Semi-quantitative Information Research Articles

Characterization of hydrochar obtained from hydrothermal carbonization of wheat straw digestate

Hydrothermal carbonization (HTC) of wheat straw digestate was performed at 180–260 °C for 2–8 h. The resulted hydrochars were analyzed by ultimate analyzer. Elemental carbon and oxygen concentration of hydrochars were fitted with power law correlation. Moreover, chemical structures of feedstocks and hydrochars were investigated by 13C cross-polarization magic angle spinning (CP/MAS) nuclear magnetic resonance (NMR) spectroscopy. In particular, a procedure including CP dynamics analysis was applied to obtain semi-quantitative information on the composition of the analyzed materials from 13C CP/MAS spectra. Up to a process temperature of 220 °C, digestate-derived hydrochar contained primarily crystalline cellulose and lignin. At 260 °C, crystalline cellulose was degraded and more aliphatic carbon and lignin-rich hydrochars were produced. Ester bands corresponding to hemicellulose disappeared at mild HTC conditions at 180 °C and 2 h.

Longitudinal relaxation properties of 1HN and 1Hα determined by direct-detected 13C NMR experiments to study intrinsically disordered proteins (IDPs)

Intrinsically disordered proteins (IDPs) are functional proteins containing large fragments characterized by high local mobility. Bioinformatic studies have suggested that a significant fraction (more than 30%) of eukaryotic proteins has disordered regions of more than 50 amino acids in length. Hence, NMR methods for the characterization of local compactness and solvent accessibility in such highly disordered proteins are of high importance. Among the available approaches, the HET-SOFAST/BEST experiments (Schanda et al., 2006, Rennella et al., 2014) provide semi-quantitative information by monitoring longitudinal 1H relaxation of amide protons under different initial conditions. However, when approaching physiological sample conditions, the potential of these amide 1H detected experiments is reduced due to rapid amide proton solvent exchange. 13C direct detection methods therefore provide a valuable alternative thanks to a higher chemical shift dispersion and their intrinsic insensitivity toward solvent exchange. Here we present two sets of 13C-detected experiments, which indirectly measure 1HN and 1Hα inversion recovery profiles. The experiments consist of an initial spin inversion-recovery block optimized for selective manipulation of different types of proton spins followed by a CON read-out scheme. The proposed experiments were tested on human α-synuclein and ubiquitin, two representative examples of unfolded and folded proteins.

Preparation of an Ester-Containing Grignard Reagent by Halogen–Metal Exchange

In this experiment, students carry out a halogen–metal exchange reaction of methyl 2-iodobenzoate with isopropylmagnesium chloride in THF at 0 °C to afford 2-carbomethoxyphenylmagnesium chloride, which is treated with p-methoxybenzaldehyde to give a lactone (phthalide) product. This reaction introduces students to the modern method of preparation of Grignard and organolithium reagents by halogen–metal exchange rather than by using metallic magnesium or lithium, which is rarely done in a research laboratory. It also demonstrates that Grignard reagents bearing reactive functionality can be prepared and utilized in synthesis, although students are still often taught otherwise. The IR spectrum of the crude product provides semiquantitative information on the success of the reaction because the lactone product and starting material ester and aldehyde have very different carbonyl absorptions, demonstrating the power of this technique to distinguish between functional groups. The product can be purified by chrom...

Sodium Hydroxide Activated Nanoporous Carbons Based on Lapsi Seed Stone.

Nanoporous activated carbons (ACs) were prepared from Lapsi (Choerospondias axillaris) seed powder by chemical activation with sodium hydroxide (NaOH) at different NaOH impregnation ratios. The prepared ACs were characterized by Fourier transform-infrared (FTIR) spectroscopy, Raman scattering, X-ray diffraction (XRD), and scanning electron microscopy (SEM). Semi-quantitative information on the surface properties was obtained by estimating iodine number. FTIR spectra showed the presence of oxygenated functional groups such as hydroxyl, carbonyl, and carboxyl in the prepared ACs. Raman scattering showed clear D and G bands in the spectra. The intensity ratio of G and D band peak intensity was ca. 1.39 at lowest NaOH and Lapsi seed powder ratio 0.25:1 showing high graphitic degree. This ratio decreased with increase in the NaOH impregnation ratio and reached minimum ca. 0.94 (comparable with commercial AC) at NaOH and Lapsi seed powder ratio 1:1 demonstrating that higher NaOH impregnation reduces the graphitic structure of the carbon. XRD patterns showed two broad peaks at diffraction angles of approximately 25 and 43 degrees indicating the amorphous structure. Surface properties of the ACs (BET surface area, pore volume, and pore size distributions) were evaluated by nitrogen adsorption-desorption isotherm. Our ACs showed strong methylene blue adsorption property (maximum methylene blue is ca. 200 mg/g). Judging from the iodine number and methylene blue values, structure, and surface areas, it can be concluded that NaOH impregnation ratio is one of the key parameters to tune the surface properties of Lapsi seed stone-based activated carbons.

