Czarnecka Karolina H, Szmyd Bartosz, Barańska Magda, Kaszkowiak Marcin, Kordiak Jacek, Antczak Adam, Pastuszak-Lewandoska Dorota, Brzeziańska-Lasota Ewa
Department of Biomedicine and Genetics, Medical University of Lodz, Łódz, Poland.
Quantitative Genomic Medicine Laboratories, S.L., Esplugues de Llobregat, Barcelona, Spain.
Front Oncol. 2019 Dec 13;9:1372. doi: 10.3389/fonc.2019.01372. eCollection 2019.
Lung cancer is one of the most common causes of death worldwide with a relatively high fatality rate and a mean 5-years survival of about 18%. One of the hallmarks of cancer is the extracellular matrix (ECM) remodeling, which is crucial for metastasis. This process may be regulated by miRs targeting metalloproteinases (MMPs) associated with the ECM breakdown and metastatic process or blocking the action of tissue inhibitors of metalloproteinases (TIMPs). Search for early biomarkers is essential in detecting non-small cell lung cancer (NSCLC) and distinguishing its subtypes: Adenocarcinoma (AC) from Squamous Cell Carcinoma (SCC), enabling targeted chemotherapy. and targeting and were selected by TCGA data analysis with further validation using miRTarBase and literature. The study group comprised 47 patients with primary NSCLC (AC and SCC subtypes). RNA was isolated from the tumor and normal-looking neighboring tissue (NLNT) free of cancer cells. MiRs from peripheral blood exosomes were extracted on admission and 5-7 days after surgery. Gene and miRs expression were assessed in qPCR using TaqMan probes. The has been expressed on a similar level in NLNT, as in cancer. While, expression was decreased both in cancer tissue and NLNT, with significantly lower expression in cancer. downregulation in NLNT and in SCC subtype correlated negatively with . The preoperative expression was significantly higher among patients with SCC compared to AC. Receiver operating characteristic (ROC) analysis of as AC subtype classifier revealed 90% specificity and 48% sensitivity in optimal cut-off point with area under ROC curve (AUC): 0.71 (95%CI: 0.55-0.87). Within NSCLC subtypes: a strong negative correlation between pack-years (PY) and expression was observed for NLNT in the SCC group. The silencing observed in the NLNT and its negative correlation with presurgical expression of (from serum exosomes), suggest that miRs can influence ECM remodeling at a distance from the center of the lesion. The expression pattern in serum obtained before surgery significantly differs between AC and SCC subtypes. Moreover, decreased expression in NLNT (in SCC group) negatively correlates with the amount of tobacco smoked in a lifetime in PY.
肺癌是全球最常见的死亡原因之一,死亡率相对较高,平均5年生存率约为18%。癌症的一个标志是细胞外基质(ECM)重塑,这对转移至关重要。这个过程可能受靶向与ECM分解和转移过程相关的金属蛋白酶(MMPs)的微小RNA(miRs)调控,或受组织金属蛋白酶抑制剂(TIMPs)作用的阻断。寻找早期生物标志物对于检测非小细胞肺癌(NSCLC)并区分其亚型:腺癌(AC)与鳞状细胞癌(SCC)至关重要,从而实现靶向化疗。通过TCGA数据分析选择了[具体miRs],并使用miRTarBase和文献进行进一步验证。研究组包括47例原发性NSCLC患者(AC和SCC亚型)。从肿瘤组织和无癌细胞的外观正常的邻近组织(NLNT)中分离RNA。入院时及术后5 - 7天提取外周血外泌体中的miRs。使用TaqMan探针通过qPCR评估基因和miRs表达。[具体基因]在NLNT中的表达水平与在癌组织中的相似。然而,[另一个具体基因]在癌组织和NLNT中的表达均降低,在癌组织中的表达显著更低。NLNT中[该基因]的下调以及SCC亚型中[该基因]的下调与[某个指标]呈负相关。SCC患者术前[该miR]的表达显著高于AC患者。将[该miR]作为AC亚型分类器的受试者工作特征(ROC)分析显示,在最佳切点处特异性为90%,敏感性为48%,ROC曲线下面积(AUC)为0.71(95%CI:0.55 - 0.87)。在NSCLC亚型中:SCC组的NLNT中,吸烟包年数(PY)与[该miR]的表达之间观察到强烈的负相关。在NLNT中观察到[该基因]的沉默及其与术前(来自血清外泌体)[该miR]表达的负相关,表明miRs可以在远离病变中心的位置影响ECM重塑。手术前获得的血清中[该miR]的表达模式在AC和SCC亚型之间存在显著差异。此外,NLNT中(SCC组)[该miR]表达的降低与一生中吸烟的PY量呈负相关。