Use of proteomics for the identification of novel drug targets in brain diseases

In spite of the rapid advances in the development of the new proteomic technologies, there are, to date, relatively fewer studies aiming to explore the neuronal proteome. One of the reasons is the complexity of the brain, which presents high cellular heterogeneity and a unique subcellular compartmentalization. Therefore, tissue fractionation of the brain to enrich proteins of interest will reduce the complexity of the proteomics approach leading to the production of manageable and meaningful results. In this review, general considerations and strategies of proteomics, the advantages and challenges to exploring the neuronal proteome are described and summarized. In addition, this article presents an overview of recent advances of proteomic technologies and shows that proteomics can serve as a valuable tool to globally explore the changes in brain proteome during various disease states. Understanding the molecular basis of brain function will be extremely useful in identifying novel targets for the treatment of brain diseases.     

Isolation of cell surface proteins for mass spectrometry-based proteomics

Defining the cell surface proteome has profound importance for understanding cell differentiation and cell–cell interactions, as well as numerous pathogenic abnormalities. Owing to their hydrophobic nature, plasma membrane proteins that reside on the cell surface pose analytical challenges and, despite efforts to overcome difficulties, remain under-represented in proteomic studies. Limitations in the classically employed ultracentrifugation-based approaches have led to the invention of more elaborate techniques for the purification of cell surface proteins. Three of these methods – cell surface coating with cationic colloidal silica beads, biotinylation and chemical capture of surface glycoproteins – allow for marked enrichment of this subcellular proteome, with each approach offering unique advantages and characteristics for different experiments. In this article, we introduce the principles of each purification method and discuss applications from the recent literature.     

Platelet proteomics applied to the search for novel antiplatelet therapeutic targets

Introduction: Unwanted platelet activation is associated with numerous diseases, mainly thrombosis-related. In this context, proteomics has emerged as a novel tool with potential for drug target discovery and to scrutinize the effects of antiplatelet drugs.

Areas covered: The present review presents the main findings of platelet proteomic studies to date in the context of drug target discovery and perspectives for the future ahead. It includes data and evidences obtained from literature searches on PubMed as well as commentaries derived from the authors’ experience and opinions.

Expert commentary: Platelet proteomics applied to drug target discovery is a young field. Recent studies have shown promising data, especially in the context of coronary artery disease. However, challenges remain such as establishing definitive guidelines for blood collection and platelet isolation, essential to guarantee data reproducibility. Recent advances in quantitative platelet proteomics should lead to novel studies with higher clinical impact in the near future.     

Crosstalk between lncRNAs in the apoptotic pathway and therapeutic targets in cancer

The assertion that a significant portion of the mammalian genome has not been translated and that non-coding RNA accounts for over half of polyadenylate RNA have received much attention. In recent years, increasing evidence proposes non-coding RNAs (ncRNAs) as new regulators of various cellular processes, including cancer progression and nerve damage. Apoptosis is a type of programmed cell death critical for homeostasis and tissue development. Cancer cells often have inhibited apoptotic pathways. It has recently been demonstrated that up/down-regulation of various lncRNAs in certain types of tumors shapes cancer cells' response to apoptotic stimuli. This review discusses the most recent studies on lncRNAs and apoptosis in healthy and cancer cells. In addition, the role of lncRNAs as novel targets for cancer therapy is reviewed here. Finally, since it has been shown that lncRNA expression is associated with specific types of cancer, the potential for using lncRNAs as biomarkers is also discussed.     

Proteins of the Hedgehog signaling pathway as therapeutic targets against cancer

The Hedgehog pathway plays a crucial role in growth and patterning during embryonic development and is involved in stem cell maintenance and proliferation in adult tissues. Mutations that increase the overall activity of the pathway are often associated with a higher incidence of cancers. This article focuses on the mutations, misfoldings and deregulations of the Hedgehog pathway proteins that have been reported to be involved in different tumors, and on small molecules targeting these proteins shown to slow down the growth of certain tumors in various animal models. We propose that proteomics could be a powerful tool to identify new targets of the Hedgehog pathway, enabling the discovery of effective and novel treatments for cancers.     

