Association between AgNORs and Immunohistochemical Expression of ER, PR, HER2/neu, and p53 in Breast Carcinoma

Settings. Despite the limited diagnostic utility of AgNORs (argyrophilic nucleolar organiser region-associated proteins) for individual breast lesions, AgNOR analysis bears a significant potential for characterizing cell proliferative activity of breast lesions. Methodology. The present study investigated the relationship between mean AgNORs count and immunohistochemical expression of ER, PR, HER2/neu, and p53 in breast carcinoma in serial paraffin sections from 137 breast carcinomas. Twenty control cases of benign breast lesions were included. Results. Mean AgNOR counts correlated significantly inversely with hormone estrogen receptors (ER), Progesterone receptors (PR), and p53 immunohistochemical expression, denoting P values of 0.05, 0.01, and 0.001, respectively. No significant correlation was found between mean AgNOR counts and HER2/neu, P = 0.9. Mean AgNOR count was significantly higher in grade II tumor cells. We conclude that mean AgNOR counts correlate with ER, PR, and P53 tumor markers in breast carcinomas. Conclusion. We recommend the use of mean AgNOR count for accurate reporting of breast carcinomas, as well as prediction of ER, PR, and P53 in routine paraffin sections

An Approach for Systems-Level Understanding of Prostate Cancer from High-Throughput Data Integration to Pathway Modeling and Simulation

To understand complex diseases, high-throughput data are generated at large and multiple levels. However, extracting meaningful information from large datasets for comprehensive understanding of cell phenotypes and disease pathophysiology remains a major challenge. Despite tremendous advances in understanding molecular mechanisms of cancer and its progression, current knowledge appears discrete and fragmented. In order to render this wealth of data more integrated and thus informative, we have developed a GECIP toolbox to investigate the crosstalk and the responsible genes’/proteins’ connectivity of enriched pathways from gene expression data. To implement this toolbox, we used mainly gene expression datasets of prostate cancer, and the three datasets were GSE17951, GSE8218, and GSE1431. The raw samples were processed for normalization, prediction of differentially expressed genes, and the prediction of enriched pathways for the differentially expressed genes. The enriched pathways have been processed for crosstalk degree calculations for which number connections per gene, the frequency of genes in the pathways, sharing frequency, and the connectivity have been used. For network prediction, protein–protein interaction network database FunCoup2.0 was used, and cytoscape software was used for the network visualization. In our results, we found that there were enriched pathways 27, 45, and 22 for GSE17951, GSE8218, and GSE1431, respectively, and 11 pathways in common between all of them. From the crosstalk results, we observe that focal adhesion and PI3K pathways, both experimentally proven central for cellular output upon perturbation of numerous individual/distinct signaling pathways, displayed highest crosstalk degree. Moreover, we also observe that there were more critical pathways which appear to be highly significant, and these pathways are HIF1a, hippo, AMPK, and Ras. In terms of the pathways’ components, GSK3B, YWHAE, HIF1A, ATP1A3, and PRKCA are shared between the aforementioned pathways and have higher connectivity with the pathways and the other pathway components. Finally, we conclude that the focal adhesion and PI3K pathways are the most critical pathways, and since for many other pathways, high-rank enrichment did not translate to high crosstalk degree, the global impact of one pathway on others appears distinct from enrichment

Rho-GTPase activating-protein 18: a biomarker associated with good prognosis in invasive breast cancer.

