Protein microarrays: meeting analytical challenges for clinical applications

Proteomics appending a complementary dimension to precision oncotherapy

Recent advances in high-throughput proteomic profiling technologies have facilitated the precise quantification of numerous proteins across multiple specimens concurrently. Researchers have the opportunity to comprehensively analyze the molecular signatures in plentiful medical specimens or disease pattern cell lines. Along with advances in data analysis and integration, proteomics data could be efficiently consolidated and employed to recognize precise elementary molecular mechanisms and decode individual biomarkers, guiding the precision treatment of tumors. Herein, we review a broad array of proteomics technologies and the progress and methods for the integration of proteomics data and further discuss how to better merge proteomics in precision medicine and clinical settings.

Lysis of Extracellular Vesicles and Multiplexed Protein Detection via a Reverse Phase Immunoassay Using a Gold-Nanoparticle-Embedded Membrane Platform

Extracellular vesicles (EVs) are cell-derived membrane-bound particles with molecular cargo reflective of their cell of origin. Analysis of disease-related EVs and associated cargo from biofluids is a promising tool for disease management. To facilitate the analysis of intravesicular molecules, EV lysis is needed. Moreover, highly sensitive and multiplexed detection methods are required to achieve early diagnostics. While cell lysis approaches have been well studied, the analysis of EV lysis methods and their effects on downstream molecular detection is lacking. In this work, we analyzed chemical, thermal, and mechanical EV lysis methods and determined their efficiency based on EV particle concentration and immunoassay activity. We, for the first time, discovered that vortex was an efficient EV lysis method and used it for detection of surface and intravesicular markers in a highly sensitive multiplexed reverse phase immunoassay on a gold-nanoparticle-embedded membrane. In phosphate-buffered saline, detection limits up to 3 orders of magnitude lower than enzyme-linked immunosorbent assay were achieved. In spiked human plasma, detection limits as low as 7.27 × 104 EVs/mL were achieved, making it suitable for early diagnostics. These results demonstrated an effective pipeline for lysing and molecular analysis of EVs from complex biofluids, paving the way for their broad applications in biomedicine.

Gut dysbiosis and neurological modalities: An engineering approach via proteomic analysis of gut-brain axis

The human gut microbiota is a complex and dynamic community of microorganisms, that influence metabolic, neurodevelopmental, and immune pathways. Microbial dysbiosis, characterized by changes in microbial diversity and relative abundances, is implicated in the development of various chronic neurological and neurodegenerative disorders. These disorders are marked by the accumulation of pathological protein aggregates, leading to the progressive loss of neurons and behavioural functions. Dysregulations in protein-protein interaction networks and signalling complexes, critical for normal brain function, are common in neurological disorders but challenging to unravel, particularly at the neuron and synapse-specific levels. To advance therapeutic strategies, a deeper understanding of neuropathogenesis, especially during the progressive disease phase, is needed. Biomarkers play a crucial role in identifying disease pathophysiology and monitoring disease progression. Proteomics, a powerful technology, shows promise in accelerating biomarker discovery and aiding in the development of novel treatments. In this chapter, we provide an in-depth overview of how proteomic techniques, utilizing various biofluid samples from patients with neurological conditions and diverse animal models, have contributed valuable insights into the pathogenesis of numerous neurological disorders. We also discuss the current state of research, potential challenges, and future directions in proteomic approaches to unravel neuro-pathological conditions.

Recent Progress in Development and Application of DNA, Protein, Peptide, Glycan, Antibody, and Aptamer Microarrays

Microarrays are one of the trailblazing technologies of the last two decades and have displayed their importance in all the associated fields of biology. They are widely explored to screen, identify, and gain insights on the characteristics traits of biomolecules (individually or in complex solutions). A wide variety of biomolecule-based microarrays (DNA microarrays, protein microarrays, glycan microarrays, antibody microarrays, peptide microarrays, and aptamer microarrays) are either commercially available or fabricated in-house by researchers to explore diverse substrates, surface coating, immobilization techniques, and detection strategies. The aim of this review is to explore the development of biomolecule-based microarray applications since 2018 onwards. Here, we have covered a different array of printing strategies, substrate surface modification, biomolecule immobilization strategies, detection techniques, and biomolecule-based microarray applications. The period of 2018-2022 focused on using biomolecule-based microarrays for the identification of biomarkers, detection of viruses, differentiation of multiple pathogens, etc. A few potential future applications of microarrays could be for personalized medicine, vaccine candidate screening, toxin screening, pathogen identification, and posttranslational modifications.

Multiplexed Bead-Based Peptide Immunoassays for the Detection of Antibody Reactivities

Antigenic peptides are commonly used in serological test settings such as enzyme-linked immunosorbent assays (ELISA) to determine reactive antibodies (ABs) from serum or plasma samples. The use of synthetic peptides provides advantages like lower production effort and easier incorporation of specific chemical modifications compared to full-length antigenic proteins. Multiplexed antibody (AB) profiling methods such as microarray technologies enable the simultaneous identification of multiple novel biomarkers for the use in early disease diagnostics, vaccine development, or monitoring of immune responses. Despite various benefits they still show major limitations which can be overcome with bead-based assay technologies like the multi-analyte profiling (xMAP) technology developed by Luminex. In this chapter we introduce our established workflow for AB profiling with a multiplexed bead-based peptide immunoassay. The workflow is based on copper-catalyzed click chemistry to immobilize designed synthetic peptides onto uniquely color-coded paramagnetic beads in an orientation-specific manner. The individual peptide-coupled beads can be distinguished by their unique emission spectra during readout in the xMAP instrument and therefore allow testing of up to 500 different antigenic peptides in one multiplexed reaction. The multistep process described in this chapter is divided into separate sections for peptide design, coupling of functionalized peptides to MagPlex beads via click chemistry, confirmation of successful peptide immobilization, processing of serum or plasma samples, or preferably purified IgG thereof, with the multiplexed bead-based peptide immunoassay and subsequent data export and analysis.

