Cao Lichao, Chen Fang, Xu Long, Zeng Jian, Wang Yun, Zhang Shenrui, Ba Ying, Zhang Hezi
Shenzhen Nucleus Gene Technology Co., Ltd., Shenzhen, Guangdong, China.
Shenzhen Nucleus Huaxi Medical Laboratory, Shenzhen, Guangdong, China.
Front Immunol. 2024 Sep 2;15:1450135. doi: 10.3389/fimmu.2024.1450135. eCollection 2024.
Cellular senescence (CS) is believed to be a major factor in the evolution of cancer. However, CS-related lncRNAs (CSRLs) involved in colon cancer regulation are not fully understood. Our goal was to create a novel CSRLs prognostic model for predicting prognosis and immunotherapy and exploring its potential molecular function in colon cancer.
The mRNA sequencing data and relevant clinical information of GDC TCGA Colon Cancer (TCGA-COAD) were obtained from UCSC Xena platform, and CS-associated genes was acquired from the CellAge website. Pearson correlation analysis was used to identify CSRLs. Then we used Kaplan-Meier survival curve analysis and univariate Cox analysis to acquire prognostic CSRL. Next, we created a CSRLs prognostic model using LASSO and multivariate Cox analysis, and evaluated its prognostic power by Kaplan-Meier and ROC curve analysis. Besides, we explored the difference in tumor microenvironment, somatic mutation, immunotherapy, and drug sensitivity between high-risk and low-risk groups. Finally, we verified the functions of MYOSLID in cell experiments.
Three CSRLs (AC025165.1, LINC02257 and MYOSLID) were identified as prognostic CSRLs. The prognostic model exhibited a powerful predictive ability for overall survival and clinicopathological features in colon cancer. Moreover, there was a significant difference in the proportion of immune cells and the expression of immunosuppressive point biomarkers between the different groups. The high-risk group benefited from the chemotherapy drugs, such as Teniposide and Mitoxantrone. Finally, cell proliferation and CS were suppressed after MYOSLID knockdown.
CSRLs are promising biomarkers to forecast survival and therapeutic responses in colon cancer patients. Furthermore, MYOSLID, one of 3-CSRLs in the prognostic model, could dramatically regulate the proliferation and CS of colon cancer.
细胞衰老（CS）被认为是癌症发生发展的一个主要因素。然而，参与结肠癌调控的与CS相关的长链非编码RNA（CSRLs）尚未完全明确。我们的目标是创建一个新的CSRLs预后模型，用于预测结肠癌的预后和免疫治疗效果，并探索其潜在的分子功能。
从UCSC Xena平台获取GDC TCGA结肠癌（TCGA-COAD）的mRNA测序数据及相关临床信息，并从CellAge网站获取与CS相关的基因。采用Pearson相关分析来鉴定CSRLs。然后使用Kaplan-Meier生存曲线分析和单因素Cox分析来获得预后性CSRL。接下来，我们使用LASSO和多因素Cox分析创建了一个CSRLs预后模型，并通过Kaplan-Meier和ROC曲线分析评估其预后能力。此外，我们还探究了高风险组和低风险组在肿瘤微环境、体细胞突变、免疫治疗和药物敏感性方面的差异。最后，我们在细胞实验中验证了MYOSLID的功能。
三个CSRLs（AC025165.1、LINC02257和MYOSLID）被鉴定为预后性CSRLs。该预后模型对结肠癌的总生存期和临床病理特征具有强大的预测能力。此外，不同组之间免疫细胞比例和免疫抑制点生物标志物的表达存在显著差异。高风险组从替尼泊苷和米托蒽醌等化疗药物中获益。最后，敲低MYOSLID后，细胞增殖和CS受到抑制。
CSRLs有望成为预测结肠癌患者生存和治疗反应的生物标志物。此外，预后模型中的3个CSRLs之一MYOSLID可显著调节结肠癌的增殖和CS。
