Shabarni Gupta

Challenges and prospects for biomarker research: A current perspective from the developing world

Majority of deaths due to communicable and non-communicable diseases occur in the low and middle-income nations (LMNs), mainly due to the lack of early diagnoses and timely treatments. In such a scenario, biomarkers serve as an indispensible resource that can be used as indicators of biological processes, specific disease conditions or response to therapeutic interventions. Evaluation, diagnosis and management of diseases in developing world by following/extrapolating the findings obtained on the basis of the research work involving only the populations from the developed countries, could often be highly misleading due to existence of diverse patterns of diseases in developing countries compared to the developed world. Biomarker candidates identified from high-throughput integrated omics technologies have promising potential; however, their actual clinical applications are found to be limited, primarily due to the challenges of disease heterogeneity and pre-analytical variability associated with the biomarker discovery pipeline. Additionally, in the developing world, economic crunches, lack of awareness and education, paucity of biorepositories, enormous diversities in socio-epidemiological background, ethnicity, lifestyle, diet, exposure to various environmental risk factors and infectious agents, and ethical and social issues also cumulatively hinder biomarker discovery ventures. Establishment of standard operating procedures, comprehensive data repositories and exchange of scientific findings are crucial for reducing the variability and fragmentation of data. This review highlights the challenges associated with the discovery, validation and translational phases of biomarker research in LMNs with some of their amenable solutions and future prospects. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.

An overview of innovations and industrial solutions in protein microarray technology

The complexity involving protein array technology reflects in the fact that instrumentation and data analysis are subject to change depending on the biological question, technical compatibility of instruments and software used in each experiment. Industry has played a pivotal role in establishing standards for future deliberations in sustenance of these technologies in the form of protein array chips, arrayers, scanning devices, and data analysis software. This has enhanced the outreach of protein microarray technology to researchers across the globe. These have encouraged a surge in the adaptation of “nonclassical” approaches such as DNA‐based protein arrays, micro‐contact printing, label‐free protein detection, and algorithms for data analysis. This review provides a unique overview of these industrial solutions available for protein microarray based studies. It aims at assessing the developments in various commercial platforms, thus providing a holistic overview of various modalities, options, and compatibility; summarizing the journey of this powerful high‐throughput technology.

Autoantibody Profiling of Glioma Serum Samples to Identify Biomarkers Using Human Proteome Arrays

The heterogeneity and poor prognosis associated with gliomas, makes biomarker identification imperative. Here, we report autoantibody signatures across various grades of glioma serum samples and sub-categories of glioblastoma multiforme using Human Proteome chips containing ~17000 full-length human proteins. The deduced sets of classifier proteins helped to distinguish Grade II, III and IV samples from the healthy subjects with 88, 89 and 94% sensitivity and 87, 100 and 73% specificity, respectively. Proteins namely, SNX1, EYA1, PQBP1 and IGHG1 showed dysregulation across various grades. Sub-classes of GBM, based on its proximity to the sub-ventricular zone, have been reported to have different prognostic outcomes. To this end, we identified dysregulation of NEDD9, a protein involved in cell migration, with probable prognostic potential. Another subcategory of patients where the IDH1 gene is mutated, are known to have better prognosis as compared to patients carrying the wild type gene. On a comparison of these two cohorts, we found STUB1 and YWHAH proteins dysregulated in Grade II glioma patients. In addition to common pathways associated with tumourigenesis, we found enrichment of immunoregulatory and cytoskeletal remodelling pathways, emphasizing the need to explore biochemical alterations arising due to autoimmune responses in glioma.

Protein microarray applications: Autoantibody detection and posttranslational modification

The discovery of DNA microarrays was a major milestone in genomics; however, it could not adequately predict the structure or dynamics of underlying protein entities, which are the ultimate effector molecules in a cell. Protein microarrays allow simultaneous study of thousands of proteins/peptides, and various advancements in array technologies have made this platform suitable for several diagnostic and functional studies. Antibody arrays enable researchers to quantify the abundance of target proteins in biological fluids and assess PTMs by using the antibodies. Protein microarrays have been used to assess protein–protein interactions, protein–ligand interactions, and autoantibody profiling in various disease conditions. Here, we summarize different microarray platforms with focus on its biological and clinical applications in autoantibody profiling and PTM studies. We also enumerate the potential of tissue microarrays to validate findings from protein arrays as well as other approaches, highlighting their significance in proteomics.

