Advances in structure-based drug design targeting membrane protein markers in prostate cancer

Prostate cancer (PCa) is one of the leading cancers in men and the lack of suitable biomarkers or their modulators results in poor prognosis. Membrane proteins (MPs) have a crucial role in the development and progression of PCa and can be attractive therapeutic targets. However, experimental limitations in targeting MPs hinder effective biomarker and inhibitor discovery. To overcome this barrier, computational methods can yield structural insights and screen large libraries of compounds, accelerating lead identification and optimization. In this review, we examine current breakthroughs in computer-aided drug design (CADD), with emphasis on structure-based approaches targeting the most relevant membrane-bound PCa biomarkers.

Lights on HBME-1: the elusive biomarker in thyroid cancer pathology

Among the different ancillary immunohistochemical tools that pathologists may employ in thyroid nodules, the so-called Hector Battifora's 'MEsothelioma' 1 (HBME-1) staining is one of the most fascinating, since its real identity is currently unknown. In the present review, the different clinical applications of HBME-1 are analysed, with main emphasis on its role in thyroid pathology with overview on less impactful fields, such as haematopathology or mesothelial lesions. Different acceptable or good diagnostic performances were recorded for HBME-1 in thyroid pathology, being used in routine practice as one of the best tools to screen thyroid malignancy both in terms of sensitivity and specificity. From a speculative point of view, after many attempts to hunt the cryptic target antigen of this antibody, its identity still remains elusive. In this setting, the application of high-throughput technologies (mainly in situ proteomics) may be the exact route to improve the knowledge about the pathophysiology of HBME-1 and to finally unveil its true identity.

Proteomic and Glyco(proteo)mic tools in the profiling of cardiac progenitors and pluripotent stem cell derived cardiomyocytes: Accelerating translation into therapy

Research in stem cells paved the way to an enormous amount of knowledge, increasing expectations on cardio regenerative therapeutic approaches in clinic. While the first generation of clinical trials using cell-based therapies in the heart were performed with bone marrow and adipose tissue derived mesenchymal stem cells, second generation cell therapies moved towards the use of cardiac-committed cell populations, including cardiac progenitor cells and pluripotent stem cell derived cardiomyocytes. Despite all these progresses, translating the aptitudes of R&D and pre-clinical data into effective clinical treatments is still highly challenging, partially due to the demanding regulatory and safety concerns but also because of the lack of knowledge on the regenerative mechanisms of action of these therapeutic products. Thus, the need of analytical methodologies that enable a complete characterization of such complex products and a deep understanding of their therapeutic effects, at the cell and molecular level, is imperative to overcome the hurdles of these advanced therapies. Omics technologies, such as proteomics and glyco(proteo)mics workflows based on state of the art mass-spectrometry, have prompted some major breakthroughs, providing novel data on cell biology and a detailed assessment of cell based-products applied in cardiac regeneration strategies. These advanced 'omics approaches, focused on the profiling of protein and glycan signatures are excelling the identification and characterization of cell populations under study, namely unveiling pluripotency and differentiation markers, as well as paracrine mechanisms and signaling cascades involved in cardiac repair. The leading knowledge generated is supporting a more rational therapy design and the rethinking of challenges in Advanced Therapy Medicinal Products development. Herein, we review the most recent methodologies used in the fields of proteomics, glycoproteomics and glycomics and discuss their impact on the study of cardiac progenitor cells and pluripotent stem cell derived cardiomyocytes biology. How these discoveries will impact the speed up of novel therapies for cardiovascular diseases is also addressed.

An overview on enrichment methods for cell surface proteome profiling

Cell surface proteins are essential for many important biological processes, including cell-cell interactions, signal transduction, and molecular transportation. With the characteristics of low abundance, high hydrophobicity, and high heterogeneity, it is difficult to get a comprehensive view of cell surface proteome by direct analysis. Thus, it is important to selectively enrich the cell surface proteins before liquid chromatography with mass spectrometry analysis. In recent years, a variety of enrichment methods have been developed. Based on the separation mechanism, these methods could be mainly classified into three types. The first type is based on their difference in the physicochemical property, such as size, density, charge, and hydrophobicity. The second one is based on the bimolecular affinity interaction with lectin or antibody. And the third type is based on the chemical covalent coupling to free side groups of surface-exposed proteins or carbohydrate chains, such as primary amines, carboxyl groups, glycan side chains. In addition, metabolic labeling and enzymatic reaction-based methods have also been employed to selectively isolate cell surface proteins. In this review, we will provide a comprehensive overview of the enrichment methods for cell surface proteome profiling.

