94 research outputs found
Bcl-2 and β1-integrin predict survival in a tissue microarray of small cell lung cancer.
INTRODUCTION: Survival in small cell lung cancer (SCLC) is limited by the development of chemoresistance. Factors associated with chemoresistance in vitro have been difficult to validate in vivo. Both Bcl-2 and β(1)-integrin have been identified as in vitro chemoresistance factors in SCLC but their importance in patients remains uncertain. Tissue microarrays (TMAs) are useful to validate biomarkers but no large TMA exists for SCLC. We designed an SCLC TMA to study potential biomarkers of prognosis and then used it to clarify the role of both Bcl-2 and β(1)-integrin in SCLC. METHODS: A TMA was constructed consisting of 184 cases of SCLC and stained for expression of Bcl-2 and β(1)-integrin. The slides were scored and the role of the proteins in survival was determined using Cox regression analysis. A meta-analysis of the role of Bcl-2 expression in SCLC prognosis was performed based on published results. RESULTS: Both proteins were expressed at high levels in the SCLC cases. For Bcl-2 (n=140), the hazard ratio for death if the staining was weak in intensity was 0.55 (0.33-0.94, P=0.03) and for β(1)-integrin (n=151) was 0.60 (0.39-0.92, P=0.02). The meta-analysis showed an overall hazard ratio for low expression of Bcl-2 of 0.91(0.74-1.09). CONCLUSIONS: Both Bcl-2 and β(1)-integrin are independent prognostic factors in SCLC in this cohort although further validation is required to confirm their importance. A TMA of SCLC cases is feasible but challenging and an important tool for biomarker validation
Parental smoking and childhood cancer: results from the United Kingdom Childhood Cancer Study
There are strong a priori reasons for considering parental smoking behaviour as a risk factor for childhood cancer but case – control studies have found relative risks of mostly only just above one. To investigate this further, self-reported smoking habits in parents of 3838 children with cancer and 7629 control children included in the United Kingdom Childhood Cancer Study (UKCCS) were analysed. Separate analyses were performed for four major groups (leukaemia, lymphoma, central nervous system tumours and other solid tumours) and more detailed diagnostic subgroups by logistic regression. In the four major groups, after adjustment for parental age and deprivation there were nonsignificant trends of increasing risk with number of cigarettes smoked for paternal preconception smoking and nonsignificant trends of decreasing risk for maternal preconception smoking (all P-values for trend >0.05). Among the diagnostic subgroups, a statistically significant increased risk of developing hepatoblastoma was found in children whose mothers smoked preconceptionally (OR=2.68, P=0.02) and strongest (relative to neither parent smoking) for both parents smoking (OR=4.74, P=0.003). This could be a chance result arising from multiple subgroup analysis. Statistically significant negative trends were found for maternal smoking during pregnancy for all diagnoses together (P<0.001) and for most individual groups, but there was evidence of under-reporting of smoking by case mothers. In conclusion, the UKCCS does not provide significant evidence that parental smoking is a risk factor for any of the major groups of childhood cancers
An Integrative -omics Approach to Identify Functional Sub-Networks in Human Colorectal Cancer
Emerging evidence indicates that gene products implicated in human cancers often cluster together in “hot spots” in protein-protein interaction (PPI) networks. Additionally, small sub-networks within PPI networks that demonstrate synergistic differential expression with respect to tumorigenic phenotypes were recently shown to be more accurate classifiers of disease progression when compared to single targets identified by traditional approaches. However, many of these studies rely exclusively on mRNA expression data, a useful but limited measure of cellular activity. Proteomic profiling experiments provide information at the post-translational level, yet they generally screen only a limited fraction of the proteome. Here, we demonstrate that integration of these complementary data sources with a “proteomics-first” approach can enhance the discovery of candidate sub-networks in cancer that are well-suited for mechanistic validation in disease. We propose that small changes in the mRNA expression of multiple genes in the neighborhood of a protein-hub can be synergistically associated with significant changes in the activity of that protein and its network neighbors. Further, we hypothesize that proteomic targets with significant fold change between phenotype and control may be used to “seed” a search for small PPI sub-networks that are functionally associated with these targets. To test this hypothesis, we select proteomic targets having significant expression changes in human colorectal cancer (CRC) from two independent 2-D gel-based screens. Then, we use random walk based models of network crosstalk and develop novel reference models to identify sub-networks that are statistically significant in terms of their functional association with these proteomic targets. Subsequently, using an information-theoretic measure, we evaluate synergistic changes in the activity of identified sub-networks based on genome-wide screens of mRNA expression in CRC. Cross-classification experiments to predict disease class show excellent performance using only a few sub-networks, underwriting the strength of the proposed approach in discovering relevant and reproducible sub-networks
