Position Matters: Pyridine Regioisomers Influence Secondary Structure and Micelle Morphology in Polymer-Homopolypeptide Micelles.

Polymer-homopolypeptide block copolymers are a class of bioinspired materials that combine the processability and stability of synthetic polymers with the biocompatibility and unique secondary structures of peptides, such as α-helices and ß-sheets. These properties make them ideal candidates for a wide variety of applications, for example, in the pharmaceutical field, where they are frequently explored as building blocks for polymeric micelle drug delivery systems. While homopolypeptide side chains can be furnished with an array of different moieties to impart the copolymers with desirable properties, such as stimulus responsivity, pyridine derivatives represent an underutilized functional group for this purpose. Additionally, the interplay between polypeptide side chain structure, secondary conformation, and micelle morphology is not yet well understood, particularly in the case of structural regioisomers. Therefore, in this work, a series of polymer-homopolypeptide copolymers were prepared from a poly(ethylene glycol)-b-poly(glutamic acid) (PEG-b-PGA) backbone, where the pendant carboxylic acid groups were covalently conjugated to a series of pyridine regioisomers by carbodiimide coupling. These pyridine regioisomers differed only in the position of the nitrogen heteroatom, ortho, meta or para, relative to the linking group, generating a series of PEG-b-poly(pyridinylmethyl glutamate) (PEG-b-PMG) copolymers. Following self-assembly of the copolymers in aqueous solutions, dynamic light scattering (DLS) revealed differences in micelle hydrodynamic diameter (Dh) (ranging from ∼60 to 120 nm), while transmission electron microscopy (TEM) and small-angle X-ray scattering (SAXS) revealed distinctive morphologies ranging from ellipsoidal, to cylindrical, and disc-like, suggesting that subtle changes in positional isomers in the polypeptide block may influence the micelle structure. Analysis of the PEG-b-PMG copolymer micelles by circular dichroism (CD) and attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy revealed that differences in the morphology were associated with changes in polypeptide secondary structure, which in turn was influenced by the position of the pyridine heteroatom. Overall, these findings contribute to the broader understanding of the relationship between polypeptide structure and micelle morphology and serve as useful insight for the rational design of polymer-polypeptide nanoparticles.

A systematic review and in silico analysis of studies investigating the ischaemic penumbra proteome in animal models of experimental stroke.

Ischaemic stroke results in the formation of a cerebral infarction bordered by an ischaemic penumbra. Characterising the proteins within the ischaemic penumbra may identify neuro-protective targets and novel circulating markers to improve patient care. This review assessed data from studies using proteomic platforms to compare ischaemic penumbra tissues to controls following experimental stroke in animal models. Proteins reported to differ significantly between penumbra and control tissues were analysed in silico to identify protein-protein interactions and over-represented pathways. Sixteen studies using rat (n = 12), mouse (n = 2) or primate (n = 2) models were included. Heterogeneity in the design of the studies and definition of the penumbra were observed. Analyses showed high abundance of p53 in the penumbra within 24 hours of permanent ischaemic stroke and was implicated in driving apoptosis, cell cycle progression, and ATM- MAPK- and p53- signalling. Between 1 and 7 days after stroke there were changes in the abundance of proteins involved in the complement and coagulation pathways. Favourable recovery 1 month after stroke was associated with an increase in the abundance of proteins involved in wound healing. Poor recovery was associated with increases in prostaglandin signalling. Findings suggest that p53 may be a target for novel therapeutics for ischaemic stroke.

Use of tryptic peptide MALDI mass spectrometry imaging to identify the spatial proteomic landscape of colorectal cancer liver metastases.

