85 resultados para Mandibular Neoplasms


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PURPOSE: To investigate the dosimetric effects of adaptive planning on lung stereotactic body radiation therapy (SBRT). METHODS AND MATERIALS: Forty of 66 consecutive lung SBRT patients were selected for a retrospective adaptive planning study. CBCT images acquired at each fraction were used for treatment planning. Adaptive plans were created using the same planning parameters as the original CT-based plan, with the goal to achieve comparable comformality index (CI). For each patient, 2 cumulative plans, nonadaptive plan (PNON) and adaptive plan (PADP), were generated and compared for the following organs-at-risks (OARs): cord, esophagus, chest wall, and the lungs. Dosimetric comparison was performed between PNON and PADP for all 40 patients. Correlations were evaluated between changes in dosimetric metrics induced by adaptive planning and potential impacting factors, including tumor-to-OAR distances (dT-OAR), initial internal target volume (ITV1), ITV change (ΔITV), and effective ITV diameter change (ΔdITV). RESULTS: 34 (85%) patients showed ITV decrease and 6 (15%) patients showed ITV increase throughout the course of lung SBRT. Percentage ITV change ranged from -59.6% to 13.0%, with a mean (±SD) of -21.0% (±21.4%). On average of all patients, PADP resulted in significantly (P=0 to .045) lower values for all dosimetric metrics. ΔdITV/dT-OAR was found to correlate with changes in dose to 5 cc (ΔD5cc) of esophagus (r=0.61) and dose to 30 cc (ΔD30cc) of chest wall (r=0.81). Stronger correlations between ΔdITV/dT-OAR and ΔD30cc of chest wall were discovered for peripheral (r=0.81) and central (r=0.84) tumors, respectively. CONCLUSIONS: Dosimetric effects of adaptive lung SBRT planning depend upon target volume changes and tumor-to-OAR distances. Adaptive lung SBRT can potentially reduce dose to adjacent OARs if patients present large tumor volume shrinkage during the treatment.

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PURPOSE: Malignant ureteral obstruction often necessitates chronic urinary diversion and is associated with high rates of failure with traditional ureteral stents. We evaluated the outcomes of a metallic stent placed for malignant ureteral obstruction and determined the impact of risk factors previously associated with increased failure rates of traditional stents. MATERIALS AND METHODS: Patients undergoing placement of the metallic Resonance® stent for malignant ureteral obstruction at an academic referral center were identified retrospectively. Stent failure was defined as unplanned stent exchange or nephrostomy tube placement for signs or symptoms of recurrent ureteral obstruction (recurrent hydroureteronephrosis or increasing creatinine). Predictors of time to stent failure were assessed using Cox regression. RESULTS: A total of 37 stents were placed in 25 patients with malignant ureteral obstruction. Of these stents 12 (35%) were identified to fail. Progressive hydroureteronephrosis and increasing creatinine were the most common signs of stent failure. Three failed stents had migrated distally and no stents required removal for recurrent infection. Patients with evidence of prostate cancer invading the bladder at stent placement were found to have a significantly increased risk of failure (HR 6.50, 95% CI 1.45-29.20, p = 0.015). Notably symptomatic subcapsular hematomas were identified in 3 patients after metallic stent placement. CONCLUSIONS: Failure rates with a metallic stent are similar to those historically observed with traditional polyurethane based stents in malignant ureteral obstruction. The invasion of prostate cancer in the bladder significantly increases the risk of failure. Patients should be counseled and observed for subcapsular hematoma formation with this device.

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Brain tumors are typically resistant to conventional chemotherapeutics, most of which initiate apoptosis upstream of mitochondrial cytochrome c release. In this study, we demonstrate that directly activating apoptosis downstream of the mitochondria, with cytosolic cytochrome c, kills brain tumor cells but not normal brain tissue. Specifically, cytosolic cytochrome c is sufficient to induce apoptosis in glioblastoma and medulloblastoma cell lines. In contrast, primary neurons from the cerebellum and cortex are remarkably resistant to cytosolic cytochrome c. Importantly, tumor tissue from mouse models of both high-grade astrocytoma and medulloblastoma display hypersensitivity to cytochrome c when compared with surrounding brain tissue. This differential sensitivity to cytochrome c is attributed to high Apaf-1 levels in the tumor tissue compared with low Apaf-1 levels in the adjacent brain tissue. These differences in Apaf-1 abundance correlate with differences in the levels of E2F1, a previously identified activator of Apaf-1 transcription. ChIP assays reveal that E2F1 binds the Apaf-1 promoter specifically in tumor tissue, suggesting that E2F1 contributes to the expression of Apaf-1 in brain tumors. Together, these results demonstrate an unexpected sensitivity of brain tumors to postmitochondrial induction of apoptosis. Moreover, they raise the possibility that this phenomenon could be exploited therapeutically to selectively kill brain cancer cells while sparing the surrounding brain parenchyma.

