Quantification of SAA1 and SAA2 in lung cancer plasma using the isotype-specific PRM assays

Gene expression profiling and the isocitrate dehydrogenase mutational landscape of temozolomide‑resistant glioblastoma

Glioblastoma multiforme (GBM) is an aggressive brain cancer that occurs more frequently than other brain tumors. The present study aimed to reveal a novel mechanism of temozolomide resistance in GBM using bioinformatics and wet lab analyses, including meta-Z analysis, Kaplan-Meier survival analysis, protein-protein interaction (PPI) network establishment, cluster analysis of co-expressed gene networks, and hierarchical clustering of upregulated and downregulated genes. Next-generation sequencing and quantitative PCR analyses revealed downregulated [tyrosine kinase with immunoglobulin and epidermal growth factor homology domains 1 (TIE1), calcium voltage-gated channel auxiliary subunit α2Δ1 (CACNA2D1), calpain 6 (CAPN6) and a disintegrin and metalloproteinase with thrombospondin motifs 6 (ADAMTS6)] and upregulated [serum amyloid (SA)A1, SAA2, growth differentiation factor 15 (GDF15) and ubiquitin specific peptidase 26 (USP26)] genes. Different statistical models were developed for these genes using the Z-score for P-value conversion, and Kaplan-Meier plots were constructed using several patient cohorts with brain tumors. The highest number of nodes was observed in the PPI network was for ADAMTS6 and TIE1. The PPI network model for all genes contained 35 nodes and 241 edges. Immunohistochemical staining was performed using isocitrate dehydrogenase (IDH)-wild-type or IDH-mutant GBM samples from patients and a significant upregulation of TIE1 (P<0.001) and CAPN6 (P<0.05) protein expression was demonstrated in IDH-mutant GBM in comparison with IDH-wild-type GBM. Structural analysis revealed an IDH-mutant model demonstrating the mutant residues (R132, R140 and R172). The findings of the present study will help the future development of novel biomarkers and therapeutics for brain tumors.

Comprehensive investigation of malignant epithelial cell-related genes in clear cell renal cell carcinoma: development of a prognostic signature and exploration of tumor microenvironment interactions

Clear cell renal cell carcinoma (ccRCC) is a prevalent malignancy with complex heterogeneity within epithelial cells, which plays a crucial role in tumor progression and immune regulation. Yet, the clinical importance of the malignant epithelial cell-related genes (MECRGs) in ccRCC remains insufficiently understood. This research aims to undertake a comprehensive investigation into the functions and clinical relevance of malignant epithelial cell-related genes in ccRCC, providing valuable understanding of the molecular mechanisms and offering potential targets for treatment strategies. Using data from single-cell sequencing, we successfully identified 219 MECRGs and established a prognostic model MECRGS (MECRGs' signature) by synergistically analyzing 101 machine-learning models using 10 different algorithms. Remarkably, the MECRGS demonstrated superior predictive performance compared to traditional clinical features and 92 previously published signatures across six cohorts, showcasing its independence and accuracy. Upon stratifying patients into high- and low-MECRGS subgroups using the specified cut-off threshold, we noted that patients with elevated MECRGS scores displayed characteristics of an immune suppressive tumor microenvironment (TME) and showed worse outcomes after immunotherapy. Additionally, we discovered a distinct ccRCC tumor cell subtype characterized by the high expressions of PLOD2 (procollagen-lysine,2-oxoglutarate 5-dioxygenase 2) and SAA1 (Serum Amyloid A1), which we further validated in the Renji tissue microarray (TMA) cohort. Lastly, 'Cellchat' revealed potential crosstalk patterns between these cells and other cell types, indicating their potential role in recruiting CD163 + macrophages and regulatory T cells (Tregs), thereby establishing an immunosuppressive TME. PLOD2 + SAA1 + cancer cells with intricate crosstalk patterns indeed show promise for potential therapeutic interventions.

Quantification of putative ovarian cancer serum protein biomarkers using a multiplexed targeted mass spectrometry assay

BACKGROUND

Ovarian cancer is the most lethal gynecologic malignancy in women, and high-grade serous ovarian cancer (HGSOC) is the most common subtype. Currently, no clinical test has been approved by the FDA to screen the general population for ovarian cancer. This underscores the critical need for the development of a robust methodology combined with novel technology to detect diagnostic biomarkers for HGSOC in the sera of women. Targeted mass spectrometry (MS) can be used to identify and quantify specific peptides/proteins in complex biological samples with high accuracy, sensitivity, and reproducibility. In this study, we sought to develop and conduct analytical validation of a multiplexed Tier 2 targeted MS parallel reaction monitoring (PRM) assay for the relative quantification of 23 putative ovarian cancer protein biomarkers in sera.

METHODS

To develop a PRM method for our target peptides in sera, we followed nationally recognized consensus guidelines for validating fit-for-purpose Tier 2 targeted MS assays. The endogenous target peptide concentrations were calculated using the calibration curves in serum for each target peptide. Receiver operating characteristic (ROC) curves were analyzed to evaluate the diagnostic performance of the biomarker candidates.

RESULTS

We describe an effort to develop and analytically validate a multiplexed Tier 2 targeted PRM MS assay to quantify candidate ovarian cancer protein biomarkers in sera. Among the 64 peptides corresponding to 23 proteins in our PRM assay, 24 peptides corresponding to 16 proteins passed the assay validation acceptability criteria. A total of 6 of these peptides from insulin-like growth factor-binding protein 2 (IBP2), sex hormone-binding globulin (SHBG), and TIMP metalloproteinase inhibitor 1 (TIMP1) were quantified in sera from a cohort of 69 patients with early-stage HGSOC, late-stage HGSOC, benign ovarian conditions, and healthy (non-cancer) controls. Confirming the results from previously published studies using orthogonal analytical approaches, IBP2 was identified as a diagnostic biomarker candidate based on its significantly increased abundance in the late-stage HGSOC patient sera compared to the healthy controls and patients with benign ovarian conditions.

CONCLUSIONS

A multiplexed targeted PRM MS assay was applied to detect candidate diagnostic biomarkers in HGSOC sera. To evaluate the clinical utility of the IBP2 PRM assay for HGSOC detection, further studies need to be performed using a larger patient cohort.

Targeted protein quantitation in human body fluids by mass spectrometry

Human body fluids (biofluids) contain various proteins, some of which reflect individuals' physiological conditions or predict diseases. Therefore, the analysis of biofluids can provide substantial information on novel biomarkers for clinical diagnosis and prognosis. In the past decades, mass spectrometry (MS)-based technologies have been developed as proteomic strategies not only for the identification of protein biomarkers but also for biomarker verification/validation in body fluids for clinical applications. The main advantage of targeted MS-based methodologies is the accurate and specific simultaneous quantitation of multiple biomarkers with high sensitivity. Here, we review MS-based methodologies that are currently used for the targeted quantitation of protein components in human body fluids, especially in plasma, urine, cerebrospinal fluid, and saliva. In addition, the currently used MS-based methodologies are summarized with a specific focus on applicable clinical sample types, MS configurations, and acquisition modes.

