Limited Tumor Tissue Drug Penetration Contributes to Primary Resistance against Angiogenesis Inhibitors

Resistance mechanisms against antiangiogenic drugs are unclear. Here, we correlated the antitumor and antivascular properties of five different antiangiogenic receptor tyrosine kinase inhibitors (RTKIs) (motesanib, pazopanib, sorafenib, sunitinib, vatalanib) with their intratumoral distribution data obtained by matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI). In the first mouse model, only sunitinib exhibited broad-spectrum antivascular and antitumor activities by simultaneously suppressing vascular endothelial growth factor receptor-2 (VEGFR2) and desmin expression, and by increasing intratumoral hypoxia and inhibiting both tumor growth and vascularisation significantly. Importantly, the highest and most homogeneous intratumoral drug concentrations have been found in sunitinib-treated animals. In another animal model, where - in contrast to the first model - vatalanib was detectable at homogeneously high intratumoral concentrations, the drug significantly reduced tumor growth and angiogenesis. In conclusion, the tumor tissue penetration and thus the antiangiogenic and antitumor potential of antiangiogenic RTKIs vary among the tumor models and our study demonstrates the potential of MALDI-MSI to predict the efficacy of unlabelled small molecule antiangiogenic drugs in malignant tissue. Our approach is thus a major technical and preclinical advance demonstrating that primary resistance to angiogenesis inhibitors involves limited tumor tissue drug penetration. We also conclude that MALDI-MSI may significantly contribute to the improvement of antivascular cancer therapies

Evaluation of SLOG/TCI-III pediatric system on target control infusion of propofol

<p>Abstract</p> <p>Background</p> <p>The target-controlled infusion-III (SLOG/TCI-III) system was derived from a model set up by the local pediatric population for target control infusion of propofol.</p> <p>Methods</p> <p>The current study aimed at evaluating the difference between target concentrations of propofol and performance, which was measured using the SLOG/TCI-III system in children. Thirty children fulfilling the I-II criteria according to American Society of Anesthesiology were enrolled in the study. The target plasma concentration of propofol was fed into the SLOG/TCI-III system and compared with the measured concentrations of propofol. Blood samples were collected and analyzed by high performance liquid chromatography with fluorescence detector. The performance error (PE) was determined for each measured blood propofol concentration. The performances of the TCI-III system were determined by the median performance error (MDPE), the median absolute performance error (MDAPE), and Wobble (the median absolute deviation of each PE from the MDPE), respectively.</p> <p>Results</p> <p>Concentration against target concentration showed good linear correlation: concentration = 1.3428 target concentration - 0.2633 (r = 0.8667). The MDPE and MDAPE of the pediatric system were 10 and 22%, respectively, and the median value for Wobble was 24%. MDPE and MDAPE were less than 15 and 30%, respectively.</p> <p>Conclusions</p> <p>The performance of TCI-III system seems to be in the accepted limits for clinical practice in children.</p

Correlation of histopathologic characteristics to protein expression and function in malignant melanoma

BACKGROUND: Metastatic melanoma is still one of the most prevalent skin cancers, which upon progression has neither a prognostic marker nor a specific and lasting treatment. Proteomic analysis is a versatile approach with high throughput data and results that can be used for characterizing tissue samples. However, such analysis is hampered by the complexity of the disease, heterogeneity of patients, tumors, and samples themselves. With the long term aim of quest for better diagnostics biomarkers, as well as predictive and prognostic markers, we focused on relating high resolution proteomics data to careful histopathological evaluation of the tumor samples and patient survival information. PATIENTS AND METHODS: Regional lymph node metastases obtained from ten patients with metastatic melanoma (stage III) were analyzed by histopathology and proteomics using mass spectrometry. Out of the ten patients, six had clinical follow-up data. The protein deep mining mass spectrometry data was related to the histopathology tumor tissue sections adjacent to the area used for deep-mining. Clinical follow-up data provided information on disease progression which could be linked to protein expression aiming to identify tissue-based specific protein markers for metastatic melanoma and prognostic factors for prediction of progression of stage III disease. RESULTS: In this feasibility study, several proteins were identified that positively correlated to tumor tissue content including IF6, ARF4, MUC18, UBC12, CSPG4, PCNA, PMEL and MAGD2. The study also identified MYC, HNF4A and TGFB1 as top upstream regulators correlating to tumor tissue content. Other proteins were inversely correlated to tumor tissue content, the most significant being; TENX, EHD2, ZA2G, AOC3, FETUA and THRB. A number of proteins were significantly related to clinical outcome, among these, HEXB, PKM and GPNMB stood out, as hallmarks of processes involved in progression from stage III to stage IV disease and poor survival. CONCLUSION: In this feasibility study, promising results show the feasibility of relating proteomics to histopathology and clinical outcome, and insight thus can be gained into the molecular processes driving the disease. The combined analysis of histological features including the sample cellular composition with protein expression of each metastasis enabled the identification of novel, differentially expressed proteins. Further studies are necessary to determine whether these putative biomarkers can be utilized in diagnostics and prognostic prediction of metastatic melanoma