Application of chemometric algorithms to MALDI mass spectrometry imaging of pharmaceutical tablets

During drug product development, the nature and distribution of the active substance have to be controlled to ensure the correct activity and the safety of the final medication. Matrix assisted laser desorption/ionization mass spectrometry imaging (MALDI–MSI), due to its structural and spatial specificities, provides an excellent way to analyze these two critical parameters in the same acquisition. The aim of this work is to demonstrate that MALDI–MSI, coupled with four well known multivariate statistical analysis algorithms (PCA, ICA, MCR–ALS and NMF), is a powerful technique to extract spatial and spectral information about chemical compounds from known or unknown solid drug product formulations. To test this methodology, an in-house manufactured tablet and a commercialized Coversyl® tablet were studied. The statistical analysis was decomposed into three steps: preprocessing, estimation of the number of statistical components (manually or using singular value decomposition), and multivariate statistical analysis. The results obtained showed that while principal component analysis (PCA) was efficient in searching for sources of variation in the matrix, it was not the best technique to estimate an unmixing model of a tablet. Independent component analysis (ICA) was able to extract appropriate contributions of chemical information in homogeneous and heterogeneous datasets. Non-negative matrix factorization (NMF) and multivariate curve resolution–alternating least squares (MCR–ALS) were less accurate in obtaining the right contribution in a homogeneous sample but they were better at distinguishing the semi-quantitative information in a heterogeneous MALDI dataset.

Sequencing methods and datasets to improve functional interpretation of sleeping beauty mutagenesis screens.

BackgroundAnimal models of cancer are useful to generate complementary datasets for comparison to human tumor data. Insertional mutagenesis screens, such as those utilizing the Sleeping Beauty (SB) transposon system, provide a model that recapitulates the spontaneous development and progression of human disease. This approach has been widely used to model a variety of cancers in mice. Comprehensive mutation profiles are generated for individual tumors through amplification of transposon insertion sites followed by high-throughput sequencing. Subsequent statistical analyses identify common insertion sites (CISs), which are predicted to be functionally involved in tumorigenesis. Current methods utilized for SB insertion site analysis have some significant limitations. For one, they do not account for transposon footprints – a class of mutation generated following transposon remobilization. Existing methods also discard quantitative sequence data due to uncertainty regarding the extent to which it accurately reflects mutation abundance within a heterogeneous tumor. Additionally, computational analyses generally assume that all potential insertion sites have an equal probability of being detected under non-selective conditions, an assumption without sufficient relevant data. The goal of our study was to address these potential confounding factors in order to enhance functional interpretation of insertion site data from tumors.ResultsWe describe here a novel method to detect footprints generated by transposon remobilization, which revealed minimal evidence of positive selection in tumors. We also present extensive characterization data demonstrating an ability to reproducibly assign semi-quantitative information to individual insertion sites within a tumor sample. Finally, we identify apparent biases for detection of inserted transposons in several genomic regions that may lead to the identification of false positive CISs.ConclusionThe information we provide can be used to refine analyses of data from insertional mutagenesis screens, improving functional interpretation of results and facilitating the identification of genes important in cancer development and progression.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-1150) contains supplementary material, which is available to authorized users.

Cotton-based diagnostic devices.

