Antibody-based proteomics: fast-tracking molecular diagnostics in oncology

Single-cell multi-omics in the study of digestive system cancers

Digestive system cancers are prevalent diseases with a high mortality rate, posing a significant threat to public health and economic burden. The diagnosis and treatment of digestive system cancer confront conventional cancer problems, such as tumor heterogeneity and drug resistance. Single-cell sequencing (SCS) emerged at times required and has developed from single-cell RNA-seq (scRNA-seq) to the single-cell multi-omics era represented by single-cell spatial transcriptomics (ST). This article comprehensively reviews the advances of single-cell omics technology in the study of digestive system tumors. While analyzing and summarizing the research cases, vital details on the sequencing platform, sample information, sampling method, and key findings are provided. Meanwhile, we summarize the commonly used SCS platforms and their features, as well as the advantages of multi-omics technologies in combination. Finally, the development trends and prospects of the application of single-cell multi-omics technology in digestive system cancer research are prospected.

Spatial Biology of Breast Cancer

Spatial findings have shaped on our understanding of breast cancer. In this review, we discuss how spatial methods, including spatial transcriptomics and proteomics and the resultant understanding of spatial relationships, have contributed to concepts regarding cancer progression and treatment. In addition to discussing traditional approaches, we examine how emerging multiplex imaging technologies have contributed to the field and how they might influence future research.

Concentrated ionic liquids for proteomics: Caveat emptor!

The use of concentrated ionic liquids (ILs) in the bioanalytical chemistry of proteins is sparse; typically, dilute aqueous IL solutions are used. Concentrated ILs have unique properties that may allow researchers to dissolve previously insoluble protein analytes, to increase the depth and robustness of sample preparation and the analysis of proteins. Previous research using concentrated ILs for this purpose is sparse and there is a need to systematically investigate the structure-activity relationship between the IL structure and its capacity to solubilise proteins. Here, bovine serum albumin was dissolved in various ionic liquids and monitored over time by light microscopy and SDS-PAGE. While qualitative, these measures provide a good estimate of, respectively, the dissolving power of an IL towards the given protein and the retained integrity of the protein. Hydrophilic ILs show the best solubilisation capacity and higher temperatures (in a restricted sense) improve the solubility of the protein. Higher temperatures and longer reaction times reduce the molecular weight of the protein, which could inhibit their applicability in proteomics, unless the conditions are judiciously controlled. Researchers should exercise caution when using concentrated ILs for protein analysis until the full scope and limitations are known, an aspect we are presently investigating.

Realm of proteomics in breast cancer management and drug repurposing to alleviate intricacies of treatment

Breast cancer, a multi-networking heterogeneous disease, has emerged as a serious impediment to progress in clinical oncology. Although technological advancements and emerging cancer research studies have mitigated breast cancer lethality, a precision cancer-oriented solution has not been achieved. Thus, this review will persuade the acquiescence of proteomics-based diagnostic and therapeutic options in breast cancer management. Recently, the evidence of breast cancer health surveillance through imaging proteomics, single-cell proteomics, interactomics, and post-translational modification (PTM) tracking, to construct proteome maps and proteotyping for stage-specific and sample-specific cancer subtyping have outperformed conventional ways of dealing with breast cancer by increasing diagnostic efficiency, prognostic value, and predictive response. Additionally, the paradigm shift in applied proteomics for designing a chemotherapy regimen to identify novel drug targets with minor adverse effects has been elaborated. Finally, the potential of proteomics in alleviating the occurrence of chemoresistance and enhancing reprofiled drugs' effectiveness to combat therapeutic obstacles has been discussed. Owing to the enormous potential of proteomics techniques, the clinical recognition of proteomics in breast cancer management can be achievable and therapeutic intricacies can be surmountable.

Improving de novo protein binder design with deep learning

Recently it has become possible to de novo design high affinity protein binding proteins from target structural information alone. There is, however, considerable room for improvement as the overall design success rate is low. Here, we explore the augmentation of energy-based protein binder design using deep learning. We find that using AlphaFold2 or RoseTTAFold to assess the probability that a designed sequence adopts the designed monomer structure, and the probability that this structure binds the target as designed, increases design success rates nearly 10-fold. We find further that sequence design using ProteinMPNN rather than Rosetta considerably increases computational efficiency.

Single-Nanoparticle Differential Immunoassay for Multiplexed Gastric Cancer Biomarker Monitoring

Precision medicine demands the best application of multiple unambiguous biomarkers to bring uniform decisions in disease prognosis. The remarkable development of heterogeneous immunoassay greatly promotes precision medicine when combined with the biomarker combination strategy. Nevertheless, the cumbersome washing steps in heterogeneous immunoassay have inevitably compromised the accuracy because of the sample losses and nature change of the matrix, challenging the further exploration of a more facile and lower limit-of-detection analysis. The new methodologies with high throughputs and specificity are never out of date to provide simultaneous evaluations and uniform decisions on multiple analytes through a simple process. Herein, we propose a new wash-free immunoassay, named differential assay, for multiplexed biomarker monitoring. The method is based on counting the number difference of unbound nanoparticle tags before and after immunoreactions from a solid support (i.e., magnetic microsphere) by single-particle inductively coupled plasma mass spectrometry (sp-ICP-MS), discarding the tedious washing steps. We primarily explore the proof-of-concept proposal within two types (sandwich and competitive assay), demonstrating the good feasibility for further facile clinical practice. To provide efficient multiplexed evaluations, we synthesized PtNPs with four diameters and screened the most suitable size for efficient differential immunoassay. The wash-free strategy was successfully utilized in simultaneous serological biomarker (CA724, CA199, and CEA) evaluation, with results in good accordance with those measured by the clinical routine method. Potentially, the proposed differential bioassay can be regarded as a more facile and valuable tool in malignancy prognosis and cancer recurrence monitoring.