Colorectal cancer (CRC) is the second leading cause of cancer-related deaths worldwide. CRC liver metastases (CRLM) are often resistant to conventional treatments, with high rates of recurrence. Therefore, it is crucial to identify biomarkers for CRLM patients that predict cancer progression. This study utilised matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI) in combination with liquid chromatography-tandem mass spectrometry (LC-MS/MS) to spatially map the CRLM tumour proteome. CRLM tissue microarrays (TMAs) of 84 patients were analysed using tryptic peptide MALDI-MSI to spatially monitor peptide abundances across CRLM tissues. Abundance of peptides was compared between tumour vs stroma, male vs female and across three groups of patients based on overall survival (0-3 years, 4-6 years, and 7+ years). Peptides were then characterised and matched using LC-MS/MS. A total of 471 potential peptides were identified by MALDI-MSI. Our results show that two unidentified m/z values (1589.876 and 1092.727) had significantly higher intensities in tumours compared to stroma. Ten m/z values were identified to have correlation with biological sex. Survival analysis identified three peptides (Histone H4, Haemoglobin subunit alpha, and Inosine-5'-monophosphate dehydrogenase 2) and two unidentified m/z values (1305.840 and 1661.060) that were significantly higher in patients with shorter survival (0-3 years relative to 4-6 years and 7+ years). This is the first study using MALDI-MSI, combined with LC-MS/MS, on a large cohort of CRLM patients to identify the spatial proteome in this malignancy. Further, we identify several protein candidates that may be suitable for drug targeting or for future prognostic biomarker development.

Mass spectrometry imaging protocol for spatial mapping of lipids, N-glycans and peptides in murine lung tissue.

RATIONALE: The application of matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) to murine lungs is challenging due to the spongy nature of the tissue. Lungs consist of interconnected air sacs (alveoli) lined by a single layer of flattened epithelial cells, which requires inflation to maintain its natural structure. Therefore, a protocol that is compatible with both lung instillation and high spatial resolution is essential to enable multi-omic studies on murine lung disease models using MALDI-MSI. METHODS AND RESULTS: To maintain the structural integrity of the tissue, murine lungs were inflated with 8% (w/v) gelatin for lipid MSI of fresh frozen tissues or 4% (v/v) paraformaldehyde neutral buffer for N-glycan and peptide MSI of FFPE tissues. Tissues were sectioned and prepared for enzymatic digestion and/or matrix deposition. Glycerol-free PNGase F was applied for N-glycan MSI, while Trypsin Gold was applied for peptide MSI using the iMatrixSpray and ImagePrep Station, respectively. For lipid, N-glycan and peptide MSI, α-cyano-4-hydroxycinnamic acid matrix was deposited using the iMatrixSpray. MS data were acquired with 20 µm spatial resolution using a timsTOF fleX MS instrument followed by MS fragmentation of lipids, N-glycans and peptides. For lipid MSI, trapped ion mobility spectrometry was used to separate isomeric/isobaric lipid species. SCiLS™ Lab was used to visualize all MSI data. For analyte identification, MetaboScape®, GlycoMod and Mascot were used to annotate MS fragmentation spectra of lipids, N-glycans and tryptic peptides, respectively. CONCLUSIONS: Our protocol provides instructions on sample preparation for high spatial resolution MALDI-MSI, MS/MS data acquisition and lipid, N-glycan and peptide annotation and identification from murine lungs. This protocol will allow non-biased analyses of diseased lungs from preclinical murine models and provide further insight into disease models.

Label-Free Quantification Mass Spectrometry Identifies Protein Markers of Chemotherapy Response in High-Grade Serous Ovarian Cancer.

Eighty percent of ovarian cancer patients initially respond to chemotherapy, but the majority eventually experience a relapse and die from the disease with acquired chemoresistance. In addition, 20% of patients do not respond to treatment at all, as their disease is intrinsically chemotherapy resistant. Data-independent acquisition nano-flow liquid chromatography-mass spectrometry (DIA LC-MS) identified the three protein markers: gelsolin (GSN), calmodulin (CALM1), and thioredoxin (TXN), to be elevated in high-grade serous ovarian cancer (HGSOC) tissues from patients that responded to chemotherapy compared to those who did not; the differential expression of the three protein markers was confirmed by immunohistochemistry. Analysis of the online GENT2 database showed that mRNA levels of GSN, CALM1, and TXN were decreased in HGSOC compared to fallopian tube epithelium. Elevated levels of GSN and TXN mRNA expression correlated with increased overall and progression-free survival, respectively, in a Kaplan-Meier analysis of a large online repository of HGSOC patient data. Importantly, differential expression of the three protein markers was further confirmed when comparing parental OVCAR-5 cells to carboplatin-resistant OVCAR-5 cells using DIA LC-MS analysis. Our findings suggest that GSN, CALM1, and TXN may be useful biomarkers for predicting chemotherapy response and understanding the mechanisms of chemotherapy resistance. Proteomic data are available via ProteomeXchange with identifier PXD033785.

