Song Xiao-Qing, Shao Zhi-Ming
Key Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.
Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
Transl Cancer Res. 2024 Apr 30;13(4):1707-1720. doi: 10.21037/tcr-23-1554. Epub 2024 Apr 25.
Triple-negative breast cancer (TNBC), a type of breast cancer, lacks immune-related markers that can be used for prognosis or prediction. Therefore, we created a predictive framework for TNBC using a risk assessment.
Our previous study group consisted of 360 individuals who were diagnosed with TNBC through pathology using RNA sequencing and had clinical data from Fudan University Shanghai Cancer Center (FUSCC). A risk scoring model was constructed using the Cox regression method with the least absolute shrinkage and selection operator (LASSO). A multivariate Cox regression analysis was utilized to develop the prediction model, which was then assessed using the consistency index and calibration plots. The validation cohort of The Cancer Genome Atlas (TCGA) TNBC confirmed the strength of the signatures' predictive value.
The prognostic risk score model included 12 genes: , , , , , , , , , , , and . The receiver operator characteristic (ROC) curves for survivability values at 1, 3, and 5 years in the FUSCC TNBC cohort demonstrated area under the curve (AUC) values of 0.78, 0.83, and 0.75, respectively. These results indicated a high level of accuracy in predicting outcomes, which was further confirmed through validation using TCGA database. The patients in the high-risk group showed worse prognoses and lower levels of immune cell infiltration, specifically T cells, than those in the low-risk group. Furthermore, the low-risk group exhibited a significant upregulation of genes that encode immune checkpoints, including and , suggesting that immunotherapy may yield enhanced efficacy within this particular group.
In conclusion, the prognostic signature consisting of 12 genes can assist in the choice of immunotherapy for TNBC.
三阴性乳腺癌（TNBC）是一种乳腺癌，缺乏可用于预后或预测的免疫相关标志物。因此，我们使用风险评估创建了一个TNBC预测框架。
我们之前的研究组由360名通过RNA测序经病理诊断为TNBC且拥有来自复旦大学附属肿瘤医院（FUSCC）临床数据的个体组成。使用具有最小绝对收缩和选择算子（LASSO）的Cox回归方法构建风险评分模型。利用多变量Cox回归分析来开发预测模型，然后使用一致性指数和校准图对其进行评估。癌症基因组图谱（TCGA）TNBC的验证队列证实了特征预测价值的强度。
预后风险评分模型包括12个基因： ， ， ， ， ， ， ， ， ， ， ，和 。FUSCC TNBC队列中1年、3年和5年生存值的受试者工作特征（ROC）曲线显示曲线下面积（AUC）值分别为0.78、0.83和0.75。这些结果表明在预测结果方面具有较高的准确性，通过使用TCGA数据库进行验证进一步得到证实。高风险组的患者预后较差，免疫细胞浸润水平较低，特别是 T细胞，低于低风险组。此外，低风险组表现出编码免疫检查点的基因显著上调，包括 和 ，这表明免疫疗法在该特定组中可能产生更高的疗效。
总之，由12个基因组成的预后特征可有助于TNBC免疫疗法的选择。
