Long-term maintenance of prognostic value of survivin protein expression in T4 breast cancer patients: 10-year results from a single institution

Abstract Background: Breast cancer is one of the most common tumors for women worldwide. Thrombospondins (THBSs) are reported to play important roles in various cellular processes and are involved in the occurrence and development of human cancers. However, the expression and prognostic value of THBSs family in breast cancer remain unclear.Methods: In this study, we examined the genes and protein expression levels of THBSs and their prognostic value by synthesizing several mainstream databases, including Oncomine, Human Protein Atlas (HPA), UALCAN, and KM Plotter. We also analyzed THBS interaction networks, genetic alterations, functional enrichment, and drug sensitivity with several publicly accessible databases, including GEPIA, GeneMANIA, STRING, cBioPortal, Metascape and NCI-60 database.Results: The results showed that the mRNA expression levels of THBS1, THBS2, THBS3, and THBS5 in breast cancer tissues were significantly higher than in normal tissues. The mRNA expression levels of THBS4 were different in different subtypes of breast cancer, and the protein expression levels of THBS1, THBS2, and THBS4 in breast cancer tissues were higher than in normal breast tissues. Survival analysis showed that breast cancer patients with high THBS1 gene expression showed worse overall survival (OS), relapse-free survival (RFS), and post-progression survival (PPS), and breast cancer patients with high THBS2 gene expression also showed worse RFS. Conversely, lower THBS3 levels predicted worse RFS, and lower THBS4 levels predicted worse OS, RFS, and distant metastasis-free survival (DMFS). Conclusions: These results suggest that THBSs may be potential biomarkers for breast cancer.

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674a Prognostic value of steroid receptors after long term follow up of 2257 operable breast cancer patients

European Journal of Cancer ◽

10.1016/0959-8049(95)95923-t ◽

1995 ◽

Vol 31 ◽

pp. S141 ◽

Cited By ~ 1

Author(s):

M.P. Pichon ◽

P. Broet ◽

H. Magdelenat ◽

J.C. Delarue ◽

J. Spyratos ◽

...

Keyword(s):

Breast Cancer ◽

Cancer Patients ◽

Prognostic Value ◽

Steroid Receptors ◽

Operable Breast Cancer ◽

Breast Cancer Patients ◽

Long Term Follow Up

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

Journal of Clinical Oncology ◽

10.1200/jco.2019.37.15_suppl.530 ◽

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

Keyword(s):

Breast Cancer ◽

Cancer Patients ◽

Prognostic Value ◽

Prognostic Model ◽

Operable Breast Cancer ◽

Breast Cancer Patients ◽

Free Survival ◽

Distant Relapse ◽

Clinical Genomic

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.

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