Prognostic value of a new clinical-genomic model to predict 10-year risk of recurrence in patients with operable breast cancer.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 530-530
Author(s):  
Lei Lei ◽  
Tzu-Ting Huang ◽  
Andre Ching-Hsuan Chen ◽  
Tzu-Pin Lu ◽  
Skye Hung-Chun Cheng

530 Background: Searching for a specific biomarker to predict long-term risk of recurrence for all breast cancer subtypes is challenging. DGM-CM6 (Distant Genetic Model-Clinical variable Model 6) is a new clinical-genomic prognostic model developed from the 18-gene panel which was reported previously. This study aims to validate the long-term prognostic value of this new model in all subtypes of operable breast cancer patients. Methods: We included 752 operable breast cancer patients with stage I-III in all subtypes treated in a Cancer Center from 2005 to 2014 as the internal validation (IV) cohort. The median follow-up was 94.1 months. Meanwhile, Affymetrix U133P2 (n = 1139) data obtained from GEO (GSE9195/16391/17907/19615/20711/21653/42568, EMTAB365) were collected as the external validation (EV) dataset. The prognostic effect of DGM-CM6 was then evaluated by uni- and multivariate analyses. The low- and high-risk patients ( < 33 or ≥ 33 as cut-off value) classified by DGM-CM6 were evaluated by the 10-year distant relapse-free interval (DRFI), relapse-free interval (RFI), relapse-free survival (RFS) and distant relapse-free survival (DRFS), respectively. We further compared the predictive performance between DGM-CM6/DGM and PAM50-ROR score in our IV dataset. Results: In the IV dataset, DGM-CM6 was proved to be an independent prognostic factor by multivariate analysis with hazard ratios of 3.1 (1.6-6.0) for RFS (P = 0.0009) and 3.2 (1.6-6.3) for DRFS (P = 0.0009). Significant differences were observed between low- and high-risk groups with 10-year RFI (94.0% vs. 83.5%, P < 0.0001), RFS (90.0% vs. 80.5%, P = 0.0003), DRFI (94.1% vs. 85.0%, P < 0.0001), and DRFS (90.1% vs. 81.9%, P = 0.0004), respectively. The prognostic value of RFS was convinced in the EV dataset (HR = 1.34, P = 0.00052) by the DGM only. According to C-index estimate analysis, DGM appeared to have better performance comparing with PAM50 ROR score in prediction of long-term DR, DRFS, RFI, and RFS in N0 patients (C index for distant recurrence: 0.582 by DGM, 0.528 by ROR). Conclusions: DGM-CM6 could be a new long-term prognostic model to be applied in all subtypes of operable breast cancer patients. Further validation in a large scale of clinical trials is needed.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. e11532-e11532
Author(s):  
Hee-Chul Shin ◽  
Wonshik Han ◽  
Hyeong-Gon Moon ◽  
Woo Kyung Moon ◽  
Seock-Ah Im ◽  
...  

e11532 Background: Neoadjuvant chemotherapy (NCT) is a reasonable option for operable breast cancer in terms of downsizing large tumor and increasing the rate of breast-conserving surgery (BCS). However, BCS in patients with large breast tumors down-staged by NCT remains still controversial because of the possibility of residual tumor and resistance to NCT. Aims of this study were to evaluate the long-term survival results of patients who received NCT and BCS compared to patients who received BCS first and to compare recurrence and survival rates between patients who received preplanned BCS and those who received down-staged BCS among patients who underwent NCT. Methods: Between 2000 and 2007, 70 patients with clinical stage III breast cancer who received BCS after NCT (NCT group) and 72 patients with clinical stage III breast cancer who underwent BCS first (Surgery group) were retrospectively reviewed. Among 70 patients received NCT, 45 patients (64.3%) received preplanned BCS (preplanned BCS group) and 25 patients (35.7%) received down-staged BCS (down-staged BCS group). The long-term results including ipsilateral breast tumor recurrence (IBTR), locoregional recurrence (LRR), disease recurrence and survival rates were compared with groups. Results: There was no significant difference in IBTR-free survival, LRR-free survival rates, disease-free survival and overall survival rates between the NCT and the Surgery group (p=0.971, p=0.294, p=0.863 and p=0.933, respectively). Among patients who received NCT, IBTR-free survival, LRR-free survival, disease-free survival and overall survival rates was not also different between the preplanned BCS group and the down-staged BCS group (p=0.278, p=0.501, p=0.776 and p=0.412, respectively). Conclusions: Our study demonstrated that patients who received BCS after NCT showed similar long-term resutls compared to patients who received BCS first in clinical stage III breast cancer patients. Also, down-staged BCS shows is oncologically as safe as preplanned BCS in clinical stage III breast cancer patients in terms of recurrence and survival.


2021 ◽  
Author(s):  
Yuhao Xu ◽  
Yaoqiang Du ◽  
Qinghui Zheng ◽  
Hongchao Tang ◽  
Yangyang Qian ◽  
...  

Abstract Background Recent years, the breast cancer became the most commonly diagnosed cancer. The use of neoadjuvant chemotherapy (NACT) makes a significant contribution to chemotherapy in breast cancer. We aimed to develop the novel model as a predictor of distant relapse-free survival (DRFS) in breast cancer patients receiving taxane and anthracycline-based NACT. Methods We collected the mRNA expression datasets of patients from GSE25055 and GSE25065 in Gene Expression Omnibus (GEO). Univariate and Multivariate Cox Regression Analyses were conducted to achieve the prognostic genes that associated with DRFS. Moreover, the E2F targets genes were obtained from GSEA. We obtained the intersection genes between the prognostic genes and E2F target genes, then validated in GSE32603 dataset. And we established a nomogram model based on PTTG1 expression level and several clinical characteristics. Results A novel nomogram was conducted. The receiver operating characteristic (AUC = 0.849), C-index (0.805) and calibration plots were applied to assess the effect of this model. Conclusion Our study found that the E2F target genes, such as the PTTG1 may serve as a potential biomarker in breast cancer, and provided superior estimation of DRFS, which can guide the clinical practice in NACT of breast cancer.


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