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Proteomics and Nucleotide Profiling as Tools for Biomarker and Drug Target Discovery

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A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Pathology, Diagnostics, and Therapeutics".

Deadline for manuscript submissions: closed (31 October 2020) | Viewed by 39829

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Prof. Dr. Bent Honoré

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1. Department of Biomedicine, Aarhus University, Aarhus, Denmark
2. Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
Interests: discovery based and targeted proteomics; tandem mass spectrometry; protein biomarkers; lymphoma; eye diseases; cardiovascular diseases
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Gregory Edward Rice

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Guest Editor

Exosome Biology Laboratory, Centre for Clinical Diagnostics, University of Queensland Centre for Clinical Research, Royal Brisbane and Women's Hospital, Brisbane, QLD, Australia
Interests: in vitro diagnostics; endogenous nanoparticles; miRNA; biomarker discovery; complications of pregnancy; gynaecological oncology; research quality management systems

Prof. Dr. Henrik Vorum

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Guest Editor

1. Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
2. Department of Ophthalmology, Aalborg University Hospital, Aalborg, Denmark
Interests: ocular proteomics; ophthalmology; biomarkers (diagnostic, prognostic, predictive, etc.); proteomics methods (2D-PAGE, LC-MS, protein arrays); discovery based proteomics; drug targets; bioinformatics

Special Issue Information

Dear Colleagues,

Separate developments of a wide variety of techniques including two-dimensional gel electrophoresis (2D-PAGE), mass spectrometry (MS), construction of databases with structural information as well as the development of software applications and computer science formed the basis for the field of proteomics some decades ago. The field has shown tremendous advancement ever since, especially more recently. Proteins originate from protein-coding RNA. More recently, non-coding RNAs have been shown to be important regulators of cell function, biomarkers of pathology and as putative clinical interventions.

This Special Issue addresses the challenges in the application of proteomic analysis and nucleotide profiling to support clinical decisions based on the mapping of disease-associated protein and nucleotide changes that may highlight protein and nucleotide candidates as biomarkers or drug targets. Challenges include the establishment of protocols to reliably prepare proteins or nucleotides from a variety of sample sources including cell preparations, frozen solid tumours or formalin-fixed paraffin-embedded (FFPE) tissue to liquids like plasma or cerebrospinal fluid that may each present heterogeneity or a high dynamic range of protein concentrations, different posttranslational modifications, etc. Descriptions of efforts to address such issues as well as technological developments and advances in software applications are highly welcome.

This Special Issue calls for original research manuscripts, communications and reviews that describe the current knowledge and future perspectives in the development of proteomics and nucleotide-based techniques to reveal candidate biomarkers or drug targets for diseases. Topics include but are not limited to the keywords below.

Prof. Dr. Bent Honoré
Prof. Dr. Gregory Edward Rice
Prof. Dr. Henrik Vorum
Guest Editors

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Molecular Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

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Keywords

Sample preparation (frozen tissue, FFPE tissue, cells, plasma, CSF, urine, etc.)
Proteomic methods (2D-PAGE, LC-MS, protein arrays)
Discovery-based and targeted proteomics
SWATH (sequential windowed acquisition of all theoretical mass spectra) MS
Biomarkers (diagnostic, prognostic, predictive, etc.)
Drug targets
Bioinformatics
miRNA
aptamers
nanoparticle methods

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Published Papers (10 papers)

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Editorial

Jump to: Research, Review

4 pages, 205 KiB

Open AccessEditorial

Proteomics and Nucleotide Profiling as Tools for Biomarker and Drug Target Discovery

by Bent Honoré, Gregory Edward Rice and Henrik Vorum

Int. J. Mol. Sci. 2021, 22(20), 11031; https://doi.org/10.3390/ijms222011031 - 13 Oct 2021

Cited by 2 | Viewed by 1597

Abstract

Proteomics has gone through tremendous development during recent decades [...] Full article

