Fallopian tube lesions as potential precursors of early ovarian cancer: a comprehensive proteomic analysis.

Ovarian cancer is the leading cause of death from gynecologic cancer worldwide. High-grade serous carcinoma (HGSC) is the most common and deadliest subtype of ovarian cancer. While the origin of ovarian tumors is still debated, it has been suggested that HGSC originates from cells in the fallopian tube epithelium (FTE), specifically the epithelial cells in the region of the tubal-peritoneal junction. Three main lesions, p53 signatures, STILs, and STICs, have been defined based on the immunohistochemistry (IHC) pattern of p53 and Ki67 markers and the architectural alterations of the cells, using the Sectioning and Extensively Examining the Fimbriated End Protocol. In this study, we performed an in-depth proteomic analysis of these pre-neoplastic epithelial lesions guided by mass spectrometry imaging and IHC. We evaluated specific markers related to each preneoplastic lesion. The study identified specific lesion markers, such as CAVIN1, Emilin2, and FBLN5. We also used SpiderMass technology to perform a lipidomic analysis and identified the specific presence of specific lipids signature including dietary Fatty acids precursors in lesions. Our study provides new insights into the molecular mechanisms underlying the progression of ovarian cancer and confirms the fimbria origin of HGSC.

Spatial analysis of the glioblastoma proteome reveals specific molecular signatures and markers of survival.

Molecular heterogeneity is a key feature of glioblastoma that impedes patient stratification and leads to large discrepancies in mean patient survival. Here, we analyze a cohort of 96 glioblastoma patients with survival ranging from a few months to over 4 years. 46 tumors are analyzed by mass spectrometry-based spatially-resolved proteomics guided by mass spectrometry imaging. Integration of protein expression and clinical information highlights three molecular groups associated with immune, neurogenesis, and tumorigenesis signatures with high intra-tumoral heterogeneity. Furthermore, a set of proteins originating from reference and alternative ORFs is found to be statistically significant based on patient survival times. Among these proteins, a 5-protein signature is associated with survival. The expression of these 5 proteins is validated by immunofluorescence on an additional cohort of 50 patients. Overall, our work characterizes distinct molecular regions within glioblastoma tissues based on protein expression, which may help guide glioblastoma prognosis and improve current glioblastoma classification.

Toward High Spatially Resolved Proteomics Using Expansion Microscopy.

Expansion microscopy (EM) is an emerging approach for morphological examination of biological specimens at nanoscale resolution using conventional optical microscopy. To achieve physical separation of cell structures, tissues are embedded in a swellable polymer and expanded several fold in an isotropic manner. This work shows the development and optimization of physical tissue expansion as a new method for spatially resolved large-scale proteomics. Herein we established a novel method to enlarge the tissue section to be compatible with manual microdissection on regions of interest and MS-based proteomic analysis. A major issue in expansion microscopy is the loss of protein information during the mechanical homogenization phase due to the use of proteinase K. For isotropic expansion, different homogenization agents were investigated, both to maximize protein identification and to minimize protein diffusion. Best results were obtained with SDS for homogenization. Using our modified protocol, we were able to enlarge a tissue section more than 3-fold and identified up to 655 proteins from 1 mm in size after expansion, equivalent to 330 µm in their real size corresponding thus to an average of 260 cells. This approach can be performed easily without any expensive sampling instrument. We demonstrated the compatibility of sample preparation for expansion microscopy and proteomic study in a spatial context.

In-depth proteomics analysis of sentinel lymph nodes from individuals with endometrial cancer.

Endometrial cancer (EC) is one of the most common gynecological cancers worldwide. Sentinel lymph node (SLN) status could be a major prognostic factor in evaluation of EC, but several prospective studies need to be performed. Here we report an in-depth proteomics analysis showing significant variations in the SLN protein landscape in EC. We show that SLNs are correlated to each tumor grade, which strengthens evidence of SLN involvement in EC. A few proteins are overexpressed specifically at each EC tumor grade and in the corresponding SLN. These proteins, which are significantly variable in both locations, should be considered potential markers of overall survival. Five major proteins for EC and SLN (PRSS3, PTX3, ASS1, ALDH2, and ANXA1) were identified in large-scale proteomics and validated by immunohistochemistry. This study improves stratification and diagnosis of individuals with EC as a result of proteomics profiling of SLNs.

