Background 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. Methods 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. Results 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. Conclusions 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.

中文翻译：

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发现用于诊断子宫内膜异位症的非侵入性生物标志物。

背景子宫内膜异位症是一种常见的妇科疾病，影响 5-10% 的育龄妇女，她们经常经历慢性盆腔疼痛和不孕症。明确的诊断是通过腹腔镜检查，使患者面临潜在的严重并发症，并且经常被延迟。迫切需要非侵入性生物标志物来加速诊断和对潜在患者进行手术分类。方法 本回顾性病例对照生物标志物发现和验证研究使用定量 2D 差异凝胶电泳和串联质谱标记-液相色谱-串联质谱法对采集自 28 例子宫内膜异位症患者和 18 例接受治疗的对照患者的在位和异位子宫内膜组织样本进行蛋白质表达谱分析。用于调查慢性盆腔疼痛的手术，无需子宫内膜异位症或预防性手术。样本进一步按月经周期阶段进行分组。选择的差异表达候选标志物（LUM、CPM、TNC、TPM2 和 PAEP）通过 ELISA 在从同一和其他女性收集的一组 87 个血清样本中进行验证。先前报道的生物标志物（CA125、sICAM1、FST、VEGF、MCP1、MIF 和 IL1R2) 也得到了验证，并确定了标志物和组合的诊断性能。结果 从超过 1400 个已鉴定的基因产物中鉴定了在位组织中的周期阶段和子宫内膜异位症相关的蛋白质组学变化，产生了潜在的生物标志物候选物。生物信息学分析揭示了粘附/细胞外基质蛋白和孕酮信号的富集。区分子宫内膜异位症与对照组的最佳单一标志物仍然是 CA125（AUC = 0.63），最佳交叉验证多标志物模型将 AUC 提高到 0.71-0.81，具体取决于月经周期阶段和对照组。结论 我们已经确定了与各种细胞过程相关的月经周期和子宫内膜异位症相关的蛋白质变化，这些细胞过程是潜在的生物标志物，可以深入了解子宫内膜异位症的生物学。我们的数据表明，测试的标志物虽然不能单独使用，但在组合使用时提高了诊断准确性，并证明了月经周期的特异性。组织异质性和血液污染可能阻碍了生物标志物的发现，而小样本量则妨碍了按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，它们可能在对患者进行手术分类方面具有临床实用性。而小样本量则无法准确确定循环阶段的性能。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，它们可能在对患者进行手术分类方面具有临床实用性。而小样本量则无法准确确定循环阶段的性能。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，它们可能在对患者进行手术分类方面具有临床实用性。