Assessment of yeast physiology during industrial-scale brewing practices using the redox-sensitive dye resazurin.

Beer refermentation in bottles is an industrial process utilized by breweries where yeast and fermentable extract are added to green beer. The beer is refermented for a minimum of 2 weeks before distribution, with the physiological state of the yeast a critical factor for successful refermentation. Ideally, fresh yeast that is propagated from a dedicated propagation plant should be used for refermentation in bottles. Here, we explored the applicability of the fluorescent and redox-sensitive dye, resazurin, to assess cellular metabolism in yeast and its ability to differentiate between growth stages. We applied this assay, with other markers of yeast physiology, to evaluate yeast quality during a full-scale industrial propagation. Resazurin allowed the discrimination between the different growth phases in yeast and afforded a more in-depth understanding of yeast metabolism during propagation. This assay can be used to optimize the yeast propagation process and cropping time to improve beer quality.

Proteomic analysis of holocarboxylase synthetase deficient-MDA-MB-231 breast cancer cells revealed the biochemical changes associated with cell death, impaired growth signaling, and metabolism.

We have previously shown that the holocarboxylase synthetase (HLCS) is overexpressed in breast cancer tissue of patients, and silencing of its expression in triple-negative cancer cell line inhibits growth and migration. Here we investigated the global biochemical changes associated with HLCS knockdown in MDA-MB-231 cells to discern the pathways that involve HLCS. Proteomic analysis of two independent HLCS knockdown cell lines identified 347 differentially expressed proteins (DEPs) whose expression change > 2-fold (p < 0.05) relative to the control cell line. GO enrichment analysis showed that these DEPs were mainly associated with the cellular process such as cellular metabolic process, cellular response to stimulus, and cellular component organization or biogenesis, metabolic process, biological regulation, response to stimuli, localization, and signaling. Among the 347 identified DEPs, 64 proteins were commonly found in both HLCS knockdown clones, confirming their authenticity. Validation of some of these DEPs by Western blot analysis showed that plasminogen activator inhibitor type 2 (SerpinB2) and interstitial collagenase (MMP1) were approximately 90% decreased in HLCS knockdown cells, consistent with a 50%-60% decrease in invasion ability of knockdown cells. Notably, argininosuccinate synthase 1 (ASS1), one of the enzymes in the urea cycle, showed approximately a 10-fold increase in the knockdown cells, suggesting the crucial role of HLCS in supporting the urea cycle in the triple-negative cancer cell line. Collectively, our proteomic data provide biochemical insights into how suppression of HLCS expression perturbs global changes in cellular processes and metabolic pathways, impairing cell growth and invasion.

A Protocol for the Acquisition of Comprehensive Proteomics Data from Single Cases Using Formalin-Fixed Paraffin Embedded Sections.

The molecular analysis of small or rare patient tissue samples is challenging and often limited by available technologies and resources, such as reliable antibodies against a protein of interest. Although targeted approaches provide some insight, here, we describe the workflow of two complementary mass spectrometry approaches, which provide a more comprehensive and non-biased analysis of the molecular features of the tissue of interest. Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) generates spatial intensity maps of molecular features, which can be easily correlated with histology. Additionally, liquid chromatography tandem mass spectrometry (LC-MS/MS) can identify and quantify proteins of interest from a consecutive section of the same tissue. Here, we present data from concurrent precancerous lesions from the endometrium and fallopian tube of a single patient. Using this complementary approach, we monitored the abundance of hundreds of proteins within the precancerous and neighboring healthy regions. The method described here represents a useful tool to maximize the number of molecular data acquired from small sample sizes or even from a single case. Our initial data are indicative of a migratory phenotype in these lesions and warrant further research into their malignant capabilities.

