Clinical proteomics最新文献

Background: Quantification of drug-target binding is critical for confirming that drugs reach their intended protein targets, understanding the mechanism of action, and interpreting dose-response relationships. For covalent inhibitors, target engagement can be inferred by free target levels before and after treatment. Targeted mass spectrometry assays offer precise protein quantification in complex biological samples and have been routinely applied in pre-clinical studies to quantify target engagement in frozen tumor tissues for oncology drug development. However, frozen tissues are often not available from clinical trials so it is critical that assays are applicable to formalin-fixed, paraffin-embedded (FFPE) tissues in order to extend mass spectrometry-based target engagement studies into clinical settings.

Methods: Wild-type RAS and RASG12C was quantified in FFPE tissues by a highly optimized targeted mass spectrometry assay that couples high-field asymmetric waveform ion mobility spectrometry (FAIMS) and parallel reaction monitoring (PRM) with internal standards. In a subset of samples, technical reproducibility was evaluated by analyzing consecutive tissue sections from the same tumor block and biological variation was accessed among adjacent tumor regions in the same tissue section.

Results: Wild-type RAS protein was measured in 32 clinical non-small cell lung cancer tumors (622-2525 amol/µg) as measured by FAIMS-PRM mass spectrometry. Tumors with a known KRASG12C mutation (n = 17) expressed a wide range of RASG12C mutant protein (127-2012 amol/µg). The variation in wild-type RAS and RASG12C measurements ranged 0-18% CV across consecutive tissue sections and 5-20% CV among adjacent tissue regions. Quantitative target engagement was then demonstrated in FFPE tissues from 2 xenograft models (MIA PaCa-2 and NCI-H2122) treated with a RASG12C inhibitor (AZD4625).

Conclusions: This work illustrates the potential to expand mass spectrometry-based proteomics in preclinical and clinical oncology drug development through analysis of FFPE tumor biopsies.

Background: Histones posttranslational modification represent an epigenetic mechanism that regulate gene expression and other cellular processes. Quantitative mass spectrometry used for the absolute quantification of such modifications provides further insight into cellular responses to extracellular insults such as infections or toxins. Methamphetamine (Meth), a drug of abuse, is affecting the overall function of the immune system. In this report, we developed, validated and applied a targeted, MS-based quantification assay to measure changes in histone H3 lysine 14 acetylation (H3K14Ac) during exposure of human primary macrophages to HIV-1 infection and/or Meth.

Methods: The quantification assay was developed and validated to determine H3K14Ac stoichiometry in histones that were isolated from the nuclei of control (CIC) and exposed to Meth before (CIM) or/and after (MIM) HIV-infection human monocyte-derived macrophages (hMDM) of six donors. It was based on LC-MS/MS measurement using multiple reaction monitoring (MRM) acquisition of the unmodified and acetylated form of lysine K14 of histone H3 ⁹KSTGGKAPR¹⁷ peptides and the corresponding stable isotope labeled (SIL) heavy peptide standards of the same sequences. The histone samples were propionylated (Poy) pre- and post- trypsin digestion so that the sequences of the monitored peptides were: K[Poy]STGGK[1Ac]APR, K[Poy]STGGK[1Ac]APR-heavy, K[Poy]STGGK[Poy]APR and K[Poy]STGGK[Poy]APR-heavy. The absolute amounts of the acetylated and unmodified peptides were determined by comparing to the abundances of their SIL standards, that were added to the samples in the known concentrations, and, then used for calculation of H3K14Ac stoichiometry in CIC, CIM and MIM hMDM.

Results: The assay was characterized by LLOD of 0.106 fmol/µL and 0.204 fmol/µL for unmodified and acetylated H3 ⁹KSTGGKAPR¹⁷ peptides, respectively. The LLOQ was 0.5 fmol/µL and the linear range of the assay was from 0.5 to 2500 fmol/µL. The absolute abundances of the quantified peptides varied between the donors and conditions, and so did the H3K14Ac stoichiometry. This was rather attributed to the samples nature itself, as the variability of their triplicate measurements was low.

Conclusions: The developed LC-MS/MS assay enabled absolute quantification of H3K14Ac in exposed to Meth HIV-infected hMDM. It can be further applied determination of this PTM stoichiometry in other studies on human primary macrophages.

