A Cohort Study of p53 Mutations and Protein Accumulation in Benign Breast Tissue and Subsequent Breast Cancer Risk

Menstrual Phase and Menopausal Status Classification of Benign Breast Tissue Using Hormone-Regulated Gene Expression and Histomorphology: A Validation Study

BACKGROUND

The validation of breast cancer risk biomarkers in benign breast samples (BBS) is a long-sought goal, hampered by the fluctuation of gene and protein expression with menstrual phase (MP) and menopausal status (MS). Previously, we identified hormone-related gene expression and histomorphology parameters to classify BBS by MS/MP. We now evaluate both together, to validate our prior results.

PATIENTS AND METHODS

BBS were obtained from consenting women (86 premenopausal, 55 postmenopausal) undergoing reduction mammoplasty (RM) or contralateral unaffected breast (CUB) mastectomy. MP/MS was defined using classical criteria for menstrual dates and hormone levels on the day of surgery. BBS gene expression was measured with reverse transcription quantitative polymerase chain reaction (RT-qPCR) for three luteal phase (LP) genes (TNFSF11, DIO2, MYBPC1) and four menopausal genes (PGR, GREB1, TIFF1, CCND1). Premenopausal samples were classified into LP or non-LP, using published histomorphology parameters. Logistic regression and receiver-operator curve analysis was performed to assess area under the curve (AUC) for prediction of MP/MS.

RESULTS

In all 131 women, menopausal genes plus age > 50 years predicted true MS [AUC 0.93, 95% confidence interval (CI) 0.89, 0.97]. Among premenopausal women, high TNFSF11 expression distinguished non-LP from LP samples (AUC 0.80, 95% CI 0.70, 0.91); the addition of histomorphology improved the prediction nonsignificantly (AUC 0.87, 95% CI 0.78, 0.96). In premenopausal subsets, addition of histomorphology improved LP prediction in RM (AUC 0.95, 95% CI 0.87, 1.0), but not in CUB (0.84, 95% CI 0.72, 0.96).

CONCLUSIONS

Expression of five-gene set accurately predicts menopausal status and menstrual phase in BBS, facilitating the development of breast cancer risk biomarkers using large, archived sample repositories.

Early Diagnosis of Breast Cancer

Early-stage cancer detection could reduce breast cancer death rates significantly in the long-term. The most critical point for best prognosis is to identify early-stage cancer cells. Investigators have studied many breast diagnostic approaches, including mammography, magnetic resonance imaging, ultrasound, computerized tomography, positron emission tomography and biopsy. However, these techniques have some limitations such as being expensive, time consuming and not suitable for young women. Developing a high-sensitive and rapid early-stage breast cancer diagnostic method is urgent. In recent years, investigators have paid their attention in the development of biosensors to detect breast cancer using different biomarkers. Apart from biosensors and biomarkers, microwave imaging techniques have also been intensely studied as a promising diagnostic tool for rapid and cost-effective early-stage breast cancer detection. This paper aims to provide an overview on recent important achievements in breast screening methods (particularly on microwave imaging) and breast biomarkers along with biosensors for rapidly diagnosing breast cancer.

Detection of TP53 R249 Mutation in Iranian Patients with Pancreatic Cancer

The TP53 gene encodes tumor protein p53 which play a major role in the etiology of pancreatic cancer. The important role of codon 249 of TP53 for binding of p53 to its sequence-specific consensus site in DNA has been revealed by crystallography's studies, and mutation at this codon was detected in the plasma of some human cancers. The TP53 Mut assessor software within the International Agency for Research on Cancer (IARC) TP53 Database was performed to evaluate every possible mutation at codon 249. DNA was extracted from the plasma of 133 pancreatic cancer patients and 85 noncancer-bearing individuals. Exon 7 in TP53 was amplified, and mutation at R249 was identified by the endonuclease cleavage of HaeIII. The group of patients showed a frequency of 11% (22 of 133 samples) R249 mutation compared to 3.5% (3 of 85 samples) in the group of control which was significant (P = 0.03). This mutation demonstrated statistically significant association with pancreatic cancer risk in unadjusted odds ratio (OR: 3.74, 95% CI: 1.1–13.2; P = 0.041); however when adjusted for confounding factors, it was marginally significant because of lower control samples. These findings demonstrate that mutation at R249 of TP53 can be considered for increasing risk of pancreatic cancer that needs more research.