937 resultados para Lung-cancer Mortality
Resumo:
Purpose: Eicosapentaenoic acid (EPA) has been proposed to have specific anticachectic effects. This trial compared EPA diethyl ester with placebo in cachectic cancer patients for effects on weight and lean body mass. Patients and Methods: Five hundred eighteen weight-losing patients with advanced gastrointestinal or lung cancer were studied in a multicenter, double-blind, placebo controlled trial. Patients were randomly assigned to receive a novel preparation of pure EPA at a dose of 2 g or 4 g daily or placebo (2g EPA, n = 175; 4 g EPA, n = 172; placebo, n = 171). Patients were assessed at 4 weeks and 8 weeks. Results: The groups were well balanced at baseline. Mean weight loss at baseline was 18% (n = 518). Over the 8-week treatment period, both intention-to-treat analysis and per protocol analysis revealed no statistically significant improvements in survival, weight, or other nutritional variables. There was, however, a trend in favor of EPA with analysis of the primary end point, weight, at 8 weeks showing a borderline, nonsignificant treatment effect (P = .066). Relative to placebo, mean weight increased by 1.2 kg with 2 g EPA (95% CI, 0 kg to 2.3 kg) and by 0.3 kg with 4g EPA (-0.9 kg to 1.5 kg). Conclusion: The results indicate no statistically significant benefit from single agent EPA in the treatment of cancer cachexia. Future studies should concentrate on other agents or combination regimens. © 2006 by American Society of Clinical Oncology.
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Respiratory gating in lung PET imaging to compensate for respiratory motion artifacts is a current research issue with broad potential impact on quantitation, diagnosis and clinical management of lung tumors. However, PET images collected at discrete bins can be significantly affected by noise as there are lower activity counts in each gated bin unless the total PET acquisition time is prolonged, so that gating methods should be combined with imaging-based motion correction and registration methods. The aim of this study was to develop and validate a fast and practical solution to the problem of respiratory motion for the detection and accurate quantitation of lung tumors in PET images. This included: (1) developing a computer-assisted algorithm for PET/CT images that automatically segments lung regions in CT images, identifies and localizes lung tumors of PET images; (2) developing and comparing different registration algorithms which processes all the information within the entire respiratory cycle and integrate all the tumor in different gated bins into a single reference bin. Four registration/integration algorithms: Centroid Based, Intensity Based, Rigid Body and Optical Flow registration were compared as well as two registration schemes: Direct Scheme and Successive Scheme. Validation was demonstrated by conducting experiments with the computerized 4D NCAT phantom and with a dynamic lung-chest phantom imaged using a GE PET/CT System. Iterations were conducted on different size simulated tumors and different noise levels. Static tumors without respiratory motion were used as gold standard; quantitative results were compared with respect to tumor activity concentration, cross-correlation coefficient, relative noise level and computation time. Comparing the results of the tumors before and after correction, the tumor activity values and tumor volumes were closer to the static tumors (gold standard). Higher correlation values and lower noise were also achieved after applying the correction algorithms. With this method the compromise between short PET scan time and reduced image noise can be achieved, while quantification and clinical analysis become fast and precise.
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Lung cancer is one of the most common types of cancer and has the highest mortality rate. Patient survival is highly correlated with early detection. Computed Tomography technology services the early detection of lung cancer tremendously by offering aminimally invasive medical diagnostic tool. However, the large amount of data per examination makes the interpretation difficult. This leads to omission of nodules by human radiologist. This thesis presents a development of a computer-aided diagnosis system (CADe) tool for the detection of lung nodules in Computed Tomography study. The system, called LCD-OpenPACS (Lung Cancer Detection - OpenPACS) should be integrated into the OpenPACS system and have all the requirements for use in the workflow of health facilities belonging to the SUS (Brazilian health system). The LCD-OpenPACS made use of image processing techniques (Region Growing and Watershed), feature extraction (Histogram of Gradient Oriented), dimensionality reduction (Principal Component Analysis) and classifier (Support Vector Machine). System was tested on 220 cases, totaling 296 pulmonary nodules, with sensitivity of 94.4% and 7.04 false positives per case. The total time for processing was approximately 10 minutes per case. The system has detected pulmonary nodules (solitary, juxtavascular, ground-glass opacity and juxtapleural) between 3 mm and 30 mm.