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In the intrinsic pathway of apoptosis, cell-damaging signals promote the release of cytochrome c from mitochondria, triggering activation of the Apaf-1 and caspase-9 apoptosome. The ubiquitin E3 ligase MDM2 decreases the stability of the proapoptotic factor p53. We show that it also coordinated apoptotic events in a p53-independent manner by ubiquitylating the apoptosome activator CAS and the ubiquitin E3 ligase HUWE1. HUWE1 ubiquitylates the antiapoptotic factor Mcl-1, and we found that HUWE1 also ubiquitylated PP5 (protein phosphatase 5), which indirectly inhibited apoptosome activation. Breast cancers that are positive for the tyrosine receptor kinase HER2 (human epidermal growth factor receptor 2) tend to be highly aggressive. In HER2-positive breast cancer cells treated with the HER2 tyrosine kinase inhibitor lapatinib, MDM2 was degraded and HUWE1 was stabilized. In contrast, in breast cancer cells that acquired resistance to lapatinib, the abundance of MDM2 was not decreased and HUWE1 was degraded, which inhibited apoptosis, regardless of p53 status. MDM2 inhibition overcame lapatinib resistance in cells with either wild-type or mutant p53 and in xenograft models. These findings demonstrate broader, p53-independent roles for MDM2 and HUWE1 in apoptosis and specifically suggest the potential for therapy directed against MDM2 to overcome lapatinib resistance.

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OBJECTIVE: To investigate the effect of statin use after radical prostatectomy (RP) on biochemical recurrence (BCR) in patients with prostate cancer who never received statins before RP. PATIENTS AND METHODS: We conducted a retrospective analysis of 1146 RP patients within the Shared Equal Access Regional Cancer Hospital (SEARCH) database. Multivariable Cox proportional hazards analyses were used to examine differences in risk of BCR between post-RP statin users vs nonusers. To account for varying start dates and duration of statin use during follow-up, post-RP statin use was treated as a time-dependent variable. In a secondary analysis, models were stratified by race to examine the association of post-RP statin use with BCR among black and non-black men. RESULTS: After adjusting for clinical and pathological characteristics, post-RP statin use was significantly associated with 36% reduced risk of BCR (hazard ratio [HR] 0.64, 95% confidence interval [CI] 0.47-0.87; P = 0.004). Post-RP statin use remained associated with reduced risk of BCR after adjusting for preoperative serum cholesterol levels. In secondary analysis, after stratification by race, this protective association was significant in non-black (HR 0.49, 95% CI 0.32-0.75; P = 0.001) but not black men (HR 0.82, 95% CI 0.53-1.28; P = 0.384). CONCLUSION: In this retrospective cohort of men undergoing RP, post-RP statin use was significantly associated with reduced risk of BCR. Whether the association between post-RP statin use and BCR differs by race requires further study. Given these findings, coupled with other studies suggesting that statins may reduce risk of advanced prostate cancer, randomised controlled trials are warranted to formally test the hypothesis that statins slow prostate cancer progression.

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BACKGROUND: We have previously shown that a functional polymorphism of the UGT2B15 gene (rs1902023) was associated with increased risk of prostate cancer (PC). Novel functional polymorphisms of the UGT2B17 and UGT2B15 genes have been recently characterized by in vitro assays but have not been evaluated in epidemiologic studies. METHODS: Fifteen functional SNPs of the UGT2B17 and UGT2B15 genes, including cis-acting UGT2B gene SNPs, were genotyped in African American and Caucasian men (233 PC cases and 342 controls). Regression models were used to analyze the association between SNPs and PC risk. RESULTS: After adjusting for race, age and BMI, we found that six UGT2B15 SNPs (rs4148269, rs3100, rs9994887, rs13112099, rs7686914 and rs7696472) were associated with an increased risk of PC in log-additive models (p < 0.05). A SNP cis-acting on UGT2B17 and UGT2B15 expression (rs17147338) was also associated with increased risk of prostate cancer (OR = 1.65, 95% CI = 1.00-2.70); while a stronger association among men with high Gleason sum was observed for SNPs rs4148269 and rs3100. CONCLUSIONS: Although small sample size limits inference, we report novel associations between UGT2B15 and UGT2B17 variants and PC risk. These associations with PC risk in men with high Gleason sum, more frequently found in African American men, support the relevance of genetic differences in the androgen metabolism pathway, which could explain, in part, the high incidence of PC among African American men. Larger studies are required.

