Systems Biology for Drug Target Discovery in Acute Myeloid Leukemia.

Combining new therapeutics with all-trans-retinoic acid (ATRA) could improve the efficiency of acute myeloid leukemia (AML) treatment. Modeling the process of ATRA-induced differentiation based on the transcriptomic profile of leukemic cells resulted in the identification of key targets that can be used to increase the therapeutic effect of ATRA. The genome-scale transcriptome analysis revealed the early molecular response to the ATRA treatment of HL-60 cells. In this study, we performed the transcriptomic profiling of HL-60, NB4, and K562 cells exposed to ATRA for 3-72 h. After treatment with ATRA for 3, 12, 24, and 72 h, we found 222, 391, 359, and 1032 differentially expressed genes (DEGs) in HL-60 cells, as well as 641, 1037, 1011, and 1499 DEGs in NB4 cells. We also found 538 and 119 DEGs in K562 cells treated with ATRA for 24 h and 72 h, respectively. Based on experimental transcriptomic data, we performed hierarchical modeling and determined cyclin-dependent kinase 6 (CDK6), tumor necrosis factor alpha (TNF-alpha), and transcriptional repressor CUX1 as the key regulators of the molecular response to the ATRA treatment in HL-60, NB4, and K562 cell lines, respectively. Mapping the data of TMT-based mass-spectrometric profiling on the modeling schemes, we determined CDK6 expression at the proteome level and its down-regulation at the transcriptome and proteome levels in cells treated with ATRA for 72 h. The combination of therapy with a CDK6 inhibitor (palbociclib) and ATRA (tretinoin) could be an alternative approach for the treatment of acute myeloid leukemia (AML).

Massive Proteogenomic Reanalysis of Publicly Available Proteomic Datasets of Human Tissues in Search for Protein Recoding via Adenosine-to-Inosine RNA Editing.

The proteogenomic search pipeline developed in this work has been applied for reanalysis of 40 publicly available shotgun proteomic datasets from various human tissues comprising more than 8000 individual LC-MS/MS runs, of which 5442 .raw data files were processed in total. This reanalysis was focused on searching for ADAR-mediated RNA editing events, their clustering across samples of different origins, and classification. In total, 33 recoded protein sites were identified in 21 datasets. Of those, 18 sites were detected in at least two datasets, representing the core human protein editome. In agreement with prior artworks, neural and cancer tissues were found to be enriched with recoded proteins. Quantitative analysis indicated that recoding the rate of specific sites did not directly depend on the levels of ADAR enzymes or targeted proteins themselves, rather it was governed by differential and yet undescribed regulation of interaction of enzymes with mRNA. Nine recoding sites conservative between humans and rodents were validated by targeted proteomics using stable isotope standards in the murine brain cortex and cerebellum, and an additional one was validated in human cerebrospinal fluid. In addition to previous data of the same type from cancer proteomes, we provide a comprehensive catalog of recoding events caused by ADAR RNA editing in the human proteome.

Proteomic Signature of Extracellular Vesicles Associated with Colorectal Cancer.

The proteins of extracellular vesicles (EVs) provide proteomic signatures that reflect molecular features of EV-producing cells, including cancer cells. Detection of cancer cell EV proteins is of great interest due to the development of novel predictive diagnostic approaches. Using targeted mass spectrometry with stable-isotope-labeled peptide standards (SIS), we measured in this study the levels of 34 EV-associated proteins in vesicles and whole lysate derived from the colorectal cancer (CRC) cell lines Caco-2, HT29 and HCT116. We also evaluated the abundance of 13 EV-associated proteins (FN1, TLN1, ITGB3, HSPA8, TUBA4A, CD9, CD63, HSPG2, ITGB1, GNAI2, TSG101, PACSIN2, and CDC42) in EVs isolated from blood plasma samples from 11 CRC patients and 20 healthy volunteers. Downregulation of TLN1, ITGB3, and TUBA4A with simultaneous upregulation of HSPG2 protein were observed in cancer samples compared to healthy controls. The proteomic cargo of the EVs associated with CRC represents a promising source of potential prognostic markers.

Electrochemical biosensor for trypsin activity assay based on cleavage of immobilized tyrosine-containing peptide.