Resumo:
Background: Statin therapy reduces the risk of occlusive vascular events, but uncertainty remains about potential effects on cancer. We sought to provide a detailed assessment of any effects on cancer of lowering LDL cholesterol (LDL-C) with a statin using individual patient records from 175,000 patients in 27 large-scale statin trials. Methods and Findings: Individual records of 134,537 participants in 22 randomised trials of statin versus control (median duration 4.8 years) and 39,612 participants in 5 trials of more intensive versus less intensive statin therapy (median duration 5.1 years) were obtained. Reducing LDL-C with a statin for about 5 years had no effect on newly diagnosed cancer or on death from such cancers in either the trials of statin versus control (cancer incidence: 3755 [1.4% per year [py]] versus 3738 [1.4% py], RR 1.00 [95% CI 0.96-1.05]; cancer mortality: 1365 [0.5% py] versus 1358 [0.5% py], RR 1.00 [95% CI 0.93-1.08]) or in the trials of more versus less statin (cancer incidence: 1466 [1.6% py] vs 1472 [1.6% py], RR 1.00 [95% CI 0.93-1.07]; cancer mortality: 447 [0.5% py] versus 481 [0.5% py], RR 0.93 [95% CI 0.82-1.06]). Moreover, there was no evidence of any effect of reducing LDL-C with statin therapy on cancer incidence or mortality at any of 23 individual categories of sites, with increasing years of treatment, for any individual statin, or in any given subgroup. In particular, among individuals with low baseline LDL-C (<2 mmol/L), there was no evidence that further LDL-C reduction (from about 1.7 to 1.3 mmol/L) increased cancer risk (381 [1.6% py] versus 408 [1.7% py]; RR 0.92 [99% CI 0.76-1.10]). Conclusions: In 27 randomised trials, a median of five years of statin therapy had no effect on the incidence of, or mortality from, any type of cancer (or the aggregate of all cancer).
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Some patients with cancer never develop metastasis, and their host response might provide cues for innovative treatment strategies. We previously reported an association between autoantibodies against complement factor H (CFH) and early-stage lung cancer. CFH prevents complement-mediated cytotoxicity (CDC) by inhibiting formation of cell-lytic membrane attack complexes on self-surfaces. In an effort to translate these findings into a biologic therapy for cancer, we isolated and expressed DNA sequences encoding high-affinity human CFH antibodies directly from single, sorted B cells obtained from patients with the antibody. The co-crystal structure of a CFH antibody-target complex shows a conformational change in the target relative to the native structure. This recombinant CFH antibody causes complement activation and release of anaphylatoxins, promotes CDC of tumor cell lines, and inhibits tumor growth in vivo. The isolation of anti-tumor antibodies derived from single human B cells represents an alternative paradigm in antibody drug discovery.
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Knowledge-based radiation treatment is an emerging concept in radiotherapy. It
mainly refers to the technique that can guide or automate treatment planning in
clinic by learning from prior knowledge. Dierent models are developed to realize
it, one of which is proposed by Yuan et al. at Duke for lung IMRT planning. This
model can automatically determine both beam conguration and optimization ob-
jectives with non-coplanar beams based on patient-specic anatomical information.
Although plans automatically generated by this model demonstrate equivalent or
better dosimetric quality compared to clinical approved plans, its validity and gener-
ality are limited due to the empirical assignment to a coecient called angle spread
constraint dened in the beam eciency index used for beam ranking. To eliminate
these limitations, a systematic study on this coecient is needed to acquire evidences
for its optimal value.