Delineating the glioblastoma stemness by genes involved in cytoskeletal rearrangements and metabolic alterations

Literature data on glioblastoma ongoingly underline the link between metabolism and cancer stemness, the latter is one responsible for potentiating the resistance to treatment, inter alia due to increased invasiveness. In recent years, glioblastoma stemness research has bashfully introduced a key aspect of cytoskeletal rearrangements, whereas the impact of the cytoskeleton on invasiveness is well known. Although non-stem glioblastoma cells are less invasive than glioblastoma stem cells (GSCs), these cells also acquire stemness with greater ease if characterized as invasive cells and not tumor core cells. This suggests that glioblastoma stemness should be further investigated for any phenomena related to the cytoskeleton and metabolism, as they may provide new invasion-related insights. Previously, we proved that interplay between metabolism and cytoskeleton existed in glioblastoma. Despite searching for cytoskeleton-related processes in which the investigated genes might have been involved, not only did we stumble across the relation to metabolism but also reported genes that were found to be implicated in stemness. Thus, dedicated research on these genes in GSCs seems justifiable and might reveal novel directions and/or biomarkers that could be utilized in the future. Herein, we review the previously identified cytoskeleton/metabolism-related genes through the prism of glioblastoma stemness.

Quantification of 782 Plasma Peptides by Multiplexed Targeted Proteomics

Blood analysis is one of the foundations of clinical diagnostics. In recent years, the analysis of proteins in blood samples by mass spectrometry has taken a jump forward in terms of sensitivity and the number of identified proteins. The recent development of parallel reaction monitoring with parallel accumulation and serial fragmentation (prm-PASEF) combines ion mobility as an additional separation dimension. This increases the proteome coverage while allowing the use of shorter chromatographic gradients. To demonstrate the method's full potential, we used an isotope-labeled synthetic peptide mix of 782 peptides, derived from 579 plasma proteins, spiked into blood plasma samples with a prm-PASEF measurement allowing the quantification of 565 plasma proteins by targeted proteomics. As a less time-consuming alternative to the prm-PASEF method, we describe guided data independent acquisition (dia)-PASEF (g-dia-PASEF) and compare its application to prm-PASEF for measuring blood plasma. To demonstrate both methods' performance in clinical samples, 20 patient plasma samples from a colorectal cancer (CRC) cohort were analyzed. The analysis identified 14 differentially regulated proteins between the CRC patient and control individual plasma samples. This shows the technique's potential for the rapid and unbiased screening of blood proteins, abolishing the need for the preselection of potential biomarker proteins.

Plasma Proteomics Enable Differentiation of Lung Adenocarcinoma from Chronic Obstructive Pulmonary Disease (COPD)

Chronic obstructive pulmonary disease (COPD) is a major risk factor for the development of lung adenocarcinoma (AC). AC often develops on underlying COPD; thus, the differentiation of both entities by biomarker is challenging. Although survival of AC patients strongly depends on early diagnosis, a biomarker panel for AC detection and differentiation from COPD is still missing. Plasma samples from 176 patients with AC with or without underlying COPD, COPD patients, and hospital controls were analyzed using mass-spectrometry-based proteomics. We performed univariate statistics and additionally evaluated machine learning algorithms regarding the differentiation of AC vs. COPD and AC with COPD vs. COPD. Univariate statistics revealed significantly regulated proteins that were significantly regulated between the patient groups. Furthermore, random forest classification yielded the best performance for differentiation of AC vs. COPD (area under the curve (AUC) 0.935) and AC with COPD vs. COPD (AUC 0.916). The most influential proteins were identified by permutation feature importance and compared to those identified by univariate testing. We demonstrate the great potential of machine learning for differentiation of highly similar disease entities and present a panel of biomarker candidates that should be considered for the development of a future biomarker panel.

Urine inter‐alpha‐trypsin inhibitor family‐related proteins may serve as biomarkers for disease activity of lupus

Background

Systemic lupus erythematosus (SLE) is a chronic inflammatory disease involving multiple tissues. Inter‐Alpha‐Trypsin Inhibitor (ITI) family proteins have a role in maintaining tissue homeostasis, but their possible clinical significance in the SLE patients has not been reported. The aim of this study was to analyze and verify the expression of ITI‐related proteins in the urine of SLE patients, further explore the features of these proteins in disease activity.

Methods

Based on label‐free proteomics technology and bioinformatics technology, we analyzed the expression of ITI family‐related proteins in the urine of lupus. Subsequently, Western‐blot and targeted proteomics were used to qualitatively and quantitatively verify the expression of these proteins, respectively.

Results

A total of seven ITI family‐related proteins were screened and identified; and six of these proteins were differentially expressed in the urine of SLE patients. Further quantitative analysis showed that the expressions of ITIH2, ECM1, and ITIH5 in urine between active SLE group and stable SLE group were consistent with the preliminary screening results. The expression of ITIH2 and ECM1 in the renal damage group were also consistent with the screening results. Moreover, ITIH2 and ECM1 have a good correlation with disease activity and have a certain correlation with renal damage.

Conclusions

In this exploratory study, we evaluated the expression of ITI family‐related proteins in the urine of SLE and found that urine ITIH2 and ECM1 were closely related to SLE activity, especially kidney damage, providing an experimental basis for further exploration of the potential roles in monitoring lupus and lupus nephritis activity.

Association between serum amyloid A and rheumatoid arthritis: A systematic review and meta-analysis

BACKGROUNDS

Consistent correlation of serum amyloid A (SAA) to rheumatoid arthritis (RA) is not completely established. The present study is to systematically summarize their relationship.

METHODS

Publications up to may 2021 were examined using key terms in the PubMed, Cochrane Library, Embase and China national knowledge infrastructure (CNKI) databases.

RESULTS

The total 33 studies, involving in 3524 RA cases and 3537 normal participants, were included. The pooled result indicated that the SAA level in the RA group was markedly higher than that in the control group [standardized mean difference (SMD) = 0.80, 95% CI (0.51, 1.08)]. By stratified analyses, the concentration of SAA was found to be gradually increased with the aggravation of RA. Additionally, the meta-analysis of correlation demonstrated that SAA levels were positively associated with the levels of disease activity score 28 (DAS28) [r = 0.55, 95% CI (0.15, 0.94)], erythrocyte sedimentation rate (ESR) [r = 0.65, 95% CI (0.53, 0.76)], C-reactive protein (CRP) [r = 0.92, 95% CI (0.57, 1.57)], rheumatoid factor (RF) [r = 0.24, 95% CI (0.09, 0.39)], interleukin 4 (IL-4) [r = 0.54, 95% CI (0.30, 0.78)], interleukin 6 (IL-6) [r = 0.46, 95% CI (0.27, 0.65)], interleukin 10 (IL-10) [r = 0.53, 95% CI (0.29, 0.77)], interleukin 17 (IL-17) [r = 0.52, 95% CI (0.27, 0.77)], and anti-cyclic citrullinated peptide antibody (A-CCP) [r = 0.32, 95% CI (0.15, 0.50)], but inversely linked with the levels of hemoglobin [r=-0.51, 95% CI (-0.84, -0.18)]. Furthermore, the allele of SAA 1.3 was actively related with increased risks of RA [OR=1.30, 95% CI (1.02, 1.65)] and of RA with amyloidosis [OR=2.06, 95% CI (1.63, 2.60)]. Besides, the genotype of SAA 1.3/1.3 was positively connected with the risks of RA [OR=1.56, 95% CI (1.00, 2.43)] and of RA with amyloidosis [OR=4.47, 95% CI (2.70, 7.41)].

CONCLUSIONS

High levels of SAA might be associated with elevated risk of RA, and the concentration of SAA might be gradually increased with the aggravation of RA. Moreover, high levels of SAA might play a vital role in RA by enhancing the levels of DAS28, ESR, CRP, RF, IL-4, IL-6, IL-10, IL-17 and A-CCP, or by attenuating hemoglobin levels. More importantly, the allele of SAA 1.3 and genotype of SAA 1.3/1.3 might be the risk factor of RA and of RA with amyloidosis.

