Parity-related molecular signatures and breast cancer subtypes by estrogen receptor status

INTRODUCTION: Relationships of parity with breast cancer risk are complex. Parity is associated with decreased risk of postmenopausal hormone receptor–positive breast tumors, but may increase risk for basal-like breast cancers and early-onset tumors. Characterizing parity-related gene expression patterns in normal breast and breast tumor tissues may improve understanding of the biological mechanisms underlying this complex pattern of risk. METHODS: We developed a parity signature by analyzing microRNA microarray data from 130 reduction mammoplasty (RM) patients (54 nulliparous and 76 parous). This parity signature, together with published parity signatures, was evaluated in gene expression data from 150 paired tumors and adjacent benign breast tissues from the Polish Breast Cancer Study, both overall and by tumor estrogen receptor (ER) status. RESULTS: We identified 251 genes significantly upregulated by parity status in RM patients (parous versus nulliparous; false discovery rate = 0.008), including genes in immune, inflammation and wound response pathways. This parity signature was significantly enriched in normal and tumor tissues of parous breast cancer patients, specifically in ER-positive tumors. CONCLUSIONS: Our data corroborate epidemiologic data, suggesting that the etiology and pathogenesis of breast cancers vary by ER status, which may have implications for developing prevention strategies for these tumors

Parity-related molecular signatures and breast cancer subtypes by estrogen receptor status.

INTRODUCTION:Relationships of parity with breast cancer risk are complex. Parity is associated with decreased risk of postmenopausal hormone receptor-positive breast tumors, but may increase risk for basal-like breast cancers and early-onset tumors. Characterizing parity-related gene expression patterns in normal breast and breast tumor tissues may improve understanding of the biological mechanisms underlying this complex pattern of risk. METHODS:We developed a parity signature by analyzing microRNA microarray data from 130 reduction mammoplasty (RM) patients (54 nulliparous and 76 parous). This parity signature, together with published parity signatures, was evaluated in gene expression data from 150 paired tumors and adjacent benign breast tissues from the Polish Breast Cancer Study, both overall and by tumor estrogen receptor (ER) status. RESULTS:We identified 251 genes significantly upregulated by parity status in RM patients (parous versus nulliparous; false discovery rate = 0.008), including genes in immune, inflammation and wound response pathways. This parity signature was significantly enriched in normal and tumor tissues of parous breast cancer patients, specifically in ER-positive tumors. CONCLUSIONS:Our data corroborate epidemiologic data, suggesting that the etiology and pathogenesis of breast cancers vary by ER status, which may have implications for developing prevention strategies for these tumors

Gene expression patterns associated with p53 status in breast cancer

BACKGROUND: Breast cancer subtypes identified in genomic studies have different underlying genetic defects. Mutations in the tumor suppressor p53 occur more frequently in estrogen receptor (ER) negative, basal-like and HER2-amplified tumors than in luminal, ER positive tumors. Thus, because p53 mutation status is tightly linked to other characteristics of prognostic importance, it is difficult to identify p53's independent prognostic effects. The relation between p53 status and subtype can be better studied by combining data from primary tumors with data from isogenic cell line pairs (with and without p53 function). METHODS: The p53-dependent gene expression signatures of four cell lines (MCF-7, ZR-75-1, and two immortalized human mammary epithelial cell lines) were identified by comparing p53-RNAi transduced cell lines to their parent cell lines. Cell lines were treated with vehicle only or doxorubicin to identify p53 responses in both non-induced and induced states. The cell line signatures were compared with p53-mutation associated genes in breast tumors. RESULTS: Each cell line displayed distinct patterns of p53-dependent gene expression, but cell type specific (basal vs. luminal) commonalities were evident. Further, a common gene expression signature associated with p53 loss across all four cell lines was identified. This signature showed overlap with the signature of p53 loss/mutation status in primary breast tumors. Moreover, the common cell-line tumor signature excluded genes that were breast cancer subtype-associated, but not downstream of p53. To validate the biological relevance of the common signature, we demonstrated that this gene set predicted relapse-free, disease-specific, and overall survival in independent test data. CONCLUSION: In the presence of breast cancer heterogeneity, experimental and biologically-based methods for assessing gene expression in relation to p53 status provide prognostic and biologically-relevant gene lists. Our biologically-based refinements excluded genes that were associated with subtype but not downstream of p53 signaling, and identified a signature for p53 loss that is shared across breast cancer subtypes

