Heterogeneous nuclear ribonucleoproteins and their interactors are a major class of deregulated proteins in anaplastic astrocytoma: a grade III malignant glioma

Quantitative proteomic analysis of GnRH agonist treated GBM cell line LN229 revealed regulatory proteins inhibiting cancer cell proliferation

BACKGROUND

Gonadotropin-releasing hormone (GnRH) receptor, a rhodopsin-like G-protein coupled receptor (GPCR) family member involved in GnRH signaling, is reported to be expressed in several tumors including glioblastoma multiforme (GBM), one of the most malignant and aggressive forms of primary brain tumors. However, the molecular targets associated with GnRH receptor are not well studied in GBM or in other cancers. The present study aims at investigating the effect of GnRH agonist (Gosarelin acetate) on cell proliferation and associated signaling pathways in GBM cell line, LN229.

METHODS

LN229 cells were treated with different concentrations of GnRH agonist (10^-10 M to 10^-5 M) and the effect on cell proliferation was analyzed by cell count method. Further, total protein was extracted from control and GnRH agonist treated cells (with maximum reduction in cell proliferation) followed by trypsin digestion, labeling with iTRAQ reagents and LC-MS/MS analysis to identify differentially expressed proteins. Bioinformatic analysis was performed for annotation of proteins for the associated molecular function, altered pathways and network analysis using STRING database.

RESULTS

The treatment with different concentrations of GnRH agonist showed a reduction in cell proliferation with a maximum reduction of 48.2% observed at 10^-6 M. Quantitative proteomic analysis after GnRH agonist treatment (10^-6 M) led to the identification of a total of 29 differentially expressed proteins with 1.3-fold change (23 upregulated, such as, kininogen-1 (KNG1), alpha-2-HS-glycoprotein (AHSG), alpha-fetoprotein (AFP), and 6 downregulated, such as integrator complex subunit 11 (CPSF3L), protein FRG1 (FRG1). Some of them are known [KNG1, AHSG, AFP] while others such as inter-alpha-trypsin inhibitor heavy chain H2 (ITIH2), ITIH4, and LIM domain-containing protein 1 (LIMD1) are novel to GnRH signaling pathway. Protein-protein interaction analysis showed a direct interaction of KNG1, a hub molecule, with GnRH, GnRH receptor, EGFR and other interactors including ITIH2, ITIH4 and AHSG. Overexpression of KNG1 after GnRH agonist treatment was validated using Western blot analysis, while a significant inhibition of EGFR was observed after GnRH agonist treatment.

CONCLUSIONS

The study suggests a possible link of GnRH signaling with EGFR signaling pathways likely via KNG1. KNG1 inhibitors may be investigated independently or in combination with GnRH agonist for therapeutic applications.

The development and clinical applications of proteomics: an Indian perspective

INTRODUCTION

Proteomic research has been extensively used to identify potential biomarkers or targets for various diseases. Advances in mass spectrometry along with data analytics have led proteomics to become a powerful tool for exploring the critical molecular players associated with diseases, thereby, playing a significant role in the development of proteomic applications for the clinic.

AREAS COVERED

This review presents recent advances in the development and clinical applications of proteomics in India toward understanding various diseases including cancer, metabolic diseases, and reproductive diseases. Keywords combined with 'clinical proteomics in India' 'proteomic research in India' and 'mass spectrometry' were used to search PubMed.

EXPERT OPINION

The past decade has seen a significant increase in research in clinical proteomics in India. This approach has resulted in the development of proteomics-based marker technologies for disease management in the country. The majority of these investigations are still in the discovery phase and efforts have to be made to address the intended clinical use so that the identified potential biomarkers reach the clinic. To move toward this necessity, there is a pressing need to establish some key infrastructure requirements and meaningful collaborations between the clinicians and scientists which will enable more effective solutions to address health issues specific to India.

Glioma tumor proteomics: clinically useful protein biomarkers and future perspectives

Introduction: Despite being rare cancers, gliomas account for a significant number of cancer-related deaths. Identification and treatment of these tumors at an early stage would greatly improve the therapeutic outcomes. There is an urgent need for diagnostic and prognostic markers, which can identify disease early and discriminate the subtypes of these tumors thereby improving the existing treatment modalities.Areas covered: In this article, we have reviewed published literature on proteomics biomarkers for gliomas and their importance in diagnosis or prognosis. Proteomic studies for the discovery of protein, autoantibody biomarkers, and biological pathway alterations in serum, CSF and tumor biopsies have been discussed in this review.Expert opinion: The rapid development in the field of mass spectrometry and increased sensitivity and reproducibility in assays has led to the identification and quantification of large number of proteins very precisely. Though genomic markers are the prime focus in the classification of gliomas, incorporating protein markers would further improve the existing classification. In this regard, data mining and studies on large cohorts of glioma patients would help in the identification of diagnostic and prognostic markers ultimately translating to the clinics.

