Saviana Michela, Romano Giulia, McElroy Joseph, Nigita Giovanni, Distefano Rosario, Toft Robin, Calore Federica, Le Patricia, Morales Daniel Del Valle, Atmajoana Sarah, Deppen Stephen, Wang Kai, Lee L James, Acunzo Mario, Nana-Sinkam Patrick
Department of Internal Medicine, Division of Pulmonary Diseases and Critical Care Medicine, Virginia Commonwealth University, Richmond, VA, United States.
Department of Molecular Medicine, University La Sapienza, Rome, Italy.
Front Oncol. 2023 Oct 5;13:1255527. doi: 10.3389/fonc.2023.1255527. eCollection 2023.
Small cell lung cancer (SCLC) is characterized by poor prognosis and challenging diagnosis. Screening in high-risk smokers results in a reduction in lung cancer mortality, however, screening efforts are primarily focused on non-small cell lung cancer (NSCLC). SCLC diagnosis and surveillance remain significant challenges. The aberrant expression of circulating microRNAs (miRNAs/miRs) is reported in many tumors and can provide insights into the pathogenesis of tumor development and progression. Here, we conducted a comprehensive assessment of circulating miRNAs in SCLC with a goal of developing a miRNA-based classifier to assist in SCLC diagnoses.
We profiled deregulated circulating cell-free miRNAs in the plasma of SCLC patients. We tested selected miRNAs on a training cohort and created a classifier by integrating miRNA expression and patients' clinical data. Finally, we applied the classifier on a validation dataset.
We determined that miR-375-3p can discriminate between SCLC and NSCLC patients, and between SCLC and Squamous Cell Carcinoma patients. Moreover, we found that a model comprising miR-375-3p, miR-320b, and miR-144-3p can be integrated with race and age to distinguish metastatic SCLC from a control group.
This study proposes a miRNA-based biomarker classifier for SCLC that considers clinical demographics with specific cut offs to inform SCLC diagnosis.
小细胞肺癌（SCLC）的特点是预后差且诊断具有挑战性。对高危吸烟者进行筛查可降低肺癌死亡率，然而，筛查工作主要集中在非小细胞肺癌（NSCLC）上。SCLC的诊断和监测仍然是重大挑战。循环微RNA（miRNA/miR）的异常表达在许多肿瘤中都有报道，并且可以为肿瘤发生发展和进展的发病机制提供见解。在此，我们对SCLC中的循环miRNA进行了全面评估，目的是开发一种基于miRNA的分类器以协助SCLC诊断。
我们分析了SCLC患者血浆中失调的循环游离miRNA。我们在一个训练队列中测试了选定的miRNA，并通过整合miRNA表达和患者的临床数据创建了一个分类器。最后，我们将该分类器应用于一个验证数据集。
我们确定miR-375-3p可以区分SCLC和NSCLC患者，以及SCLC和鳞状细胞癌患者。此外，我们发现一个包含miR-375-3p、miR-320b和miR-144-3p的模型可以与种族和年龄相结合，以区分转移性SCLC与对照组。
本研究提出了一种基于miRNA的SCLC生物标志物分类器，该分类器考虑了具有特定临界值的临床人口统计学特征以指导SCLC诊断。
