Protein modifications as potential biomarkers in breast cancer

Golgi apparatus targeted therapy in cancer: Are we there yet?

Membrane trafficking within the Golgi apparatus plays a pivotal role in the intracellular transportation of lipids and proteins. Dysregulation of this process can give rise to various pathological manifestations, including cancer. Exploiting Golgi defects, cancer cells capitalise on aberrant membrane trafficking to facilitate signal transduction, proliferation, invasion, immune modulation, angiogenesis, and metastasis. Despite the identification of several molecular signalling pathways associated with Golgi abnormalities, there remains a lack of approved drugs specifically targeting cancer cells through the manipulation of the Golgi apparatus. In the initial section of this comprehensive review, the focus is directed towards delineating the abnormal Golgi genes and proteins implicated in carcinogenesis. Subsequently, a thorough examination is conducted on the impact of these variations on Golgi function, encompassing aspects such as vesicular trafficking, glycosylation, autophagy, oxidative mechanisms, and pH alterations. Lastly, the review provides a current update on promising Golgi apparatus-targeted inhibitors undergoing preclinical and/or clinical trials, offering insights into their potential as therapeutic interventions. Significantly more effort is required to advance these potential inhibitors to benefit patients in clinical settings.

Deciphering a proteomic signature for the early detection of breast cancer from breast milk: the role of quantitative proteomics

INTRODUCTION

Breast cancer is one of the most prevalent cancers among women in the United States. Current research regarding breast milk has been focused on the composition and its role in infant growth and development. There is little information about the proteins, immune cells, and epithelial cells present in breast milk which can be indicative of the emergence of BC cells and tumors.

AREAS COVERED

We summarize all breast milk studies previously done in our group using proteomics. These studies include 1D-PAGE and 2D-PAGE analysis of breast milk samples, which include within woman and across woman comparisons to identify dysregulated proteins in breast milk and the roles of these proteins in both the development of BC and its diagnosis. Our projected outlook for the use of milk for cancer detection is also discussed.

EXPERT OPINION

Analyzing the samples by multiple methods allows one to interrogate a set of samples with various biochemical methods that complement each other, thus providing a more comprehensive proteome. Complementing methods like 1D-PAGE, 2D-PAGE, in-solution digestion and proteomics analysis with PTM-omics, peptidomics, degradomics, or interactomics will provide a better understanding of the dysregulated proteins, but also the modifications or interactions between these proteins.

XGDAG: explainable gene-disease associations via graph neural networks

MOTIVATION

Disease gene prioritization consists in identifying genes that are likely to be involved in the mechanisms of a given disease, providing a ranking of such genes. Recently, the research community has used computational methods to uncover unknown gene-disease associations; these methods range from combinatorial to machine learning-based approaches. In particular, during the last years, approaches based on deep learning have provided superior results compared to more traditional ones. Yet, the problem with these is their inherent black-box structure, which prevents interpretability.

RESULTS

We propose a new methodology for disease gene discovery, which leverages graph-structured data using graph neural networks (GNNs) along with an explainability phase for determining the ranking of candidate genes and understanding the model's output. Our approach is based on a positive-unlabeled learning strategy, which outperforms existing gene discovery methods by exploiting GNNs in a non-black-box fashion. Our methodology is effective even in scenarios where a large number of associated genes need to be retrieved, in which gene prioritization methods often tend to lose their reliability.

AVAILABILITY AND IMPLEMENTATION

The source code of XGDAG is available on GitHub at: https://github.com/GiDeCarlo/XGDAG. The data underlying this article are available at: https://www.disgenet.org/, https://thebiogrid.org/, https://doi.org/10.1371/journal.pcbi.1004120.s003, and https://doi.org/10.1371/journal.pcbi.1004120.s004.

Spatial Proteomics for the Molecular Characterization of Breast Cancer

Breast cancer (BC) is a major global health issue, affecting a significant proportion of the female population and contributing to high rates of mortality. One of the primary challenges in the treatment of BC is the disease's heterogeneity, which can lead to ineffective therapies and poor patient outcomes. Spatial proteomics, which involves the study of protein localization within cells, offers a promising approach for understanding the biological processes that contribute to cellular heterogeneity within BC tissue. To fully leverage the potential of spatial proteomics, it is critical to identify early diagnostic biomarkers and therapeutic targets, and to understand protein expression levels and modifications. The subcellular localization of proteins is a key factor in their physiological function, making the study of subcellular localization a major challenge in cell biology. Achieving high resolution at the cellular and subcellular level is essential for obtaining an accurate spatial distribution of proteins, which in turn can enable the application of proteomics in clinical research. In this review, we present a comparison of current methods of spatial proteomics in BC, including untargeted and targeted strategies. Untargeted strategies enable the detection and analysis of proteins and peptides without a predetermined molecular focus, whereas targeted strategies allow the investigation of a predefined set of proteins or peptides of interest, overcoming the limitations associated with the stochastic nature of untargeted proteomics. By directly comparing these methods, we aim to provide insights into their strengths and limitations and their potential applications in BC research.

DeepGpgs: a novel deep learning framework for predicting arginine methylation sites combined with Gaussian prior and gated self-attention mechanism

Protein arginine methylation is an important posttranslational modification (PTM) associated with protein functional diversity and pathological conditions including cancer. Identification of methylation binding sites facilitates a better understanding of the molecular function of proteins. Recent developments in the field of deep neural networks have led to a proliferation of deep learning-based methylation identification studies because of their fast and accurate prediction. In this paper, we propose DeepGpgs, an advanced deep learning model incorporating Gaussian prior and gated attention mechanism. We introduce a residual network channel to extract the evolutionary information of proteins. Then we combine the adaptive embedding with bidirectional long short-term memory networks to form a context-shared encoder layer. A gated multi-head attention mechanism is followed to obtain the global information about the sequence. A Gaussian prior is injected into the sequence to assist in predicting PTMs. We also propose a weighted joint loss function to alleviate the false negative problem. We empirically show that DeepGpgs improves Matthews correlation coefficient by 6.3% on the arginine methylation independent test set compared with the existing state-of-the-art methylation site prediction methods. Furthermore, DeepGpgs has good robustness in phosphorylation site prediction of SARS-CoV-2, which indicates that DeepGpgs has good transferability and the potential to be extended to other modification sites prediction. The open-source code and data of the DeepGpgs can be obtained from https://github.com/saizhou1/DeepGpgs.