Evaluation of autoantibody signatures in meningioma patients using human proteome arrays

Meningiomas are one of the most common tumors of the Central nervous system (CNS). This study aims to identify the autoantibody biomarkers in meningiomas using high-density human proteome arrays (~17,000 full-length recombinant human proteins). Screening of sera from 15 unaffected healthy individuals, 10 individuals with meningioma grade I and 5 with meningioma grade II was performed. This comprehensive proteomics based investigation revealed the dysregulation of 489 and 104 proteins in grades I and II of meningioma, respectively, along with the enrichment of several signalling pathways, which might play a crucial role in the manifestation of the disease. Autoantibody targets like IGHG4, CRYM, EFCAB2, STAT6, HDAC7A and CCNB1 were significantly dysregulated across both the grades. Further, we compared this to the tissue proteome and gene expression profile from GEO database. Previously reported upregulated proteins from meningioma tissue-based proteomics obtained from high-resolution mass spectrometry demonstrated an aggravated autoimmune response, emphasizing the clinical relevance of these targets. Some of these targets like SELENBP1 were tested for their presence in tumor tissue using immunoblotting. In the light of highly invasive diagnostic modalities employed to diagnose CNS tumors like meningioma, these autoantibody markers offer a minimally invasive diagnostic platform which could be pursued further for clinical translation.Meningiomas are one of the most common tumors of the Central nervous system (CNS). This study aims to identify the autoantibody biomarkers in meningiomas using high-density human proteome arrays (~17,000 full-length recombinant human proteins). Screening of sera from 15 unaffected healthy individuals, 10 individuals with meningioma grade I and 5 with meningioma grade II was performed. This comprehensive proteomics based investigation revealed the dysregulation of 489 and 104 proteins in grades I and II of meningioma, respectively, along with the enrichment of several signalling pathways, which might play a crucial role in the manifestation of the disease. Autoantibody targets like IGHG4, CRYM, EFCAB2, STAT6, HDAC7A and CCNB1 were significantly dysregulated across both the grades. Further, we compared this to the tissue proteome and gene expression profile from GEO database. Previously reported upregulated proteins from meningioma tissue-based proteomics obtained from high-resolution mass spectrometry demonstrated an aggravated autoimmune response, emphasizing the clinical relevance of these targets. Some of these targets like SELENBP1 were tested for their presence in tumor tissue using immunoblotting. In the light of highly invasive diagnostic modalities employed to diagnose CNS tumors like meningioma, these autoantibody markers offer a minimally invasive diagnostic platform which could be pursued further for clinical translation.

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

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

Omics: Data Processing and Analysis

The innovations in genome sequencing technologies have emanated in better understanding of biosystems leading to the dawn of the “omics” era. Proteomics has been an integral interface in the post-genomic era, and has allowed researchers to explore other omics-based platforms like metabolomics, transcriptomics, phenomics, etc. In pursuit of obtaining a systemic understanding of biosystems, the scientific community is now largely incorporating a multi-omics-based workflow, with genomics and proteomics at the centre of this integrated approach. Techniques such as gel-based proteomics, mass spectrometry, protein microarrays and label-free platforms have emerged as powerful tools for high-throughput screening and discovery-based studies in many of these multi-omics disciplines. However, with increased throughput, large amount of data is generated, and analysis of huge data often poses a challenge to researchers. The automation in specialized software has been immensely helpful to researchers in data acquisition; however, the downstream workflow of these sophisticated technologies continues to disconcert scientists, embracing an integrated multi-omics approach. This chapter aims at providing an overview of various proteomics-based technologies and their data evaluation strategies in context to biological studies. Data storage in specialized databases also requires attention, but is beyond the scope of this chapter. Gel-based proteomics, mass spectrometry, protein microarrays and label-free technologies are some of the commonly employed techniques in metabolomics, interactomics, genomics and transcriptomics, thus encompassing a multi-omics perspective on data analysis.