(This article belongs to the Special Issue Proteomics and Nucleotide Profiling as Tools for Biomarker and Drug Target Discovery)

Research

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16 pages, 4102 KiB

Open AccessArticle

Classification of Thyroid Tumors Based on Mass Spectrometry Imaging of Tissue Microarrays; a Single-Pixel Approach

by Agata Kurczyk, Marta Gawin, Mykola Chekan, Agata Wilk, Krzysztof Łakomiec, Grzegorz Mrukwa, Katarzyna Frątczak, Joanna Polanska, Krzysztof Fujarewicz, Monika Pietrowska and Piotr Widlak

Int. J. Mol. Sci. 2020, 21(17), 6289; https://doi.org/10.3390/ijms21176289 - 31 Aug 2020

Cited by 15 | Viewed by 3812

Abstract

The primary diagnosis of thyroid tumors based on histopathological patterns can be ambiguous in some cases, so proper classification of thyroid diseases might be improved if molecular biomarkers support cytological and histological assessment. In this work, tissue microarrays representative for major types of thyroid malignancies—papillary thyroid cancer (classical and follicular variant), follicular thyroid cancer, anaplastic thyroid cancer, and medullary thyroid cancer—and benign thyroid follicular adenoma and normal thyroid were analyzed by mass spectrometry imaging (MSI), and then different computation approaches were implemented to test the suitability of the registered profiles of tryptic peptides for tumor classification. Molecular similarity among all seven types of thyroid specimens was estimated, and multicomponent classifiers were built for sample classification using individual MSI spectra that corresponded to small clusters of cells. Moreover, MSI components showing the most significant differences in abundance between the compared types of tissues detected and their putative identity were established by annotation with fragments of proteins identified by liquid chromatography-tandem mass spectrometry in corresponding tissue lysates. In general, high accuracy of sample classification was associated with low inter-tissue similarity index and a high number of components with significant differences in abundance between the tissues. Particularly, high molecular similarity was noted between three types of tumors with follicular morphology (adenoma, follicular cancer, and follicular variant of papillary cancer), whose differentiation represented the major classification problem in our dataset. However, low level of the intra-tissue heterogeneity increased the accuracy of classification despite high inter-tissue similarity (which was exemplified by normal thyroid and benign adenoma). We compared classifiers based on all detected MSI components (n = 1536) and the subset of the most abundant components (n = 147). Despite relatively higher contribution of components with significantly different abundance and lower overall inter-tissue similarity in the latter case, the precision of classification was generally higher using all MSI components. Moreover, the classification model based on individual spectra (a single-pixel approach) outperformed the model based on mean spectra of tissue cores. Our result confirmed the high feasibility of MSI-based approaches to multi-class detection of cancer types and proved the good performance of sample classification based on individual spectra (molecular image pixels) that overcame problems related to small amounts of heterogeneous material, which limit the applicability of classical proteomics. Full article

(This article belongs to the Special Issue Proteomics and Nucleotide Profiling as Tools for Biomarker and Drug Target Discovery)

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11 pages, 1236 KiB

Open AccessArticle

Affinity Capture Enrichment versus Affinity Depletion: A Comparison of Strategies for Increasing Coverage of Low-Abundant Human Plasma Proteins

by Nicolai Bjødstrup Palstrøm, Lars Melholt Rasmussen and Hans Christian Beck

Int. J. Mol. Sci. 2020, 21(16), 5903; https://doi.org/10.3390/ijms21165903 - 17 Aug 2020

