Irungu Stella, Mavrelos Dimitrios, Worthington Jenny, Blyuss Oleg, Saridogan Ertan, Timms John F
1Department of Women's Cancer, Institute for Women's Health, University College London, Cruciform Building 1.1, Gower Street, London, WC1E 6BT UK.
Reproductive Medicine Unit, University College London Hospital, Elizabeth Garrett Anderson Wing, Lower Ground Floor, 235 Euston Road, London, NW1 2BU UK.
Clin Proteomics. 2019 Apr 6;16:14. doi: 10.1186/s12014-019-9235-3. eCollection 2019.
Endometriosis is a common gynaecological disorder affecting 5-10% of women of reproductive age who often experience chronic pelvic pain and infertility. Definitive diagnosis is through laparoscopy, exposing patients to potentially serious complications, and is often delayed. Non-invasive biomarkers are urgently required to accelerate diagnosis and for triaging potential patients for surgery.
This retrospective case control biomarker discovery and validation study used quantitative 2D-difference gel electrophoresis and tandem mass tagging-liquid chromatography-tandem mass spectrometry for protein expression profiling of eutopic and ectopic endometrial tissue samples collected from 28 cases of endometriosis and 18 control patients undergoing surgery for investigation of chronic pelvic pain without endometriosis or prophylactic surgery. Samples were further sub-grouped by menstrual cycle phase. Selected differentially expressed candidate markers (LUM, CPM, TNC, TPM2 and PAEP) were verified by ELISA in a set of 87 serum samples collected from the same and additional women. Previously reported biomarkers (CA125, sICAM1, FST, VEGF, MCP1, MIF and IL1R2) were also validated and diagnostic performance of markers and combinations established.
Cycle phase and endometriosis-associated proteomic changes were identified in eutopic tissue from over 1400 identified gene products, yielding potential biomarker candidates. Bioinformatics analysis revealed enrichment of adhesion/extracellular matrix proteins and progesterone signalling. The best single marker for discriminating endometriosis from controls remained CA125 (AUC = 0.63), with the best cross-validated multimarker models improving the AUC to 0.71-0.81, depending upon menstrual cycle phase and control group.
We have identified menstrual cycle- and endometriosis-associated protein changes linked to various cellular processes that are potential biomarkers and that provide insight into the biology of endometriosis. Our data indicate that the markers tested, whilst not useful alone, have improved diagnostic accuracy when used in combination and demonstrate menstrual cycle specificity. Tissue heterogeneity and blood contamination is likely to have hindered biomarker discovery, whilst a small sample size precludes accurate determination of performance by cycle phase. Independent validation of these biomarker panels in a larger cohort is however warranted, and if successful, they may have clinical utility in triaging patients for surgery.
子宫内膜异位症是一种常见的妇科疾病，影响5% - 10%的育龄女性，这些女性常经历慢性盆腔疼痛和不孕。确诊需通过腹腔镜检查，这会使患者面临潜在的严重并发症，且诊断往往延迟。迫切需要非侵入性生物标志物来加速诊断，并对潜在手术患者进行分类。
这项回顾性病例对照生物标志物发现与验证研究，使用定量二维差异凝胶电泳和串联质量标签 - 液相色谱 - 串联质谱法，对从28例子宫内膜异位症患者和18例因慢性盆腔疼痛接受手术（无子宫内膜异位症或预防性手术）的对照患者中收集的在位和异位子宫内膜组织样本进行蛋白质表达谱分析。样本按月经周期阶段进一步分组。通过酶联免疫吸附测定法（ELISA）在从相同及其他女性中收集的87份血清样本中验证选定的差异表达候选标志物（LUM、CPM、TNC、TPM2和PAEP）。还对先前报道的生物标志物（CA125、sICAM1、FST、VEGF、MCP1、MIF和IL1R2）进行了验证，并确定了标志物及其组合的诊断性能。
在超过1400种已鉴定的基因产物的在位组织中，识别出与月经周期阶段和子宫内膜异位症相关的蛋白质组变化，产生了潜在的生物标志物候选物。生物信息学分析揭示了黏附/细胞外基质蛋白和孕酮信号通路的富集。用于区分子宫内膜异位症与对照的最佳单一标志物仍然是CA125（曲线下面积[AUC]=0.63），最佳交叉验证多标志物模型根据月经周期阶段和对照组将AUC提高到0.71 - 0.81。
我们已经确定了与月经周期和子宫内膜异位症相关的蛋白质变化，这些变化与各种细胞过程相关，是潜在的生物标志物，并为子宫内膜异位症的生物学特性提供了见解。我们的数据表明，所测试的标志物虽然单独使用无用，但联合使用时可提高诊断准确性，并显示出月经周期特异性。组织异质性和血液污染可能阻碍了生物标志物的发现，而样本量小妨碍了按月经周期阶段准确确定性能。然而，有必要在更大的队列中对这些生物标志物组进行独立验证，如果成功，它们可能在对手术患者进行分类方面具有临床应用价值。
