Charkiewicz Radoslaw, Sulewska Anetta, Mroz Robert, Charkiewicz Alicja, Naumnik Wojciech, Kraska Marcin, Gyenesei Attila, Galik Bence, Junttila Sini, Miskiewicz Borys, Stec Rafal, Karabowicz Piotr, Zawada Magdalena, Miltyk Wojciech, Niklinski Jacek
Center of Experimental Medicine, Medical University of Bialystok, 15-369 Bialystok, Poland.
Department of Clinical Molecular Biology, Medical University of Bialystok, 15-269 Bialystok, Poland.
Cancers (Basel). 2023 Oct 10;15(20):4910. doi: 10.3390/cancers15204910.
Non-small cell lung cancer is the predominant form of lung cancer and is associated with a poor prognosis. MiRNAs implicated in cancer initiation and progression can be easily detected in liquid biopsy samples and have the potential to serve as non-invasive biomarkers. In this study, we employed next-generation sequencing to globally profile miRNAs in serum samples from 71 early-stage NSCLC patients and 47 non-cancerous pulmonary condition patients. Preliminary analysis of differentially expressed miRNAs revealed 28 upregulated miRNAs in NSCLC compared to the control group. Functional enrichment analyses unveiled their involvement in NSCLC signaling pathways. Subsequently, we developed a gradient-boosting decision tree classifier based on 2588 miRNAs, which demonstrated high accuracy (0.837), sensitivity (0.806), and specificity (0.859) in effectively distinguishing NSCLC from non-cancerous individuals. Shapley Additive exPlanations analysis improved the model metrics by identifying the top 15 miRNAs with the strongest discriminatory value, yielding an AUC of 0.96 ± 0.04, accuracy of 0.896, sensitivity of 0.884, and specificity of 0.903. Our study establishes the potential utility of a non-invasive serum miRNA signature as a supportive tool for early detection of NSCLC while also shedding light on dysregulated miRNAs in NSCLC biology. For enhanced credibility and understanding, further validation in an independent cohort of patients is warranted.
非小细胞肺癌是肺癌的主要形式，且预后较差。参与癌症发生和进展的微小RNA（miRNA）可在液体活检样本中轻松检测到，并有潜力作为非侵入性生物标志物。在本研究中，我们采用下一代测序技术对71例早期非小细胞肺癌患者和47例非癌性肺部疾病患者的血清样本中的miRNA进行全面分析。对差异表达miRNA的初步分析显示，与对照组相比，非小细胞肺癌中有28种miRNA上调。功能富集分析揭示了它们参与非小细胞肺癌信号通路。随后，我们基于2588种miRNA开发了一种梯度提升决策树分类器，该分类器在有效区分非小细胞肺癌患者与非癌个体方面表现出高准确性（0.837）、敏感性（0.806）和特异性（0.859）。Shapley值相加解释分析通过识别具有最强判别价值的前15种miRNA改进了模型指标，得到的曲线下面积为0.96±0.04，准确性为0.896，敏感性为0.884，特异性为0.903。我们的研究确立了非侵入性血清miRNA特征作为早期检测非小细胞肺癌的辅助工具的潜在效用，同时也揭示了非小细胞肺癌生物学中失调的miRNA。为提高可信度和加深理解，有必要在独立的患者队列中进行进一步验证。