Immobilization of Active Antibodies at Polymer Melt Surfaces during Injection Molding

We demonstrate the transfer and immobilization of active antibodies from a low surface- energy mold surface to thermoplastic replica surfaces using injection molding, and we investigate the process at molecular scale. The transfer process is highly efficient, as verified by atomic force microscopy (AFM) and X-ray photoelectron spectroscopy (XPS) of the mold and replica surfaces. AFM analysis reveals partial nanometer-scale embedding of the protein into the polymer matrix as a possible mechanism of permanent immobilization. Replicas with rabbit anti-mouse IgG immobilized as capture antibody at the hot polymer melt surface during injection molding show similar affinity for their antigen (mouse IgG) in sandwich enzyme-linked immunosorbent assay (ELISA) as capture antibodies deposited by passive adsorption onto a bare thermoplastic replica. The transferred antibodies retain their functionality after incubation in serum-containing cell medium for >1 week. A mold coating time of 10 min prior to injection molding is sufficient for producing highly sensitive ELISA assays, thus enabling the short processing cycle times required for mass production of single-use biodevices relying on active immobilized antibodies.

RPPA SPACE: an R package for normalization and quantitation of Reverse-Phase Protein Array data

SUMMARY

Reverse-Phase Protein Array (RPPA) is a robust high-throughput, cost-effective platform for quantitatively measuring proteins in biological specimens. However, converting raw RPPA data into normalized, analysis-ready data remains a challenging task. Here, we present the RPPA SPACE (RPPA Superposition Analysis and Concentration Evaluation) R package, a substantially improved successor to SuperCurve, to meet that challenge. SuperCurve has been used to normalize over 170 000 samples to date. RPPA SPACE allows exclusion of poor-quality samples from the normalization process to improve the quality of the remaining samples. It also features a novel quality-control metric, 'noise', that estimates the level of random errors present in each RPPA slide. The noise metric can help to determine the quality and reliability of the data. In addition, RPPA SPACE has simpler input requirements and is more flexible than SuperCurve, it is much faster with greatly improved error reporting.

AVAILABILITY AND IMPLEMENTATION

The standalone RPPA SPACE R package, tutorials and sample data are available via https://rppa.space/, CRAN (https://cran.r-project.org/web/packages/RPPASPACE/index.html) and GitHub (https://github.com/MD-Anderson-Bioinformatics/RPPASPACE).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Characterization of anticancer drug resistance by reverse-phase protein array: new targets and strategies

INTRODUCTION

Drug resistance is the main barrier to achieving cancer cures with medical therapy. Cancer drug resistance occurs, in part, due to adaptation of the tumor and microenvironment to therapeutic stress at a proteomic level. Reverse-phase protein arrays (RPPA) are well suited to proteomic analysis of drug resistance due to high sample throughput, sensitive detection of phosphoproteins, and validation for a large number of critical cellular pathways.

AREAS COVERED

This review summarizes contributions of RPPA to understanding and combating drug resistance. In particular, contributions of RPPA to understanding resistance to PARP inhibitors, BRAF inhibitors, immune checkpoint inhibitors, and breast cancer investigational therapies are discussed. Articles reviewed were identified by MEDLINE, Scopus, and Cochrane search for keywords 'proteomics,' 'reverse-phase protein array,' 'drug resistance,' 'PARP inhibitor,' 'BRAF inhibitor,' 'immune checkpoint inhibitor,' and 'I-SPY' spanning October 1, 1960 - October 1, 2021.

EXPERT OPINION

Precision oncology has thus far failed to convert the armament of targeted therapies into durable responses for most patients, highlighting that genetic sequencing alone is insufficient to guide therapy selection and overcome drug resistance. Combined genomic and proteomic analyses paired with creative drug combinations and dosing strategies hold promise for maturing precision oncology into an era of improved patient outcomes.

Functional Mapping of AKT Signaling and Biomarkers of Response from the FAIRLANE Trial of Neoadjuvant Ipatasertib plus Paclitaxel for Triple-Negative Breast Cancer

PURPOSE

Despite extensive genomic and transcriptomic profiling, it remains unknown how signaling pathways are differentially activated and how tumors are differentially sensitized to certain perturbations. Here, we aim to characterize AKT signaling activity and its association with other genomic or IHC-based PI3K/AKT pathway biomarkers as well as the clinical activity of ipatasertib (AKT inhibitor) in the FAIRLANE trial.

EXPERIMENTAL DESIGN

In FAIRLANE, 151 patients with early triple-negative breast cancer (TNBC) were randomized 1:1 to receive paclitaxel with ipatasertib or placebo for 12 weeks prior to surgery. Adding ipatasertib did not increase pathologic complete response rate and numerically improved overall response rate by MRI. We used reverse-phase protein microarrays (RPPA) to examine the total level and/or phosphorylation states of over 100 proteins in various signaling or cell processes including PI3K/AKT and mTOR signaling. One hundred and twenty-five baseline and 127 on-treatment samples were evaluable by RPPA, with 110 paired samples at both time points.

RESULTS

Tumors with genomic/protein alterations in PIK3CA/AKT1/PTEN were associated with higher levels of AKT phosphorylation. In addition, phosphorylated AKT (pAKT) levels exhibited a significant association with enriched clinical benefit of ipatasertib, and identified patients who received benefit in the absence of PIK3CA/AKT1/PTEN alterations. Ipatasertib treatment led to a downregulation of AKT/mTORC1 signaling, which was more pronounced among the tumors with PIK3CA/AKT1/PTEN alterations or among the responders to the treatment.

CONCLUSIONS

We showed that the high baseline pAKT levels are associated with the alterations of PI3K/AKT pathway components and enriched benefit of ipatasertib in TNBC.