A good diagnostic procedure avoids wasting medical resources, is easy to use, resists contamination, and provides accurate information quickly to allow for rapid follow-up therapies. We developed a novel diagnostic procedure using a “cotton-based diagnostic device” capable of real-time detection, i.e., in vitro diagnostics (IVD), which avoids reagent contamination problems common to existing biomedical devices and achieves the abovementioned goals of economy, efficiency, ease of use, and speed. Our research reinforces the advantages of an easy-to-use, highly accurate diagnostic device created from an inexpensive and readily available U.S. FDA-approved material (i.e., cotton as flow channel and chromatography paper as reaction zone) that adopts a standard calibration curve method in a buffer system (i.e., nitrite, BSA, urobilinogen and uric acid assays) to accurately obtain semi-quantitative information and limit the cross-contamination common to multiple-use tools. Our system, which specifically targets urinalysis diagnostics and employs a multiple biomarker approach, requires no electricity, no professional training, and is exceptionally portable for use in remote or home settings. This could be particularly useful in less industrialized areas.

Predicting the distribution of deep-sea vulnerable marine ecosystems using high-resolution data: Considerations and novel approaches

Little is known about species distribution patterns in deep-sea environments, primarily because sampling surveys in the high seas are expensive and time consuming. The increasing need to manage and protect vulnerable marine ecosystems, such as cold-water corals, has motivated the use of predictive modelling tools, which produce continuous maps of potential species or habitat distribution from limited point observations and full coverage environmental data. Rapid advances in acoustic remote sensing, oceanographic modelling and sampling technology now provide high quality datasets, facilitating model development with high spatial detail. This paper provides a short overview of existing methodologies for predicting deep-sea benthic species distribution, and illustrates emerging issues related to spatial and thematic data resolution, and the use of transect-derived species distribution data. In order to enhance the ecological relevance and reliability of deep-sea species distribution models, novel techniques are presented based on a case study predicting the distribution of the cold-water coral Lophelia pertusa in three carbonate mound provinces in Irish waters. Specifically, the study evaluates (1) the capacity of newly developed high-resolution (250m grid cell size) hydrodynamic variables to explain local scale cold-water coral distribution patterns, (2) the potential value of species occurrence proportion data to maintain semi-quantitative information of coral prevalence (i.e. coverage) and sampling effort per grid cell within the response variable, and (3) mixed effect modelling to deal with spatially grouped transect data. The study shows that predictive models using vertical and horizontal flow parameters perform significantly better than models based on terrain parameters only. Semi-quantitative proportion data may decrease model uncertainty and increase model reliability, and provide a fruitful avenue of research for analysing large quantities of video data in a detailed yet time-efficient manner. The study concludes with an outlook of how species distribution models could improve our understanding of vulnerable marine ecosystem functioning and processes in the deep sea.

Study of Fuel Assessment and Adulteration Using EEMF and Multiway PCA

In this work classification of several petroleum products (gasoline, diesel, and kerosene) and some organic solvents (hexane, paint thinner) using the excitation emission matrices fluorescence spectroscopy and multiway principal component analysis was achieved successfully. Twelve samples of each of the above substances were studied; the total number of the neat samples including the petroleum and organic samples was 60 samples. The same protocol used above for classification was also used successfully for uncovering the adulterated gasoline with less expensive petroleum or organic substances of different compositions, namely, 2, 5, 10, and 20% v/v. Similar composition ratios were also used to uncover the adulteration of diesel with kerosene. Semiquantitative information in case of adulterating the gasoline with diesel was also possible.

A model for online failure prognosis subject to two failure modes based on belief rule base and semi-quantitative information

As one of most important aspects in condition-based maintenance (CBM), failure prognosis has attracted an increasing attention with the growing demand for higher operational efficiency and safety in complex engineering systems. Currently there are no effective methods for predicting the failure of a system in real-time by using both expert knowledge and quantitative information (i.e., semi-quantitative information) when degradation failure and shock failure are dependent and competitive. Since belief rule base (BRB) can model the complex system when semi-quantitative information is available, this paper focuses on developing a new BRB based method for online failure prognosis that can deal with this problem. Although it is difficult to obtain accurate and complete quantitative information, some expert knowledge can be collected and represented by a BRB which is an expert system essentially. As such, a new BRB based prognosis model is proposed to predict the system failure in real-time when two failure modes are dependent and competitive. Moreover, a recursive algorithm for online updating the parameters of the failure prognosis model is developed. Equipped with the recursive algorithm, the proposed prognosis model can predict the failure in real-time when two failure modes are dependent and competitive. An experimental case study is examined to demonstrate the implementation and potential applications of the proposed online failure prognosis method.