Inflammation-related immune proteins in maternal plasma as potential predictive biomarkers for rescue cerclage outcome in women with cervical insufficiency

PROBLEM

This study aimed to determine whether various novel plasma mediators of immune regulation associated with inflammation could independently predict the clinical outcome of rescue cerclage in patients with cervical insufficiency (CI).

METHOD OF STUDY

A total of 41 singleton pregnant women (17-25 weeks) who underwent rescue cerclage for CI were retrospectively evaluated. Stored plasma samples were assayed for IGFBP-1, -2, -3, IL-6, latexin, LBP, lipocalin-2, M-CSF, MIP-1α, MMP-8, -9, pentraxin 3, resistin, S100A8, S100A8/A9, thrombospondin-2, TIMP-1, and TNFR2 levels. The primary outcome measures were spontaneous preterm birth (SPTB) at < 28 and < 34 weeks after cerclage placement.

RESULTS

Multivariate Firth's logistic regression analysis revealed that high levels of IGFBP-3 and S100A8/A9, and low levels of MIP-1α were significantly associated with SPTB at < 28 weeks after cerclage placement, whereas only low MIP-1α levels were significantly associated with SPTB at < 34 weeks, even after adjustment for baseline clinical covariates (e.g., cervical dilatation). For the prediction of SPTB at < 28 weeks, the area under the curves (AUC) of IGFBP-3, MIP-1α, and S100A8/A9 were of .686, .691, and .693, respectively. Similarly, the AUC of MIP-1 α was of .659 to predict SPTB at < 34 weeks.

CONCLUSIONS

These findings suggest that plasma IGFBP-3, MIP-1α, and S100A8/A9 can represent noninvasive independent biomarkers for identifying women with CI at high risk for SPTB following rescue cerclage. Nonetheless, further in large, multicenter clinical studies should be performed to confirm the clinical value of these biomarkers.

High ETV6 Levels Support Aggressive B Lymphoma Cell Survival and Predict Poor Outcome in Diffuse Large B-Cell Lymphoma Patients

The identification of prognostic factors for aggressive B-cell lymphomas still represents an unmet clinical need. We used forward phase protein arrays (FFPA) to identify proteins associated with overall survival (OS) from diagnostic formalin-fixed paraffin-embedded material of diffuse large B-cell lymphoma (DLBCL) patients (n = 47). Univariate Cox regression analysis identified numerous proteins, including immune check-point molecules (PDCD1, PDCD2 and PD1L2) and BCL2 to be significantly associated with OS. However, only ETV6 and PIM2 proteins persisted following multivariate Cox analysis. Independent validation studies by immunohistochemistry and analysis of public gene expression profiles of DLBCL confirmed a prognostic role for high ETV6 and ETV6/PIM2 ratios in DLBCL. ETV6 is a recurrently mutated/deleted gene in DLBCL for which its function in this disease entity is currently unknown. We find that ETV6 is upregulated during oncogenic transformation of germinal center B-cells and that it regulates DLBCL survival, as its acute loss results in marked apoptosis. Fluctuations in survivin (BIRC5) expression levels were associated with this phenomenon. Furthermore, an inverse correlation between ETV6 and BIRC5 expression levels was found and correlated with a response to the BIRC5 inhibitor, YM155. In conclusion, we present evidence for an oncogenic function of ETV6 in DLBCL.

A multicolor enzyme-linked immunoassay method for visual readout of carbendazim

Enzyme-linked immunosorbent assay (ELISA) with high specificity and sensitivity is one of the most popular techniques for detecting carbendazim (CBD), a commonly used benzimidazole fungicide in agriculture. However, the traditional ELISA based on the horseradish peroxidase (HRP)-3,3',5,5'-tetramethylbenzidine (TMB) system for CBD only displays the yellow color of TMB²⁺ from deep to light, making it difficult for the naked eye to judge whether CBD in fruits and vegetables exceeds the maximum residue limit. In this article, we intend to improve the traditional ELISA method to establish a multicolor signal output ELISA to achieve visual semiquantitative detection of CBD. This method is based on the optical properties of gold nanorods (AuNRs). After introducing AuNRs into TMB²⁺ solution, which was produced by the HRP-TMB system of traditional ELISA, AuNRs were quickly etched by TMB²⁺. Consequently, the longitudinal localized surface plasmon resonance peak of AuNRs shows a clear blue shift and a vivid color change. Different concentrations of CBD generate different amounts of TMB²⁺, which in turn leads to different etching degrees of AuNRs, and ultimately results in a rainbow-like color change. As a result, CBD from 0.08 to 100 ng mL^-1 can be easily distinguished by the naked eye, which does not require any large instruments. Moreover, the colors displayed by 0.49 ng mL^-1 (purple) and 0 ng mL^-1 (pink) are significantly different from each other. It should be noted that 0.49 ng mL^-1 is far below the most stringent maximum residue limit of CBD in the world. Additionally, the quantitative determination of CBD spiked in canned citrus, citrus fruits, chives, and cabbage samples showed satisfactory recoveries. The good performance of the AuNR-based ELISA makes it have a wide range of application prospects in food safety and international trade.

Towards Building a Quantitative Proteomics Toolbox in Precision Medicine: A Mini-Review

Precision medicine as a framework for disease diagnosis, treatment, and prevention at the molecular level has entered clinical practice. From the start, genetics has been an indispensable tool to understand and stratify the biology of chronic and complex diseases in precision medicine. However, with the advances in biomedical and omics technologies, quantitative proteomics is emerging as a powerful technology complementing genetics. Quantitative proteomics provide insight about the dynamic behaviour of proteins as they represent intermediate phenotypes. They provide direct biological insights into physiological patterns, while genetics accounting for baseline characteristics. Additionally, it opens a wide range of applications in clinical diagnostics, treatment stratification, and drug discovery. In this mini-review, we discuss the current status of quantitative proteomics in precision medicine including the available technologies and common methods to analyze quantitative proteomics data. Furthermore, we highlight the current challenges to put quantitative proteomics into clinical settings and provide a perspective to integrate proteomics data with genomics data for future applications in precision medicine.