A rhabdomyosarcoma hydrogel model to unveil cell-extracellular matrix interactions

Three-dimensional (3D) culture systems have progressively attracted attention given their potential to overcome limitations of classical 2D in vitro systems. Among different supports for 3D cell culture, hydrogels (HGs) offer important advantages such as tunable mechanical and biological properties. Here, a biocompatible hyaluronic acid-polyethylene glycol HG was developed to explore the pro-migratory behavior of alveolar rhabdomyosarcoma (ARMS) cells. Proteomic analysis of ARMS xenografts unveiled the composition of the extracellular matrix (ECM) elucidating the most representative proteins. In parallel, HGs were obtained by the combination of a thiol-containing hyaluronic acid derivative and different polyethylene glycol (PEG) dimaleimide polymers. The selection of the optimal HG for ARMS cell growth was made based on degradation time, swelling, and cell distribution. Rheology measures and mechanical properties were assessed in the presence or absence of ECM proteins (collagen type I and fibronectin), as well as viability tests and cell distribution analysis. The role of ITGA5, the receptor of fibronectin, in determining ARMS cell migration was validated in vitro upon ITGA5 silencing. In vivo, cell dissemination and the capacity for engrafting were validated after injecting ARMS cell populations enriched for the level of ITGA5 in zebrafish embryos. To study the interactions with ARMS-specific ECM proteins (HG + P), the key players from the Rho and heat-shock pathways were investigated by reverse phase protein array (RPPA). Our data suggest that the developed 3D ARMS model is useful for identifying potential physical hallmarks that allow cancer cells to resist therapy, escape from the immune-system and increase dissemination.

Increased PD-L1 Expression in Human Skin Acutely and Chronically Exposed to UV Irradiation

Overexpression of PD-L1 (CD274) on tumor cells may represent a hallmark of immune evasion, and overexpression has been documented in several tumors including cutaneous squamous cell carcinoma (cSCC). While PD-L1/PD-1 activity in the skin has been primarily described in inflammatory models, our goal was to examine PD-L1 expression in human keratinocytes exposed to UV irradiation. We assessed PD-L1 expression in human sun-protected (SP) and sun-damaged (SD) skin, actinic keratosis (AK), and cSCC using IHC and protein microarray. Both methods found low baseline levels of PD-L1 in SP and SD skin and significantly increased expression in cSCC. Next, we examined PD-L1 expression in acute models of UV exposure. In human SP skin exposed to 2-3 MED of UV (n = 20), epidermal PD-L1 was induced in 70% of subjects after 24 h (P = 0.0001). SKH-1 mice exposed to acute UV also showed significant epidermal PD-L1 induction at 16, 24 and 48 h. A time- and dose-dependent induction of PD-L1 was confirmed in cultured human keratinocytes after UV, which was markedly reduced in the presence of MEK/ERK, JNK or STAT3 inhibitors. These findings suggest that UV induces upregulation of PD-L1 through established, pharmacologically targetable stress-signaling pathways in keratinocytes.

Reverse Phase Protein Arrays

Reverse phase protein arrays (RPPA) are used to quantify proteins and protein posttranslational modifications in cellular lysates and body fluids. RPPA technology is suitable for biomarker discovery, protein pathway profiling, functional phenotype analysis, and drug discovery mechanism of action. The principles of RPPA technology are (a) immobilizing protein-containing specimens on a coated slide in discrete spots, (b) antibody recognition of proteins, (c) amplification chemistries to detect the protein-antibody complex, and (d) quantifying spot intensity. Construction of a RPPA begins with the robotic liquid transfer of protein-containing specimens from microtiter plates onto nitrocellulose-coated slides. The robotic arrayer deposits each sample as discrete spots in an array format. Specimens, controls, and calibrators are printed on each array, thus providing a complete calibrated assay on a single slide. Each RPPA slide is subsequently probed with catalyzed signal amplification chemistries and a single primary antibody, a secondary antibody, and either fluorescent or colorimetric dyes. The focus of this chapter is to describe RPPA detection and imaging using a colorimetric (diaminobenzidine (DAB)) detection strategy.

Profiling Autoantibody Responses to Devise Novel Diagnostic and Prognostic Markers Using High-Density Protein Microarrays

Protein microarrays are a diverse and high-throughput platform for screening biomolecular interactions, autoantigens, and protein expression profiles across tissues, etc. Autoantibodies produced against aberrant protein expression are often observed in malignancies which makes protein microarrays a powerful platform to elucidate biomarkers of translational interest. Early diagnosis of malignancies is an enduring clinical problem that has a direct impact on disease prognosis. Here, we provide an overview of a method employed to screen autoantibodies using patient sera in brain tumors. In case of brain malignancies, early diagnosis is particularly challenging and often requires highly invasive brain biopsies as a confirmatory test. This chapter summarizes the various considerations for applying a serum-based autoantibody biomarker discovery pipeline that could provide a minimally invasive initial diagnostic screen, potentiating classical diagnostic approaches.

A comprehensive overview of proteomics approach for COVID 19: new perspectives in target therapy strategies

World Health Organisation declared COVID-19 a pandemic on March 11, 2020. It was temporarily named as 2019-nCoV then subsequently named as COVID-19 virus. A coronavirus is a group of viruses, known to be zoonotic, causing illness ranging from acute to mild respiratory infections. These are spherical or pleomorphic enveloped particles containing positive sense RNA. The virus enters host cells, its uncoated genetic material transcribes, and translates. Since it has started spreading rapidly, protective measures have been taken all over the world. However, its transmission has been proved to be unstoppable and the absence of an effective drug makes the situation worse. The scientific community has gone all-out to discover and develop a possible vaccine or a competent antiviral drug. Other domains of biological sciences that promise effective results and target somewhat stable entities that are proteins, could be very useful in this time of crisis. Proteomics and metabolomics are the vast fields that are equipped with sufficient technologies to face this challenge. Various protein separation and identification techniques are available which facilitates the analysis of various types of interactions among proteins and their evolutionary lineages. The presented review aims at confronting the question: 'how proteomics can help in tackling SARS-CoV-2?' It deals with the role of upcoming proteome technology in these pandemic situations and discusses the proteomics approach towards the COVID-19 dilemma.

