Mapping Proteome Changes in Microsatellite Stable, Recurrent Colon Cancer Reveals a Significant Immune System Signature

BACKGROUND/AIM

Better stratification of the risk of relapse will help select the right patients for adjuvant treatment and improve targeted therapies for patients with colon cancer.

MATERIALS AND METHODS

To understand why a subset of tumors relapse, we compared the proteome of two groups of patients with colon cancer with similar stage, stratified based on the presence or absence of recurrence.

RESULTS

Using tumor biopsies from the primary operation, we identified dissimilarity between recurrent and nonrecurrent mismatch satellite stable colon cancer and found that signaling related to immune activation and inflammation was associated with relapse.

CONCLUSION

Immune modulation may have an effect on mismatch satellite stable colon cancer. At present, immune therapy is offered primarily to microsatellite instable colon cancer. Hopefully, immune therapy in mismatch satellite stable colon cancer beyond PD-1 and PD-L1 inhibitors can be implemented.

The Effect of Wnt Pathway Modulators on Human iPSC-Derived Pancreatic Beta Cell Maturation

Current published protocols for targeted differentiation of human stem cells toward pancreatic β-cells fail to deliver sufficiently mature cells with functional properties comparable to human islet β-cells. We aimed to assess whether Wnt-modulation could promote the final protocol stages of β-cell maturation, building our hypothesis on our previous findings of Wnt activation in immature hiPSC-derived stage 7 (S7) cells compared to adult human islets and with recent data reporting a link between Wnt/PCP and in vitro β-cell maturation. In this study, we stimulated canonical and non-canonical Wnt signaling in hiPSC-derived S7 cells using syntetic proteins including WNT3A, WNT4, WNT5A and WNT5B, and we inhibited endogenous Wnt signaling with the Tankyrase inhibitor G007-LK (TKi). Whereas neither canonical nor non-canonical Wnt stimulation alone was able to mature hiPSC-derived S7 cells, WNT-inhibition with TKi increased the fraction of monohormonal cells and global proteomics of TKi-treated S7 cells showed a proteomic signature more similar to adult human islets, suggesting that inhibition of endogenous Wnt contributes toward final β-cell maturation.

Label-free analysis of human cerebrospinal fluid addressing various normalization strategies and revealing protein groups affected by multiple sclerosis

The aims of the study were to: (i) identify differentially regulated proteins in cerebrospinal fluid (CSF) between multiple sclerosis (MS) patients and non-MS controls; (ii) examine the effect of matching the CSF samples on either total protein amount or volume, and compare four protein normalization strategies for CSF protein quantification. CSF from MS patients (n = 37) and controls (n = 64), consisting of other noninflammatory neurological diseases (n = 50) and non neurological spinal anesthetic subjects (n = 14), were analyzed using label-free proteomics, quantifying almost 800 proteins. In total, 122 proteins were significantly regulated (p < 0.05), where 77 proteins had p-value <0.01 or AUC value >0.75. Hierarchical clustering indicated that there were two main groups of MS patients, those with increased levels of inflammatory response proteins and decreased levels of proteins involved in neuronal tissue development (n = 30), and those with normal protein levels for both of these protein groups (n = 7). The main subgroup of controls clustering with the MS patients showing increased inflammation and decreased neuronal tissue development were patients suffering from chronic fatigue. Our data indicate that the preferable way to quantify proteins in CSF is to first match the samples on total protein amount and then normalize the data based on the median intensities, preferably from the CNS-enriched proteins.

In-depth characterization of the cerebrospinal fluid (CSF) proteome displayed through the CSF proteome resource (CSF-PR)

In this study, the human cerebrospinal fluid (CSF) proteome was mapped using three different strategies prior to Orbitrap LC-MS/MS analysis: SDS-PAGE and mixed mode reversed phase-anion exchange for mapping the global CSF proteome, and hydrazide-based glycopeptide capture for mapping glycopeptides. A maximal protein set of 3081 proteins (28,811 peptide sequences) was identified, of which 520 were identified as glycoproteins from the glycopeptide enrichment strategy, including 1121 glycopeptides and their glycosylation sites. To our knowledge, this is the largest number of identified proteins and glycopeptides reported for CSF, including 417 glycosylation sites not previously reported. From parallel plasma samples, we identified 1050 proteins (9739 peptide sequences). An overlap of 877 proteins was found between the two body fluids, whereas 2204 proteins were identified only in CSF and 173 only in plasma. All mapping results are freely available via the new CSF Proteome Resource (http://probe.uib.no/csf-pr), which can be used to navigate the CSF proteome and help guide the selection of signature peptides in targeted quantitative proteomics.

Quantitative proteomics comparison of arachnoid cyst fluid and cerebrospinal fluid collected perioperatively from arachnoid cyst patients

BACKGROUND

There is little knowledge concerning the content and the mechanisms of filling of arachnoid cysts. The aim of this study was to compare the protein content of arachnoid cysts and cerebrospinal fluid by quantitative proteomics to increase the understanding of arachnoid cysts.