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Prostate growth is dependent on circulating androgens, which can be influenced by hepatic function. Liver disease has been suggested to influence prostate cancer (CaP) incidence. However, the effect of hepatic function on CaP outcomes has not been investigated. A total of 1181 patients who underwent radical prostatectomy (RP) between 1988 and 2008 at four Veterans Affairs hospitals that comprise the Shared Equal Access Regional Cancer Hospital database and had available liver function test (LFT) data were included in the study. Independent associations of LFTs with unfavorable pathological features and biochemical recurrence were determined using logistic and Cox regression analyses. Serum glutamic oxaloacetic transaminase (SGOT) and serum glutamic pyruvic transaminase (SGPT) levels were elevated in 8.2 and 4.4% of patients, respectively. After controlling for CaP features, logistic regression revealed a significant association between SGOT levels and pathological Gleason sum > or =7(4+3) cancer (odds ratio=2.12; 95% confidence interval=1.11-4.05; P=0.02). Mild hepatic dysfunction was significantly associated with adverse CaP grade, but was not significantly associated with other adverse pathological features or biochemical recurrence in a cohort of men undergoing RP. The effect of moderate-to-severe liver disease on disease outcomes in CaP patients managed non-surgically remains to be investigated.

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OBJECTIVES: To compare the predictive performance and potential clinical usefulness of risk calculators of the European Randomized Study of Screening for Prostate Cancer (ERSPC RC) with and without information on prostate volume. METHODS: We studied 6 cohorts (5 European and 1 US) with a total of 15,300 men, all biopsied and with pre-biopsy TRUS measurements of prostate volume. Volume was categorized into 3 categories (25, 40, and 60 cc), to reflect use of digital rectal examination (DRE) for volume assessment. Risks of prostate cancer were calculated according to a ERSPC DRE-based RC (including PSA, DRE, prior biopsy, and prostate volume) and a PSA + DRE model (including PSA, DRE, and prior biopsy). Missing data on prostate volume were completed by single imputation. Risk predictions were evaluated with respect to calibration (graphically), discrimination (AUC curve), and clinical usefulness (net benefit, graphically assessed in decision curves). RESULTS: The AUCs of the ERSPC DRE-based RC ranged from 0.61 to 0.77 and were substantially larger than the AUCs of a model based on only PSA + DRE (ranging from 0.56 to 0.72) in each of the 6 cohorts. The ERSPC DRE-based RC provided net benefit over performing a prostate biopsy on the basis of PSA and DRE outcome in five of the six cohorts. CONCLUSIONS: Identifying men at increased risk for having a biopsy detectable prostate cancer should consider multiple factors, including an estimate of prostate volume.

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BACKGROUND: Genetic association studies are conducted to discover genetic loci that contribute to an inherited trait, identify the variants behind these associations and ascertain their functional role in determining the phenotype. To date, functional annotations of the genetic variants have rarely played more than an indirect role in assessing evidence for association. Here, we demonstrate how these data can be systematically integrated into an association study's analysis plan. RESULTS: We developed a Bayesian statistical model for the prior probability of phenotype-genotype association that incorporates data from past association studies and publicly available functional annotation data regarding the susceptibility variants under study. The model takes the form of a binary regression of association status on a set of annotation variables whose coefficients were estimated through an analysis of associated SNPs in the GWAS Catalog (GC). The functional predictors examined included measures that have been demonstrated to correlate with the association status of SNPs in the GC and some whose utility in this regard is speculative: summaries of the UCSC Human Genome Browser ENCODE super-track data, dbSNP function class, sequence conservation summaries, proximity to genomic variants in the Database of Genomic Variants and known regulatory elements in the Open Regulatory Annotation database, PolyPhen-2 probabilities and RegulomeDB categories. Because we expected that only a fraction of the annotations would contribute to predicting association, we employed a penalized likelihood method to reduce the impact of non-informative predictors and evaluated the model's ability to predict GC SNPs not used to construct the model. We show that the functional data alone are predictive of a SNP's presence in the GC. Further, using data from a genome-wide study of ovarian cancer, we demonstrate that their use as prior data when testing for association is practical at the genome-wide scale and improves power to detect associations. CONCLUSIONS: We show how diverse functional annotations can be efficiently combined to create 'functional signatures' that predict the a priori odds of a variant's association to a trait and how these signatures can be integrated into a standard genome-wide-scale association analysis, resulting in improved power to detect truly associated variants.

