ATBF1 and NQO1 as candidate targets for allelic loss at chromosome arm 16q in breast cancer: Absence of somatic ATBF1 mutations and no role for the C609T NQO1 polymorphism

<p>Abstract</p> <p>Background</p> <p>Loss of heterozygosity (LOH) at chromosome arm 16q is frequently observed in human breast cancer, suggesting that one or more target tumor suppressor genes (TSGs) are located there. However, detailed mapping of the smallest region of LOH has not yet resulted in the identification of a TSG at 16q. Therefore, the present study attempted to identify TSGs using an approach based on mRNA expression.</p> <p>Methods</p> <p>A cDNA microarray for the 16q region was constructed and analyzed using RNA samples from 39 breast tumors with known LOH status at 16q.</p> <p>Results</p> <p>Five genes were identified to show lower expression in tumors with LOH at 16q compared to tumors without LOH. The genes for NAD(P)H dehydrogenase quinone (<it>NQO1</it>) and AT-binding transcription factor 1 (<it>ATBF1</it>) were further investigated given their functions as potential TSGs. <it>NQO1 </it>has been implicated in carcinogenesis due to its role in quinone detoxification and in stabilization of p53. One inactive polymorphic variant of <it>NQO1 </it>encodes a product showing reduced enzymatic activity. However, we did not find preferential targeting of the active <it>NQO1 </it>allele in tumors with LOH at 16q. Immunohistochemical analysis of 354 invasive breast tumors revealed that NQO1 protein expression in a subset of breast tumors is higher than in normal epithelium, which contradicts its proposed role as a tumor suppressor gene.</p> <p><it>ATBF1 </it>has been suggested as a target for LOH at 16q in prostate cancer. We analyzed the entire coding sequence in 48 breast tumors, but did not identify somatic sequence changes. We did find several in-frame insertions and deletions, two variants of which were reported to be somatic pathogenic mutations in prostate cancer. Here, we show that these variants are also present in the germline in 2.5% of 550 breast cancer patients and 2.9% of 175 healthy controls. This indicates that the frequency of these variants is not increased in breast cancer patients. Moreover, there is no preferential LOH of the wildtype allele in breast tumors.</p> <p>Conclusion</p> <p>Two likely candidate TSGs at 16q in breast cancer, <it>NQO1 </it>and <it>ATBF1</it>, were identified here as showing reduced expression in tumors with 16q LOH, but further analysis indicated that they are not target genes of LOH. Furthermore, our results call into question the validity of the previously reported pathogenic variants of the <it>ATBF1 </it>gene.</p

Expression of cell cycle proteins in male breast carcinoma

<p>Abstract</p> <p>Introduction</p> <p>Male breast cancer (MBC) is a rare, yet potentially aggressive disease. Although literature regarding female breast cancer (FBC) is extensive, little is known about the etiopathogenesis of male breast cancer. Studies from our laboratory show that MBCs have a distinct immunophenotypic profile, suggesting that the etiopathogenesis of MBC is different from FBCs. The aim of this study was to evaluate and correlate the immunohistochemical expression of cell cycle proteins in male breast carcinoma to significant clinico-biological endpoints.</p> <p>Methods</p> <p>75 cases of MBC were identified using the records of the Saskatchewan Cancer Agency over 26 years (1970-1996). Cases were reviewed and analyzed for the immunohistochemical expression of PCNA, Ki67, p27, p16, p57, p21, cyclin-D1 and c-myc and correlated to clinico-biological endpoints of tumor size, node status, stage of the disease, and disease free survival (DFS).</p> <p>Results</p> <p>Decreased DFS was observed in the majority of tumors that overexpressed PCNA (98%, p = 0.004). The overexpression of PCNA was inversely correlated to the expression of Ki67 which was predominantly negative (78.3%). Cyclin D1 was overexpressed in 83.7% of cases. Cyclin D1 positive tumors were smaller than 2 cm (55.6%, p = 0.005), had a low incidence of lymph node metastasis (38.2%, p = 0.04) and were associated with increased DFS of >150 months (p = 0.04). Overexpression of c-myc (90%) was linked with a higher incidence of node negativity (58.3%, p = 0.006) and increased DFS (p = 0.04). p27 over expression was associated with decreased lymph node metastasis (p = 0.04). P21 and p57 positive tumors were related to decreased DFS (p = 0.04). Though p16 was overexpressed in 76.6%, this did not reach statistical significance with DFS (p = 0.06) or nodal status (p = 0.07).</p> <p>Conclusion</p> <p>Aberrant cell cycle protein expression supports our view that these are important pathways involved in the etiopathogenesis of MBC. Tumors with overexpression of Cyclin D1 and c-myc had better outcomes, in contrast to tumors with overexpression of p21, p57, and PCNA with significantly worse outcomes. P27 appears to be a predictive marker for lymph nodal status. Such observation strongly suggests that dysregulation of cell cycle proteins may play a unique role in the initiation and progression of disease in male breast cancer. Such findings open up new avenues for the treatment of MBC as a suitable candidate for novel CDK-based anticancer therapies in the future.</p

