Tamura Keita, Horikawa Makoto, Sato Shumpei, Miyake Hideaki, Setou Mitsutoshi
Department of Cellular and Molecular Anatomy, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka, Japan.
Department of Urology, Hamamatsu University School of Medicine, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka, Japan.
Oncotarget. 2019 Mar 1;10(18):1688-1703. doi: 10.18632/oncotarget.26706.
Clear cell renal cell carcinoma (ccRCC) often results in recurrence or metastasis, and there are only a few clinically effective biomarkers for early diagnosis and personalized therapy. Metabolic changes have been widely studied using mass spectrometry (MS) of tissue lysates to identify novel biomarkers. Our objective was to identify lipid biomarkers that can predict disease progression in ccRCC by a tissue-based approach. We retrospectively investigated lipid molecules in cancerous tissues and normal renal cortex tissues obtained from patients with ccRCC ( = 47) using desorption electrospray ionization imaging mass spectrometry (DESI-IMS). We selected eight candidate lipid biomarkers showing higher signal intensity in cancerous than in normal tissues, with a clear distinction of the tissue type based on the images. Of these candidates, low maximum intensity ratio (cancerous/normal) values of ions of oleic acid, 389.2, and 391.3 significantly correlated with shorter progression-free survival compared with high maximum intensity ratio values ( = 0.011, = 0.022, and < 0.001, respectively). This study identified novel lipid molecules contributing to the prediction of disease progression in ccRCC using DESI-IMS. Our findings on lipid storage may provide a new diagnostic or therapeutic strategy for targeting cancer cell metabolism.
透明细胞肾细胞癌(ccRCC)常导致复发或转移,且早期诊断和个性化治疗的临床有效生物标志物很少。代谢变化已通过组织裂解物的质谱(MS)进行广泛研究,以识别新型生物标志物。我们的目标是通过基于组织的方法识别可预测ccRCC疾病进展的脂质生物标志物。我们使用解吸电喷雾电离成像质谱(DESI-IMS)回顾性研究了47例ccRCC患者癌组织和正常肾皮质组织中的脂质分子。我们选择了8种候选脂质生物标志物,其在癌组织中的信号强度高于正常组织,基于图像可清晰区分组织类型。在这些候选物中,油酸离子(m/z 389.2和391.3)的低最大强度比(癌组织/正常组织)值与较短的无进展生存期显著相关,而高最大强度比则不然(分别为P = 0.011、P = 0.022和P < 0.001)。本研究使用DESI-IMS识别了有助于预测ccRCC疾病进展的新型脂质分子。我们关于脂质储存的发现可能为靶向癌细胞代谢提供新的诊断或治疗策略。