The role of autophagy in liver cancer: Molecular mechanisms and potential therapeutic targets

Autophagy is an evolutionarily conserved pathway for degradation of cytoplasmic proteins and organelles via lysosome. Proteins coded by the autophagy-related genes (Atgs) are the core molecular machinery in control of autophagy. Among the various biological functions of autophagy identified so far, the link between autophagy and cancer is probably among the most extensively studied and is often viewed as controversial. Autophagy might exert a dual role in cancer development: autophagy can serve as an anti-tumor mechanism, as defective autophagy (e.g., heterozygous knockdown Beclin 1 and Atg7 in mice) promotes the malignant transformation and spontaneous tumors. On the other hand, autophagy functions as a protective or survival mechanism in cancer cells against cellular stress (e.g., nutrient deprivation, hypoxia and DNA damage) and hence promotes tumorigenesis and causes resistance to therapeutic agents. Liver cancer is one of the common cancers with well-established etiological factors including hepatitis virus infection and environmental carcinogens such as aflatoxin and alcohol exposure. In recent years, the involvement of autophagy in liver cancer has been increasingly studied. Here, we aim to provide a systematic review on the close cross-talks between autophagy and liver cancer, and summarize the current status in development of novel liver cancer therapeutic approaches by targeting autophagy. It is believed that understanding the molecular mechanisms underlying the autophagy modulation and liver cancer development may provoke the translational studies that ultimately lead to new therapeutic strategies for liver cancer.     

Advances in ovarian cancer proteomics: the quest for biomarkers and improved therapeutic interventions

Epithelial ovarian cancer is the leading cause of cancer-related death among gynecological cancers due to the asymptomatic nature of the disease, a lack of early detection markers and the development of resistance to current chemotherapeutic agents. Currently available tests (CA-125, transvaginal ultrasound or combination of both) lack the sensitivity and specificity to be useful as an efficient screening tool for surveillance of the general population. Thus, there is an urgent need for the development and validation of new molecular markers that would be both specific and sensitive indicators of disease onset, as well as progression. Proteomic profiling has emerged as a powerful tool to study ovarian cancer in an unbiased way at the molecular level, to monitor the effects of given treatment options and for the discovery of biomarkers. In this review we discuss the challenges associated with proteomics-based biomarker discovery and some recent concepts to potentially overcome these hurdles. Recent proteomics work on ovarian cancer cells and tissues will be discussed in light of obtaining new insights into fundamental biological processes, as well as their potential integration with ongoing biomarker discovery pipelines.     

MHC-associated peptide proteomics enabling highly sensitive detection of immunogenic sequences for the development of therapeutic antibodies with low immunogenicity

ABSTRACT

Immunogenicity is a key factor capable of influencing the efficacy and safety of therapeutic antibodies. A recently developed method called MHC-associated peptide proteomics (MAPPs) uses liquid chromatography/mass spectrometry to identify the peptide sequences derived from a therapeutic protein that are presented by major histocompatibility complex class II (MHC II) on antigen-presenting cells, and therefore may induce immunogenicity. In this study, we developed a MAPPs technique (called Ab-MAPPs) that has high throughput and can efficiently identify the MHC II-presented peptides derived from therapeutic antibodies using magnetic nanoparticle beads coated with a hydrophilic polymer in the immunoprecipitation process. The magnetic beads could identify more peptides and sequence regions originating from infliximab and adalimumab in a shorter measurement time than Sepharose beads, which are commonly used for MAPPs. Several sequence regions identified by Ab-MAPPs from infliximab corresponded to immunogenic sequences reported by other methods, which suggests the method’s high potential for identifying significant sequences involved in immunogenicity. Furthermore, our study suggests that the Ab-MAPPs method can recognize the difference of a single amino acid residue between similar antibody sequences with different levels of T-cell proliferation activity and can identify potentially immunogenic peptides with high binding affinity to MHC II. In conclusion, Ab-MAPPs is useful for identifying the immunogenic sequences of therapeutic antibodies and will contribute to the design of therapeutic antibodies with low immunogenicity during the drug discovery stage.     