EltonTraits 1.0: Species‐level foraging attributes of the world's birds and mammals

Species are characterized by physiological, behavioral, and ecological attributes that are all subject to varying evolutionary and ecological constraints and jointly determine species' role and function in ecosystems. Attributes such as diet, foraging strata, foraging time, and body size, in particular, characterize a large portion of the “Eltonian” niches of species. Here we present a global species‐level compilation of these key attributes for all 9993 and 5400 extant bird and mammal species derived from key literature sources. Global handbooks and monographs allowed the consistent sourcing of attributes for most species. For diet and foraging stratum we followed a defined protocol to translate the verbal descriptions into standardized, semiquantitative information about relative importance of different categories. Together with body size (continuous) and activity time (categorical) this enables a much finer distinction of species' foraging ecology than typical categorical guild assignments allow. Attributes lacking information for specific species are flagged, and interpolated values based on taxonomy are provided instead. The presented data set is limited by, among others, these select cases missing observed data, by errors and uncertainty in the expert assessment as presented in the literature, and by the lack of intraspecific information. However, the standardized and transparent nature and complete global coverage of the data set should support an array of potential studies in biogeography, community ecology, macroevolution, global change biology, and conservation. Potential uses include comparative work involving these traits as focal or secondary variables, ecological research on the trait or trophic structure of communities, or conservation science concerned with the loss of function among species or in ecosystems in a changing world. We hope that this publication will spur the sharing, collaborative curation, and extension of data to the benefit of a more integrative, rigorous, and global biodiversity science.

A review of historical reconstruction methods of land use/land cover

Understanding long-term human-environment interactions requires historical reconstruction of past land-use and land-cover changes. Most reconstructions have been based primarily on consistently available and relatively standardized information from historical sources. Based on available data sources and a retrospective research, in this paper we review the approaches and methods of the digital reconstruction and analyze their advantages and possible constraints in the following aspects: (1) Historical documents contain qualitative or semi-quantitative information about past land use, which also usually include land-cover data, but preparation of archival documents is very time-consuming. (2) Historical maps and pictures offer visual and spatial quantitative land-cover information. (3) Natural archive has significant advantages as a method for reconstructing past vegetation and has its unique possibilities especially when historical records are missing or lacking, but it has great limits of rebuilding certain land-cover types. (4) Historical reconstruction models have been gradually developed from empirical models to mechanistic ones. The method does not only reconstruct the quantity of land use/cover in historical periods, but it also reproduces the spatial distribution. Yet there are still few historical land-cover datasets with high spatial resolution. (5) Reconstruction method based on multiple-source data and multidisciplinary research could build historical land-cover from multiple perspectives, complement the missing data, verify reconstruction results and thus improve reconstruction accuracy. However, there are challenges that make the method still in the exploratory stage. This method can be a long-term development goal for the historical land-cover reconstruction. Researchers should focus on rebuilding historical land-cover dataset with high spatial resolution by developing new models so that the study results could be effectively applied in simulations of climatic and ecological effects.

An integrated approach for detection and characterization of the trace impurities in levofloxacin using liquid chromatography-tandem mass spectrometry

Impurity analysis plays an important role to guarantee the quality and safety of pharmaceuticals. However, identification of impurities remains challenging, especially for those unknown or at trace levels. We present an integrated approach to detect and characterize the trace impurities in drugs. Based on liquid chromatography-tandem mass spectrometry (LC-MS/MS), an approach integrating automatic impurity screening method using multiple mass defect filters (MMDFs) and background subtraction (BS) was developed. This approach was used to acquire the structural and semi-quantitative information in a single sample run, and even to discover the impurity signals submerged by background and drug ions. This approach was illustrated by the comprehensive impurity analysis of levofloxacin. This approach was sensitive to detect impurities at the level of 0.02% with respect to levofloxacin concentration. Nineteen impurities were detected, fourteen of which were structurally characterized and eight impurities were reported for the first time. Impurity profiles of levofloxacin drug substances and degradation samples were obtained reliably. A plausible degradation pathway of levofloxacin was proposed including descarboxyl reaction under acid, piperazinyl ring cleavage degradation under light, and N-oxidation under oxidative condition. The generic approach integrating LC-MS/MS and an automatic impurity screening method was developed for the detection, characterization and monitoring of impurities, especially those unknown or at trace levels. This approach was demonstrated to be rapid, sensitive and automatic for impurity profiling of drugs.