Targeting α-synuclein post-translational modifications in Parkinson's disease

Parkinson's disease (PD) is a neurodegenerative disease characterized by the progressive loss of dopaminergic neurons in the nigrostriatal pathway. Although the exact mechanisms underlying PD are still not completely understood, it is well accepted that α-synuclein plays key pathophysiological roles as the main constituent of the cytoplasmic inclusions known as Lewy bodies. Several post-translational modifications (PTMs), such as the best-known phosphorylation, target α-synuclein and are thus implicated in its physiological and pathological functions. In this review, we present (1) an overview of the pathophysiological roles of α-synuclein, (2) a descriptive analysis of α-synuclein PTMs, including phosphorylation, ubiquitination, SUMOylation, acetylation, glycation, truncation, and O-GlcNAcylation, as well as (3) a brief summary on α-synuclein PTMs as potential biomarkers for PD. A better understanding of α-synuclein PTMs is of paramount importance for elucidating the mechanisms underlying PD and can thus be expected to improve early detection and monitoring disease progression, as well as identify promising new therapeutic targets.

Lysine Malonylation and Its Links to Metabolism and Diseases

Malonylation is a recently identified post-translational modification with malonyl-coenzyme A as the donor. It conserved both in prokaryotes and eukaryotes. Recent advances in the identification and quantification of lysine malonylation by bioinformatic analysis have improved our understanding of its role in the regulation of protein activity, interaction, and localization and have elucidated its involvement in many biological processes. Malonylation has been linked to diverse physiological processes, including metabolic disorders, inflammation, and immune regulation. This review discusses malonylation in theory, describes the underlying mechanism, and summarizes the recent progress in malonylation research. The latest findings point to novel functions of malonylation and highlight the mechanisms by which malonylation regulates a variety of cellular processes. Our review also marks the association between lysine malonylation, the enzymes involved, and various diseases, and discusses promising diagnostic and therapeutic biomolecular targets for future clinical applications.

Proteomics-Based Identification of Dysregulated Proteins in Breast Cancer

Immunohistochemistry (IHC) is still widely used as a morphology-based assay for in situ analysis of target proteins as specific tumor antigens. However, as a very heterogeneous collection of neoplastic diseases, breast cancer (BC) requires an accurate identification and characterization of larger panels of candidate biomarkers, beyond ER, PR, and HER2 proteins, for diagnosis and personalized treatment, without the limited availability of antibodies that are required to identify specific proteins. Top-down, middle-down, and bottom-up mass spectrometry (MS)-based proteomics approaches complement traditional histopathological tissue analysis to examine expression, modification, and interaction of hundreds to thousands of proteins simultaneously. In this review, we discuss the proteomics-based identification of dysregulated proteins in BC that are essential for the following issues: discovery and validation of new biomarkers by analysis of solid and liquid/non-invasive biopsies, cell lines, organoids and xenograft models; identification of panels of biomarkers for early detection and accurate discrimination between cancer, benign and normal tissues; identification of subtype-specific and stage-specific protein expression profiles in BC grading and measurement of disease progression; characterization of new subtypes of BC; characterization and quantitation of post-translational modifications (PTMs) and aberrant protein-protein interactions (PPI) involved in tumor development; characterization of the global remodeling of BC tissue homeostasis, diagnosis and prognostic information; and deciphering of molecular functions, biological processes and mechanisms through which the dysregulated proteins cause tumor initiation, invasion, and treatment resistance.

Glycyrrhizic Acid Inhibits Core Fucosylation Modification Modulated EMT and Attenuates Bleomycin-Induced Pulmonary Fibrosis

Idiopathic pulmonary fibrosis (IPF) is a fatal and incurable chronic interstitial lung disease with an unknown etiology. Recent evidence suggests that epithelial-mesenchymal transition (EMT) is one of the possible factors in the pathogenesis of pulmonary fibrosis. Glycyrrhizic acid (GA) is a natural active ingredient extracted from the root of the traditional Chinese herb licorice, which has been shown in previous studies to have the effect of alleviating lung injury. In this study, our objective was to investigate whether GA could ameliorate pulmonary fibrosis by altering EMT, as well as the therapeutic potential of changing core fucosylation (CF) to target EMT-related pathways. First, we verified that GA partially reverses EMT in a rat model of bleomycin-induced lung interstitial fibrosis, alleviating pulmonary fibrosis, and implying that GA has antifibrotic potential. Next, we discovered that GA attenuated lung interstitial fibrosis by reducing CF modifications to some extent. Interestingly, we found that GA therapy reduced the expression of phosphorylated Smad2/3 (p-Smad2/3) and β-catenin in the EMT pathway and that GA inhibited the modification of TGF-βR and WNT receptor proteins by CF, suggesting that GA may interfere with the EMT process by modulating TGF-βR, WNT core fucosylation modifications to attenuate pulmonary fibrosis. In conclusion, these findings indicate that GA could be a potential therapeutic agent for IPF, and further support the idea that targeting CF alterations could be a novel technique for the treatment of diseases involving EMT.