In this work, we proposed a biosensor for trypsin proteolytic activity assay using immobilization of model peptides on screen-printed electrodes (SPE) modified with gold nanoparticles (AuNPs) prepared by electrosynthetic method. Sensing of proteolytic activity was based on electrochemical oxidation of tyrosine residues of peptides. We designed peptides containing N-terminal cysteine residue for immobilization on an SPE, modified with gold nanoparticles, trypsin-specific cleavage site and tyrosine residue as a redox label. The peptides were immobilized on SPE by formation of chemical bonds between mercapto groups of the N-terminal cysteine residues and AuNPs. After the incubation with trypsin, time-dependent cleavage of the immobilized peptides was observed by decline in tyrosine electrochemical oxidation signal. The kinetic parameters of trypsin, such as the catalytic constant (kcat), the Michaelis constant (KM) and the catalytic efficiency (kcat/KM), toward the CGGGRYR peptide were determined as 0.33 ± 0.01 min-1, 198 ± 24 nM and 0.0016 min-1 nM-1, respectively. Using the developed biosensor, we demonstrated the possibility of analysis of trypsin specificity toward the peptides with amino acid residues disrupting proteolysis. Further, we designed the peptides with proline or glutamic acid residues after the cleavage site (CGGRPYR and CGGREYR), and trypsin had reduced activity toward both of them according to the existing knowledge of the enzyme specificity. The developed biosensor system allows one to perform a comparative analysis of the protease steady-state kinetic parameters and specificity toward model peptides with different amino acid sequences.

Nuclear Proteomics of Induced Leukemia Cell Differentiation.

Studies of induced granulocytic differentiation help to reveal molecular mechanisms of cell maturation. The nuclear proteome represents a rich source of regulatory molecules, including transcription factors (TFs). It is important to have an understanding of molecular perturbations at the early stages of the differentiation processes. By applying the proteomic quantitative profiling using isobaric labeling, we found that the contents of 214, 319, 376, 426, and 391 proteins were altered at 3, 6, 9, 12, and 72 h, respectively, compared to 0 h in the HL-60 cell nuclear fraction under all-trans-retinoid acid (ATRA) treatment. From 1860 identified nuclear proteins, 231 proteins were annotated as proteins with transcription factor (TF) activity. Six TFs (RREB1, SRCAP, CCDC124, TRIM24, BRD7, and BUD31) were downregulated and three TFs EWSR1, ENO1, and FUS were upregulated at early time points (3-12 h) after ATRA treatment. Bioinformatic annotation indicates involvement of the HL-60 nuclear proteome in DNA damage recognition in the RUNX1-triggered pathway, and in the p53-regulation pathway. By applying scheduled multiple reaction monitoring using stable isotopically labeled peptide standards (MRM/SIS), we found a persistent increase in the content of the following proteins: PRAM1, CEPBP, RBPJ, and HIC1 in the HL-60 cell nuclear fraction during ATRA-induced granulocytic differentiation. In the case of STAT1, CASP3, PARP1, and PRKDC proteins, a transient increase in their content was observed at early time points (3-12 h) after the ATRA treatment. Obtained data on nuclear proteome composition and dynamics during granulocytic differentiation could be beneficial for the development of new treatment approaches for leukemias with the mutated p53 gene.

Number of Detected Proteins as the Function of the Sensitivity of Proteomic Technology in Human Liver Cells.

