Molecular prognostic indicators in breast cancer

Comprehensive analysis of gene expression profiles to identify differential prognostic factors of primary and metastatic breast cancer

Breast cancer accounts for nearly half of all cancer-related deaths in women worldwide. However, the molecular mechanisms that lead to tumour development and progression remain poorly understood and there is a need to identify candidate genes associated with primary and metastatic breast cancer progression and prognosis. In this study, candidate genes associated with prognosis of primary and metastatic breast cancer were explored through a novel bioinformatics approach. Primary and metastatic breast cancer tissues and adjacent normal breast tissues were evaluated to identify biomarkers characteristic of primary and metastatic breast cancer. The Cancer Genome Atlas-breast invasive carcinoma (TCGA-BRCA) dataset (ID: HS-01619) was downloaded using the mRNASeq platform. Genevestigator 8.3.2 was used to analyse TCGA-BRCA gene expression profiles between the sample groups and identify the differentially-expressed genes (DEGs) in each group. For each group, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were used to determine the function of DEGs. Networks of protein-protein interactions were constructed to identify the top hub genes with the highest degree of interaction. Additionally, the top hub genes were validated based on overall survival and immunohistochemistry using The Human Protein Atlas. Of the top 20 hub genes identified, four (KRT14, KIT, RAD51, and TTK) were considered as prognostic risk factors based on overall survival. KRT14 and KIT expression levels were upregulated while those of RAD51 and TTK were downregulated in patients with breast cancer. The four proposed candidate hub genes might aid in further understanding the molecular changes that distinguish primary breast tumours from metastatic tumours as well as help in developing novel therapeutics. Furthermore, they may serve as effective prognostic risk markers based on the strong correlation between their expression and patient overall survival.

Computational prognostic indicators for breast cancer

Breast cancer remains the leading cause of cancer-related mortality in women. Comprehensive genomics, proteomics, and metabolomics studies are emerging that offer an opportunity to model disease biology, prognosis, and response to specific therapies. Although many biomarkers have been identified through advances in data mining techniques, few have been applied broadly to make patient-specific decisions. Here, we review a selection of breast cancer prognostic indicators and their implications. Our goal is to provide clinicians with a general evaluation of emerging computational methodologies for outcome prediction.

Detecting metastasis of lymph nodes and predicting aggressiveness in patients with breast carcinomas

OBJECTIVE

The purpose of this study was to evaluate the contrast-enhanced ultrasonographic (CEUS) characteristics of metastatic lymph nodes (LNs) and to determine the correlation of CEUS parameters with the tumor aggressiveness in patients with breast cancer.

METHODS

Real-time gray scale CEUS of axillary LNs was preoperatively performed in 51 consecutive patients with breast carcinoma who were scheduled for axillary lymph node dissection. The CEUS characteristics assessed by a direct visualization method and quantification software were compared with pathologic findings. Expression of human epidermal growth factor receptor 2 (HER-2/neu) in the primary tumor was detected by immunohistochemical analysis. Correlation analysis of CEUS parameters with HER-2/neu expression and the LN stage was performed.

RESULTS

Of the LNs examined, 27 were metastatic, and 25 were diagnosed as reactive hyperplasia. Lymph nodes with metastasis were characterized by centripetal progress (66.7%) and a heterogeneous pattern (55.6%) or no or scarce perfusion (25.9%). However, LNs with nonmetastases were characterized by with centrifugal enhancement (56.0%) and a homogeneous pattern (80.0%). The difference between the hyperintense and hypointense regions was higher in metastatic LNs than nonmetastatic ones (P < .001). No significant differences were found in the arrival time, time to peak intensity, and peak intensity between the two groups. A histopathologic diagnosis could be predicted with sensitivity, specificity, and accuracy of 92.6%, 76.0%, and 84.6% respectively, by a standardized difference between maximum and minimum signal intensity (SI(max)-SI(min)) value of 28. Human epidermal growth factor receptor 2 expression and the LN histopathologic stage were significantly associated with the SI(max)-SI(min). In metastatic LNs, the relationship between the diagnostic sensitivity of CEUS and the transverse diameter of LNs remained statistically significant (P < .05).

