Center for Gastrointestinal Research, Baylor Scott & White Research Institute and Charles A. Sammons Cancer Center, Baylor University Medical Center, Dallas, TX, USA; Department of Gastroenterological Surgery, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, Japan; Department of Surgery, Kumamoto General Hospital, Kumamoto, Japan.
Department of Biomedical Sciences, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong, China.
EBioMedicine. 2019 Mar;41:268-275. doi: 10.1016/j.ebiom.2019.01.057. Epub 2019 Feb 13.
Although identification of lymph node (LN) metastasis is a well-recognized strategy for improving outcomes in patients with gastric cancer (GC), currently there is lack of availability of adequate molecular biomarkers that can identify such metastasis. Herein we have developed a robust gene-expression signature for detecting LN metastasis in early stage GC by using a transcriptome-wide biomarker discovery and subsequent validation in multiple clinical cohorts.
A total of 532 patients with pathological T1 and T2 GC from 4 different cohorts were analyzed. Two independent datasets (n = 96, and n = 188) were used to establish a gene signature for the identification of LN metastasis in GC patients. The diagnostic performance of our gene-expression signature was subsequently assessed in two independent clinical cohorts using qRT-PCR assays (n = 101, and n = 147), and subsequently compared against conventional tumor markers and image-based diagnostics.
We established a 15-gene signature by analyzing multiple high throughput datasets, which robustly distinguished LN status in both training (AUC = 0.765, 95% CI 0.667-0.863) and validation cohorts (AUC = 0.742, 95% CI 0.630-0.852). Notably, the 15-gene signature was significantly superior compared to the conventional tumor markers, CEA (P = .04) and CA19-9 (P = .005), as well as computed tomography-based imaging (P = .04).
We have established and validated a 15-gene signature for detecting LN metastasis in GC patients, which offers a robust diagnostic tool for potentially improving treatment outcomes in gastric cancer patients. FUND: NIH: CA72851, CA181572, CA14792, CA202797, CA187956; CPRIT: RP140784: Baylor Sammons Cancer Center polot grants (AG), VPRT: 9610337, CityU 21101115, 11102317, 11103718; JCYJ20170307091256048 (XW).
尽管识别淋巴结（LN）转移是提高胃癌（GC）患者预后的一种公认策略，但目前缺乏可识别此类转移的充分分子生物标志物。在此，我们通过在多个临床队列中进行全转录组生物标志物发现和后续验证，开发了一种用于检测早期 GC 中 LN 转移的稳健基因表达谱。
对来自 4 个不同队列的 532 例病理 T1 和 T2 GC 患者进行分析。使用两个独立数据集（n=96 和 n=188）来建立用于识别 GC 患者 LN 转移的基因谱。随后，通过 qRT-PCR 检测在两个独立的临床队列中评估我们的基因表达谱的诊断性能（n=101 和 n=147），并随后与传统肿瘤标志物和基于图像的诊断方法进行比较。
通过分析多个高通量数据集，我们建立了一个 15 基因标志物，该标志物可在训练队列（AUC=0.765，95%CI 0.667-0.863）和验证队列（AUC=0.742，95%CI 0.630-0.852）中可靠地区分 LN 状态。值得注意的是，与传统肿瘤标志物 CEA（P=0.04）和 CA19-9（P=0.005）以及基于计算机断层扫描的成像相比，15 基因标志物具有显著优势（P=0.04）。
我们已经建立并验证了一个用于检测 GC 患者 LN 转移的 15 基因标志物，这为潜在改善胃癌患者的治疗结果提供了一个强大的诊断工具。
美国国立卫生研究院：CA72851、CA181572、CA14792、CA202797、CA187956；CPRIT：RP140784：贝勒萨姆斯癌症中心拨款（AG），VPRT：9610337、城大 21101115、11102317、11103718；JCYJ20170307091256048（XW）。