AIMS: The main goal of the Russian part of C-HPP is to detect and functionally annotate missing proteins (PE2-PE4) encoded by human chromosome 18. To achieve this goal, it is necessary to use the most sensitive methods of analysis. BACKGROUND: However, identifying such proteins in a complex biological mixture using mass spectrometry (MS)-based methods is difficult due to the insufficient sensitivity of proteomic analysis methods. A possible solution to the problem is the pre-fractionation of a complex biological sample at the sample preparation stage. OBJECTIVE: This study aims to measure the detection limit of SRM SIS analysis using a standard set of UPS1 proteins and find a way to enhance the sensitivity of the analysis and to, detect proteins encoded by the human chromosome 18 in liver tissue samples, and compare the data with transcriptomic analysis of the same samples. METHODS: Mass spectrometry, data-dependent acquisition, selected reaction monitoring, highperformance liquid chromatography, data-dependent acquisition in combination with pre-fractionation by alkaline reversed-phase chromatography, selected reaction monitoring in combination with prefractionation by alkaline reversed-phase chromatography methods were used in this study. RESULTS: The results revealed that 100% of UPS1 proteins in a mixture could only be identified at a concentration of at least 10-9 М. The decrease in concentration leads to protein losses associated with technology sensitivity, and no UPS1 protein is detected at a concentration of 10-13 М. Therefore, the two-dimensional fractionation of samples was applied to improve sensitivity. The human liver tissue was examined by selected reaction monitoring and shotgun methods of MS analysis using onedimensional and two-dimensional fractionation to identify the proteins encoded by human chromosome 18. A total of 134 proteins were identified. The overlap between proteomic and transcriptomic data in human liver tissue was ~50%. CONCLUSION: The sample concentration technique is well suited for a standard UPS1 system that is not contaminated with a complex biological sample. However, it is not suitable for use with a complex biological protein mixture. Thus, it is necessary to develop more sophisticated fractionation systems for the detection of all low-copy proteins. This weak convergence is due to the low sensitivity of proteomic technology compared to transcriptomic approaches. Also, total mRNA was used to perform RNA-seq analysis, but not all detected mRNA molecules could be translated into proteins. This introduces additional uncertainty in the data; in the future, we plan to study only translated mRNA molecules-the translatome. Data is available via ProteomeXchange with identifier PXD026997.

Deep proteomic dataset of human liver samples obtained by two-dimensional sample fractionation coupled with tandem mass spectrometry.

The data was acquired from 3 normal human liver tissues by LC-MS methods. The tissue liver samples from male subjects post mortem were obtained from ILSBio LLC (https://bioivt.com/). Liver tissue was frozen in liquid nitrogen, transported and shipped on dry ice. The proteins were extracted and purified followed up by trypsin hydrolysis. The peptide mixture was aliquoted and analyzed by different LC-MS approaches: one-dimensional shotgun LC-MS, two-dimensional LC-MS, two-dimensional SRM SIS (Selected Reaction Monitoring with Stable Isotope-labeled peptide Standards). The Shotgun assay resulted in a qualitative in-depth human liver proteome, and a semi-quantitative iBAQ (intensity-based absolute quantification) value was calculated to show the relative protein content of the sample. Absolute quantitative concentrations of proteins encoded by human chromosome 18 using SRM SIS were obtained.

Proteomic Signature of Extracellular Vesicles for Lung Cancer Recognition.

The proteins of extracellular vesicles (EVs) that originate from tumors reflect the producer cells' proteomes and can be detected in biological fluids. Thus, EVs provide proteomic signatures that are of great interest for screening and predictive cancer diagnostics. By applying targeted mass spectrometry with stable isotope-labeled peptide standards, we assessed the levels of 28 EV-associated proteins, including the conventional exosome markers CD9, CD63, CD81, CD82, and HSPA8, in vesicles derived from the lung cancer cell lines NCI-H23 and A549. Furthermore, we evaluated the detectability of these proteins and their abundance in plasma samples from 34 lung cancer patients and 23 healthy volunteers. The abundance of TLN1, TUBA4A, HSPA8, ITGB3, TSG101, and PACSIN2 in the plasma of lung cancer patients was measured using targeted mass spectrometry and compared to that in plasma from healthy volunteers. The most diagnostically potent markers were TLN1 (AUC, 0.95), TUBA4A (AUC, 0.91), and HSPA8 (AUC, 0.88). The obtained EV proteomic signature allowed us to distinguish between the lung adenocarcinoma and squamous cell carcinoma histological types. The proteomic cargo of the extracellular vesicles represents a promising source of potential biomarkers.

Omics Technologies to Decipher Regulatory Networks in Granulocytic Cell Differentiation.

Induced granulocytic differentiation of human leukemic cells under all-trans-retinoid acid (ATRA) treatment underlies differentiation therapy of acute myeloid leukemia. Knowing the regulation of this process it is possible to identify potential targets for antileukemic drugs and develop novel approaches to differentiation therapy. In this study, we have performed transcriptomic and proteomic profiling to reveal up- and down-regulated transcripts and proteins during time-course experiments. Using data on differentially expressed transcripts and proteins we have applied upstream regulator search and obtained transcriptome- and proteome-based regulatory networks of induced granulocytic differentiation that cover both up-regulated (HIC1, NFKBIA, and CASP9) and down-regulated (PARP1, VDR, and RXRA) elements. To verify the designed network we measured HIC1 and PARP1 protein abundance during granulocytic differentiation by selected reaction monitoring (SRM) using stable isotopically labeled peptide standards. We also revealed that transcription factor CEBPB and LYN kinase were involved in differentiation onset, and evaluated their protein levels by SRM technique. Obtained results indicate that the omics data reflect involvement of the DNA repair system and the MAPK kinase cascade as well as show the balance between the processes of the cell survival and apoptosis in a p53-independent manner. The differentially expressed transcripts and proteins, predicted transcriptional factors, and key molecules such as HIC1, CEBPB, LYN, and PARP1 may be considered as potential targets for differentiation therapy of acute myeloid leukemia.