Recombinant antibodies for the diagnosis and treatment of cancer

The advent of recombinant antibody technology led to an enormous revival in the use of antibodies as diagnostic and therapeutic tools for fighting cancer. This review provides a brief historical sketch of the development of recombinant antibodies for the diagnosis and immunotherapy of cancer and summarizes the most significant clinical data for the best established reagents to date. It also discusses clinically relevant aspects of the use of recombinant antibodies in cancer patients.     

The exploration of new therapeutic targets for HPV-negative head and neck squamous cell cancer through the construction of a ceRNA network and immune microenvironment analysis

Previous studies have shown that human papillomavirus (HPV)-negative patients with head and neck squamous cell cancer (HNSCC) suffer from an unsatisfactory prognosis. Long noncoding RNAs (lncRNAs) have been verified to participate in many biological processes, including regulating gene expression as competing endogenous RNAs (ceRNAs), while few studies focused the ceRNA network regulation mechanism in patients with HPV-negative HNSCC tumor. Meanwhile, the immune microenvironment may be critical in the development and prognosis of HPV-negative tumors. Our study aimed to further investigate the pathogenesis and potential biomarkers for the diagnosis, therapy and prognosis of HPV-negative HNSCC through a ceRNA network. Comprehensively analyzing the sequencing data of lncRNAs, microRNAs (miRNAs), and messenger RNAs (mRNAs) in The Cancer Genome Atlas HNSCC dataset, we constructed a differentially expressed ceRNA network containing 131 lncRNAs, 35 miRNAs and 162 mRNAs. Then, survival analysis in the network was cited to explore the prognostic biomarkers. Eight mRNAs, nine lncRNAs, and one miRNA were identified to be associated with prognosis. Neuropilin (NRP) binding function, retinoid X receptor (RXR) binding, and the vascular endothelial growth factor (VEGF) signaling pathway were associated with the enrichment analysis, and they also related to the immune microenvironment. Combined with the analysis of the immune microenvironment differences, we obtained new targeted therapies using an RXR agonist, or a combination of the VEGF monoclonal antibody and an NRP antagonist, which may provide a promising future for HPV-negative HNSCC patients.     

The Yin and Yang functions of the Myc oncoprotein in cancer development and as targets for therapy

The Myc proto-oncoprotein coordinates a number of normal physiological processes necessary for growth and expansion of somatic cells by controlling the expression of numerous target genes. Deregulation of MYC as a consequence of carciogenic events enforces cells to undergo a transition to a hyperproliferative state. This increases the risk of additional oncogenic mutations that in turn can result in further tumor progression. However, Myc activation also provokes intrinsic tumor suppressor mechanisms including apoptosis, cellular senescence and DNA damage responses that act as barriers for tumor development and therefore needs to be overcome during tumorigenesis. Myc thus possesses two seemingly contradictory “faces” here referred to as “Yin and Yang”. Observations that many tumor suppressor pathways remain intact but are latent in tumor cells opens the possibility that pharmacological inhibition of the Yin or activation of the Yang functions can prevail and offer new attractive approaches for treating diverse types of cancer.     

Proteomic strategies in the search for novel pancreatic cancer biomarkers and drug targets: recent advances and clinical impact

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers; despite a low incidence rate it is the fourth leading cause of cancer-related death in the world. Improvement of the diagnosis, prognosis and treatment remains the main focus of pancreatic cancer research. Rapid developments in proteomic technologies has improved our understanding of the pancreatic cancer proteome. Here, the authors summarise the recent proteomic strategies undertaken in the search for: novel biomarkers for early diagnosis, pancreatic cancer-specific proteins which may be used for novel targeted therapies and proteins which may be useful for monitoring disease progression post-therapy. Recent advances and findings discussed here provide great promise of having a significant clinical impact and improving the outcome of patients with this malignancy.     