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BACKGROUND: We analyzed the association between 53 genes related to DNA repair and p53-mediated damage response and serous ovarian cancer risk using case-control data from the North Carolina Ovarian Cancer Study (NCOCS), a population-based, case-control study. METHODS/PRINCIPAL FINDINGS: The analysis was restricted to 364 invasive serous ovarian cancer cases and 761 controls of white, non-Hispanic race. Statistical analysis was two staged: a screen using marginal Bayes factors (BFs) for 484 SNPs and a modeling stage in which we calculated multivariate adjusted posterior probabilities of association for 77 SNPs that passed the screen. These probabilities were conditional on subject age at diagnosis/interview, batch, a DNA quality metric and genotypes of other SNPs and allowed for uncertainty in the genetic parameterizations of the SNPs and number of associated SNPs. Six SNPs had Bayes factors greater than 10 in favor of an association with invasive serous ovarian cancer. These included rs5762746 (median OR(odds ratio)(per allele) = 0.66; 95% credible interval (CI) = 0.44-1.00) and rs6005835 (median OR(per allele) = 0.69; 95% CI = 0.53-0.91) in CHEK2, rs2078486 (median OR(per allele) = 1.65; 95% CI = 1.21-2.25) and rs12951053 (median OR(per allele) = 1.65; 95% CI = 1.20-2.26) in TP53, rs411697 (median OR (rare homozygote) = 0.53; 95% CI = 0.35 - 0.79) in BACH1 and rs10131 (median OR( rare homozygote) = not estimable) in LIG4. The six most highly associated SNPs are either predicted to be functionally significant or are in LD with such a variant. The variants in TP53 were confirmed to be associated in a large follow-up study. CONCLUSIONS/SIGNIFICANCE: Based on our findings, further follow-up of the DNA repair and response pathways in a larger dataset is warranted to confirm these results.

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With the lifetime risk of being diagnosed with prostate cancer so great, an effective chemopreventive agent could have a profound impact on the lives of men. Despite decades of searching for such an agent, physicians still do not have an approved drug to offer their patients. In this article, we outline current strategies for preventing prostate cancer in general, with a focus on the 5-α-reductase inhibitors (5-ARIs) finasteride and dutasteride. We discuss the two landmark randomized, controlled trials of finasteride and dutasteride, highlighting the controversies stemming from the results, and address the issue of 5-ARI use, including reasons why providers may be hesitant to use these agents for chemoprevention. We further discuss the recent US Food and Drug Administration ruling against the proposed new indication for dutasteride and the change to the labeling of finasteride, both of which were intended to permit physicians to use the drugs for chemoprevention. Finally, we discuss future directions for 5-ARI research.

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Currently, no available pathological or molecular measures of tumor angiogenesis predict response to antiangiogenic therapies used in clinical practice. Recognizing that tumor endothelial cells (EC) and EC activation and survival signaling are the direct targets of these therapies, we sought to develop an automated platform for quantifying activity of critical signaling pathways and other biological events in EC of patient tumors by histopathology. Computer image analysis of EC in highly heterogeneous human tumors by a statistical classifier trained using examples selected by human experts performed poorly due to subjectivity and selection bias. We hypothesized that the analysis can be optimized by a more active process to aid experts in identifying informative training examples. To test this hypothesis, we incorporated a novel active learning (AL) algorithm into FARSIGHT image analysis software that aids the expert by seeking out informative examples for the operator to label. The resulting FARSIGHT-AL system identified EC with specificity and sensitivity consistently greater than 0.9 and outperformed traditional supervised classification algorithms. The system modeled individual operator preferences and generated reproducible results. Using the results of EC classification, we also quantified proliferation (Ki67) and activity in important signal transduction pathways (MAP kinase, STAT3) in immunostained human clear cell renal cell carcinoma and other tumors. FARSIGHT-AL enables characterization of EC in conventionally preserved human tumors in a more automated process suitable for testing and validating in clinical trials. The results of our study support a unique opportunity for quantifying angiogenesis in a manner that can now be tested for its ability to identify novel predictive and response biomarkers.