Protein Kinase C Activation Drives a Differentiation Program in an Oligodendroglial Precursor Model through the Modulation of Specific Biological Networks.

Protein kinase C (PKC) activation induces cellular reprogramming and differentiation in various cell models. Although many effectors of PKC physiological actions have been elucidated, the molecular mechanisms regulating oligodendrocyte differentiation after PKC activation are still unclear. Here, we applied a liquid chromatography-mass spectrometry (LC-MS/MS) approach to provide a comprehensive analysis of the proteome expression changes in the MO3.13 oligodendroglial cell line after PKC activation. Our findings suggest that multiple networks that communicate and coordinate with each other may finally determine the fate of MO3.13 cells, thus identifying a modular and functional biological structure. In this work, we provide a detailed description of these networks and their participating components and interactions. Such assembly allows perturbing each module, thus describing its physiological significance in the differentiation program. We applied this approach by targeting the Rho-associated protein kinase (ROCK) in PKC-activated cells. Overall, our findings provide a resource for elucidating the PKC-mediated network modules that contribute to a more robust knowledge of the molecular dynamics leading to this cell fate transition.

Cross-talk between YAP and RAR-RXR Drives Expression of Stemness Genes to Promote 5-FU Resistance and Self-Renewal in Colorectal Cancer Cells.

The mechanisms whereby the Hippo pathway effector YAP regulates cancer cell stemness, plasticity, and chemoresistance are not fully understood. We previously showed that in 5-fluorouracil (5-FU)-resistant colorectal cancer cells, the transcriptional coactivator YAP is differentially regulated at critical transitions connected with reversible quiescence/dormancy to promote metastasis. Here, we found that experimental YAP activation in 5-FU-sensitive and 5-FU-resistant HT29 colorectal cancer cells enhanced nuclear YAP localization and the transcript levels of the retinoic acid (RA) receptors RARα/γ and RAR target genes CYP26A1, ALDH1A3, and LGR5 through RA Response Elements (RARE). In these two cell models, constitutive YAP activation reinforced the expression of the stemness biomarkers and regulators ALDH1A3, LGR5, and OCT4. Conversely, YAP silencing, RAR/RXR inhibition by the pan-RAR antagonist BMS493, and vitamin A depletion downregulated stemness traits and self-renewal. Regarding the mechanisms engaged, proximity-dependent labeling, nuclear YAP pulldown coupled with mass spectrometry, and chromatin immunoprecipitation (ChIP)/re-ChIP experiments revealed: (i) the nuclear colocalization/interaction of YAP with RARγ and RXRs; and (ii) combined genomic co-occupancy of YAP, RARα/γ, and RXRα interactomes at proximal RAREs of LGR5 and ALDH1A3 promoters. Moreover, activation of the YAP/RAR-RXR cross-talk in colorectal cancer cells promoted RAR self-activation loops via vitamin A metabolism, RA, and active RAR ligands generated by ALDH1A3. Together, our data identify YAP as a bona fide RAR-RXR transcriptional coactivator that acts through RARE-activated stemness genes. IMPLICATIONS: Targeting the newly identified YAP/RAR-RXR cross-talk implicated in cancer cell stemness maintenance may lead to multitarget combination therapies for patients with colorectal cancer.

Cumulative learning enables convolutional neural network representations for small mass spectrometry data classification.

Rapid and accurate clinical diagnosis remains challenging. A component of diagnosis tool development is the design of effective classification models with Mass spectrometry (MS) data. Some Machine Learning approaches have been investigated but these models require time-consuming preprocessing steps to remove artifacts, making them unsuitable for rapid analysis. Convolutional Neural Networks (CNNs) have been found to perform well under such circumstances since they can learn representations from raw data. However, their effectiveness decreases when the number of available training samples is small, which is a common situation in medicine. In this work, we investigate transfer learning on 1D-CNNs, then we develop a cumulative learning method when transfer learning is not powerful enough. We propose to train the same model through several classification tasks over various small datasets to accumulate knowledge in the resulting representation. By using rat brain as the initial training dataset, a cumulative learning approach can have a classification accuracy exceeding 98% for 1D clinical MS-data. We show the use of cumulative learning using datasets generated in different biological contexts, on different organisms, and acquired by different instruments. Here we show a promising strategy for improving MS data classification accuracy when only small numbers of samples are available.