Proteomic profiling of bladder cancer for precision medicine in the clinical setting: A review for the busy urologist

At present, proteomic methods have successfully identified potential biomarkers of urological malignancies, such as prostate cancer (PC), bladder cancer (BC), and renal cell carcinoma (RCC), reflecting different numbers of key cellular processes, including extracellular environment modification, invasion and metastasis, chemotaxis, differentiation, metabolite transport, and apoptosis. The potential application of proteomics in the detection of clinical markers of urological malignancies can help improve patient assessment through early cancer detection, prognosis, and treatment response prediction. A variety of proteomic studies have already been carried out to find prognostic BC biomarkers, and a large number of potential biomarkers have been reported. It is worth noting that proteomics research has not been applied to the study of predictive markers; this may be due to the incompatibility between the number of measured variables and the available sample size, which has become particularly evident in the study of therapeutic response. On the contrary, prognostic correlation is more common, which is also reflected in existing research. We are now entering an era of clinical proteomics. Driven by proteomic-based workflows, computing tools, and the applicability of cross-correlation of proteomic data, it is now feasible to use proteomic analysis to support personalized medicine. In this paper, we will summarize the current emerging technologies for advanced discovery, targeted proteomics, and proteomic applications in BC, particularly in discovery of human-based biomarkers.

Multiplexed Detection of Cancer Serum Antigens with a Quantum Dot-Based Lab-on-Bead System

A quantum dot (QD)-based lab-on-bead system is a unique tool for multiple analysis of cancer markers in human serum samples by using a flow cytometer. In terms of specificity and sensitivity, this method is comparable with ELISA, the "gold standard" of serological in-clinic detection of single analytes. Fluorescent microspheres encoded with QDs have been used for the quantitative detection of free and total prostate-specific antigen in human serum samples. Developed multiplex assay demonstrates a clear discrimination between serum samples from control subjects and cancer patients. The proposed QD-based method is adaptable and makes it possible to develop numerous clinical tests with decreased duration and cost for early diagnosis of various diseases.

Chemoradiotherapy response prediction model by proteomic expressional profiling in patients with locally advanced cervical cancer

OBJECTIVE

Resistance to chemo-radiation therapy is a substantial obstacle that compromises treatment of advanced cervical cancer. The objective of this study was to investigate if a proteomic panel associated with radioresistance could predict survival of patients with locally advanced cervical cancer.

METHODS

A total of 181 frozen tissue samples were prospectively obtained from patients with locally advanced cervical cancer before chemoradiation. Expression levels of 22 total and phosphorylated proteins were evaluated using well-based reverse phase protein arrays. Selected proteins were validated with western blotting analysis and immunohistochemistry. Performances of models were internally and externally validated.

RESULTS

Unsupervised clustering stratified patients into three major groups with different overall survival (OS, P = 0.001) and progression-free survival (PFS, P = 0.003) based on detection of BCL2, HER2, CD133, CAIX, and ERCC1. Reverse-phase protein array results significantly correlated with western blotting results (R² = 0.856). The C-index of model was higher than clinical model in the prediction of OS (C-index: 0.86 and 0.62, respectively) and PFS (C-index: 0.82 and 0.64, respectively). The Kaplan-Meier survival curve showed a dose-dependent prognostic significance of risk score for PFS and OS. Multivariable Cox proportional hazard model confirmed that the risk score was an independent predictor of PFS (HR: 1.6; 95% CI: 1.4-1.9; P < 0.001) and OS (HR: 2.1; 95% CI: 1.7-2.5; P < 0.001).

CONCLUSION

A proteomic panel of BCL2, HER2, CD133, CAIX, and ERCC1 independently predicted survival in locally advanced cervical cancer patients. This prediction model can help identify chemoradiation responsive tumors and improve prediction for clinical outcome of cervical cancer patients.

Chemical Sensing Platforms Based on Organic Thin-Film Transistors Functionalized with Artificial Receptors

Organic thin-film transistors (OTFTs) have attracted intense attention as promising electronic devices owing to their various applications such as rollable active-matrix displays, flexible nonvolatile memories, and radiofrequency identification (RFID) tags. To further broaden the scope of the application of OTFTs, we focus on the host-guest chemistry combined with the electronic devices. Extended-gate types of OTFTs functionalized with artificial receptors were fabricated to achieve chemical sensing of targets in complete aqueous media. Organic and inorganic ions (cations and anions), neutral molecules, and proteins, which are regarded as target analytes in the field of host-guest chemistry, were electrically detected by artificial receptors. Molecular recognition phenomena on the extended-gate electrode were evaluated by several analytical methods such as photoemission yield spectroscopy in the air, contact angle goniometry, and X-ray photoelectron spectroscopy. Interestingly, the electrical responses of the OTFTs were highly sensitive to the chemical structures of the guests. Thus, the OTFTs will facilitate the selective sensing of target analytes and the understanding of chemical conversions in biological and environmental systems. Furthermore, such cross-reactive responses observed in our studies will provide some important insights into next-generation sensing systems such as OTFT arrays. We strongly believe that our approach will enable the development of new intriguing sensor platforms in the field of host-guest chemistry, analytical chemistry, and organic electronics.

Proteomics for cancer drug design

Introduction: Signal transduction cascades drive cellular proliferation, apoptosis, immune, and survival pathways. Proteins have emerged as actionable drug targets because they are often dysregulated in cancer, due to underlying genetic mutations, or dysregulated signaling pathways. Cancer drug development relies on proteomic technologies to identify potential biomarkers, mechanisms-of-action, and to identify protein binding hot spots. Areas covered: Brief summaries of proteomic technologies for drug discovery include mass spectrometry, reverse phase protein arrays, chemoproteomics, and fragment based screening. Protein-protein interface mapping is presented as a promising method for peptide therapeutic development. The topic of biosimilar therapeutics is presented as an opportunity to apply proteomic technologies to this new class of cancer drug. Expert opinion: Proteomic technologies are indispensable for drug discovery. A suite of technologies including mass spectrometry, reverse phase protein arrays, and protein-protein interaction mapping provide complimentary information for drug development. These assays have matured into well controlled, robust technologies. Recent regulatory approval of biosimilar therapeutics provides another opportunity to decipher the molecular nuances of their unique mechanisms of action. The ability to identify previously hidden protein hot spots is expanding the gamut of potential drug targets. Proteomic profiling permits lead compound evaluation beyond the one drug, one target paradigm.