Fluorescent paper strip immunoassay with carbon nanodots@silica for determination of human serum amyloid A1

A fluorescent paper strip immunoassay in conjunction with carbon nanodots@silica (CND@SiO₂) as a label was developed for the quantitative measurements of human serum amyloid A1 (hSAA1) in serum at clinically significant concentrations for lung cancer diagnosis. Monodispersed CND@SiO₂ was prepared by cohydrolysis between silane-crosslinked carbon nanodots and silica precursors via the Ströber method and further attached covalently to anti-hSAA1 (14F8) monoclonal antibody [anti-hSAA1(14F8)] specific to the hSAA1 target. The hSAA1 concentrations were then determined by quantifying the blue fluorescence intensity upon 365 nm excitation of the captured hSAA1 with anti-hSAA1(14F8)-CND@SiO₂ conjugates in the test line on a paper strip where anti-hSAA1 (10G1) monoclonal antibody was physisorbed. The developed fluorescent paper strip with CND@SiO₂ can detect hSAA1 at concentrations ranging from 0.1 to 5 nM (R² = 0.995), with a limit of detection of  0.258 nM in 10 mM phosphate buffer pH 7.4 containing human serum albumin. The performance of  recovery (90.98-109.17%) and repeatability (coefficients of variation < 8.46%) obtained was also acceptable for quantitative determinations. The platform was employed for direct determination of hSAA1 concentrations in undiluted serum samples from lung cancer patients (relative standard deviation (RSD) < 7.46%) and healthy humans (RSD < 3.96%). The results were compared with those obtained using a commercially available enzyme-linked immunosorbent assay alongside liquid chromatography with tandem mass spectrometry measurements.

A Cross-Sectional and Longitudinal Study to Define Alarmins and A-SAA Variants as Companion Markers in Early Rheumatoid Arthritis

Nowadays, in the study of rheumatoid arthritis (RA), more and more interest is directed towards an earlier effective therapeutic intervention and the determination of companion markers for predicting response to therapy with the goal to prevent progressive joint damage, deformities, and functional disability. With the present work, we aimed at quantifying in a cohort of early RA (ERA) patients naïve to DMARD therapy, proteins whose increase was previously found associated with RA: serum amyloid A (A-SAA) and alarmins. Five A-SAA variants (SAA1α, SAA1β, SAA1γ, SAA2α, and SAA2β) but also S100A8 and S100A9 proteins were simultaneously quantified in plasma applying a method based on single targeted bottom-up proteomics LC-MS/MS. First, we compared their expression between ERA (n = 100) and healthy subjects (n = 100), then we focused on their trend by monitoring ERA patients naïve to DMARD treatment, 1 year after starting therapy. Only SAA1α and SAA2α levels were increased in ERA patients, and SAA2α appears to mostly mediate the pathological role of A-SAA. Levels of these variants, together with SAA1β, only decreased under biologic DMARD treatment but not under methotrexate monotherapy. This study highlights the importance to better understand the modulation of expression of these variants in ERA in order to subsequently better characterize their biological function. On the other hand, alarmin expression increased in ERA compared to controls but remained elevated after 12 months of methotrexate or biologic treatment. The work overcomes the concept of considering these proteins as biomarkers for diagnosis, demonstrating that SAA1α, SAA1β, and SAA2α variants but also S100A8 and S100A9 do not respond to all early treatment in ERA and should be rather considered as companion markers useful to improve the follow-up of treatment response and remission state. Moreover, it suggests that earlier use of biologics in addition to methotrexate may be worth considering.

PLEK2, RRM2, GCSH: A Novel WWOX-Dependent Biomarker Triad of Glioblastoma at the Crossroads of Cytoskeleton Reorganization and Metabolism Alterations

Glioblastoma is one of the deadliest human cancers. Its malignancy depends on cytoskeleton reorganization, which is related to, e.g., epithelial-to-mesenchymal transition and metastasis. The malignant phenotype of glioblastoma is also affected by the WWOX gene, which is lost in nearly a quarter of gliomas. Although the role of WWOX in the cytoskeleton rearrangement has been found in neural progenitor cells, its function as a modulator of cytoskeleton in gliomas was not investigated. Therefore, this study aimed to investigate the role of WWOX and its collaborators in cytoskeleton dynamics of glioblastoma. Methodology on RNA-seq data integrated the use of databases, bioinformatics tools, web-based platforms, and machine learning algorithm, and the obtained results were validated through microarray data. PLEK2, RRM2, and GCSH were the most relevant WWOX-dependent genes that could serve as novel biomarkers. Other genes important in the context of cytoskeleton (BMP4, CCL11, CUX2, DUSP7, FAM92B, GRIN2B, HOXA1, HOXA10, KIF20A, NF2, SPOCK1, TTR, UHRF1, and WT1), metabolism (MTHFD2), or correlation with WWOX (COL3A1, KIF20A, RNF141, and RXRG) were also discovered. For the first time, we propose that changes in WWOX expression dictate a myriad of alterations that affect both glioblastoma cytoskeleton and metabolism, rendering new therapeutic possibilities.

Quantitative Mass Spectrometry-Based Proteomics for Biomarker Development in Ovarian Cancer

Ovarian cancer is the most lethal gynecologic malignancy among women. Approximately 70–80% of patients with advanced ovarian cancer experience relapse within five years and develop platinum-resistance. The short life expectancy of patients with platinum-resistant or platinum-refractory disease underscores the need to develop new and more effective treatment strategies. Early detection is a critical step in mitigating the risk of disease progression from early to an advanced stage disease, and protein biomarkers have an integral role in this process. The best biological diagnostic tool for ovarian cancer will likely be a combination of biomarkers. Targeted proteomics methods, including mass spectrometry-based approaches, have emerged as robust methods that can address the chasm between initial biomarker discovery and the successful verification and validation of these biomarkers enabling their clinical translation due to the robust sensitivity, specificity, and reproducibility of these versatile methods. In this review, we provide background information on the fundamental principles of biomarkers and the need for improved treatment strategies in ovarian cancer. We also provide insight into the ways in which mass spectrometry-based targeted proteomics approaches can provide greatly needed solutions to many of the challenges related to ovarian cancer biomarker development.

Comparative plasma proteomics in muscle atrophy during cancer-cachexia and disuse: The search for atrokines

Skeletal muscle atrophy is common across a variety of pathologies. Underlying mechanisms of atrophy differ between pathologies, and in many conditions, circulating factors are tied to muscle atrophy. Therefore, we sought to identify alterations to the plasma proteome across divergent forms of muscle atrophy, disuse and cancer cachexia, as potential mediators of atrophy. C57BL6/J mice were assigned to Lewis Lung Carcinoma (LLC)-induced cachexia, disuse by hindlimb unloading (HU), or control (CON). Plasma samples were submitted for discovery proteomics and targets of interest confirmed by immunoblot. Considerably more peptides were altered in plasma from LLC (91) than HU (9) as compared to CON. Five total proteins were similarly modulated in HU and LLC compared to CON, none reached criteria for differential expression. Serum Amyloid A1 (SAA) was 4 and 6 Log2 FC greater in LLC than CON or HU, respectively, confirmed by immunoblot. Recent reports suggest SAA is sufficient to induce atrophy via TLR. Therefore, we assessed TLR2,4, and IL-6 mRNAs in hindlimb muscles. TLR mRNAs were not altered, suggesting SAA effects on atrophy during LLC are independent of TLR signaling. However, we noted > 6-fold induction of IL-6 in soleus of HU mice, despite minimal shift in the plasma proteome, indicating potential localized inflammation in atrophying muscle. Furthermore, paraoxonase 1 (PON1) was highly repressed in LLC mice and largely undetectable by immunoblot in this group. Our data suggest SAA and PON1 as potential novel atrokines for cancer cachexia and indicate localized inflammation in atrophying muscles independent of the plasma proteome.

