79 resultados para Cancer biomarkers


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We investigated the role of the C1772T polymorphisms in exon 12 of the Hypoxia-inducible factor-1 alpha (HIF-1alpha) gene C1772T genotype in prostate cancer (PCa) and amplification of the hypoxic response. We identified the heterozygous germline CT genotype as an increased risk factor for clinically localised prostate cancer (Odds ratio = 6.2; p < 0.0001). While immunostaining intensity for HIF-1alpha and VEGF was significantly enhanced in 75% of PCa specimens when compared to matched benign specimens (p < 0.0001), the CT genotype did not modulate the kinetics of HIF-1alpha protein expression in hypoxia in vitro, and was not associated with enhanced expression of hypoxic biomarkers. This study provides the first evidence of an increased risk for clinically localised prostate cancer in men carrying the C1772T HIF-1alpha gene polymorphism. Although our results did not suggest an association between expression of hypoxic biomarkers and genotype status, the correlation may merit further investigation.

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Microarray technology has recently accelerated the study of the molecular events involved in prostate cancer, offering the prospect of more precise prognosis and new therapeutic strategies. This review summarises current knowledge of the molecular pathology of prostate cancer. The expression and function of numerous genes have been shown to be altered in prostate cancer. Many of these genes are involved in cell cycle regulation, steroid hormone metabolism or regulation of gene expression. The mechanisms by which androgen independence arises are discussed, including cross-activation, gene amplification and point mutations of the androgen receptor. Analysis of changes in the levels of expression of large numbers of genes during prostate cancer progression have provided a better understanding of the basis of the disease, yielding new molecular markers, such as hepsin, with potential use in diagnosis and prognosis.

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The progressive elucidation of the molecular pathogenesis of cancer has fueled the rational development of targeted drugs for patient populations stratified by genetic characteristics. Here we discuss general challenges relating to molecular diagnostics and describe predictive biomarkers for personalized cancer medicine. We also highlight resistance mechanisms for epidermal growth factor receptor (EGFR) kinase inhibitors in lung cancer. We envisage a future requiring the use of longitudinal genome sequencing and other omics technologies alongside combinatorial treatment to overcome cellular and molecular heterogeneity and prevent resistance caused by clonal evolution.

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To date, estrogen receptor, progestogen receptor, and HER2/neu represent molecular biomarkers currently used in routine clinical practice to aid treatment decisions. Over the last few years, a large body of preclinical and retrospective clinical data has accumulated that suggests that BRCA1 mutation functions as a novel predictive marker of response to chemotherapy. This article reviews the role of BRCA1 as a predictive marker of chemotherapy response in breast cancer and examines the link between BRCA1 deficiency and the basal-like phenotype. Search strategy. Data for this article were identified through MEDLINE and PubMed searches for published reports using the terms BRCA1, breast cancer, basal-like, chemotherapy, prognosis, and predictive markers. In some cases, due to the restriction of space, readers are referred to review articles to allow further reading. Only articles published in English were included.

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Background: Non-small cell lung cancer (NSCLC) is the leading cause of cancer mortality worldwide. At present no reliable biomarkers are available to guide the management of this condition. Microarray technology may allow appropriate biomarkers to be identified but present platforms are lacking disease focus and are thus likely to miss potentially vital information contained in patient tissue samples.

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Objectives: Treatment of epithelial ovarian cancer (EOC) remains a challenge, despite advances in surgery and chemotherapy. Hereditary ovarian cancer is primarily due to germline mutations in the BRCA1 tumour suppressor gene. In addition, sporadic EOC tumours display signi?cant of loss of BRCA1 function due to epigenetic inactivation of the BRCA1 gene. This article reviews the preclinical and clinical evidence to support a role for BRCA1 as a potential predictive biomarker of response to both platinum and taxane based chemotherapy in EOC.

Methods: We conducted a Medline and Pubmed search for reports between 1990 and 2008 using the search terms: BRCA1 and hereditary ovarian cancer, BRCA1 and sporadic ovarian cancer, ovarian cancer and chemotherapy, ovarian cancer and taxanes, ovarian cancer and platinums, ovarian cancer and clinical response, BRCA1 and DNA damage, BRCA1 and DNA repair, BRCA1 and mitotic checkpoint. If reports identi?ed by these criteria referred to other papers not in the initial search, then these were also reviewed if relevant to BRCA1 and ovarian cancer.

Results: The BRCA1 pathway plays a signi?cant role in the development of both hereditary and sporadic EOC. Evidence suggests that BRCA1 is a potential biomarker of response to platinum chemotherapy in EOC with BRCA1 de?ciency predicting for enhanced response. In contrast, initial evidence suggests that loss of BRCA1 function results in reduced response to antimicrotubule-based chemotherapy. The ability of BRCA1 to differentially modulate response to these agents involves loss of BRCA1 mediated DNA repair and mitotic checkpoint control, respectively.

Conclusions: Standard ?rst line treatment of EOC consists of a combination of platinum and taxane chemotherapy, however clinically useful biomarkers for predicting response to these agents have yet to be established. BRCA1 may prove useful as a biomarker in EOC for assigning chemotherapy treatments based on the presence or absence of BRCA1 function.