High‐throughput serum proteomics for the identification of protein biomarkers of mortality in older men

The biological perturbations associated with incident mortality are not well elucidated, and there are limited biomarkers for the prediction of mortality. We used a novel high‐throughput proteomics approach to identify serum peptides and proteins associated with 5‐year mortality in community‐dwelling men age ≥65 years who participated in a longitudinal observational study of musculoskeletal aging (Osteoporotic Fractures in Men: MrOS). In a discovery phase, serum specimens collected at baseline in 2473 men were analyzed using liquid chromatography–ion mobility–mass spectrometry, and incident mortality in the subsequent 5 years was ascertained by tri‐annual questionnaire. Rigorous statistical methods were utilized to identify 56 peptides (31 proteins) that were associated with 5‐year mortality. In an independent replication phase, selected reaction monitoring was used to examine 21 of those peptides in baseline serum from 750 additional men; 81% of those peptides remained significantly associated with mortality. Mortality‐associated proteins included a variety involved in inflammation or complement activation; several have been previously linked to mortality (e.g., C‐reactive protein, alpha 1‐antichymotrypsin) and others are not previously known to be associated with mortality. Other novel proteins of interest included pregnancy‐associated plasma protein, VE‐cadherin, leucine‐rich α‐2 glycoprotein 1, vinculin, vitronectin, mast/stem cell growth factor receptor, and Saa4. A panel of peptides improved the predictive value of a commonly used clinical predictor of mortality. Overall, these results suggest that complex inflammatory pathways, and proteins in other pathways, are linked to 5‐year mortality risk. This work may serve to identify novel biomarkers for near‐term mortality.     

Comparative assessment of the therapeutic drug targets of C. botulinum ATCC 3502 and C. difficile str. 630 using in silico subtractive proteomics approach

Growing antimicrobial resistance of the pathogens against multiple drugs posed a serious threat to the human health worldwide. This fueled the need of identifying the novel therapeutic targets that can be used for developing new class of the drugs. Recently, there is a substantial rise in the rate of Clostridium infections as well as in the emergence of virulent and antibiotic resistant strains. Hence, there is an urgent need for the identification of potential therapeutic targets and the development of new drugs for the treatment and prevention of Clostridium infections. In the present study, a combinatorial approach involving systems biology and comparative genomics strategy was tested against Clostridium botulinum ATCC 3502 and Clostridium difficile str. 630 pathogens, to render potential therapeutic target at qualitative and quantitative level. This resulted in the identification of five common (present in both the pathogens, 34 in C. botulinum ATCC 3502 and 42 in C. difficile str. 630) drug targets followed by virtual screening–based identification of potential inhibitors employing molecular docking and molecular dynamics simulations. The identified targets will provide a solid platform for the designing of novel wide-spectrum lead compounds capable of inhibiting their catalytic activities against multidrug-resistant Clostridium in the near future.     

Tangible benefits of the aphid Acyrthosiphon pisum genome sequencing for aphid proteomics: Enhancements in protein identification and data validation for homology-based proteomics

Homology-driven proteomics promises to reveal functional biology in insects with sparse genome sequence information. A proteomics study comparing plant virus transmission competent and refractive genotypes of the aphid Schizaphis graminum isolated numerous candidate proteins involved in virus transmission, but limited genome sequence information hampered their identification. The complete genome of the pea aphid, Acyrthosiphon pisum, released in 2008, enabled us to double the number of protein identifications beyond what was possible using available EST libraries and other insect sequences. This was concomitant with a dramatic increase of the number of MS and MS/MS peptide spectra matching the genome-derived protein sequence. LC-MS/MS proved to be the most robust method of peptide detection. Cross-matching spectral data to multiple EST sequences and error tolerant searching to identify amino acid substitutions enhanced the percent coverage of the Schizaphis graminum proteins. 2-D electrophoresis provided the protein pI and MW which enabled the refinement of the candidate protein selection and provided a measure of protein abundance when coupled to the spectral data. Thus, the homology-based proteomics pipeline for insects should include efforts to maximize the number of peptide matches to the protein to increase certainty in protein identification and relative protein abundance.     