Chemoresistant Cancer Cell Lines Are Characterized by Migratory, Amino Acid Metabolism, Protein Catabolism and IFN1 Signalling Perturbations.

Chemoresistance remains the major barrier to effective ovarian cancer treatment. The molecular features and associated biological functions of this phenotype remain poorly understood. We developed carboplatin-resistant cell line models using OVCAR5 and CaOV3 cell lines with the aim of identifying chemoresistance-specific molecular features. Chemotaxis and CAM invasion assays revealed enhanced migratory and invasive potential in OVCAR5-resistant, compared to parental cell lines. Mass spectrometry analysis was used to analyse the metabolome and proteome of these cell lines, and was able to separate these populations based on their molecular features. It revealed signalling and metabolic perturbations in the chemoresistant cell lines. A comparison with the proteome of patient-derived primary ovarian cancer cells grown in culture showed a shared dysregulation of cytokine and type 1 interferon signalling, potentially revealing a common molecular feature of chemoresistance. A comprehensive analysis of a larger patient cohort, including advanced in vitro and in vivo models, promises to assist with better understanding the molecular mechanisms of chemoresistance and the associated enhancement of migration and invasion.

Using GPCRs as Molecular Beacons to Target Ovarian Cancer with Nanomedicines.

The five-year survival rate for women with ovarian cancer is very poor despite radical cytoreductive surgery and chemotherapy. Although most patients initially respond to platinum-based chemotherapy, the majority experience recurrence and ultimately develop chemoresistance, resulting in fatal outcomes. The current administration of cytotoxic compounds is hampered by dose-limiting severe adverse effects. There is an unmet clinical need for targeted drug delivery systems that transport chemotherapeutics selectively to tumor cells while minimizing off-target toxicity. G protein-coupled receptors (GPCRs) are the largest family of membrane receptors, and many are overexpressed in solid tumors, including ovarian cancer. This review summarizes the progress in engineered nanoparticle research for drug delivery for ovarian cancer and discusses the potential use of GPCRs as molecular entry points to deliver anti-cancer compounds into ovarian cancer cells. A newly emerging treatment paradigm could be the personalized design of nanomedicines on a case-by-case basis.

Cancer Tissue Classification Using Supervised Machine Learning Applied to MALDI Mass Spectrometry Imaging.

Matrix assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) can determine the spatial distribution of analytes such as protein distributions in a tissue section according to their mass-to-charge ratio. Here, we explored the clinical potential of machine learning (ML) applied to MALDI MSI data for cancer diagnostic classification using tissue microarrays (TMAs) on 302 colorectal (CRC) and 257 endometrial cancer (EC)) patients. ML based on deep neural networks discriminated colorectal tumour from normal tissue with an overall accuracy of 98% in balanced cross-validation (98.2% sensitivity and 98.6% specificity). Moreover, our machine learning approach predicted the presence of lymph node metastasis (LNM) for primary tumours of EC with an accuracy of 80% (90% sensitivity and 69% specificity). Our results demonstrate the capability of MALDI MSI for complementing classic histopathological examination for cancer diagnostic applications.

Strategies for the Development of pH-Responsive Synthetic Polypeptides and Polymer-Peptide Hybrids: Recent Advancements.

