Yu Long, Wang Hao, Wang Fulong, Guo Jian, Xiao Binyi, Hou Zhenlin, Lu Zhenhai, Pan Zhizhong, Zhou Yaxian, Ye Sibin, Wan Desen, Lin Bo, Ou Qingjian, Fang Yujing
State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, China.
Department of Colorectal Surgery, Sun Yat-Sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, China.
Clin Transl Oncol. 2025 Jan;27(1):277-290. doi: 10.1007/s12094-024-03566-6. Epub 2024 Jul 4.
To develop and validate a serum protein nomogram for colorectal cancer (CRC) screening.
The serum protein characteristics were extracted from an independent sample containing 30 colorectal cancer and 12 polyp tissues along with their paired samples, and different serum protein expression profiles were validated using RNA microarrays. The prediction model was developed in a training cohort that included 1345 patients clinicopathologically confirmed CRC and 518 normal participants, and data were gathered from November 2011 to January 2017. The lasso logistic regression model was employed for features selection and serum nomogram building. An internal validation cohort containing 576 CRC patients and 222 normal participants was assessed.
Serum signatures containing 27 secreted proteins were significantly differentially expressed in polyps and CRC compared to paired normal tissue, and REG family proteins were selected as potential predictors. The C-index of the nomogram1 (based on Lasso logistic regression model) which contains REG1A, REG3A, CEA and age was 0.913 (95% CI, 0.899 to 0.928) and was well calibrated. Addition of CA199 to the nomogram failed to show incremental prognostic value, as shown in nomogram2 (based on logistic regression model). Application of the nomogram1 in the independent validation cohort had similar discrimination (C-index, 0.912 [95% CI, 0.890 to 0.934]) and good calibration. The decision curve (DCA) and clinical impact curve (ICI) analysis demonstrated that nomogram1 was clinically useful.
This study presents a serum nomogram that included REG1A, REG3A, CEA and age, which can be convenient for screening of colorectal cancer.
开发并验证用于结直肠癌（CRC）筛查的血清蛋白列线图。
从一个包含30例结直肠癌组织、12例息肉组织及其配对样本的独立样本中提取血清蛋白特征，并使用RNA微阵列验证不同的血清蛋白表达谱。在一个训练队列中建立预测模型，该队列包括1345例经临床病理确诊的CRC患者和518名正常参与者，数据收集时间为2011年11月至2017年1月。采用套索逻辑回归模型进行特征选择和血清列线图构建。评估了一个包含576例CRC患者和222名正常参与者的内部验证队列。
与配对的正常组织相比，包含27种分泌蛋白的血清标志物在息肉和CRC中显著差异表达，REG家族蛋白被选为潜在预测因子。包含REG1A、REG3A、癌胚抗原（CEA）和年龄的列线图1（基于套索逻辑回归模型）的C指数为0.913（95%置信区间，0.899至0.928），且校准良好。如列线图2（基于逻辑回归模型）所示，将糖类抗原199（CA199）添加到列线图中未显示出增量预后价值。列线图1在独立验证队列中的应用具有相似的区分度（C指数，0.912 [95%置信区间，0.890至0.934]）和良好的校准。决策曲线（DCA）和临床影响曲线（ICI）分析表明列线图1具有临床实用性。
本研究提出了一种包含REG1A、REG3A、CEA和年龄的血清列线图，可方便用于结直肠癌的筛查。