Precision medicine and phosphoproteomics for the identification of novel targeted therapeutic avenues in sarcomas

Rapid advances in genomic technologies have enabled in-depth interrogation of cancer genomes, revealing novel and unexpected therapeutic targets in many cancer types. Identifying actionable dependencies in the diverse and heterogeneous group of sarcomas, particularly those that occur in children or adolescents and young adults (AYAs), remains especially challenging. These patients rarely harbor actionable genomic aberrations, no targeted agent is approved, and outcomes have remained poor for the past decades. This underlines a clear need to refine our methods for target identification. Phosphoproteomics studies in sarcoma showed the power of such analyses to capture novel actionable drivers that are not accompanied by mutational events or gene amplifications. This Review makes the case that incorporating phosphoproteomic molecular profiling alongside (functional) genomics technologies can significantly expand therapeutic target identification, and pinpoint drug mechanisms of action, in pediatric and AYA sarcoma patients. We explore the utility and prospects of phosphoproteomics in personalized medicine.

The geometry of clinical labs and wellness states from deeply phenotyped humans

Longitudinal multi-omics measurements are highly valuable in studying heterogeneity in health and disease phenotypes. For thousands of people, we have collected longitudinal multi-omics data. To analyze, interpret and visualize this extremely high-dimensional data, we use the Pareto Task Inference (ParTI) method. We find that the clinical labs data fall within a tetrahedron. We then use all other data types to characterize the four archetypes. We find that the tetrahedron comprises three wellness states, defining a wellness triangular plane, and one aberrant health state that captures aspects of commonality in movement away from wellness. We reveal the tradeoffs that shape the data and their hierarchy, and use longitudinal data to observe individual trajectories. We then demonstrate how the movement on the tetrahedron can be used for detecting unexpected trajectories, which might indicate transitions from health to disease and reveal abnormal conditions, even when all individual blood measurements are in the norm.

High-throughput determination of protein affinities using unmodified peptide libraries in nanomolar scale

Protein-protein interactions (PPIs) are of fundamental importance for our understanding of physiology and pathology. PPIs involving short, linear motifs play a major role in immunological recognition, signaling, and regulation and provide attractive starting points for pharmaceutical intervention. Yet, state-of-the-art protein-peptide affinity determination approaches exhibit limited throughput and sensitivity, often resulting from ligand immobilization, labeling, or synthesis. Here, we introduce a high-throughput method for in-solution analysis of protein-peptide interactions using a phenomenon called temperature related intensity change (TRIC). We use TRIC for the identification and fine-mapping of low- and high-affinity protein interaction sites and the definition of sequence binding requirements. Validation is achieved by microarray-based studies using wild-type and mutated recombinant protein and the native protein within tissue lysates. On-chip neutralization and strong correlation with structural data establish TRIC as a quasi-label-free method to determine binding affinities of unmodified peptide libraries with large dynamic range.

Solubility, Stability, and Avidity of Recombinant Antibody Fragments Expressed in Microorganisms

Solubility of recombinant proteins (i.e., the extent of soluble versus insoluble expression in heterogeneous hosts) is the first checkpoint criterion for determining recombinant protein quality. However, even soluble proteins often fail to represent functional activity because of the involvement of non-functional, misfolded, soluble aggregates, which compromise recombinant protein quality. Therefore, screening of solubility and folding competence is crucial for improving the quality of recombinant proteins, especially for therapeutic applications. The issue is often highlighted especially in bacterial recombinant hosts, since bacterial cytoplasm does not provide an optimal environment for the folding of target proteins of mammalian origin. Antibody fragments, such as single-chain variable fragment (scFv), single-chain antibody (scAb), and fragment antigen binding (Fab), have been utilized for numerous applications such as diagnostics, research reagents, or therapeutics. Antibody fragments can be efficiently expressed in microorganisms so that they offer several advantages for diagnostic applications such as low cost and high yield. However, scFv and scAb fragments have generally lower stability to thermal stress than full-length antibodies, necessitating a judicious combination of designer antibodies, and bacterial hosts harnessed with robust chaperone function. In this review, we discuss efforts on not only the production of antibodies or antibody fragments in microorganisms but also scFv stabilization via (i) directed evolution of variants with increased stability using display systems, (ii) stabilization of the interface between variable regions of heavy (V_H) and light (V_L) chains through the introduction of a non-native covalent bond between the two chains, (iii) rational engineering of V_H-V_L pair, based on the structure, and (iv) computational approaches. We also review recent advances in stability design, increase in avidity by multimerization, and maintaining the functional competence of chimeric proteins prompted by various types of chaperones.

Heterogeneous Strategies to Eliminate Intracellular Bacterial Pathogens

Antibiotic tolerance in bacterial pathogens that are genetically susceptible, but phenotypically tolerant to treatment, represents a growing crisis for public health. In particular, the intracellular bacteria-mediated antibiotic tolerance by acting as “Trojan horses” play a critical and underappreciated role in the disease burden of bacterial infections. Thus, more intense efforts are required to tackle this problem. In this review, we firstly provide a brief overview of modes of action of bacteria invasion and survival in macrophage or non-professional phagocytic cells. Furthermore, we summarize our current knowledge about promising strategies to eliminate these intracellular bacterial pathogens, including direct bactericidal agents, antibiotic delivery to infection sites by various carriers, and activation of host immune functions. Finally, we succinctly discuss the challenges faced by bringing them into clinical trials and our constructive perspectives.