Identification of prostate-specific antigen (PSA) isoforms in complex biological samples utilizing complementary platforms.

Measurements of the prostate-specific antigen (PSA) levels in blood are widely used as diagnostic, predictive and prognostic marker of prostate disease. The selective detection of molecular forms of PSA can contribute clinically to meaningful enhancements of the conventional PSA-test. As it is plausible that an in-depth search for structural variants of PSA gene products may increase our ability to discriminate distinct patho-biological basis and stages of prostate diseases, we have developed a multi-step protocol comprising gel-based methods followed by mass spectrometric identification. Our current aim was to provide a comprehensive identification of PSA variants occurring in seminal fluid. We provide a proof-of-principle for this multiple step analytical approach to identify multiple PSA variants from complex biological samples that revealed distinct molecular characteristics. In addition, sequence-annotated protein bands in SDS-PAGE gels were compared to those detected by Western blots, and by monitoring the enzymatic activity in zymogram gels, using gelatin as a substrate. The high accuracy annotations were obtained by fast turnaround MALDI-Orbitrap analysis from excised and digested gel bands. Multiple PSA forms were identified utilizing a combination of MASCOT and SEQUEST search engines

Bioinformatic strategies for unambiguous identification of prostate specific antigen in clinical samples.

Prostate specific antigen (PSA), as a widely used clinical biomarker in prostate cancer diagnostics, exists in multiple molecular forms. However, all of these forms might not be recognized in a given sample by the standard immunoassays. Therefore, we have investigated PSA isoforms, separated by size, using mass spectrometric analyses. The objective of these developments was to identify and specify the various forms of PSA. To optimize successful identification of different PSA forms, we have developed a bioinformatic strategy, consisting of high resolution MALDI-MS PMF and sequencing MS/MS data searches. To improve sequence-based identification, the recently introduced Proteios software environment was employed, allowing the combination of multiple database search engines in an automated manner. We could unambiguously identify PSA in clinical samples by all detectable tryptic peptides, which were found to be common in several isoforms

Molecular microheterogeneity of prostate specific antigen in seminal fluid by mass spectrometry.

OBJECTIVES: Prostate specific antigen (PSA) is a widely used and clinically valuable marker for prostate disease. In order to enable the development of new PSA assays and progress the understanding of the biology of PSA we have analyzed PSA in seminal plasma. DESIGN AND METHODS: PSA in seminal plasma from men attending a fertility clinic and healthy controls was analyzed using SDS-PAGE, Western blotting and mass spectrometry. RESULTS: Using mass spectrometry, different forms of PSA could be identified in 1-9 bands seen on SDS-PAGE analysis of the respective sample. However, a majority of these molecular forms of PSA were not observed on Western blots. Enzymatic activity of PSA isoforms was demonstrated by sequencing data in zymogram gels. Multivariate analysis of clinical data revealed well-separated patient groups. CONCLUSIONS: We demonstrated that PSA in seminal plasma occurs in several isoforms, yet not all were detectable using an antibody based clinical routine method. The heterogeneity of PSA expression might be of clinical significance, by an improved patient phenotyping

Differences in biomarker concentrations and predictions of long-term outcome in patients with ST-elevation and non-ST-elevation myocardial infarction