Mechanisms of innate events during skin reaction following intradermal injection of seasonal influenza vaccine.

The skin plays a crucial role in host defences against microbial attack and the innate cells must provide the immune system with sufficient information to organize these defences. This unique feature makes the skin a promising site for vaccine administration. Although cellular innate immune events during vaccination have been widely studied, initial events remain poorly understood. Our aim is to determine molecular biomarkers of skin innate reaction after intradermal (i.d.) immunization. Using an ex vivo human explant model from healthy donors, we investigated by NanoLC-MS/MS analysis and MALDI-MSI imaging, to detect innate molecular events (lipids, metabolites, proteins) few hours after i.d. administration of seasonal trivalent influenza vaccine (TIV). This multimodel approach allowed to identify early molecules differentially expressed in dermal and epidermal layers at 4 and 18 h after TIV immunization compared with control PBS. In the dermis, the most relevant network of proteins upregulated were related to cell-to-cell signalling and cell trafficking. The molecular signatures detected were associated with chemokines such as CXCL8, a chemoattractant of neutrophils. In the epidermis, the most relevant networks were associated with activation of antigen-presenting cells and related to CXCL10. Our study proposes a novel step-forward approach to identify biomarkers of skin innate reaction. SIGNIFICANCE: To our knowledge, there is no study analyzing innate molecular reaction to vaccines at the site of skin immunization. What is known on skin reaction is based on macroscopic (erythema, redness…), microscopic (epidermal and dermal tissues) and cellular events (inflammatory cell infiltrate). Therefore, we propose a multimodal approach to analyze molecular events at the site of vaccine injection on skin tissue. We identified early molecular networks involved biological functions such cell migration, cell-to-cell interaction and antigen presentation, validated by chemokine expression, in the epidermis and dermis, then could be used as early indicator of success in immunization.

ALK4/5-dependent TGF-ß signaling contributes to the crosstalk between neurons and microglia following axonal lesion.

Neuronal activity is closely influenced by glia, especially microglia which are the resident immune cells in the central nervous system (CNS). Microglia in medicinal leech are the only cells able to migrate to the injury site within the 24 hours post-lesion. The microglia-neuron interactions constitute an important mechanism as there is neither astrocyte nor oligodendrocyte in the leech CNS. Given that axonal sprouting is impaired when microglia recruitment is inhibited, the crosstalk between microglia and neurons plays a crucial role in neuroprotection. The present results show that neurons and microglia both use ALK4/5 (a type of TGF-ß receptor) signaling in order to maintain mutual exchanges in an adult brain following an axonal injury. Indeed, a TGF-ß family member (nGDF) is immediately released by injured axons contributing to the early recruitment of ALK4/5+ microglia to the lesion site. Surprisingly, within the following hours, nGDF from microglia activates ALK4/5+ neurons to maintain a later microglia accumulation in lesion. Taken together, the results demonstrate that ALK4/5 signaling is essential throughout the response to the lesion in the leech CNS and gives a new insight in the understanding of this pathway. This latter is an important signal contributing to a correct sequential mobilization over time of microglia recruitment leading to axon regeneration.

Paclitaxel Treatment and Proprotein Convertase 1/3 (PC1/3) Knockdown in Macrophages is a Promising Antiglioma Strategy as Revealed by Proteomics and Cytotoxicity Studies.

