High expression of Notch-1 and Jagged-1 mRNA correlates with poor prognosis in breast cancer. Elucidating the cross-talk between Notch and other major breast cancer pathways is necessary to determine which patients may benefit from Notch inhibitors, which agents should be combined with them, and which biomarkers indicate Notch activity in vivo. We explored expression of Notch receptors and ligands in clinical specimens, as well as activity, regulation, and effectors of Notch signaling using cell lines and xenografts. Ductal and lobular carcinomas commonly expressed Notch-1, Notch-4, and Jagged-1 at variable levels. However, in breast cancer cell lines, Notch-induced transcriptional activity did not correlate with Notch receptor levels and was highest in estrogen receptor α–negative (ERα–), Her2/Neu nonoverexpressing cells. In ERα+ cells, estradiol inhibited Notch activity and Notch-1IC nuclear levels and affected Notch-1 cellular distribution. Tamoxifen and raloxifene blocked this effect, reactivating Notch. Notch-1 induced Notch-4. Notch-4 expression in clinical specimens correlated with proliferation (Ki67). In MDA-MB231 (ERα–) cells, Notch-1 knockdown or γ-secretase inhibition decreased cyclins A and B1, causing G2 arrest, p53-independent induction of NOXA, and death. In T47D:A18 (ERα+) cells, the same targets were affected, and Notch inhibition potentiated the effects of tamoxifen. In vivo, γ;-secretase inhibitor treatment arrested the growth of MDA-MB231 tumors and, in combination with tamoxifen, caused regression of T47D:A18 tumors. Our data indicate that combinations of antiestrogens and Notch inhibitors may be effective in ERα+ breast cancers and that Notch signaling is a potential therapeutic target in ERα– breast cancers.

Patients with metastatic melanoma or multiple myeloma have a dismal prognosis because these aggressive malignancies resist conventional treatment. A promising new oncologic approach uses molecularly targeted therapeutics that overcomes apoptotic resistance and, at the same time, achieves tumor selectivity. The unexpected selectivity of proteasome inhibition for inducing apoptosis in cancer cells, but not in normal cells, prompted us to define the mechanism of action for this class of drugs, including Food and Drug Administration-approved bortezomib. In this report, five melanoma cell lines and a myeloma cell line are treated with three different proteasome inhibitors (MG-132, lactacystin, and bortezomib), and the mechanism underlying the apoptotic pathway is defined. Following exposure to proteasome inhibitors, effective killing of human melanoma and myeloma cells, but not of normal proliferating melanocytes, was shown to involve p53-independent induction of the BH3-only protein NOXA. Induction of NOXA at the protein level was preceded by enhanced transcription of NOXA mRNA. Engagement of mitochondrial-based apoptotic pathway involved release of cytochrome c, second mitochondria-derived activator of caspases, and apoptosis-inducing factor, accompanied by a proteolytic cascade with processing of caspases 9, 3, and 8 and poly(ADP)-ribose polymerase. Blocking NOXA induction using an antisense (but not control) oligonucleotide reduced the apoptotic response by 30% to 50%, indicating a NOXAdependent component in the overall killing of melanoma cells. These results provide a novel mechanism for overcoming the apoptotic resistance of tumor cells, and validate agents triggering NOXA induction as potential selective cancer therapeutics for life-threatening malignancies such as melanoma and multiple myeloma. (Cancer Res 2005; 65(14): 6282-93)

Copy Number Variations (CNVs) of regions of the human genome have been associated with multiple diseases. We present an algorithm which is mathematically sound and computationally efficient to accurately analyze CNV in a DNA sample utilizing a nanofluidic device, known as the digital array. This numerical algorithm is utilized to compute copy number variation and the associated statistical confidence interval and is based on results from probability theory and statistics. We also provide formulas which can be used as close approximations.

The frequency of the most common sporadic Apert syndrome mutation (C755G) in the human fibroblast growth factor receptor 2 gene (FGFR2) is 100–1,000 times higher than expected from average nucleotide substitution rates based on evolutionary studies and the incidence of human genetic diseases. To determine if this increased frequency was due to the nucleotide site having the properties of a mutation hot spot, or some other explanation, we developed a new experimental approach. We examined the spatial distribution of the frequency of the C755G mutation in the germline by dividing four testes from two normal individuals each into several hundred pieces, and, using a highly sensitive PCR assay, we measured the mutation frequency of each piece. We discovered that each testis was characterized by rare foci with mutation frequencies 103 to >104 times higher than the rest of the testis regions. Using a model based on what is known about human germline development forced us to reject (p < 10−6) the idea that the C755G mutation arises more frequently because this nucleotide simply has a higher than average mutation rate (hot spot model). This is true regardless of whether mutation is dependent or independent of cell division. An alternate model was examined where positive selection acts on adult self-renewing Ap spermatogonial cells (SrAp) carrying this mutation such that, instead of only replacing themselves, they occasionally produce two SrAp cells. This model could not be rejected given our observed data. Unlike the disease site, similar analysis of C-to-G mutations at a control nucleotide site in one testis pair failed to find any foci with high mutation frequencies. The rejection of the hot spot model and lack of rejection of a selection model for the C755G mutation, along with other data, provides strong support for the proposal that positive selection in the testis can act to increase the frequency of premeiotic germ cells carrying a mutation deleterious to an offspring, thereby unfavorably altering the mutational load in humans. Studying the anatomical distribution of germline mutations can provide new insights into genetic disease and evolutionary change.

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