MCM2 - a promising marker for premalignant lesions of the lung: a cohort study

BACKGROUND: Because cells progressing to cancer must proliferate, marker proteins specific to proliferating cells may permit detection of premalignant lesions. Here we compared the sensitivities of a classic proliferation marker, Ki-67, with a new proliferation marker, MCM2, in 41 bronchial biopsy specimens representing normal mucosa, metaplasia, dysplasia, and carcinoma in situ. METHODS: Parallel sections were stained with antibodies against MCM2 and Ki-67, and the frequencies of staining were independently measured by two investigators. Differences were evaluated statistically using the two-sided correlated samples t-test and Wilcoxon rank sum test. RESULTS: For each of the 41 specimens, the average frequency of staining by anti-MCM2 (39%) was significantly (p < 0.001) greater than by anti-Ki-67 (16%). In metaplastic lesions anti-MCM2 frequently detected cells near the epithelial surface, while anti-Ki-67 did not. CONCLUSIONS: We conclude that MCM2 is detectable in 2-3 times more proliferating premalignant lung cells than is Ki-67. The promise of MCM2 as a sensitive marker for premalignant lung cells is enhanced by the fact that it is present in cells at the surface of metaplastic lung lesions, which are more likely to be exfoliated into sputum. Future studies will determine if use of anti-MCM2 makes possible sufficiently early detection to significantly enhance lung cancer survival rates

A national survey of the prevalence of schistosomiasis and soil transmitted helminths in Malaŵi

BACKGROUND: Past estimates have put the prevalence of schistosomiasis between 40% and 50% in the Malawi population overall based on studies undertaken ten years or more ago. More recent surveys in known high risk areas find similar levels. However control measures, changing ecology and migration may have led to changes in the prevalence of schistosomiasis in different parts of Malawi. A national schistosomiasis and soil-transmitted helminth (STH) survey was undertaken to measure the distribution, prevalence and intensity of infection in November 2002. METHODS: A school was selected randomly from a random sample of 30 Traditional Authorities stratified by six distinct ecological zones, and 1,664 year 3 pupils (9–10 year olds) were questioned about recent illnesses and "red urine". Samples of urine and faeces were examined for the presence of eggs using the standard Kato-Katz technique for soil-transmitted helminths and intestinal schistosomiasis and urine samples using the filtration technique for Schistosoma haematobium. RESULTS: The prevalence of Schistosoma mansoni is 0.4% (95% CI 0–1.3%), S. haematobium 6.9% (95% CI 1.9 – 11.9%), hookworm 1.3% (95% CI 0.4–2.3%), Ascariasis 0.5% (95% CI 0.1–1.0%) and trichuriasis 0% in year 3 pupils (modal age 10 years of age). Intensity of infection is low for all infections except for 2.5% who have high intensity S. haematobium infection. The "red urine" question is 67% sensitive and 80% specific for positive S. haematobium microscopy. CONCLUSIONS: The reduction in prevalences may be real as a result of recent control measures, or false if historical results were based on surveys of high risk populations. Another explanation is that this survey used an unrepresentative sample of schools. Detailed analysis suggests this is unlikely. Recommendations include the use of a 30% positive threshold for the "red urine" screening question to be used in schoolchildren in high prevalence areas. This survey, based on a national probability sample excluding the northern region lakeside area, finds much lower overall prevalence and intensity of schistosomiasis and STHs than previous estimates based on selected surveys. Disease control featuring chemotherapy may be having a profound effect. The localised nature of the distribution of the infections means that control programmes may work best if undertaken at district level or below. "Red urine" questionnaire surveys may help identify hot spots

Exploring the uncertainties of early detection results: model-based interpretation of mayo lung project

Background: The Mayo Lung Project (MLP), a randomized controlled clinical trial of lung cancer screening conducted between 1971 and 1986 among male smokers aged 45 or above, demonstrated an increase in lung cancer survival since the time of diagnosis, but no reduction in lung cancer mortality. Whether this result necessarily indicates a lack of mortality benefit for screening remains controversial. A number of hypotheses have been proposed to explain the observed outcome, including over-diagnosis, screening sensitivity, and population heterogeneity (initial difference in lung cancer risks between the two trial arms). This study is intended to provide model-based testing for some of these important arguments.Method: Using a micro-simulation model, the MISCAN-lung model, we explore the possible influence of screening sensitivity, systematic error, over-diagnosis and population heterogeneity.Results: Calibrating screening sensitivity, systematic error, or over-diagnosis does not noticeably improve the fit of the model, whereas calibrating population heterogeneity helps the model predict lung cancer incidence better.Conclusions: Our conclusion is that the hypothesized imperfection in screening sensitivity, systematic error, and over-diagnosis do not in themselves explain the observed trial results. Model fit improvement achieved by accounting for population heterogeneity suggests a higher risk of cancer incidence in the intervention group as compared with the control group

Identification of lung cancer with high sensitivity and specificity by blood testing

