Department of Internal Medicine, Università degli Studi di Genova, Genova, Italy.
IRCSS Ospedale Policlinico San Martino, Genova, Italy.
PLoS One. 2020 Feb 5;15(2):e0226595. doi: 10.1371/journal.pone.0226595. eCollection 2020.
Standard treatment for locally advanced rectal adenocarcinoma (LARC) includes a combination of chemotherapy with pyrimidine analogues, such as capecitabine, and radiation therapy, followed by surgery. Currently no clinically useful genomic predictors of benefit from neoadjuvant chemoradiotherapy (nCRT) exist for LARC. In this study we assessed the expression of 8,127 long noncoding RNAs (lncRNAs), poorly studied in LARC, to infer their ability in classifying patients' pathological complete response (pCR). We collected and analyzed, using lncRNA-specific Agilent microarrays a consecutive series of 61 LARC cases undergoing nCRT. Potential lncRNA predictors in responders and non-responders to nCRT were identified with LASSO regression, and a model was optimized using k-fold cross-validation after selection of the three most informative lncRNA. 11 lncRNAs were differentially expressed with false discovery rate < 0.01 between responders and non-responders to NACT. We identified lnc-KLF7-1, lnc-MAB21L2-1, and LINC00324 as the most promising variable subset for classification building. Overall sensitivity and specificity were 0.91 and 0.94 respectively, with an AUC of our ROC curve = 0.93. Our study shows for the first time that lncRNAs can accurately predict response in LARC undergoing nCRT. Our three-lncRNA based signature must be independently validated and further analyses must be conducted to fully understand the biological role of the identified signature, but our results suggest lncRNAs may be an ideal biomarker for response prediction in the studied setting.
局部晚期直肠腺癌(LARC)的标准治疗包括联合使用嘧啶类似物(如卡培他滨)的化疗和放射治疗,然后进行手术。目前,对于 LARC 患者,没有临床有用的预测新辅助放化疗(nCRT)获益的基因组标志物。在这项研究中,我们评估了 8127 个长链非编码 RNA(lncRNA)的表达,这些 lncRNA 在 LARC 中研究较少,以推断它们在分类患者病理完全缓解(pCR)方面的能力。我们使用 lncRNA 特异性的安捷伦微阵列收集和分析了连续的 61 例接受 nCRT 的 LARC 病例。使用 LASSO 回归识别对 nCRT 有反应和无反应的潜在 lncRNA 预测因子,并在选择三个最具信息量的 lncRNA 后使用 k 折交叉验证对模型进行优化。在对 NACT 有反应和无反应的患者之间,有 11 个 lncRNA 的表达存在差异,假发现率<0.01。我们确定 lnc-KLF7-1、lnc-MAB21L2-1 和 LINC00324 是构建分类最有前途的变量子集。总体敏感性和特异性分别为 0.91 和 0.94,ROC 曲线的 AUC=0.93。我们的研究首次表明,lncRNA 可以准确预测接受 nCRT 的 LARC 的反应。我们基于三个 lncRNA 的特征必须独立验证,并进一步进行分析以充分了解所鉴定特征的生物学作用,但我们的结果表明 lncRNA 可能是该研究环境中预测反应的理想生物标志物。