196 resultados para tumour biology


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Respiratory motion introduces complex spatio-temporal variations in the dosimetry of radiotherapy and may contribute towards uncertainties in radiotherapy planning. This study investigates the potential radiobiological implications occurring due to tumour motion in areas of geometric miss in lung cancer radiotherapy. A bespoke phantom and motor-driven platform to replicate respiratory motion and study the consequences on tumour cell survival in vitro was constructed. Human non-small-cell lung cancer cell lines H460 and H1299 were irradiated in modulated radiotherapy configurations in the presence and absence of respiratory motion. Clonogenic survival was calculated for irradiated and shielded regions. Direction of motion, replication of dosimetry by multi-leaf collimator (MLC) manipulation and oscillating lead shielding were investigated to confirm differences in cell survival. Respiratory motion was shown to significantly increase survival for out-of-field regions for H460/H1299 cell lines when compared with static irradiation (p <0.001). Significantly higher survival was found in the in-field region for the H460 cell line (p <0.030). Oscillating lead shielding also produced these significant differences. Respiratory motion and oscillatory delivery of radiation dose to human tumour cells has a significant impact on in- and out-of-field survival in the presence of non-uniform irradiation in this in vitro set-up. This may have important radiobiological consequences for modulated radiotherapy in lung cancer. 

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For the delivery of intensity-modulated radiation therapy (IMRT), highly modulated fields are used to achieve dose conformity across a target tumour volume. Recent in vitro evidence has demonstrated significant alterations in cell survival occurring out-of-field which cannot be accounted for on the basis of scattered dose. The radiobiological effect of area, dose and dose-rate on out-of-field cell survival responses following exposure to intensity-modulated radiation fields is presented in this study. Cell survival was determined by clonogenic assay in human prostate cancer (DU-145) and primary fibroblast (AG0-1522) cells following exposure to different modulated field configurations delivered using a X-Rad 225 kVp x-ray source. Uniform survival responses were compared to in- and out-of-field responses in which 25-99% of the cell population was shielded. Dose delivered to the out-of-field region was varied from 1.6-37.2% of that delivered to the in-field region using different levels of brass shielding. Dose rate effects were determined for 0.2-4 Gy min⁻¹ for uniform and modulated exposures with no effect seen in- or out-of-field. Survival responses showed little dependence on dose rate and area in- and out-of-field with a trend towards increased survival with decreased in-field area. Out-of-field survival responses were shown to scale in proportion to dose delivered to the in-field region and also local dose delivered out-of-field. Mathematical modelling of these findings has shown survival response to be highly dependent on dose delivered in- and out-of-field but not on area or dose rate. These data provide further insight into the radiobiological parameters impacting on cell survival following exposure to modulated irradiation fields highlighting the need for refinement of existing radiobiological models to incorporate non-targeted effects and modulated dose distributions.

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Radiation therapy is one of the most common and effective strategies used to treat cancer. The irradiation is usually performed with a fractionated scheme, where the dose required to kill tumour cells is given in several sessions, spaced by specific time intervals, to allow healthy tissue recovery. In this work, we examined the DNA repair dynamics of cells exposed to radiation delivered in fractions, by assessing the response of histone-2AX (H2AX) phosphorylation (γ-H2AX), a marker of DNA double strand breaks. γ-H2AX foci induction and disappearance were monitored following split dose irradiation experiments in which time interval between exposure and dose were varied. Experimental data have been coupled to an analytical theoretical model, in order to quantify key parameters involved in the foci induction process. Induction of γ-H2AX foci was found to be affected by the initial radiation exposure with a smaller number of foci induced by subsequent exposures. This was compared to chromatin relaxation and cell survival. The time needed for full recovery of γ-H2AX foci induction was quantified (12 hours) and the 1:1 relationship between radiation induced DNA double strand breaks and foci numbers was critically assessed in the multiple irradiation scenarios.