Challenges and Opportunities in Clinical Applications of Blood-Based Proteomics in Cancer

Simple Summary

The traditional approach in identifying cancer related protein biomarkers has focused on evaluation of a single peptide/protein in tissue or circulation. At best, this approach has had limited success for clinical applications, since multiple pathological tumor pathways may be involved during initiation or progression of cancer which diminishes the significance of a single candidate protein/peptide. Emerging sensitive proteomic based technologies like liquid chromatography mass spectrometry (LC-MS)-based quantitative proteomics can provide a platform for evaluating serial serum or plasma samples to interrogate secreted products of tumor–host interactions, thereby revealing a more “complete” repertoire of biological variables encompassing heterogeneous tumor biology. However, several challenges need to be met for successful application of serum/plasma based proteomics. These include uniform pre-analyte processing of specimens, sensitive and specific proteomic analytical platforms and adequate attention to study design during discovery phase followed by validation of discovery-level signatures for prognostic, predictive, and diagnostic cancer biomarker applications.

Abstract

Blood is a readily accessible biofluid containing a plethora of important proteins, nucleic acids, and metabolites that can be used as clinical diagnostic tools in diseases, including cancer. Like the on-going efforts for cancer biomarker discovery using the liquid biopsy detection of circulating cell-free and cell-based tumor nucleic acids, the circulatory proteome has been underexplored for clinical cancer biomarker applications. A comprehensive proteome analysis of human serum/plasma with high-quality data and compelling interpretation can potentially provide opportunities for understanding disease mechanisms, although several challenges will have to be met. Serum/plasma proteome biomarkers are present in very low abundance, and there is high complexity involved due to the heterogeneity of cancers, for which there is a compelling need to develop sensitive and specific proteomic technologies and analytical platforms. To date, liquid chromatography mass spectrometry (LC-MS)-based quantitative proteomics has been a dominant analytical workflow to discover new potential cancer biomarkers in serum/plasma. This review will summarize the opportunities of serum proteomics for clinical applications; the challenges in the discovery of novel biomarkers in serum/plasma; and current proteomic strategies in cancer research for the application of serum/plasma proteomics for clinical prognostic, predictive, and diagnostic applications, as well as for monitoring minimal residual disease after treatments. We will highlight some of the recent advances in MS-based proteomics technologies with appropriate sample collection, processing uniformity, study design, and data analysis, focusing on how these integrated workflows can identify novel potential cancer biomarkers for clinical applications.

Targeted mass spectrometry for Serum Amyloid A (SAA) isoform profiling in sequential blood samples from experimentally Staphylococcus aureus infected pigs

Serum amyloid A (SAA) is a well-described acute phase protein induced during the acute phase response (APR) to infection. Four isoform specific genes are found in most mammals. Depending on species, SAA3 and SAA4 are generally preferentially expressed extrahepatically whereas SAA1 and SAA2 are hepatic isoforms dominating the SAA serum pool. Little is known about how specific infections affect the serum SAA isoform profile, as SAA isoform discriminating antibodies are not generally available. An antibody independent, quantitative targeted MS method (Selected Reaction Monitoring, SRM) based on available information on porcine SAA isoform genes was developed and used to profile SAA in serum samples from pigs experimentally infected with Staphylococcus aureus (Sa). While results suggest SAA2 as the main circulating porcine SAA isoform, induced around 10 times compared to non-infected controls, total SAA serum concentrations reached only around 4 μg/mL, much lower than established previously by immunoassays. This might suggest that SAA isoform variants not detected by the SRM method might be present in porcine serum. The assay allows monitoring host responses to experimental infections, infectious diseases and inflammation states in the pig at an unprecedented level of detail. It can also be used in a non-calibrated (relative quantification) format. SIGNIFICANCE: We developed an SRM MS method which for the first time allowed the specific quantification of each of the circulating porcine SAA isoforms (SAA2, SAA3, SAA4). It was found that SAA2 is the dominating circulating isoform of SAA in the pig and that, during the acute phase response to Sa infection SAA2, SAA3 and SAA4 are induced approx. 10, 15 and 2 times, respectively. Absolute levels of the isoforms as determined by SRM MS were much lower than reported previously for total SAA quantified by immunosassays, suggesting the existence of hitherto non-described SAA variants. SRM MS holds great promise for the study of the basic biology of SAA isoforms with the potential to study an even broader range of SAA variants.

Identification of a Blood-Based Protein Biomarker Panel for Lung Cancer Detection

Lung cancer is the deadliest cancer worldwide, mainly due to its advanced stage at the time of diagnosis. A non-invasive method for its early detection remains mandatory to improve patients’ survival. Plasma levels of 351 proteins were quantified by Liquid Chromatography-Parallel Reaction Monitoring (LC-PRM)-based mass spectrometry in 128 lung cancer patients and 93 healthy donors. Bootstrap sampling and least absolute shrinkage and selection operator (LASSO) penalization were used to find the best protein combination for outcome prediction. The PanelomiX platform was used to select the optimal biomarker thresholds. The panel was validated in 48 patients and 49 healthy volunteers. A 6-protein panel clearly distinguished lung cancer from healthy individuals. The panel displayed excellent performance: area under the receiver operating characteristic curve (AUC) = 0.999, positive predictive value (PPV) = 0.992, negative predictive value (NPV) = 0.989, specificity = 0.989 and sensitivity = 0.992. The panel detected lung cancer independently of the disease stage. The 6-protein panel and other sub-combinations displayed excellent results in the validation dataset. In conclusion, we identified a blood-based 6-protein panel as a diagnostic tool in lung cancer. Used as a routine test for high- and average-risk individuals, it may complement currently adopted techniques in lung cancer screening.

Deciphering tissue-based proteome signatures revealed novel subtyping and prognostic markers for thymic epithelial tumors

Thymic epithelial tumors (TETs) belong to a group of tumors that rarely occur, but have unresolved mechanisms and heterogeneous clinical behaviors. Current care of TET patients demands biomarkers of high sensitivity and specificity for accurate histological classification and prognosis management. In this study, 134 fresh‐frozen tissue samples (84 tumor, 40 tumor adjacent, and 10 normal thymus) were recruited to generate a quantitative and systematic view of proteomic landscape of TETs. Among them, 90 samples were analyzed by data‐independent acquisition mass spectrometry (DIA‐MS) leading to discovery of novel classifying molecules among different TET subtypes. The correlation between clinical outcome and the identified molecules was probed, and the prioritized proteins of interest were further validated on the remaining samples (n = 44) via parallel reaction monitoring (PRM) as well as immunohistochemical and confocal imaging analysis. In particular, two proteins, the cellular mRNA deadenylase CCR4 (carbon catabolite repressor 4)‐NOT (negative on TATA) complex subunit 2/9 (CNOT2/9) and the serine hydroxymethyltransferase that catalyzes the reversible interconversions of serine and glycine (SHMT1), were found at dramatic low levels in the thymic epithelia of more malignant subtype, thymic squamous cell carcinoma (TSCC). Interestingly, the mRNA levels of these two genes were shown to be closely correlated with prognosis of the TET patients. These results extended the existing human tissue proteome atlas and allowed us to identify several new protein classifiers for TET subtyping. Newly identified subtyping and prognosis markers, CNOT2/9 and SHMT1, will expand current diagnostic arsenal in terms of higher specificity and prognostic insights for TET diagnosis and management.

