Degradation of polysorbate investigated by a high-performance liquid chromatography multi-detector system with charged aerosol and mass detection.

Polysorbate 80 is widely used as a formulation component in biopharmaceutical drug products. Recent studies have shown that polysorbate 80 is readily degraded either through direct or indirect means. The degradation of polysorbate 80 causes a concern for the long-term stability of biopharmaceutical drug product, as the breakdown products of polysorbate 80 have been shown to cause adverse effects, such as formation of sub-visible and visible particles and mAb aggregation. Understanding the path and extent of degradation is of a paramount importance for the formulator during formulation development. A multi-detector HPLC system using charged aerosol and mass detection was developed and optimized for the characterization of polysorbate 80 standards. The system included a post-column make-up flow, i.e. an inverse gradient, that enabled constant eluent composition at the detectors. The inverse gradient eliminated the main source of variability for the charged aerosol detector response, thereby enabling the calculation of the mass balance between polysorbate components with different degrees of esterification. Extracted ion chromatograms of the mass detector combined with their respective retention times were used to qualitatively characterize the polysorbate samples down to the individual components. The system was applied to study the degradation of several polysorbate standards which occurred by enzymatic digestion or long-term storage. The system provided detailed information on the mechanism of degradation without the need for additional orthogonal analytical techniques.

High-resolution MALDI mass spectrometric imaging of lipids in the mammalian retina.

Matrix-assisted laser desorption/ionization mass spectrometric imaging (MALDI-MSI) is emerging as a powerful tool for the analysis of molecular distributions in biological samples in situ. When compared to classical histology, the major benefit of this method is the ability to identify and localize many molecules in a single tissue sample. MALDI-MSI spatial resolution currently falls short of traditional microscopic methods as it is limited by instrumentation and sample preparation. Tissue preparation steps, such as matrix deposition, are critical when considering strategies to further enhance the spatial resolution. The mammalian retina was selected as the tissue of choice for method development; its stratified anatomy renders it an ideal tissue to test high-resolution MALDI-MSI as the different layers correspond to specific neuronal classes and cellular structures. We compared alcohol-fixed, paraffin-embedded retina to fresh-frozen samples and matrix that had been deposited by spray or by sublimation. We present a lipid imaging method based on MALDI-MSI of frozen retinal sections with sublimated 2,5-dihydroxybenzoic acid matrix, which results in a highly advanced resolution compared to previous established methods. Hierarchical clustering of the primary data allows robust detection and differentiation of molecular distributions at a spatial resolution between 10 and 20 µm, thus approaching single-cell resolution.

High-resolution metabolite imaging of light and dark treated retina using MALDI-FTICR mass spectrometry.

MS imaging (MSI) is a valuable tool for diagnostics and systems biology studies, being a highly sensitive, label-free technique capable of providing comprehensive spatial distribution of different classes of biomolecules. The application of MSI to the study of endogenous compounds has received considerable attention because metabolites are the result of the interactions of a biosystem with its environment. MSI can therefore enhance understanding of disease mechanisms and elucidate mechanisms for biological variation. We present the in situ comparative metabolomics imaging data for analyses of light- and dark-treated retina using MALDI-FTICR. A wide variety of tissue metabolites were imaged at a high spatial resolution. These include nucleotides, central carbon metabolism pathway intermediates, 2-oxocarboxylic acid metabolism, oxidative phosphorylation, glycerophospholipid metabolism, and cysteine and methionine metabolites. The high lateral resolution enabled the differentiation of retinal layers, allowing determination of the spatial distributions of different endogenous compounds. A number of metabolites demonstrated differences between light and dark conditions. These findings add to the understanding of metabolic activity in the retina.

MALDI-MS tissue imaging identification of biliverdin reductase B overexpression in prostate cancer.