Synthetic polypeptides and polymer-peptide hybrid materials have been successfully implemented in an array of biomedical applications owing to their biocompatibility, biodegradability and ability to mimic natural proteins. In addition, these materials have the capacity to form complex supramolecular structures, facilitate specific biological interactions, and incorporate a diverse selection of functional groups that can be used as the basis for further synthetic modification. Like conventional synthetic polymers, polypeptide-based materials can be designed to respond to external stimuli (e.g., light and temperature) or changes in the environmental conditions (e.g., redox reactions and pH). In particular, pH-responsive polypeptide-based systems represent an interesting avenue for the preparation of novel drug delivery systems that can exploit physiological or pathological pH variations within the body, such as those that arise in the extracellular tumour microenvironment, intracellularly within endosomes/lysosomes, or during tissue inflammation. Here, we review the significant progress made in advancing pH-responsive polypeptides and polymer-peptide hybrid materials during the last five years, with a particular emphasis on the manipulation of ionisable functional groups, pH-labile linkages, pH-sensitive changes to secondary structure, and supramolecular interactions.

Altered N-linked glycosylation in endometrial cancer.

It is well established that cell surface glycans play a vital role in biological processes and their altered form can lead to carcinogenesis. Mass spectrometry-based techniques have become prominent for analysing N-linked glycans, for example using matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS). Additionally, MALDI MS can be used to spatially map N-linked glycans directly from cancer tissue using a technique termed MALDI MS imaging (MALDI MSI). This powerful technique combines mass spectrometry and histology to visualise the spatial distribution of N-linked glycans on a single tissue section. Here, we performed N-glycan MALDI MSI on six endometrial cancer (EC) formalin-fixed paraffin-embedded (FFPE) tissue sections and tissue microarrays (TMA) consisting of eight EC patients with lymph node metastasis (LNM) and twenty without LNM. By doing so, several putative N-linked glycan compositions were detected that could significantly distinguish normal from cancerous endometrium. Furthermore, a complex core-fucosylated N-linked glycan was detected that could discriminate a primary tumour with and without LNM. Structural identification of these putative N-linked glycans was performed using porous graphitized carbon liquid chromatography tandem mass spectrometry (PGC-LC-MS/MS). Overall, we observed higher abundance of oligomannose glycans in tumour compared to normal regions with AUC ranging from 0.85-0.99, and lower abundance of complex N-linked glycans with AUC ranges from 0.03-0.28. A comparison of N-linked glycans between primary tumours with and without LNM indicated a reduced abundance of a complex core-fucosylated N-glycan (Hex)2(HexNAc)2(Deoxyhexose)1+(Man)3(GlcNAc)2, in primary tumour with associated lymph node metastasis. In summary, N-linked glycan MALDI MSI can be used to differentiate cancerous endometrium from normal, and endometrial cancer with LNM from endometrial cancer without.

Novel technical developments in mass spectrometry imaging in 2020: A mini review.

The applicability of mass spectrometry imaging (MSI) has exponentially increased with the improvement of sample preparation, instrumentation (spatial resolution) and data analysis. The number of MSI publications listed in PubMed continues to grow with 378 published articles in 2020-2021. Initially, MSI was just sensitive enough to identify molecular features correlating with distinct tissue regions, similar to the resolution achieved by visual inspection after standard immunohistochemical staining. Although the spatial resolution was limited compared with other imaging modalities, the molecular intensity mapping added a new exciting capability. Over the past decade, significant improvements in every step of the workflow and most importantly in instrumentation were made, which now enables the molecular analysis at a cellular and even subcellular level. Here, we summarize the latest developments in MSI, with a focus on the latest approaches for tissue-based imaging described in 2020.

Ovarian Blood Sampling Identifies Junction Plakoglobin as a Novel Biomarker of Early Ovarian Cancer.