Interleukin-1β Induces Intracellular Serum Amyloid A1 Expression in Human Coronary Artery Endothelial Cells and Promotes its Intercellular Exchange

Serum amyloid A (SAA) is an acute-phase protein with important, pathogenic role in the development of atherosclerosis. Since dysfunctional endothelium represents a key early step in atherogenesis, we aimed to determine whether induced human coronary artery endothelial cells (HCAEC) modulate SAA1/2/4 expression and influence intracellular location and intercellular transport of SAA1. HCAEC were stimulated with 1 ng/ml IL-1β, 10 ng/ml IL-6, and/or 1 μM dexamethasone for 24 h. QPCR, Western blots, ELISA, and immunofluorescent labeling were performed for detection of SAA1/2/4 mRNA and protein levels, respectively. In SAA1 transport experiments, FITC- or Cy3-labeled SAA1 were added to HCAEC separately, for 24 h, followed by a combined incubation of SAA1-FITC and SAA1-Cy3 positive cells, with IL-1β and analysis by flow cytometry. IL-1β upregulated SAA1 (119.9-fold, p < 0.01) and SAA2 (9.3-fold; p < 0.05) mRNA expression levels, while mRNA expression of SAA4 was not affected. Intracellular SAA1 was found mainly as a monomer, while SAA2 and SAA4 formed octamers as analyzed by Western blots. Within HCAEC, SAA1/2/4 located mostly to the perinuclear area and tunneling membrane nanotubes. Co-culturing of SAA1-FITC and SAA1-Cy3 positive cells for 48 h showed a significantly higher percentage of double positive cells in IL-1β-stimulated (mean ± SD; 60 ± 4%) vs. non-stimulated cells (48 ± 2%; p < 0.05). IL-1β induces SAA1 expression in HCAEC and promotes its intercellular exchange, suggesting that direct communication between cells in inflammatory conditions could ultimately lead to faster development of atherosclerosis in coronary arteries.

Targeted proteomics reveals serum amyloid A variants and alarmins S100A8-S100A9 as key plasma biomarkers of rheumatoid arthritis

Serum amyloid A (SAA) and S100 (S100A8, S100A9 and S100A12) proteins were previously identified as biomarkers of interest for rheumatoid arthritis (RA). Among SAA family, two closely related isoforms (SAA-1 and SAA-2) are linked to the acute-phase of inflammation. They respectively exist under the form of three (α, β, and γ) and two (α and β) allelic variants. We developed a single run quantitative method for these protein variants and investigated their clinical relevance in the context of RA. The method was developed and validated according to regulations before being applied on plasma coming from RA patients (n = 46), other related inflammatory pathologies (n = 116) and controls (n = 62). Depending on the activity score of RA, SAA1 isoforms (mainly of SAA1α and SAA1β subtypes) were found to be differentially present in plasma revealing their dual role during the development of RA. In addition, the weight of SAA1α in the total SAA response varied from 32 to 80% depending on the pathology studied. A negative correlation between SAA1α and SAA1β was also highlighted for RA early-onset (r = -0.41). SAA2 and S100A8/S100A9 proteins were significantly overexpressed compared to control samples regardless of RA stage. The pathophysiological relevance of these quantitative and qualitative characteristics of the SAA response remains unknown. However, the significant negative correlation observed between SAA1α and SAA1β levels in RA early-onset suggests the existence of still unknown regulatory mechanisms in these diseases.

Applications of multiple reaction monitoring targeted proteomics assays in human plasma

Introduction: Multiple (or selected) reaction monitoring-mass spectrometry (MRM/SRM) is a targeted proteomic method that can be used for relative and absolute quantification. Multiple reports exist supporting the potential of the approach in proteomic biomarker validation. Areas covered: To get an overview of the applications of MRM in protein quantification in plasma, a search in MedLine/PubMed was performed using the keywords: 'MRM/SRM plasma proteomic/proteomics/proteome'. The retrieved studies were further filtered to focus on disease biomarkers and the main results are summarized. Expert opinion: MRM is increasingly employed for the quantification of both well-established but also newly discovered putative biomarkers and occasionally their post-translationally modified forms in plasma. Fractionation is regularly required for the detection of low abundance proteins. Standardized procedures to facilitate assay establishment and marker quantification have been proposed and, in few cases, implemented. Nevertheless, in most cases, absolute quantification is not performed. To advance, multiple technical issues including the regular use of standard labeled peptides and appropriate quality controls to monitor assay performance should be considered. Additionally, clinical aspects involving careful study design to address biomarker clinical use should also be considered.

Multiplex Assay for Quantification of Acute Phase Proteins and Immunoglobulin A in Dried Blood Spots

Inflammation is the first line defense mechanism against infection, tissue damage, or cancer development. However, inappropriate inflammatory response may also trigger diseases. The quantification of inflammatory proteins is essential to distinguish between harmful and beneficial immune response. Currently used immunoanalytical assays may suffer specificity issues due to antigen-antibody interaction and possible cross-reactivity of antibody with other protein species. In addition, immunoanalytical assays typically require invasive blood sampling and additional logistics; they are relatively costly and highly challenging to multiplex. We present a multiplex assay based on selected reaction monitoring (SRM) for quantification of seven acute-phase proteins (i.e., SAA1, SAA2-isoform1, SAA4, CRP, A1AT-isoform1, A1AG1, A1AG2) and the adaptive immunity effector IGHA1 in dried blood spots. This type of sample is readily available from all human subjects including newborns. The study utilizes proteotypic isotopically labeled peptides with trypsin-cleavable tag and presents optimized and reproducible workflow and several important practical remarks regarding quantitative SRM assays development. The panel of inflammatory proteins was quantified with sequence specificity capable to differentiate protein isoforms with intra- and interday precision (<16.4% coefficient of variation (CV) and <14.3% CV, respectively). Quantitative results were correlated with immuno-nephelometric assay (typically greater than 0.9 Pearson's R).

Identification of beta-arrestin-1 as a diagnostic biomarker in lung cancer

Background

Distinguishing lung adenocarcinoma (ADC) from squamous cell carcinoma (SCC) has a tremendous therapeutic implication. Sometimes, the commonly used immunohistochemistry (IHC) markers fail to discriminate between them, urging for the identification of new diagnostic biomarkers.

Methods

We performed IHC on tissue microarrays from two cohorts of lung cancer patients to analyse the expression of beta-arrestin-1, beta-arrestin-2 and clinically used diagnostic markers in ADC and SCC samples. Logistic regression models were applied for tumour subtype prediction. Parallel reaction monitoring (PRM)-based mass spectrometry was used to quantify beta-arrestin-1 in plasma from cancer patients and healthy donors.

Results

Beta-arrestin-1 expression was significantly higher in ADC versus SCC samples. Beta-arrestin-1 displayed high sensitivity, specificity and negative predictive value. Its usefulness in an IHC panel was also shown. Plasma beta-arrestin-1 levels were considerably higher in lung cancer patients than in healthy donors and were higher in patients who later experienced a progressive disease than in patients showing complete/partial response following EGFR inhibitor therapy.

Conclusions

Our data identify beta-arrestin-1 as a diagnostic marker to differentiate ADC from SCC and indicate its potential as a plasma biomarker for non-invasive diagnosis of lung cancer. Its utility to predict response to EGFR inhibitors is yet to be confirmed.

Relative and Absolute Quantitation in Mass Spectrometry-Based Proteomics

Mass spectrometry-based quantitative proteomics is a powerful tool for gaining insights into function and dynamics of biological systems. However, peptides with different sequences have different ionization efficiencies, and their intensities in a mass spectrum are not correlated with their abundances. Therefore, various label-free or stable isotope label-based quantitation methods have emerged to assist mass spectrometry to perform comparative proteomic experiments, thus enabling nonbiased identification of thousands of proteins differentially expressed in healthy versus diseased cells. Here, we discuss the most widely used label-free and metabolic-, enzymatic-, and chemical labeling-based proteomic strategies for relative and absolute quantitation. We summarize the specific strengths and weaknesses of each technique in terms of quantification accuracy, proteome coverage, multiplexing capability, and robustness. Applications of each strategy for solving specific biological complexities are also presented.

Serum amyloid A1 in combination with integrin αVβ3 increases glioblastoma cells mobility and progression

Glioblastoma multiforme (GBM) is a highly malignant type of brain tumor found in humans. GBM cells reproduce quickly, and the median survival time for patients after therapy is approximately 1 year with a high relapse rate. Current therapies and diagnostic tools for GBM are limited; therefore, we searched for a more favorable therapeutic target or marker protein for both therapy and diagnosis. We used mass spectrometry (MS) analysis to identify GBM-associated marker proteins from human plasma and GBM cell cultures. Additional plasma and 52 brain tissues obtained from patients with gliomas were used to validate the association rate of serum amyloid A1 (SAA1) in different grades of gliomas and its distribution in tumors. Microarray database analysis further validated the coefficient of SAA1 levels in gliomas. The cellular mechanisms of SAA1 in GBM proliferation and infiltration were investigated in vitro. We analyzed the correlation between SAA1 and patients' medication requirement to demonstrate the clinical effects of SAA1 in GBM. SAA1 was identified from MS analysis, and its level was revealed to be correlated with the disease grade, clinical severity, and survival rate of patients with gliomas. In vitro cultures, including GBM cells and normal astrocytes, revealed that SAA1 promotes cell migration and invasion through integrin αVβ3 to activate the Erk signaling pathway. Magnetic resonance imaging and tumor region-specific microarray analysis identified a correlation between SAA1 and GBM cell infiltration in patients. In summary, our results demonstrate that SAA1 in combination with integrin αV and β3 can serve as an indicator of high glioblastoma risk. We also identified the cellular mechanisms of SAA1 contributing to GBM progression, which can serve as the basis for future GBM therapy.

Exploring the expression bar code of SAA variants for gastric cancer detection

We reported an integrated platform to explore serum protein variant pattern in cancer and its utility as a new class of biomarker panel for diagnosis. On the model study of serum amyloid A (SAA), we employed nanoprobe-based affinity mass spectrometry for enrichment, identification and quantitation of SAA variants from serum of 105 gastric cancer patients in comparison with 54 gastritis patients, 54 controls, and 120 patients from other cancer. The result revealed surprisingly heterogeneous and most comprehensive SAA bar code to date, which comprises 24 SAA variants including SAA1- and SAA2-encoded products, polymorphic isoforms, N-terminal-truncated forms, and three novel SAA oxidized isotypes, in which the variant-specific peptide sequence were also confirmed by LC-MS/MS. A diagnostic model was developed for dimension reduction and computational classification of the 24 SAA-variant bar code, providing good discrimination (AUC = 0.85 ± 3.2E-3) for differentiating gastric cancer group from gastritis and normal groups (sensitivity, 0.76; specificity, 0.81) and was validated with external validation cohort (sensitivity, 0.71; specificity, 0.74). Our platform not only shed light on the occurrence and modification extent of under-represented serum protein variants in cancer, but also suggested a new concept of diagnostic platform by serum protein variant profile.

Mass Spectrometry Analysis of Lysine Posttranslational Modifications of Tau Protein from Alzheimer's Disease Brain

Recent advances in mass spectrometry (MS)-based proteomics have greatly facilitated the robust identification and quantification of posttranslational modifications (PTMs), including those that are present at substoichiometric site occupancies. The abnormal posttranslational modification and accumulation of the microtubule-associated protein tau has been implicated in the pathogenesis of Alzheimer's disease (AD), and it is thought that the primary mode of regulation of tau occurs through PTMs. Several studies have been published regarding tau phosphorylation; however, other tau PTMs such as ubiquitylation, acetylation, methylation, oxidation, sumoylation, nitration, and glycosylation have not been analyzed as extensively. The comprehensive detection and delineation of these PTMs is critical for drug target discovery and validation. Lysine-directed PTMs including ubiquitylation, acetylation, and methylation play key regulatory roles with respect to the rates of tau turnover and aggregation. MS-based analytical approaches have been used to gain insight into the tau lysine-directed PTM signature that is most closely associated with neurofibrillary lesion formation. This chapter provides details pertaining to the liquid chromatography tandem mass spectrometry (LC-MS/MS)-based analysis of the lysine-directed posttranslational modification of tau.

Development of a sequential workflow based on LC-PRM for the verification of endometrial cancer protein biomarkers in uterine aspirate samples

About 30% of endometrial cancer (EC) patients are diagnosed at an advanced stage of the disease, which is associated with a drastic decrease in the 5-year survival rate. The identification of biomarkers in uterine aspirate samples, which are collected by a minimally invasive procedure, would improve early diagnosis of EC. We present a sequential workflow to select from a list of potential EC biomarkers, those which are the most promising to enter a validation study. After the elimination of confounding contributions by residual blood proteins, 52 potential biomarkers were analyzed in uterine aspirates from 20 EC patients and 18 non-EC controls by a high-resolution accurate mass spectrometer operated in parallel reaction monitoring mode. The differential abundance of 26 biomarkers was observed, and among them ten proteins showed a high sensitivity and specificity (AUC > 0.9). The study demonstrates that uterine aspirates are valuable samples for EC protein biomarkers screening. It also illustrates the importance of a biomarker verification phase to fill the gap between discovery and validation studies and highlights the benefits of high resolution mass spectrometry for this purpose. The proteins verified in this study have an increased likelihood to become a clinical assay after a subsequent validation phase.

Serum amyloid A expression in the breast cancer tissue is associated with poor prognosis

Background

Serum amyloid A (SAA), an acute-phase protein, is expressed primarily in the liver, and recently found also expressed in cancer tissues. However, its expression and prognostic value in breast cancer have not been described.

Results

SAA protein was found expressed in tumor cells in 44.2% cases and in TAM in 62.5% cases. FISH showed more frequent SAA mRNA expression in TAM than in tumor cells (76% versus 12%, p < 0.001), and a significant association between the frequencies of SAA mRNA expression in TAM and tumor cells (r_s = 0.603, p < 0.001). The immunoreactivities of SAA protein in TAM and tumor cells were both associated with lymphovascular invasion and lymph node metastasis. Moreover, SAA-positivity in TAMs was associated with larger tumor-size, higher histological-grade, negative estrogen-receptor and progesterone-receptor statuses, and HER-2 overexpression. It was also linked to worse recurrence-free survival in a multivariable regression model.

Methods

Immunohistochemistry was applied on the tumor tissues from 208 breast cancer patients to evaluate the local SAA-protein expression with additional CD68 stain to identify the tumor-associated macrophage (TAM) on the serial tissue sections. Fluorescent in situ hybridization (FISH) was conducted on serial tissue sections from 25 of the 208 tumors to examine the expression and location of SAA mRNA.

Conclusions

Our results suggested that the TAMs may be a pivotal and main source of SAA production in tumor microenvironment of breast cancer. SAA immunoreactivity in TAM is associated with worse recurrence-free survival, and is therefore a biomarker candidate for postoperative surveillance and perhaps a therapeutic target for breast cancer.

Quantification of Cardiovascular Disease Biomarkers in Human Platelets by Targeted Mass Spectrometry

Platelets are known to be key players in thrombosis and hemostasis, contributing to the genesis and progression of cardiovascular diseases. Due to their pivotal role in human physiology and pathology, platelet function is regulated tightly by numerous factors which have either stimulatory or inhibitory effects. A variety of factors, e.g., collagen, fibrinogen, ADP, vWF, thrombin, and thromboxane promote platelet adhesion and aggregation by utilizing multiple intracellular signal cascades. To quantify platelet proteins for this work, a targeted proteomics workflow was applied. In detail, platelets are isolated and lyzed, followed by a tryptic protein digest. Subsequently, a mix of stable isotope-labeled peptides of interesting biomarker proteins in concentrations ranging from 0.1 to 100 fmol is added to 3 μg digest. These peptides are used as an internal calibration curve to accurately quantify endogenous peptides and corresponding proteins in a pooled platelet reference sample by nanoLC-MS/MS with parallel reaction monitoring. In order to assure a valid quantification, limit of detection (LOD) and limit of quantification (LOQ), as well as linear range, were determined. This quantification of platelet activation and proteins by targeted mass spectrometry may enable novel diagnostic strategies in the detection and prevention of cardiovascular diseases.

Proteome characterization of human pancreatic cyst fluid from intraductal papillary mucinous neoplasm by liquid chromatography/tandem mass spectrometry

RATIONALE

In recent years, the molecular components of pancreatic cyst fluid have been used for diagnosis and prognosis. Because the protein markers that are currently used in clinical tests are unreliable, proteomic studies to find new protein markers are being conducted. However, such researches have been limited due to the complexity of pancreatic cyst fluid and the immaturity of proteomic techniques.

METHODS

To overcome these limitations and provide a pancreatic cyst proteome dataset, we examined cyst fluid proteome with tandem mass spectrometry. The proteomic analysis was performed using a Orbitrap-based mass spectrometer (Q-Exactive) coupled with a 50-cm-long nano-liquid chromatography column. Protein mutations were identified using mutation sequence database search.

RESULTS

A total of 5850 protein groups were identified from microliters of cyst fluid. Among those, 3934 protein groups were reported for the first time in pancreatic cyst fluid. Although high-abundance proteins were not depleted in the experiment, our dataset detected almost all pancreatic tumor markers such as mucin family members, S100 proteins, and CEA-related proteins. In addition, 590 protein mutation marker candidates were discovered.

CONCLUSIONS

We provide a comprehensive cyst proteome dataset that includes cystic cellular proteins and mutated proteins. Our findings would serve as a rich resource for further IPMN studies and clinical applications. The MS data have been deposited in the ProteomeXchange with identifier PXD005671 (http://proteomecentral.proteomexchange.org/dataset/PXD005671).

Strategies for Characterization of Low-Abundant Intact or Truncated Low-Molecular-Weight Proteins From Human Plasma

Low-molecular-weight region (LMW, MW≤30kDa) of human serum/plasma proteins, including small intact proteins, truncated fragments of larger proteins, along with some other small components, has been associated with the ongoing physiological and pathological events, and thereby represent a treasure trove of diagnostic molecules. Great progress in the mining of novel biomarkers from this diagnostic treasure trove for disease diagnosis and health monitoring has been achieved based on serum samples from healthy individuals and patients and powerful new approaches in biochemistry and systems biology. However, cumulative evidence indicates that many potential LMW protein biomarkers might still have escaped from detection due to their low abundance, the dynamic complexity of serum/plasma, and the limited efficiency of characterization approaches. Here, we provide an overview of the current state of knowledge with respect to strategies for the characterization of low-abundant LMW proteins (small intact or truncated proteins) from human serum/plasma, involving prefractionation or enrichment methods to reduce dynamic range and mass spectrometry-based characterization of low-abundant LMW proteins.

Proteomic discovery and verification of serum amyloid A as a predictor marker of patients at risk of post-stroke infection: a pilot study

Background

Post-stroke infections occur in 20–36% of stroke patients and are associated with high morbidity and mortality rates. Early identification of patients at risk of developing an infection could improve care via an earlier treatment leading to a better outcome. We used proteomic tools in order to discover biomarkers able to stratify patients at risk of post-stroke infection.

Methods

The post hoc analysis of a prospective cohort study including 40 ischemic stroke patients included 21 infected and 19 non-infected participants. A quantitative, isobaric labeling, proteomic strategy was applied to the plasma samples of 5 infected and 5 non-infected patients in order to highlight any significantly modulated proteins. A parallel reaction monitoring (PRM) assay was applied to 20 additional patients (10 infected and 10 non-infected) to verify discovery results. The most promising protein was pre-validated using an ELISA immunoassay on 40 patients and at different time points after stroke onset.

Results

Tandem mass analysis identified 266 proteins, of which only serum amyloid A (SAA1/2) was significantly (p = 0.007) regulated between the two groups of patients. This acute-phase protein appeared to be 2.2 times more abundant in infected patients than in non-infected ones. These results were verified and validated using PRM and ELISA immunoassays, which showed that infected patients had significantly higher concentrations of SAA1/2 than non-infected patients at hospital admission, but also at 1, 3, and 5 days after admission.

Conclusions

The present study demonstrated that SAA1/2 is a promising predictor, at hospital admission, of stroke patients at risk of developing an infection. Further large, multicenter validation studies are needed to confirm these results. If confirmed, SAA1/2 concentrations could be used to identify the patients most at risk of post-stroke infections and therefore implement treatments more rapidly, thus reducing mortality.

Electronic supplementary material

The online version of this article (doi:10.1186/s12014-017-9162-0) contains supplementary material, which is available to authorized users.

Determination of differentially regulated proteins upon proteasome inhibition in AML cell lines by the combination of large-scale and targeted quantitative proteomics

The ubiquitin-proteasome pathway (UPP) plays a critical role in the degradation of proteins implicated in cell cycle control, signal transduction, DNA damage response, apoptosis and immune response. Proteasome inhibitors can inhibit the growth of a broad spectrum of human cancer cells by altering the balance of intracellular proteins. However, the targets of these compounds in acute myeloid leukemia (AML) cells have not been fully characterized. Herein, we combined large-scale quantitative analysis by SILAC-MS and targeted quantitative proteomic analysis in order to identify proteins regulated upon proteasome inhibition in two AML cell lines displaying different stages of maturation: immature KG1a cells and mature U937 cells. In-depth data analysis enabled accurate quantification of more than 7000 proteins in these two cell lines. Several candidates were validated by selected reaction monitoring (SRM) measurements in a large number of samples. Despite the broad range of proteins known to be affected by proteasome inhibition, such as heat shock (HSP) and cell cycle proteins, our analysis identified new differentially regulated proteins, including IL-32, MORF family mortality factors and apoptosis inducing factor SIVA, a target of p53. It could explain why proteasome inhibitors induce stronger apoptotic responses in immature AML cells.

Recent mass spectrometry-based proteomics for biomarker discovery in lung cancer, COPD, and asthma

INTRODUCTION

Lung cancer and related diseases have been one of the most common causes of deaths worldwide. Genomic-based biomarkers may hardly reflect the underlying dynamic molecular mechanism of functional protein interactions, which is the center of a disease. Recent developments in mass spectrometry (MS) have made it possible to analyze disease-relevant proteins expressed in clinical specimens by proteomic challenges. Areas covered: To understand the molecular mechanisms of lung cancer and its subtypes, chronic obstructive pulmonary disease (COPD), asthma and others, great efforts have been taken to identify numerous relevant proteins by MS-based clinical proteomic approaches. Since lung cancer is a multifactorial disease that is biologically associated with asthma and COPD among various lung diseases, this study focused on proteomic studies on biomarker discovery using various clinical specimens for lung cancer, COPD, and asthma. Expert commentary: MS-based exploratory proteomics utilizing clinical specimens, which can incorporate both experimental and bioinformatic analysis of protein-protein interaction and also can adopt proteogenomic approaches, makes it possible to reveal molecular networks that are relevant to a disease subgroup and that could differentiate between drug responders and non-responders, good and poor prognoses, drug resistance, and so on.