Cobalt-Directed Assembly of Antibodies onto Metal-Phenolic Networks for Enhanced Particle Targeting

The orientation-specific immobilization of antibodies onto nanoparticles, to preserve antibody-antigen recognition, is a key challenge in developing targeted nanomedicines. Herein, we report the targeting ability of metal-phenolic network (MPN)-coated gold nanoparticles with surface-physisorbed antibodies against respective antigens. The MPN coatings were self-assembled from metal ions (Fe^III, Co^II, Cu^II, Ni^II, or Zn^II) cross-linked with tannic acid. Upon physisorption of antibodies, all particle systems exhibited enhanced association with target antigens, with Co^II systems demonstrating more than 2-fold greater association. These systems contained more metal atoms distributed in a way to specifically interact with antibodies, which were investigated by molecular dynamics simulations. A model antibody fragment crystallizable (Fc) region in solution with Co^II-tannic acid complexes revealed that the solvent-exposed Co^II can directly coordinate to the histidine-rich portion of the Fc region. This one-pot interaction suggests anchoring of the antibody Fc region to the MPN on nanoparticles, allowing for enhanced targeting.

Advances in quantitative immunohistochemistry and their contribution to breast cancer

Introduction: Automated image analysis provides an objective, quantitative, and reproducible method of measurement of biomarkers. Image quantification is particularly well suited for the analysis of tissue microarrays which has played a major pivotal role in the rapid assessment of molecular biomarkers. Data acquired from grinding up bulk tissue samples miss spatial information regarding cellular localization; therefore, methods that allow for spatial cell phenotyping at high resolution have proven to be valuable in many biomarker discovery assays. Here, we focus our attention on breast cancer as an example of a tumor type that has benefited from quantitative biomarker studies using tissue microarray format.Areas covered: The history of immunofluorescence and immunohistochemistry and the current status of these techniques, including multiplexing technologies (spectral and non-spectral) and image analysis software will be addressed. Finally, we will turn our attention to studies that have provided proof-of-principle evidence that have been impacted from the use of these techniques.Expert opinion: Assessment of prognostic and predictive biomarkers on tissue sections and TMA using Quantitative immunohistochemistry is an important advancement in the investigation of biologic markers. The challenges in standardization of quantitative technologies for accurate assessment are required for adoption into routine clinical practice.

Nanoplasmonic On-Chip PCR for Rapid Precision Molecular Diagnostics

Emerging molecular diagnosis requires ultrafast polymerase chain reaction (PCR) on chip for rapid precise detection of infectious diseases in the point-of-care test. Here, we report nanoplasmonic on-chip PCR for rapid precision molecular diagnostics. The nanoplasmonic pillar arrays (NPA) comprise gold nanoislands on the top and sidewall of large-scale glass nanopillar arrays. The nanoplasmonic pillars enhance light absorption of a white light-emitting diode (LED) over the whole visible range due to strong electromagnetic hotspots between the nanoislands. As a result, they effectively induce photothermal heating for ultrafast PCR thermal cycling. The temperature profile of NPA exhibits 30 cycles between 98 and 60 °C for a total of 3 min and 30 s during the cyclic excitation of white LED light. The experimental results also demonstrate the rapid DNA amplification of both 0.1 ng μL^-1 of λ-DNA in 20 thermal cycles and 0.1 ng μL^-1 of complementary DNA of Middle East respiratory syndrome coronavirus in 30 thermal cycles using a conventional PCR volume of 15 μL. This nanoplasmonic PCR technique provides a new opportunity for rapid precision molecular diagnostics.

Programmable Bivalent Peptide-DNA Locks for pH-Based Control of Antibody Activity

The ability to control antibody activity by pH has important applications in diagnostics, therapeutic antibody targeting, and antibody-guided imaging. Here, we report the rational design of bivalent peptide-DNA ligands that allow pH-dependent control of antibody activity. Our strategy uses a pH-responsive DNA triple helix to control switching from a tight-binding bivalent peptide-DNA lock into a weaker-binding monovalent ligand. Different designs are introduced that allow antibody activation at both basic and acidic pHs, either autonomously or in the presence of an additional oligonucleotide trigger. The pH of antibody activation could be precisely tuned by changing the DNA triple helix sequence. The peptide-DNA locks allowed pH-dependent antibody targeting of tumor cells both in bulk and for single cells confined in water-in-oil microdroplets. The latter approach enables high-throughput antibody-mediated detection of single tumor cells based on their distinctive metabolic activity.

Serum IGFBP-1 as a potential biomarker for diagnosis of early-stage upper gastrointestinal tumour

BACKGROUND

Early detection would improve upper gastrointestinal cancer prognosis. We aimed to identify serum protein biomarker for the detection of early-stage upper gastrointestinal cancer.

METHODS

We performed a three-tiered study including 2028 participants from three medical centres. First, we applied two different antibody arrays to screen candidate serum proteins that increased in 20 patients with oesophageal squamous cell carcinoma (ESCC) compared with 20 normal controls. We then evaluated the selected protein by enzyme-linked immunosorbent assay in 1064 participants including 731 upper gastrointestinal cancer patients (287 ESCCs, 237 oesophagogastric junction adenocarcinomas (EJAs), and 207 stomach cancers) and 333 normal controls. The diagnostic value of the selected protein was finally validated in two independent cohorts of ESCC patients and controls (n=472 and 452, respectively). The receiver operating characteristic was used to calculate diagnostic accuracy.