Glioblastoma is one of the most malignant primary brain cancer. Despite surgical resection with modern technology followed by chemo-radiation therapy with temozolomide, resistance to the treatment and recurrence is common due to its aggressive and infiltrating nature of the tumor with high proliferation index. The median survival time of the patients with glioblastomas is less than 15 months. Till now there has been no report of molecular target specific for glioblastomas. Early diagnosis and development of molecular target specific for glioblastomas are essential for longer survival of the patients with glioblastomas. Development of biomarkers specific for glioblastomas is most important for early diagnosis, estimation of the prognosis, and molecular target therapy of glioblastomas. To that end, in this study, we have conducted a comprehensive proteome study using primary cells and tissues from patients with glioblastoma. In the discovery stage, we have identified 7429 glioblastoma-specific proteins, where 476 proteins were quantitated using Tandem Mass Tag (TMT) method; 228 and 248 proteins showed up and down-regulated pattern, respectively. In the validation stage (20 selected target proteins), we developed quantitative targeted method (MRM: Multiple reaction monitoring) using stable isotope standards (SIS) peptide. In this study, five proteins (CCT3, PCMT1, TKT, TOMM34, UBA1) showed the significantly different protein levels (t-test: p value ≤ 0.05, AUC ≥ 0.7) between control and cancer groups and the result of multiplex assay using logistic regression showed the 5-marker panel showed better sensitivity (0.80 and 0.90), specificity (0.92 and 1.00), error rate (10 and 2%), and AUC value (0.94 and 0.98) than the best single marker (TOMM34) in primary cells and tissues, respectively. Although we acknowledge that the model requires further validation in a large sample size, the 5 protein marker panel can be used as baseline data for the discovery of novel biomarkers of the glioblastoma.

The quest for understanding and managing the long-term effects of COVID-19, often referred to as Long COVID or post-COVID-19 condition (PCC), remains an active research area. Recent findings highlighted angiopoietin-1 (ANG-1) and p-selectin (P-SEL) as potential diagnostic markers, but validation is essential, given the inconsistency in COVID-19 biomarker studies. Leveraging the biobanque québécoise de la COVID-19 (BQC19) biobank, we analyzed the data of 249 participants. Both ANG-1 and P-SEL levels were significantly higher in patients with PCC participants compared with control subjects at 3 months using the Mann-Whitney U test. We managed to reproduce and validate the findings, emphasizing the importance of collaborative biobanking efforts in enhancing the reproducibility and credibility of Long COVID research outcomes.

Background: Systemic lupus erythematosus (SLE) is an autoimmune disease with multiple organ involvement, especially the kidneys. However, the underlying mechanism remains unclear, and accurate biomarkers are still lacking. This study aimed to identify biomarkers to assess organ damage and disease activity in patients with SLE using quantitative proteomics.

Methods: Proteomic analysis was performed using mass spectrometry in 15 patients with SLE and 15 age-matched healthy controls. Proteomic profiles were compared in four main subtypes: SLE with proteinuria (SLE-PN), SLE without proteinuria (SLE-non-PN), SLE with anti-dsDNA positivity (SLE-DP), and SLE with anti-dsDNA negativity (SLE-non-DP). Gene ontology biological process analysis revealed differentially expressed protein networks. Cystatin C (CysC) levels were measured in 200 patients with SLE using an immunoturbidimetric assay. Clinical and laboratory data were collected to assess their correlation with serum CysC levels.

Results: Proteomic analysis showed that upregulated proteins in both the SLE-PN and SLE-DP groups were mainly mapped to neutrophil activation networks. Moreover, CysC from neutrophil activation networks was upregulated in both the SLE-PN and SLE-DP groups. The associations of serum CysC level with proteinuria, anti-dsDNA positivity, lower complement C3 levels, and SLE disease activity index score in patients with SLE were further validated in a large independent cohort.

Conclusions: Neutrophil activation is more prominent in SLE with proteinuria and anti-dsDNA positivity, and CysC is a promising marker for monitoring organ damage and disease activity in SLE.

Serological diagnostics is generally defined as the detection of specific human immunoglobulins developed against viral, bacterial, or parasitic diseases. Serological tests facilitate the detection of past infections, evaluate immune status, and provide prognostic information. Serological assays were traditionally implemented as indirect immunoassays, and their design has not changed for decades. The advantages of straightforward setup and manufacturing, analytical sensitivity and specificity, affordability, and high-throughput measurements were accompanied by limitations such as semi-quantitative measurements, lack of universal reference standards, potential cross-reactivity, and challenges with multiplexing the complete panel of human immunoglobulin isotypes and subclasses. Redesign of conventional serological tests to include multiplex quantification of immunoglobulin isotypes and subclasses, utilize universal reference standards, and minimize cross-reactivity and non-specific binding will facilitate the development of assays with higher diagnostic specificity. Improved serological assays with higher diagnostic specificity will enable screenings of asymptomatic populations and may provide earlier detection of infectious diseases, autoimmune disorders, and cancer. In this review, we present the major clinical needs for serological diagnostics, overview conventional immunoassay detection techniques, present the emerging immunoassay detection technologies, and discuss in detail the advantages and limitations of mass spectrometry and immunoaffinity proteomics for serological diagnostics. Finally, we explore the design of novel immunoaffinity-proteomic assays to evaluate cell-mediated immunity and advance the sequencing of clinically relevant immunoglobulins.

Background: Meningiomas are the most prevalent primary brain tumors. Due to their increasing burden on healthcare, meningiomas have become a pivot of translational research globally. Despite many studies in the field of discovery proteomics, the identification of grade-specific markers for meningioma is still a paradox and requires thorough investigation. The potential of the reported markers in different studies needs further verification in large and independent sample cohorts to identify the best set of markers with a better clinical perspective.