To achieve this purpose, eleven lung cancer patients with complex tumor shape
with non-coplanar beams adopted in clinical approved plans were retrospectively
studied in the frame of the automatic lung IMRT treatment algorithm. The primary
and boost plans used in three patients were treated as dierent cases due to the
dierent target size and shape. A total of 14 lung cases, thus, were re-planned using
the knowledge-based automatic lung IMRT planning algorithm by varying angle
spread constraint from 0 to 1 with increment of 0.2. A modied beam angle eciency
index used for navigate the beam selection was adopted. Great eorts were made to assure the quality of plans associated to every angle spread constraint as good
as possible. Important dosimetric parameters for PTV and OARs, quantitatively
re
ecting the plan quality, were extracted from the DVHs and analyzed as a function
of angle spread constraint for each case. Comparisons of these parameters between
clinical plans and model-based plans were evaluated by two-sampled Students t-tests,
and regression analysis on a composite index built on the percentage errors between
dosimetric parameters in the model-based plans and those in the clinical plans as a
function of angle spread constraint was performed.
Results show that model-based plans generally have equivalent or better quality
than clinical approved plans, qualitatively and quantitatively. All dosimetric param-
eters except those for lungs in the automatically generated plans are statistically
better or comparable to those in the clinical plans. On average, more than 15% re-
duction on conformity index and homogeneity index for PTV and V40, V60 for heart
while an 8% and 3% increase on V5, V20 for lungs, respectively, are observed. The
intra-plan comparison among model-based plans demonstrates that plan quality does
not change much with angle spread constraint larger than 0.4. Further examination
on the variation curve of the composite index as a function of angle spread constraint
shows that 0.6 is the optimal value that can result in statistically the best achievable
plans.
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Tumor angiogenesis is critical to tumor growth and metastasis, yet much is unknown about the role vascular cells play in the tumor microenvironment. A major outstanding challenge associated with studying tumor angiogenesis is that existing preclinical models are limited in their recapitulation of in vivo cellular organization in 3D. This disparity highlights the need for better approaches to study the dynamic interplay of relevant cells and signaling molecules as they are organized in the tumor microenvironment. In this thesis, we combined 3D culture of lung adenocarcinoma cells with adjacent 3D microvascular cell culture in 2-layer cell-adhesive, proteolytically-degradable poly(ethylene glycol) (PEG)-based hydrogels to study tumor angiogenesis and the impacts of neovascularization on tumor cell behavior.
In initial studies, 344SQ cells, a highly metastatic, murine lung adenocarcinoma cell line, were characterized alone in 3D in PEG hydrogels. 344SQ cells formed spheroids in 3D culture and secreted proangiogenic growth factors into the conditioned media that significantly increased with exposure to transforming growth factor beta 1 (TGF-β1), a potent tumor progression-promoting factor. Vascular cells alone in hydrogels formed tubule networks with localized activated TGF-β1. To study cancer cell-vascular cell interactions, the engineered 2-layer tumor angiogenesis model with 344SQ and vascular cell layers was employed. Large, invasive 344SQ clusters developed at the interface between the layers, and were not evident further from the interface or in control hydrogels without vascular cells. A modified model with spatially restricted 344SQ and vascular cell layers confirmed that observed 344SQ cluster morphological changes required close proximity to vascular cells. Additionally, TGF-β1 inhibition blocked endothelial cell-driven 344SQ migration.
Two other lung adenocarcinoma cell lines were also explored in the tumor angiogenesis model: primary tumor-derived metastasis-incompetent, murine 393P cells and primary tumor-derived metastasis-capable human A549 cells. These lung cancer cells also formed spheroids in 3D culture and secreted proangiogenic growth factors into the conditioned media. Epithelial morphogenesis varied for the primary tumor-derived cell lines compared to 344SQ cells, with far less epithelial organization present in A549 spheroids. Additionally, 344SQ cells secreted the highest concentration of two of the three angiogenic growth factors assessed. This finding correlated to 344SQ exhibiting the most pronounced morphological response in the tumor angiogenesis model compared to the 393P and A549 cell lines.
Overall, this dissertation demonstrates the development of a novel 3D tumor angiogenesis model that was used to study vascular cell-cancer cell interactions in lung adenocarcinoma cell lines with varying metastatic capacities. Findings in this thesis have helped to elucidate the role of vascular cells in tumor progression and have identified differences in cancer cell behavior in vitro that correlate to metastatic capacity, thus highlighting the usefulness of this model platform for future discovery of novel tumor angiogenesis and tumor progression-promoting targets.