Proteomic Strategies and their Application in Cancer Research

The understanding of carcinogenesis and tumor progression on a molecular basis needs a detailed study of proteins as effector molecules and as critical components of the multiple interconnected signaling pathways that drive the neoplastic phenotype. Thus, the proteomic approach represents a powerful tool for the challenge of the post-genomic era. The term “cancer proteome” refers to the collection of proteins expressed by a given cancer cell and should be considered as a highly dynamic entity within the cell, which affects a variety of cellular activities. The emerging proteomic analysis platforms including 2D-PAGE, mass spectrometry technologies, and protein microarrays represent powerful tools to study and understand cancer. These systems aim to not only identify, catalogue, and characterize cancer proteins, but also to unveil how they interact to affect overall tumor progression. Moreover, recent studies on various cancers have reported promising results concerning the detection of novel molecular biomarkers useful in the early diagnosis of cancer and in drug discovery. Thus, a new subdiscipline named clinical proteomics, concomitant with new molecular technologies that are developed, demonstrates promise to discover new cancer biomarkers. The early diagnosis of cancer, even in a premalignant state, is crucial for the successful treatment of this disease. For these reasons, it is clear that the identification of biomarkers for the early diagnosis of cancer should represent one of the main goals of this emerging field of study.

Characterization of troponin T binding aptamers for an innovative enzyme-linked oligonucleotide assay (ELONA)

Early diagnosis of acute myocardial infarction (AMI) is of outmost importance to reduce the mortality rate, and cardiac troponins are considered the gold standard biomarkers of myocardial necrosis. In this scenario, the characterization of two troponin T (TnT)-binding aptamers as viable alternative to antibodies employed on clinical immunoassays is here reported for the first time. Their recognition ability was first investigated through surface plasmon resonance (SPR). Subsequently, an enzyme-linked oligonucleotide assay (ELONA) was developed on common 96-well polystyrene plates, both by direct and sandwich detection strategies for comparison. In both cases, the assay exhibits a detection ability of TnT in the range of low nanomolar but a great advantage on serum interference was obtained by using both aptamers in a sandwich format, with excellent reproducibility and recovery values. Despite the sensitivity needing to be enhanced to the low picomolar range, these results are encouraging for the development of new, low-cost, and rapid antibody-free colorimetric assays for AMI studies based on aptamer-Troponin T recognition.

Histopathological markers of treatment response and recurrence risk in ovarian cancers and borderline tumors

Histopathology plays an important role in defining response to treatment for different tumor types. Histopathologic response criteria are currently used as reference standard in various types of cancer, including breast cancer, gastroesophageal cancer, and bone tumors. Since there were no generally accepted response criteria established for ovarian cancer, a systematic analysis of various features of tumor regression was performed. Patient survival served as the reference standard to validate the histopathologic features of tumor regression. In contrast to ovarian cancer, borderline ovarian tumors are epithelial ovarian neoplasms characterized by up-regulated cellular proliferation and cytologic atypia but without destructive stromal invasion. While borderline ovarian tumors generally have an excellent prognosis with a 5‑year survival of > 95%, recurrences and malignant transformation occur in a small percentage of patients. Nevertheless, the identification of patients at increased risk for recurrence remains difficult. The aim of studying histopathological markers in ovarian cancers and borderline tumors was to evaluate whether histopathologic features including molecular pathologic alterations can predict patient outcome, particularly the risk of recurrence of serous and mucinous borderline tumors.

RPPA: Origins, Transition to a Validated Clinical Research Tool, and Next Generations of the Technology

RPPA technology has graduated from a research tool to an essential component of clinical drug discovery research and personalized medicine. Next generations of RPPA technology will be a single clinical instrument that integrates all the steps of the workflow.

Urine lipoarabinomannan glycan in HIV-negative patients with pulmonary tuberculosis correlates with disease severity

An accurate urine test for pulmonary tuberculosis (TB), affecting 9.6 million patients worldwide, is critically needed for surveillance and treatment management. Past attempts failed to reliably detect the mycobacterial glycan antigen lipoarabinomannan (LAM), a marker of active TB, in HIV-negative, pulmonary TB–infected patients’ urine (85% of 9.6 million patients). We apply a copper complex dye within a hydrogel nanocage that captures LAM with very high affinity, displacing interfering urine proteins. The technology was applied to study pretreatment urine from 48 Peruvian patients, all negative for HIV, with microbiologically confirmed active pulmonary TB. LAM was quantitatively measured in the urine with a sensitivity of >95%and a specificity of >80% (n = 101) in a concentration range of 14 to 2000 picograms per milliliter, as compared to non-TB, healthy and diseased, age-matched controls (evaluated by receiver operating characteristic analysis; area under the curve, 0.95; 95% confidence interval, 0.9005 to 0.9957). Urinary LAM was elevated in patients with a higher mycobacterial burden (n = 42), a higher proportion of weight loss (n = 37), or cough (n = 50). The technology can be configured in a variety of formats to detect a panel of previously undetectable very-low-abundance TB urinary analytes. Eight of nine patients who were smear-negative and culture-positive for TB tested positive for urinary LAM. This technology has broad implications for pulmonary TB screening, transmission control, and treatment management for HIV-negative patients.

Dual-Color, Multiplex Analysis of Protein Microarrays for Precision Medicine

Generating molecular information in a clinically relevant time frame is the first hurdle to truly integrating precision medicine in health care. Reverse phase protein microarrays are being utilized in clinical trials for quantifying posttranslationally modified signal transduction proteins and cellular signaling pathways, allowing direct comparison of the activation state of proteins from multiple specimens, or individual patient specimens, within the same array. This technology provides diagnostic and therapeutic information critical to precision medicine. To enhance accessibility of this technology, two hurdles must be overcome: data normalization and data acquisition. Herein we describe an unamplified, dual-color signal detection methodology for reverse phase protein microarrays that allows multiplex, within spot data normalization, reduces data acquisition time, simplifies automated spot detection, and provides a stable signal output. This method utilizes Quantum Nanocrystal fluorophore labels (Qdot) substituted for organic fluorophores coupled with an imager (ArrayCAM) that captures images of the microarray rather than sequentially scanning the array. Streamlining and standardizing the data analysis steps with ArrayCAM high-resolution, dual mode chromogenic/fluorescent array imaging overcomes the data acquisition hurdle. The spot location and analysis algorithm provides certain parameter settings that can be tailored to the particular microarray type (fluorescent vs. colorimetric), resulting in greater than 99 % spot location sensitivity. The described method demonstrates equivalent sensitivity for a non-amplified Qdot immunoassay when using automated vs. manual immunostaining procedures.