FINDINGS

Serum insulin-like growth factor binding protein-1 (IGFBP-1) identified in both antibody arrays showed significantly elevated levels in upper gastrointestinal cancers, compared with normal controls. Serum IGFBP-1 provided high diagnostic accuracy of early-stage ESCC, EJA, stomach and cancer (areas under the curve: 0·898, 0·936 and 0·864, respectively). This protein maintained diagnostic performance for early-stage ESCC in independent cohorts 1 and 2 (0·849 and 0·911, respectively). Additionally, serum levels of IGFBP-1 dropped significantly after surgical resection of primary tumours, compared with the corresponding pre-operative ESCC samples (p < 0·05).

INTERPRETATION

Serum IGFBP-1 represents a promising diagnostic biomarker to detect early-stage upper gastrointestinal cancer.

Plasmon-Amplified Endogenous Fluorescence Nanospectroscopic Sensor Based on Inherent Elastic Scattering for Ultratrace Ratiometric Detection of Capsaicinoids

Endogenous fluorescence imaging techniques are key for modern single-molecule quantification without the use of additional labeling probes. However, the drawback of weak fluorescence signal is the primary challenge in meeting the ever-increasing demands of single-molecule detection. Here, we report a simple and reliable method that provides up to ∼100-fold uniform fluorescence enhancement of endogenous fluorescence of the capsaicinoid molecule. The method is based on a single nanoparticle plasmon-amplified endogenous fluorescence nanospectroscopic sensor (PAEFS). This work demonstrated the applicability of PAEFS in refining sensitivity at the single-molecule level by showing ultralow limits of detection (10⁶ times lower than previous reports) of fluorescence-based capsaicinoids with a wide range of linear response (18 zM to 85 pM). Spectrally overlapped capsaicinoid analogues were quantified ratiometrically to detect the analogue percentages in real samples. The novel endogenous fluorescence enhancement approach presented here represents a universal sensor for enhanced detection of single molecules using existing techniques without altering the original molecular features or using add-on labeling probes.

Applying Machine Learning of Erythrocytes Dynamic Antigens Store in Medicine

Erythrocytes Dynamic Antigens Store (EDAS) is a new discovery. EDAS consists of self-antigens and foreign (non-self) antigens. In patients with infectious diseases or malignancies, antigens of infection microorganism or malignant tumor exist in EDAS. Storing EDAS of normal individuals and patients in a database has, at least, two benefits. First, EDAS can be mined to determine biomarkers representing diseases which can enable researchers to develop a new line of laboratory diagnostic tests and vaccines. Second, EDAS can be queried, directly, to reach a precise diagnosis without the need to do many laboratory tests. The target is to find the minimum set of proteins that can be used as biomarkers for a particular disease. A hypothetical EDAS is created. Hundred-thousand records are randomly generated. The mathematical model of hypothetical EDAS together with the proposed techniques for biomarker discovery and direct diagnosis are described. The different possibilities that may occur in reality are experimented. Biomarkers' proteins are identified for pathogens and malignancies, which can be used to diagnose conditions that are difficult to diagnose. The presented tool can be used in clinical laboratories to diagnose disease disorders.

Integrated analysis of transcription factors and targets co-expression profiles reveals reduced correlation between transcription factors and target genes in cancer

Transcription factors are recognized as the key regulators of gene expression. However, the changes in the correlation of transcription factors and their target genes between normal and tumor tissues are usually ignored. In this research, we used mRNA expression profile data from The Cancer Genome Atlas which included 5726 samples across 11 major human cancers to perform co-expression analysis by the Pearson correlation coefficients. Then, integrating 81,357 pairs of transcription factors and target genes from transcription factors databases to find out the changes in the co-expression correlation of these gene pairs from normal to tumor tissues. Based on the changes in the number of co-expressed TF-TG pairs and changes in the level of co-expression, we found the generally reduced correlation between transcription factors and their target genes in cancer. Additionally, we screened out universal and specific transcription factors-target genes pairs which may significant influence particular cancer. Then, we obtained 423 cancer cell line expression profiles from Broad Institute Cancer Cell Line Encyclopedia to verify our results. Some of these pairs like XRCC5-XRCC6 have been reported to involve in multiple cancers, while pairs like IRF1-PSMB9 without any previous articles related to tumor but involve in the biological processes of cancer, which are of great potential to be therapeutic targets. Our research may provide insights to better understand the tumor development mechanisms and find potential therapeutic targets.

Add-on plasmonic patch as a universal fluorescence enhancer

Fluorescence-based techniques are the cornerstone of modern biomedical optics, with applications ranging from bioimaging at various scales (organelle to organism) to detection and quantification of a wide variety of biological species of interest. However, the weakness of the fluorescence signal remains a persistent challenge in meeting the ever-increasing demand to image, detect, and quantify biological species with low abundance. Here, we report a simple and universal method based on a flexible and conformal elastomeric film with adsorbed plasmonic nanostructures, which we term a "plasmonic patch," that provides large (up to 100-fold) and uniform fluorescence enhancement on a variety of surfaces through simple transfer of the plasmonic patch to the surface. We demonstrate the applications of the plasmonic patch in improving the sensitivity and limit of detection (by more than 100 times) of fluorescence-based immunoassays implemented in microtiter plates and in microarray format. The novel fluorescence enhancement approach presented here represents a disease, biomarker, and application agnostic ubiquitously applicable fundamental and enabling technology to immediately improve the sensitivity of existing analytical methodologies in an easy-to-handle and cost-effective manner, without changing the original procedures of the existing techniques.