New biomarkers are needed to improve the specificity of prostate cancer detection and characterisation of individual tumors. In a proteomics profiling approach using MALDI-MS tissue imaging on frozen tissue sections, we identified discriminating masses. Imaging analysis of cancer, non-malignant benign epithelium and stromal areas of 15 prostatectomy specimens in a test and 10 in a validation set identified characteristic m/z peaks for each tissue type, e.g. m/z 10775 for benign epithelial, m/z 6284 and m/z 6657.5 for cancer and m/z 4965 for stromal tissue. A 10-fold cross-validation analysis showed highest discriminatory ability to separate tissue types for m/z 6284 and m/z 6657.5, both overexpressed in cancer, and a multicomponent mass peak cluster at m/z 10775-10797.4 overexpressed in benign epithelial tissue. ROC AUC values for these three masses ranged from 0.85 to 0.95 in the discrimination of malignant and non-malignant tissue. To identify the underlying proteins, prostate whole tissue extract was separated by nano-HPLC and subjected to MALDI TOF/TOF analysis. Proteins in fractions containing discriminatory m/z masses were identified by MS/MS analysis and candidate marker proteins subsequently validated by immunohistochemistry (IHC). Biliverdin reductase B (BLVRB) turned out to be overexpressed in PCa tissue. BIOLOGICAL SIGNIFICANCE: In this study on cryosections of radical prostatectomies of prostate cancer patients, we performed a MALDI-MS tissue imaging analysis and a consecutive protein identification of significant m/z masses by nano-HPLC, MALDI TOF/TOF and MS/MS analysis. We identified BLVRB as a potential biomarker in the discrimination of PCa and benign tissue, also suggesting BVR as a feasible therapeutic target.

Comprehensive identification of proteins from MALDI imaging.

Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) is a powerful tool for the visualization of proteins in tissues and has demonstrated considerable diagnostic and prognostic value. One main challenge is that the molecular identity of such potential biomarkers mostly remains unknown. We introduce a generic method that removes this issue by systematically identifying the proteins embedded in the MALDI matrix using a combination of bottom-up and top-down proteomics. The analyses of ten human tissues lead to the identification of 1400 abundant and soluble proteins constituting the set of proteins detectable by MALDI IMS including >90% of all IMS biomarkers reported in the literature. Top-down analysis of the matrix proteome identified 124 mostly N- and C-terminally fragmented proteins indicating considerable protein processing activity in tissues. All protein identification data from this study as well as the IMS literature has been deposited into MaTisse, a new publically available database, which we anticipate will become a valuable resource for the IMS community.

Clinical response to chemotherapy in oesophageal adenocarcinoma patients is linked to defects in mitochondria.

Chemotherapeutic drugs kill cancer cells, but it is unclear why this happens in responding patients but not in non-responders. Proteomic profiles of patients with oesophageal adenocarcinoma may be helpful in predicting response and selecting more effective treatment strategies. In this study, pretherapeutic oesophageal adenocarcinoma biopsies were analysed for proteomic changes associated with response to chemotherapy by MALDI imaging mass spectrometry. Resulting candidate proteins were identified by liquid chromatography-tandem mass spectrometry (LC-MS/MS) and investigated for functional relevance in vitro. Clinical impact was validated in pretherapeutic biopsies from an independent patient cohort. Studies on the incidence of these defects in other solid tumours were included. We discovered that clinical response to cisplatin correlated with pre-existing defects in the mitochondrial respiratory chain complexes of cancer cells, caused by loss of specific cytochrome c oxidase (COX) subunits. Knockdown of a COX protein altered chemosensitivity in vitro, increasing the propensity of cancer cells to undergo cell death following cisplatin treatment. In an independent validation, patients with reduced COX protein expression prior to treatment exhibited favourable clinical outcomes to chemotherapy, whereas tumours with unchanged COX expression were chemoresistant. In conclusion, previously undiscovered pre-existing defects in mitochondrial respiratory complexes cause cancer cells to become chemosensitive: mitochondrial defects lower the cells' threshold for undergoing cell death in response to cisplatin. By contrast, cancer cells with intact mitochondrial respiratory complexes are chemoresistant and have a high threshold for cisplatin-induced cell death. This connection between mitochondrial respiration and chemosensitivity is relevant to anticancer therapeutics that target the mitochondrial electron transport chain.

Matrix-assisted laser desorption/ionization imaging protocol for in situ characterization of tryptic peptide identity and distribution in formalin-fixed tissue.

RATIONALE: Matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry provides the means to map the in situ distribution of tryptic peptides in formalin-fixed clinical tissue samples. The ability to analyze clinical samples is of great importance to further developments in the imaging field. However, there is a requirement in this field of research for additional methods describing the characterization of tryptic peptides by MALDI imaging. METHODS AND RESULTS: This protocol gives highly detailed instructions, with examples, for (1) successfully performing tryptic peptide MALDI imaging on formalin-fixed cancer tissue using a MALDI-TOF/TOF MS instrument, (2) tentatively generating identifications through nLC/MS/MS, and (3) validating these identifications by in situ MS/MS of peptides of interest. CONCLUSIONS: This protocol provides a detailed and straightforward description of the methods required for groups new to MALDI imaging to begin analysis of formalin-fixed clinical samples.