CONCLUSIONS

Noninvasive CEUS can play a role in discriminating metastatic from nonmetastatic LNs and predicting the aggressiveness in patients with breast cancer.

14-3-3zeta overexpression defines high risk for breast cancer recurrence and promotes cancer cell survival

The ubiquitously expressed 14-3-3 proteins are involved in numerous important cellular functions. The loss of 14-3-3sigma is a common event in breast cancer; however, the role of other 14-3-3s in breast cancer is unclear. Recently, we found that 14-3-3zeta overexpression occurs in early stage breast diseases and contributes to transformation of human mammary epithelial cells. Here, we show that 14-3-3zeta overexpression also persisted in invasive ductal carcinoma and contributed to the further progression of breast cancer. To examine the clinical effect of 14-3-3zeta overexpression in advanced stage breast cancer, we performed immunohistochemical analysis of 14-3-3zeta expression in primary breast carcinomas. 14-3-3zeta overexpression occurred in 42% of breast tumors and was determined to be an independent prognostic factor for reduced disease-free survival. 14-3-3zeta overexpression combined with ErbB2 overexpression and positive lymph node status identified a subgroup of patients at high risk for developing distant metastasis. To investigate whether 14-3-3zeta overexpression causally promotes breast cancer progression, we overexpressed 14-3-3zeta by stable transfection or reduced 14-3-3zeta expression by siRNA in cancer cell lines. Increased 14-3-3zeta expression enhanced anchorage-independent growth and inhibited stress-induced apoptosis, whereas down-regulation of 14-3-3zeta reduced anchorage-independent growth and sensitized cells to stress-induced apoptosis via the mitochondrial apoptotic pathway. Transient blockade of 14-3-3zeta expression by siRNA in cancer cells effectively reduced the onset and growth of tumor xenografts in vivo. Therefore, 14-3-3zeta overexpression is a novel molecular marker for disease recurrence in breast cancer patients and may serve as an effective therapeutic target in patients whose tumors overexpress 14-3-3zeta.

Tissue microarray analysis of connexin expression and its prognostic significance in human breast cancer

Breast cancer accounts for approximately 15% of all cancer deaths. Currently, axillary nodal status is the most reliable prognostic indicator for breast cancer. Tumor size and histological grade are used to stage breast cancer. Estrogen receptor/progesterone receptor (ER/PR) and HER-2/neu status are useful in predicting patient survival and relapse. Ki67, an indicator of proliferative activity, also correlates well with prognosis. Connexin proteins form gap junction channels, permitting intercellular exchange of ions and small molecules. Reduced connexin protein levels and impaired gap junctional intercellular communication are associated with tumor phenotypes. This study investigated the prognostic value of connexin proteins as breast cancer markers. Tissue microarrays, containing 438 cases of invasive breast carcinoma, were stained with Cx26, Cx32, and Cx43 antibodies. The degree of connexin immunoreactivity was determined and then correlated with patient outcome, tumor grade, tumor size, lymph node status, and immunohistochemical markers, such as p53, ER/PR status, Ki67 and c-erbB-2 expression. Cx26, Cx32, or Cx43 did not correlate well with tumor grade, tumor size, p53 or c-erbB-2 status. There was an inverse correlation between Cx32 and lymph node status (P <0.05) and a positive correlation between Cx43 and PR status (P <0.01). Cx32 and Cx43 correlated positively with ER status (P <0.01). Cx43 correlated negatively with Ki67 expression (P <0.01). Cx26, Cx32, and Cx43 did not correlate with patient outcome. Based on our observations in this study, connexin proteins do not appear to be reliable indicators of breast cancer prognosis.

