7 resultados para Human breast cancer
em Duke University
Resumo:
PURPOSE: To define the biology driving the aggressive nature of breast cancer arising in young women. EXPERIMENTAL DESIGN: Among 784 patients with early stage breast cancer, using prospectively-defined, age-specific cohorts (young
Resumo:
The ABL family of non-receptor tyrosine kinases, ABL1 (also known as c-ABL) and ABL2 (also known as Arg), links diverse extracellular stimuli to signaling pathways that control cell growth, survival, adhesion, migration and invasion. ABL tyrosine kinases play an oncogenic role in human leukemias. However, the role of ABL kinases in solid tumors including breast cancer progression and metastasis is just emerging.
To evaluate whether ABL family kinases are involved in breast cancer development and metastasis, we first analyzed genomic data from large-scale screen of breast cancer patients. We found that ABL kinases are up-regulated in invasive breast cancer patients and high expression of ABL kinases correlates with poor prognosis and early metastasis. Using xenograft mouse models combined with genetic and pharmacological approaches, we demonstrated that ABL kinases are required for regulating breast cancer progression and metastasis to the bone. Using next generation sequencing and bioinformatics analysis, we uncovered a critical role for ABL kinases in promoting multiple oncogenic pathways including TAZ and STAT5 signaling networks and the epithelial to mesenchymal transition (EMT). These findings revealed a role for ABL kinases in regulating breast cancer tumorigenesis and bone metastasis and provide a rationale for targeting breast tumors with ABL-specific inhibitors.
Resumo:
During oncogenesis, cancer cells go through metabolic reprogramming to maintain their high growth rates and adapt to changes in the microenvironment and the lack of essential nutrients. Several types of cancer are dependent on de novo fatty acid synthesis to sustain their growth rates by providing precursors to construct membranes and produce vital signaling lipids. Fatty acid synthase (FASN) catalyze the terminal step of de novo fatty acid synthesis and it is highly expressed in many types of cancers where it’s up-regulation is correlated with cancer aggressiveness and low therapeutic outcome. Many FASN inhibitors were developed and showed potent anticancer activity however, only one inhibitor advanced to early stage clinical trials with some dose limiting toxicities. Using a modified fluorescence-linked enzyme chemoproteomic strategy (FLECS) screen, we identified HS-106, a thiophenopyrimiden FASN inhibitor that has anti-neoplastic activity against breast cancer in vitro and in vivo. HS-106 was able to inhibit both; purified human FASN activity and cellular fatty acid synthesis activity as evaluated by radioactive tracers incorporation into lipids experiments. In proliferation and apoptosis assays, HS-106 was able to block proliferation and induce apoptosis in several breast cancer cell lines. Several rescue experiment and global lipidome analysis were performed to probe the mechanism by which HS-106 induces apoptosis. HS-106 was found to induce several changes in lipids metabolism: (i) inhibit fatty acids synthesis. (ii) Inhibit fatty acids oxidation as indicated by the ability of inhibiting Malonyl CoA accumulation to block HS-106 induced apoptosis and the increase in the abundance of ceramides. (iii) Increase fatty acids uptake and neutral lipids formation as confirmed 14C Palmitate uptake assay and neutral lipids staining. (iv)Inhibit the formation of phospholipids by inhibiting de novo fatty acid synthesis and diverting exogenous fatty acids to neutral lipids. All of these events would lead to disruption in membranes structure and function. HS-106 was also tested in Lapatinib resistant cell lines and it was able to induce apoptosis and synergizes Lapatinib activity in these cell lines. This may be due the disruption of lipid rafts based on the observation that HS-106 reduces the expression of both HER2 and HER3. HS-106 was found to be well tolerated and bioavailable in mice with high elimination rate. HS-106 efficacy was tested in MMTV neu mouse model. Although did not significantly reduced tumor size (alone), HS-106 was able to double the median survival of the mice and showed potent antitumor activity when combined with Carboplatin. Similar results were obtained when same combinations and dosing schedule was used in C3Tag mouse model except for the inability of HS-106 affect mice survival.
From the above, HS-106 represent a novel FASN inhibitor that has anticancer activity both in vivo and in vitro. Being a chemically tractable molecule, the synthetic route to HS-106 is readily adaptable for the preparation of analogs that are similar in structure, suggesting that, the pharmacological properties of HS-106 can be improved.
Resumo:
As more diagnostic testing options become available to physicians, it becomes more difficult to combine various types of medical information together in order to optimize the overall diagnosis. To improve diagnostic performance, here we introduce an approach to optimize a decision-fusion technique to combine heterogeneous information, such as from different modalities, feature categories, or institutions. For classifier comparison we used two performance metrics: The receiving operator characteristic (ROC) area under the curve [area under the ROC curve (AUC)] and the normalized partial area under the curve (pAUC). This study used four classifiers: Linear discriminant analysis (LDA), artificial neural network (ANN), and two variants of our decision-fusion technique, AUC-optimized (DF-A) and pAUC-optimized (DF-P) decision fusion. We applied each of these classifiers with 100-fold cross-validation to two heterogeneous breast cancer data sets: One of mass lesion features and a much more challenging one of microcalcification lesion features. For the calcification data set, DF-A outperformed the other classifiers in terms of AUC (p < 0.02) and achieved AUC=0.85 +/- 0.01. The DF-P surpassed the other classifiers in terms of pAUC (p < 0.01) and reached pAUC=0.38 +/- 0.02. For the mass data set, DF-A outperformed both the ANN and the LDA (p < 0.04) and achieved AUC=0.94 +/- 0.01. Although for this data set there were no statistically significant differences among the classifiers' pAUC values (pAUC=0.57 +/- 0.07 to 0.67 +/- 0.05, p > 0.10), the DF-P did significantly improve specificity versus the LDA at both 98% and 100% sensitivity (p < 0.04). In conclusion, decision fusion directly optimized clinically significant performance measures, such as AUC and pAUC, and sometimes outperformed two well-known machine-learning techniques when applied to two different breast cancer data sets.