Proteomic Analysis of Chr 18 Proteins Using 2D Fractionation.

One of the main goals of the Chromosome-Centric Human Proteome Project (C-HPP) is detection of "missing proteins" (PE2-PE4). Using the UPS2 (Universal proteomics standard 2) set as a model to simulate the range of protein concentrations in the cell, we have previously shown that 2D fractionation enables the detection of more than 95% of UPS2 proteins in a complex biological mixture. In this study, we propose a novel experimental workflow for protein detection during the analysis of biological samples. This approach is extremely important in the context of the C-HPP and the neXt-MP50 Challenge, which can be solved by increasing the sensitivity and the coverage of the proteome encoded by a particular human chromosome. In this study, we used 2D fractionation for in-depth analysis of the proteins encoded by human chromosome 18 (Chr 18) in the HepG2 cell line. Use of 2D fractionation increased the sensitivity of the SRM SIS method by 1.3-fold (68 and 88 proteins were identified by 1D fractionation and 2D fractionation, respectively) and the shotgun MS/MS method by 2.5-fold (21 and 53 proteins encoded by Chr 18 were detected by 1D fractionation and 2D fractionation, respectively). The results of all experiments indicate that 111 proteins encoded by human Chr 18 have been identified; this list includes 42% of the Chr 18 protein-coding genes and 67% of the Chr 18 transcriptome species (Illumina RNaseq) in the HepG2 cell line obtained using a single sample. Corresponding mRNAs were not registered for 13 of the detected proteins. The combination of 2D fractionation technology with SRM SIS and shotgun mass spectrometric analysis did not achieve full coverage, i.e., identification of at least one protein product for each of the 265 protein-coding genes of the selected chromosome. To further increase the sensitivity of the method, we plan to use 5-10 crude synthetic peptides for each protein to identify the proteins and select one of the peptides based on the obtained mass spectra for the synthesis of an isotopically labeled standard for subsequent quantitative analysis. Data are available via ProteomeXchange with the identifier PXD019263.

Proteomic Approach for Searching for Universal, Tissue-Specific, and Line-Specific Markers of Extracellular Vesicles in Lung and Colorectal Adenocarcinoma Cell Lines.

Tumor-derived extracellular vesicles (EVs), including exosomes, contain proteins that mirror the molecular landscape of producer cells. Being potentially detectible in biological fluids, EVs are of great interest for the screening of cancer biomarkers. To reveal universal, tissue-specific, and line-specific markers, we performed label-free mass spectrometric profiling of EVs originating from the human colon cancer cell lines Caco-2, HT29, and HCT-116, as well as from the lung cancer cell lines NCI-H23 and A549. A total of 651 proteins was identified in the EV samples using at least two peptides. These proteins were highly enriched in exosome markers. We found 11 universal, eight tissue-specific, and 29 line-specific markers, the levels of which were increased in EVs compared to the whole lysates. The EV proteins were involved in the EGFR, Rap1, integrin, and microRNA signaling associated with metastasis and cancer progression. An EV protein-based assay could be developed as a liquid biopsy tool.

200+ Protein Concentrations in Healthy Human Blood Plasma: Targeted Quantitative SRM SIS Screening of Chromosomes 18, 13, Y, and the Mitochondrial Chromosome Encoded Proteome.