Systematic Bias in Genomic Classification Due to Contaminating Non-neoplastic Tissue in Breast Tumor Samples

Abstract Background Genomic tests are available to predict breast cancer recurrence and to guide clinical decision making. These predictors provide recurrence risk scores along with a measure of uncertainty, usually a confidence interval. The confidence interval conveys random error and not systematic bias. Standard tumor sampling methods make this problematic, as it is common to have a substantial proportion (typically 30-50%) of a tumor sample comprised of histologically benign tissue. This "normal" tissue could represent a source of non-random error or systematic bias in genomic classification. Methods To assess the performance characteristics of genomic classification to systematic error from normal contamination, we collected 55 tumor samples and paired tumor-adjacent normal tissue. Using genomic signatures from the tumor and paired normal, we evaluated how increasing normal contamination altered recurrence risk scores for various genomic predictors. Results Simulations of normal tissue contamination caused misclassification of tumors in all predictors evaluated, but different breast cancer predictors showed different types of vulnerability to normal tissue bias. While two predictors had unpredictable direction of bias (either higher or lower risk of relapse resulted from normal contamination), one signature showed predictable direction of normal tissue effects. Due to this predictable direction of effect, this signature (the PAM50) was adjusted for normal tissue contamination and these corrections improved sensitivity and negative predictive value. For all three assays quality control standards and/or appropriate bias adjustment strategies can be used to improve assay reliability. Conclusions Normal tissue sampled concurrently with tumor is an important source of bias in breast genomic predictors. All genomic predictors show some sensitivity to normal tissue contamination and ideal strategies for mitigating this bias vary depending upon the particular genes and computational methods used in the predictor

Gene Expression Profiling Identifies Two Chordoma Subtypes Associated with Distinct Molecular Mechanisms and Clinical Outcomes.

PURPOSE: Chordoma is a rare bone tumor with a high recurrence rate and limited treatment options. The aim of this study was to identify molecular subtypes of chordoma that may improve clinical management. EXPERIMENTAL DESIGN: We conducted RNA sequencing in 48 tumors from patients with Chinese skull-base chordoma and identified two major molecular subtypes. We then replicated the classification using a NanoString panel in 48 patients with chordoma from North America. RESULTS: Tumors in one subtype were more likely to have somatic mutations and reduced expression in chromatin remodeling genes, such as PBRM1 and SETD2, whereas the other subtype was characterized by the upregulation of genes in epithelial-mesenchymal transition and Sonic Hedgehog pathways. IHC staining of top differentially expressed genes between the two subtypes in 312 patients with Chinese chordoma with long-term follow-up data showed that the expression of some markers such as PTCH1 was significantly associated with survival outcomes. CONCLUSIONS: Our findings may improve the understanding of subtype-specific tumorigenesis of chordoma and inform clinical prognostication and targeted options

Clinicopathological, therapeutic and prognostic features of the triple-negative tumors in moroccan breast cancer patients (experience of Hassan II university hospital in Fez)