Sensitive profiling of cell surface proteome by using an optimized biotinylation method

Cell surface proteins are responsible for many critical functions. Systematical profiling of these proteins would provide a unique molecular fingerprint to classify cells and provide important information to guide immunotherapy. Cell surface biotinylation method is one of the effective methods for cell surface proteome profiling. However, classical workflows suffer the disadvantage of poor sensitivity. In this work, we presented an optimized protocol which enabled identification of more cell surface proteins from a smaller number of cells. When this protocol was combined with a tip based fractionation scheme, 4510 proteins, including 2055 annotated cell surface-associated proteins, were identified with only 20 microgram protein digest, showing the superior sensitivity of the approach. To enable process 10 times fewer cells, a pipet tip based protocol was developed, which led to the identification of about 600 cell surface-associated proteins. Finally, the new protocol was applied to compare the cell surface proteomes of two breast cancer cell lines, BT474 and MCF7. It was found that many cell surface-associated proteins were differentially expressed. The new protocols were demonstrated to be easy to perform, time-saving, and yielding good selectivity and high sensitivity. We expect this protocol would have broad applications in the future. SIGNIFICANCE: Cell surface proteins confer specific cellular functions and are easily accessible. They are often used as drug targets and potential biomarkers for prognostic or diagnostic purposes. Thus, efficient methods for profiling cell surface proteins are highly demanded. Cell surface biotinylation method is one of the effective methods for cell surface proteome profiling. However, classical workflows suffer the disadvantage of poor sensitivity. In this work, we presented an optimized protocol which enabled identification of more cell surface proteins from a smaller number of starting cells. The new protocol is easier to perform, time-saving and has less protein loss. By using a special pipet tip, sensitive and in-depth cell surface proteome analysis could be achieved. In combination with label-free quantitative MS, the new protocol can be applied to the differential analysis of the cell surface proteomes between different cell lines to find genetically- or drug-induced changes. We expect this protocol would have broad application in cell surface protein studies, including the discovery of diagnostic marker proteins and potential therapeutic targets.

Membrane proteomics of cervical cancer cell lines reveal insights on the process of cervical carcinogenesis

The available therapeutic approaches for cervical cancer can seriously affect the fertility potential of patient; thus, there is a pressing requirement for less toxic and targeted therapies. The membrane proteome is a potential source of therapeutic targets; however, despite the significance of membrane proteins in cancer, proteomic analysis has been a challenging task due to their unique biochemical properties. The aim of the present study was to develop an efficient membrane protein enrichment protocol, and to the best of our knowledge, to compare for the first time the expression pattern of membrane proteins of one normal cell line, HCK1T, and three cervical cancer cell lines, C33A, a human papilloma virus (HPV)-negative cell line, and two HPV-positive cell lines, SiHa (HPV16+) and HeLa (HPV18+). The study aimed to identify the proteins that are involved in cervical carcinogenesis and may constitute novel drug targets. Membrane protein isolation, liquid chromatography coupled with tandem mass spectrometry proteomics and bioinformatics analysis were performed in the membrane fraction of the informative cervical cell lines following a novel enrichment protocol. The percentages of membrane and transmembrane proteins in the enrichment protocol were higher compared with those of the corresponding data derived from total cell extract analysis. Differentially expressed proteins were detected by the comparison of the cervical cancer cell lines with the normal cell line. These proteins constitute molecular features of cancer pathology and participate in biological pathways relevant to malignancy, including 'HIPPO signaling', 'PI3K/Akt signaling', 'cell cycle: G2/M DNA damage checkpoint regulation' and 'EIF2 signaling'. These unique membrane protein identifications offer insights on a previously inaccessible region of the cervical cancer proteome, and may represent putative diagnostic and prognostic markers, and eventually therapeutic targets.