In situ protein detection with enhanced specificity using DNA-conjugated antibodies and proximity ligation

Antibodies are important tools in anatomical pathology and research, but the quality of in situ protein detection by immunohistochemistry greatly depends on the choice of antibodies and the abundance of the targeted proteins. Many antibodies used in scientific research do not meet requirements for specificity and sensitivity. Accordingly, methods that improve antibody performance and produce quantitative data can greatly advance both scientific investigations and clinical diagnostics based on protein expression and in situ localization. We demonstrate here protocols for antibody labeling that allow specific protein detection in tissues via bright-field in situ proximity ligation assays, where each protein molecule must be recognized by two antibodies. We further demonstrate that single polyclonal antibodies or purified serum preparations can be used for these dual recognition assays. The requirement for protein recognition by pairs of antibody conjugates can significantly improve specificity of protein detection over single-binder assays.

Assessment of Significance of Novel Proteins in Breast Cancer Using Tissue Microarray Technology

The arraying of formalin-fixed paraffin-embedded (FFPE) tissue, or less commonly frozen tissue, in tissue microarrays (TMAs) is an invaluable method with which to assess the association of novel proteins with a myriad of diseases in large cohorts of patients allowing high throughput evaluation as potential biomarkers. TMAs are most frequently used in cancer studies although they are not limited to this application. The most common method of evaluation of TMAs is via immunohistochemistry (IHC) which is an antibody-based protein localisation method routinely used in the clinical laboratory. However, significant issues still exist with respect to the validation of antibodies for use on TMA sections, with a large number of published studies failing to do so correctly [O'Hurley et al. Mol Oncol, doi:10.1016/j.molonc.2014.03.008, 2014]. Here, we present a method to determine the antibody specificity for use in immunohistochemistry (IHC), as well as the analysis and interpretation of results from an IHC-stained TMA.

Spatial perspectives in the redox code-Mass spectrometric proteomics studies of moonlighting proteins

The Redox Code involves specific, reversible oxidative changes in proteins that modulate protein tertiary structure, interactions, trafficking, and activity, and hence couple the proteome to the metabolic/oxidative state of cells. It is currently a major focus of study in cell biology. Recent studies of dynamic cellular spatial reorganization with MS-based subcellular-spatial-razor proteomics reveal that protein constituents of many subcellular structures, including mitochondria, the endoplasmic reticulum, the plasma membrane, and the extracellular matrix, undergo changes in their subcellular abundance/distribution in response to oxidative stress. These proteins are components of a diverse variety of functional processes spatially distributed across cells. Many of the same proteins are involved in response to suppression of DNA replication indicate that oxidative stress is strongly intertwined with DNA replication/proliferation. Both are replete with networks of moonlighting proteins that show coordinated changes in subcellular location and that include primary protein actuators of the redox code involved in the processing of NAD⁺ /NADH, NADP⁺ /NADPH, Cys/CySS, and GSH/GSSG redox couples. Small groups of key proteins such as {KPNA2, KPNB1, PCNA, PTMA, SET} constitute "spatial switches" that modulate many nuclear processes. Much of the functional response involves subcellular protein trafficking, including nuclear import/export processes, vesicle-mediated trafficking, the endoplasmic reticulum/Golgi pathway, chaperone-assisted processes, and other transport systems. This is not visible to measurements of total protein abundance by transcriptomics or proteomics. Comprehensive pictures of cellular function will require collection of data on the subcellular transport and local functions of many moonlighting proteins, especially of those with critical roles in spatial coordination across cells. The proteome-wide analysis of coordinated changes in abundance and trafficking of proteins offered by MS-based proteomics has a unique, crucial role to play in deciphering the complex adaptive systems that underlie cellular function. © 2016 Wiley Periodicals, Inc. Mass Spec Rev.

Tissue and plasma proteomics for early stage cancer detection

The pursuit of novel and effective biomarkers is essential in the struggle against cancer, which is a leading cause of mortality worldwide. Here we discuss the relative advantages and disadvantages of the most frequently used proteomics techniques, concentrating on the latest advances and application of tissue and plasma proteomics for novel cancer biomarker discovery.

A pathology atlas of the human cancer transcriptome

Cancer is one of the leading causes of death, and there is great interest in understanding the underlying molecular mechanisms involved in the pathogenesis and progression of individual tumors. We used systems-level approaches to analyze the genome-wide transcriptome of the protein-coding genes of 17 major cancer types with respect to clinical outcome. A general pattern emerged: Shorter patient survival was associated with up-regulation of genes involved in cell growth and with down-regulation of genes involved in cellular differentiation. Using genome-scale metabolic models, we show that cancer patients have widespread metabolic heterogeneity, highlighting the need for precise and personalized medicine for cancer treatment. All data are presented in an interactive open-access database (www.proteinatlas.org/pathology) to allow genome-wide exploration of the impact of individual proteins on clinical outcomes.

Oxidative Stress in Kidney Diseases: The Cause or the Consequence?

Exaggerated oxidative stress (OS) is usually considered as a disturbance in regular function of an organism. The excessive levels of OS mediators may lead to major damage within the organism’s cells and tissues. Therefore, the OS-associated biomarkers may be considered as new diagnostic tools of various diseases. In nephrology, researchers are looking for alternative methods replacing the renal biopsy in patients with suspicion of chronic kidney disease (CKD). Currently, CKD is a frequent health problem in world population, which can lead to progressive loss of kidney function and eventually to end-stage renal disease. The course of CKD depends on the primary disease. It is assumed that one of the factors influencing the course of CKD might be OS. In the current work, we review whether monitoring the OS-associated biomarkers in nephrology patients can support the decision-making process regarding diagnosis, prognostication and treatment initiation.

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.