MALDI imaging mass spectrometry for direct tissue analysis.

MALDI (Matrix-Assisted Laser Desorption/Ionization) Imaging mass spectrometry is a powerful new method for analyzing the spatial distribution of molecules in tissues. Several different classes of cellular constituents such as proteins, peptides, lipids, and small molecules can be analyzed in situ while maintaining the morphological integrity of the tissue. This allows a correlation of the morphology with the previously acquired molecular patterns. By this, specific molecules can be clearly assigned to their cellular origin. Here, we will present a protocol for the analysis of proteins in tissues which are either native or alcohol-fixed and paraffin-embedded.

Tryptic peptide reference data sets for MALDI imaging mass spectrometry on formalin-fixed ovarian cancer tissues.

MALDI imaging mass spectrometry is a powerful tool for morphology-based proteomic tissue analysis. However, peptide identification is still a major challenge due to low S/N ratios, low mass accuracy and difficulties in correlating observed m/z species with peptide identities. To address this, we have analyzed tryptic digests of formalin-fixed paraffin-embedded tissue microarray cores, from 31 ovarian cancer patients, by LC-MS/MS. The sample preparation closely resembled the MALDI imaging workflow in order to create representative reference data sets containing peptides also observable in MALDI imaging experiments. This resulted in 3844 distinct peptide sequences, at a false discovery rate of 1%, for the entire cohort and an average of 982 distinct peptide sequences per sample. From this, a total of 840 proteins and, on average, 297 proteins per sample could be inferred. To support the efforts of the Chromosome-centric Human Proteome Project Consortium, we have annotated these proteins with their respective chromosome location. In the presented work, the benefit of using a large cohort of data sets was exemplified by correct identification of several m/z species observed in a MALDI imaging experiment. The tryptic peptide data sets generated will facilitate peptide identification in future MALDI imaging studies on ovarian cancer.

Internal calibrants allow high accuracy peptide matching between MALDI imaging MS and LC-MS/MS.

One of the important challenges for MALDI imaging mass spectrometry (MALDI-IMS) is the unambiguous identification of measured analytes. One way to do this is to match tryptic peptide MALDI-IMS m/z values with LC-MS/MS identified m/z values. Matching using current MALDI-TOF/TOF MS instruments is difficult due to the variability of in situ time-of-flight (TOF) m/z measurements. This variability is currently addressed using external calibration, which limits achievable mass accuracy for MALDI-IMS and makes it difficult to match these data to downstream LC-MS/MS results. To overcome this challenge, the work presented here details a method for internally calibrating data sets generated from tryptic peptide MALDI-IMS on formalin-fixed paraffin-embedded sections of ovarian cancer. By calibrating all spectra to internal peak features the m/z error for matches made between MALDI-IMS m/z values and LC-MS/MS identified peptide m/z values was significantly reduced. This improvement was confirmed by follow up matching of LC-MS/MS spectra to in situ MS/MS spectra from the same m/z peak features. The sum of the data presented here indicates that internal calibrants should be a standard component of tryptic peptide MALDI-IMS experiments.

Tissue-based proteomics reveals FXYD3, S100A11 and GSTM3 as novel markers for regional lymph node metastasis in colon cancer.

Regional lymph node metastasis negatively affects prognosis in colon cancer patients. The molecular processes leading to regional lymph node metastasis are only partially understood and proteomic markers for metastasis are still scarce. Therefore, a tissue-based proteomic approach was undertaken for identifying proteins associated with regional lymph node metastasis. Two complementary tissue-based proteomic methods have been employed. MALDI imaging was used for identifying small proteins (≤25 kDa) in situ and label-free quantitative proteomics was used for identifying larger proteins. A tissue cohort comprising primary colon tumours without metastasis (UICC II, pN0, n = 21) and with lymph node metastasis (UICC III, pN2, n = 33) was analysed. Subsequent validation of identified proteins was done by immunohistochemical staining on an independent tissue cohort consisting of primary colon tumour specimens (n = 168). MALDI imaging yielded ten discriminating m/z species, and label-free quantitative proteomics 28 proteins. Two MALDI imaging-derived candidate proteins (FXYD3 and S100A11) and one from the label-free quantitative proteomics (GSTM3) were validated on the independent tissue cohort. All three markers correlated significantly with regional lymph node metastasis: FXYD3 (p = 0.0110), S100A11 (p = 0.0071), and GSTM3 (p = 0.0173). FXYD3 and S100A11 were more highly expressed in UICC II patient tumour tissues. GSTM3 was more highly expressed in UICC III patient tumour tissues. By our tissue-based proteomic approach, we could identify a large panel of proteins which are associated with regional lymph node metastasis and which have not been described so far. Here we show that novel markers for regional lymph metastasis can be identified by MALDI imaging or label-free quantitative proteomics and subsequently validated on an independent tissue cohort.