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Recent studies suggest that lung cancer stem cells (CSCs) may play major roles in lung cancer development, metastasis and drug resistance. Therefore, identification of lung CSC drivers may provide promising targets for lung cancer. TAZ (transcriptional co-activator with PDZ-binding motif) is a transcriptional co-activator and key downstream effector of the Hippo pathway, which plays critical roles in various biological processes. TAZ has been shown to be overexpressed in non-small cell lung cancer (NSCLC) and involved in tumorigenicity of lung epithelial cells. However, whether TAZ is a driver for lung CSCs and tumor formation in vivo is unknown. In addition, the molecular mechanism underlying TAZ-induced lung tumorigenesis remains to be determined. In this study, we provided evidence that constitutively active TAZ (TAZ-S89A) is a driver for lung tumorigenesis in vivo in mice and formation of lung CSC. Oncogenes upregulated in TAZ-overexpressing cells were identified with further validation. The most dramatically activated gene, Aldh1a1 (Aldehyde dehydrogenase 1 family member a1), a well-established CSC marker, showed that TAZ induces Aldh1a1 transcription by activating its promoter activity through interaction with the transcription factor TEA domain (TEAD) family member. Most significantly, inhibition of ALDH1A1 with its inhibitor A37 or CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) gene knockout in lung cancer cells suppressed lung tumorigenic and CSC phenotypes in vitro, and tumor formation in mice in vivo. In conclusion, this study identified TAZ as a novel inducer of lung CSCs and the first transcriptional activator of the stem cell marker ALDH1A1. Most significantly, we identified ALDH1A1 as a critical meditator of TAZ-induced tumorigenic and CSC phenotypes in lung cancer. Our studies provided preclinical data for targeting of TAZ-TEAD-ALDH1A1 signaling to inhibit CSC-induced lung tumorigenesis and drug resistance in the future.
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Introduction: Detection of the ALK rearrangement in a solid tumor gives these patients the option of crizotinib as an oral form of anticancer treatment. The current test of choice is fluorescence in situ hybridization (FISH), but various cheaper and more convenient immunohistochemical (IHC) assays have been proposed as alternatives.
Methods: Fifteen FISH-positive cases from patients, seven with data on crizotinib therapy and clinical response, were evaluated for the presence of ALK protein using three different commercially available antibodies: D5F3, using the proprietary automated system (Ventana), ALK1 (Dako), and 5A4 (Abcam). A further 14 FISH-negative and three uncertain (<15% rearrangement detected) cases were also retrieved. Of the total 32 specimens, 17 were excisions and 15 were computed tomography-guided biopsies or cytological specimens. All three antibodies were applied to all cases. Antibodies were semiquantitatively scored on intensity, and the proportion of malignant cells stained was documented. Cutoffs were set by receiver operating curve analysis for positivity to optimize correct classification.
Results: All three IHC assays were 100% specific but sensitivity did vary: D5F3 86%, ALK 79%, 5A4 71%. Intensity was the most discriminating measure overall, with a combination of proportion and intensity not improving the test. No FISH-negative IHC-positive cases were seen. Two FISH-positive cases were negative with all three IHC assays. One of these had been treated with crizotinib and had failed to show clinical response. The other harbored a second driving mutation in the EGFR gene.
Conclusions: IHC with all three antibodies is especially highly specific (100%) although variably sensitive (71%-86%), specifically in cases with scanty material. D5F3 assay was most sensitive in these latter cases. Occasional cases are IHC-positive but FISH-negative, suggesting either inaccuracy of one assay or occasional tumors with ALK rearrangement that do not express high levels of ALK protein.