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Gliomagenesis is driven by a complex network of genetic alterations and while the glioma genome has been a focus of investigation for many years; critical gaps in our knowledge of this disease remain. The identification of novel molecular biomarkers remains a focus of the greater cancer community as a method to improve the consistency and accuracy of pathological diagnosis. In addition, novel molecular biomarkers are drastically needed for the identification of targets that may ultimately result in novel therapeutics aimed at improving glioma treatment. Through the identification of new biomarkers, laboratories will focus future studies on the molecular mechanisms that underlie glioma development. Here, we report a series of genomic analyses identifying novel molecular biomarkers in multiple histopathological subtypes of glioma and refine the classification of malignant gliomas. We have completed a large scale analysis of the WHO grade II-III astrocytoma exome and report frequent mutations in the chromatin modifier, alpha thalassemia mental retardation x-linked (ATRX), isocitrate dehydrogenase 1 and 2 (IDH1 and IDH2), and mutations in tumor protein 53 (TP53) as the most frequent genetic mutations in low grade astrocytomas. Furthermore, by analyzing the status of recurrently mutated genes in 363 brain tumors, we establish that highly recurrent gene mutational signatures are an effective tool in stratifying homogeneous patient populations into distinct groups with varying outcomes, thereby capable of predicting prognosis. Next, we have established mutations in the promoter of telomerase reverse transcriptase (TERT) as a frequent genetic event in gliomas and in tissues with low rates of self renewal. We identify TERT promoter mutations as the most frequently mutated gene in primary glioblastoma. Additionally, we show that TERT promoter mutations in combination with IDH1 and IDH2 mutations are able to delineate distinct clinical tumor cohorts and are capable of predicting median overall survival more effectively than standard histopathological diagnosis alone. Taken together, these data advance our understanding of the genetic alterations that underlie the transformation of glial cells into neoplasms and we provide novel genetic biomarkers and multi – gene mutational signatures that can be utilized to refine the classification of malignant gliomas and provide opportunity for improved diagnosis.

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Previously published reports indicate that serum copper levels are elevated in patients with prostate cancer and that increased copper uptake can be used as a means to image prostate tumors. It is unclear, however, to what extent copper is required for prostate cancer cell function as we observed only modest effects of chelation strategies on the growth of these cells in vitro. With the goal of exploiting prostate cancer cell proclivity for copper uptake, we developed a "conditional lethal" screen to identify compounds whose cytotoxic actions were manifested in a copper-dependent manner. Emerging from this screen was a series of dithiocarbamates, which, when complexed with copper, induced reactive oxygen species-dependent apoptosis of malignant, but not normal, prostate cells. One of the dithiocarbamates identified, disulfiram (DSF), is an FDA-approved drug that has previously yielded disappointing results in clinical trials in patients with recurrent prostate cancer. Similarly, in our studies, DSF alone had a minimal effect on the growth of prostate cancer tumors when propagated as xenografts. However, when DSF was coadministered with copper, a very dramatic inhibition of tumor growth in models of hormone-sensitive and of castrate-resistant disease was observed. Furthermore, we determined that prostate cancer cells express high levels of CTR1, the primary copper transporter, and additional chaperones that are required to maintain intracellular copper homeostasis. The expression levels of most of these proteins are increased further upon treatment of androgen receptor (AR)-positive prostate cancer cell lines with androgens. Not surprisingly, robust CTR1-dependent uptake of copper into prostate cancer cells was observed, an activity that was accentuated by activation of AR. Given these data linking AR to intracellular copper uptake, we believe that dithiocarbamate/copper complexes are likely to be effective for the treatment of patients with prostate cancer whose disease is resistant to classical androgen ablation therapies.

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Pharmacogenomics (PGx) offers the promise of utilizing genetic fingerprints to predict individual responses to drugs in terms of safety, efficacy and pharmacokinetics. Early-phase clinical trial PGx applications can identify human genome variations that are meaningful to study design, selection of participants, allocation of resources and clinical research ethics. Results can inform later-phase study design and pipeline developmental decisions. Nevertheless, our review of the clinicaltrials.gov database demonstrates that PGx is rarely used by drug developers. Of the total 323 trials that included PGx as an outcome, 80% have been conducted by academic institutions after initial regulatory approval. Barriers for the application of PGx are discussed. We propose a framework for the role of PGx in early-phase drug development and recommend PGx be universally considered in study design, result interpretation and hypothesis generation for later-phase studies, but PGx results from underpowered studies should not be used by themselves to terminate drug-development programs.