High grade gliomas are the most common brain tumors in adult. These tumors are characterized by a high infiltration in microglial cells and macrophages. The immunosuppressive tumor environment is known to orient immune cells toward a pro-tumoral and anti-inflammatory phenotype. Therefore, the current challenge for cancer therapy is to find a way to reorient macrophages toward an antitumoral phenotype. Previously, we demonstrated that macrophages secreted antitumoral factors when they were invalidated for the proprotein converstase 1/3 (PC1/3) and treated with LPS. However, achieving an activation of macrophages via LPS/TLR4/Myd88-dependent pathway appears yet unfeasible in cancer patients. On the contrary, the antitumor drug Paclitaxel is also known to activate the TLR4 MyD88-dependent signaling pathway and mimics LPS action. Therefore, we evaluated if PC1/3 knock-down (KD) macrophages could be activated by Paclitaxel and efficient against glioma. We report here that such a treatment of PC1/3 KD macrophages drove to the overexpression of proteins mainly involved in cytoskeleton rearrangement. In support of this finding, we found that these cells exhibited a Ca2+ increase after Paclitaxel treatment. This is indicative of a possible depolymerization of microtubules and may therefore reflect an activation of inflammatory pathways in macrophages. In such a way, we found that PC1/3 KD macrophages displayed a repression of the anti-inflammatory pathway STAT3 and secreted more pro-inflammatory cytokines. Extracellular vesicles isolated from these PC1/3 KD cells inhibited glioma growth. Finally, the supernatant collected from the coculture between glioma cells and PC1/3 KD macrophages contained more antitumoral factors. These findings unravel the potential value of a new therapeutic strategy combining Paclitaxel and PC1/3 inhibition to switch macrophages toward an antitumoral immunophenotype.

Spatially-Resolved Top-down Proteomics Bridged to MALDI MS Imaging Reveals the Molecular Physiome of Brain Regions.

Tissue spatially-resolved proteomics was performed on 3 brain regions, leading to the characterization of 123 reference proteins. Moreover, 8 alternative proteins from alternative open reading frames (AltORF) were identified. Some proteins display specific post-translational modification profiles or truncation linked to the brain regions and their functions. Systems biology analysis performed on the proteome identified in each region allowed to associate sub-networks with the functional physiology of each brain region. Back correlation of the proteins identified by spatially-resolved proteomics at a given tissue localization with the MALDI MS imaging data, was then performed. As an example, mapping of the distribution of the matrix metallopeptidase 3-cleaved C-terminal fragment of α-synuclein (aa 95-140) identified its specific distribution along the hippocampal dentate gyrus. Taken together, we established the molecular physiome of 3 rat brain regions through reference and hidden proteome characterization.

Combined Mass Spectrometry Imaging and Top-down Microproteomics Reveals Evidence of a Hidden Proteome in Ovarian Cancer.

BACKGROUND: Recently, it was demonstrated that proteins can be translated from alternative open reading frames (altORFs), increasing the size of the actual proteome. Top-down mass spectrometry-based proteomics allows the identification of intact proteins containing post-translational modifications (PTMs) as well as truncated forms translated from reference ORFs or altORFs. METHODS: Top-down tissue microproteomics was applied on benign, tumor and necrotic-fibrotic regions of serous ovarian cancer biopsies, identifying proteins exhibiting region-specific cellular localization and PTMs. The regions of interest (ROIs) were determined by MALDI mass spectrometry imaging and spatial segmentation. FINDINGS: Analysis with a customized protein sequence database containing reference and alternative proteins (altprots) identified 15 altprots, including alternative G protein nucleolar 1 (AltGNL1) found in the tumor, and translated from an altORF nested within the GNL1 canonical coding sequence. Co-expression of GNL1 and altGNL1 was validated by transfection in HEK293 and HeLa cells with an expression plasmid containing a GNL1-FLAG(V5) construct. Western blot and immunofluorescence experiments confirmed constitutive co-expression of altGNL1-V5 with GNL1-FLAG. CONCLUSIONS: Taken together, our approach provides means to evaluate protein changes in the case of serous ovarian cancer, allowing the detection of potential markers that have never been considered.

Progress and Potential of Imaging Mass Spectrometry Applied to Biomarker Discovery.

Mapping provides a direct means to assess the impact of protein biomarkers and puts into context their relevance in the type of cancer being examined. To this end, mass spectrometry imaging (MSI) was developed to provide the needed spatial information which is missing in traditional liquid-based mass spectrometric proteomics approaches. Aptly described as a "molecular histology" technique, MSI gives an additional dimension in characterizing tumor biopsies, allowing for mapping of hundreds of molecules in a single analysis. A decade of developments focused on improving and standardizing MSI so that the technique can be translated into the clinical setting. This review describes the progress made in addressing the technological development that allows to bridge local protein detection by MSI to its identification and to illustrate its potential in studying various aspects of cancer biomarker discovery.