Altered transcriptional regulatory proteins in glioblastoma and YBX1 as a potential regulator of tumor invasion

We have studied differentially regulated nuclear proteome of the clinical tissue specimens of glioblastoma (GBM, WHO Grade IV) and lower grades of gliomas (Grade II and III) using high resolution mass spectrometry- based quantitative proteomics approach. The results showed altered expression of many regulatory proteins from the nucleus such as DNA binding proteins, transcription and post transcriptional processing factors and also included enrichment of nuclear proteins that are targets of granzyme signaling – an immune surveillance pathway. Protein - protein interaction network analysis using integrated proteomics and transcriptomics data of transcription factors and proteins for cell invasion process (drawn from another GBM dataset) revealed YBX1, a ubiquitous RNA and DNA-binding protein and a transcription factor, as a key interactor of major cell invasion-associated proteins from GBM. To verify the regulatory link between them, the co-expression of YBX1 and six of the interacting proteins (EGFR, MAPK1, CD44, SOX2, TNC and MMP13) involved in cell invasion network was examined by immunohistochemistry on tissue micro arrays. Our analysis suggests YBX1 as a potential regulator of these key molecules involved in tumor invasion and thus as a promising target for development of new therapeutic strategies for GBM.

Evaluation of non-supervised MALDI mass spectrometry imaging combined with microproteomics for glioma grade III classification

An integrated diagnosis using molecular features is recommended in the 2016 World Health Organization (WHO) classification. Our aim was to explore non-targeted molecular classification using MALDI mass spectrometry imaging (MALDI MSI) associated to microproteomics in order to classify anaplastic glioma by integration of clinical data. We used fresh-frozen tissue sections to perform MALDI MSI of proteins based on their digestion peptides after in-situ trypsin digestion of the tissue sections and matrix deposition by micro-spraying. The generated 70μm spatial resolution image datasets were further processed by individual or global segmentation in order to cluster the tissues according to their molecular protein signature. The clustering gives 3 main distinct groups. Within the tissues the ROIs (regions of interest) defined by these groups were used for microproteomics by micro-extraction of the tryptic peptides after on-tissue enzymatic digestion. More than 2500 proteins including 22 alternative proteins (AltProt) are identified by the Shotgun microproteomics. Statistical analysis on the basis of the label free quantification of the proteins shows a similar classification to the MALDI MSI segmentation into 3 groups. Functional analysis performed on each group reveals sub-networks related to neoplasia for group 1, glioma with inflammation for group 2 and neurogenesis for group 3. This demonstrates the interest on these new non-targeted large molecular data combining both MALDI MSI and microproteomics data, for tumor classification. This analysis provides new insights into grade III glioma organization. This specific information could allow a more accurate classification of the biopsies according to the prognosis and the identification of potential new targeted therapeutic options. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.

Differential proteomics analysis of low- and high-grade of astrocytoma using iTRAQ quantification

Astrocytoma is one of the most common types of brain tumor, which is histologically and clinically classified into four grades (I–IV): I (pilocytic astrocytoma), II (diffuse astrocytoma), III (anaplastic astrocytoma), and IV (glioblastoma multiforme). A higher grade astrocytoma represents a worse prognosis and is more aggressive. In this study, we compared the differential proteome profile of astrocytoma from grades I to IV. The protein samples from clinical specimens of grades I, II, III, and IV astrocytoma were analyzed by two-dimensional liquid chromatography–tandem mass spectrometry and isobaric tags for relative and absolute quantitation and quantification. A total of 2,190 proteins were identified. Compared to grade I astrocytoma, 173 (12.4%), 304 (14%), and 462 (21.2%) proteins were aberrantly expressed in grades II, III, and IV, respectively. By bioinformatics analysis, the cell proliferation, invasion, and angiogenesis-related pathways increase from low- to high-grade of astrocytoma. Five differentially expressed proteins were validated by Western blot. Within them, matrix metalloproteinase-9 and metalloproteinase inhibitor 1 were upregulated in glioblastoma multiforme group; whereas fibulin-2 and -5 were downregulated in grade II/III/IV astrocytoma, and the negative expression was significantly associated with advanced clinical stage. Functional analysis showed that both fibulin-2 and -5 may exert an antitumor effect by inhibiting cell proliferation, in vitro migration/invasion in glioma cells. New molecular biomarkers are likely to be used for accurate classification of astrocytoma and likely to be the target for drug development.

