Dataset Information

Predictive and prognostic value of EPIC1 in patients with breast cancer receiving neoadjuvant chemotherapy.

ABSTRACT:

Background

EPIC1 is an oncogenic long non-coding ribonucleic acid (RNA) that promotes cell growth and cell-cycle progression and inhibits apoptosis in several cancer cell lines. However, clinical studies on EPIC1 in breast cancer, specifically in the neoadjuvant setting, are relatively few.

Methods

Patients treated with weekly paclitaxel-cisplatin-based neoadjuvant chemotherapy after core-needle biopsy were included in the study. Real-time quantitative polymerase chain reaction assays were performed to detect EPIC1 expression.

Results

Among all patients included in this study (n = 111), higher EPIC1 expression was associated with estrogen receptor negativity, human epidermal growth factor receptor 2 positivity, higher Ki67 index, and higher histologic grade. Multivariate analysis suggested that EPIC1 expression was an independent predictive factor for pathological complete response, with a significant interaction between EPIC1 expression and age. The Kaplan-Meier Plotter dataset suggested that the EPIC1 high-expression group showed a worse 10-year distant metastasis-free survival and post-progression survival when compared with the EPIC1 low-expression group. The Cancer Genome Atlas dataset suggested that the overall survival in the EPIC1 high-expression group was inferior to that in the EPIC1 low-expression group, specifically in hormone receptor (HorR)-positive patients and patients aged <50 years. Pathway analysis revealed the top pathways that indicated the potential mechanisms of EPIC1 in chemoresistance, including the daunorubicin and doxorubicin metabolic processes.

Conclusions

Our study suggests that EPIC1 may be a promising biomarker for both neoadjuvant chemosensitivity and long-term clinical outcomes in breast cancer, specifically in the HorR-positive premenopausal subgroup. It may also help identify candidate responders and determine treatment strategies.

SUBMITTER: Xu Y

PROVIDER: S-EPMC7383657 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Predictive and prognostic value of EPIC1 in patients with breast cancer receiving neoadjuvant chemotherapy.

Xu Yaqian Y Wang Yan Y Yuan Chenwei C Sheng Xiaonan X Sha Rui R Dai Huijuan H Zhang Shan S Wang Yaohui Y Lin Yanping Y Zhou Liheng L Xu Shuguang S Zhang Jie J Yin Wenjin W Lu Jinsong J

Therapeutic advances in medical oncology 20200724

<h4>Background</h4>EPIC1 is an oncogenic long non-coding ribonucleic acid (RNA) that promotes cell growth and cell-cycle progression and inhibits apoptosis in several cancer cell lines. However, clinical studies on EPIC1 in breast cancer, specifically in the neoadjuvant setting, are relatively few.<h4>Methods</h4>Patients treated with weekly paclitaxel-cisplatin-based neoadjuvant chemotherapy after core-needle biopsy were included in the study. Real-time quantitative polymerase chain reaction as ...[more]

PMID: 32782487

Similar Datasets

Project description:BackgroundZinc finger E-box binding homeobox 1 (ZEB1) is a molecule involved in the progression of epithelial-to-mesenchymal transition (EMT) in various kinds of cancers. Here, we aimed to determine whether the expression of the ZEB1 protein is related to the response of patients to neoadjuvant therapy as well as their survival outcome.MethodsImmunohistochemistry (IHC) was performed on paraffin-embedded tumor samples from core needle biopsy before neoadjuvant therapy (NAT). Univariate and multivariate logistic regression analyses were used to analyze the associations between the protein expression of ZEB1 and the pathological complete response (pCR) outcome. Kaplan-Meier plots and log-rank tests were used to compare disease-free survival (DFS) between groups. A Cox proportional hazards model was used to calculate the adjusted hazard ratio (HR) with a 95% confidential interval (95% CI).ResultsA total of 75 patients were included in the IHC test. High ZEB1 protein expression was associated with a low pCR rate in both univariate (OR = 0.260, 95% CI 0.082-0.829, p = 0.023) and multivariate (OR = 0.074, 95% CI 0.011-0.475, p = 0.006) logistic regression analyses. High ZEB1 protein expression was also associated with a short DFS according to both the log-rank test (p = 0.023) and Cox proportional hazard model (HR = 9.025, 95% CI 1.024-79.519, p = 0.048). In hormone receptor positive (HorR-positive) patients, high ZEB1 protein expression was also associated with a lower pCR (OR = 0.054, 95% CI 0.007-0.422, p = 0.005) and a poorer DFS (HR = 10.516, 95% CI 1.171-94.435, p = 0.036) compared with low ZEB1 protein expression. In HER2-overexpressing patients, ZEB1 protein expression was also associated with poor survival (p = 0.042).ConclusionsOur results showed that high ZEB1 protein expression was a negative predictive marker of pCR and DFS in neoadjuvant therapy in breast cancer patients and in HorR-positive and HER2-overexpressing subgroups.Trial registration NCT, NCT02199418. Registered 24 July 2014-Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT02199418?term=NCT02199418&rank=1. NCT, NCT 02221999. Registered 21 August 2014-Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT02221999?term=NCT02221999&rank=1.

Project description:ObjectiveThis study aims at investigating the potential prognostic significance of the breast immune prognostic index (BIPI) in breast cancer patients who received neoadjuvant chemotherapy (NACT).MethodsThe optimal cutoff value was calculated through the receiver operating characteristic curve (ROC). The correlations between BIPI and clinicopathologic characteristics were determined by the chi-square test or Fisher's exact test. The Kaplan-Meier method was used to estimate the survival probability, and the log-rank test was used to analyze the differences in the survival probability among patients. The univariate and multivariate Cox proportional hazard regression model was used to screen the independent prognostic factors. A prognostic nomogram for disease-free survival (DFS) and overall survival (OS) was built on the basis of the multivariate analyses. Furthermore, the calibration curve and decision curve analysis (DCA) were used to assess the predictive performance of the nomogram.ResultsAll enrolled patients were split into three subgroups based on the BIPI score. The mean DFS and OS of the BIPI score 0 group and BIPI score 1 group were significantly longer than those of the BIPI score 2 group (42.02 vs. 38.61 vs. 26.01 months, 77.61 vs. 71.83 vs. 53.15 months; p < 0.05). Univariate and multivariate analyses indicated that BIPI was an independent prognostic factor for patients' DFS and OS (DFS, hazard ratio (HR): 6.720, 95% confidence interval (CI): 1.629-27.717; OS, HR: 8.006, 95% CI: 1.638-39.119). A nomogram with a C-index of 0.873 (95% CI: 0.779-0.966) and 0.801 (95% CI: 0.702-0.901) had a favorable performance for predicting DFS and OS survival rates for clinical use by combining immune scores with other clinical features. The calibration curves at 1-, 3-, and 5-year survival suggested a good consistency between the predicted and actual DFS and OS probability. The DCA demonstrated that the constructed nomogram had better clinical predictive usefulness than only BIPI in predictive clinical applications of 5-year DFS and OS prognostic assessments.ConclusionsThe patients with low BIPI score have better prognoses and longer DFS and OS. Furthermore, the BIPI-based nomogram may serve as a convenient prognostic tool for breast cancer and help in clinical decision-making.

Dataset Information

Predictive and prognostic value of EPIC1 in patients with breast cancer receiving neoadjuvant chemotherapy.

Background

Methods

Results

Conclusions

Publications

Predictive and prognostic value of EPIC1 in patients with breast cancer receiving neoadjuvant chemotherapy.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets