Mass Spectrometry-based Protein Profiling Research Articles

Global Protein Profiling in Processed Immunohistochemistry Tissue Sections.

Tissue sections, which are widely used in research and diagnostic laboratories and have already been examined by immunohistochemistry (IHC), may subsequently provide a resource for proteomic studies, even though only small amount of protein is available. Therefore, we established a workflow for tandem mass spectrometry-based protein profiling of IHC specimens and characterized defined brain area sections. We investigated the CA1 region of the hippocampus dissected from brain slices of adult C57BL/6J mice. The workflow contains detailed information on sample preparation from brain slices, including removal of antibodies and cover matrices, dissection of region(s) of interest, protein extraction and digestion, mass spectrometry measurement, and data analysis. The Gene Ontology (GO) knowledge base was used for further annotation. Literature searches and Gene Ontology annotation of the detected proteins verify the applicability of this method for global protein profiling using formalin-fixed and embedded material and previously used IHC slides.

Statistical and machine learning methods to study human CD4+ T cell proteome profiles

Mass spectrometry proteomics has become an important part of modern immunology, making major contributions to understanding protein expression levels, subcellular localizations, posttranslational modifications, and interactions in various immune cell populations. New developments in both experimental and computational techniques offer increasing opportunities for exploring the immune system and the molecular mechanisms involved in immune responses. Here, we focus on current computational approaches to infer relevant information from large mass spectrometry based protein profiling datasets, covering the different steps of the analysis from protein identification and quantification to further mining and modelling of the protein abundance data. Additionally, we provide a summary of the key proteome profiling studies on human CD4+ T cells and their different subtypes in health and disease.

Protein Profiling Identify Distinct Tumor-Tissue Protein Expression Pattern Specific for Relapsing Diffuse Large B-Cell Lymphoma

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease. Several genetic drivers have been suggested based on gene-expression and RNA sequencing. However, clinical trials based on these molecular subclassifications have failed to improve treatment results and standard of care in DLBCL is still R-CHOP (rituximab, cyclophosphamide, doxorubicin, prednisone) based therapy, which results in approximately an 70% 5-year overall survival rate. Nordic Lymphoma Group (NLG) has conducted two large phase II trials (NLG-LBC-04; NCT 01502982 and NLG-LBC-05; NCT 01325194) during the last decade with the aim of improving the treatment outcome for young (<65 years) high-risk patients with primary DLBCL. Both protocols were based on biweekly administered R-CHOP-14 with etoposide (R-CHOEP) and systemic central nervous system (CNS) prophylaxis. Various factors acting at different biological levels may influence pathology of the disease, and discrepancies between gene expression and the final combination of the functional proteins may be present due to, e.g., translational inhibition/activation and posttranslational modifications. Mass spectrometry-based protein profiling is a high throughput methodology that enables identification of the proteins in a given cell or tissue and the global protein expression can be compared between patients.The aim of our study was to search for prognostic markers and possible therapeutic targets at the protein level in a uniformly treated patient cohort from the two Nordic trials (n=64) with available tumor-tissue. Thus, in this study, we investigated the protein expression pattern in the pre-therapeutic formalin-fixed paraffin embedded tumor samples by nano liquid-chromatography coupled to a mass spectrometer (Orbitrap Fusion) through an EASY-Spray nano-electrospray ion source (nLC-MS/MS). We identified 4,622 proteins with at least two unique peptides across all samples. In the combined cohort, we were able to, based on differential protein expression of 190 proteins between patients (p<0.05) with treatment sensitive (n=53) and relapsing (n=11) lymphoma, identify three clusters with one of the clusters containing only patients with experienced relapsing disease. Interestingly, among other identified differentially expressed proteins, we emphasize the identification of voltage dependent anion channel 3 (VDAC3) and the GTPase RAC1. This pattern of protein expression suggests disturbance in reactive oxidative species (ROS) signaling and regulation of tumor cell proliferation between relapsing and therapy-responding patients. Assessment of these specific protein expression patterns in the three clusters may provide a useful parameter for prediction of relapsing disease in DLBCL patients but still awaits further validation in a separate patient cohort. DisclosuresHolte: Gilead: Membership on an entity's Board of Directors or advisory committees; Roche: Membership on an entity's Board of Directors or advisory committees; Nordic: Membership on an entity's Board of Directors or advisory committees; Nanovector: Membership on an entity's Board of Directors or advisory committees, Other: lectures honorarias; Novartis: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees. Jørgensen: Gilead/Kite: Consultancy; Novartis: Consultancy; Celgene/BMS: Consultancy; Roche: Consultancy.

Abstract 1939: Follicular Lymphoma-associated mutations in the V-ATPase assembly factor VMA21 activate autophagic flux

Abstract Introduction: Follicular lymphoma (FL) constitutes the second most common non-Hodgkin lymphoma in the Western world. FL carries a high incidence of gene mutations in various V-ATPase subunits and regulators (ATP6V1B2, ATP6AP1, and VMA21) accounting for a combined 25-30% of FL cases. We have previously demonstrated that an FL-associated mutation in the V-ATPase V1 subunit ATP6V1B2 induces autophagic flux, thus conferring a survival addiction on mutated FL B cells. Here, we report results from functional analysis of the common hotspot truncating mutations p.R93* in the V-ATPase assembly factor VMA21 in FL. Methods: We measured autophagic flux using a variety of complementary assays in recombinant cell lines expressing inducible VMA21 WT and MUT (p.R93*). Lysosome acidification was measured using pH-sensitive dyes linked to dextran and flow-cytometry. The subcellular localization of VAM21 was investigated using confocal microscopy. The VMA21 WT and MUT-associated proteome was analyzed using immunoprecipitation followed by quantitative mass spectrometry-based protein profiling (IP-MS). Results: The inducible expression of VMA21 p.R93* activated autophagic flux as measured through various assays, including: i) increased autolysosome numbers measured via electron microscopy, ii) elevated LC3-II and elevated free GFP in HEK293T and lymphoma cells expressing a GFP-LC3-RFP probe, iii) elevated autophagosomes and autolysosomes detected via confocal microscopy in HEK293T cells, which were ablated by ULK1 and PIK3C3/VPS34 inhibitors, iv) elevated autophagic flux in various yeast assays. The inducible expression of mutant VMA21 partially impaired lysosomal acidification, implicating inhibitory effects on the V-ATPase holoenzyme. Analysis of subcellular localization of WT and MUT VMA21 using lysosomal-IPs and confocal microscopy showed that VMA21 MUT mislocalized to lysosomes and did not shuttle back to the ER. Using quantitative IP-MS, we detected elevated amounts of V-ATPase components in the VMA21 MUT immunoprecipitates, indicating increased complex formation between MUT VMA21 and fully assembled V-ATPase. Studies are underway measuring V-ATPase activity in lysosomes in VMA21 WT and MUT cells and effects on the lysosomal metabolome. In addition, we are testing the effects of small molecule autophagy inhibitors on the survival of VMA21 MUT primary FL cells. Conclusion: Our data support the hypothesis that the FL-associated VMA21 p.R93* has altered subcellular trafficking. As a consequence, more MUT VMA21 associates with the V-ATPase holoenzyme resulting in partial impairment of V-ATPase activity. Similar to our previous findings on ATP6V1B2 mutations, the MUT VMA21 aberrantly activates autophagic flux possibly as compensation to impaired V-ATPase function. This study supports future investigations into therapeutic targeting of aberrantly activated autophagy in FL. Citation Format: Fangyang Wang, Ying Yang, Gabriel Boudagh, Eeva-Liisa Eskelinen, Daniel J. Klionsky, Sami N. Malek. Follicular Lymphoma-associated mutations in the V-ATPase assembly factor VMA21 activate autophagic flux [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1939.

Exosomes Derived from the Human Primary Colorectal Cancer Cell Line SW480 Orchestrate Fibroblast‐Led Cancer Invasion

In localized tumors, basement membrane (BM) prevents invasive outgrowth of tumor cells into surrounding tissues. When carcinomas become invasive, cancer cells either degrade BM or reprogram stromal fibroblasts to breach BM barrier and lead invasion of cancer cells into surrounding tissues in a process called fibroblast-led invasion. However, tumor-derived factors orchestrating fibroblast-led invasion remain poorly understood. Here it is shown that although early-stage primary colorectal adenocarcinoma (SW480) cells are themselves unable to invade Matrigel matrix, they secrete exosomes that reprogram normal fibroblasts to acquire de novo capacity to invade matrix and lead invasion of SW480 cells. Strikingly, cancer cells follow leading fibroblasts as collective epithelial-clusters, thereby circumventing need for epithelial to mesenchymal transition, a key event associated with invasion. Moreover, acquisition of pro-invasive phenotype by fibroblasts treated with SW480-derived exosomes relied on exosome-mediated MAPK pathway activation. Mass spectrometry-based protein profiling reveals that cancer exosomes upregulate fibroblasts proteins implicated in focal adhesion (ITGA2/A6/AV, ITGB1/B4/B5, EGFR, CRK), regulators of actin cytoskeleton (RAC1, ARF1, ARPC3, CYFIP1, NCKAP1, ICAM1, ERM complex), and signalling pathways (MAPK, Rap1, RAC1, Ras) important in pro-invasive remodeling of extracellular matrix. Blocking tumor exosome-mediated signaling to fibroblasts therefore represents an attractive therapeutic strategy in restraining tumors by perturbing stroma-driven invasive outgrowth.

DIA-SIFT: A Precursor and Product Ion Filter for Accurate Stable Isotope Data-Independent Acquisition Proteomics.

Quantitative mass spectrometry-based protein profiling is widely used to measure protein levels across different treatments or disease states, yet current mass spectrometry acquisition methods present distinct limitations. While data-independent acquisition (DIA) bypasses the stochastic nature of data-dependent acquisition (DDA), fragment spectra derived from DIA are often complex and challenging to deconvolve. In-line ion mobility separation (IMS) adds an additional dimension to increase peak capacity for more efficient product ion assignment. As a similar strategy to sequential window acquisition methods (SWATH), IMS-enabled DIA methods rival DDA methods for protein annotation. Here we evaluate IMS-DIA quantitative accuracy using stable isotope labeling by amino acids in cell culture (SILAC). Since SILAC analysis doubles the sample complexity, we find that IMS-DIA analysis is not sufficiently accurate for sensitive quantitation. However, SILAC precursor pairs share common retention and drift times, and both species cofragment to yield multiple quantifiable isotopic y-ion peak pairs. Since y-ion SILAC ratios are intrinsic for each quantified precursor, combined MS1 and y-ion ratio analysis significantly increases the total number of measurements. With increased sampling, we present DIA-SIFT ( SILAC Intrinsic Filtering Tool), a simple statistical algorithm to identify and eliminate poorly quantified MS1 and/or MS2 events. DIA-SIFT combines both MS1 and y-ion ratios, removes outliers, and provides more accurate and precise quantitation (<15% CV) without removing any proteins from the final analysis. Overall, pooled MS1 and MS2 quantitation increases sampling in IMS-DIA SILAC analyses for accurate and precise quantitation.

Application of a Serum Protein Signature for Pancreatic Cancer to Separate Cases from Controls in a Pancreatic Surveillance Cohort

BACKGROUND: Pancreatic cancer (PC) surveillance is currently offered to individuals with a genetic predisposition to PC, but routinely used radiological screening modalities are not entirely reliable in detecting early-stage PC or its precursor lesions. We recently identified a discriminating PC biomarker signature in a sporadic patient cohort. In this study, we investigated if protein profiling can accurately distinguish PC from non-PC in a pancreatic surveillance cohort of genetically predisposed individuals. METHODS: Serum samples of 66 individuals with a CDKN2A germline mutation who participated in the pancreatic surveillance program (5 cases, 61 controls) were obtained following a standardized protocol. After sample clean-up, peptide and protein profiles were obtained on an ultrahigh-resolution matrix-assisted laser desorption/ionization–Fourier transform ion cyclotron resonance mass spectrometry platform. A discriminant score for each sample was calculated with a previously designed prediction rule, and the median discriminant scores of cases and controls were compared. Individuals with precursor lesions of PC (n = 4) and individuals with a recent diagnosis of melanoma (n = 4) were also separately considered. RESULTS: Cases had a higher median discriminant score than controls (0.26 vs 0.016; P = .001). The only individual with pathologically confirmed precursor lesions of PC could also be clearly distinguished from controls, and having a (recent) medical history of melanoma did not influence the protein signatures. CONCLUSIONS: Peptide and protein signatures are able to accurately distinguish PC cases from controls in a pancreatic surveillance setting. Mass spectrometry–based protein profiling therefore seems to be a promising candidate for implementation in the pancreatic surveillance program as an additional screening modality.

Identification of short terminal motifs enriched by antibodies using peptide mass fingerprinting

Mass spectrometry-based protein profiling has become a key technology in biomedical research and biomarker discovery. Sample preparation strategies that reduce the complexity of tryptic digests by immunoaffinity substantially increase throughput and sensitivity in proteomic mass spectrometry. The scarce availability of peptide-specific capture antibodies limits these approaches. Recently antibodies directed against short terminal motifs were found to enrich subsets of peptides with identical terminal sequences. This approach holds the promise of a significant gain in efficiency. TXP (Triple X Proteomics) and context-independent motif specific/global proteome survey binders are variants of this concept. Principally the binding motifs of such antibodies have to be elucidated after generating these antibodies. This entails a substantial effort in the lab, as it requires synthetic peptide libraries and numerous mass spectrometry experiments. We present an algorithm for predicting the antibody-binding motif in a mass spectrum obtained from a tryptic digest of a common cell line after immunoprecipitation. The epitope prediction, based on peptide mass fingerprinting, reveals the most enriched terminal epitopes. The tool provides a P-value for each potential epitope, estimated by sampling random spectra from a peptide database. The second algorithm combines the predicted sequences to more complex binding motifs. A comparison with library screenings shows that the predictions made by the novel methods are reliable and reproducible indicators of the binding properties of an antibody.

Utilized mass spectrometry-based protein profiling system to identify potential biomarkers of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common malignant liver tumor. The purpose of this study is to characterize proteins secreted from the HepG2 cells, which may relate to cell differentiation and tumor metastasis. In the proteomic analysis, the secretome was identified by nano-high–performance liquid chromatography/electrospray ionization tandem mass spectrometry (nano-HPLC/ESIMS/MS) followed by peptide fragmentation pattern analysis. In this study, three proteins, p130Cas-associated protein (p130Cas/BCAR1), TAR DNA-binding protein 43 (TDP43/TARDBP) and translationally controlled tumor protein (TCTP/TPT1), were identified and confirmed by Western blotting, which showed significantly differential expression compared with the normal liver cells. Analyzing differential protein expressions in HepG2 cell by proteomic approaches suggests that p130Cas/BCAR1, TDP43/TARDBP and TCTP/TPT1 as key proteins and may serve as biomarkers for HCC.

Serum peptide/protein profiling by mass spectrometry provides diagnostic information independently of CA125 in women with an ovarian tumor

In the present study, the use of a robust and sensitive mass spectrometry based protein profiling analysis was tested as diagnostic tools for women with an ovarian tumor. The potential additional diagnostic value of serum protein profiles independent of the information provided by CA125 were also investigated. Protein profiles of 113 serum samples from women with an ovarian tumor (54 malign and 59 benign) were generated using MALDI-TOF MS. A total of 98 peaks with a significant difference (p< 0.01) in intensity between women with benign tumors/cysts and malignant ovarian tumors were identified. After average linkage clustering, a profile of 46 statistical significant mass peaks was identified to distinguish malignant tumors and benign tumors/cysts. In the subgroup of women with normal CA125 values (< or =35 U/mL) (62 patients) 36 of the 504 mass peaks showed significant (p< 0.05) differences in intensity between benign and malignant disease. After average linkage clustering, 25 statistical significant mass values were identified in this clinical difficult and important subgroup presenting with normal CA125 values. The current study demonstrates the potential of mass spectrometry based serum protein profiling as a diagnostic tool in discrimination between benign ovarian tumors/cysts and malignant ovarian tumors. Additionally, the method provided diagnostic information independent of CA125.