<p>Abstract</p> <p>Introduction</p> <p>Triple-negative breast cancer (TNBC) is defined as a group of breast carcinomas that are negative for expression of hormone receptors (ER, PR) and Her2, we can distinguish between two groups: basal-like (ER-, PR-, Her2-, cytokeratin (CK) 5/6+ and/or Her1+) and unclassified subtype (ER-, PR-, Her2-, Her1- and CK5/6-).</p> <p>The aim of this study is to determine the clinicopathological, histological, therapeutic and prognostic features associated with this type of breast cancer.</p> <p>Methods</p> <p>This is a retrospective study of 366 female breast cancer patients, diagnosed between January 2007 and June 2010 at the Department of Pathology. Epidemiological, clinical, histological, therapeutic and evolutive data were analyzed. OS and DFS rates were estimated by Kaplan-Meier analysis and a log-rank test to estimate outcome.</p> <p>Results</p> <p>A total of 64 women were identified as having TNBC (17.5% of all female breast cancer patients), 12.6% were basal-like, 4.9% were unclassified subtype, with a median age of 45 years. The median histological tumor diameter was 4.3 cm. TNBC were most often associated with a high grade, 49.2% grade III (53% for unclassified subtype, 47.6% for basal-like). Vascular invasion was found in 26.6% of cases (22% for unclassified subtype and 28.3% for basal-like). For the lymph node involvement: 51% had positive lymph nodes, and 22.4% had distant metastases. Neoadjuvant chemotherapy was administered to 18% patients with 26% of complete pathologic response; therefore adjuvant chemotherapy was given to 82%. 98% received anthracycline based regimen and only 30% received taxanes.</p> <p>The Kaplan-Meier curves based showed the lowest survival probability at 3-years (49% of OS, and 39% of DFS).</p> <p>Conclusion</p> <p>TNBC is associated with young age, high grade tumors, advanced stage at diagnosis, difference chemo response compared to other subtypes, and shortest survival. Critical to optimal future management is accurate identification of truly triple negative disease, and adequately powered prospective TNBC trials to establish treatment efficacy and define predictive biomarkers.</p

Evaluation of biological pathways involved in chemotherapy response in breast cancer

INTRODUCTION: Our goal was to examine the association between biological pathways and response to chemotherapy in estrogen receptor-positive (ER+) and ER-negative (ER-) breast tumors separately. METHODS: Gene set enrichment analysis including 852 predefined gene sets was applied to gene expression data from 51 ER- and 82 ER+ breast tumors that were all treated with a preoperative paclitaxel, 5-fluoruracil, doxorubicin, and cyclophosphamide chemotherapy. RESULTS: Twenty-seven (53%) ER- and 7 (9%) ER+ patients had pathologic complete response (pCR) to therapy. Among the ER- tumors, a proliferation gene signature (false discovery rate [FDR] q = 0.1), the genomic grade index (FDR q = 0.044), and the E2F3 pathway signature (FDR q = 0.22, P = 0.07) were enriched in the pCR group. Among the ER+ tumors, the proliferation signature (FDR q = 0.001) and the genomic grade index (FDR q = 0.015) were also significantly enriched in cases with pCR. Ki67 expression, as single gene marker of proliferation, did not provide the same information as the entire proliferation signature. An ER-associated gene set (FDR q = 0.03) and a mutant p53 gene signature (FDR q = 0.0019) were enriched in ER+ tumors with residual cancer. CONCLUSION: Proliferation- and genomic grade-related gene signatures are associated with chemotherapy sensitivity in both ER- and ER+ breast tumors. Genes involved in the E2F3 pathway are associated with chemotherapy sensitivity among ER- tumors. The mutant p53 signature and expression of ER-related genes were associated with lower sensitivity to chemotherapy in ER+ breast tumors only.Journal ArticleResearch Support, N.I.H. ExtramuralResearch Support, Non-U.S. Gov'tSCOPUS: ar.jinfo:eu-repo/semantics/publishe

Identification and characterization of seed-specific transcription factors regulating anthocyanin biosynthesis in black rice

Black rice is rich in anthocyanin and is expected to have more healthful dietary potential than white rice. We assessed expression of anthocyanin in black rice cultivars using a newly designed 135 K Oryza sativa microarray. A total of 12,673 genes exhibited greater than 2.0-fold up- or down-regulation in comparisons between three rice cultivars and three seed developmental stages. The 137 transcription factor genes found to be associated with production of anthocyanin pigment were classified into 10 groups. In addition, 17 unknown and hypothetical genes were identified from comparisons between the rice cultivars. Finally, 15 out of the 17 candidate genes were verified by RT-PCR analysis. Among the genes, nine were up-regulated and six exhibited down-regulation. These genes likely play either a regulatory role in anthocyanin biosynthesis or are related to anthocyanin metabolism during flavonoid biosynthesis. While these genes require further validation, the results here underline the potential use of the new microarray and provide valuable insight into anthocyanin pigment production in rice