Background: Plasminogen activator inhibitor 1 (PAI-1) overexpression is an important prognostic and predictive biomarker in human breast cancer. SERBP1, a protein that is supposed to regulate the stability of PAI-1 mRNA, may play a role in gynaecological cancers as well, since upregulation of SERBP1 was described in ovarian cancer recently. This is the first study to present a systematic characterisation of SERBP1 expression in human breast cancer and normal breast tissue at both the mRNA and the protein level.

Methods: Using semiquantitative realtime PCR we analysed SERBP1 expression in different normal human tissues (n = 25), and in matched pairs of normal (n = 7) and cancerous breast tissues (n = 7). SERBP1 protein expression was analysed in two independent cohorts on tissue microarrays (TMAs), an initial evaluation set, consisting of 193 breast carcinomas and 48 normal breast tissues, and a second large validation set, consisting of 605 breast carcinomas. In addition, a collection of benign (n = 2) and malignant (n = 6) mammary cell lines as well as breast carcinoma lysates (n = 16) were investigated for SERBP1 expression by Western blot analysis. Furthermore, applying non-radioisotopic in situ hybridisation a subset of normal (n = 10) and cancerous (n = 10) breast tissue specimens from the initial TMA were analysed for SERBP1 mRNA expression.

Results: SERBP1 is not differentially expressed in breast carcinoma compared to normal breast tissue, both at the RNA and protein level. However, recurrence-free survival analysis showed a significant correlation (P = 0.008) between abundant SERBP1 expression in breast carcinoma and favourable prognosis. Interestingly, overall survival analysis also displayed a tendency (P = 0.09) towards favourable prognosis when SERBP1 was overexpressed in breast cancer.

Conclusions: The RNA-binding protein SERBP1 is abundantly expressed in human breast cancer and may represent a novel breast tumour marker with prognostic significance. Its potential involvement in the plasminogen activator protease cascade warrants further investigation.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3538721PMC
http://dx.doi.org/10.1186/1471-2407-12-597DOI Listing

Publication Analysis

Top Keywords

breast
16
human breast
16
breast cancer
16
serbp1 expression
16
plasminogen activator
12
favourable prognosis
12
normal breast
12
breast tissue
12
breast carcinoma
12
serbp1
11

Similar Publications

Importance: Research indicates that social drivers of health are associated with cancer screening adherence, although the exact magnitude of these associations remains unclear.

Objective: To investigate the associations between individual-level social risks and nonadherence to guideline-recommended cancer screenings.

Design, Setting, And Participants: This cross-sectional study used 2022 Behavioral Risk Factor Surveillance System data from 39 US states and Washington, DC.

View Article and Find Full Text PDF

Canine mammary tumors as a promising adjunct preclinical model for human breast cancer research: similarities, opportunities, and challenges.

Arch Pharm Res

January 2025

Laboratory of Biochemistry and Immunology, College of Veterinary Medicine, Chungbuk National University, Cheongju, 28644, Republic of Korea.

Despite significant progress in the field of human breast cancer research and treatment, there is a consistent increase in the incidence rate of 0.5 percent annually, posing challenges in the development of effective novel therapeutic strategies. The failure rate of drugs in clinical trials stands at approximately 95%, primarily attributed to the limitations and lack of reliability of existing preclinical models, such as mice, which do not mimic human tumor biology.

View Article and Find Full Text PDF

A Review on Integrating Breast Cancer Clinical Data: A Unified Platform Perspective.

Curr Treat Options Oncol

January 2025

Department of Pharmacognosy, JSS College of Pharmacy, JSS Academy of Higher Education & Research, Mysuru, Karnataka, India.

Integrating clinical datasets in breast cancer research emerges as a necessary tool for advancing our knowledge of the disease and enhancing patient outcomes. Synthesizing diverse datasets offers advantages, from facilitating evidence-based insights to enabling predictive analytics and precision medicine strategies. Crucially, effective integration of clinical datasets necessitates collaborative efforts, policy interventions, and technological advancements to elevate global standards of breast cancer care.

View Article and Find Full Text PDF

Objectives: Automated breast ultrasound imaging (ABUS) results in a reduction in breast cancer stage at diagnosis beyond that seen with mammographic screening in women with increased breast density or who are at a high risk of breast cancer. It is unknown if the addition of ABUS to mammography or ABUS imaging alone, in this population, is a cost-effective screening strategy.

Methods: A discrete event simulation (Monte Carlo) model was developed to assess the costs of screening, diagnostic evaluation, biopsy, and breast cancer treatment.

View Article and Find Full Text PDF

Background: Flat epithelial atypia (FEA), a rare breast proliferative lesion, is often diagnosed following core biopsy (CB) of mammographic microcalcifications. In the prospective multi-institution TBCRC 034 trial, we investigate the upgrade rate to ductal carcinoma in situ (DCIS) or invasive cancer following excision for patients diagnosed with FEA on CB.

Patients And Methods: Patients with a breast imaging reporting and data system (BI-RADS) ≤ 4 imaging abnormality and a concordant CB diagnosis of FEA were identified for excision.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!