This work continues the series of the quantitative measurements of the proteins encoded by different chromosomes in the blood plasma of a healthy person. Selected Reaction Monitoring with Stable Isotope-labeled peptide Standards (SRM SIS) and a gene-centric approach, which is the basis for the implementation of the international Chromosome-centric Human Proteome Project (C-HPP), were applied for the quantitative measurement of proteins in human blood plasma. Analyses were carried out in the frame of C-HPP for each protein-coding gene of the four human chromosomes: 18, 13, Y, and mitochondrial. Concentrations of proteins encoded by 667 genes were measured in 54 blood plasma samples of the volunteers, whose health conditions were consistent with requirements for astronauts. The gene list included 276, 329, 47, and 15 genes of chromosomes 18, 13, Y, and the mitochondrial chromosome, respectively. This paper does not make claims about the detection of missing proteins. Only 205 proteins (30.7%) were detected in the samples. Of them, 84, 106, 10, and 5 belonged to chromosomes 18, 13, and Y and the mitochondrial chromosome, respectively. Each detected protein was found in at least one of the samples analyzed. The SRM SIS raw data are available in the ProteomeXchange repository (PXD004374, PASS01192).

Increased Sensitivity of Mass Spectrometry by Alkaline Two-Dimensional Liquid Chromatography: Deep Cover of the Human Proteome in Gene-Centric Mode.

Currently, great interest is paid to the identification of "missing" proteins that have not been detected in any biological material at the protein level (PE1). In this paper, using the Universal Proteomic Standard sets 1 and 2 (UPS1 and UPS2, respectively) as an example, we characterized mass spectrometric approaches from the point of view of sensitivity (Sn), specificity (Sp), and accuracy (Ac). The aim of the paper was to show the utility of a mass spectra approach for protein detection. This sets consists of 48 high-purity human proteins without single aminoacid polymorphism (SAP) or post translational modification (PTM). The UPS1 set consists of the same 48 proteins at 5 pmols each, and in UPS2, proteins were grouped into 5 groups in accordance with their molar concentration, ranging from 10-11 to 10-6 M. Single peptides from the 92% and 96% of all sets of proteins could be detected in a pure solution of UPS2 and UPS1, respectively, by selected reaction monitoring with stable isotope-labeled standards (SRM-SIS). We also found that, in the presence of a biological matrix such as Escherichia coli extract or human blood plasma (HBP), SRM-SIS makes it possible to detect from 63% to 79% of proteins in the UPS2 set (sensitivity) with the highest specificity (∼100%) and an accuracy of 80% by increasing the sensitivity of shotgun and selected reaction monitoring combined with a stable-isotope-labeled peptide standard (SRM-SIS technology) by fractionating samples using reverse-phase liquid chromatography under alkaline conditions (2D-LC_alk). It is shown that this technique of sample fractionation allows the SRM-SIS to detect 98% of the single peptides from the proteins present in the pure solution of UPS2 (47 out of 48 proteins). When the extracts of E. coli or Pichia pastoris are added as biological matrixes to the UPS2, 46, and 45 out of 48 proteins (∼95%) can be detected, respectively, using the SRM-SIS combined with 2D-LC_alk. The combination of the 2D-LC_alk SRM-SIS and shotgun technologies allows us to increase the sensitivity up to 100% in the case of the proteins of the UPS2 set. The usage of that technology can be a solution for identifying the so-called "missing" proteins and, eventually, creating the deep proteome of a particular chromosome of tissue or organs. Experimental data have been deposited in the PeptideAtlas SRM Experiment Library with the dataset identifier PASS01192 and the PRIDE repository with the dataset identifier PXD007643.

Application of selected reaction monitoring and parallel reaction monitoring for investigation of HL-60 cell line differentiation.

Targeted mass spectrometry represents a powerful tool for investigation of biological processes. The convenient approach of selected reaction monitoring using stable isotope-labeled peptide standard (SIS) is widely applied for protein quantification. Along with this method, high-resolution parallel reaction monitoring has been increasingly used for protein targeted analysis. Here we applied two targeted approaches (selected reaction monitoring with SIS and label-free parallel reaction monitoring) to investigate expression of 11 proteins during all-trans retinoic acid-induced differentiation of HL-60 cells. In our experiments, we have determined the proteins expression ratio at 3, 24, 48, and 96 h after all-trans retinoic acid treatment in comparison with 0 h, respectively. Expression profiles of four proteins (VAV1, PRAM1, LYN, and CEBPB) were highly correlated ( r > 0.75) and FGR expression was detected on proteome level starting from 24 h by both techniques. For prominent differences (fold change ≥ 2) label-free parallel reaction monitoring is not inferior to selected reaction monitoring with isotopically labeled peptide standards. Differentially expressed proteins, that have been determined in our study, can be considered as potential drug targets for acute myeloid leukemia (AML) treatment.