Huai Yajun, Lai Liting, Ren Yuanhui, Yang Bowen, Yu Shasha, Wang Shanshan, Mei Jinhong
Department of Oncology, First Affiliated Hospital of Nanchang University, Nanchang, China.
Institute of Molecular Pathology, Nanchang University, Nanchang, China.
J Gastrointest Oncol. 2023 Jun 30;14(3):1360-1377. doi: 10.21037/jgo-23-412.
Colorectal cancer (CRC) remains the most common gastrointestinal malignancy. Despite multimodal therapy, its mortality is high due to recurrence and metastasis. This study developed and verified a risk model consisting of 14 N-methyladenosine (mA) long noncoding RNAs (lncRNAs) to assess the prognosis of patients with CRC and investigated its relevance to immune regulation and drug sensitivity.
The gene expression profiles and clinical data of 446 patients with CRC were retrieved from The Cancer Genome Atlas (TCGA). 14 lncRNAs were screened using the Gene Co-expression Network (corFilter =0.5, P<0.001), and univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analysis to construct the optimal risk model. The predictive performance and clinical applicability of the model were next verified. In addition, we performed Gene Ontology (GO) enrichment analysis to identify potential biological functions and detected the difference in tumor mutational burden (TMB), immune function, and sensitivity to immunotherapy and other drugs between the high- and low-risk groups to evaluate the application of the constructed risk model in depth.
The model was found to be an appropriate marker for predicting the prognosis of patients with CRC, independent of other clinical features, and demonstrated good precision and broad clinical applicability. It correlated with pathways in the development of cancer and immune-related functions, and patients in the high-risk group had higher tumor immune dysfunction and escape (TIDE) scores. Furthermore, we found significant differences in the overall survival (OS) between patients in the high- and low-tumor mutation burden (TMB) groups, which may work in conjunction with the constructed model to better predict patients' prognosis. Finally, we identified 12 drugs, including A-443654 and sorafenib, with lower half maximal inhibitory concentration (IC) values in the high-risk group. Conversely, 21 drugs, including gemcitabine and rapamycin, had lower IC values in the low-risk group.
We constructed a risk model based on 14 mA-related lncRNAs that could predict the prognosis of patients with CRC and provided additional therapeutic ideas for their treatment. These findings may additionally serve as a foundation for further studies on regulating CRC via mA-related lncRNAs.
结直肠癌（CRC）仍是最常见的胃肠道恶性肿瘤。尽管采用了多模式治疗，但由于复发和转移，其死亡率仍然很高。本研究开发并验证了一种由14种N-甲基腺苷（mA）长链非编码RNA（lncRNA）组成的风险模型，以评估CRC患者的预后，并研究其与免疫调节和药物敏感性的相关性。
从癌症基因组图谱（TCGA）中检索446例CRC患者的基因表达谱和临床数据。使用基因共表达网络（corFilter = 0.5，P < 0.001）、单因素和最小绝对收缩和选择算子（LASSO）Cox回归分析筛选14种lncRNA，以构建最佳风险模型。接下来验证该模型的预测性能和临床适用性。此外，我们进行了基因本体（GO）富集分析以确定潜在的生物学功能，并检测高风险组和低风险组之间肿瘤突变负担（TMB）、免疫功能以及对免疫治疗和其他药物的敏感性差异，以深入评估所构建风险模型的应用。
该模型被发现是预测CRC患者预后的合适标志物，独立于其他临床特征，并显示出良好的准确性和广泛的临床适用性。它与癌症发展途径和免疫相关功能相关，高风险组患者的肿瘤免疫功能障碍和逃逸（TIDE）评分更高。此外，我们发现高肿瘤突变负担（TMB）组和低肿瘤突变负担（TMB）组患者的总生存期（OS）存在显著差异，这可能与所构建的模型协同作用，以更好地预测患者的预后。最后，我们确定了12种药物，包括A - 443654和索拉非尼，在高风险组中的半数最大抑制浓度（IC）值较低。相反，21种药物，包括吉西他滨和雷帕霉素，在低风险组中的IC值较低。
我们构建了一种基于14种与mA相关的lncRNA的风险模型，该模型可以预测CRC患者的预后，并为其治疗提供额外的治疗思路。这些发现还可为进一步研究通过与mA相关的lncRNA调节CRC奠定基础。
