袭受到抑制，PD-L1和TGF-分泌的表达降低。据我们所知，这是首个利用 TIL 相关 lncRNA 建立 ccRCC 预后模型的生物信息学研究。这些 lncRNA 与 T 细胞活性相关，可能作为疾病预后的生物标志物。
Clear cell renal cell carcinoma (ccRCC) is a common aggressive malignant tumor of the urinary system. Given the heterogeneity of the tumor microenvironment, immunotherapy may not fully exert its role in the treatment of advanced patients. Long noncoding RNA (lncRNA) has been reported to be critically associated with the differentiation and maturation of tumor-infiltrating lymphocytes (TILs), which work against tumor cells. In this study, we identified 10 TIL-related lncRNAs (AL590094. 1, LINC02027, LINC00460, AC147651. 1, AC026401.
3, LINC00944, LINC01615, AP000439. 2, AL162586. 1, and AC084876. 1) by Pearson correlation, univariate Cox regression, Lasso regression, and multivariate Cox regression based on The Cancer Genome Atlas (TCGA) database. A risk score model was established based on these lncRNAs.
Next, a nomogram was constructed to predict the overall survival. By employing differentially expressed genes (DEGs) between groups with high and low risk scores, gene ontology (GO) enrichment analysis was performed to identify the major biological processes (BP) related to immune DEGs.
We analyzed the mutation data of the groups and demonstrated that SETD2 and BAP1 had the highest mutation frequency in the high-risk group. The "CIBERSORT" R package was used to detect the abundance of TILs in the groups. The expression of lymphocyte markers was compared.
We also determined the expression of two lncRNAs (AC084876. 1 and AC026401. 3) and their relationship with lymphocyte markers in the kidney tissue of ccRCC patients and showed that there was a positive correlation between AC084876. 1 and FoxP3. Proliferation, migration, and invasion of AC084876.
1-downregulated ccRCC cell lines were inhibited, and the expression of PD-L1 and TGF- secretion decreased. To our knowledge, this is the first bioinformatics study to establish a prognostic model for ccRCC using TIL-related lncRNAs. These lncRNAs were associated with T-cell activities and may serve as biomarkers of disease prognosis.
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