Methods: A total of 53 fresh frozen tumor tissue and 51 serum samples were acquired from meningioma patients respectively along with healthy controls, to validate the prospect of reported differentially expressed proteins and claimed markers of Meningioma mined from numerous manuscripts and knowledgebases. A small subset of Glioma/Glioblastoma samples were also included to investigate inter-tumor segregation. Furthermore, a simple Machine Learning (ML) based analysis was performed to evaluate the classification accuracy of the list of proteins.

Results: A list of 15 proteins from tissue and 12 proteins from serum were found to be the best segregator using a feature selection-based machine learning strategy with an accuracy of around 80% in predicting low grade (WHO grade I) and high grade (WHO grade II and WHO grade III) meningiomas. In addition, the discriminant analysis could also unveil the complexity of meningioma grading from a segregation pattern, which leads to the understanding of transition phases between the grades.

Conclusions: The identified list of validated markers could play an instrumental role in the classification of meningioma as well as provide novel clinical perspectives in regard to prognosis and therapeutic targets.

Background: Cardiac troponin is a complex protein consisting of the three subunits I, T and C located in heart muscle cells. When the heart muscle is damaged, it is released into the blood and can be detected. Cardiac troponin I (cTnI) is considered the most reliable and widely accepted test for detecting and confirming acute myocardial infarction. However, there is no current standardization between the commercial assays for cTnI quantification. Our work aims to create a measurement procedure that is traceable to the International System of Units for accurately measuring cardiac cTnI levels in serum samples from patients.

Methods: The workflow begins with immobilizing anti-cTnI antibodies onto magnetic nanoparticles to form complexes. These complexes are used to isolate cTnI from serum. Next, trypsin is used to enzymatically digest the isolated cTnI. Finally, the measurement of multiple cTnI peptides is done simultaneously using isotope dilution liquid chromatography-tandem mass spectrometry (ID-LC-MS/MS).

Results: The maximum antibody immobilization was achieved by combining 1 mg of nanoparticles with 100 μg of antibody, resulting in an average of 59.2 ± 5.7 μg/mg of immobilized antibody. Subsequently, the anti-cTnI-magnetic nanoparticle complex was utilized to develop and validate a method for quantifying cTnI in human serum using ID-LC-MS/MS and a protein calibration approach. The analytical method was assessed regarding linearity and recovery. The developed method enables the quantification of cTnI from 0.7 to 24 μg/L (R > 0.996). The limit of quantification was 1.8 μg/L and the limit of detection was 0.6 μg/L. Intermediate precision was ≤ 9.6% and repeatability was 2.0-8.7% for all quality control materials. The accuracy of the analyzed quality control materials was between 90 and 110%. Total measurement uncertainties for target value assignment (n = 6) were found to be ≤ 12.5% for all levels.

Conclusions: The analytical method demonstrated high analytical performance in accurately quantifying cardiac troponin I levels in human serum. The proposed analytical method has the potential to facilitate the harmonization of cTnI results between clinical laboratories, assign target values to secondary certified reference materials and support reliable measurement of cTnI.

Background: Pheochromocytomas and paragangliomas (PPGLs) are rare neuroendocrine tumors. New drug targets and proteins that would assist sensitive PPGL imagining could improve therapy and quality of life of patients with PPGL, namely those with recurrent or metastatic disease. Using a combined proteomic strategy, we looked for such clinically relevant targets among integral membrane proteins (IMPs) upregulated on the surface of tumor cells and non-membrane druggable enzymes in PPGL.

Methods: We conducted a detailed proteomic analysis of 22 well-characterized human PPGL samples and normal chromaffin tissue from adrenal medulla. A standard quantitative proteomic analysis of tumor lysate, which provides information largely on non-membrane proteins, was accompanied by specific membrane proteome-aimed methods, namely glycopeptide enrichment using lectin-affinity, glycopeptide capture by hydrazide chemistry, and enrichment of membrane-embedded hydrophobic transmembrane segments.

Results: The study identified 67 cell surface integral membrane proteins strongly upregulated in PPGL compared to control chromaffin tissue. We prioritized the proteins based on their already documented direct role in cancer cell growth or progression. Increased expression of the seven most promising drug targets (CD146, CD171, ANO1, CD39, ATP8A1, ACE and SLC7A1) were confirmed using specific antibodies. Our experimental strategy also provided expression data for soluble proteins. Among the druggable non-membrane enzymes upregulated in PPGL, we identified three potential drug targets (SHMT2, ARG2 and autotaxin) and verified their upregulated expression.

Conclusions: Application of a combined proteomic strategy recently presented as "Pitchfork" enabled quantitative analysis of both, membrane and non-membrane proteome, and resulted in identification of 10 potential drug targets in human PPGL. Seven membrane proteins localized on the cell surface and three non-membrane druggable enzymes proteins were identified and verified as significantly upregulated in PPGL. All the proteins have been previously shown to be upregulated in several human cancers, and play direct role in cancer progression. Marked upregulation of these proteins along with their localization and established direct roles in tumor progression make these molecules promising candidates as drug targets or proteins for sensitive PPGL imaging.