Holistic multilevel modeling of type‐2 diabetes (1180.5)

Type‐2 diabetes (T2D), is presenting a rapidly growing health and economic problem. For personalized lifestyle/medical treatment advice, it is essential that computer modelling tools become available to integrate the results from diagnostic tools that probe the function of all involved organs/processes in a single holistic view. Our objective is to build such a model for T2D, an important comorbidity of metabolic syndrome.As a first step towards fully personalized quantitative diagnosis and prediction we developed a descriptive model based on causal loop diagrams at a very high aggregation level that integrates mechanisms across all relevant domains including body weight dynamics, glucose/insulin dynamics, inflammation, gut health, and mental stress. The model integrates qualitative and semi‐quantitative information and expert knowledge.The model was able to simulate the development of T2D over a multi‐year period following different food intake profiles, as well as disease modulation by increased physical activity or mental stress‐relieving lifestyles.In a recently started EU project MISSION‐T2D (www.mission‐t2d.eu), the high aggregation level model will be interlinked with a model at a second aggregation level that describes the integrated dynamics of all processes at the minute‐day timescale. This allows to enrich the model with mechanisms probed by PK‐PD studies and nutritional challenge tests and should pave the way for translating validated multilevel immune‐metabolic models into the clinical setting of T2D.Concluding, we have successfully made a first step towards a multiorgan, multilevel systems health model of T2D that can be used to integrate diagnostic data from different domains for personalized lifestyle/treatment advice.

Identification of plaque location using indocyanine green videoangiography during carotid endarterectomy.

The aim of the present study was to assess whether surgical microscope-based indocyanine green (ICG) videoangiography (ICG-VA) using FLOW 800 software provides useful evaluation of blood flow during carotid endarterectomy (CEA). Twenty CEA procedures were performed in 19 patients between July 2011 and January 2012. ICG was injected intravenously before and after CEA, and ICG-VA video sequences were analyzed using FLOW 800. Regions of interest were identified in the common carotid artery, plaque, internal carotid artery, and external carotid artery, and changes in intensity values were evaluated. The distal and proximal ends of the carotid plaque were identified in 87.5 and 75 % of cases, respectively. After CEA, intensity values in the common carotid artery, plaque, internal carotid artery, and external carotid artery had increased by 162 ± 129, 337 ± 212, 139 ± 151, and 177 ± 143, respectively. The intensity values in the region of the plaque showed the greatest improvement. ICG-VA can provide information regarding plaque location vessel patency during CEA. FLOW 800 software provides semiquantitative information regarding blood flow, especially in cases of severe stenosis with collapse of the internal carotid artery.

Technetium-99m methoxyisobutylisonitrile scintigraphy in the assessment of cold thyroid nodules

Scanning with technetium-99m methoxyisobutylisonitrile (Tc-MIBI) is recommended for evaluating thyroid nodule metabolism. In addition, it may help differentiate between benign and malignant nodules; however, the efficacy of this technique has not been fully elucidated. Therefore, it is not currently performed for routine clinical application. This prospective study was conducted to investigate the clinical significance of Tc-MIBI scintigraphy in the assessment of patients with cold thyroid nodules. This prospective study was conducted on 104 patients with cold thyroid nodules greater than 1 cm in diameter as detected on Tc-pertechnetate scintigraphy. Uptake of MIBI in thyroid nodules was compared with that in the surrounding normal thyroid tissue for both early and delayed images, and a score of 0-3 was assigned to each nodule as follows: 0, cold; 1, decreased; 2, equal; 3, increased. The thyroid scan was performed 20 and 40 min after intravenous injection of 555 MBq of Tc-MIBI. The patients underwent fine-needle aspiration cytology (FNAC). Detailed statistical parameters were determined on a per-nodule basis for each qualitative and quantitative scan analysis, as defined by histology. A total of 104 patients (93 women and 11 men; mean age 40.76±11.40 years, range 20-73) with a total number of 167 cold nodules were included in this study. When Tc-MIBI uptake was regarded as the criterion of malignancy in Tc-MIBI scintigraphy, the accuracy was between 69.46 and 92.21% on using seven different methods. In addition, FNAC findings indicated a sensitivity of 66.66%, a specificity of 100%, a negative predictive value of 95.72%, a positive predictive value of 100%, and an accuracy of 96.06%. Six malignant cold nodules were detected on a positive Tc-MIBI scan, which were determined as benign nodules on FNAC examinations. The study demonstrated that Tc-MIBI scanning can be complementary to other diagnostic techniques in patients with cold thyroid nodules. In addition, because of its availability, rather low cost, simple protocol, and objective semiquantitative information, Tc-MIBI scanning seems to hold promise in routine imaging of cold thyroid nodules.