Ferrochelatase: Mapping the Intersection of Iron and Porphyrin Metabolism in the Mitochondria

Porphyrin and iron are ubiquitous and essential for sustaining life in virtually all living organisms. Unlike iron, which exists in many forms, porphyrin macrocycles are mostly functional as metal complexes. The iron-containing porphyrin, heme, serves as a prosthetic group in a wide array of metabolic pathways; including respiratory cytochromes, hemoglobin, cytochrome P450s, catalases, and other hemoproteins. Despite playing crucial roles in many biological processes, heme, iron, and porphyrin intermediates are potentially cytotoxic. Thus, the intersection of porphyrin and iron metabolism at heme synthesis, and intracellular trafficking of heme and its porphyrin precursors are tightly regulated processes. In this review, we discuss recent advances in understanding the physiological dynamics of eukaryotic ferrochelatase, a mitochondrially localized metalloenzyme. Ferrochelatase catalyzes the terminal step of heme biosynthesis, the insertion of ferrous iron into protoporphyrin IX to produce heme. In most eukaryotes, except plants, ferrochelatase is localized to the mitochondrial matrix, where substrates are delivered and heme is synthesized for trafficking to multiple cellular locales. Herein, we delve into the structural and functional features of ferrochelatase, as well as its metabolic regulation in the mitochondria. We discuss the regulation of ferrochelatase via post-translational modifications, transportation of substrates and product across the mitochondrial membrane, protein-protein interactions, inhibition by small-molecule inhibitors, and ferrochelatase in protozoal parasites. Overall, this review presents insight on mitochondrial heme homeostasis from the perspective of ferrochelatase.

Dance of The Golgi: Understanding Golgi Dynamics in Cancer Metastasis

The Golgi apparatus is at the center of protein processing and trafficking in normal cells. Under pathological conditions, such as in cancer, aberrant Golgi dynamics alter the tumor microenvironment and the immune landscape, which enhances the invasive and metastatic potential of cancer cells. Among these changes in the Golgi in cancer include altered Golgi orientation and morphology that contribute to atypical Golgi function in protein trafficking, post-translational modification, and exocytosis. Golgi-associated gene mutations are ubiquitous across most cancers and are responsible for modifying Golgi function to become pro-metastatic. The pharmacological targeting of the Golgi or its associated genes has been difficult in the clinic; thus, studying the Golgi and its role in cancer is critical to developing novel therapeutic agents that limit cancer progression and metastasis. In this review, we aim to discuss how disrupted Golgi function in cancer cells promotes invasion and metastasis.

Improved Prediction Model of Protein Lysine Crotonylation Sites Using Bidirectional Recurrent Neural Networks

Histone lysine crotonylation (Kcr) is a post-translational modification of histone proteins that is involved in the regulation of gene transcription, acute and chronic kidney injury, spermatogenesis, depression, cancer, and so forth. The identification of Kcr sites in proteins is important for characterizing and regulating primary biological mechanisms. The use of computational approaches such as machine learning and deep learning algorithms have emerged in recent years as the traditional wet-lab experiments are time-consuming and costly. We propose as part of this study a deep learning model based on a recurrent neural network (RNN) termed as Sohoko-Kcr for the prediction of Kcr sites. Through the embedded encoding of the peptide sequences, we investigate the efficiency of RNN-based models such as long short-term memory (LSTM), bidirectional LSTM (BiLSTM), and bidirectional gated recurrent unit (BiGRU) networks using cross-validation and independent tests. We also established the comparison between Sohoko-Kcr and other published tools to verify the efficiency of our model based on 3-fold, 5-fold, and 10-fold cross-validations using independent set tests. The results then show that the BiGRU model has consistently displayed outstanding performance and computational efficiency. Based on the proposed model, a webserver called Sohoko-Kcr was deployed for free use and is accessible at https://sohoko-research-9uu23.ondigitalocean.app.

Proteomic and molecular dynamic investigations of PTM-induced structural fluctuations in breast and ovarian cancer

Post-translational processing leads to conformational changes in protein structure that modulate molecular functions and change the signature of metabolic transformations and immune responses. Some post-translational modifications (PTMs), such as phosphorylation and acetylation, are strongly related to oncogenic processes and malignancy. This study investigated a PTM pattern in patients with gender-specific ovarian or breast cancer. Proteomic profiling and analysis of cancer-specific PTM patterns were performed using high-resolution UPLC-MS/MS. Structural analysis, topology, and stability of PTMs associated with sex-specific cancers were analyzed using molecular dynamics modeling. We identified highly specific PTMs, of which 12 modified peptides from eight distinct proteins derived from patients with ovarian cancer and 6 peptides of three proteins favored patients from the group with breast cancer. We found that all defined PTMs were localized in the compact and stable structural motifs exposed outside the solvent environment. PTMs increase the solvent-accessible surface area of the modified moiety and its active environment. The observed conformational fluctuations are still inadequate to activate the structural degradation and enhance protein elimination/clearance; however, it is sufficient for the significant modulation of protein activity.

Proteomics and its applications in breast cancer

Breast cancer is an individually unique, multi-faceted and chameleonic disease, an eternal challenge for the new era of high-integrated precision diagnostic and personalized oncomedicine. Besides traditional single-omics fields (such as genomics, epigenomics, transcriptomics and metabolomics) and multi-omics contributions (proteogenomics, proteotranscriptomics or reproductomics), several new "-omics" approaches and exciting proteomics subfields are contributing to basic and advanced understanding of these "multiple diseases termed breast cancer": phenomics/cellomics, connectomics and interactomics, secretomics, matrisomics, exosomics, angiomics, chaperomics and epichaperomics, phosphoproteomics, ubiquitinomics, metalloproteomics, terminomics, degradomics and metadegradomics, adhesomics, stressomics, microbiomics, immunomics, salivaomics, materiomics and other biomics. Throughout the extremely complex neoplastic process, a Breast Cancer Cell Continuum Concept (BCCCC) has been modeled in this review as a spatio-temporal and holistic approach, as long as the breast cancer represents a complex cascade comprising successively integrated populations of heterogeneous tumor and cancer-associated cells, that reflect the carcinoma's progression from a "driving mutation" and formation of the breast primary tumor, toward the distant secondary tumors in different tissues and organs, via circulating tumor cell populations. This BCCCC is widely sustained by a Breast Cancer Proteomic Continuum Concept (BCPCC), where each phenotype of neoplastic and tumor-associated cells is characterized by a changing and adaptive proteomic profile detected in solid and liquid minimal invasive biopsies by complex proteomics approaches. Such a profile is created, beginning with the proteomic landscape of different neoplastic cell populations and cancer-associated cells, followed by subsequent analysis of protein biomarkers involved in epithelial-mesenchymal transition and intravasation, circulating tumor cell proteomics, and, finally, by protein biomarkers that highlight the extravasation and distant metastatic invasion. Proteomics technologies are producing important data in breast cancer diagnostic, prognostic, and predictive biomarkers discovery and validation, are detecting genetic aberrations at the proteome level, describing functional and regulatory pathways and emphasizing specific protein and peptide profiles in human tissues, biological fluids, cell lines and animal models. Also, proteomics can identify different breast cancer subtypes and specific protein and proteoform expression, can assess the efficacy of cancer therapies at cellular and tissular level and can even identify new therapeutic target proteins in clinical studies.