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Core biopsy is an increasingly used technique in the pre-operative diagnosis of breast carcinoma, as it provides useful prognostic information with respect to tumour type and grade. Neoadjuvant chemotherapy is being used in the treatment of large and locally advanced breast cancers but little is known regarding the correlation between tumour histology on pre-treatment core biopsy and that in residual tumour following primary chemotherapy and surgery. This study aimed to evaluate the accuracy of core biopsy in predicting these features in patients treated with primary chemotherapy. One hundred and thirty-three patients with carcinoma of the breast diagnosed on clinical, radiological and cytological examination underwent core biopsy, followed by primary chemotherapy (with cyclophosphamide, vincristine, doxorubicin and prednisolone) and surgery. The false-negative rate for pre-treatment core biopsy was 14%, with 91% agreement between the grade demonstrated on core biopsy and that in the residual tumour following completion of chemotherapy. Tumour type in the residual post-chemotherapy tumour was predicted by core biopsy in 84%. This study suggests that pre-treatment core biopsy histology accurately predicts residual tumour histology following primary chemotherapy and surgery in patients with breast cancer. (C) 2002 Elsevier Science Ltd. All rights reserved.

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The discovery of underlying mechanisms of drug resistance, and the development of novel agents to target these pathways, is a priority for patients with advanced colorectal cancer (CRC). We previously undertook a systems biology approach to design a functional genomic screen and identified fibroblast growth factor receptor 4 (FGFR4) as a potential mediator of drug resistance. The aim of this study was to examine the role of FGFR4 in drug resistance using RNAi and the small-molecule inhibitor BGJ398 (Novartis). We found that FGFR4 is highly expressed at the RNA and protein levels in colon cancer tumour tissue compared with normal colonic mucosa and other tumours. Silencing of FGFR4 reduced cell viability in a panel of colon cancer cell lines and increased caspase-dependent apoptosis. A synergistic interaction was also observed between FGFR4 silencing and 5-fluorouracil (5-FU) and oxaliplatin chemotherapy in colon cancer cell lines. Mechanistically, FGFR4 silencing decreased activity of the pro-survival STAT3 transcription factor and expression of the anti-apoptotic protein c-FLIP. Furthermore, silencing of STAT3 resulted in downregulation of c-FLIP protein expression, suggesting that FGFR4 may regulate c-FLIP expression via STAT3. A similar phenotype and downstream pathway changes were observed following FGFR4 silencing in cell lines resistant to 5-FU, oxaliplatin and SN38 and upon exposure of parental cells to the FGFR small-molecule inhibitor BGJ398. Our results indicate that FGFR4 is a targetable regulator of chemo-resistance in CRC, and hence inhibiting FGFR4 in combination with 5-FU and oxaliplatin is a potential therapeutic strategy for this disease.

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Macrophage migration inhibitory factor (MIF), which inhibits apoptosis and promotes angiogenesis, is expressed in cancers suppressing immune surveillance. Its biological role in human glioblastoma is, however, only poorly understood. We examined in-vivo expression of MIF in 166 gliomas and 23 normal control brains by immunohistochemistry. MIF immunoreactivity was enhanced in neoplastic astrocytes in WHO grade II glioma and increased significantly in higher tumour grades (III-IV). MIF expression was further assessed in 12 glioma cell lines in vitro. Quantitative RT-PCR showed that MIF mRNA expression was elevated up to 800-fold in malignant glioma cells compared with normal brain. This translated into high protein levels as assessed by immunoblotting of total cell lysates and by ELISA-based measurement of secreted MIF. Wild-type p53-retaining glioma cell lines expressed higher levels of MIF, which may be connected with the previously described role of MIF as a negative regulator of wild-type p53 signalling in tumour cells. Stable knockdown of MIF by shRNA in glioma cells significantly increased tumour cell susceptibility towards NK cell-mediated cytotoxicity. Furthermore, supernatant from mock-transfected cells, but not from MIF knockdown cells, induced downregulation of the activating immune receptor NKG2D on NK and CD8+ T cells. We thus propose that human glioma cell-derived MIF contributes to the immune escape of malignant gliomas by counteracting NK and cytotoxic T-cell-mediated tumour immune surveillance. Considering its further cell-intrinsic and extrinsic tumour-promoting effects and the availability of small molecule inhibitors, MIF seems to be a promising candidate for future glioma therapy.

