A Novel Seven Gene Signature-Based Prognostic Model to Predict Distant Metastasis of Lymph Node-Negative Triple-Negative Breast Cancer.
A Novel Seven Gene Signature-Based Prognostic Model to Predict Distant Metastasis of Lymph Node-Negative Triple-Negative Breast Cancer.
复制标题
一种基于七基因特征的新型预后模型来预测淋巴结阴性三阴性乳腺癌的远处转移
DOI：
10.3389/fonc.2021.746763
复制
发表时间：
2021
影响因子：
4.7
通讯作者：
Shao Z
中科院分区：
文献类型：
--
作者：
Peng W;Lin C;Jing S;Su G;Jin X;Di G;Shao Z
背景 尽管进行辅助化疗，淋巴结阴性三阴性乳腺癌（TNBC）的预后仍然比其他亚型差。需要可靠的预后生物标志物来识别远处转移高风险的淋巴结阴性 TNBC 患者并优化个体化治疗。方法对202例淋巴结阴性TNBC患者的原发肿瘤组织RNA测序数据和临床病理资料进行分析。该队列被随机分为训练集和验证集。使用最小绝对收缩和选择算子Cox回归和多元Cox回归构建预后模型。结果使用训练集构建了临床预后模型、七基因特征和组合模型，并使用验证集进行了验证。七基因特征是根据收缩校正后与远处转移相关的基因组变量建立的。使用七基因特征，低风险组和高风险组之间的远处转移风险差异具有统计学意义（训练集：P < 0.001；验证集：P = 0.039）。组合模型在训练集中表现出显着性（P < 0.001），并且在验证集中表现出显着性（P = 0.071）。相对于训练数据中的临床特征，七基因特征显示出更高的预后准确性（4 年 ROC 的 AUC 值，0.879 vs. 0.699，P = 0.046）。此外，综合临床和基因特征还显示出相对于临床特征的预后准确性的提高（4年ROC的AUC值：0.888 vs. 0.699，P = 0.029；5年ROC的AUC值：0.882 vs. 0.693，P = 0.038）。利用七基因特征、患者年龄和肿瘤大小构建了列线图模型。结论 所提出的签名可以改善淋巴结阴性 TNBC 患者的风险分层。高危淋巴结阴性 TNBC 患者可能会受益于治疗升级。
Background The prognosis of lymph node-negative triple-negative breast cancer (TNBC) is still worse than that of other subtypes despite adjuvant chemotherapy. Reliable prognostic biomarkers are required to identify lymph node-negative TNBC patients at a high risk of distant metastasis and optimize individual treatment. Methods We analyzed the RNA sequencing data of primary tumor tissue and the clinicopathological data of 202 lymph node-negative TNBC patients. The cohort was randomly divided into training and validation sets. Least absolute shrinkage and selection operator Cox regression and multivariate Cox regression were used to construct the prognostic model. Results A clinical prognostic model, seven-gene signature, and combined model were constructed using the training set and validated using the validation set. The seven-gene signature was established based on the genomic variables associated with distant metastasis after shrinkage correction. The difference in the risk of distant metastasis between the low- and high-risk groups was statistically significant using the seven-gene signature (training set: P < 0.001; validation set: P = 0.039). The combined model showed significance in the training set (P < 0.001) and trended toward significance in the validation set (P = 0.071). The seven-gene signature showed improved prognostic accuracy relative to the clinical signature in the training data (AUC value of 4-year ROC, 0.879 vs. 0.699, P = 0.046). Moreover, the composite clinical and gene signature also showed improved prognostic accuracy relative to the clinical signature (AUC value of 4-year ROC: 0.888 vs. 0.699, P = 0.029; AUC value of 5-year ROC: 0.882 vs. 0.693, P = 0.038). A nomogram model was constructed with the seven-gene signature, patient age, and tumor size. Conclusions The proposed signature may improve the risk stratification of lymph node-negative TNBC patients. High-risk lymph node-negative TNBC patients may benefit from treatment escalation.
登录
查看更多内容
DOI：
10.1093/jnci/djt376
发表时间：
2014-02
期刊：
Journal of the National Cancer Institute
影响因子：
--
作者：
Liu NQ;Stingl C;Look MP;Smid M;Braakman RB;De Marchi T;Sieuwerts AM;Span PN;Sweep FC;Linderholm BK;Mangia A;Paradiso A;Dirix LY;Van Laere SJ;Luider TM;Martens JW;Foekens JA;Umar A
通讯作者：
Umar A
三阴性乳腺癌的基因组和转录组景观：亚型和治疗策略
影响因子：
50.3
作者：
Jiang, Yi-Zhou;Ma, Ding;Shao, Zhi-Ming
通讯作者：
Shao, Zhi-Ming
全基因组 SNP 标记揭示中国和西方猪的遗传多样性、连锁不平衡和选择特征
影响因子：
3.7
作者：
Ai H;Huang L;Ren J
通讯作者：
Ren J
影响因子：
3.8
作者：
Kwon JH;Kim YJ;Lee KW;Oh DY;Park SY;Kim JH;Chie EK;Kim SW;Im SA;Kim IA;Kim TY;Park IA;Noh DY;Bang YJ;Ha SW
通讯作者：
Ha SW
影响因子：
45.3
作者：
Bonastre, Julia;Marguet, Sophie;Saghatchian, Mahasti
通讯作者：
Saghatchian, Mahasti