Mass Spectrometry-based Protein Profiling to Determine the Cause of Lysosomal Storage Diseases of Unknown Etiology

Diagnosis of lysosomal storage diseases (LSDs) can be problematic in atypical cases where clinical phenotype may overlap with other genetically distinct disorders. In addition, LSDs may result from mutations in genes not yet implicated in disease. Thus, there are individuals that are diagnosed with apparent LSD based upon clinical criteria where the gene defect remains elusive. The objective of this study was to determine whether comparative proteomics approaches could provide useful insights into such cases. Most LSDs arise from mutations in genes encoding lysosomal proteins that contain mannose 6-phosphate, a carbohydrate modification that acts as a signal for intracellular targeting to the lysosome. We purified mannose 6-phosphorylated proteins by affinity chromatography and estimated relative abundance of individual proteins in the mixture by spectral counting of peptides detected by tandem mass spectrometry. Our rationale was that proteins that are decreased or absent in patients compared with controls could represent candidates for the primary defect, directing biochemical or genetics studies. On a survey of brain autopsy specimens from 23 patients with either confirmed or possible lysosomal disease, this approach identified or validated the genetic basis for disease in eight cases. These results indicate that this protein expression approach is useful for identifying defects in cases of undiagnosed lysosomal disease, and we demonstrated that it can be used with more accessible patient samples, e.g. cultured cells. Furthermore this approach was instrumental in the identification or validation of mutations in two lysosomal proteins, CLN5 and sulfamidase, in the adult form of neuronal ceroid lipofuscinosis.

Identification of serum biomarkers for nasopharyngeal carcinoma by proteomic analysis

Early diagnosis of nasopharyngeal carcinoma (NPC) remains a challenge. Serum protein profiling is a promising approach for the classification of cancer versus noncancer samples. The objective of the current study was to assess the feasibility of mass spectrometry-based protein profiling and a classification tree algorithm for discriminating between patients with NPC and noncancer controls. Serum samples from patients with NPC and noncancer controls were analyzed by using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS). The study was divided into a preliminary training set and a blind test set: A preliminary training set and a classification tree of spectra derived from 55 patients with NPC and a group of 60 noncancer controls were used to develop a proteomic model that discriminated cancer from noncancer effectively. Then, the validity of the classification tree was challenged with a blind test set, which included another 25 patients with NPC and 28 noncancer controls. Four protein peaks at 4097 daltons (Da), 4180 Da, 5912 Da, and 8295 Da were chosen automatically as a biomarker pattern in the training set that discriminated cancer from noncancer with sensitivity of 94.5% and specificity of 96.7%. When the SELDI marker pattern was tested with the blinded test set, it yielded a sensitivity of 92%, a specificity of 92.9%, and an accuracy rate of 92.5%. The accuracy of 2 protein peaks (4581 Da and 7802 Da) was 80% for predicting stage I and II NPC and 86% for predicting stage III and IV NPC. The high sensitivity and specificity obtained by the serum protein profiling approach demonstrated that SELDI-TOF-MS combined with a tree analysis model both can facilitate discriminating between NPC and noncancer controls and can provide an innovative clinical diagnostic platform to improve the detection of NPC.

Detection of colorectal cancer using MALDI-TOF serum protein profiling

Serum protein profiling is a promising approach for classification of cancer versus non-cancer samples. The objective of our study was to assess the feasibility of mass spectrometry based protein profiling for the discrimination of colorectal cancer (CRC) patients from healthy individuals. In a randomized block design, pre-operative serum samples obtained from 66 colorectal cancer patients and 50 controls were used to generate MALDI-TOF protein profiles. After pre-processing of the spectra, linear discriminant analysis with double cross-validation was used to classify protein profiles. A total recognition rate (92.6%), sensitivity (95.2%) and specificity (90.0%) for the detection of CRC were shown. The area under the curve of the classifier was 97.3%, and demonstrated the high, significant separation power of the classifier. Double cross-validation shows that classification can be attributed to information in the protein profile. Although preliminary, the high sensitivity and specificity indicate the potential usefulness of serum protein profiles for the detection of colorectal cancer.