Identification of hnRNP-A1 as a pharmacodynamic biomarker of type I PRMT inhibition in blood and tumor tissues

Medicinal chemistry insights into PRMT5 inhibitors

Protein arginine methyltransferase 5 (PRMT5) is a type II PRMT enzyme that plays an important role in protein formation. PRMT5 is widely distributed in the nucleus and is involved in regulating a variety of biological processes, including gene transcription, signaling, and cell proliferation. PRMT5 regulates the function and stability of histones through methylation, affecting important cellular activities such as cell cycle regulation, DNA repair, and RNA processing. Studies have shown that PRMT5 is overexpressed in a variety of tumors and is closely related to the occurrence and development of tumors. In recent years, several PRMT5 inhibitors have entered clinical trials for the treatment of various cancers. In view of their importance, this paper reviews the first generation of PRMT5 inhibitors obtained by high-throughput screening, virtual screening, lead compound optimization and substitution modification, as well as novel PRMT5 inhibitors obtained by PROTAC technology and by synthetic lethal principle. Finally, by comparing the differences between the first generation and the second generation, the challenges and future development directions of PRMT5 inhibitors are discussed.

Phase 1 study of GSK3368715, a type I PRMT inhibitor, in patients with advanced solid tumors

BACKGROUND

GSK3368715, a first-in-class, reversible inhibitor of type I protein methyltransferases (PRMTs) demonstrated anticancer activity in preclinical studies. This Phase 1 study (NCT03666988) evaluated safety, pharmacokinetics, pharmacodynamics, and preliminary efficacy of GSK3368715 in adults with advanced-stage solid tumors.

METHODS

In part 1, escalating doses of oral once-daily GSK3368715 (50, 100, and 200 mg) were evaluated. Enrollment was paused at 200 mg following a higher-than-expected incidence of thromboembolic events (TEEs) among the first 19 participants, resuming under a protocol amendment starting at 100 mg. Part 2 (to evaluate preliminary efficacy) was not initiated.

RESULTS

Dose-limiting toxicities were reported in 3/12 (25%) patients at 200 mg. Nine of 31 (29%) patients across dose groups experienced 12 TEEs (8 grade 3 events and 1 grade 5 pulmonary embolism). Best response achieved was stable disease, occurring in 9/31 (29%) patients. Following single and repeat dosing, GSK3368715 maximum plasma concentration was reached within 1 h post dosing. Target engagement was observed in the blood, but was modest and variable in tumor biopsies at 100 mg.

CONCLUSION

Based on higher-than-expected incidence of TEEs, limited target engagement at lower doses, and lack of observed clinical efficacy, a risk/benefit analysis led to early study termination.

TRIAL REGISTRATION NUMBER

NCT03666988.

SMGR: a joint statistical method for integrative analysis of single-cell multi-omics data

Unravelling the regulatory programs from single-cell multi-omics data has long been one of the major challenges in genomics, especially in the current emerging single-cell field. Currently there is a huge gap between fast-growing single-cell multi-omics data and effective methods for the integrative analysis of these inherent sparse and heterogeneous data. In this study, we have developed a novel method, Single-cell Multi-omics Gene co-Regulatory algorithm (SMGR), to detect coherent functional regulatory signals and target genes from the joint single-cell RNA-sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) data obtained from different samples. Given that scRNA-seq and scATAC-seq data can be captured by zero-inflated Negative Binomial distribution, we utilize a generalized linear regression model to identify the latent representation of consistently expressed genes and peaks, thus enables the identification of co-regulatory programs and the elucidation of regulating mechanisms. Results from both simulation and experimental data demonstrate that SMGR outperforms the existing methods with considerably improved accuracy. To illustrate the biological insights of SMGR, we apply SMGR to mixed-phenotype acute leukemia (MPAL) and identify the MPAL-specific regulatory program with significant peak-gene links, which greatly enhance our understanding of the regulatory mechanisms and potential targets of this complex tumor.

2021 White Paper on Recent Issues in Bioanalysis: Mass Spec of Proteins, Extracellular Vesicles, CRISPR, Chiral Assays, Oligos; Nanomedicines Bioanalysis; ICH M10 Section 7.1; Non-Liquid & Rare Matrices; Regulatory Inputs (Part 1A - Recommendations on Endogenous Compounds, Small Molecules, Complex Methods, Regulated Mass Spec of Large Molecules, Small Molecule, PoC & Part 1B - Regulatory Agencies' Inputs on Bioanalysis, Biomarkers, Immunogenicity, Gene & Cell Therapy and Vaccine)