The Burden of Post-Translational Modification (PTM)-Disrupting Mutations in the Tumor Matrisome

BACKGROUND

To evaluate the occurrence of mutations affecting post-translational modification (PTM) sites in matrisome genes across different tumor types, in light of their genomic and functional contexts and in comparison with the rest of the genome.

METHODS

This study spans 9075 tumor samples and 32 tumor types from The Cancer Genome Atlas (TCGA) Pan-Cancer cohort and identifies 151,088 non-silent mutations in the coding regions of the matrisome, of which 1811 affecting known sites of hydroxylation, phosphorylation, N- and O-glycosylation, acetylation, ubiquitylation, sumoylation and methylation PTM.

RESULTS

PTM-disruptive mutations (PTMmut) in the matrisome are less frequent than in the rest of the genome, seem independent of cell-of-origin patterns but show dependence on the nature of the matrisome protein affected and the background PTM types it generally harbors. Also, matrisome PTMmut are often found among structural and functional protein regions and in proteins involved in homo- and heterotypic interactions, suggesting potential disruption of matrisome functions.

CONCLUSIONS

Though quantitatively minoritarian in the spectrum of matrisome mutations, PTMmut show distinctive features and damaging potential which might concur to deregulated structural, functional, and signaling networks in the tumor microenvironment.

Autoantibodies in Early Detection of Breast Cancer

In spite of the progress made in treatment and early diagnosis, breast cancer remains a major public health issue worldwide. Although modern image-based screening modalities have significantly improved early diagnosis, around 15% to 20% of breast cancers still go undetected. In underdeveloped countries, lack of resources and cost concerns prevent implementing mammography for routine screening. Noninvasive, low-cost, blood-based markers for early breast cancer diagnosis would be an invaluable alternative that would complement mammography screening. Tumor-specific autoantibodies are excellent biosensors that could be exploited to monitor disease-specific changes years before disease onset. Although clinically informative autoantibody markers for early breast cancer screening have yet to emerge, progress has been made in the development of tools to discover and validate promising autoantibody signatures. This review focuses on the current progress toward the development of autoantibody-based early screening markers for breast cancer.See all articles in this CEBP Focus section, "NCI Early Detection Research Network: Making Cancer Detection Possible."

Use of Lectin-based Affinity Techniques in Breast Cancer Glycoproteomics: A Review

Changes in glycoprotein content, altered glycosylations, and aberrant glycan structures are increasingly recognized as cancer hallmarks. Because breast cancer is one of the most common causes of cancer deaths in the world, it is highly urgent to find other reliable biomarkers for its initial diagnosis and to learn as much as possible about this disease. In this Review, the applications of lectins to a screening of potential breast cancer biomarkers published during recent years are overviewed. These data provide a deeper insight into the use of modern strategies, technologies, and scientific knowledge in glycoproteomic breast cancer research. Particular attention is concentrated on the use of lectin-based affinity techniques, applied independently or most frequently in combination with mass spectrometry, as an effective tool for the targeting, separation, and reliable identification of glycoprotein molecules. Individual procedures and lectins used in published glycoproteomic studies of breast-cancer-related glycoproteins are discussed. The summarized approaches have the potential for use in diagnostic and predictive applications. Finally, the use of lectins is briefly discussed from the view of their future applications in the analysis of glycoproteins in cancer.

The implication of the SUMOylation pathway in breast cancer pathogenesis and treatment

Breast cancer is the most commonly diagnosed malignancy in woman worldwide, and is the second most common cause of death in developed countries. The transformation of a normal cell into a malignant derivate requires the acquisition of diverse genomic and proteomic changes, including enzymatic post-translational modifications (PTMs) on key proteins encompassing critical cell signaling events. PTMs occur on proteins after translation, and regulate several aspects of proteins activity, including their localization, activation and turnover. Deregulation of PTMs can potentially lead to tumorigenesis, and several de-regulated PTM pathways contribute to abnormal cell proliferation during breast tumorigenesis. SUMOylation is a PTM that plays a pivotal role in numerous aspects of cell physiology, including cell cycle regulation, protein trafficking and turnover, and DNA damage repair. Consistently with this, the deregulation of the SUMO pathway is observed in different human pathologies, including breast cancer. In this review we will describe the role of SUMOylation in breast tumorigenesis and its implication for breast cancer therapy.