Reverse Phase Protein Microarrays

While genes and RNA encode information about cellular status, proteins are considered the engine of the cellular machine, as they are the effective elements that drive all cellular functions including proliferation, migration, differentiation, and apoptosis. Consequently, investigations of the cellular protein network are considered a fundamental tool for understanding cellular functions.Alteration of the cellular homeostasis driven by elaborate intra- and extracellular interactions has become one of the most studied fields in the era of personalized medicine and targeted therapy. Increasing interest has been focused on developing and improving proteomic technologies that are suitable for analysis of clinical samples. In this context, reverse-phase protein microarrays (RPPA) is a sensitive, quantitative, high-throughput immunoassay for protein analyses of tissue samples, cells, and body fluids.RPPA is well suited for broad proteomic profiling and is capable of capturing protein activation as well as biochemical reactions such as phosphorylation, glycosylation, ubiquitination, protein cleavage, and conformational alterations across hundreds of samples using a limited amount of biological material. For these reasons, RPPA represents a valid tool for protein analyses and generates data that help elucidate the functional signaling architecture through protein-protein interaction and protein activation mapping for the identification of critical nodes for individualized or combinatorial targeted therapy.

Effects of low dose ionizing radiation on DNA damage-caused pathways by reverse-phase protein array and Bayesian networks

Ionizing radiation (IR) causing damages to Deoxyribonucleic acid (DNA) constitutes a broad range of base damage and double strand break, and thereby, it induces the operation of relevant signaling pathways such as DNA repair, cell cycle control, and cell apoptosis. The goal of this paper is to study how the exposure to low dose radiation affects the human body by observing the signaling pathway associated with Ataxia Telangiectasia mutated (ATM) using Reverse-Phase Protein Array (RPPA) and isogenic human Ataxia Telangiectasia (A-T) cells under different amounts and durations of IR exposure. In order to verify which proteins could be involved in a DNA damage-caused pathway, only proteins that highly interact with each other under IR are selected by using correlation coefficient. The pathway inference is derived from learning Bayesian networks in combination with prior knowledge such as Protein-Protein Interactions (PPIs) and signaling pathways from well-known databases. Learning Bayesian networks is based on a score and search scheme that provides the highest scored network structure given a score function, and the prior knowledge is included in the score function as a prior probability by using Dempster-Shafer theory (DST). In this way, the inferred network can be more likely to be similar to already discovered pathways and consistent with confirmed PPIs for more reliable inference. The experimental results show which proteins are involved in signaling pathways under IR, how the inferred pathways are different under low and high doses of IR, and how the selected proteins regulate each other in the inferred pathways. As our main contribution, overall results confirm that low dose IR could cause DNA damage and thereby induce and affect related signaling pathways such as apoptosis, cell cycle, and DNA repair.

Resistance mechanisms to genetic suppression of mutant NRAS in melanoma

Targeted therapies have revolutionized cancer care, but the development of resistance remains a challenge in the clinic. To identify rational targets for combination strategies, we used an established melanoma mouse model and selected for resistant tumors following genetic suppression of NRAS expression. Complete tumor regression was observed in all mice, but 40% of tumors recurred. Analysis of resistant tumors showed that the most common mechanism of resistance was overexpression and activation of receptor tyrosine kinases (RTKs). Interestingly, the most commonly overexpressed RTK was Met and inhibition of Met overcame NRAS resistance in this context. Analysis of NRAS mutant human melanoma cells showed enhanced efficacy of cytotoxicity with combined RTK and mitogen-activated protein kinase kinase inhibition. In this study, we establish the importance of adaptive RTK signaling in the escape of NRAS mutant melanoma from inhibition of RAS and provide the rationale for combined blockade of RAS and RTK signaling in this context.

Proteomics and Mass Spectrometry for Cancer Biomarker Discovery

Proteomics is a rapidly advancing field not only in the field of biology but also in translational cancer research. In recent years, mass spectrometry and associated technologies have been explored to identify proteins or a set of proteins specific to a given disease, for the purpose of disease detection and diagnosis. Such biomarkers are being investigated in samples including cells, tissues, serum/plasma, and other types of body fluids. When sufficiently refined, proteomic technologies may pave the way for early detection of cancer or individualized therapy for cancer. Mass spectrometry approaches coupled with bioinformatic tools are being developed for biomarker discovery and validation. Understanding basic concepts and application of such technology by investigators in the field may accelerate the clinical application of protein biomarkers in disease management.

Glucocorticoid resistance is reverted by LCK inhibition in pediatric T-cell acute lymphoblastic leukemia

Pediatric T-acute lymphoblastic leukemia (T-ALL) patients often display resistance to glucocorticoid (GC) treatment. These patients, classified as prednisone poor responders (PPR), have poorer outcome than do the other pediatric T-ALL patients receiving a high-risk adapted therapy. Because glucocorticoids are administered to ALL patients during all the different phases of therapy, GC resistance represents an important challenge to improving the outcome for these patients. Mechanisms underlying resistance are not yet fully unraveled; thus our research focused on the identification of deregulated signaling pathways to point out new targeted approaches. We first identified, by reverse-phase protein arrays, the lymphocyte cell-specific protein-tyrosine kinase (LCK) as aberrantly activated in PPR patients. We showed that LCK inhibitors, such as dasatinib, bosutinib, nintedanib, and WH-4-023, are able to induce cell death in GC-resistant T-ALL cells, and remarkably, cotreatment with dexamethasone is able to reverse GC resistance, even at therapeutic drug concentrations. This was confirmed by specific LCK gene silencing and ex vivo combined treatment of cells from PPR patient-derived xenografts. Moreover, we observed that LCK hyperactivation in PPR patients upregulates the calcineurin/nuclear factor of activated T cells signaling triggering to interleukin-4 (IL-4) overexpression. GC-sensitive cells cultured with IL-4 display an increased resistance to dexamethasone, whereas the inhibition of IL-4 signaling could increase GC-induced apoptosis in resistant cells. Treatment with dexamethasone and dasatinib also impaired engraftment of leukemia cells in vivo. Our results suggest a quickly actionable approach to supporting conventional therapies and overcoming GC resistance in pediatric T-ALL patients.