Cited by 27 | Viewed by 4339

Abstract

In the present study, we evaluated four small molecule affinity-based probes based on agarose-immobilized benzamidine (ABA), O-Phospho-L-Tyrosine (pTYR), 8-Amino-hexyl-cAMP (cAMP), or 8-Amino-hexyl-ATP (ATP) for their ability to remove high-abundant proteins such as serum albumin from plasma samples thereby enabling the detection of medium-to-low abundant proteins in plasma samples by mass spectrometry-based proteomics. We compared their performance with the most commonly used immunodepletion method, the Multi Affinity Removal System Human 14 (MARS14) targeting the top 14 most abundant plasma proteins and also the ProteoMiner protein equalization method by label-free quantitative liquid chromatography tandem mass spectrometry (LC-MSMS) analysis. The affinity-based probes demonstrated a high reproducibility for low-abundant plasma proteins, down to picomol per mL levels, compared to the Multi Affinity Removal System (MARS) 14 and the Proteominer methods, and also demonstrated superior removal of the majority of the high-abundant plasma proteins. The ABA-based affinity probe and the Proteominer protein equalization method performed better compared to all other methods in terms of the number of analyzed proteins. All the tested methods were highly reproducible for both high-abundant plasma proteins and low-abundant proteins as measured by correlation analyses of six replicate experiments. In conclusion, our results demonstrated that small-molecule based affinity-based probes are excellent alternatives to the commonly used immune-depletion methods for proteomic biomarker discovery studies in plasma. Data are available via ProteomeXchange with identifier PXD020727. Full article

(This article belongs to the Special Issue Proteomics and Nucleotide Profiling as Tools for Biomarker and Drug Target Discovery)

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26 pages, 3009 KiB

Open AccessArticle

A Comprehensive Proteomic SWATH-MS Workflow for Profiling Blood Extracellular Vesicles: A New Avenue for Glioma Tumour Surveillance

by Susannah Hallal, Ali Azimi, Heng Wei, Nicholas Ho, Maggie Yuk Ting Lee, Hao-Wen Sim, Joanne Sy, Brindha Shivalingam, Michael Edward Buckland and Kimberley Louise Alexander-Kaufman

Int. J. Mol. Sci. 2020, 21(13), 4754; https://doi.org/10.3390/ijms21134754 - 3 Jul 2020

Cited by 38 | Viewed by 5403

Abstract

Improving outcomes for diffuse glioma patients requires methods that can accurately and sensitively monitor tumour activity and treatment response. Extracellular vesicles (EV) are membranous nanoparticles that can traverse the blood–brain-barrier, carrying oncogenic molecules into the circulation. Measuring clinically relevant glioma biomarkers cargoed in circulating EVs could revolutionise how glioma patients are managed. Despite their suitability for biomarker discovery, the co-isolation of highly abundant complex blood proteins has hindered comprehensive proteomic studies of circulating-EVs. Plasma-EVs isolated from pre-operative glioma grade II–IV patients (n = 41) and controls (n = 11) were sequenced by Sequential window acquisition of all theoretical fragment ion spectra mass spectrometry (SWATH-MS) and data extraction was performed by aligning against a custom 8662-protein library. Overall, 4054 proteins were measured in plasma-EVs. Differentially expressed proteins and putative circulating-EV markers were identified (adj. p-value < 0.05), including those reported in previous in-vitro and ex-vivo glioma-EV studies. Principal component analysis showed that plasma-EV protein profiles clustered according to glioma histological-subtype and grade, and plasma-EVs resampled from patients with recurrent tumour progression grouped with more aggressive glioma samples. The extensive plasma-EV proteome profiles achieved here highlight the potential for SWATH-MS to define circulating-EV biomarkers for objective blood-based measurements of glioma activity that could serve as ideal surrogate endpoints to assess tumour progression and allow more dynamic, patient-centred treatment protocols. Full article

(This article belongs to the Special Issue Proteomics and Nucleotide Profiling as Tools for Biomarker and Drug Target Discovery)

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17 pages, 3226 KiB

Open AccessArticle

Sequesterpene Lactones Isolated from a Brazilian Cerrado Plant (Eremanthus spp.) as Anti-Proliferative Compounds, Characterized by Functional and Proteomic Analysis, Are Candidates for New Therapeutics in Glioblastoma

by Clarice Izumi, Helen Julie Laure, Nayara Gonçalves Barbosa, Carolina Hassibe Thomé, Germano Aguiar Ferreira, João Paulo Barreto Sousa, Norberto Peporine Lopes and José César Rosa