Combined MALDI Mass Spectrometry Imaging and Parafilm-Assisted Microdissection-Based LC-MS/MS Workflows in the Study of the Brain.

Proteins and other biomolecules such as lipids are significant players in the central nervous system and are implicated in various neurological disorders. Their identification, quantification, and distribution are thus important not only in understanding the disease but also in developing treatments. A combined workflow allowing the localized microextraction of discrete regions identified by a matrix-assisted laser desorption/ionization mass spectrometry (MSI) imaging experiment for proteomics analysis by liquid chromatography/tandem mass spectrometry (LC MS/MS) is described in this chapter. MSI was initially used to map lipid distributions allowing for the identification of regions of interest (ROIs) that are then subjected to microextraction in a consecutive tissue section. Mounting of consecutive tissue on parafilm allows microdissection of the ROIs, where proteins can then be recovered for processing and LC MS/MS analysis. The PAM method provides a fast and cheap means to perform further downstream analysis after an MSI experiment.

Droplet-Based Liquid Extraction for Spatially-Resolved Microproteomics Analysis of Tissue Sections.

Obtaining information on protein content while keeping their localization on tissue or organ is of importance in different domains to understand pathophysiological processes. There is increasing interest in studying the microenvironment and heterogeneity of tumors, which currently is difficult with existing proteomics techniques. The advent of new techniques, like MALDI Mass Spectrometry Imaging, made a significant progress in the last decade but is characterized by a number of inherent drawbacks. One of these is the limited identification of proteins. New alternative approaches such as spatially-resolved liquid microextraction have recently been proposed to overcome this limitation. In this chapter, we describe strategies using liquid microjunction to perform extraction of previously digested peptides or of intact proteins from tissue section in a localized manner.

Integrated mass spectrometry imaging and omics workflows on the same tissue section using grid-aided, parafilm-assisted microdissection.

BACKGROUND: In spite of the number of applications describing the use of MALDI MSI, one of its major drawbacks is the limited capability of identifying multiple compound classes directly on the same tissue section. METHODS: We demonstrate the use of grid-aided, parafilm-assisted microdissection to perform MALDI MS imaging and shotgun proteomics and metabolomics in a combined workflow and using only a single tissue section. The grid is generated by microspotting acid dye 25 using a piezoelectric microspotter, and this grid was used as a guide to locate regions of interest and as an aid during manual microdissection. Subjecting the dissected pieces to the modified Folch method allows to separate the metabolites from proteins. The proteins can then be subjected to digestion under controlled conditions to improve protein identification yields. RESULTS: The proof of concept experiment on rat brain generated 162 and 140 metabolite assignments from three ROIs (cerebellum, hippocampus and midbrain/hypothalamus) in positive and negative modes, respectively, and 890, 1303 and 1059 unique proteins. Integrated metabolite and protein overrepresentation analysis identified pathways associated with the biological functions of each ROI, most of which were not identified when looking at the protein and metabolite lists individually. CONCLUSIONS: This combined MALDI MS imaging and multi-omics approach further extends the amount of information that can be generated from single tissue sections. GENERAL SIGNIFICANCE: To the best of our knowledge, this is the first report combining both imaging and multi-omics analyses in the same workflow and on the same tissue section.

NanoLC-MS coupling of liquid microjunction microextraction for on-tissue proteomic analysis.

Mass spectrometry (MS)-based microproteomics on localized regions of tissue sections was achieved by direct coupling of liquid microjunction microextraction with a nanoscale liquid chromatography-tandem MS, resulting in the identification of >500 protein groups from a region as small as 250µm in diameter representing only a few hundred of cells. The method was applied on the examination of benign and tumor regions initially defined by imaging mass spectrometry (IMS) analysis of a consecutive high grade serous ovarian tumor tissue section. Results identified the higher abundance of eukaryotic translation initiation factors eIF4A, its isoform eIF4A2, and eIF5A and its isoform eIF5A2, and lower abundance of actin-binding proteins OBSCN, TAGLN and CNN3 on tumor regions, concomitant with previous findings. This demonstrates the use of the method for downstream characterization of distinct regions identified by IMS. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.

