Duscharla Divya, Bhumireddy Sudarshana Reddy, Lakshetti Sridhar, Pospisil Heike, Murthy P V L N, Walther Reinhard, Sripadi Prabhakar, Ummanni Ramesh
Center for Chemical Biology, CSIR-Indian Institute of Chemical Technology (CSIR-IICT), Hyderabad, India.
Centre for Academy of Scientific & Innovative Research, CSIR-Indian Institute of Chemical Technology (CSIR-IICT), Hyderabad, India.
PLoS One. 2016 Mar 9;11(3):e0150253. doi: 10.1371/journal.pone.0150253. eCollection 2016.
Prostate cancer (PCa) is one amongst the most common cancersin western men. Incidence rate ofPCa is on the rise worldwide. The present study deals with theserum lipidome profiling of patients diagnosed with PCa to identify potential new biomarkers. We employed ESI-MS/MS and GC-MS for identification of significantly altered lipids in cancer patient's serum compared to controls. Lipidomic data revealed 24 lipids are significantly altered in cancer patinet's serum (n = 18) compared to normal (n = 18) with no history of PCa. By using hierarchical clustering and principal component analysis (PCA) we could clearly separate cancer patients from control group. Correlation and partition analysis along with Formal Concept Analysis (FCA) have identified that PC (39:6) and FA (22:3) could classify samples with higher certainty. Both the lipids, PC (39:6) and FA (22:3) could influence the cataloging of patients with 100% sensitivity (all 18 control samples are classified correctly) and 77.7% specificity (of 18 tumor samples 4 samples are misclassified) with p-value of 1.612×10-6 in Fischer's exact test. Further, we performed GC-MS to denote fatty acids altered in PCa patients and found that alpha-linolenic acid (ALA) levels are altered in PCa. We also performed an in vitro proliferation assay to determine the effect of ALA in survival of classical human PCa cell lines LNCaP and PC3. We hereby report that the altered lipids PC (39:6) and FA (22:3) offer a new set of biomarkers in addition to the existing diagnostic tests that could significantly improve sensitivity and specificity in PCa diagnosis.
前列腺癌（PCa）是西方男性中最常见的癌症之一。全球范围内，PCa的发病率正在上升。本研究对被诊断为PCa的患者进行血清脂质组分析，以确定潜在的新生物标志物。我们采用电喷雾串联质谱（ESI-MS/MS）和气相色谱-质谱联用（GC-MS）技术，以识别癌症患者血清中与对照组相比有显著变化的脂质。脂质组学数据显示，与无PCa病史的正常组（n = 18）相比，癌症患者（n = 18）血清中有24种脂质发生了显著变化。通过层次聚类和主成分分析（PCA），我们能够清晰地将癌症患者与对照组区分开来。相关性和分区分析以及形式概念分析（FCA）已确定，磷脂酰胆碱（PC，39:6）和脂肪酸（FA，22:3）能够更准确地对样本进行分类。在费舍尔精确检验中，这两种脂质，即PC（39:6）和FA（22:3），能够以100%的灵敏度（所有18个对照样本均被正确分类）和77.7%的特异性（18个肿瘤样本中有4个样本被误分类）影响患者的分类，p值为1.612×10-6。此外，我们进行了GC-MS分析以检测PCa患者体内脂肪酸的变化，发现α-亚麻酸（ALA）水平在PCa患者中发生了改变。我们还进行了体外增殖试验，以确定ALA对经典人PCa细胞系LNCaP和PC3存活的影响。我们在此报告，除了现有的诊断测试外已改变的脂质PC（39:6）和FA（22:3）提供了一组新的生物标志物，可显著提高PCa诊断的灵敏度和特异性。