[Analysis of contribution of protein phosphorylation in the development of the diseases]

In recent decades, studies in the molecular origins of socially significant diseases have made a big step forward with the development and using of high-performance methods in genomics and proteomics. Numerous studies in the framework of the global program "Human Proteome" were aimed at the identification of all possible proteins in various cell cultures and tissues, including cancer. One of the objectives was to identify biomarkers - proteins with high specificity to certain pathologies. However, in many cases, it is shown that the development of the disease is not associated with the appearance of new proteins, but depends on the level of gene expression or forming of proteoforms - splice variants, single amino acid substitutions (SAP variants), and post-translational modifications (PTM) of proteins. PTM may play a key role in the development of pathology because they activate a variety of regulatory or structural proteins in the majority of cell physiological processes. Phosphorylation is among the most significant of these protein modifications.This review will describe methods for analysis of protein phosphorylation used in the studies of such diseases as cancer and neurodegenerative diseases, as well as examples of cases when the modified proteins are involved directly to their development, and screening such significant PTM is used for the diagnosis and choice of treatment.

Optomechanical devices for deep plasma cancer proteomics

Most of the cancer deaths could be avoided by early detection of the tumor when it is confined to its primary site and it has not metastasized. To this aim, one of the most promising strategies is the discovery and detection of protein biomarkers shed by the young tumor to the bloodstream. Proteomic technologies, mainly mass spectrometry and multiplexed immunoassays, have rapidly developed during last years with improved limits of detection and multiplexing capability. Unfortunately, these developments together major investments and large international efforts have not resulted into new useful protein biomarkers. Here, we analyze the potential and limitations of current proteomic technologies for detecting protein biomarkers released into circulation by the tumor. We find that these technologies can hardly probe the deepest region of the plasma proteome, at concentrations below the pg/mL level, where protein biomarkers for early cancer detection may exist. This clearly indicates the need of incorporating novel ultrasensitive techniques to the proteomic tool-box that can cover the inaccessible regions of the plasma proteome. We here propose biological detectors based on nanomechanical systems for discovery and detection of cancer protein biomarkers in plasma. We review the modes of operation of these devices, putting our focus on recent developments on nanomechanical sandwich immunoassays and nanomechanical spectrometry. The first technique enables reproducible immunodetection of proteins at concentrations well below the pg/mL level, with a limit of detection on the verge of 10 ag/mL. This technology can potentially detect low abundance tumor-associated proteins in plasma at the very early stages of the tumor. The second technique enables the identification of individual intact proteins by two physical coordinates, the mass and stiffness, instead of the mass-to-charge ratio of the protein constituents. This technology enormously simplifies the identification of proteins and it can provide useful information on interactions and posttranslational modifications, that otherwise is lost in mass spectrometry.

Inhibition of AKT1 signaling promotes invasion and metastasis of non-small cell lung cancer cells with K-RAS or EGFR mutations

Accumulating evidence supports a role of the PI3K-AKT pathway in the regulation of cell motility, invasion and metastasis. AKT activation is known to promote metastasis, however under certain circumstances, it also shows an inhibitory activity on metastatic processes, and the cause of such conflicting results is largely unclear. Here we found that AKT1 is an important regulator of metastasis and down-regulation of its activity is associated with increased metastatic potential of A549 cells. Inhibition of AKT1 enhanced migration and invasion in KRAS- or EGFR-mutant non-small cell lung cancer (NSCLC) cells. The allosteric AKT inhibitor MK-2206 promoted metastasis of KRAS-mutated A549 cells in vivo. We next identified that the phosphorylation of Myristoylated alanine-rich C-kinase substrate (MARCKS) and LAMC2 protein level were increased with AKT1 inhibition, and MARCKS or LAMC2 knockdown abrogated migration and invasion induced by AKT1 inhibition. This study unravels an anti-metastatic role of AKT1 in the NSCLC cells with KRAS or EGFR mutations, and establishes an AKT1-MARCKS-LAMC2 feedback loop in this regulation.

Increased PDGFR-beta and VEGFR-2 protein levels are associated with resistance to platinum-based chemotherapy and adverse outcome of ovarian cancer patients

Despite frequent initial response rates of epithelial ovarian cancer to platinum-based chemotherapy the majority of patients develop drug resistance. Our aim was to evaluate differential expression of signaling-pathway proteins in platinum-sensitive versus platinum-resistant primary epithelial ovarian cancer specimens to identify predictive biomarkers for treatment response.

192 patients were studied comprising of independent training (n = 89) and validation (n = 103) cohorts. Full-length proteins were extracted from paraffin-embedded samples including multiple regions per tumor to account for intratumoral heterogeneity. Quantitative reverse-phase-protein-arrays were used to analyze protein and phospho-protein levels of 41 signaling molecules including growth-factor receptors, AKT and MAPK signaling pathways as well as angiogenesis and cell-adhesion.

Platinum-resistant ovarian cancers (56/192) demonstrated significantly higher intratumoral levels of the angiogenesis-associated growth-factor receptors PDGFR-beta and VEGFR2 compared to platinum-sensitive tumors. In addition, patients with high PDGFR-beta expression had significantly shorter overall and progression-free survival (HR 3.6 and 2.4; p < 0.001). The prognostic value of PDGFR-beta and VEGFR2 was confirmed in publicly available microarray-datasets.

High intratumoral levels of the angiogenesis-related growth-factor receptors PDGFR-beta and VEGFR2 might serve as novel predictive biomarkers to identify primary resistance to platinum-based chemotherapy. Those ovarian cancer patients might particularly benefit from additional anti-vascular therapy including anti-VEGF antibody or receptor tyrosine-kinase-inhibitor therapy.

