Expression and clinical significance of undifferentiated embryonic cell transcription factor 1 in breast cancer.

Background: At present, due to the heterogeneity of breast cancer, common tumor markers have certain limitations in clinical prognostic evaluation. This suggests an unmet need for markers to predict clinical outcomes and potentially guide targeted therapies. The present study sought to explore the expression level and clinical significance of undifferentiated embryonic cell transcription factor 1 (UTF1) in breast cancer. Methods: Immunohistochemistry (IHC) was used to detect the expression of UTF1 in 221 breast cancer samples. The clinical significance of UTF1 protein expression in breast cancer tissues was evaluated by combining clinicopathological parameters and UTF1 expression profile. We performed 3-(4,5-dimethylthiazolyl-2)-2,5-diphenyltetrazolium bromide (MTT) and clone formation assays to evaluate the effect of UTF1 on Bcap37 cell proliferation. Wound healing assay and transwell migration assay were used to evaluate the changes of cell invasion and migration ability, respectively. All experiments were performed with 3 biological replicates. Genomic differences after UTF1 overexpression were evaluated by RNA sequencing technology and the possible functions and regulatory mechanisms were elucidated. Results: The findings showed that UTF1 expression level was significantly correlated with tumor size (P=0.004), but not with patient age, tumor histological stage, lymph node metastasis, as well as estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor-2 (HER-2), and Ki67 expression levels. Kaplan-Meier survival analysis and Cox proportional hazard model indicated that UTF1 expression was significantly associated with overall survival (OS) time of breast cancer patients. The median survival time of patients with high expression level of UTF1 was shorter compared with that of patients with low UTF1 expression level. The results of cell experiments showed that UTF1 overexpression could significantly promote the growth, proliferation, migration, and invasion of breast cancer cells. The RNA sequencing results showed that UTF1 was not only closely related to apoptosis genes, but also closely related to the nuclear factor (NF)-kappa B pathway. Conclusions: The findings of the current study indicate that UTF1 is involved in occurrence and tumor progression and is significantly associated with prognosis of breast cancer patients.

Estrogen receptor-negative/progesterone receptor-positive and her-2-negative breast cancer might no longer be classified as hormone receptor-positive breast cancer.

BACKGROUND: The single progesterone receptor (PR)-positive phenotype (estrogen receptor (ER)-/PR + , sPR positive) is an infrequent and independent biological entity. However, the prognosis of patients with sPR-positive and her-2-negative phenotype is still controversial, and it is not always easy to decide treatment strategies for them. METHODS: Patients during 2010-2014 were identified from Surveillance, Epidemiology, and End Results (SEER) database. The Kaplan-Meier method was used to evaluate cancer-specific survival (CSS). The propensity score matching (PSM) method was used to balance differences of characteristics in groups. The Life-Table method was used to calculate 5-year CSS rates and the annual hazard rate of death (HRD). RESULTS: A total of 97,527 patients were included, and only 745 (0.76%) patients were sPR-positive phenotype. The majority of sPR-positive breast cancer were basal-like subtype. Survival analysis showed that the sPR-positive breast cancer had similar prognosis comparing to double hormonal receptor-negative (ER-/PR-, dHoR-negative) breast cancer, and had the highest HRD during the initial 1-2 years of follow-up, then maintained the HRD of almost zero during the late years of follow-up. CONCLUSIONS: The patients with sPR-positive and her-2-negative breast cancer, similar to dHoR-negative breast cancer, had a worse survival, and could benefit from chemotherapy significantly. However, the escalating endocrine therapy was not recommended for sPR-positive patients. The patients with sPR positive should be excluded from future clinical trials concerning endocrine therapy.

How Young Is Too Young in Breast Cancer?-Young Breast Cancer Is Not a Unique Biological Subtype.