Mass Spectrometry Analyses of Multicellular Tumor Spheroids

Multicellular tumor spheroids (MCTS) are a powerful biological in vitro model, which closely mimics the 3D structure of primary avascularized tumors. Mass spectrometry (MS) has established itself as a powerful analytical tool, not only to better understand and describe the complex structure of MCTS, but also to monitor their response to cancer therapeutics. The first part of this review focuses on traditional mass spectrometry approaches with an emphasis on elucidating the molecular characteristics of these structures. Then the mass spectrometry imaging (MSI) approaches used to obtain spatially defined information from MCTS is described. Finally the analysis of primary spheroids, such as those present in ovarian cancer, and the great potential that mass spectrometry analysis of these structures has for improved understanding of cancer progression and for personalized in vitro therapeutic testing is discussed.

Quantitative proteomic analysis of HeLa cells in response to biocompatible Fe2C@C nanoparticles: 16O/18O-labelling & HPLC-ESI-orbit-trap profiling approach

The effective detection of molecular biomarkers, such as proteins, lipids, carbohydrates, and pathogens, in a living body is a huge challenge in the field of nanomedicine. Here, we have investigated the comparative quantitative proteomics analysis of the molecular response of HeLa cells to biocompatible Fe2C@C nanoparticles (NPs) using 16O/18O isotopic labelling of the cell culture. The relative binding efficiency of proteins to Fe2C@C NPs was calculated. HPLC-ESI-orbit-trap analysis found 51 differentially expressed proteins, out of which 23 were over-expressed and 28 down-regulated. This study showed that Fe2C@C NPs alter the expression of the proteins involved in endocytosis, cell-cycle regulation, and cell membrane protrusion. Further, the quantification and validation of the mass spectrometry (MS) results was successfully confirmed by western blot analysis of cytochrome C. The change in the expression of proteins can be useful for early stage disease diagnoses and the development of tailored therapeutic strategies. This study is the first large-scale characterization of low abundance proteins on Fe2C@C NPs, providing the biochemical basis for the assessment of the suitability of magnetic NPs as biomedical markers and emerging functional probes.

Efficient isolation and proteomic analysis of cell plasma membrane proteins in gastric cancer reveal a novel differentiation and progression related cell surface marker, R-cadherin

Cell plasma membrane proteins, playing a crucial role in cell malignant transformation and development, were the main targets of tumor detection and therapy. In this study, CyDye/biotin double-labeling proteomic approach was adopted to profile the membrane proteome of gastric cancer cell line BGC-823 and paired immortalized gastric epithelial cell GES-1. Real-time PCR, Western blotting, and immunohistochemical staining were used to validate the differential expression of a novel identified cell surface marker R-cadherin in gastric cancer cells and tissues. Clinicopathological study and survival analysis were performed to estimate its roles in tumor progression and outcome prediction. Real-time PCR and Western blotting showed that the expression level of R-cadherin in gastric cancer were significantly lower than non-cancerous epithelial cell and tissues. Clinicopathological study indicated that R-cadherin was dominantly expressed on cell surface of normal gastric epithelium, and its expression deletion in gastric cancer tissues was associated with tumor site, differentiation, lymph node metastasis, and pTNM (chi-square test, P < 0.05). Those patients with R-cadherin positive expression displayed better overall survivals than negative expression group (log-rank test, P = 0.000). Cox multivariate survival analysis revealed lacking the expression of R-cadherin was a main independent predictor for poor clinical outcome in gastric cancer (RR = 5.680, 95 % CI 2.250–14.341, P < 0.01). We have established a fundamental membrane proteome database for gastric cancer and identified R-cadherin as a tumor differentiation and progression-related cell surface marker of gastric cancer. Lacking the expression of R-cadherin indicates poor prognosis in patients with gastric cancer.

Direct Interface between Digital Microfluidics and High Performance Liquid Chromatography-Mass Spectrometry

We introduce an automated method to facilitate in-line coupling of digital microfluidics (DMF) with HPLC-MS, using a custom, 3D-printed manifold and a custom plugin to the popular open-source control system, DropBot. The method was designed to interface directly with commercial autosamplers (with no prior modification), suggesting that it will be widely accessible for end-users. The system was demonstrated to be compatible with samples dissolved in aqueous buffers and neat methanol and was validated by application to a common steroid-labeling derivatization reaction. We propose that the methods described here will be useful for a wide range of applications, combining the automated sample processing power of DMF with the resolving and analytical capacity of HPLC-MS.

Proteomics in cancer research: Are we ready for clinical practice?

Although genomics has delivered major advances in cancer prognostics, treatment and diagnostics, it still only provides a static image of the situation. To study more dynamic molecular entities, proteomics has been introduced into the cancer research field more than a decade ago. Currently, however, the impact of clinical proteomics on patient management and clinical decision-making is low and the implementations of scientific results in the clinic appear to be scarce. The search for cancer-related biomarkers with proteomics however, has major potential to improve risk assessment, early detection, diagnosis, prognosis, treatment selection and monitoring. In this review, we provide an overview of the transition of oncoproteomics towards translational oncology. We describe which lessons are learned from currently approved protein biomarkers and previous proteomic studies, what the pitfalls and challenges are in clinical proteomics applications, and how proteomic research can be successfully translated into medical practice.

Transformative Impact of Proteomics on Cardiovascular Health and Disease: A Scientific Statement From the American Heart Association

The year 2014 marked the 20th anniversary of the coining of the term proteomics. The purpose of this scientific statement is to summarize advances over this period that have catalyzed our capacity to address the experimental, translational, and clinical implications of proteomics as applied to cardiovascular health and disease and to evaluate the current status of the field. Key successes that have energized the field are delineated; opportunities for proteomics to drive basic science research, facilitate clinical translation, and establish diagnostic and therapeutic healthcare algorithms are discussed; and challenges that remain to be solved before proteomic technologies can be readily translated from scientific discoveries to meaningful advances in cardiovascular care are addressed. Proteomics is the result of disruptive technologies, namely, mass spectrometry and database searching, which drove protein analysis from 1 protein at a time to protein mixture analyses that enable large-scale analysis of proteins and facilitate paradigm shifts in biological concepts that address important clinical questions. Over the past 20 years, the field of proteomics has matured, yet it is still developing rapidly. The scope of this statement will extend beyond the reaches of a typical review article and offer guidance on the use of next-generation proteomics for future scientific discovery in the basic research laboratory and clinical settings.

Proteomics in pharmaceutical research and development

In the 20 years since its inception, the evolution of proteomics in pharmaceutical industry has mirrored the developments within academia and indeed other industries. From initial enthusiasm and subsequent disappointment in global protein expression profiling, pharma research saw the biggest impact when relating to more focused approaches, such as those exploring the interaction between proteins and drugs. Nowadays, proteomics technologies have been integrated in many areas of pharmaceutical R&D, ranging from the analysis of therapeutic proteins to the monitoring of clinical trials. Here, we review the development of proteomics in the drug discovery process, placing it in a historical context as well as reviewing the current status in light of the contributions to this special issue, which reflect some of the diverse demands of the drug and biomarker pipelines.

Coupling enrichment methods with proteomics for understanding and treating disease

Owing to recent advances in proteomics analytical methods and bioinformatics capabilities there is a growing trend toward using these capabilities for the development of drugs to treat human disease, including target and drug evaluation, understanding mechanisms of drug action, and biomarker discovery. Currently, the genetic sequences of many major organisms are available, which have helped greatly in characterizing proteomes in model animal systems and humans. Through proteomics, global profiles of different disease states can be characterized (e.g. changes in types and relative levels as well as changes in PTMs such as glycosylation or phosphorylation). Although intracellular proteomics can provide a broad overview of physiology of cells and tissues, it has been difficult to quantify the low abundance proteins which can be important for understanding the diseased states and treatment progression. For this reason, there is increasing interest in coupling comparative proteomics methods with subcellular fractionation and enrichment techniques for membranes, nucleus, phosphoproteome, glycoproteome as well as low abundance serum proteins. In this review, we will provide examples of where the utilization of different proteomics-coupled enrichment techniques has aided target and biomarker discovery, understanding the drug targeting mechanism, and mAb discovery. Taken together, these improvements will help to provide a better understanding of the pathophysiology of various diseases including cancer, autoimmunity, inflammation, cardiovascular disease, and neurological conditions, and in the design and development of better medicines for treating these afflictions.