Decoding the PTM-switchboard of Notch

The developmentally indispensable Notch pathway exhibits a high grade of pleiotropism in its biological output. Emerging evidence supports the notion of post-translational modifications (PTMs) as a modus operandi controlling dynamic fine-tuning of Notch activity. Although, the intricacy of Notch post-translational regulation, as well as how these modifications lead to multiples of divergent Notch phenotypes is still largely unknown, numerous studies show a correlation between the site of modification and the output. These include glycosylation of the extracellular domain of Notch modulating ligand binding, and phosphorylation of the PEST domain controlling half-life of the intracellular domain of Notch. Furthermore, several reports show that multiple PTMs can act in concert, or compete for the same sites to drive opposite outputs. However, further investigation of the complex PTM crosstalk is required for a complete understanding of the PTM-mediated Notch switchboard. In this review, we aim to provide a consistent and up-to-date summary of the currently known PTMs acting on the Notch signaling pathway, their functions in different contexts, as well as explore their implications in physiology and disease. Furthermore, we give an overview of the present state of PTM research methodology, and allude to a future with PTM-targeted Notch therapeutics.

Protein Post-Translational Modification Crosstalk in Acute Myeloid Leukemia Calls for Action

BACKGROUND

Post-translational modification (PTM) crosstalk is a young research field. However, there is now evidence of the extraordinary characterization of the different proteoforms and their interactions in a biological environment that PTM crosstalk studies can describe. Besides gene expression and phosphorylation profiling of acute myeloid leukemia (AML) samples, the functional combination of several PTMs that might contribute to a better understanding of the complexity of the AML proteome remains to be discovered.

OBJECTIVE

By reviewing current workflows for the simultaneous enrichment of several PTMs and bioinformatics tools to analyze mass spectrometry (MS)-based data, our major objective is to introduce the PTM crosstalk field to the AML research community.

RESULTS

After an introduction to PTMs and PTM crosstalk, this review introduces several protocols for the simultaneous enrichment of PTMs. Two of them allow a simultaneous enrichment of at least three PTMs when using 0.5-2 mg of cell lysate. We have reviewed many of the bioinformatics tools used for PTM crosstalk discovery as its complex data analysis, mainly generated from MS, becomes challenging for most AML researchers. We have presented several non-AML PTM crosstalk studies throughout the review in order to show how important the characterization of PTM crosstalk becomes for the selection of disease biomarkers and therapeutic targets.

CONCLUSION

Herein, we have reviewed the advances and pitfalls of the emerging PTM crosstalk field and its potential contribution to unravel the heterogeneity of AML. The complexity of sample preparation and bioinformatics workflows demands a good interaction between experts of several areas.

PTMD: A Database of Human Disease-associated Post-translational Modifications

Various posttranslational modifications (PTMs) participate in nearly all aspects of biological processes by regulating protein functions, and aberrant states of PTMs are frequently implicated in human diseases. Therefore, an integral resource of PTM–disease associations (PDAs) would be a great help for both academic research and clinical use. In this work, we reported PTMD, a well-curated database containing PTMs that are associated with human diseases. We manually collected 1950 known PDAs in 749 proteins for 23 types of PTMs and 275 types of diseases from the literature. Database analyses show that phosphorylation has the largest number of disease associations, whereas neurologic diseases have the largest number of PTM associations. We classified all known PDAs into six classes according to the PTM status in diseases and demonstrated that the upregulation and presence of PTM events account for a predominant proportion of disease-associated PTM events. By reconstructing a disease–gene network, we observed that breast cancers have the largest number of associated PTMs and AKT1 has the largest number of PTMs connected to diseases. Finally, the PTMD database was developed with detailed annotations and can be a useful resource for further analyzing the relations between PTMs and human diseases. PTMD is freely accessible at http://ptmd.biocuckoo.org.

Pan-Cancer Analysis Reveals the Functional Importance of Protein Lysine Modification in Cancer Development

Large-scale tumor genome sequencing projects have revealed a complex landscape of genomic mutations in multiple cancer types. A major goal of these projects is to characterize somatic mutations and discover cancer drivers, thereby providing important clues to uncover diagnostic or therapeutic targets for clinical treatment. However, distinguishing only a few somatic mutations from the majority of passenger mutations is still a major challenge facing the biological community. Fortunately, combining other functional features with mutations to predict cancer driver genes is an effective approach to solve the above problem. Protein lysine modifications are an important functional feature that regulates the development of cancer. Therefore, in this work, we have systematically analyzed somatic mutations on seven protein lysine modifications and identified several important drivers that are responsible for tumorigenesis. From published literature, we first collected more than 100,000 lysine modification sites for analysis. Another 1 million non-synonymous single nucleotide variants (SNVs) were then downloaded from TCGA and mapped to our collected lysine modification sites. To identify driver proteins that significantly altered lysine modifications, we further developed a hierarchical Bayesian model and applied the Markov Chain Monte Carlo (MCMC) method for testing. Strikingly, the coding sequences of 473 proteins were found to carry a higher mutation rate in lysine modification sites compared to other background regions. Hypergeometric tests also revealed that these gene products were enriched in known cancer drivers. Functional analysis suggested that mutations within the lysine modification regions possessed higher evolutionary conservation and deleteriousness. Furthermore, pathway enrichment showed that mutations on lysine modification sites mainly affected cancer related processes, such as cell cycle and RNA transport. Moreover, clinical studies also suggested that the driver proteins were significantly associated with patient survival, implying an opportunity to use lysine modifications as molecular markers in cancer diagnosis or treatment. By searching within protein-protein interaction networks using a random walk with restart (RWR) algorithm, we further identified a series of potential treatment agents and therapeutic targets for cancer related to lysine modifications. Collectively, this study reveals the functional importance of lysine modifications in cancer development and may benefit the discovery of novel mechanisms for cancer treatment.

Label-Free and Real-Time Detection of Protein Ubiquitination with a Biological Nanopore

The covalent addition of ubiquitin to target proteins is a key post-translational modification that is linked to a myriad of biological processes. Here, we report a fast, single-molecule, and label-free method to probe the ubiquitination of proteins employing an engineered Cytolysin A (ClyA) nanopore. We show that ionic currents can be used to recognize mono- and polyubiquitinated forms of native proteins under physiological conditions. Using defined conjugates, we also show that isomeric monoubiquitinated proteins can be discriminated. The nanopore approach allows following the ubiquitination reaction in real time, which will accelerate the understanding of fundamental mechanisms linked to protein ubiquitination.