The role of cognitive group therapy and happiness training on cerebral blood flow using 99mTc-ECD brain perfusion SPECT: a quasi-experimental study of depressed patients.

The purpose of this study is to investigate the impact of cognitive group therapy and happiness training objectively in the local cerebral blood flow of patients with major depression (MD). The present research is semi-experimental to pre- and post-test with a control group. Three groups were formed, and this number was incorporated in each group: 12 patients were chosen randomly; the first group of depressed patients benefited from the combination of pharmacotherapy and sessions of cognitive group therapy; the second group used a combination of pharmacotherapy and sessions of happiness training; and a third group used only pharmacotherapy. We compared cognitive-behavioural therapy and happiness training efficacy with only pharmacotherapy in MD patients. We performed brain perfusion SPECT in each group, before and after each trial. The study was conducted on 36 patients with MD (32 women and 4 men; mean age: 41.22 ± 9.08; range: 27-65 years). There were significant differences regarding the two trial effects into two experimental groups (p < 0/001) before and after trials, while such differences were not significant in the control group (p > 0.05). In addition, there was significant difference among the regional cerebral blood flow in the frontal and prefrontal regions into two experimental groups before and after trials (p < 0/001), while such differences were not significant in the control group (p > 0.05). This study demonstrated decreased cerebral perfusion in the frontal regions in MD patients, which increased following cognitive group therapy and happiness training. Because of its availability, low costs, easy performance, and the objective semi-quantitative information supplied, brain perfusion SPECT scanning might be useful to assess the diagnosis and therapy efficacy. Further exploration is needed to validate its clinical role.

Comprehensive identification of walnut polyphenols by liquid chromatography coupled to linear ion trap–Orbitrap mass spectrometry

Epidemiologic studies and clinical trials have demonstrated consistent benefits of walnut consumption on coronary heart disease risk and other chronic diseases. Walnuts (Juglans regia L.) have been described previously as a rich source of polyphenols with a broad array of different structures. However, an accurate screening of its complete phenolic profile is still lacking. In the present work, liquid chromatography coupled with electrospray ionization hybrid linear trap quadrupole-Orbitrap mass spectrometry (LC–LTQ-Orbitrap) was applied for a comprehensive identification of phenolic compounds in walnuts. A total of 120 compounds, including hydrolysable and condensed tannins, flavonoids and phenolic acids were identified or tentatively identified on the base of their retention times, accurate mass measurements and subsequent mass fragmentation data, or by comparing with reference substances and literature. The peak area of each signal in mass chromatograms was used to provide semiquantitative information for comparison purposes. The most abundant ions were observed for ellagitannins, ellagic acid and its derivatives. Furthermore, the high-resolution MS analysis revealed the presence of eight polyphenols that have never been reported in walnuts: stenophyllanin C, malabathrin A, eucalbanin A, cornusiin B, heterophylliin E, pterocarinin B, reginin A and alienanin B.

HLA Ligandome Analysis Of Chronic Myeloid Leukemia (CML), Revealed Novel Tumor Associated Antigens For Peptide Based Immunotherapy