Drug-Tolerant Cancer Cells Show Reduced Tumor-Initiating Capacity: Depletion of CD44+ Cells and Evidence for Epigenetic Mechanisms

Cancer stem cells (CSCs) possess high tumor-initiating capacity and have been reported to be resistant to therapeutics. Vice versa, therapy-resistant cancer cells seem to manifest CSC phenotypes and properties. It has been generally assumed that drug-resistant cancer cells may all be CSCs although the generality of this assumption is unknown. Here, we chronically treated Du145 prostate cancer cells with etoposide, paclitaxel and some experimental drugs (i.e., staurosporine and 2 paclitaxel analogs), which led to populations of drug-tolerant cells (DTCs). Surprisingly, these DTCs, when implanted either subcutaneously or orthotopically into NOD/SCID mice, exhibited much reduced tumorigenicity or were even non-tumorigenic. Drug-tolerant DLD1 colon cancer cells selected by a similar chronic selection protocol also displayed reduced tumorigenicity whereas drug-tolerant UC14 bladder cancer cells demonstrated either increased or decreased tumor-regenerating capacity. Drug-tolerant Du145 cells demonstrated low proliferative and clonogenic potential and were virtually devoid of CD44+ cells. Prospective knockdown of CD44 in Du145 cells inhibited cell proliferation and tumor regeneration, whereas restoration of CD44 expression in drug-tolerant Du145 cells increased cell proliferation and partially increased tumorigenicity. Interestingly, drug-tolerant Du145 cells showed both increases and decreases in many “stemness” genes. Finally, evidence was provided that chronic drug exposure generated DTCs via epigenetic mechanisms involving molecules such as CD44 and KDM5A. Our results thus reveal that 1) not all DTCs are necessarily CSCs; 2) conventional chemotherapeutic drugs such as taxol and etoposide may directly target CD44+ tumor-initiating cells; and 3) DTCs generated via chronic drug selection involve epigenetic mechanisms

Global analysis of estrogen receptor beta binding to breast cancer cell genome reveals an extensive interplay with estrogen receptor alpha for target gene regulation