Int. J. Mol. Sci. 2020, 21(13), 4713; https://doi.org/10.3390/ijms21134713 - 1 Jul 2020

Cited by 8 | Viewed by 2387

Abstract

Gliomas are responsible for more than 60% of all primary brain tumors. Glioblastoma multiforme (GBM), a grade IV tumor (WHO), is one of the most frequent and malignant gliomas. Despite two decades of advances in the discovery of new markers for GBM, the chemotherapy of choice falls to temozolomide after surgery and radiotherapy, which are not enough to increase the survival of patients to more than 15 months. It is urgent to discover new anti-glioma compounds. Many compounds derived from natural products have been used in the development of anti-tumor drugs. In this work, we have screened six low molecular weight sesquiterpene lactones, isolated from Eremanthus spp., and studied their function as anti-proliferative agents against GBM strains. We demonstrated that two of them, goyazensolide and lychnofolide, were effective in reducing cell viability, preventing the formation of anchorage-dependent colony and were able to pass through a mimetic blood-brain barrier making them candidates for glioma therapy, being more potent than temozolomide, according to in vitro assays for the cell lines tested. Proteomic analysis revealed a number of altered proteins involved in glycolytic metabolism and cellular catabolism. Full article

(This article belongs to the Special Issue Proteomics and Nucleotide Profiling as Tools for Biomarker and Drug Target Discovery)

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18 pages, 3189 KiB

Open AccessArticle

Proteomic Characterization of Colorectal Cancer Cells versus Normal-Derived Colon Mucosa Cells: Approaching Identification of Novel Diagnostic Protein Biomarkers in Colorectal Cancer

by Maja Ludvigsen, Louise Thorlacius-Ussing, Henrik Vorum, Mary Pat Moyer, Mogens Tornby Stender, Ole Thorlacius-Ussing and Bent Honoré

Int. J. Mol. Sci. 2020, 21(10), 3466; https://doi.org/10.3390/ijms21103466 - 14 May 2020

Cited by 26 | Viewed by 4561

Abstract

In the western world, colorectal cancer (CRC) is the third most common cause of cancer-related deaths. Survival is closely related to the stage of cancer at diagnosis striking the clinical need for biomarkers capable of early detection. To search for possible biological parameters for early diagnosis of CRC we evaluated protein expression for three CREC (acronym: Cab45, reticulocalbin, ERC-55, calumenin) proteins: reticulocalbin, calumenin, and ERC-55 in a cellular model consisting of a normal derived colon mucosa cell line, NCM460, and a primary adenocarcinoma cell line of the colon, SW480. Furthermore, this cellular model was analyzed by a top-down proteomic approach, 2-dimensional polyacrylamide gel electrophoresis (2D-PAGE) and liquid chromatography–tandem mass spectrometry (LC–MS/MS) for novel putative diagnostic markers by identification of differentially expressed proteins between the two cell lines. A different colorectal carcinoma cell line, HCT 116, was used in a bottom-up proteomic approach with label-free quantification (LFQ) LC–MS/MS. The two cellular models gave sets of putative diagnostic CRC biomarkers. Various of these novel putative markers were verified with increased expression in CRC patient neoplastic tissue compared to the expression in a non-involved part of the colon, including reticulocalbin, calumenin, S100A6 and protein SET. Characterization of these novel identified biological features for CRC patients may have diagnostic potential and therapeutic relevance in this malignancy characterized by a still unmet clinical need. Full article

(This article belongs to the Special Issue Proteomics and Nucleotide Profiling as Tools for Biomarker and Drug Target Discovery)

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18 pages, 6124 KiB

Open AccessArticle

Morphometric, Hemodynamic, and Multi-Omics Analyses in Heart Failure Rats with Preserved Ejection Fraction

by Wenxi Zhang, Huan Zhang, Weijuan Yao, Li Li, Pei Niu, Yunlong Huo and Wenchang Tan