MALDI imaging mass spectrometry reveals COX7A2, TAGLN2 and S100-A10 as novel prognostic markers in Barrett's adenocarcinoma.

To characterize proteomic changes found in Barrett's adenocarcinoma and its premalignant stages, the proteomic profiles of histologically defined precursor and invasive carcinoma lesions were analyzed by MALDI imaging MS. For a primary proteomic screening, a discovery cohort of 38 fresh frozen Barrett's adenocarcinoma patient tissue samples was used. The goal was to find proteins that might be used as markers for monitoring cancer development as well as for predicting regional lymph node metastasis and disease outcome. Using mass spectrometry for protein identification and validating the results by immunohistochemistry on an independent validation set, we could identify two of 60 differentially expressed m/z species between Barrett's adenocarcinoma and the precursor lesion: COX7A2 and S100-A10. Furthermore, among 22 m/z species that are differentially expressed in Barrett's adenocarcinoma cases with and without regional lymph node metastasis, one was identified as TAGLN2. In the validation set, we found a correlation of the expression levels of COX7A2 and TAGLN2 with a poor prognosis while S100-A10 was confirmed by multivariate analysis as a novel independent prognostic factor in Barrett's adenocarcinoma. Our results underscore the high potential of MALDI imaging for revealing new biologically significant molecular details from cancer tissues which might have potential for clinical application. This article is part of a Special Issue entitled: Translational Proteomics.

Tumor classification of six common cancer types based on proteomic profiling by MALDI imaging.

In clinical diagnostics, it is of outmost importance to correctly identify the source of a metastatic tumor, especially if no apparent primary tumor is present. Tissue-based proteomics might allow correct tumor classification. As a result, we performed MALDI imaging to generate proteomic signatures for different tumors. These signatures were used to classify common cancer types. At first, a cohort comprised of tissue samples from six adenocarcinoma entities located at different organ sites (esophagus, breast, colon, liver, stomach, thyroid gland, n = 171) was classified using two algorithms for a training and test set. For the test set, Support Vector Machine and Random Forest yielded overall accuracies of 82.74 and 81.18%, respectively. Then, colon cancer liver metastasis samples (n = 19) were introduced into the classification. The liver metastasis samples could be discriminated with high accuracy from primary tumors of colon cancer and hepatocellular carcinoma. Additionally, colon cancer liver metastasis samples could be successfully classified by using colon cancer primary tumor samples for the training of the classifier. These findings demonstrate that MALDI imaging-derived proteomic classifiers can discriminate between different tumor types at different organ sites and in the same site.

S100-A10, thioredoxin, and S100-A6 as biomarkers of papillary thyroid carcinoma with lymph node metastasis identified by MALDI imaging.

In papillary thyroid carcinoma (PTC), metastasis is a feature of an aggressive tumor phenotype. To identify protein biomarkers that distinguish patients with an aggressive tumor behavior, proteomic signatures in metastatic and non-metastatic tumors were investigated comparatively. In particular, matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) was used to analyze primary tumor samples. We investigated a tumor cohort of PTC (n = 118) that were matched for age, tumor stage, and gender. Proteomic screening by MALDI-IMS was performed for a discovery set (n = 29). Proteins related to the discriminating mass peaks were identified by 1D-gel electrophoresis followed by mass spectrometry. The candidate proteins were subsequently validated by immunohistochemistry (IHC) using a tissue microarray for an independent PTC validation set (n = 89). In this study, we found 36 mass-to-charge-ratio (m/z) species that specifically distinguished metastatic from non-metastatic tumors, among which m/z 11,608 was identified as thioredoxin, m/z 11,184 as S100-A10, and m/z 10,094 as S100-A6. Furthermore, using IHC on the validation set, we showed that the overexpression of these three proteins was highly associated with lymph node metastasis in PTC (p < 0.005). For functional analysis of the metastasis-specific proteins, we performed an Ingenuity Pathway Analysis and discovered a strong relationship of all candidates with the TGF-ß-dependent EMT pathway. Our results demonstrated the potential application of the MALDI-IMS proteomic approach in identifying protein markers of metastasis in PTC. The novel protein markers identified in this study may be used for risk stratification regarding metastatic potential in PTC.

