Oops, you're using an old version of your browser so some of the features on this page may not be displaying properly.

MINIMAL Requirements: Google Chrome 24+Mozilla Firefox 20+Internet Explorer 11Opera 15–18Apple Safari 7SeaMonkey 2.15-2.23

ePoster Display

255P - Propreseer: A reliable, collaborative prognostic model for tamoxifen-resistance breast cancer

Date

16 Sep 2021

Session

ePoster Display

Topics

Tumour Site

Breast Cancer

Presenters

Weiqi Nian

Citation

Annals of Oncology (2021) 32 (suppl_5): S457-S515. 10.1016/annonc/annonc689

Authors

W. Nian1, Z. Kai2, C. Xia3, P. Luo2, F. Pang4, Z. Yan2

Author affiliations

  • 1 Phase I Clinical Trial Ward, Chongqing Key Laboratory Of Translational Research For Cancer Metastasis And Individualized Treatment, Chongqing University Cancer Hospital, 400030 - Chongqing/CN
  • 2 Bioinformatics, Shanghai Topgen Biomedical Technology Co., Ltd., 200120 - Shanghai/CN
  • 3 Medical, Shanghai Topgen Biomedical Technology Co., Ltd., 201203 - Shanghai/CN
  • 4 Medical, Shanghai Topgen Biomedical Technology Co., Ltd., 200120 - Shanghai/CN

Resources

Login to get immediate access to this content.

If you do not have an ESMO account, please create one for free.

Abstract 255P

Background

Breast cancer by far has risen to the most common cancer overall. The estrogen receptor (ER) is expressed in 75% of breast cancers in general. Tamoxifen (TAM) has been approved for reducing relapse by approximately 40%-50% in ER positive metastatic breast cancer. There are still approximately 40% patients showing primary or secondary TAM drug resistance to endocrine therapies, leading to relapse and metastasis. It’s urgent to develop an approach for evaluation of prognosis and drug resistance at an early stage. Here comes Propreseer applied in TAM-resistance breast cancer.

Methods

We presented a prognostic model called Propreseer to facilitate the routine of large-scale long-running prognostic analysis. Public databases like Gene Expression Omnibus (GEO) and Cancer Genome Atlas (TCGA), and bio-statistics were involved, and 737 cases with breast cancer and 584 cases with ovarian cancer were considered. By Propreseer, the patients were then divided into high-risk group and low-risk group according to the risk value output, and the correlations among the risk value, clinical indexes and prognosis were analyzed.

Results

By Propreseer, six differentially expressed lncRNA (ENG00000230440, ENG00000231128, ENG00000232986, ENG00000249346, ENG00000253898, and ENG00000258412) were identified (all P<0.05). The mortality rate in high-risk group was higher than that in low-risk group(P<0.01), indicating the overall survival was worse in high-risk group. The overall survival in high-risk group was shorter than that in low-risk group(P<0.01), presenting consistency both in training set (P =7*10-7) and validation set (P =0.008). Area under the curve (AUC) was 0.750 from three-year track, and 0.680 from five-year track, confirming that Propreseer had certain accuracy. Risk value remained an independent prognostic factor (all P<0.001), and was significantly correlated with TNM stage (P<0.05) and lymph node metastasis (P<0.05).

Conclusions

Propreseer had certain value in prognostic for TAM-resistance breast cancer, providing new target molecules for further use in combination therapies, molecular mechanisms and potential drug targets.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

The authors.

Funding

Has not received any funding.

Disclosure

All authors have declared no conflicts of interest.

This site uses cookies. Some of these cookies are essential, while others help us improve your experience by providing insights into how the site is being used.

For more detailed information on the cookies we use, please check our Privacy Policy.

Customise settings
  • Necessary cookies enable core functionality. The website cannot function properly without these cookies, and you can only disable them by changing your browser preferences.