Int. J. Mol. Sci. 2020, 21(9), 3362; https://doi.org/10.3390/ijms21093362 - 9 May 2020

Cited by 23 | Viewed by 4839

Abstract

(1) Background: There are no successive treatments for heart failure with preserved ejection fraction (HFpEF) because of complex interactions between environmental, histological, and genetic risk factors. The objective of the study is to investigate changes in cardiomyocytes and molecular networks associated with HFpEF. (2) Methods: Dahl salt-sensitive (DSS) rats developed HFpEF when fed with a high-salt (HS) diet for 7 weeks, which was confirmed by in vivo and ex vivo measurements. Shotgun proteomics, microarray, Western blot, and quantitative RT-PCR analyses were further carried out to investigate cellular and molecular mechanisms. (3) Results: Rats with HFpEF showed diastolic dysfunction, impaired systolic function, and prolonged repolarization of myocytes, owing to an increase in cell size and apoptosis of myocytes. Heatmap of multi-omics further showed significant differences between rats with HFpEF and controls. Gene Set Enrichment Analysis (GSEA) of multi-omics revealed genetic risk factors involved in cardiac muscle contraction, proteasome, B cell receptor signaling, and p53 signaling pathway. Gene Ontology (GO) analysis of multi-omics showed the inflammatory response and mitochondrial fission as top biological processes that may deteriorate myocyte stiffening. GO analysis of protein-to-protein network indicated cytoskeleton protein, cell fraction, enzyme binding, and ATP binding as the top enriched molecular functions. Western blot validated upregulated Mff and Itga9 and downregulated Map1lc3a in the HS group, which likely contributed to accumulation of aberrant mitochondria to increase ROS and elevation of myocyte stiffness, and subsequent contractile dysfunction and myocardial apoptosis. (4) Conclusions: Multi-omics analysis revealed multiple pathways associated with HFpEF. This study shows insight into molecular mechanisms for the development of HFpEF and may provide potential targets for the treatment of HFpEF. Full article

(This article belongs to the Special Issue Proteomics and Nucleotide Profiling as Tools for Biomarker and Drug Target Discovery)

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14 pages, 968 KiB

Open AccessArticle

Proteomic Analysis of Renal Biomarkers of Kidney Allograft Fibrosis—A Study in Renal Transplant Patients

by Line Aas Mortensen, Anne Marie Svane, Mark Burton, Claus Bistrup, Helle Charlotte Thiesson, Niels Marcussen and Hans Christian Beck

Int. J. Mol. Sci. 2020, 21(7), 2371; https://doi.org/10.3390/ijms21072371 - 30 Mar 2020

Cited by 11 | Viewed by 3077

Abstract

Renal transplantation is the preferred treatment of end stage renal disease, but allograft survival is limited by the development of interstitial fibrosis and tubular atrophy in response to various stimuli. Much effort has been put into identifying new protein markers of fibrosis to support the diagnosis. In the present work, we performed an in-depth quantitative proteomics analysis of allograft biopsies from 31 prevalent renal transplant patients and correlated the quantified proteins with the volume fraction of fibrosis as determined by a morphometric method. Linear regression analysis identified four proteins that were highly associated with the degree of interstitial fibrosis, namely Coagulation Factor XIII A chain (estimate 18.7, adjusted p < 0.03), Uridine Phosphorylase 1 (estimate 19.4, adjusted p < 0.001), Actin-related protein 2/3 subunit 2 (estimate 34.2, adjusted p < 0.05) and Cytochrome C Oxidase Assembly Factor 6 homolog (estimate −44.9, adjusted p < 0.002), even after multiple testing. Proteins that were negatively associated with fibrosis (p < 0.005) were primarily related to normal metabolic processes and respiration, whereas proteins that were positively associated with fibrosis (p < 0.005) were involved in catabolic processes, cytoskeleton organization and the immune response. The identified proteins may be candidates for further validation with regards to renal fibrosis. The results support the notion that cytoskeleton organization and immune responses are prevalent processes in renal allograft fibrosis. Full article