MALDI imaging identifies prognostic seven-protein signature of novel tissue markers in intestinal-type gastric cancer.

Proteomics-based approaches allow us to investigate the biology of cancer beyond genomic initiatives. We used histology-based matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry to identify proteins that predict disease outcome in gastric cancer after surgical resection. A total of 181 intestinal-type primary resected gastric cancer tissues from two independent patient cohorts were analyzed. Protein profiles of the discovery cohort (n = 63) were directly obtained from tumor tissue sections by MALDI imaging. A seven-protein signature was associated with an unfavorable overall survival independent of major clinical covariates. The prognostic significance of three individual proteins identified (CRIP1, HNP-1, and S100-A6) was validated immunohistochemically on tissue microarrays of an independent validation cohort (n = 118). Whereas HNP-1 and S100-A6 were found to further subdivide early-stage (Union Internationale Contre le Cancer [UICC]-I) and late-stage (UICC II and III) cancer patients into different prognostic groups, CRIP1, a protein previously unknown in gastric cancer, was confirmed as a novel and independent prognostic factor for all patients in the validation cohort. The protein pattern described here serves as a new independent indicator of patient survival complementing the previously known clinical parameters in terms of prognostic relevance. These results show that this tissue-based proteomic approach may provide clinically relevant information that might be beneficial in improving risk stratification for gastric cancer patients.

Classification of HER2/neu status in gastric cancer using a breast-cancer derived proteome classifier.

HER2-testing in breast and gastric cancers is mandatory for the treatment with trastuzumab. We hypothesized that imaging mass spectrometry (IMS) of breast cancers may be useful for generating a classifier that may determine HER2-status in other cancer entities irrespective of primary tumor site. A total of 107 breast (n = 48) and gastric (n = 59) cryo tissue samples was analyzed by IMS (HER2 was present in 29 cases). The obtained proteomic profiles were used to create HER2 prediction models using different classification algorithms. A breast cancer proteome derived classifier, with HER2 present in 15 cases, correctly predicted HER2-status in gastric cancers with a sensitivity of 65% and a specificity of 92%. To create a universal classifier for HER2-status, breast and nonbreast cancer samples were combined, which increased sensitivity to 78%, and specificity was 88%. Our proof of principle study provides evidence that HER2-status can be identified on a proteomic level across different cancer types suggesting that HER2 overexpression may constitute a unique molecular event independent of the tumor site. Furthermore, these results indicate that IMS may be useful for the determination of potential drugable targets, as it offers a quicker, cheaper, and more objective analysis than the standard HER2-testing procedures immunohistochemistry and fluorescence in situ hybridization.

Proteomic analysis of PAXgene-fixed tissues.

Formalin fixation and paraffin embedding is the standard technique for preserving biological material for both storage and histological analysis. Although recent progress has been made in the molecular analysis of formalin-fixed, paraffin-embedded (FFPE) tissues, proteomic applications are a special challenge due to the cross-linking property of formalin. Here we present the results of a new formalin-free tissue fixative, PAXgene, and demonstrate successful extraction of nondegraded and immunoreactive protein for subsequent standard protein assays, such as Western blot analysis and reverse-phase protein arrays. High amounts of protein can be obtained from PAXgene-fixed, paraffin-embedded (PFPE) mouse liver and human spleen, breast, duodenum, and stomach tissues, similar to frozen material. By Western blot analysis, we found that the detection of membrane, cytoplasmic, nuclear, and phosphorylated protein from PAXgene-fixed human tissue samples was comparable to cryopreserved samples. Furthermore, the distribution of protein in PAXgene-fixed human tissue specimens is adequate for matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry for in situ proteomic analysis. Taken together, we demonstrate here that PAXgene has great potential to serve as a novel multimodal fixative for modern pathology, enabling extensive protein biomarker studies on clinical tissue samples.