The 15th edition of the Workshop on Recent Issues in Bioanalysis (15th WRIB) was held on 27 September to 1 October 2021. Even with a last-minute move from in-person to virtual, an overwhelmingly high number of nearly 900 professionals representing pharma and biotech companies, contract research organizations (CROs), and multiple regulatory agencies still eagerly convened to actively discuss the most current topics of interest in bioanalysis. The 15th WRIB included 3 Main Workshops and 7 Specialized Workshops that together spanned 1 week in order to allow exhaustive and thorough coverage of all major issues in bioanalysis, biomarkers, immunogenicity, gene therapy, cell therapy and vaccines. Moreover, in-depth workshops on biomarker assay development and validation (BAV) (focused on clarifying the confusion created by the increased use of the term "Context of Use - COU"); mass spectrometry of proteins (therapeutic, biomarker and transgene); state-of-the-art cytometry innovation and validation; and, critical reagent and positive control generation were the special features of the 15th edition. This 2021 White Paper encompasses recommendations emerging from the extensive discussions held during the workshop, and is aimed to provide the bioanalytical community with key information and practical solutions on topics and issues addressed, in an effort to enable advances in scientific excellence, improved quality and better regulatory compliance. Due to its length, the 2021 edition of this comprehensive White Paper has been divided into three parts for editorial reasons. This publication (Part 1A) covers the recommendations on Endogenous Compounds, Small Molecules, Complex Methods, Regulated Mass Spec of Large Molecules, Small Molecule, PoC. Part 1B covers the Regulatory Agencies' Inputs on Bioanalysis, Biomarkers, Immunogenicity, Gene & Cell Therapy and Vaccine. Part 2 (ISR for Biomarkers, Liquid Biopsies, Spectral Cytometry, Inhalation/Oral & Multispecific Biotherapeutics, Accuracy/LLOQ for Flow Cytometry) and Part 3 (TAb/NAb, Viral Vector CDx, Shedding Assays; CRISPR/Cas9 & CAR-T Immunogenicity; PCR & Vaccine Assay Performance; ADA Assay Comparabil ity & Cut Point Appropriateness) are published in volume 14 of Bioanalysis, issues 10 and 11 (2022), respectively.

Love is in the hair: arginine methylation of human hair proteins as novel cardiovascular biomarkers

Cardiovascular disease is the major cause of death worldwide. Extensive cardiovascular biomarkers are available using blood tests but very few, if any, investigations have described non-invasive tests for cardiovascular biomarkers based on readily available hair samples. Here we show, first, that human hair proteins are post-translationally modified by arginine methylation (ArgMe). Using western blot, proteomic data mining and mass spectrometry, we identify several ArgMe events in hair proteins and we show that keratin-83 is extensively modified by ArgMe in the human hair. Second, using a preliminary cohort (n = 18) of heterogenous healthy donors, we show that the levels of protein ArgMe in hair correlate with serum concentrations of a well-established cardiovascular biomarker, asymmetric dimethylarginine (ADMA). Compared to blood collection, hair sampling is cheaper, simpler, requires minimal training and carries less health and safety and ethical risks. For these reasons, developing the potential of hair protein ArgMe as clinically useful cardiovascular biomarkers through further research could be useful in future prevention and diagnosis of cardiovascular disease.

Affinity capture in bottom-up protein analysis - Overview of current status of proteolytic peptide capture using antibodies and molecularly imprinted polymers

Antibody-based affinity capture has become the gold standard in sample preparation for determination of low-abundance protein biomarkers in biological matrices prior to liquid chromatography-mass spectrometry (LC-MS) determination. This comprises both capture of intact proteins prior to the digestion step and capture of proteolytic peptides after digestion of the sample. The latter can be performed both using antibodies specifically developed to capture target proteolytic peptides, as well as by the less explored use of anti-protein antibodies to capture the proteolytic epitope peptide. Molecularly imprinted polymers (MIPs), also called plastic antibodies are another affinity-based approach emerging as sample preparation technique in LC-MS based protein biomarker analysis. The current review gives a critical and comprehensive overview of proteolytic peptide capture using antibodies and MIPs in LC-MS based protein biomarker determination during the last five years. The main emphasis is on capture of non-modified peptides, while a brief overview of affinity capture of peptides containing post-translational modifications (PTMs) is provided.

Proteomics in the pharmaceutical and biotechnology industry: a look to the next decade

INTRODUCTION

Pioneering technologies such as proteomics have helped fuel the biotechnology and pharmaceutical industry with the discovery of novel targets and an intricate understanding of the activity of therapeutics and their various activities in vitro and in vivo. The field of proteomics is undergoing an inflection point, where new sensitive technologies are allowing intricate biological pathways to be better understood, and novel biochemical tools are pivoting us into a new era of chemical proteomics and biomarker discovery. In this review, we describe these areas of innovation, and discuss where the fields are headed in terms of fueling biotechnological and pharmacological research and discuss current gaps in the proteomic technology landscape.

AREAS COVERED

Single cell sequencing and single molecule sequencing. Chemoproteomics. Biological matrices and clinical samples including biomarkers. Computational tools including instrument control software, data analysis.

EXPERT OPINION

Proteomics will likely remain a key technology in the coming decade, but will have to evolve with respect to type and granularity of data, cost and throughput of data generation as well as integration with other technologies to fulfill its promise in drug discovery.

Pan-methylarginine antibody generation using PEG linked GAR motifs as antigens

Arginine methylation is a prevalent posttranslational modification which is deposited by a family of protein arginine methyltransferases (PRMTs), and is found in three different forms in mammalian cells: monomethylarginine (MMA), asymmetric dimethylarginine (ADMA) and symmetric dimethylarginine (SDMA). Pan-methylarginine antibodies are critical for identifying proteins that are methylated on arginine residues, and are also used for evaluating signaling pathways that modulate this methyltransferase activity. Although good pan-MMA, -ADMA and -SDMA antibodies have been developed over the years, there is still room for improvement. Here we use a novel antigen approach, which involves the separation of short methylated motifs with inert polyethylene glycol (PEG) linkers, to generate a set of pan antibodies to the full range of methylarginine marks. Using these antibodies, we observed substrate scavenging by PRMT1, when PRMT5 activity is blocked. Specifically, we find that the splicing factor SmD1 displays increased ADMA levels upon PRMT5 inhibitor treatment. Furthermore, when the catalysis of both SDMA and ADMA is blocked with small molecule inhibitors, we demonstrate that SmD1 and SMN no longer interact. This could partially explain the synergistic effect of PRMT5 and type I PRMT inhibition on RNA splicing and cancer cell growth.