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Here, we show for the first time that the familial breast/ovarian cancer susceptibility gene, BRCA1, along with interacting ΔNp63 proteins, transcriptionally upregulate the putative tumour suppressor protein, S100A2. Both BRCA1 and ΔNp63 proteins are required for S100A2 expression. BRCA1 requires ΔNp63 proteins for recruitment to the S100A2 proximal promoter region, while exogenous expression of individual ΔNp63 proteins cannot activate S100A2 transcription in the absence of a functional BRCA1. Consequently, mutation of the ΔNp63/p53 response element within the S100A2 promoter completely abrogates the ability of BRCA1 to upregulate S100A2. S100A2 shows growth control features in a range of cell models. Transient or stable exogenous S100A2 expression inhibits the growth of BRCA1 mutant and basal-like breast cancer cell lines, while short interfering RNA (siRNA) knockdown of S100A2 in non-tumorigenic cells results in enhanced proliferation. S100A2 modulates binding of mutant p53 to HSP90, which is required for efficient folding of mutant p53 proteins, by competing for binding to HSP70/HSP90 organising protein (HOP). HOP is a cochaperone that is required for the efficient transfer of proteins from HSP70 to HSP90. Loss of S100A2 leads to an HSP90-dependent stabilisation of mutant p53 with a concomitant loss of p63. Accordingly, S100A2-deficient cells are more sensitive to the HSP-90 inhibitor, 17-N-allylamino-17-demethoxygeldanamycin, potentially representing a novel therapeutic strategy for S100A2- and BRCA1-deficient cancers. Taken together, these data demonstrate the importance of S100A2 downstream of the BRCA1/ΔNp63 signalling axis in modulating transcriptional responses and enforcing growth control mechanisms through destabilisation of mutant p53.

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Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms.

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Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 × 10(-8)), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ∼2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.

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Objective: Molecular pathology relies on identifying anomalies using PCR or analysis of DNA/RNA. This is important in solid tumours where molecular stratification of patients define targeted treatment. These molecular biomarkers rely on examination of tumour, annotation for possible macro dissection/tumour cell enrichment and the estimation of % tumour. Manually marking up tumour is error prone. Method: We have developed a method for automated tumour mark-up and % cell calculations using image analysis called TissueMark® based on texture analysis for lung, colorectal and breast (cases=245, 100, 100 respectively). Pathologists marked slides for tumour and reviewed the automated analysis. A subset of slides was manually counted for tumour cells to provide a benchmark for automated image analysis. Results: There was a strong concordance between pathological and automated mark-up (100 % acceptance rate for macro-dissection). We also showed a strong concordance between manually/automatic drawn boundaries (median exclusion/inclusion error of 91.70 %/89 %). EGFR mutation analysis was precisely the same for manual and automated annotation-based macrodissection. The annotation accuracy rates in breast and colorectal cancer were 83 and 80 % respectively. Finally, region-based estimations of tumour percentage using image analysis showed significant correlation with actual cell counts. Conclusion: Image analysis can be used for macro-dissection to (i) annotate tissue for tumour and (ii) estimate the % tumour cells and represents an approach to standardising/improving molecular diagnostics.

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Background: Oncology is a field that profits tremendously from the genomic data generated by high-throughput technologies, including next-generation sequencing. However, in order to exploit, integrate, visualize and interpret such high-dimensional data efficiently, non-trivial computational and statistical analysis methods are required that need to be developed in a problem-directed manner.

Discussion: For this reason, computational cancer biology aims to fill this gap. Unfortunately, computational cancer biology is not yet fully recognized as a coequal field in oncology, leading to a delay in its maturation and, as an immediate consequence, an under-exploration of high-throughput data for translational research.

Summary: Here we argue that this imbalance, favoring 'wet lab-based activities', will be naturally rectified over time, if the next generation of scientists receives an academic education that provides a fair and competent introduction to computational biology and its manifold capabilities. Furthermore, we discuss a number of local educational provisions that can be implemented on university level to help in facilitating the process of harmonization.