Expression Data Analysis for the Identification of Potential Biomarker of Pregnancy Associated Breast Cancer

Breast cancer affects every 1 of 3000 pregnant women or in the first post-partum year is referred as Pregnancy Associated Breast Cancer (PABC) in mid 30s. Even-though rare disease, classified under hormone receptor negative status which metastasis quickly to other parts by extra cellular matrix degradation. Hence it is important to find an optimal treatment option for a PABC patient. Also additional care should be taken to choose the drug; in order to avoid fetal malformation and post-partum stage side-effects. The adaptation of target based therapy in the clinical practice may help to substitute the mastectomy treatment. Recent studies suggested that certain altered Post Translational Modifications (PTMs) may be an indicative of breast cancer progression; an attempt is made to consider the over represented PTM as a parameter for gene selection. The public dataset of PABC from GEO were examined to select Differentially Expressed Genes (DEG). The corresponding PTMs for DEG were collected and association between them was found using data mining technique. Usually clustering algorithm has been applied for the study of gene expression with drawback of clustering of gene products based on specified features. But association rule mining method overcome this shortcoming and determines the useful and in depth relationships. From the association, genes were selected to study the interactions and pathways. These studies emphasis that the genes KLF12, FEN1 MUC1 and SP110, can be chosen as target, which control cancer development, without any harm to pregnancy as well as fetal developmental process.

Inhibiting post-translational core fucosylation prevents vascular calcification in the model of uremia

Vascular calcification (VC) is an independent risk factor for cardiovascular disease and mortality in uremia. Post-translational core fucosylation is implicated in a number of pathological processes. First, we investigated the role of core fucosylation and key TGF-β1 pathway receptors in calcified arteries in vivo. To determine whether blocking core fucosylation effectively inhibited VC and TGF-β/Smad signaling pathway, we established an in vitro model of phosphate-induced calcification in rat vascular smooth muscle cells (VSMCs) to assess the role of core fucosylation in VC. Core fucose could be detected at markedly higher levels in calcified VSMCs than control cells. Fut8 (α-1,6 fucosyltransferase), the only enzyme responsible for core fucosylation in humans, was significantly upregulated by high phosphate. Exposed to high phosphate media and blocking core fucosylation in VSMCs by knocking down Fut8 using a siRNA markedly reduced calcium and phosphorus deposition and Cbfα1 expression (osteoblast-specific transcription factor), and increased α-Sma expression (smooth muscle cell marker). Fut8 siRNA significantly inhibited TGF-β/Smad2/3 signaling activation in VSMCs cultured in high phosphate media. In conclusion, this study provides evidence to suggest core fucosylation plays a major role in the process of VC and appropriate blockade of core fucosylation may represent a potential therapeutic strategy for treating VC in end-stage renal disease.

Oxidatively modified proteins as plasma biomarkers in breast cancer

BACKGROUND

Post-translational protein modifications (PTMs) are increased in breast tumors.

OBJECTIVE

We explored whether PTMs on proteins secreted by the breast could be detected in plasma and potentially used for the early detection of breast cancer.

METHODS

We used a custom ELISA microarray platform to measure 4-hydroxynonenal (HNE), glutathione (GSH), nitrotyrosine and halotyrosine adducts in 27 secreted proteins, for a total of 108 candidate biomarkers. Two independent sets of human plasma samples were measured, for a total of 160 samples. The results were analyzed for consistent cancer-associated changes across the two sample sets. Plasma samples for both cases and benign controls were collected at the time of tissue diagnosis after referral from a positive screen (such as mammography). The results from both studies were evaluated using ANOVA and t-tests or receiver operator curves (ROC).

RESULTS

Levels of GSH-modified ceruloplasmin and HNE-modified PDGF were significantly altered in plasma samples from cancer patients relative to benign controls. Healthy controls, which were only included in the first set of samples, were similar to the benign controls for both of these markers. A combination of three glutathionylated proteins produced the best area under the ROC curve, with a value of 76%.

CONCLUSIONS

Specific PTMs in individual proteins may be useful for distinguishing between women with breast cancer and those with benign breast disease. These oxidative changes in plasma proteins may reflect redox changes in breast cancer. Additional studies on oxidative modifications in individual proteins are warranted.

Synergistic effects of ethyl acetate fraction of Ficus septica Burm. f. and doxorubicin chemotherapy on T47D human breast cancer cell line

OBJECTIVE

Previously, ethanolic extract of Ficus septica Burm. f. (Moraceae) leaves and its ethyl acetate soluble fraction (EASF) exhibited potent cytotoxic effects on T47D breast cancer cells. In the present study, we further investigated the effects of EASF of ethanolic extract of F. septica leaves in combination with doxorubicin on T47D breast cancer cell line in cytotoxicity, cell cycle arrest and apoptosis induction.

METHODS

The cytotoxic effect analysis on T47D cells was carried out using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay. Analysis of cell cycle distribution was performed using a flowcytometer and the data were analyzed using ModFit LT 3.0 program. Apoptosis assay was carried out by double staining method using ethidium bromide-acridin orange. The expression of cleaved-poly ADP-ribose polymerase in the T47D cell line was identified using immunohistochemical techniques.

RESULTS

The combination of doxorubicin (2 to 8 nmol/L) with EASF (0.875 to 7 μg/mL) more potently inhibited cell growth than the single treatment of doxorubicin in T47D cells. In addition, the combination of doxorubicin and EASF could increase the incidence of cells undergoing apoptosis. EASF was found to improve cytotoxic effect of doxorubicin by changing the inhibition of cell cycle G(2)/M to G(1) phase. The combination also exhibited a more intensive stimulatory effect on cleaved-PARP expression in T47D cells than the single treatment.

CONCLUSION

It is concluded that EASF may enhance doxorubicin activities in T47D cells by inducing apoptosis and cell cycle arrest.

