Objective. To improve the diagnostic capacity of serum biomarkers for colorectal cancer (CRC), we introduced three novel indicators, namely, the C-X-C motif chemokine ligand 5 (CXCL5), stanniocalcin 2 (STC2), and chitinase 3 like 1 (CHI3L1) and assessed their performances in the detection of CRC. Methods. A total of 887 serum samples (153 health, 342 polyps, and 392 CRCs) were collected. Concentrations of CXCL5, STC2, and CHI3L1 were measured by the ELISA. CEA and CA199 were determined by electrochemiluminescence. Binary logistic regression was used to build the combination model. ROC analysis was used to evaluate the performance of biomarkers alone or in combination. Results. Model_2 that based on CXCL5, STC2, and CHI3L1 was the best approach in discriminating CRC from non-CRC controls (AUC, 0.943 (0.922–0.960); sensitivity, 0.848; specificity, 0.917; and accuracy, 0.887 in the training cohort and 0.959 (95% CI 0.927–0.980), 0.878, 0.917, and 0.900 in the testing cohort, respectively). In the detection of early CRC, Model_2 revealed AUC, sensitivity, specificity, and accuracy of 0.925 (0.897–0.947), 0.793, 0.917, and 0.886 in the training cohort and those of 0.926 (0.979–0.959), 0.786, 0.931, and 0.898 in the testing cohort. Furthermore, Model_2 exhibited an excellent diagnostic performance in CEA-negative cases (0.938 (0.913–0.957), 0.826, 0.917, and 0.888 in the training cohort and 0.961 (0.925–0.983), 0.887, 0.931, and 0.918 in the testing cohort). As used alone, STC2 achieved the capacities that is second only to that of Model_2 (0.866 (0.837–0.892), 0.859, 0.842, and 0.853 in the training cohort and 0.887 (0.842–0.923), 0.922, 0.799, and 0.853 in the testing cohort). STC2 alone also yielded acceptable results for early CRC detection (0.815 (0.776–0.849), 0.767, 0.849, and 0.829 in the training cohort and 0.870 (0.812–0.914), 0.952, 0.799, and 0.833 in the testing cohort). Moreover, STC2 maintained diagnostic accuracy for CRC patients with negative CEA (0.874 (0.842–0.901), 0.862, 0.849, and 0.853 in the training cohort and 0.898 (0.848–0.936), 0.930, 0.801, and 0.842 in the testing cohort). In comparison, the performances of the CEA and CA199 based Model_1 were far from satisfactory, especially in early cases (0.767 (0.726–0.805), 0.491, 0.863, and 0.771 in the training cohort and 0.817 (0.754–0.870), 0.476, 0.889, and 0.796 in the testing cohort). Conclusions. STC2 was a promising serum biomarker for CRC diagnosis either used alone or in combination with CXCL5 and CHI3L1.

中文翻译：

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CXCL5、STC2和CHI3L1在结直肠癌诊断中的联合疗效

客观。为了提高血清生物标志物对结直肠癌（CRC）的诊断能力，我们引入了三个新指标，即CXC基序趋化因子配体5（CXCL5）、斯钙素2（STC2）和几丁质酶3样1（CHI3L1），并对其进行评估。 CRC检测性能 方法。共收集了 887 份血清样本（153 份健康、342 份息肉和 392 份 CRC）。通过 ELISA 测量 CXCL5、STC2 和 CHI3L1 的浓度。CEA和CA199通过电化学发光测定。使用二元逻辑回归建立组合模型。ROC 分析用于单独或组合评估生物标志物的性能。结果. 基于 CXCL5、STC2 和 CHI3L1 的 Model_2 是区分 CRC 与非 CRC 对照的最佳方法（AUC，0.943 (0.922–0.960)；敏感性，0.848；特异性，0.917；准确度，训练队列中的 0.887 和 0.959 (95% CI 0.927–0.980)、0.878、0.917 和 0.900 在测试队列中，分别）。在早期 CRC 的检测中，Model_2 在训练队列中的 AUC、敏感性、特异性和准确性分别为 0.925（0.897–0.947）、0.793、0.917 和 0.886，在训练队列中为 0.926（0.979–0.959）、0.786、0.931 和在测试队列中为 0.898。此外，Model_2 在 CEA 阴性病例中表现出出色的诊断性能（训练队列中的 0.938（0.913–0.957）、0.826、0.917 和 0.888 以及测试队列中的 0.961（0.925–0.983）、0.887、0.931 和 0.918） . 单独使用时，STC2 的容量仅次于 Model_2（训练队列中的 0.866（0.837-0.892）、0.859、0.842 和 0.853 以及测试队列中的 0.887（0.842-0.923）、0.922、0.799 和 0.853）。单独的 STC2 也为早期 CRC 检测产生了可接受的结果（在训练队列中为 0.815（0.776-0.849）、0.767、0.849 和 0.829，在测试队列中为 0.870（0.812-0.914）、0.952、0.799 和 0.833）。此外，STC2 对 CEA 阴性的 CRC 患者保持了诊断准确性（在训练队列中为 0.874（0.842-0.901）、0.862、0.849 和 0.853，在测试队列中为 0.898（0.848-0.936）、0.930、0.801 和 0.842）。相比之下，基于 CEA 和 CA199 的 Model_1 的性能远不能令人满意，尤其是在早期情况下（0.767（0.726-0.805）、0.491、0.863 和 0.771 在训练队列中和 0.817（0.754-0.870）、0.00）。结论。STC2 是用于 CRC 诊断的有前途的血清生物标志物，可单独使用或与 CXCL5 和 CHI3L1 联合使用。