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Tissue microarrays allow high throughput molecular profiling of diagnostic or predictive markers in cancer specimens and rapid validation of novel potential candidates identified from genomic and proteomic analyses in a large number of tumor samples. To validate the use of tissue microarray technology for all the main biomarkers routinely used to decide breast cancer prognostication and postsurgical adjuvant therapy, we constructed a tissue microarray from 97 breast tumors, with a single 0.6 mm core per specimen. Inummostaining; of tissue microarray sections and conventional full sections of each tumor were performed using well-characterized prognostic markers (estrogen receptor ER, progesterone receptor PR and c-erbB2). The full section versus tissue microarray concordance for these stains was 97% for ER, 98% for PR, and 97% for c-erbB2, respectively, with a strong statistical association (kappa value more than 0.90). Fluorescence in situ hybridization analysis for HER-2/neu gene amplification from the single-core tissue microarray was technically successful in about 90% (87/97) of the cases, with a concordance of 95% compared with parallel analyses with the full sections. The correlation with other pathological parameters was not significantly different between full-section and array-based results. It is concluded that the constructed tissue microarray with a single core per specimen ensures full biological representativeness to identify the associations between biomarkers and clinicopathological parameters, with no significant associated sampling bias.

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Purpose: We previously found that cellular FLICE-inhibitory protein (c-FLIP), caspase 8, and tumor necrosis factor–related apoptosis-inducing ligand (TRAIL) receptor 2 (DR5) are major regulators of cell viability and chemotherapy-induced apoptosis in colorectal cancer. In this study, we determined the prognostic significance of c-FLIP, caspase 8, TRAIL and DR5 expression in tissues from patients with stage II and III colorectal cancer.

Experimental Design: Tissue microarrays were constructed from matched normal and tumor tissue derived from patients (n = 253) enrolled in a phase III trial of adjuvant 5-fluorouracil–based chemotherapy versus postoperative observation alone. TRAIL, DR5, caspase 8, and c-FLIP expression levels were determined by immunohistochemistry.

Results: Colorectal tumors displayed significantly higher expression levels of c-FLIP (P < 0.001), caspase 8 (P = 0.01), and DR5 (P < 0.001), but lower levels of TRAIL (P < 0.001) compared with matched normal tissue. In univariate analysis, higher TRAIL expression in the tumor was associated with worse overall survival (P = 0.026), with a trend to decreased relapse-free survival (RFS; P = 0.06), and higher tumor c-FLIP expression was associated with a significantly decreased RFS (P = 0.015). Using multivariate predictive modeling for RFS in all patients and including all biomarkers, age, treatment, and stage, we found that the model was significant when the mean tumor c-FLIP expression score and disease stage were included (P < 0.001). As regards overall survival, the overall model was predictive when both TRAIL expression and disease stage were included (P < 0.001).

Conclusions: High c-FLIP and TRAIL expression may be independent adverse prognostic markers in stage II and III colorectal cancer and might identify patients most at risk of relapse.

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Observational evidence consistently shows that consumption of a diet rich in fruit and vegetables may offer protection against diseases such as cardiovascular disease and cancer. Assessment of dietary intake is complex and prone to many sources of error. More objective biomarkers of fruit and vegetable intake are therefore of interest. The aim of this review is to examine the usefulness of the main biomarkers of fruit and vegetable intake to act as objective indicators of compliance in dietary intervention studies. A comprehensive search of the literature was conducted using six databases. Suitable papers were selected and relevant data extracted. The papers were categorized into 3 sub-groups: whole diet interventions; mixed fruit and vegetable interventions; and studies involving individual varieties of fruits or vegetables. Ninety-six studies were included in the review. Overall, the most commonly measured, and most consistently responsive, biomarkers were the carotenoids and vitamin C. Based on the results of this systematic review, it remains prudent to measure a panel of biomarkers in fruit and vegetable intervention studies. The only possible exception to this is “fruit only” intervention studies where assessment of vitamin C alone may suffice.

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Clinically, our ability to predict disease outcome for patients with early stage lung cancer is currently poor. To address this issue, tumour specimens were collected at surgery from non-small cell lung cancer (NSCLC) patients as part of the European Early Lung Cancer (EUELC) consortium. The patients were followed-up for three years post-surgery and patients who suffered progressive disease (PD, tumour recurrence, metastasis or a second primary) or remained disease-free (DF) during follow-up were identified. RNA from both tumour and adjacent-normal lung tissue was extracted from patients and subjected to microarray expression profiling. These samples included 36 adenocarcinomas and 23 squamous cell carcinomas from both PD and DF patients. The microarray data was subject to a series of systematic bioinformatics analyses at gene, network and transcription factor levels. The focus of these analyses was 2-fold: firstly to determine whether there were specific biomarkers capable of differentiating between PD and DF patients, and secondly, to identify molecular networks which may contribute to the progressive tumour phenotype. The experimental design and analyses performed permitted the clear differentiation between PD and DF patients using a set of biomarkers implicated in neuroendocrine signalling and allowed the inference of a set of transcription factors whose activity may differ according to disease outcome. Potential links between the biomarkers, the transcription factors and the genes p21/CDKN1A and Myc, which have previously been implicated in NSCLC development, were revealed by a combination of pathway analysis and microarray meta-analysis. These findings suggest that neuroendocrine-related genes, potentially driven through p21/CDKN1A and Myc, are closely linked to whether or not a NSCLC patient will have poor clinical outcome.