BACKGROUND: There is no uniformly adopted cutoff value to define "young patients" with breast cancer. This study was designed to determine an optimal cutoff value, to investigate prognostic factors and to explore gene expression profiles of young female breast cancer. MATERIALS AND METHODS: The Surveillance, Epidemiology, and End Results database was examined to identify cases of female breast cancer diagnosed between 2000 and 2007. The optimal cutoff value for young age was determined using the X-tile program (Yale University, version 3.6.1). Age-specific gene expression profiles were explored using RNA sequence data from the Cancer Genome Atlas database. RESULTS: The age of 40 years was determined as the optimal cutoff value. Among 94,087 patients, 12,755 were aged 40 years or younger (younger group), and 81,332 were older (older group). The 5- and 10-year cancer-specific survival rates in younger and older groups were 88.74% and 80.65%, respectively, and 93.22% and 88.43%, respectively (P < .001). Univariate and multivariate analyses indicated younger patients had worse prognosis. Subgroup analysis according to estrogen receptor (ER) showed the risk for cancer-specific death of ER-positive (ER+) younger patients increased by approximately 2 times (hazard ratio, 1.96) compared with ER+ older patients. We failed to find any age-related gene in 509 patients after adjusting according to subtype (50-gene prediction analysis of a microarray) and histological type. CONCLUSION: The age of 40 years is a reasonable cutoff value for defining "young." Young patients with breast cancer, especially those in the ER+ subgroup, have worse prognosis. However, we found that young breast cancer is not a unique biological entity, and therefore, a lack of new potential targets.

Clinical Nomogram for Predicting Survival Outcomes in Early Mucinous Breast Cancer.

BACKGROUND: The features related to the prognosis of patients with mucinous breast cancer (MBC) remain controversial. We aimed to explore the prognostic factors of MBC and develop a nomogram for predicting survival outcomes. METHODS: The Surveillance, Epidemiology, and End Results (SEER) database was searched to identify 139611 women with resectable breast cancer from 1990 to 2007. Survival curves were generated using Kaplan-Meier methods. The 5-year and 10-year cancer-specific survival (CSS) rates were calculated using the Life-Table method. Based on Cox models, a nomogram was constructed to predict the probabilities of CSS for an individual patient. The competing risk regression model was used to analyse the specific survival of patients with MBC. RESULTS: There were 136569 (97.82%) infiltrative ductal cancer (IDC) patients and 3042 (2.18%) MBC patients. Patients with MBC had less lymph node involvement, a higher frequency of well-differentiated lesions, and more estrogen receptor (ER)-positive tumors. Patients with MBC had significantly higher 5 and10-year CSS rates (98.23 and 96.03%, respectively) than patients with IDC (91.44 and 85.48%, respectively). Univariate and multivariate analyses showed that MBC was an independent factor for better prognosis. As for patients with MBC, the event of death caused by another disease exceeded the event of death caused by breast cancer. A competing risk regression model further showed that lymph node involvement, poorly differentiated grade and advanced T-classification were independent factors of poor prognosis in patients with MBC. The Nomogram can accurately predict CSS with a high C-index (0.816). Risk scores developed from the nomogram can more accurately predict the prognosis of patients with MBC (C-index = 0.789) than the traditional TNM system (C-index = 0.704, P< 0.001). CONCLUSIONS: Patients with MBC have a better prognosis than patients with IDC. Nomograms could help clinicians make more informed decisions in clinical practice. The competing risk regression model, as a more rational model, is recommended for use in the survival analysis of patients with MBC in the future.

[Efficacy of neoadjuvant chemotherapy with FEC and TEC regimen on breast cancer].

BACKGROUND AND OBJECTIVE: Neoadjuvant chemotherapy can remarkably decrease tumor size and stage, and improve the efficacy of comprehensive treatment on breast carcinoma. This study was to investigate the efficacy of neoadjuvant chemotherapy with FEC and TEC regimen on breast cancer. METHODS: From April 1998 to April 2004, 112 breast cancer patients were treated with neoadjuvant chemotherapy. Among them, 77 were treated with FEC regimen and 35 with TEC regimen for 2-3 cycles before operation. Simultaneously, 105 breast cancer patients who only received postoperative chemotherapy were regarded as control. RESULTS: All patients were followed up for 10-107 months (median, 61.4 months). After neoadjuvant chemotherapy, 31 patients (27.7%) had clinical complete remission, and the total response rate was 79.5%. The 5-year disease-free and overall survival rates were significantly higher in neoadjuvant chemotherapy group than in control group (67.2% vs. 49.4%, chi(2)=4.092, P=0.043; 84.7% vs. 69.1%, chi(2)=4.034, P=0.045). CONCLUSION: Neoadjuvant chemotherapy with FEC and TEC regimens is an effective treatment for operable breast cancers, and can prolong the long-term survival and disease-free survival after operation.