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Several different acquired resistance mechanisms of EGFR mutant lung adenocarcinoma to EGFR-tyrosine kinase inhibitor (TKI) therapy have been described, most recently transformation to small cell lung carcinoma (SCLC). We describe the case of a 46-year-old female with relapsed EGFR exon 19 deletion lung adenocarcinoma treated with erlotinib, and on resistance, cisplatin-pemetrexed. Liver rebiopsy identified an afatinib-resistant combined SCLC and non-small cell carcinoma with neuroendocrine morphology, retaining the EGFR exon 19 deletion. This case highlights acquired EGFR-TKI resistance through transformation to the high-grade neuroendocrine carcinoma spectrum and that that such transformation may not be evident at time of progression on TKI therapy.
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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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BACKGROUND: ALK rearrangement is particularly observed in signet-ring sub-type adenocarcinoma. Since fluorescence in situ hybridization (FISH) is not suitable for mass screening, we aimed to characterize the predictive utility of tumour morphology and ALK immunoreactivity to identify ALK rearrangement, in a primary lung adenocarcinoma dataset enriched for signet-ring morphology, compared with that of other morphology. METHODS: 7 adenocarcinomas from diagnostic archives reported with signet-ring morphology were assessed and compared with 11 adenocarcinomas without signet-ring features over the same time period. Growth patterns were reviewed, ALK expression was assessed by standard immunohistochemistry using ALK1 clone and Envision detection (Dako), and ALK rearrangement was assessed by FISH (Abbott Molecular). Associations between groups and predictive utility of tumour morphology and ALK expression using FISH as gold standard were calculated. RESULTS: 2 excision lung biopsy cases with pure (100%) signet-ring morphology and solid patterns demonstrated diffuse moderate cytoplasmic ALK immunoreactivity (2+) and harboured ALK rearrangements (p=0.007), unlike 5 mixed-signet-ring and 11 non-signet-ring adenocarcinomas, which showed negative or 1+ immunoreactivity; and did not harbour ALK rearrangements (p>0.1). ALK expression was not associated with ALK copy number. 6 of 7 cases with signet ring morphology stained for TTF-1. Pure signet-ring morphology and moderate ALK expression were both associated with ALK rearranged tumours. CONCLUSION: ALK rearrangement is strongly associated with ALK immunoreactivity, and was seen only in tumours with pure signet-ring morphology and solid growth pattern. Tumour morphology, growth pattern and ALK immunoreactivity appear to be good indicators of ALK rearrangement, with TTF-1 positivity aiding in proving primary pulmonary origin.
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INTRODUCTION: The dichotomization of non-small cell carcinoma (NSCLC) subtype into squamous (SQCC) and adenocarcinoma (ADC) has become important in recent years and is increasingly required with regard to management. The aim of this study was to determine the utility of a panel of commercially available antibodies in refining the diagnosis on small biopsies and also to determine whether cytologic material is suitable for somatic EGFR genotyping in a prospectively analyzed series of patients undergoing investigation for suspected lung cancer. METHODS: Thirty-two consecutive cases of NSCLC were first tested using a panel comprising cytokeratin 5/6, P63, thyroid transcription factor-1, 34betaE12, and a D-PAS stain for mucin, to determine their value in refining diagnosis of NSCLC. After this test phase, two further pathologists independently reviewed the cases using a refined panel that excluded 34betaE12 because of its low specificity for SQCC, and refinement of diagnosis and concordance were assessed. Ten cases of ADC, including eight derived from cytologic samples, were sent for EGFR mutation analysis. RESULTS: There was refinement of diagnosis in 65% of cases of NSCLC to either SQCC or ADC in the test phase. This included 10 of 13 cases where cell pellets had been prepared from transbronchial needle aspirates. Validation by two further pathologists with varying expertise in lung pathology confirmed increased refinement and concordance of diagnosis. All samples were adequate for analysis, and they all showed a wild-type EGFR genotype. CONCLUSION: A panel comprising cytokeratin 5/6, P63, thyroid transcription factor-1, and a D-PAS stain for mucin increases diagnostic accuracy and agreement between pathologists when faced with refining a diagnosis of NSCLC to SQCC or ADC. These small samples, even cell pellets derived from transbronchial needle aspirates, seem to be adequate for EGFR mutation analysis.