In silico synteny based comparative genomics approach for identification and characterization of novel therapeutic targets in Chlamydophila pneumoniae

Chlamydophila pneumoniae is one of the most important and well studied gram negative bacterial strain with respect to community acquired pneumonia and other respiratory diseases like Chronic obstructive pulmonary disease (COPD), Chronic asthma, Alzheimer''s disease, Atherosclerosis and Multisclerosis which have a great potential to infect humans and many other mammals. According to WHO prediction, COPD is to become the third leading cause of death by 2030. Unfortunately, the molecular mechanisms leading to chronic infections are poorly understood and the difficulty in culturing C pneumoniae in experimental conditions and lack of entirely satisfactory serological methods for diagnosis is also a hurdle for drug discovery and development. We have performed an insilico synteny based comparative genomics analysis of C pneumoniae and other eight Chlamydial organisms to know the potential of C pneumoniae which cause COPD but other Chlamydial organisms lack in potential to cause COPD though some are involved in human pathogenesis. We have identified total 354 protein sequences as non-orthologous to other Chlamydial organisms, except hypothetical proteins 70 were found functional out of which 60 are non homologous to Homo sapiens proteome and among them 18 protein sequences are found to be essential for survival of the C pneumoniae based on BLASTP search against DEG database of essential genes. CELLO analysis results showed that about 80% proteins are found to be cytoplasmic, Among which 5 were found as bacterial exotoxins and 2 as bacterial endotoxins, remaining 11 proteins were found to be involved in DNA binding, RNA binding, catalytic activity, ATP binding, oxidoreductase activity, hydrolase activity and proteolysis activity. It is expected that our data will facilitate selection of C pneumoniae proteins for successful entry into drug design pipelines.     

A novel targeted proteomics method for identification and relative quantitation of difference in nitration degree of OGDH between healthy and diabetic mouse

For analysis of nitration modification of α oxoglutarate dehydrogenase (α‐OGDH) induced by diabetes, a targeted proteomics strategy was developed through the use of Skyline. All peptides containing Y and W of the target proteins were nitrated in silico and output to produce parallel reaction monitoring (PRM) or SRM method for nitration analysis. A nitrated casein mixture was used as standard protein to assess the feasibility of this method. The results demonstrated the availability of this strategy for nitration identification, and subsequently this method was used to analyze the nitration of α‐OGDH from myocardial tissue extracts of diabetic mouse. The PRM method was primarily generated by Skyline for identification of the actual nitrated peptides from all possible nitrated peptides of α‐OGDH due to the complexity of α‐OGDH. The PRM‐based data were analyzed by SEQUEST, and transitions of the identified nitrated peptides were used to develop an SRM method for relative quantitation of nitration degree. The nitration degree of α‐OGDH for diabetic mouse is higher than that for control mouse, indicating that α‐OGDH of the diabetic mouse suffered from more intense oxidative damage. We believe that this approach for obtaining information regarding nitration will facilitate the study of other PTMs in complex mixtures.     

Evaluating the potential of a novel oral lesion exudate collection method coupled with mass spectrometry-based proteomics for oral cancer biomarker discovery

Introduction  

Early diagnosis of Oral Squamous Cell Carcinoma (OSCC) increases the survival rate of oral cancer. For early diagnosis, molecular biomarkers contained in samples collected non-invasively and directly from at-risk oral premalignant lesions (OPMLs) would be ideal.