PO.PS01.01 · 人群科学

利用前瞻性采集的血样开发并验证用于卵巢癌早期诊断的血浆蛋白质组学特征

Development and validation of a plasma proteomics signature for earlier diagnosis of ovarian cancer using prospectively collected blood samples

编号 2310 展板 9 时间 4/20 09:00–12:00 区域 Section 35 主讲 Nan Lin, MPH;MS;PhD

分会场 Biomarkers of Endogenous or Exogenous Exposures, Early Detection, Biological Effects, and Prognosis

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作者与单位 Authors & Affiliations

Nan Lin¹, Ngo Long², Allison F. Vitonis¹, Tara Eicher³, SHELLEY TWOROGER⁴, Simon T. Dillon², Towia A. Libermann², Daniel W. Cramer¹, John Quackenbush³, Kathryn L. Terry¹, Naoko Sasamoto⁵

¹Department of Obstetrics and Gynecology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA,²Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA,³Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA,⁴Division of Oncological Sciences, Knight Cancer Institute, Oregon Health & Science University, Portland, OR,⁵Department of Obstetrics and Gynecology, University of Washington, Seattle, WA

摘要 Abstract

中文摘要

背景：目前尚无适合筛查的卵巢癌生物标志物，部分原因是生物标志物发现使用了诊断时采集的回顾性临床样本。因此，我们试图利用前瞻性采集的血样来发现用于卵巢癌早期检测的新型血浆蛋白质组学生物标志物。方法：我们评估了在前列腺癌、肺癌、结直肠癌和卵巢癌筛查试验（PLCO；n=98，训练数据集）和护士健康研究（NHS；n=99，重复验证数据集）中，卵巢癌诊断至少三年前采集的血液中使用 SomaScan v5.0 检测测量的 10,778 种血浆蛋白及其配对对照。我们使用条件逻辑回归分别在两个数据集中识别与卵巢癌相关的单个蛋白。我们还在术前盆腔肿块研究中比较了诊断时采集的血液中早期和晚期卵巢癌的血浆蛋白与年龄匹配的基于人群的对照（PreOp；n=134）。然后我们使用弹性网络（Elastic Net）开发了一个基于蛋白质组学的评分，以在 PLCO 中区分卵巢癌病例和对照，并与仅含 CA125 的模型进行比较，通过计算受试者工作特征曲线下面积（AUC）和 95% 置信区间（CI）在 NHS 中验证基于蛋白质组学评分的性能。结果：前瞻性采集血样中与卵巢癌相关的血浆蛋白，不同于早期疾病诊断时采集血样中与对照相比相关的蛋白。在 PLCO 中，有 99 种蛋白与采血至少 3 年后诊断的卵巢癌相关（p<0.05），其中 2 种蛋白 RCN3 和 OBP2B 在 NHS 中得到重复验证（p<0.05）。在这 99 种蛋白中，大多数在 PreOp 中与卵巢癌无关，仅有三种蛋白重叠（即 SERPINF2、ASAH2、BAGE3）。在 PLCO 中，将由 56 种蛋白组成的基于蛋白质组学的评分添加到仅含 CA125 的模型中，显著（p=0.02）改善了对卵巢癌病例与对照的区分，AUC（95%CI）从 0.65（0.50-0.80）提高到 0.86（0.67,1.00）。在 NHS 中，基于蛋白质组学的评分产生的 AUC 为 0.60（0.49-0.72），具有边缘显著性。结论：我们的结果揭示，诊断前至少 3 年前瞻性采集的血样与诊断时采集的血样之间的血浆蛋白质组学谱存在差异，无论分期如何。我们开发了一个基于蛋白质组学的评分，优于单独的 CA-125，尽管应用于独立队列时未显示出强烈的改善。然而，研究之间的差异（如绝经状态和激素治疗使用）可能解释了这一变异。

查看英文原文 English abstract

Background: There is currently no ovarian cancer biomarker appropriate for screening which is partially due to using retrospective clinical samples obtained at the time of diagnosis for biomarker discovery. Thus, we sought to discover novel plasma proteomic biomarkers for ovarian cancer early detection using prospectively collected blood samples. Method: We evaluated 10,778 plasma proteins measured using the SomaScan v5.0 assay in blood drawn at least three years prior to ovarian cancer diagnosis and matched controls in the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO; n=98, training dataset) and the Nurses' Health Studies (NHS; n=99, replication dataset). We used a conditional logistic regression to identify individual proteins associated with ovarian cancer in the two datasets separately. We also compared plasma proteins for early-stage and late-stage ovarian cancer in blood collected at diagnosis in the PreOperative Pelvic Mass Study to age-matched population-based controls (PreOp; n=134). Then we used Elastic Net to develop a proteomic-based score to discriminate ovarian cancer cases from controls in PLCO, compared to a model with CA125 alone, and validated the proteomic-based score performance in NHS by calculating the area under the receiver operating characteristic curve (AUC) and 95% confidence interval (CI). Results: Plasma proteins associated with ovarian cancer in blood samples collected prospectively differed from those associated with blood samples collected at diagnosis of early-stage disease compared to controls. There were 99 proteins associated with ovarian cancer diagnosed at least 3 years from blood collection (p<0.05) in PLCO, where 2 proteins, RCN3 and OBP2B, replicated in NHS (p<0.05). Of these 99 proteins, majority were not associated with ovarian cancer in PreOp and only three proteins overlapped (i.e., SERPINF2, ASAH2, BAGE3). In PLCO, adding a proteomic-based score comprised of 56 proteins to a model with CA125 alone significantly (p=0.02) improved discriminating ovarian cancer cases from controls with an AUC (95%CI) from 0.65(0.50-0.80) to 0.86(0.67,1.00). In NHS, proteomic-based score resulted in an AUC of 0.60(0.49-0.72) with marginal significance. Conclusion: Our results revealed plasma proteomic profiles differ between prospectively collected blood samples at least 3 years prior to diagnosis and blood samples collected at time of diagnosis regardless of stage. We developed a proteomics-based score that improved upon CA-125 alone, although application to an independent cohort did not demonstrate a strong improvement. However, differences between studies (e.g., menopausal status and hormone therapy use) may explain this variation.

利益披露 Disclosure

N. Lin, None.. N. Long, None.. A. F. Vitonis, None.. T. Eicher, None.. S. Tworoger, None.. S. T. Dillon, None.. T. A. Libermann, None.. D. W. Cramer, None.. J. Quackenbush, None.. K. L. Terry, None.. N. Sasamoto, None.

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