Further characterization of the target of a potential aptamer biomarker for pancreatic cancer: cyclophilin B and its posttranslational modifications

Posttranslational modifications on proteins can serve as useful biomarkers for disease. However, their discovery and detection in biological fluids is challenging. Aptamers are oligonucleotide ligands that demonstrate high affinity toward their target proteins and can discriminate closely related proteins with superb specificity. Previously, we generated a cyclophilin B aptamer (M9-5) that could discriminate sera from pancreatic cancer patients and healthy volunteers with high specificity and sensitivity. In our present work we further characterize the aptamer and the target protein, cyclophilin B, and demonstrate that the aptamer could discriminate between cyclophilin B expressed in human cells versus bacteria. Using mass-spectrometric analysis, we discovered post-translational modifications on cyclophilin B that might be responsible for the M9-5 selectivity. The ability to distinguish between forms of the same protein with differing post-translational modifications is an important advantage of aptamers as tools for identification and detection of biomarkers.

Binding of circulating autoantibodies in breast cancer to native and peroxynitrite-modified RNA

Peroxynitrite (ONOO(-)) is a powerful oxidant and nitrosative agent and has in vivo existence. The half life of ONOO(-) at physiological pH is less than 1 s. It can react with nucleic acids, proteins, lipoproteins, saccharides, cardiolipin, etc., and can modify their native structures. Action of ONOO(-), synthesized in the authors' laboratory by a rapid quenched flow process, on structural changes of commercially available RNA was studied by ultraviolet (UV), fluorescence, and agarose gel electrophoresis. Compared to native RNA, the ONOO(-)-modified RNA showed hyperchromicity at 260 nm. Furthermore, the ethidium bromide (EtBr) assisted emission intensities of ONOO(-)-modified RNA samples were found to be lower than the emission intensity of native RNA-EtBr complex. Agarose gel electrophoresis of ONOO(-)-modified RNA showed a gradual decrease in band intensities compared to native RNA, an observation clearly due to the poor intercalation of EtBr with ONOO(-)-modified RNA. Native and ONOO(-)-modified RNA samples were used as an antigen to detect autoantibodies in sera of patients with clinically defined breast cancer. Both direct binding and inhibition enzyme-linked immunosorbent assay (ELISA) confirmed the prevalence of native and 0.8 mmol/L ONOO(-)-modified RNA specific autoantibodies in breast cancer patients. Moreover, the progressive retardation in the mobility of immune complexes formed with native or 0.8 mmol/L ONOO(-)-modified RNA and affinity purified immunoglobulin G (IgG) from sera of breast cancer patients supports the findings of the direct binding and inhibition ELISAs. The peroxynitrite treatment to RNA at a higher concentration appears to have damaged or destroyed the typical epitopes on RNA and thus there was a sharp decrease in autoantibodies binding to 1.4 mmol/L ONOO(-)-modified RNA. It may be interpreted that cellular nitrosative stress can modify and confer immunogenicity on RNA molecules. Higher concentrations of nitrogen reactive species can be detrimental to RNA. However, the emergence of native as well as 0.8 mmol/L ONOO(-)-modified RNA as a novel antigen/substrate for autoantibodies in breast cancer patients indicates that, in future, these molecules might find a place on the panel of antigens for early diagnosis of breast cancer.

Preclinical evaluation of the novel monoclonal antibody H6-11 for prostate cancer imaging

The biological properties of the novel monoclonal antibody (mAb) H6-11 and its potential utility for oncological imaging studies were evaluated using in vitro and in vivo assays. Immunoreactivity of H6-11 to the human prostate cancer PC-3 cell line and solid tumor xenografts was initially demonstrated using immunofluorescence staining; the specificity of H6-11 for prostate cancer was further evaluated using a commercial array of human prostate cancer and normal tissue samples (n=49) in which H6-11 detected 95% of prostate adenocarcinomas. The Kd value of 61.7±30 nM was determined using 125I-labeled H6-11. Glycosylation analysis suggested the antigenic epitope of the glycan is an O-linked β-N-acetylglucoside (O-GlcNAc) group. Imaging studies of PC-3 tumor-bearing mice were performed using both optical imaging with NIR fluorescent dye-labeled H6-11 and microPET imaging with 89Zr-labeled H6-11. These in vivo studies revealed that the labeled probes accumulated in PC-3 tumors 48-72 h postinjection, although significant retention in liver was also observed. By 120 h postinjection, the tumors were still evident, although the liver showed significant clearance. These studies suggest that the mAb H6-11 may be a useful tool to detect prostate cancer in vitro and in vivo.

Serum markers in small cell lung cancer: opportunities for improvement

Lung cancer is one of the leading causes of death from malignancy worldwide. In particular small cell lung cancers, which comprise about 15-20% of all lung cancers, are extremely aggressive and cure rates are extremely low. Therefore, new treatment modalities are needed and detection at an early stage of disease, as well as adequate monitoring of treatment response is essential in order to improve outcome. In this respect, the use of non-invasive tools for screening and monitoring has gained increasing interest and the clinical applicability of reliable, tumor-related substances that can be detected as tumor markers in easily accessible body fluids is subject of intense investigation. Some of these indicators, such as high LDH levels in serum as a reflection of the disease, have been in use for a long time as a general tumor marker. To allow for improved monitoring of the efficacy of new therapeutic modalities and for accurate subtyping, there is a strong need for specific and sensitive markers that are more directly related to the biology and behavior of small cell lung cancer. In this review the current status of these potential markers, like CEA, NSE, ProGRP, CK-BB, SCC, CgA, NCAM and several cytokeratins will be critically analyzed with respect to their performance in blood based assays. Based on known cleavage sites for cytoplasmic and extracellular proteases, a prediction of stable fragments can be obtained and used for optimal test design. Furthermore, insight into the synthesis of specific splice variants and neo-epitopes resulting from protein modification and cleavage, offers further opportunities for improvement of tumor assays. Finally, we discuss the possibility that detection of SCLC related autoantibodies in paraneoplastic disease can be used as a very early indicator of SCLC.