METHODS

Arachnoid cyst fluid and cerebrospinal fluid from five patients were analyzed by quantitative proteomics in two separate experiments.In a label-free experiment arachnoid cyst fluid and cerebrospinal fluid samples from individual patients were trypsin digested and analyzed by Orbitrap mass spectrometry in a label-free manner followed by data analysis using the Progenesis software.In the second proteomics experiment, a patient sample pooling strategy was followed by MARS-14 immunodepletion of high abundant proteins, trypsin digestion, iTRAQ labelling, and peptide separation by mix-phase chromatography followed by Orbitrap mass spectrometry analysis. The results from these analyzes were compared to previously published mRNA microarray data obtained from arachnoid membranes.

RESULTS

We quantified 348 proteins by the label-free individual patient approach and 1425 proteins in the iTRAQ experiment using a pool from five patients of arachnoid cyst fluid and cerebrospinal fluid. This is by far the largest number of arachnoid cyst fluid proteins ever identified, and the first large-scale quantitative comparison between the protein content of arachnoid cyst fluid and cerebrospinal fluid from the same patients at the same time. Consistently in both experiment, we found 22 proteins with significantly increased abundance in arachnoid cysts compared to cerebrospinal fluid and 24 proteins with significantly decreased abundance. We did not observe any molecular weight gradient over the arachnoid cyst membrane. Of the 46 proteins we identified as differentially abundant in our study, 45 were also detected from the mRNA expression level study. None of them were previously reported as differentially expressed. We did not quantify any of the proteins corresponding to gene products from the ten genes previously reported as differentially abundant between arachnoid cysts and control arachnoid membranes.

CONCLUSIONS

From our experiments, the protein content of arachnoid cyst fluid and cerebrospinal fluid appears to be similar. There were, however, proteins that were significantly differentially abundant between arachnoid cyst fluid and cerebrospinal fluid. This could reflect the possibility that these proteins are affected by the filling mechanism of arachnoid cysts or are shed from the membranes into arachnoid cyst fluid. Our results do not support the proposed filling mechanisms of oncotic pressure or valves.

Protein profiling reveals inter-individual protein homogeneity of arachnoid cyst fluid and high qualitative similarity to cerebrospinal fluid

BACKGROUND

The mechanisms behind formation and filling of intracranial arachnoid cysts (AC) are poorly understood. The aim of this study was to evaluate AC fluid by proteomics to gain further knowledge about ACs. Two goals were set: 1) Comparison of AC fluid from individual patients to determine whether or not temporal AC is a homogenous condition; and 2) Evaluate the protein content of a pool of AC fluid from several patients and qualitatively compare this with published protein lists of cerebrospinal fluid (CSF) and plasma.

METHODS

AC fluid from 15 patients with temporal AC was included in this study. In the AC protein comparison experiment, AC fluid from 14 patients was digested, analyzed by LC-MS/MS using a semi-quantitative label-free approach and the data were compared by principal component analysis (PCA) to gain knowledge of protein homogeneity of AC. In the AC proteome evaluation experiment, AC fluid from 11 patients was pooled, digested, and fractionated by SCX chromatography prior to analysis by LC-MS/MS. Proteins identified were compared to published databases of proteins identified from CSF and plasma. AC fluid proteins not found in these two databases were experimentally searched for in lumbar CSF taken from neurologically-normal patients, by a targeted protein identification approach called MIDAS (Multiple Reaction Monitoring (MRM) initiated detection and sequence analysis).

RESULTS

We did not identify systematic trends or grouping of data in the AC protein comparison experiment, implying low variability between individual proteomic profiles of AC.In the AC proteome evaluation experiment, we identified 199 proteins. When compared to previously published lists of proteins identified from CSF and plasma, 15 of the AC proteins had not been reported in either of these datasets. By a targeted protein identification approach, we identified 11 of these 15 proteins in pooled CSF from neurologically-normal patients, demonstrating that the majority of abundant proteins in AC fluid also can be found in CSF. Compared to plasma, as many as 104 proteins in AC were not found in the list of 3017 plasma proteins.

CONCLUSIONS

Based on the protein content of AC fluid, our data indicate that temporal AC is a homogenous condition, pointing towards a similar AC filling mechanism for the 14 patients examined. Most of the proteins identified in AC fluid have been identified in CSF, indicating high similarity in the qualitative protein content of AC to CSF, whereas this was not the case between AC and plasma. This indicates that AC is filled with a liquid similar to CSF. As far as we know, this is the first proteomics study that explores the AC fluid proteome.

Arachnoid cysts do not contain cerebrospinal fluid: A comparative chemical analysis of arachnoid cyst fluid and cerebrospinal fluid in adults

Background

Arachnoid cyst (AC) fluid has not previously been compared with cerebrospinal fluid (CSF) from the same patient. ACs are commonly referred to as containing "CSF-like fluid". The objective of this study was to characterize AC fluid by clinical chemistry and to compare AC fluid to CSF drawn from the same patient. Such comparative analysis can shed further light on the mechanisms for filling and sustaining of ACs.

Methods

Cyst fluid from 15 adult patients with unilateral temporal AC (9 female, 6 male, age 22-77y) was compared with CSF from the same patients by clinical chemical analysis.