Ovarian cancer is the most lethal gynecologic malignancy. Early detection would improve survival, but an effective diagnostic test does not exist. Novel biomarkers for early ovarian cancer diagnosis are therefore warranted. We performed intraoperative blood sampling from ovarian veins of stage I epithelial ovarian carcinomas and analyzed the serum proteome. Junction plakoglobin (JUP) was found to be elevated in venous blood from ovaries with malignancies when compared to those with benign disease. Peripheral plasma JUP levels were validated by ELISA in a multicenter international patient cohort. JUP was significantly increased in FIGO serous stage IA+B (1.97-fold increase; p < 0.001; n = 20), serous stage I (2.09-fold increase; p < 0.0001; n = 40), serous stage II (1.81-fold increase, p < 0.001, n = 23) and serous stage III ovarian carcinomas (1.98-fold increase; p < 0.0001; n = 34) vs. normal controls (n = 109). JUP plasma levels were not increased in early stage breast cancer (p = 0.122; n = 12). In serous ovarian cancer patients, JUP had a sensitivity of 85% in stage IA+B and 60% in stage IA-C, with specificities of 76 and 94%, respectively. A logistic regression model of JUP and Cancer Antigen 125 (CA125) revealed a sensitivity of 70% for stage IA+B and 75% for stage IA-C serous carcinomas at 100% specificity. Our novel ovarian blood sampling - proteomics approach identified JUP as a promising new biomarker for epithelial ovarian cancer, which in combination with CA125 might fulfill the test criteria for ovarian cancer screening.

Uncovering Tumor-Stroma Inter-relationships Using MALDI Mass Spectrometry Imaging.

Tumorigenesis involves a complex interplay between genetically modified cancer cells and their adjacent normal tissue, the stroma. We used an established breast cancer mouse model to investigate this inter-relationship. Conditional activation of Rho-associated protein kinase (ROCK) in a model of mammary tumorigenesis enhances tumor growth and progression by educating the stroma and enhancing the production and remodeling of the extracellular matrix. We used peptide matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) to quantify the proteomic changes occurring within tumors and their stroma in their regular spatial context. Peptides were ranked according to their ability to discriminate between the two groups, using a receiver operating characteristic tool. Peptides were identified by liquid chromatography tandem mass spectrometry, and protein expression was validated by quantitative immunofluorescence using an independent set of tumor samples. We have identified and validated four key proteins upregulated in ROCK-activated mammary tumors relative to those expressing kinase-dead ROCK, namely, collagen I, α-SMA, Rab14, and tubulin-ß4. Rab14 and tubulin-ß4 are expressed within tumor cells, whereas collagen I is localized within the stroma. α-SMA is predominantly localized within the stroma but is also expressed at higher levels in the epithelia of ROCK-activated tumors. High expression of COL1A, the gene encoding the pro-α 1 chain of collagen, correlates with cancer progression in two human breast cancer genomic data sets, and high expression of COL1A and ACTA2 (the gene encoding α-SMA) are associated with a low survival probability (COLIA, p = 0.00013; ACTA2, p = 0.0076) in estrogen receptor-negative breast cancer patients. To investigate whether ROCK-activated tumor cells cause stromal cancer-associated fibroblasts (CAFs) to upregulate expression of collagen I and α-SMA, we treated CAFs with medium conditioned by primary mammary tumor cells in which ROCK had been activated. This led to abundant production of both proteins in CAFs, clearly highlighting the inter-relationship between tumor cells and CAFs and identifying CAFs as the potential source of high levels of collagen 1 and α-SMA and associated enhancement of tissue stiffness. Our research emphasizes the capacity of MALDI-MSI to quantitatively assess tumor-stroma inter-relationships and to identify potential prognostic factors for cancer progression in human patients, using sophisticated mouse cancer models.

Proteomic Analysis of Pre-Invasive Serous Lesions of the Endometrium and Fallopian Tube Reveals Their Metastatic Potential.

Serous endometrial cancer (SEC) and high grade serous ovarian cancer (HGSOC) are aggressive gynecological malignancies with high rates of metastasis and poor prognosis. Endometrial intraepithelial carcinoma (EIC), the precursor for SEC, and serous tubal intraepithelial carcinoma (STIC), believed to be the precursor lesion for HGSOC, can also be associated with intraabdominal spread. To provide insight into the etiology of these precancerous lesions and to explore the potential molecular mechanisms underlying their metastatic behavior, we performed a proteomic mass spectrometry analysis in a patient with synchronous EIC and STIC. Through histological and molecular identification of precancerous lesions followed by laser capture microdissection, we were able to identify over 450 proteins within the precancerous lesions and adjacent healthy tissue. The proteomic analysis of STIC and EIC showed remarkable overlap in the proteomic patterns, reflecting early neoplastic changes in proliferation, loss of polarity and attachment. Our proteomic analysis showed that both EIC and STIC, despite being regarded as premalignant lesions, have metastatic potential, which correlates with the common presentation of invasive serous gynecological malignancies at advanced stage.

