Search

In cancer cells, loss of E-cadherin gene expression caused dysfunction of the cell-cell junction system, triggering cancer invasion and metastasis. Therefore, E-cadherin is an important tumor-suppressor gene. To understand how E-cadherin gene expression is regulated in cancer cells, we have used E-cadherin-positive and -negative expressing cells to find out the possible up- or downregulating transcription factors in human E-cadherin regulatory sequences. Functional analysis of human E-cadherin regulatory sequences constructs indicated that AML1, Sp1, and p300 may play important roles in promoting E-cadherin expression. in addition, we found there are four HNF3-binding sites in human E-cadherin regulatory sequences. The exogenous HNF3 can enhance the E-cadherin promoter activity in metastatic breast cancer cells and the met astatic breast cancer cells stably transfected with HNF3 showed re-expression of E-cadherin. The HNF3 stable transfectants changed from mesenchymal-like into epithelial morphology. The trans-well assays showed the re-expressed E-cadherin reduced cell motility of metastatic breast cancer cells. These results suggested HNF3 may play important roles in the upregulation of the E-cadherin promoter, with the consequent re-expression of E-cadherin, thus reducing the met astatic potential of breast cancer cells. These findings suggested HNF3 plays important roles in the upregulation of the E-cadherin gene and may be able to reduce the motility of metastatic breast cancer cells. [ABSTRACT FROM AUTHOR]

The management of metaplastic breast carcinoma (MBC) has largely paralleled the paradigms used for invasive ductal carcinoma (IDC) in the current National Comprehensive Cancer Network guidelines of breast cancer. However, patients with IDC and MBC have been shown to have a different prognosis, and there are significant differences in risk and failure patterns after treatment. The purpose of this study was to compare breast cancer specific survival (BCSS) and hazard function between IDC and MBC. We included patients from the Surveillance, Epidemiology, and End Results program with stage I-III IDC and MBC between 2000 and 2012. Statistical analyses were including chi-square analysis, life-table methods, multivariate Cox proportional hazards models, and propensity score matching (PSM). We identified 294,719 patients; 293,199 patients with IDC and 1520 patients with MBC. Multivariate analyses showed that the MBC subtype had significantly lower BCSS than the IDC subtype before and after PSM (p < 0.001). There were significant differences in the hazard curve between IDC and MBC. The hazard curve for breast cancer mortality in the IDC cohort peaked at 3 years (2%), and then changed to a slowly decreasing plateau after prolonged follow up. However, the hazard curve for breast cancer mortality in the MBC cohort peaked at 2 years (7%), then declined sharply between 3 and 6 years, and changed to a low death rate after a follow-up time exceeding 6 years. Subgroup analyses revealed that the hazard curves significantly differed between IDC and MBC after stratifying by tumor stage and hormone receptor status. Our study suggests that patients with MBC should receive more effective systemic agents and intensive follow-up because of their significantly augmented risk of death compared to IDC patients. [ABSTRACT FROM AUTHOR]

The challenge of decoding information about complex diseases hidden in huge number of single nucleotide polymorphism (SNP) genotypes is undertaken based on five dbGaP studies. Current genome-wide association studies have successfully identified many high-risk SNPs associated with diseases, but precise diagnostic models for complex diseases by these or more other SNP genotypes are still unavailable in the literature. We report that lung cancer, breast cancer and prostate cancer as the first three top cancers worldwide can be predicted precisely via 240–370 SNPs with accuracy up to 99% according to leave-one-out and 10-fold cross-validation. Our findings (1) confirm an early guess of Dr. Mitchell H. Gail that about 300 SNPs are needed to improve risk forecasts for breast cancer, (2) reveal an incredible fact that SNP genotypes may contain almost all information that one wants to know, and (3) show a hopeful possibility that complex diseases can be precisely diagnosed by means of SNP genotypes without using phenotypical features. In short words, information hidden in SNP genotypes can be extracted in efficient ways to make precise diagnoses for complex diseases. [ABSTRACT FROM AUTHOR]

Breast carcinoma(BC)is the most common cancer type among females globally. Understanding the molecular pathways that trigger the development of BC is crucial for both prevention and treatment. As such, the role of transcription factors (TFs) in the development of BC is a focal point in this field. CREB3s play a critical role in initiating the unfolded protein response (UPR); however, the role of CREB3 family members in breast cancer development remains largely unknown. Here, we mined the ONCOMINE database for the transcriptional data of CREB3s in patients with BC. Then, the regulatory functions of a novel TF, CREB3L4, were investigated. CREB3L4 knockdown in MDA-MB-231 and MCF-7 cells suppressed proliferation and promoted apoptosis and cell cycle arrest. ChIP assays confirmed that CREB3L4 can directly bind to the PCNA promoter region, suggesting that the PCNA protein may be functionally downstream of CREB3L4. Additionally, the expression level of CREB3L4 was assessed using our cohort. CREB3L4 is upregulated in breast cancer tissues and is significantly associated with histological grade and tumour size (P = 0.001 and P < 0.001, respectively). Furthermore, PCNA expression was upregulated in breast cancer tissues and positively correlated with CREB3L4. In summary, CREB3L4 may play an important role in the progression of human BC and may serve as a therapeutic target. [ABSTRACT FROM AUTHOR]