Microsomal membrane proteome of low grade diffuse astrocytomas: Differentially expressed proteins and candidate surveillance biomarkers

Diffuse astrocytoma (DA; WHO grade II) is a low-grade, primary brain neoplasm with high potential of recurrence as higher grade malignant form. We have analyzed differentially expressed membrane proteins from these tumors, using high-resolution mass spectrometry. A total of 2803 proteins were identified, 340 of them differentially expressed with minimum of 2 fold change and based on ≥2 unique peptides. Bioinformatics analysis of this dataset also revealed important molecular networks and pathways relevant to tumorigenesis, mTOR signaling pathway being a major pathway identified. Comparison of 340 differentially expressed proteins with the transcript data from Grade II diffuse astrocytomas reported earlier, revealed about 190 of the proteins correlate in their trends in expression. Considering progressive and recurrent nature of these tumors, we have mapped the differentially expressed proteins for their secretory potential, integrated the resulting list with similar list of proteins from anaplastic astrocytoma (WHO Grade III) tumors and provide a panel of proteins along with their proteotypic peptides, as a resource that would be useful for investigation as circulatory plasma markers for post-treatment surveillance of DA patients.

Network analysis of microRNAs, transcription factors, target genes and host genes in human anaplastic astrocytoma

Numerous studies have investigated the roles played by various genes and microRNAs (miRNAs) in neoplasms, including anaplastic astrocytoma (AA). However, the specific regulatory mechanisms involving these genes and miRNAs remain unclear. In the present study, associated biological factors (miRNAs, transcription factors, target genes and host genes) from existing studies of human AA were combined methodically through the interactions between genes and miRNAs, as opposed to studying one or several. Three regulatory networks, including abnormally expressed, related and global networks were constructed with the aim of identifying significant gene and miRNA pathways. Each network is composed of three associations between miRNAs targeted at genes, transcription factors (TFs) regulating miRNAs and miRNAs located on their host genes. Among these, the abnormally expressed network, which involves the pathways of previously identified abnormally expressed genes and miRNAs, partially indicated the regulatory mechanism underlying AA. The network contains numerous abnormal regulation associations when AA emerges. By modifying the abnormally expressed network factors to a normal expression pattern, the faulty regulation may be corrected and tumorigenesis of AA may be prevented. Certain specific pathways are highlighted in AA, for example PTEN which is targeted by miR-21 and miR-106b, regulates miR-25 which in turn targets TP53. PTEN and miR-21 have been observed to form feedback loops. Furthermore, by comparing and analyzing the pathway predecessors and successors of abnormally expressed genes and miRNAs in three networks, similarities and differences of regulatory pathways may be identified and proposed. In summary, the present study aids in elucidating the occurrence, mechanism, prevention and treatment of AA. These results may aid further investigation into therapeutic approaches for this disease.

Insights from Chromosome-Centric Mapping of Disease-Associated Genes: Chromosome 12 Perspective

In line with the aims of the Chromosome-based Human Proteome Project and the Biology/Disease-based Human Proteome Project, we have been studying differentially expressed transcripts and proteins in gliomas—the most prevalent primary brain tumors. Here, we present a perspective on important insights from this analysis in terms of their co-expression, co-regulation/de-regulation, and co-localization on chromosome 12 (Chr. 12). We observe the following: (1) Over-expression of genes mapping onto amplicon regions of chromosomes may be considered as a biological validation of mass spectrometry data. (2) Their co-localization further suggests common determinants of co-expression and co-regulation of these clusters. (3) Co-localization of "missing" protein genes of Chr. 12 in close proximity to functionally related genes may help in predicting their functions. (4) Further, integrating differentially expressed gene-protein sets and their ontologies with medical terms associated with clinical phenotypes in a chromosome-centric manner reveals a network of genes, diseases, and pathways—a diseasome network. Thus, chromosomal mapping of disease data sets can help uncover important regulatory and functional links that may offer new insights for biomarker development.

Towards developing biomarkers for glioblastoma multiforme: a proteomics view

Glioblastoma multiforme (GBM) is one of the most aggressive and lethal forms of the primary brain tumors. With predominance of tumor heterogeneity and emergence of new subtypes, new approaches are needed to develop tissue-based markers for tumor typing or circulatory markers to serve as blood-based assays. Multi-omics data integration for GBM tissues would offer new insights on the molecular view of GBM pathogenesis useful to identify biomarker panels. On the other hand, mapping differentially expressed tissue proteins for their secretory potential through bioinformatics analysis or analysis of the tumor cell secretome or tumor exosomes would enhance our understanding of the tumor microenvironment and prospects for targeting circulatory biomarkers. In this review, the authors first present potential biomarker candidates for GBM that have been reported and then focus on plausible pipelines for multi-omic data integration to identify additional, high-confidence molecular panels for clinical applications in GBM.