Egg White as a Quality Control in Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI-MSI).

The strength of MALDI-MSI is to analyze and visualize spatial intensities of molecular features from an intact tissue. The distribution of the intensities can then be visualized within a single tissue section or compared in between sections, acquired consecutively. This method can be reliably used to reveal physiological structures and has the potential to identify molecular details, which correlate with biological outcomes. MALDI-MSI implementation in clinical laboratories requires the ability to ensure method quality and validation to meet diagnostic expectations. To be able to get consistent qualitative and quantitative results, standardized sample preparation and data acquisition are of highest priority. We have previously shown that the deposition of internal standards onto the tissue section during sample preparation can be used to improve the mass accuracy of monitored m/z features across the sample. Here, we present the use of external and internal controls for the quality check of sample preparation and data acquisition, which is particularly relevant when either many spectra are acquired during a single MALDI-MSI experiment or data from independent experiments are processed together. To monitor detector performance and sample preparation, we use egg white as an external control for peptide and N-glycan MALDI-MSI throughout the experiment. We have also identified endogenous peptides from cytoskeletal proteins, which can be reliably monitored in gynecological tissue samples. Lastly, we summarize our standard quality control workflow designed to produce reliable and comparable MALDI-MSI data from single sections and tissue microarrays (TMAs).

Matrix Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI MSI) for Monitoring of Drug Response in Primary Cancer Spheroids.

Malignant ascites is a fluid, which builds up in the abdomen and contains cancer cells in the form of single cells or multicellular clusters called spheroids. Malignant ascites has been observed in patients suffering from ovarian, cervical, gastric, colorectal, pancreatic, endometrial, or primary liver cancer. The spheroids are believed to play a major role in chemo resistance and metastasis of the cancer. To ease the discomfort of patients, malignant ascites (MA) is often drained from the abdomen using a procedure called paracentesis. MA retrieved via this minimal invasive procedure is a great source for cancer spheroids, which can be used for testing chemotherapeutic drugs and drug combinations. Herein, the existing workflow is adapted to make concurrent monitoring of drug accumulation, drug response, and drug metabolites feasible using primary spheroids or spheroids grown without a scaffolding matrix. To achieve this, those spheroids are embedded in matrigel, before fixing them with formalin. This makes it possible to process, store, and ship samples at room temperature. This new approach might be used to choose the best targeted therapy for each patient and thereby facilitate personalized medicine.

The Emerging Role of Cytoskeletal Proteins as Reliable Biomarkers.

Cytoskeletal proteins are essential building blocks of cells. More than 100 cytoskeletal and cytoskeleton-associated proteins are known and for some, their function and regulation are understood in great detail. Apart from cell shape and support, they facilitate many processes such as intracellular signaling and transport, and cancer related processes such as proliferation, migration, and invasion. During the last decade, comparative proteomic studies have identified cytoskeletal proteins as in vitro markers for tumor progression and metastasis. Here, these results are summarized and a number of unrelated studies are highlighted, identifying the same cytoskeletal proteins as potential biomarkers. These findings might indicate that the abundance of these potential markers of tumor progression is associated with the biological outcome and are independent of the cancer origin. This correlates well with recently published results from the Cancer Genome Atlas, indicating that cancers show remarkable similarities in their analyzed molecular information, independent of their organ of origin. It is postulated that the quantification of cytoskeletal proteins in healthy tissues, tumors, in adjacent tissues, and in stroma, is a great source of molecular information, which might not only be used to classify tumors, but more importantly to predict patients' outcome or even best treatment choices.