Establishment of a Multi-Analyte Serum Biomarker Panel to Identify Lymph Node Metastases in Non-small Cell Lung Cancer

IntroductionIn non-small cell lung cancer (NSCLC), the presence of locoregional lymph node metastases remains the most important prognostic factor and significantly guides treatment regimens. Unfortunately, currently-available noninvasive staging modalities have limited accuracy. The objective of this study was to create a multianalyte blood test capable of discriminating a patient's true (pathologic) nodal status preoperatively.MethodsPretreatment serum specimens collected from 107 NSCLC patients with localized disease were screened with 47 biomarkers implicated in disease presence or progression. Multivariate statistical algorithms were then used to identify the optimal combination of biomarkers for accurately discerning each patient's nodal status.ResultsWe identified 15 candidate biomarkers that met our criteria for statistical relevance in discerning a patient's preoperative nodal status. A ‘random forest’ classification algorithm was used with these parameters to define a 6-analyte panel, consisting of macrophage inflammatory protein-1α, carcinoembryonic antigen, stem cell factor, tumor necrosis factor-receptor I, interferon-γ, and tumor necrosis factor-α, that was the optimum combination of biomarkers for identifying a patient's pathologic nodal status. A Classification and Regression Tree analysis was then created with this panel that was capable of correctly classifying 88% of the patients tested, relative to the pathologic assessments. This value is in contrast to our observed 85% classification rate using conventional clinical methods.ConclusionsThis study establishes a serum biomarker panel with efficacy in discerning preoperative nodal status. With further validation, this blood test may be useful for assessing nodal status (including occult disease) in NSCLC patients facing tumor resection therapy

Multiband tight-binding theory of disordered ABC semiconductor quantum dots: Application to the optical properties of alloyed CdZnSe nanocrystals

Zero-dimensional nanocrystals, as obtained by chemical synthesis, offer a broad range of applications, as their spectrum and thus their excitation gap can be tailored by variation of their size. Additionally, nanocrystals of the type ABC can be realized by alloying of two pure compound semiconductor materials AC and BC, which allows for a continuous tuning of their absorption and emission spectrum with the concentration x. We use the single-particle energies and wave functions calculated from a multiband sp^3 empirical tight-binding model in combination with the configuration interaction scheme to calculate the optical properties of CdZnSe nanocrystals with a spherical shape. In contrast to common mean-field approaches like the virtual crystal approximation (VCA), we treat the disorder on a microscopic level by taking into account a finite number of realizations for each size and concentration. We then compare the results for the optical properties with recent experimental data and calculate the optical bowing coefficient for further sizes

Soil methane sink capacity response to a long-term wildfire chronosequence in Northern Sweden

Boreal forests occupy nearly one fifth of the terrestrial land surface and are recognised as globally important regulators of carbon (C) cycling and greenhouse gas emissions. Carbon sequestration processes in these forests include assimilation of CO2 into biomass and subsequently into soil organic matter, and soil microbial oxidation of methane (CH4). In this study we explored how ecosystem retrogression, which drives vegetation change, regulates the important process of soil CH4 oxidation in boreal forests. We measured soil CH4 oxidation processes on a group of 30 forested islands in northern Sweden differing greatly in fire history, and collectively representing a retrogressive chronosequence, spanning 5000 years. Across these islands the build-up of soil organic matter was observed to increase with time since fire disturbance, with a significant correlation between greater humus depth and increased net soil CH4 oxidation rates. We suggest that this increase in net CH4 oxidation rates, in the absence of disturbance, results as deeper humus stores accumulate and provide niches for methanotrophs to thrive. By using this gradient we have discovered important regulatory controls on the stability of soil CH4 oxidation processes that could not have not been explored through shorter-term experiments. Our findings indicate that in the absence of human interventions such as fire suppression, and with increased wildfire frequency, the globally important boreal CH4 sink could be diminished

Evaluating methane inventories by isotopic analysis in the London region

A thorough understanding of methane sources is necessary to accomplish methane reduction targets. Urban environments, where a large variety of methane sources coexist, are one of the most complex areas to investigate. Methane sources are characterised by specific δ13C-CH4 signatures, so high precision stable isotope analysis of atmospheric methane can be used to give a better understanding of urban sources and their partition in a source mix. Diurnal measurements of methane and carbon dioxide mole fraction, and isotopic values at King’s College London, enabled assessment of the isotopic signal of the source mix in central London. Surveys with a mobile measurement system in the London region were also carried out for detection of methane plumes at near ground level, in order to evaluate the spatial allocation of sources suggested by the inventories. The measured isotopic signal in central London (−45.7 ±0.5‰) was more than 2‰ higher than the isotopic value calculated using emission inventories and updated δ13C-CH4 signatures. Besides, during the mobile surveys, many gas leaks were identified that are not included in the inventories. This suggests that a revision of the source distribution given by the emission inventories is needed

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Immunohistochemical analysis of changes in signaling pathway activation downstream of growth factor receptors in pancreatic duct cell carcinogenesis

<p>Abstract</p> <p>Background</p> <p>The pathogenesis of pancreatic ductal adenocarcinoma (PDAC) involves multi-stage development of molecular aberrations affecting signaling pathways that regulate cancer growth and progression. This study was performed to gain a better understanding of the abnormal signaling that occurs in PDAC compared with normal duct epithelia.</p> <p>Methods</p> <p>We performed immunohistochemistry on a tissue microarray of 26 PDAC, 13 normal appearing adjacent pancreatic ductal epithelia, and 12 normal non-PDAC ducts. We compared the levels of 18 signaling proteins including growth factor receptors, tumor suppressors and 13 of their putative downstream phosphorylated (p-) signal transducers in PDAC to those in normal ductal epithelia.</p> <p>Results</p> <p>The overall profiles of signaling protein expression levels, activation states and sub-cellular distribution in PDAC cells were distinguishable from non-neoplastic ductal epithelia. The ERK pathway activation was correlated with high levels of ^S2448p-mTOR (100%, p = 0.05), ^T389p-S6K (100%, p = 0.02 and ^S235/236p-S6 (86%, p = 0.005). Additionally, ^T389p-S6K correlated with ^S727p-STAT3 (86%, p = 0.005). Advanced tumors with lymph node metastasis were characterized by high levels of ^S276p-NFκB (100%, p = 0.05) and ^S9p-GSK3β (100%, p = 0.05). High levels of PKBβ/AKT2, EGFR, as well as nuclear ^T202/Y204p-ERK and ^T180/Y182p-p38 were observed in normal ducts adjacent to PDAC compared with non-cancerous pancreas.</p> <p>Conclusion</p> <p>Multiple signaling proteins are activated in pancreatic duct cell carcinogenesis including those associated with the ERK, PKB/AKT, mTOR and STAT3 pathways. The ERK pathway activation appears also increased in duct epithelia adjacent to carcinoma, suggesting tumor micro-environmental effects.</p