Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China.
Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China.
J Cancer Res Clin Oncol. 2023 Oct;149(13):12115-12129. doi: 10.1007/s00432-023-05107-0. Epub 2023 Jul 9.
Long noncoding RNAs (lncRNAs) have been reported to play an important role in tumor immune modification. Nonetheless, the clinical implication of immune-associated lncRNAs in renal cell carcinoma (RCC) remains to be further explored.
76 combinations of machine learning algorithms were integrated to develop and validate a machine learning-derived immune-related lncRNA signature (MDILS) in five independent cohorts (n = 801). We collected 28 published signatures and collated clinical variables for comparison with MDILS to verify its efficacy. Subsequently, molecular mechanisms, immune status, mutation landscape, and pharmacological profile were further investigated in different stratified patients.
Patients with high MDILS displayed worse overall survival than those with low MDILS. The MDILS could independently predict overall survival and convey robust performance across five cohorts. MDILS has a significantly better performance compared with traditional clinical variables and 28 published signatures. Patients with low MDILS exhibited more abundant immune infiltration and higher potency of immunotherapeutic response, while patients with high MDILS might be more sensitive to multiple chemotherapeutic drugs (e.g., sunitinib and axitinib).
MDILS is a robust and promising tool to facilitate clinical decision-making and precision treatment of RCC.
长链非编码 RNA（lncRNA）已被报道在肿瘤免疫修饰中发挥重要作用。然而，免疫相关 lncRNA 在肾细胞癌（RCC）中的临床意义仍有待进一步探索。
整合了 76 种机器学习算法组合，在五个独立队列（n=801）中开发和验证了一种基于机器学习的免疫相关 lncRNA 特征（MDILS）。我们收集了 28 个已发表的特征，并整理了临床变量与 MDILS 进行比较，以验证其功效。随后，在不同分层的患者中进一步研究了分子机制、免疫状态、突变景观和药物特征。
MDILS 高表达的患者总生存情况差于 MDILS 低表达的患者。MDILS 可独立预测总生存情况，在五个队列中均具有稳健的性能。MDILS 的性能明显优于传统临床变量和 28 个已发表的特征。MDILS 低表达的患者表现出更丰富的免疫浸润和更高的免疫治疗反应能力，而 MDILS 高表达的患者可能对多种化疗药物（如舒尼替尼和阿昔替尼）更敏感。
MDILS 是一种强大且有前途的工具，可促进 RCC 的临床决策和精准治疗。