Background Differences in biomarkers reflective of pathobiology and prognosis between ST-elevation myocardial infarction (STEMI) and non-ST-elevation myocardial infarction (NSTEMI) are incompletely understood and may offer insights for tailoring of treatment. Methods This registry-based study included 538 STEMI and 544 NSTEMI patients admitted 2008–2014. Blood samples were collected day 1–3 after admission and 175 biomarkers were analyzed using Proximity Extension Assay and Multiple Reaction Monitoring mass spectrometry. Adjusted Lasso analysis (penalized logistic regression model) was used to select biomarkers that discriminated STEMI from NSTEMI patients. Biomarkers identified by the Lasso analysis were then evaluated in adjusted Cox regressions for associations with death or major adverse cardiovascular events. Results Biomarkers strongly discriminated STEMI and NSTEMI when considered simultaneously in adjusted Lasso analysis (c-statistic 0.764). Eleven biomarkers independently discriminated STEMI and NSTEMI; seven showing higher concentrations in STEMI: myoglobin, N-terminal pro-B-type natriuretic peptide, serum amyloid A-1 and A-2 protein, ST2 protein, interleukin-6 and chitinase-3-like protein 1; and four showing higher concentrations in NSTEMI: fibroblast growth factor 23, membrane-bound aminopeptidase P, tumor necrosis factor-related activation-induced cytokine and apolipoprotein C-I. During up to 6.6 years of prognostic follow-up, none of these biomarkers exhibited different associations with adverse outcome between STEMI and NSTEMI. Conclusions In the acute setting, biomarkers indicated greater myocardial dysfunction and inflammation in STEMI, whereas they displayed a more diverse pathophysiologic pattern in NSTEMI patients. These biomarkers were similarly prognostic in STEMI and NSTEMI patients. The results do not support treating STEMI and NSTEMI patients differently based on the concentrations of these biomarkers

Sex-differences in circulating biomarkers during acute myocardial infarction : An analysis from the SWEDEHEART registry

Background Sex-differences in the pathobiology of myocardial infarction are well established but incompletely understood. Improved knowledge on this topic may help clinicians to improve management of men and women with myocardial infarction. Methods In this registry-based cohort study (SWEDEHEART), we analyzed 175 circulating biomarkers reflecting various pathobiological axes in 856 men and 243 women admitted to Swedish coronary care units because of myocardial infarction. Two multimarker panels were applied (Proximity Extension Assay [Olink Bioscience], Multiple Reaction Monitoring mass spectrometry). Lasso analysis (penalized logistic regression), multiple testing-corrected Mann-Whitney tests and Cox regressions were used to assess sex-differences in the concentrations of these biomarkers and their implications on all-cause mortality and major adverse events (median follow-up up to 6.6 years). Results Biomarkers provided a very high discrimination between both sexes, when considered simultaneously (c-statistics 0.972). Compared to women, men had higher concentrations of six biomarkers with the most pronounced differences seen for those reflecting atherogenesis, myocardial necrosis and metabolism. Women had higher concentrations of 14 biomarkers with the most pronounced differences seen for those reflecting activation of the renin-angiotensin-aldosterone axis, inflammation and for adipokines. There were no major variations between sexes in the associations of these biomarkers with outcome. Conclusions Severable sex-differences exist in the expression of biomarkers in patients with myocardial infarction. While these differences had no impact on outcome, our data suggest the presence of various sex-related pathways involved in the development of coronary atherosclerosis, the progression to plaque rupture and acute myocardial damage, with a greater heterogeneity in women

Insights into the changes in the proteome of Alzheimer disease elucidated by a meta-analysis

Mass spectrometry (MS)-based proteomics is a powerful tool to explore pathogenic changes of a disease in an unbiased manner and has been used extensively in Alzheimer disease (AD) research. Here, by performing a meta-analysis of high-quality proteomic studies, we address which pathological changes are observed consistently and therefore most likely are of great importance for AD pathogenesis. We retrieved datasets, comprising a total of 21,588 distinct proteins identified across 857 postmortem human samples, from ten studies using labeled or label-free MS approaches. Our meta-analysis findings showed significant alterations of 757 and 1,195 proteins in AD in the labeled and label-free datasets, respectively. Only 33 proteins, some of which were associated with synaptic signaling, had the same directional change across the individual studies. However, despite alterations in individual proteins being different between the labeled and the label-free datasets, several pathways related to synaptic signaling, oxidative phosphorylation, immune response and extracellular matrix were commonly dysregulated in AD. These pathways represent robust changes in the human AD brain and warrant further investigation