Prediction of Response to Sorafenib in Hepatocellular Carcinoma: A Putative Marker Panel by Multiple Reaction Monitoring-Mass Spectrometry (MRM-MS)

Sorafenib is the only standard treatment for unresectable hepatocellular carcinoma (HCC), but it provides modest survival benefits over placebo, necessitating predictive biomarkers of the response to sorafenib. Serum samples were obtained from 115 consecutive patients with HCC before sorafenib treatment and analyzed by multiple reaction monitoring-mass spectrometry (MRM-MS) and ELISA to quantify candidate biomarkers. We verified a triple-marker panel to be predictive of the response to sorafenib by MRM-MS, comprising CD5 antigen-like (CD5L), immunoglobulin J (IGJ), and galectin-3-binding protein (LGALS3BP), in HCC patients. This panel was a significant predictor (AUROC > 0.950) of the response to sorafenib treatment, having the best cut-off value (0.4) by multivariate analysis. In the training set, patients who exceeded this cut-off value had significantly better overall survival (median, 21.4 months) than those with lower values (median, 8.6 months; p = 0.001). Further, a value that was lower than this cutoff was an independent predictor of poor overall survival [hazard ratio (HR), 2.728; 95% confidence interval (CI), 1.312-5.672; p = 0.007] and remained an independent predictive factor of rapid progression (HR, 2.631; 95% CI, 1.448-4.780; p = 0.002). When applied to the independent validation set, levels of the cut-off value for triple-marker panel maintained their prognostic value for poor clinical outcomes. On the contrast, the triple-marker panel was not a prognostic factor for patients who were treated with transarterial chemoembolization (TACE). The discriminatory signature of a triple-marker panel provides new insights into targeted proteomic biomarkers for individualized sorafenib therapy.

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.

A Stepwise Integrated Approach to Personalized Risk Predictions in Stage III Colorectal Cancer

Purpose: Apoptosis is essential for chemotherapy responses. In this discovery and validation study, we evaluated the suitability of a mathematical model of apoptosis execution (APOPTO-CELL) as a stand-alone signature and as a constituent of further refined prognostic stratification tools.Experimental Design: Apoptosis competency of primary tumor samples from patients with stage III colorectal cancer (n = 120) was calculated by APOPTO-CELL from measured protein concentrations of Procaspase-3, Procaspase-9, SMAC, and XIAP. An enriched APOPTO-CELL signature (APOPTO-CELL-PC3) was synthesized to capture apoptosome-independent effects of Caspase-3. Furthermore, a machine learning Random Forest approach was applied to APOPTO-CELL-PC3 and available molecular and clinicopathologic data to identify a further enhanced signature. Association of the signature with prognosis was evaluated in an independent colon adenocarcinoma cohort (TCGA COAD, n = 136).Results: We identified 3 prognostic biomarkers (P = 0.04, P = 0.006, and P = 0.0004 for APOPTO-CELL, APOPTO-CELL-PC3, and Random Forest signatures, respectively) with increasing stratification accuracy for patients with stage III colorectal cancer.The APOPTO-CELL-PC3 signature ranked highest among all features. The prognostic value of the signatures was independently validated in stage III TCGA COAD patients (P = 0.01, P = 0.04, and P = 0.02 for APOPTO-CELL, APOPTO-CELL-PC3, and Random Forest signatures, respectively). The signatures provided further stratification for patients with CMS1-3 molecular subtype.Conclusions: The integration of a systems-biology-based biomarker for apoptosis competency with machine learning approaches is an appealing and innovative strategy toward refined patient stratification. The prognostic value of apoptosis competency is independent of other available clinicopathologic and molecular factors, with tangible potential of being introduced in the clinical management of patients with stage III colorectal cancer. Clin Cancer Res; 23(5); 1200-12. ©2016 AACR.

SpotLight Proteomics: uncovering the hidden blood proteome improves diagnostic power of proteomics

The human blood proteome is frequently assessed by protein abundance profiling using a combination of liquid chromatography and tandem mass spectrometry (LC-MS/MS). In traditional sequence database search, many good-quality MS/MS data remain unassigned. Here we uncover the hidden part of the blood proteome via novel SpotLight approach. This method combines de novo MS/MS sequencing of enriched antibodies and co-extracted proteins with subsequent label-free quantification of new and known peptides in both enriched and unfractionated samples. In a pilot study on differentiating early stages of Alzheimer’s disease (AD) from Dementia with Lewy Bodies (DLB), on peptide level the hidden proteome contributed almost as much information to patient stratification as the apparent proteome. Intriguingly, many of the new peptide sequences are attributable to antibody variable regions, and are potentially indicative of disease etiology. When the hidden and apparent proteomes are combined, the accuracy of differentiating AD (n = 97) and DLB (n = 47) increased from ≈85% to ≈95%. The low added burden of SpotLight proteome analysis makes it attractive for use in clinical settings.

Fluorescence Sensing of Circulating Diagnostic Biomarkers Using Molecular Probes and Nanoparticles

The interplay of photonics, nanotechnology, and biochemistry has significantly improved the identification and characterization of multiple types of biomarkers by optical biosensors. Great achievements in fluorescence-based technologies have been realized, for example, by the advancement of multiplexing techniques or the introduction of nanoparticles to biochemical and clinical research. This review presents a concise overview of recent advances in fluorescence sensing techniques for the detection of circulating disease biomarkers. Detection principles of representative approaches, including fluorescence detection using molecular fluorophores, quantum dots, and metallic and silica nanoparticles, are explained and illustrated by pertinent examples from the recent literature. Advanced detection technologies and material development play a major role in modern biosensing and consistently provide significant improvements toward robust, sensitive, and versatile platforms for early detection of circulating diagnostic biomarkers.

ANLN is a prognostic biomarker independent of Ki-67 and essential for cell cycle progression in primary breast cancer

BACKGROUND

Anillin (ANLN), an actin-binding protein required for cytokinesis, has recently been presented as part of a prognostic marker panel in breast cancer. The objective of the current study was to further explore the prognostic and functional value of ANLN as a single biomarker in breast cancer.