Vaccination via Chloroplast Genetics: Affordable Protein Drugs for the Prevention and Treatment of Inherited or Infectious Human Diseases

Plastid-made biopharmaceuticals treat major metabolic or genetic disorders, including Alzheimer's, diabetes, hypertension, hemophilia, and retinopathy. Booster vaccines made in chloroplasts prevent global infectious diseases, such as tuberculosis, malaria, cholera, and polio, and biological threats, such as anthrax and plague. Recent advances in this field include commercial-scale production of human therapeutic proteins in FDA-approved cGMP facilities, development of tags to deliver protein drugs to targeted human cells or tissues, methods to deliver precise doses, and long-term stability of protein drugs at ambient temperature, maintaining their efficacy. Codon optimization utilizing valuable information from sequenced chloroplast genomes enhanced expression of eukaryotic human or viral genes in chloroplasts and offered unique insights into translation in chloroplasts. Support from major biopharmaceutical companies, development of hydroponic production systems, and evaluation by regulatory agencies, including the CDC, FDA, and USDA, augur well for advancing this novel concept to the clinic and revolutionizing affordable healthcare.

Advances in targeted proteomics and applications to biomedical research

Targeted proteomics technique has emerged as a powerful protein quantification tool in systems biology, biomedical research, and increasing for clinical applications. The most widely used targeted proteomics approach, selected reaction monitoring (SRM), also known as multiple reaction monitoring (MRM), can be used for quantification of cellular signaling networks and preclinical verification of candidate protein biomarkers. As an extension to our previous review on advances in SRM sensitivity (Shi et al., Proteomics, 12, 1074-1092, 2012) herein we review recent advances in the method and technology for further enhancing SRM sensitivity (from 2012 to present), and highlighting its broad biomedical applications in human bodily fluids, tissue and cell lines. Furthermore, we also review two recently introduced targeted proteomics approaches, parallel reaction monitoring (PRM) and data-independent acquisition (DIA) with targeted data extraction on fast scanning high-resolution accurate-mass (HR/AM) instruments. Such HR/AM targeted quantification with monitoring all target product ions addresses SRM limitations effectively in specificity and multiplexing; whereas when compared to SRM, PRM and DIA are still in the infancy with a limited number of applications. Thus, for HR/AM targeted quantification we focus our discussion on method development, data processing and analysis, and its advantages and limitations in targeted proteomics. Finally, general perspectives on the potential of achieving both high sensitivity and high sample throughput for large-scale quantification of hundreds of target proteins are discussed.

Proteomic profiling of pretreatment serum from HIV-infected patients identifies candidate markers predictive of lymphoma development

OBJECTIVE

HIV-infected individuals have an increased risk of developing lymphoma. We sought to identify markers predictive of lymphoma development by comparing protein expression patterns in serum obtained at the time of HIV diagnosis from patients who later developed malignant lymphoma or benign lymphadenopathy, with samples from patients with no subsequent history of neoplasia.

DESIGN

All patients were identified retrospectively from the Danish HIV cohort.

METHODS

Serum samples (N = 21), obtained at time of HIV diagnosis, were subjected to high-resolution two-dimensional gel electrophoresis. Differentially expressed proteins were identified by liquid chromatography-tandem mass spectrometry. A tissue microarray, containing diagnostic HIV-lymphoma tissue samples (N = 40), was used to investigate immunohistochemical expression of markers in tumoural lesions.

RESULTS

Fourteen differentially expressed protein spots were detected. Using principal components analysis, spots containing immunoglobulin J chain, apolipoprotein A-I, procollagen C-endopeptidase enhancer-1 and complement C4-A were associated with lymphoma development (P < 0.0001). Serum amyloid A-2 was increased almost 10-fold in patients with subsequent lymphoma compared with patients without subsequent lymphoma. In the tissue microarray, amyloid A was widely expressed, and high expression showed a tendency towards inferior outcome (log-rank 0.073).

CONCLUSION

We identified several differentially expressed protein spots present already at the time of HIV diagnosis. Analysis of biological differences correlating to lymphoma development at this early stage of a possible malignant transformation may lead to the identification of predictive markers. Further investigation of the potential clinical application of differentially expressed proteins as risk stratification markers for monitoring HIV-positive individuals is warranted.

Integration of Breast Cancer Secretomes with Clinical Data Elucidates Potential Serum Markers for Disease Detection, Diagnosis, and Prognosis

Cancer cells secrete factors that influence adjacent cell behavior and can lead to enhanced proliferation and metastasis. To better understand the role of these factors in oncogenesis and disease progression, estrogen and progesterone receptor positive MCF-7 cells, triple negative breast cancer MDA-MB-231, DT22, and DT28 cells, and MCF-10A non-transformed mammary epithelial cells were grown in 3D cultures. A special emphasis was placed on triple negative breast cancer since these tumors are highly aggressive and no targeted treatments are currently available. The breast cancer cells secreted factors of variable potency that stimulated proliferation of the relatively quiescent MCF-10A cells. The conditioned medium from each cell line was subjected to mass spectrometry analysis and a variety of secreted proteins were identified including glycolytic enzymes, proteases, protease inhibitors, extracellular matrix proteins, and insulin-like growth factor binding proteins. An investigation of the secretome from each cell line yielded clues about strategies used for breast cancer proliferation and metastasis. Some of the proteins we identified may be useful in the development of a serum-based test for breast cancer detection, diagnosis, prognosis, and monitoring.

Parallel reaction monitoring using quadrupole-Orbitrap mass spectrometer: Principle and applications

Targeted mass spectrometry-based approaches are nowadays widely used for quantitative proteomics studies and more recently have been implemented on high resolution/accurate mass (HRAM) instruments resulting in a considerable performance improvement. More specifically, the parallel reaction monitoring technique (PRM) performed on quadrupole-Orbitrap mass spectrometers, leveraging the high resolution and trapping capabilities of the instrument, offers a clear advantage over the conventional selected reaction monitoring (SRM) measurements executed on triple quadrupole instruments. Analyses performed in HRAM mode allow for an improved discrimination between signals derived from analytes and those resulting from matrix interferences translating in the reliable quantification of low abundance components. The purpose of the study defines various implementation schemes of PRM, namely: (i) exploratory experiments assessing the detectability of very large sets of peptides (100-1000), (ii) wide-screen analyses using (crude) internal standards to obtain statistically meaningful (relative) quantitative analyses, and (iii) precise/accurate quantification of a limited number of analytes using calibrated internal standards. Each of the three implementation schemes requires specific acquisition methods with defined parameters to appropriately control the acquisition during the actual peptide elution. This tutorial describes the different PRM approaches and discusses their benefits and limitations in terms of quantification performance and confidence in analyte identification.

Parallel Reaction Monitoring: A Targeted Experiment Performed Using High Resolution and High Mass Accuracy Mass Spectrometry

The parallel reaction monitoring (PRM) assay has emerged as an alternative method of targeted quantification. The PRM assay is performed in a high resolution and high mass accuracy mode on a mass spectrometer. This review presents the features that make PRM a highly specific and selective method for targeted quantification using quadrupole-Orbitrap hybrid instruments. In addition, this review discusses the label-based and label-free methods of quantification that can be performed with the targeted approach.