Background: Estrogen receptors alpha (ERa) and beta (ERb) are transcription factors (TFs) that mediate estrogen signaling and define the hormone-responsive phenotype of breast cancer (BC). The two receptors can be found co-expressed and play specific, often opposite, roles, with ERb being able to modulate the effects of ERa on gene transcription and cell proliferation. ERb is frequently lost in BC, where its presence generally correlates with a better prognosis of the disease. The identification of the genomic targets of ERb in hormone-responsive BC cells is thus a critical step to elucidate the roles of this receptor in estrogen signaling and tumor cell biology. Results: Expression of full-length ERb in hormone-responsive, ERa-positive MCF-7 cells resulted in a marked reduction in cell proliferation in response to estrogen and marked effects on the cell transcriptome. By ChIP-Seq we identified 9702 ERb and 6024 ERa binding sites in estrogen-stimulated cells, comprising sites occupied by either ERb, ERa or both ER subtypes. A search for TF binding matrices revealed that the majority of the binding sites identified comprise one or more Estrogen Response Element and the remaining show binding matrixes for other TFs known to mediate ER interaction with chromatin by tethering, including AP2, E2F and SP1. Of 921 genes differentially regulated by estrogen in ERb+ vs ERb- cells, 424 showed one or more ERb site within 10 kb. These putative primary ERb target genes control cell proliferation, death, differentiation, motility and adhesion, signal transduction and transcription, key cellular processes that might explain the biological and clinical phenotype of tumors expressing this ER subtype. ERb binding in close proximity of several miRNA genes and in the mitochondrial genome, suggests the possible involvement of this receptor in small non-coding RNA biogenesis and mitochondrial genome functions. Conclusions: Results indicate that the vast majority of the genomic targets of ERb can bind also ERa, suggesting that the overall action of ERb on the genome of hormone-responsive BC cells depends mainly on the relative concentration of both ERs in the cell

Frequency, prognostic impact, and subtype association of 8p12, 8q24, 11q13, 12p13, 17q12, and 20q13 amplifications in breast cancers

BACKGROUND: Oncogene amplification and overexpression occur in tumor cells. Amplification status may provide diagnostic and prognostic information and may lead to new treatment strategies. Chromosomal regions 8p12, 8q24, 11q13, 17q12 and 20q13 are recurrently amplified in breast cancers. METHODS: To assess the frequencies and clinical impact of amplifications, we analyzed 547 invasive breast tumors organized in a tissue microarray (TMA) by fluorescence in situ hybridization (FISH) and calculated correlations with histoclinical features and prognosis. BAC probes were designed for: (i) two 8p12 subregions centered on RAB11FIP1 and FGFR1 loci, respectively; (ii) 11q13 region centered on CCND1; (iii) 12p13 region spanning NOL1; and (iv) three 20q13 subregions centered on MYBL2, ZNF217 and AURKA, respectively. Regions 8q24 and 17q12 were analyzed with MYC and ERBB2 commercial probes, respectively. RESULTS: We observed amplification of 8p12 (amplified at RAB11FIP1 and/or FGFR1) in 22.8%, 8q24 in 6.1%, 11q13 in 19.6%, 12p13 in 4.1%, 17q12 in 9.9%, 20q13(Z )(amplified at ZNF217 only) in 9.9%, and 20q13(Co )(co-amplification of two or three 20q13 loci) in 8.5% of cases. The 8q24, 12p13, and 17q12 amplifications were correlated with high grade. The most frequent single amplifications were 8p12 (9.8%), 8q24 (3.3%) and 12p13 (3.3%), 20q13(Z )and 20q13(Co )(1.6%) regions. The 17q12 and 11q13 regions were never found amplified alone. The most frequent co-amplification was 8p12/11q13. Amplifications of 8p12 and 17q12 were associated with poor outcome. Amplification of 12p13 was associated with basal molecular subtype. CONCLUSION: Our results establish the frequencies, prognostic impacts and subtype associations of various amplifications and co-amplifications in breast cancers

Using State Space Exploration to Determine How Gene Regulatory Networks Constrain Mutation Order in Cancer Evolution

Cancer develops via the progressive accumulation of somatic mutations, which subvert the normal operation of the gene regulatory network of the cell. However, little is known about the order in which mutations are acquired in successful clones. A particular sequence of mutations may confer an early selective advantage to a clone by increasing survival or proliferation, or lead to negative selection by triggering cell death. The space of allowed sequences of mutations is therefore constrained by the gene regulatory network. Here, we introduce a methodology for the systematic exploration of the effect of every possible sequence of oncogenic mutations in a cancer cell modelled as a qualitative network. Our method uses attractor identification using binary decision diagrams and can be applied to both synchronous and asynchronous systems. We demonstrate our method using a recently developed model of ER-negative breast cancer. We show that there are differing levels of constraint in the order of mutations for different combinations of oncogenes, and that the effects of ErbB2/HER2 over-expression depend on the preceding mutations