METHODS

Immunohistochemical assessment of ANLN protein expression was performed in two well characterized breast cancer cohorts (n = 484) with long-term clinical follow-up data and the results were further validated at the mRNA level in a publicly available transcriptomics dataset. The functional relevance of ANLN was investigated in two breast cancer cell lines using RNA interference.

RESULTS

High nuclear fraction of ANLN in breast tumor cells was significantly associated with large tumor size, high histological grade, high proliferation rate, hormone receptor negative tumors and poor prognosis in both examined cohorts. Multivariable analysis showed that the association between ANLN and survival was significantly independent of age in cohort I and significantly independent of proliferation, as assessed by Ki-67 expression in tumor cells, age, tumor size, ER and PR status, HER2 status and nodal status in cohort II. Analysis of ANLN mRNA expression confirmed that high expression of ANLN was significantly correlated to poor overall survival in breast cancer patients. Consistent with the role of ANLN during cytokinesis, transient knock-down of ANLN protein expression in breast cancer cell lines resulted in an increase of senescent cells and an accumulation of cells in the G2/M phase of the cell cycle with altered cell morphology including large, poly-nucleated cells. Moreover, ANLN siRNA knockdown also resulted in decreased expression of cyclins D1, A2 and B1.

CONCLUSIONS

ANLN expression in breast cancer cells plays an important role during cell division and a high fraction of nuclear ANLN expression in tumor cells is correlated to poor prognosis in breast cancer patients, independent of Ki-67, tumor size, hormone receptor status, HER2 status, nodal status and age.

Urinary biomarkers for renal tract malformations

INTRODUCTION

Renal tract malformations (RTMs) are congenital anomalies of the kidneys and urinary tract, which are the major cause of end-stage renal disease in children. Using immunoassay-based approaches (ELISA, western blot), individual urinary proteins including transforming growth factor β, tumor necrosis factor and monocyte attractant proteins 1 were found to be associated to RTMs. However, only mass spectrometry (MS) based methods leading to the identification of panels of protein-based markers composed of fragments of the extracellular matrix allowed the prediction of progression of RTMs and its complications. Areas covered: In this review, we summarized relevant studies identified in "Pubmed" using the keywords "urinary biomarkers" and "proteomics" and "renal tract malformations" or "hydronephrosis" or "ureteropelvic junction obstruction" or "posterior urethral valves" or "vesicoureteral reflux". These publications represent studies on potential protein-based biomarkers, either individually or combined in panels, of RTMs in human and animal models. Expert commentary: Successful use in the clinic of these protein-based biomarkers will need to involve larger scale studies to reach sufficient power. Improved performance will potentially come from combining immunoassay- and MS-based markers.

Emerging power of proteomics for delineation of intrinsic tumor subtypes and resistance mechanisms to anti-cancer therapies

INTRODUCTION

Despite extreme genetic heterogeneity, tumors often show similar alterations in the expression, stability, and activation of proteins important in oncogenic signaling pathways. Thus, classifying tumor samples according to shared proteomic features may help facilitate the identification of cancer subtypes predictive of therapeutic responses and prognostic for patient outcomes. Meanwhile, understanding mechanisms of intrinsic and acquired resistance to anti-cancer therapies at the protein level may prove crucial to devising reversal strategies. Areas covered: Herein, we review recent advances in quantitative proteomic technology and their applications in studies to identify intrinsic tumor subtypes of various tumors, to illuminate mechanistic aspects of pharmacological and oncogenic adaptations, and to highlight interaction targets for anti-cancer compounds and cancer-addicted proteins. Expert commentary: Quantitative proteomic technologies are being successfully employed to classify tumor samples into distinct intrinsic subtypes, to improve existing DNA/RNA based classification methods, and to evaluate the activation status of key signaling pathways.

Omics Profiling in Precision Oncology

Cancer causes significant morbidity and mortality worldwide, and is the area most targeted in precision medicine. Recent development of high-throughput methods enables detailed omics analysis of the molecular mechanisms underpinning tumor biology. These studies have identified clinically actionable mutations, gene and protein expression patterns associated with prognosis, and provided further insights into the molecular mechanisms indicative of cancer biology and new therapeutics strategies such as immunotherapy. In this review, we summarize the techniques used for tumor omics analysis, recapitulate the key findings in cancer omics studies, and point to areas requiring further research on precision oncology.

Protein Profiling Gastric Cancer and Neighboring Control Tissues Using High-Content Antibody Microarrays

In this study, protein profiling was performed on gastric cancer tissue samples in order to identify proteins that could be utilized for an effective diagnosis of this highly heterogeneous disease and as targets for therapeutic approaches. To this end, 16 pairs of postoperative gastric adenocarcinomas and adjacent non-cancerous control tissues were analyzed on microarrays that contain 813 antibodies targeting 724 proteins. Only 17 proteins were found to be differentially regulated, with much fewer molecules than the numbers usually identified in studies comparing tumor to healthy control tissues. Insulin-like growth factor-binding protein 7 (IGFBP7), S100 calcium binding protein A9 (S100A9), interleukin-10 (IL‐10) and mucin 6 (MUC6) exhibited the most profound variations. For an evaluation of the proteins’ capacity for discriminating gastric cancer, a Receiver Operating Characteristic curve analysis was performed, yielding an accuracy (area under the curve) value of 89.2% for distinguishing tumor from non-tumorous tissue. For confirmation, immunohistological analyses were done on tissue slices prepared from another cohort of patients with gastric cancer. The utility of the 17 marker proteins, and particularly the four molecules with the highest specificity for gastric adenocarcinoma, is discussed for them to act as candidates for diagnosis, even in serum, and targets for therapeutic approaches.