Heat shock protein-90-alpha, a prolactin-STAT5 target gene identified in breast cancer cells, is involved in apoptosis regulation
Introduction The prolactin-Janus-kinase-2-signal transducer and activator of transcription-5 (JAK2-STAT5) pathway is essential for the development and functional differentiation of the mammary gland. The pathway also has important roles in mammary tumourigenesis. Prolactin regulated target genes are not yet well defined in tumour cells, and we undertook, to the best of our knowledge, the first large genetic screen of breast cancer cells treated with or without exogenous prolactin. We hypothesise that the identification of these genes should yield insights into the mechanisms by which prolactin participates in cancer formation or progression, and possibly how it regulates normal mammary gland development. Methods We used subtractive hybridisation to identify a number of prolactin-regulated genes in the human mammary carcinoma cell line SKBR3. Northern blotting analysis and luciferase assays identified the gene encoding heat shock protein 90-alpha (HSP90A) as a prolactin-JAK2-STAT5 target gene, whose function was characterised using apoptosis assays. Results We identified a number of new prolactin-regulated genes in breast cancer cells. Focusing on HSP90A, we determined that prolactin increased HSP90A mRNA in cancerous human breast SKBR3 cells and that STAT5B preferentially activated the HSP90A promoter in reporter gene assays. Both prolactin and its downstream protein effector, HSP90α, promote survival, as shown by apoptosis assays and by the addition of the HSP90 inhibitor, 17-allylamino-17-demethoxygeldanamycin (17-AAG), in both untransformed HC11 mammary epithelial cells and SKBR3 breast cancer cells. The constitutive expression of HSP90A, however, sensitised differentiated HC11 cells to starvation-induced wild-type p53-independent apoptosis. Interestingly, in SKBR3 breast cancer cells, HSP90α promoted survival in the presence of serum but appeared to have little effect during starvation. Conclusions In addition to identifying new prolactin-regulated genes in breast cancer cells, we found that prolactin-JAK2-STAT5 induces expression of the HSP90A gene, which encodes the master chaperone of cancer. This identifies one mechanism by which prolactin contributes to breast cancer. Increased expression of HSP90A in breast cancer is correlated with increased cell survival and poor prognosis and HSP90α inhibitors are being tested in clinical trials as a breast cancer treatment. Our results also indicate that HSP90α promotes survival depending on the cellular conditions and state of cellular transformation
Active, but not passive cigarette smoking was inversely associated with mammographic density
The opposing carcinogenic and antiestrogenic properties of tobacco smoke may explain why epidemiologic studies have not consistently reported positive associations for active smoking and breast cancer risk. A negative relation between mammographic density, a strong breast cancer risk factor, and active smoking would lend support for an antiestrogenic mechanism.
We used multivariable linear regression to assess the associations of active smoking and secondhand smoke (SHS) exposure with mammographic density in 799 pre- and early perimenopausal women in the Study of Women’s Health Across the Nation (SWAN).
We observed that current active smoking was associated with 7.2% lower mammographic density, compared to never active smoking and no SHS exposure (p = 0.02). Starting to smoke before 18 years of age and having smoked ≥20 cigarettes/day were also associated with statistically significantly lower percent densities. Among nulliparous women having smoked ≥20 cigarettes/day was associated with 23.8% lower density, compared to having smoked ≤9 cigarettes/day (p < 0.001).
Our findings support the hypothesis that tobacco smoke exerts an antiestrogenic effect on breast tissue, but counters the known increased risk of breast cancer with smoking prior to first full-term birth. Thus, our data suggest that the antiestrogenic but not the carcinogenic effects of smoking may be reflected by breast density
Tratamento da mucosite em pacientes submetidos a transplante de medula óssea: uma revisão sistemática
Allogeneic transplant outcomes are not affected by body mass index (BMI) in patients with haematological malignancies
A Prospective Proteomic-Based Study for Identifying Potential Biomarkers for the Diagnosis of Cholangiocarcinoma
Global loss of DNA methylation uncovers intronic enhancers in genes showing expression changes
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