Regulatory Norms and Intellectual Property Rights for Biomarker Research

The healthcare industry has hugely benefited from the advent of biomarkers in diagnostics. The process of translation of a biomarker from “bench to bedside,” however, involves various key steps which are monitored by autonomous bodies to ensure that the biomarker/biosimilars under consideration are safe and meet the regulatory guidelines established by them. This chapter aims to provide an overview of global regulatory bodies and discusses the various norms required for commercialization of biomarkers, with special focus on the role of proteomic-based tools to help study the efficacy of these biomarkers. Another facet, concurrent with the post discovery-based endeavors from regulatory bodies, is the protection of intellectual property rights of a researcher’s discovery-based work. Patent claims have repeatedly been under the scrutiny of legislative bodies due to controversies on subjects like patent eligibility resulting in the impediment of scientific progress and research. This has consequently resulted in restricting the disputed product’s use in diagnoses and other applications. Additionally, this chapter overviews the nuances of patent filing to protect the intellectual property rights of researchers involved in the discovery of biomarkers prior to their commercialization.

Exigencies of Biomarker Research in the Developing World: A Focus on the Dearth of Biobanking Resources

The enormous burden of infectious as well as noninfectious diseases makes biomarker discovery-based research an imperative in the developing world. The extent of diversity and heterogeneity in the type of diseases that plague the low- and middle-income group nations often show a stark difference with the diseases that affect the developed countries. In order to enable global efforts to combat any given disease, it is important for researchers to have a large number of reliable biospecimens on which they could validate their findings. Inappropriate representation of samples at primary stages of research has sometimes been attributed to researchers not being able to find gold-standard biomarkers. To capture the disease heterogeneity in the subjects ranging from genetic and ethnic diversity to the underlying pathogenesis, it is important to create a resource which could facilitate the availability of biospecimens from a large cohort of subjects along with their clinical annotation, which can be studied by researchers for reliable biomarker discovery. Moreover, biorepositories are also necessary resources for facilitating validation-based studies following the discovery phase. This chapter summarizes the pressing need for well-planned and managed biorepositories as one of the primary steps to facilitate reliable biomarker discovery in the developing world.

Geographic Pervasiveness of Cancer: Prospects of Novel Biomarker and Therapeutic Research in Developing Countries using OMICS approaches

Lack of homogeneity in lineages of tumour cell population, in addition to constant evolution of abnormal cells, results in intratumour heterogeneity. Tumour prognosis, to a great extent, depends on the permutations and combinations in which one or more clonal lineage prevails. This directly affects therapeutic decisions as tumour sensitivity, or resistance to a particular treatment is reflected in the heterogeneity it presents. In this context, geographic predisposition presents a different dimension which may drive this heterogeneity in a particular direction and is probably the larger set of cause followed by subsets of causes like clonal evolution or cancer stem cells which result in the idiopathic nature of tumour heterogeneity. However, the geographic pervasiveness of cancers has not been studied in depth in context to tumour heterogeneity. The suffix “-omics” denotes a study in total of that particular stream of science. For example, the study of genome is referred to as genomics. Off late, multi-omics approaches encompassing a systemic understanding of cancer tissues have shed immense light in understanding the molecular basis of tumour heterogeneity with regard to the classical models traditionally proposed to explain the heterogeneity. Genomics, proteomics, metabolomics and transcriptomics have received an enormous boost with emergence and evolution of high-throughput technology like mass spectrometry and next-generation sequencing. This chapter discusses briefly about the type of tumour heterogeneity noticed especially in context of the developing world and how OMICS-based research can bring about a revolution in understanding any geographic bias that may exist and contribute to tumour heterogeneity.