Despite the success of targeted therapy using tyrosine kinase inhibitors (TKIs), chronic myeloid leukemia (CML) remains largely incurable, most likely due to the treatment resistance of leukemic stem cells. Specific T-cell based immunotherapies for patients with CML might be able to eliminate these residual CML cells. For this goal the identification of tumor associated HLA-presented peptides, which are able to induce a tumor-specific T cell response, is indispensable. However, only few tumor associated antigens for CML are described till date. Thus the aim of this study was to identify for the first time naturally processed and presented HLA ligands from the cell surface of primary CML cells. HLA class I ligands from primary CML cells as well as from bone marrow mononuclear cell (BMNCs) and peripheral blood PBMCs of healthy donors were analyzed using the approach of direct isolation and identification of naturally presented HLA peptides by affinity chromatography and mass spectrometry (LC-MS/MS). LC-MS/MS peptide analysis provided qualitative and semi-quantitative information regarding the composition of the respective ligandomes. Comparative analysis of malignant and benign samples served to identify ligandome-derived tumor associated antigens (LiTAAs) and to select peptide vaccine candidates. So far 10 CML patients (8 chronic phase, 2 accelerated phase) and 30 healthy donors were analyzed within this study. We were able to identify a total of more than 8200 CML derived HLA ligands representing >4500 different source proteins, of which 734 were exclusively represented in CML, but not in healthy PBMCs/BMNCs. 55 of these CML exclusive antigens are presented on 3 or more of all examined CML patients, representing, as broadly represented LiTAAs, promising targets for peptide vaccination. For the first time, previously predicted CML tumor associated antigens for example Myeloperoxidase (10 peptide sequences on 7 CML patients) and Proteinase 3 (5 peptide sequences on 4 CML patients) were here confirmed by direct elution from primary CML cells, which also served to validate our methodological approach. Notably, beyond that we also identified a vast array of novel proteins (e.g. Carcinoembryonic antigen-related cell adhesion molecule 8, CEACAM8; Matrix metallopeptidase 8, MMP8; intracellular adhesion molecule 3, ICAM3) that are broadly and exclusively represented in the ligandome of CML cells.By providing for the first time HLA class I tumor associated antigens, directly obtained from the HLA ligandomes of CML patients, this study may pave the way for the future development of a multipeptide-based immunotherapy approach to eradicate residual CML cells after conventional TKI therapy. Disclosures:No relevant conflicts of interest to declare.

Characterization Of The HLA Class II Ligandome In Acute Myeloid Leukemia (AML) Reveals Novel Candidates For Peptide-Based Immunotherapy

CD4+ T cells are crucial for the induction and maintenance of cytotoxic T cell responses, but can also mediate direct tumor rejection. The therapeutic efficacy of peptide-based cancer vaccines may thus be improved by including HLA class II epitopes to stimulate T helper cells. In contrast to HLA class I ligands, only a small number of class II ligands of TAA has been described so far. We recently reported on the overexpression of HLA class II in AML cells as compared to autologous monocytes and granulocytes as well as on the first HLA class I leukemia associated antigens identified directly on the cell surface of primary AML cells (Stickel et. al. abstract in Blood 2012). In this study we characterized the HLA class II ligandome in AML to identify additional ligands for a peptide-based immunotherapy approach.HLA class II ligands from primary AML cells as well as bone marrow and peripheral blood mononuclear cell (BMNCs/PBMCs) of healthy donors were analyzed using the approach of direct isolation and identification of naturally presented HLA peptides by affinity chromatography and mass spectrometry (LC-MS/MS). LC-MS/MS peptide analysis provided qualitative and semi-quantitative information regarding the composition of the respective ligandomes. Comparative analysis of malignant and benign samples served to identify ligandome-derived tumor associated antigens (LiTAAs) and to select peptide vaccine candidates. Most abundantly detected peptides were functionally characterized with regard to their ability to induce a specific CD4+ T-cell response in healthy donors and in tumor patients using ELISpot. Samples from 10 AML patients (5 FLT3-ITD mutated) and 18 healthy donors were analyzed. We identified more than 2,100 AML-derived HLA class II ligands representing >1,000 different source proteins, of which 315 were exclusively represented in AML, but not in healthy PBMC/BMNC. Data mining for broadly represented LiTAAs pinpointed 26 HLA class II ligands from 8 source proteins that were presented exclusively on more than 40% of all analyzed AML samples as most promising targets. Amongst them were already described TAAs (e.g., RAB5A) as well as several so far understated proteins (e.g. calsyntenin 1, glycophorin A, mannose-binding lectin 2). Subset analysis revealed 58 LiTAAs presented exclusively on FLT3-ITD mutated AML cells. Additional screening for HLA class II ligands from described leukemia associated antigens showed positive results for NPM1 (1 peptide sequence) and MPO (13 peptide sequences). Peptides from calsyntenin 1 and RAB5A were able to elicit CD4+-T-cell response in 25% of tested AML patients (n=16). Thus, our study identified, for the first time, HLA class II tumor associated antigens directly obtained from the HLA ligandomes of AML patients and thereby represents a further step to our goal of developing a multipeptide vaccine for immunotherapy of AML. Disclosures:No relevant conflicts of interest to declare.