Prospective Proteomic Study Identifies Potential Circulating Protein Biomarkers for Colorectal Cancer Risk.
Prospective Proteomic Study Identifies Potential Circulating Protein Biomarkers for Colorectal Cancer Risk.
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缺乏前瞻性研究设计中关于循环蛋白与结直肠癌风险的研究。本研究的目的是通过使用蛋白质组学技术在两阶段病例对照研究嵌套在上海妇女健康研究（SWHS），一个以人群为基础的前瞻性队列研究扫描和识别蛋白质标记。在发现集中，我们发现了27个循环蛋白质与名义上的显着关联。其中6种，包括CD 79 B、DDR 1、EFNA 4、FLRT 2、LTA 4 H和NCR 1，在研究的验证阶段进行了验证。这项研究首次评估了东亚人诊断前血液样本中超过1000种循环蛋白与CRC风险的相关性。背景：基于蛋白质组学的技术是用于癌症生物标志物发现的新兴工具。已经进行了有限的前瞻性研究来评估循环蛋白在结直肠癌（CRC）发展中的作用。方法：在上海妇女健康研究中进行两阶段病例对照蛋白质组学研究。在发现阶段共测量了1104种循环蛋白，包括100例偶发CRC病例和100例单独匹配的对照。另外选择了60个病例对照对进行验证。使用Olink平台完成两个阶段的蛋白质谱分析。条件Logistic回归用于评估循环蛋白与CRC风险之间的关联。采用弹性网络方法来开发CRC风险的蛋白质评分。结果如下：在发现集中，27种蛋白质显示出与CRC风险名义上显著的相关性，其中22种为正相关，5种为负相关。在验证集中，27种蛋白质标志物中有6种与CRC风险显著相关。在合并的发现和验证集的分析中，这些蛋白质水平的每标准差（SD）增加的比值比（OR）为1.54（95%置信区间（CI）：1.15-2.06），CD 79 B; 1.71（95% CI：1.24-2.34）对于DDR 1; 2.04（95% CI：1.39-3.01）; FLRT 2为1.54（95% CI：1.16-2.02）; LTA 4 H为2.09（95% CI：1.47-2.98）; NCR 1为1.88（95% CI：1.35-2.62）。敏感性分析显示，除CD 79 B外，所有蛋白质与排除队列入组后前两年内诊断的病例的相关性一致。此外，基于所鉴定的六种蛋白质开发了五种蛋白质评分，并且在发现集和验证集中均显示出与CRC风险的显著相关性（发现：OR 1-SD = 2.46，95%CI：1.53-3.95;验证：OR 1-SD = 4.16，95%CI：1.92-8.99）。结论：一组五种蛋白质标志物被确定为CRC风险的潜在生物标志物。我们的研究结果提供了新的见解CRC的病因，并可能促进恶性肿瘤的风险评估。
Studies on circulating protein for colorectal cancer risk in a prospective study design is lacking. The aim of the present study was to scan and identify the protein markers by using proteomics technologies in a two-stage case-control study nested within the Shanghai Women’s Health Study (SWHS), a population-based prospective cohort study. In the discovery set, we found 27 circulating proteins with a nominally significant association. Six of them, including CD79B, DDR1, EFNA4, FLRT2, LTA4H, and NCR1, were validated in the validation phase of the study. This study is the first to evaluate over 1000 circulating proteins in prediagnostic blood samples for their associations with CRC risk in East Asians. Background: Proteomics-based technologies are emerging tools used for cancer biomarker discovery. Limited prospective studies have been conducted to evaluate the role of circulating proteins in colorectal cancer (CRC) development. Methods: A two-stage case-control proteomics study nested in the Shanghai Women’s Health Study was conducted. A total of 1104 circulating proteins were measured in the discovery phase, consisting of 100 incident CRC cases and 100 individually matched controls. An additional 60 case-control pairs were selected for validation. Protein profiling at both stages was completed using the Olink platforms. Conditional logistic regression was used to evaluate the associations between circulating proteins and CRC risk. The elastic net method was employed to develop a protein score for CRC risk. Results: In the discovery set, 27 proteins showed a nominally significant association with CRC risk, among which 22 were positively and 5 were inversely associated. Six of the 27 protein markers were significantly associated with CRC risk in the validation set. In the analysis of pooled discovery and validation sets, odds ratios (ORs) per standard deviation (SD) increase in levels of these proteins were 1.54 (95% confidence interval (CI): 1.15–2.06) for CD79B; 1.71 (95% CI: 1.24–2.34) for DDR1; 2.04 (95% CI: 1.39–3.01) for EFNA4; 1.54 (95% CI: 1.16–2.02) for FLRT2; 2.09 (95% CI: 1.47–2.98) for LTA4H and 1.88 (95% CI: 1.35–2.62) for NCR1. Sensitivity analyses showed consistent associations for all proteins with the exclusion of cases diagnosed within the first two years after the cohort enrollment, except for CD79B. Furthermore, a five-protein score was developed based on the six proteins identified and showed significant associations with CRC risk in both discovery and validation sets (Discovery: OR1-SD = 2.46, 95% CI: 1.53–3.95; validation: OR1-SD = 4.16, 95% CI: 1.92–8.99). Conclusions: A panel of five protein markers was identified as potential biomarkers for CRC risk. Our findings provide novel insights into the etiology of CRC and may facilitate the risk assessment of the malignancy.
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影响因子：
5.2
作者：
Harlid S;Gunter MJ;Van Guelpen B
通讯作者：
Van Guelpen B
影响因子：
5.6
作者：
Flintoff, K. A.;Arudchelvan, Y.;Gong, Siew-Ging
通讯作者：
Gong, Siew-Ging
影响因子：
254.7
作者：
Jemal, Ahmedin;Siegel, Rebecca;Thun, Michael J.
通讯作者：
Thun, Michael J.
影响因子：
3.9
作者：
Chen H;Qian J;Werner S;Cuk K;Knebel P;Brenner H
通讯作者：
Brenner H
影响因子：
4.6
作者：
Harlid S;Harbs J;Myte R;Brunius C;Gunter MJ;Palmqvist R;Liu X;Van Guelpen B
通讯作者：
Van Guelpen B