BACKGROUND: The prognostic value of lymphovascular invasion (LVI) in breast cancer (BC) has been demonstrated in several independent studies. However, identification of driver molecules for LVI remains a challenging task. Large-scale transcriptomic profiling of histologically validated LVI can potentially identify genes that regulate LVI. METHODS: Integrative bio-informatics analyses of the METABRIC study were performed utilising a subset of strictly defined LVI using histological and immunohistochemical (IHC) criteria. ARHGAP18 was among the top differentially expressed genes between LVI+ and LVI- BC with a 1.8-fold change. The prognostic impact of ARHGAP18 gene expression was assessed in the METABRIC data set (n=1980) and externally validated using the online BC gene expression data sets utilising bc-GenExMiner v4.0 (n=2016). Subsequently, ARHGAP18 protein expression was assessed on a large cohort of invasive BC (n=959) with long-term follow-up using IHC. RESULTS: Pooled analysis of ARHGAP18 mRNA expression showed that overexpression was associated with better outcome (P<0.001, hazard ratio (HR)=0.82, 95% CI 0.75-0.90). ARHGAP18 protein was expressed in the cytoplasm and nuclei of the tumour cells and its expression was positively associated with good prognostic variables. Lack of cytoplasmic expression showed associations with LVI (P=0.006), epithelial-mesenchymal transition and the HER+ subtype (P=0.01). Loss of nuclear expression was associated with higher grade, HER2+ and high Ki67LI (P=0.001). Cytoplasmic and nuclear expression showed a positive association with improved survival independent of other variables (P=0.01, HR=0.74, 95% CI 0.60-87). CONCLUSIONS: ARHGAP18 expression at transcriptomic and protein levels is associated with improved patients' outcomes whose deregulation may play a role in tumour progression and the development of LVI in BC. Further assessment of its potential therapeutic value in BC is warranted

The prognostic significance of STAT3 in invasive breast cancer: analysis of protein and mRNA expressions in large cohorts

Signal transducer and activator of transcription (STAT) transcription factors family are involved in diverse cellular biological functions. Reports regarding the prognostic impact of STAT3 expression in breast cancer (BC) are variable whether being a factor of poor or good prognosis. Immunohistochemical expression of phospho-STAT3 (pSTAT3) was studied in large series of invasive BC (n = 1270). pSTAT3 and STAT3 were quantified using reverse phase protein array (RPPA) on proteins extracted from macro-dissected FFPE tissues (n = 49 cases). STAT3 gene expression in the METABRIC cohort was also investigated. STAT3 gene expression prognostic impact was externally validated using the online BC gene expression data (n = 26 datasets, 4.177 patients). pSTAT3 was expressed in the nuclei and cytoplasm of invasive BC cells. Nuclear pSTAT3 overexpression was positively associated with smaller tumour size, lower grade, good NPI, negative lymphovascular invasion (LVI), ER+, PgR+, p53−, HER2−, and low Ki67LI and an improved breast cancer-specific survival (BCSS), independently of other factors. On RPPA, the mean pSTAT3 and STAT3 expressions were higher in ER+, PgR+, and smaller size tumours. Higher STAT3 transcripts in the METABRIC cohort were observed in cases with favourable prognostic criteria and as well as improved BCSS within the whole cohort, ER+ cohort with and without hormonal therapy, and ER− cohort including those who did not receive adjuvant chemotherapy. Pooled STAT3 gene expression data in the external validation cohort showed an association with improved patients’ outcome (P < 0.001, HR = 0.84, 95 % CI 0.79–0.90). Results of this study suggest nuclear localisation of pSTAT3 as favourable prognostic marker in invasive BC, results re-enforced by analysis of STAT3 gene expression data. This good prognostic advantage was maintained in patients who received and who did not receive adjuvant therapy. Therefore, STAT3 could have context-dependent molecular roles of in BC, results which warrant further prospective verification in clinical trials

A Key Genomic Subtype Associated with Lymphovascular Invasion in Invasive Breast Cancer

Background: Lymphovascular invasion (LVI) is associated with the development of metastasis in invasive breast cancer (BC). However, the complex molecular mechanisms of LVI, which overlap with other oncogenic pathways, remain unclear. This study, using available large transcriptomic datasets, aims to identify genes associated with LVI in early-stage BC patients.Methods: Gene expression data from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) cohort (n = 1565) was used as a discovery dataset, and The Cancer Genome Atlas (TCGA; n = 854) cohort was used as a validation dataset. Key genes were identified on the basis of differential mRNA expression with respect to LVI status as characterized by histological review. The relationships among LVI-associated genomic subtype, clinicopathological features and patient outcomes were explored.Results: A 99-gene set was identified that demonstrated significantly different expression between LVI-positive and LVI-negative cases. Clustering analysis with this gene set further divided cases into two molecular subtypes (subtypes 1 and 2), which were significantly associated with pathology-determined LVI status in both cohorts. The 10-year overall survival of subtype 2 was significantly worse than that of subtype 1.Conclusion: This study demonstrates that LVI in BC is associated with a specific transcriptomic profile with potential prognostic value