Evaluation of non-supervised MALDI mass spectrometry imaging combined with microproteomics for glioma grade III classification.

An integrated diagnosis using molecular features is recommended in the 2016 World Health Organization (WHO) classification. Our aim was to explore non-targeted molecular classification using MALDI mass spectrometry imaging (MALDI MSI) associated to microproteomics in order to classify anaplastic glioma by integration of clinical data. We used fresh-frozen tissue sections to perform MALDI MSI of proteins based on their digestion peptides after in-situ trypsin digestion of the tissue sections and matrix deposition by micro-spraying. The generated 70µm spatial resolution image datasets were further processed by individual or global segmentation in order to cluster the tissues according to their molecular protein signature. The clustering gives 3 main distinct groups. Within the tissues the ROIs (regions of interest) defined by these groups were used for microproteomics by micro-extraction of the tryptic peptides after on-tissue enzymatic digestion. More than 2500 proteins including 22 alternative proteins (AltProt) are identified by the Shotgun microproteomics. Statistical analysis on the basis of the label free quantification of the proteins shows a similar classification to the MALDI MSI segmentation into 3 groups. Functional analysis performed on each group reveals sub-networks related to neoplasia for group 1, glioma with inflammation for group 2 and neurogenesis for group 3. This demonstrates the interest on these new non-targeted large molecular data combining both MALDI MSI and microproteomics data, for tumor classification. This analysis provides new insights into grade III glioma organization. This specific information could allow a more accurate classification of the biopsies according to the prognosis and the identification of potential new targeted therapeutic options. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.

Proteomic Analysis of the Spatio-temporal Based Molecular Kinetics of Acute Spinal Cord Injury Identifies a Time- and Segment-specific Window for Effective Tissue Repair.

Spinal cord injury (SCI) represents a major debilitating health issue with a direct socioeconomic burden on the public and private sectors worldwide. Although several studies have been conducted to identify the molecular progression of injury sequel due from the lesion site, still the exact underlying mechanisms and pathways of injury development have not been fully elucidated. In this work, based on OMICs, 3D matrix-assisted laser desorption ionization (MALDI) imaging, cytokines arrays, confocal imaging we established for the first time that molecular and cellular processes occurring after SCI are altered between the lesion proximity, i.e. rostral and caudal segments nearby the lesion (R1-C1) whereas segments distant from R1-C1, i.e. R2-C2 and R3-C3 levels coexpressed factors implicated in neurogenesis. Delay in T regulators recruitment between R1 and C1 favor discrepancies between the two segments. This is also reinforced by presence of neurites outgrowth inhibitors in C1, absent in R1. Moreover, the presence of immunoglobulins (IgGs) in neurons at the lesion site at 3 days, validated by mass spectrometry, may present additional factor that contributes to limited regeneration. Treatment in vivo with anti-CD20 one hour after SCI did not improve locomotor function and decrease IgG expression. These results open the door of a novel view of the SCI treatment by considering the C1 as the therapeutic target.

In vivo Real-Time Mass Spectrometry for Guided Surgery Application.

Here we describe a new instrument (SpiderMass) designed for in vivo and real-time analysis. In this instrument ion production is performed remotely from the MS instrument and the generated ions are transported in real-time to the MS analyzer. Ion production is promoted by Resonant Infrared Laser Ablation (RIR-LA) based on the highly effective excitation of O-H bonds in water molecules naturally present in most biological samples. The retrieved molecular patterns are specific to the cell phenotypes and benign versus cancer regions of patient biopsies can be easily differentiated. We also demonstrate by analysis of human skin that SpiderMass can be used under in vivo conditions with minimal damage and pain. Furthermore SpiderMass can also be used for real-time drug metabolism and pharmacokinetic (DMPK) analysis or food safety topics. SpiderMass is thus the first MS based system designed for in vivo real-time analysis under minimally invasive conditions.