Resumo:
We have previously shown that treatment of prostate cancer and melanoma cells expressing GRP78 on their cell surface with antibody directed against the COOH-terminal domain of GRP78 upregulates and activates p53 causing decreased cell proliferation and upregulated apoptosis. In this report, we demonstrate that treatment of 1-LN prostate cancer cells with this antibody decreases cell surface expression of GRP78, Akt(Thr308) and Akt(Ser473) kinase activities and reduces phosphorylation of FOXO, and GSK3beta. This treatment also suppresses activation of ERK1/2, p38 MAPK and MKK3/6; however, it upregulates MKK4 activity. JNK, as determined by its phosphorylation state, is subsequently activated, triggering apoptosis. Incubation of cells with antibody reduced levels of anti-apoptotic Bcl-2, while elevating pro-apoptotic BAD, BAX and BAK expression as well as cleaved caspases-3, -7, -8 and -9. Silencing GRP78 or p53 gene expression by RNAi prior to antibody treatment abrogated these effects. We conclude that antibody directed against the COOH-terminal domain of GRP78 may prove useful as a pan suppressor of proliferative/survival signaling in cancer cells expressing GRP78 on their cell surface.
Resumo:
BACKGROUND: The Exercise Intensity Trial (EXcITe) is a randomized trial to compare the efficacy of supervised moderate-intensity aerobic training to moderate to high-intensity aerobic training, relative to attention control, on aerobic capacity, physiologic mechanisms, patient-reported outcomes, and biomarkers in women with operable breast cancer following the completion of definitive adjuvant therapy. METHODS/DESIGN: Using a single-center, randomized design, 174 postmenopausal women (58 patients/study arm) with histologically confirmed, operable breast cancer presenting to Duke University Medical Center (DUMC) will be enrolled in this trial following completion of primary therapy (including surgery, radiation therapy, and chemotherapy). After baseline assessments, eligible participants will be randomized to one of two supervised aerobic training interventions (moderate-intensity or moderate/high-intensity aerobic training) or an attention-control group (progressive stretching). The aerobic training interventions will include 150 mins.wk⁻¹ of supervised treadmill walking per week at an intensity of 60%-70% (moderate-intensity) or 60% to 100% (moderate to high-intensity) of the individually determined peak oxygen consumption (VO₂peak) between 20-45 minutes/session for 16 weeks. The progressive stretching program will be consistent with the exercise interventions in terms of program length (16 weeks), social interaction (participants will receive one-on-one instruction), and duration (20-45 mins/session). The primary study endpoint is VO₂peak, as measured by an incremental cardiopulmonary exercise test. Secondary endpoints include physiologic determinants that govern VO₂peak, patient-reported outcomes, and biomarkers associated with breast cancer recurrence/mortality. All endpoints will be assessed at baseline and after the intervention (16 weeks). DISCUSSION: EXCITE is designed to investigate the intensity of aerobic training required to induce optimal improvements in VO₂peak and other pertinent outcomes in women who have completed definitive adjuvant therapy for operable breast cancer. Overall, this trial will inform and refine exercise guidelines to optimize recovery in breast and other cancer survivors following the completion of primary cytotoxic therapy. TRIAL REGISTRATION: NCT01186367.
Resumo:
BACKGROUND: A major challenge in oncology is the selection of the most effective chemotherapeutic agents for individual patients, while the administration of ineffective chemotherapy increases mortality and decreases quality of life in cancer patients. This emphasizes the need to evaluate every patient's probability of responding to each chemotherapeutic agent and limiting the agents used to those most likely to be effective. METHODS AND RESULTS: Using gene expression data on the NCI-60 and corresponding drug sensitivity, mRNA and microRNA profiles were developed representing sensitivity to individual chemotherapeutic agents. The mRNA signatures were tested in an independent cohort of 133 breast cancer patients treated with the TFAC (paclitaxel, 5-fluorouracil, adriamycin, and cyclophosphamide) chemotherapy regimen. To further dissect the biology of resistance, we applied signatures of oncogenic pathway activation and performed hierarchical clustering. We then used mRNA signatures of chemotherapy sensitivity to identify alternative therapeutics for patients resistant to TFAC. Profiles from mRNA and microRNA expression data represent distinct biologic mechanisms of resistance to common cytotoxic agents. The individual mRNA signatures were validated in an independent dataset of breast tumors (P = 0.002, NPV = 82%). When the accuracy of the signatures was analyzed based on molecular variables, the predictive ability was found to be greater in basal-like than non basal-like patients (P = 0.03 and P = 0.06). Samples from patients with co-activated Myc and E2F represented the cohort with the lowest percentage (8%) of responders. Using mRNA signatures of sensitivity to other cytotoxic agents, we predict that TFAC non-responders are more likely to be sensitive to docetaxel (P = 0.04), representing a viable alternative therapy. CONCLUSIONS: Our results suggest that the optimal strategy for chemotherapy sensitivity prediction integrates molecular variables such as ER and HER2 status with corresponding microRNA and mRNA expression profiles. Importantly, we also present evidence to support the concept that analysis of molecular variables can present a rational strategy to identifying alternative therapeutic opportunities.