Risk assessment, disease prevention and personalised treatments in breast cancer: is clinically qualified integrative approach in the horizon?

Breast cancer is a multifactorial disease. A spectrum of internal and external factors contributes to the disease promotion such as a genetic predisposition, chronic inflammatory processes, exposure to toxic compounds, abundant stress factors, a shift-worker job, etc. The cumulative effects lead to high incidence of breast cancer in populations worldwide. Breast cancer in the USA is currently registered with the highest incidence rates amongst all cancer related patient cohorts. Currently applied diagnostic approaches are frequently unable to recognise early stages in tumour development that impairs individual outcomes. Early diagnosis has been demonstrated to be highly beneficial for significantly enhanced therapy efficacy and possibly full recovery. Actual paper shows that the elaboration of an integrative diagnostic approach combining several levels of examinations creates a robust platform for the reliable risk assessment, targeted preventive measures and more effective treatments tailored to the person in the overall task of breast cancer management. The levels of examinations are proposed, and innovative technological approaches are described in the paper. The absolute necessity to create individual patient profiles and extended medical records is justified for the utilising by routine medical services. Expert recommendations are provided to promote further developments in the field.

High-throughput, multiplexed analysis of 3-nitrotyrosine in individual proteins

Reactive nitrogen species (RNS) and reactive oxygen species (ROS) are derived as a result of inflammation and oxidative stress and can result in protein modifications. As such, these protein modifications are used as biomarkers for inflammation and oxidative stress. In addition, modifications in single-tissue-associated proteins released into blood can provide insight into the tissue localization of the inflammation or oxidative stress. We have developed an enzyme-linked immunosorbent assay antibody microarray platform to analyze the levels of 3-nitrotyrosine in specific proteins in a variety of biological samples, including human plasma and sputum. Selective-capture antibodies are used to immunoprecipitate individual proteins from samples onto isolated spots on the microarray chips. Then, a monoclonal antibody for 3-nitrotyrosine is used to detect the amount of 3-nitrotyrosine on each spot. Our studies suggest that this approach can be used to detect trace amounts of 3-nitrotyrosine in human plasma and sputum. In this paper, we describe our antibody microarray protocol for detecting 3-nitrotyrosine in specific proteins.

Spatially selective photonic crystal enhanced fluorescence and application to background reduction for biomolecule detection assays

By combining photonic crystal label-free biosensor imaging with photonic crystal enhanced fluorescence, it is possible to selectively enhance the fluorescence emission from regions of the PC surface based upon the density of immobilized capture molecules. A label-free image of the capture molecules enables determination of optimal coupling conditions of the laser used for fluorescence imaging of the photonic crystal surface on a pixel-by-pixel basis, allowing maximization of fluorescence enhancement factor from regions incorporating a biomolecule capture spot and minimization of background autofluorescence from areas between capture spots. This capability significantly improves the contrast of enhanced fluorescent images, and when applied to an antibody protein microarray, provides a substantial advantage over conventional fluorescence microscopy. Using the new approach, we demonstrate detection limits as low as 0.97 pg/ml for a representative protein biomarker in buffer.

A biologically inspired measure for coexpression analysis

Two genes are said to be coexpressed if their expression levels have a similar spatial or temporal pattern. Ever since the profiling of gene microarrays has been in progress, computational modeling of coexpression has acquired a major focus. As a result, several similarity/distance measures have evolved over time to quantify coexpression similarity/dissimilarity between gene pairs. Of these, correlation coefficient has been established to be a suitable quantifier of pairwise coexpression. In general, correlation coefficient is good for symbolizing linear dependence, but not for nonlinear dependence. In spite of this drawback, it outperforms many other existing measures in modeling the dependency in biological data. In this paper, for the first time, we point out a significant weakness of the existing similarity/distance measures, including the standard correlation coefficient, in modeling pairwise coexpression of genes. A novel measure, called BioSim, which assumes values between -1 and +1 corresponding to negative and positive dependency and 0 for independency, is introduced. The computation of BioSim is based on the aggregation of stepwise relative angular deviation of the expression vectors considered. The proposed measure is analytically suitable for modeling coexpression as it accounts for the features of expression similarity, expression deviation and also the relative dependence. It is demonstrated how the proposed measure is better able to capture the degree of coexpression between a pair of genes as compared to several other existing ones. The efficacy of the measure is statistically analyzed by integrating it with several module-finding algorithms based on coexpression values and then applying it on synthetic and biological data. The annotation results of the coexpressed genes as obtained from gene ontology establish the significance of the introduced measure. By further extending the BioSim measure, it has been shown that one can effectively identify the variability in the expression patterns over multiple phenotypes. We have also extended BioSim to figure out pairwise differential expression pattern and coexpression dynamics. The significance of these studies is shown based on the analysis over several real-life data sets. The computation of the measure by focusing on stepwise time points also makes it effective to identify partially coexpressed genes. On the whole, we put forward a complete framework for coexpression analysis based on the BioSim measure.

Photobleaching on photonic crystal enhanced fluorescence surfaces

The effect of resonant fluorescent enhancement from a photonic crystal surface upon the fluorescent photobleaching rate of Cyanine-5 labeled protein has been investigated. We show that the enhanced excitation mechanism for photonic crystal enhanced fluorescence, in which the device surface resonantly couples light from an excitation laser, accelerates photobleaching in proportion to the coupling efficiency of the laser to the photonic crystal. We also show that the enhanced extraction mechanism, in which the photonic crystal directs emitted photons approximately normal to the surface, does not play a role in the rate of photobleaching. We show that the photobleaching rate of dye molecules on the photonic crystal surface is accelerated by 30x compared to an ordinary glass surface, but substantial signal gain is still evident, even after extended periods of continuous illumination at the resonant condition.