Results

AC fluid and CSF had the same osmolarity. There were no significant differences in the concentrations of sodium, potassium, chloride, calcium, magnesium or glucose. We found significant elevated concentration of phosphate in AC fluid (0.39 versus 0.35 mmol/L in CSF; p = 0.02), and significantly reduced concentrations of total protein (0.30 versus 0.41 g/L; p = 0.004), of ferritin (7.8 versus 25.5 ug/L; p = 0.001) and of lactate dehydrogenase (17.9 versus 35.6 U/L; p = 0.002) in AC fluid relative to CSF.

Conclusions

AC fluid is not identical to CSF. The differential composition of AC fluid relative to CSF supports secretion or active transport as the mechanism underlying cyst filling. Oncotic pressure gradients or slit-valves as mechanisms for generating fluid in temporal ACs are not supported by these results.

[Lymphoma of the pituitary stalk]

INTRODUCTION

Tumors of the pituitary stalk are rare and their diagnosis is sometimes difficult.

CASE REPORT

We report a case of a primary lymphoma of the pituitary stalk in a 78-year-old patient. To our knowledge, only seven similar cases have been previously published: prominent symptoms were headache, fatigue and diplopia; biologically, anterior pituitary low secretion or hyperprolactinemia were found in the majority of cases; regarding the imaging, only three patients presented an initial and isolated lesion of the stalk; histological evidence was obtained by a trans-sphenoidal biopsy in case of hypothalamic or pituitary associated lesion or by a trans-cranial biopsy in the event of an isolated lesion. As an alternative, a lumbar puncture could be performed; although less invasive, its diagnostic performance is lower.

CONCLUSION

Current treatment relies on chemotherapy with intravenous methotrexate associated with intrathecal methotrexate infusion if cerebrospinal showed abnormal cells. Unfortunately, the results remain poor with a median survival of 9 months.

Pretreatment of Mass Spectral Profiles: Application to Proteomic Data

Mass spectral profiles are influenced by several factors that have no relation to compositional differences between samples: baseline effects, shifts in mass-to-charge ratio (m/z) (synchronization/alignment problem), structured noise (heteroscedasticity), and, differences in signal intensities (normalization problem). Different procedures for pretreatment of whole mass spectral profiles described by almost 50,000 m/z values are investigated in order to find optimal approaches with respect to revealing the information content in the data. In order to quantitatively assess the impact of different procedures for pretreatment of mass spectral profiles, we use factorial designs with the ratio between intergroup and intragroup (replicate) variance as response. We have examined the influence of smoothing, binning, alignment/synchronization, noise pattern, and normalization on data interpretation. Our analysis shows that the spectral profiles have to be corrected for heteroscedastic noise prior to normalization. An nth root transform, where n is a small, positive integer, is used to create a homoscedastic noise structure without destroying the linear correlation structures describing individual components when using whole mass spectral profiles. The choice of n is decided by a simple graphic procedure using replicate information. Log transform is shown to change the heteroscedastic noise structure from being dominant in high-intensity regions, to produce the largest noise in the low-intensity regions. In addition, log transform has a negative effect on the collinearity in the profiles. Factorial designs reveal strong interactions between several of the pretreatment steps, e.g., noise structure and normalization. This underlines the limited usability of looking at the different pretreatment steps in isolation. Binning turns out to be able to substitute smoothing of spectra by, for example, moving average or Savitsky-Golay, while, at the same time, reducing the data point description of the profiles by 1 order of magnitude. Thus, if the sampling density is high, binning seems to be an attractive option for data reduction without the risk of losing information accompanying the integration of profiles into peaks. In the absence of smoothing, binning should be executed prior to alignment. If binning is not performed, the order of pretreatment should be smoothing, alignment, nth root transform, and normalization.

Proteomic-based biomarker discovery with emphasis on cerebrospinal fluid and multiple sclerosis

Discovery of disease specific biomarkers in human body fluids has become an important challenge in clinical proteomics. Facing the increasing threat of degenerative and disabling diseases like cancer, cardiovascular, neurological and inflammatory diseases in large parts of the world's population, there is an urgent need to improve early diagnostics. In this review we discuss possibilities and limitations connected to using mass spectrometry based proteomics in the search for novel biomarkers, with focus on multiple sclerosis as a typical representative for the large group of non-curable degenerative and disabling disease with the lack of specific tests for early diagnosis. Careful control of the pre-analytical phase including sampling, storage and fractionation of samples, in addition to a thoroughly considered patient selection, is important in order to avoid false biomarkers to appear in the resulting mass spectra. Furthermore, advanced computational tools are needed in order to discover potential biomarkers from the enormous data amounts generated by the mass spectrometers. The development of such computer tools is a research field currently in the start phase and could prove to be a bottle neck in the biomarker discovery the next years. Therefore, a rather detailed review of the most used computational and pre-analytical methods is given in this review. Mass spectrometry based biomarker discovery is undoubtedly still in its early infancy. However, in light of the potential of this technology to provide deep coverage of the body fluid proteomes, it will certainly consolidate its role in developing molecular medicine into clinical practice.