(This article belongs to the Special Issue Proteomics and Nucleotide Profiling as Tools for Biomarker and Drug Target Discovery)

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19 pages, 3846 KiB

Open AccessArticle

Gel-Based Proteomics of Clinical Samples Identifies Potential Serological Biomarkers for Early Detection of Colorectal Cancer

by Stine F. Thorsen, Irina Gromova, Ib J. Christensen, Simon Fredriksson, Claus L. Andersen, Hans J. Nielsen, Jan Stenvang and José M.A. Moreira

Int. J. Mol. Sci. 2019, 20(23), 6082; https://doi.org/10.3390/ijms20236082 - 2 Dec 2019

Cited by 8 | Viewed by 4090

Abstract

The burden of colorectal cancer (CRC) is considerable—approximately 1.8 million people are diagnosed each year with CRC and of these about half will succumb to the disease. In the case of CRC, there is strong evidence that an early diagnosis leads to a better prognosis, with metastatic CRC having a 5-year survival that is only slightly greater than 10% compared with up to 90% for stage I CRC. Clearly, biomarkers for the early detection of CRC would have a major clinical impact. We implemented a coherent gel-based proteomics biomarker discovery platform for the identification of clinically useful biomarkers for the early detection of CRC. Potential protein biomarkers were identified by a 2D gel-based analysis of a cohort composed of 128 CRC and site-matched normal tissue biopsies. Potential biomarkers were prioritized and assays to quantitatively measure plasma expression of the candidate biomarkers were developed. Those biomarkers that fulfilled the preset criteria for technical validity were validated in a case-control set of plasma samples, including 70 patients with CRC, adenomas, or non-cancer diseases and healthy individuals in each group. We identified 63 consistently upregulated polypeptides (factor of four-fold or more) in our proteomics analysis. We selected 10 out of these 63 upregulated polypeptides, and established assays to measure the concentration of each one of the ten biomarkers in plasma samples. Biomarker levels were analyzed in plasma samples from healthy individuals, individuals with adenomas, CRC patients, and patients with non-cancer diseases and we identified one protein, tropomyosin 3 (Tpm3) that could discriminate CRC at a significant level (p = 0.0146). Our results suggest that at least one of the identified proteins, Tpm3, could be used as a biomarker in the early detection of CRC, and further studies should provide unequivocal evidence for the real-life clinical validity and usefulness of Tpm3. Full article

(This article belongs to the Special Issue Proteomics and Nucleotide Profiling as Tools for Biomarker and Drug Target Discovery)

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Review

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14 pages, 1601 KiB

Open AccessReview

Antibodies, Nanobodies, or Aptamers—Which Is Best for Deciphering the Proteomes of Non-Model Species?

by Poshmaal Dhar, Rasika M. Samarasinghe and Sarah Shigdar

Int. J. Mol. Sci. 2020, 21(7), 2485; https://doi.org/10.3390/ijms21072485 - 3 Apr 2020

Cited by 26 | Viewed by 4967

Abstract

This planet is home to countless species, some more well-known than the others. While we have developed many techniques to be able to interrogate some of the “omics”, proteomics is becoming recognized as a very important part of the puzzle, given how important the protein is as a functional part of the cell. Within human health, the proteome is fairly well-established, with numerous reagents being available to decipher cellular pathways. Recent research advancements have assisted in characterizing the proteomes of some model (non-human) species, however, in many other species, we are only just touching the surface. This review considers three main reagent classes—antibodies, aptamers, and nanobodies—as a means of continuing to investigate the proteomes of non-model species without the complications of understanding the full protein signature of a species. Considerations of ease of production, potential applications, and the necessity for producing a new reagent depending on homology are presented. Full article

(This article belongs to the Special Issue Proteomics and Nucleotide Profiling as Tools for Biomarker and Drug Target Discovery)

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