<p>Abstract</p> <p>Background</p> <p>Lung cancer is a very frequent and lethal tumor with an identifiable risk population. Cytological analysis and chest X-ray failed to reduce mortality, and CT screenings are still controversially discussed. Recent studies provided first evidence for the potential usefulness of autoantigens as markers for lung cancer.</p> <p>Methods</p> <p>We used extended panels of arrayed antigens and determined autoantibody signatures of sera from patients with different kinds of lung cancer, different common non-tumor lung pathologies, and controls without any lung disease by a newly developed computer aided image analysis procedure. The resulting signatures were classified using linear kernel Support Vector Machines and 10-fold cross-validation.</p> <p>Results</p> <p>The novel approach allowed for discriminating lung cancer patients from controls without any lung disease with a specificity of 97.0%, a sensitivity of 97.9%, and an accuracy of 97.6%. The classification of stage IA/IB tumors and controls yielded a specificity of 97.6%, a sensitivity of 75.9%, and an accuracy of 92.9%. The discrimination of lung cancer patients from patients with non-tumor lung pathologies reached an accuracy of 88.5%.</p> <p>Conclusion</p> <p>We were able to separate lung cancer patients from subjects without any lung disease with high accuracy. Furthermore, lung cancer patients could be seprated from patients with other non-tumor lung diseases. These results provide clear evidence that blood-based tests open new avenues for the early diagnosis of lung cancer.</p

The Dispersal Ecology of Rhodesian Sleeping Sickness Following Its Introduction to a New Area

Tsetse-transmitted human and animal trypanosomiasis are constraints to both human and animal health in sub-Saharan Africa, and although these diseases have been known for over a century, there is little recent evidence demonstrating how the parasites circulate in natural hosts and ecosystems. The spread of Rhodesian sleeping sickness (caused by Trypanosoma brucei rhodesiense) within Uganda over the past 15 years has been linked to the movement of infected, untreated livestock (the predominant reservoir) from endemic areas. However, despite an understanding of the environmental dependencies of sleeping sickness, little research has focused on the environmental factors controlling transmission establishment or the spatially heterogeneous dispersal of disease following a new introduction. In the current study, an annually stratified case-control study of Rhodesian sleeping sickness cases from Serere District, Uganda was used to allow the temporal assessment of correlations between the spatial distribution of sleeping sickness and landscape factors. Significant relationships were detected between Rhodesian sleeping sickness and selected factors, including elevation and the proportion of land which was “seasonally flooding grassland” or “woodlands and dense savannah.” Temporal trends in these relationships were detected, illustrating the dispersal of Rhodesian sleeping sickness into more ‘suitable’ areas over time, with diminishing dependence on the point of introduction in concurrence with an increasing dependence on environmental and landscape factors. These results provide a novel insight into the ecology of Rhodesian sleeping sickness dispersal and may contribute towards the implementation of evidence-based control measures to prevent its further spread

Proteomics as a Method for Early Detection of Cancer: A Review of Proteomics, Exhaled Breath Condensate, and Lung Cancer Screening

The study of expressed proteins in neoplasia is undergoing a revolution with the advent of proteomic analysis. Unlike genomic studies where individual changes may have no functional significance, protein expression is closely aligned with cellular activity. This perspective will review proteomics as a method of detecting markers of neoplasia with a particular emphasis on lung cancer and the potential to sample the lung by exhaled breath condensate (EBC). EBC collection is a simple, new, and noninvasive technique, which allows sampling of lower respiratory tract fluid. EBC enables the study of a wide variety of biological markers from low molecular weight mediators to macromolecules, such as proteins, in a range of pulmonary diseases. EBC may be applied to the detection of lung cancer where it could be a tool in early diagnosis. This perspective will explore the potential of applying proteomics to the EBC from lung cancer patients as an example of detecting potential biomarkers of disease and progression

Magnetic resonance imaging for lung cancer detection: Experience in a population of more than 10,000 healthy individuals

<p>Abstract</p> <p>Background</p> <p>Recent refinements of lung MRI techniques have reduced the examination time and improved diagnostic sensitivity and specificity. We conducted a study to assess the feasibility of MRI for the detection of primary lung cancer in asymptomatic individuals.</p> <p>Methods</p> <p>A retrospective chart review was performed on images of lung parenchyma, which were extracted from whole-body MRI examinations between October 2000 and December 2007. 11,766 consecutive healthy individuals (mean age, 50.4 years; 56.8% male) were scanned using one of two 1.5-T scanners (Sonata and Sonata Maestro, Siemens Medical Solutions, Erlangen, Germany). The standard protocol included a quick whole-lung survey with T2-weighted 2-dimensional half Fourier acquisition single shot turbo spin echo (HASTE) and 3-dimensional volumetric interpolated breath-hold examination (VIBE). Total examination time was less than 10 minutes, and scanning time was only 5 minutes. Prompt referrals and follow-ups were arranged in cases of suspicious lung nodules.</p> <p>Results</p> <p>A total of 559 individuals (4.8%) had suspicious lung nodules. A total of 49 primary lung cancers were diagnosed in 46 individuals: 41 prevalence cancers and 8 incidence cancers. The overall detection rate of primary lung cancers was 0.4%. For smokers aged 51 to 70 years, the detection rate was 1.4%. TNM stage I disease accounted for 37 (75.5%). The mean size of detected lung cancers was 1.98 cm (median, 1.5 cm; range, 0.5-8.2 cm). The most histological types were adenocarcinoma in 38 (77.6%).</p> <p>Conclusion</p> <p>Rapid zero-dose MRI can be used for lung cancer detection in a healthy population.</p