2007;13:2329C2334. G2/M genes as being induced in overexpressing cells. These results confirm that B-Myb is involved in cell cycle control, and that dysregulation of may contribute to increased sensitivity to a specific class of chemotherapeutic agents. These data provide insight into the influence of in human breast cancer, which is of potential clinical importance for determining disease risk and for guiding MK-8719 treatment. (MYBL1), (MYBL2), and (MYB). Each family member is able to recognize and bind to the same DNA consensus sequence (PyAAC(G/T)G) to promote gene transcription; however, varying tissue-specific expression patterns, as well as protein-protein interactions with MK-8719 unique co-factors, suggests that distinct biological roles exist for each MYB family member (Rosinski & Atchley, 1998; Sala, 2005). Found in the genomes of both plants and animals, MYB proteins are conserved throughout evolution and control processes from flavonoid production to cellular proliferation (Rosinski & Atchley, 1998; Ito and (Mucenski causes early embryonic lethality (E4.5-6.5) resulting from unsuccessful inner cell mass formation (Tanaka proto-oncogene was first identified as the mammalian homolog of and were later discovered during low stringency screening of human cDNA libraries (Nomura chromosomal locus, 20q13, is amplified and/or highly expressed in a variety of tumor types including breast, prostate, liver and ovarian carcinomas, and in most cases this high expression portends a poor prognosis (Sala, 2005). is also an important marker of poor outcome in embryonal tumors of the central nervous system (CNS) (Pomeroy germline variant (rs2070235) causing a serine to glycine amino acid change (S427G) was linked to a decrease in overall cancer risk for neuroblastomas, chronic myelogenous leukemia, and colon cancers in a combined dataset of cases and controls (Schwab in disease progression, as well as its transcriptional target genes in the mammary gland, are still poorly understood. To gain insight into and its involvement in breast cancer, we analyzed the expression of across the breast cancer subtypes, examined its relationship to survival and pathological complete response and the correlation of variant rs2070235 to disease risk. We also manipulated the expression of and the S427G variant in normal and tumor derived mammary cell lines and observed alterations in drug Angiotensin Acetate sensitivity and cell cycle profiles. RESULTS High Expression in Breast Tumors Predicts Poor Outcome To asses the relevance of gene expression across the breast cancer subtypes, breast tumor microarray data from the Netherlands Cancer Institute (NKI-295, n=295, (van de Vijver expression differs significantly across the subtypes and was highest in basal-like tumors (Figure 1). Open in a separate window Figure 1 expression across breast cancer subtypesThe NKI breast tumor microarray dataset (n=295) was classified into the five intrinsic subtypes and box MK-8719 plots used to visualize expression according to breast cancer subtypes. Statistical significance was calculated by ANOVA. To test for correlations between mRNA expression alone and patient outcome, we analyzed the NKI patients not receiving adjuvant systemic treatment (i.e. local treatment only; n=165). This allowed us to better identify the prognostic abilities of without the confounding data of treatment response. The NKI local-only tumors were rank ordered into halves MK-8719 (low/high) based on their expression levels and analyzed for overall survival (OS) and relapse free survival (RFS) by Kaplan-Meier analysis. Poor OS and RFS were highly correlated (p<0.001) with high expression levels in these NKI samples (Figure 2A, and RFS data not shown). expression alone was also able to significantly predict OS on local-only treated luminal A subtype tumors (n=72) (Figure 2B), luminal B (n=26) (Figure 2C), HER2+/ER? (n=21) (Figure 2D), but not basal-like tumors (n=30) (Supplementary Figure 1A). We then evaluated the prognostic ability of using two other published breast tumor microarray datasets (Miller was capable of predicting RFS in these patients (Figure 2E). On this same dataset, also predicted RFS in the ER+ patient subset (n=209), but not the ER? subset (n=77) (Supplementary Figures 1B, C). Another dataset consisting of primary invasive tumors (Miller correlates with poor outcomeKaplan-Meier survival analyses based on expression values rank ordered into halves.