Cell Proliferation in Breast Cancer is a Major Determinant of Clinical Outcome in Node-Positive but Not in Node-Negative Patients

The growth rate of a tumor cell population depends on two major factors: the percentage of proliferating cells (cell growth fraction) and the rapidity of their duplication (cell proliferation rate). The authors evaluated the prognostic and predictive value of both kinetics parameters in a large series of breast cancer patients (n=504). The cell growth fraction was determined by MIB-1 immunostaining, the cell proliferation rate by AgNOR analysis. Ki-67 LI (labeling index) and AgNOR area were significantly associated with histotype, histologic grade, tumor size, estrogen/progesterone receptor status, patient age, and lymph node involvement (P<0.005). In the entire series of patients, both kinetics variables were significantly and independently associated with the clinical outcome, but their prognostic relevance was quite different when node-negative and node-positive patients were considered separately. Although in node-positive patients Ki-67 LI and AgNOR area were the unique independent predictors of disease-free and overall survival, they were excluded by the multivariate Cox model in node-negative patients, where only tumor size and estrogen receptor status retained a significant P-value. These results show that in breast carcinoma the cell growth fraction and the cell proliferation rate have a different prognostic impact with respect to the lymph node status and are major determinants of clinical outcome in node-positive patients only. Within this subgroup, the rapidity of cell proliferation as assessed by AgNOR analysis also served as a sensitive predictor of the response to adjuvant treatments.

Prognostic and predictive molecular markers in DCIS: a review

Eighteen percent of all new breast cancers detected on screening mammography are ductal carcinoma in situ (DCIS), a preinvasive lesion that is highly curable. However, some women with DCIS will develop life-threatening invasive breast cancer. Because the determinants of invasive recurrence are unknown, all women with DCIS require the same treatment (usually with surgery and radiation). Therefore, there is a need to identify biologic markers and create a profile that will provide prognostic information that is more accurate than the currently used van Nuys Index to predict invasive recurrence. In the present review, we examined the many biologic markers studied in breast cancer, describe their main biologic role and their expression in DCIS, and review the various studies regarding their ability to serve as prognostic factors in breast cancer with an emphasis on predicting invasive recurrence in patients with DCIS. This review covers established markers, namely, ER, PR and HER2/neu, that are used routinely to make treatment decisions as well as investigative biologic factors involved in cell proliferation, cell cycle regulation, extracellular molecules, factors involved in extracellular matrix degradation, and angiogenesis. However, controversies exist regarding the value of these prognostic factors, their interrelationship, and their advantages over morphologic evaluation.

Tumor Markers in Breast Cancer – European Group on Tumor Markers Recommendations

Recommendations are presented for the routine clinical use of serum and tissue-based markers in the diagnosis and management of patients with breast cancer. Their low sensitivity and specificity preclude the use of serum markers such as the MUC-1 mucin glycoproteins (CA 15.3, BR 27.29) and carcinoembryonic antigen in the diagnosis of early breast cancer. However, serial measurement of these markers can result in the early detection of recurrent disease as well as indicate the efficacy of therapy. Of the tissue-based markers, measurement of estrogen and progesterone receptors is mandatory in the selection of patients for treatment with hormone therapy, while HER-2 is essential in selecting patients with advanced breast cancer for treatment with Herceptin (trastuzumab). Urokinase plasminogen activator and plasminogen activator inhibitor 1 are recently validated prognostic markers for lymph node-negative breast cancer patients and thus may be of value in selecting node-negative patients that do not require adjuvant chemotherapy.

HER2 polymorphism and breast cancer risk in Portugal

Breast cancer is a major public health problem around the world, and its carcinogenesis is not yet well understood. The human epidermal growth factor Receptor 2 (HER2) seems to play an important role in the development of this neoplasia, and genetic alterations in this gene, such as point mutations and polymorphisms have been detected in breast cancer patients. We analysed the frequency of a single nucleotide polymorphism in the HER2 gene in blood samples from 152 breast cancer patients and 146 healthy controls using the polymerase chain reaction methodology, followed by restriction fragment length polymorphism (PCR-RFLP). We found a twofold increase in risk of breast cancer in women who are carriers of a Val allele genotype-Ile/Val and Val/Val genotypes [odds ratio (OR)=2.00; 95% confidence interval (CI) 1.23-3.25; P=0.005]. Our results indicate an association between the presence of the Val allele in the HER2 polymorphism and the risk of breast cancer. Further studies are needed to evaluate the role of this polymorphism in the behaviour of breast cancer.