Quantum-dot-based suspension microarray for multiplex detection of lung cancer markers: preclinical validation and comparison with the Luminex xMAP® system

A novel suspension multiplex immunoassay for the simultaneous specific detection of lung cancer markers in bronchoalveolar lavage fluid (BALF) clinical samples based on fluorescent microspheres having different size and spectrally encoded with quantum dots (QDEM) was developed. The designed suspension immunoassay was validated for the quantitative detection of three lung cancer markers in BALF samples from 42 lung cancer patients and 10 control subjects. Tumor markers were detected through simultaneous formation of specific immune complexes consisting of a capture molecule, the target antigen, and biotinylated recognition molecule on the surface of the different QDEM in a mixture. The immune complexes were visualized by fluorescently labeled streptavidin and simultaneously analyzed using a flow cytometer. Preclinical validation of the immunoassay was performed and results were compared with those obtained using an alternative 3-plex immunoassay based on Luminex xMAP^® technology, developed on classical organic fluorophores. The comparison showed that the QDEM and xMAP^® assays yielded almost identical results, with clear discrimination between control and clinical samples. Thus, developed QDEM technology can become a good alternative to xMAP^® assays permitting analysis of multiple protein biomarkers using conventional flow cytometers.

Precision diagnostics: moving towards protein biomarker signatures of clinical utility in cancer

Interest in precision diagnostics has been fuelled by the concept that early detection of cancer would benefit patients; that is, if detected early, more tumours should be resectable and treatment more efficacious. Serum contains massive amounts of potentially diagnostic information, and affinity proteomics has risen as an accurate approach to decipher this, to generate actionable information that should result in more precise and evidence-based options to manage cancer. To achieve this, we need to move from single to multiplex biomarkers, a so-called signature, that can provide significantly increased diagnostic accuracy. This Opinion article focuses on the progress being made in identifying protein biomarker signatures of clinical utility, using blood-based proteomics.

Serum Profiling for Identification of Autoantibody Signatures in Diseases Using Protein Microarrays

Protein microarrays are platforms for studying protein-protein interactions and identifying disease-related self-antigens/autoantigens, which elicit an immune response in a high-throughput format. Protein arrays have been extensively used over the past two decades for several clinical applications. By using this platform, serum containing autoantibodies against potential self-antigens can be screened on proteome-wide arrays, harboring a large repertoire of full-length human proteins. Identification of such autoantigens can help deducing early diagnostic, as well as, prognostic markers in case of malignancies, autoimmune disorders, and other systemic diseases. Here, we provide an overview of the protein microarray technology along with details of an established method to study autoantibody profiles from patient sera.

Infrared imaging of high density protein arrays

We propose in this paper that protein microarrays could be analysed by infrared imaging in place of enzymatic or fluorescence labelling.

Proteomic profiling predicts drug response to novel targeted anticancer therapeutics

Most recently approved anti-cancer drugs by the US FDA are targeted therapeutic agents and this represents an important trend for future anticancer therapy. Unlike conventional chemotherapy that rarely considers individual differences, it is crucial for targeted therapies to identify the beneficial subgroup of patients for the treatment. Currently, genomics and transcriptomics are the major 'omic' analytics used in studies of drug response prediction. However, proteomic profiling excels both in its advantages of directly detecting an instantaneous dynamic of the whole proteome, which contains most current diagnostic markers and therapeutic targets. Moreover, proteomic profiling improves understanding of the mechanism for drug resistance and helps finding optimal combination therapy. This article reviews the recent success of applications of proteomic analytics in predicting the response to targeted anticancer therapeutics, and discusses the potential avenues and pitfalls of proteomic platforms and techniques used most in the field.

A multi-analyte immunoassay for thyroid related analytes

We describe the development and validation of multianalyte immunoassays (MAIA) for three analytes, viz., thyroxine (T4), thyroid stimulating hormone (TSH), and thyroglobulin (Tg) essential for assessment of thyroid function but having widely varying molecular weights. Using polycarbonate (PC) track-etched membranes (TEM) as an immobilization support and ¹²⁵I as the tracer, both competitive assay for T4 and non-competitive assay for TSH and Tg were performed on the same TEM. MAIA was found to be highly sensitive and precise with clinically useful working range and correlated very well with individual analyte immunoassays. While we have demonstrated this assay format with radiotracer, it can be used with non-isotopic tracers equally well.

Bulked sample analysis in genetics, genomics and crop improvement

Biological assay has been based on analysis of all individuals collected from sample populations. Bulked sample analysis (BSA), which works with selected and pooled individuals, has been extensively used in gene mapping through bulked segregant analysis with biparental populations, mapping by sequencing with major gene mutants and pooled genomewide association study using extreme variants. Compared to conventional entire population analysis, BSA significantly reduces the scale and cost by simplifying the procedure. The bulks can be built by selection of extremes or representative samples from any populations and all types of segregants and variants that represent wide ranges of phenotypic variation for the target trait. Methods and procedures for sampling, bulking and multiplexing are described. The samples can be analysed using individual markers, microarrays and high-throughput sequencing at all levels of DNA, RNA and protein. The power of BSA is affected by population size, selection of extreme individuals, sequencing strategies, genetic architecture of the trait and marker density. BSA will facilitate plant breeding through development of diagnostic and constitutive markers, agronomic genomics, marker-assisted selection and selective phenotyping. Applications of BSA in genetics, genomics and crop improvement are discussed with their future perspectives.

Cell signaling regulation by protein phosphorylation: a multivariate, heterogeneous, and context-dependent process

Proper spatiotemporal regulation of protein phosphorylation in cells and tissues is required for normal development and homeostasis, but aberrant protein phosphorylation regulation leads to various diseases. The study of signaling regulation by protein phosphorylation is complicated in part by the sheer scope of the kinome and phosphoproteome, dependence of signaling protein functionality on cellular localization, and the complex multivariate relationships that exist between protein phosphorylation dynamics and the cellular phenotypes they control. Additional complexities arise from the ability of microenvironmental factors to influence phosphorylation-dependent signaling and from the tendency for some signaling processes to occur heterogeneously among cells. These considerations should be taken into account when measuring cell signaling regulation by protein phosphorylation.