The majority of cell differentiation associated tumor markers reported to date are either glycoproteins or glycolipids. Despite there being a large number of glycoproteins reported as candidate markers for various cancers, only a handful are approved by the US Food and Drug Administration. Lectins, which bind to the glycan part of the glycoproteins, can be exploited to identify aberrant glycosylation patterns, which in turn would help in enhancing the specificity of cancer diagnosis. Although conventional techniques such as HPLC and MS have been instrumental in performing the glycomic analyses, these techniques lack multiplexity. Lectin microarrays have proved to be useful in studying multiple lectin-glycan interactions in a single experiment and, with the advances made in the field, hold a promise of enabling glycomic profiling of cancers in a fast and efficient manner.

No abstract

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.

The analysis of extracellular vesicles (EVs) typically requires tedious and time-consuming isolation process from bio-fluids. We developed a nanoparticle-based time resolved fluorescence immunoassay (NP-TRFIA) that uses biotinylated antibodies against the proteins of tetraspanin family and tumor-associated antigens for capturing EVs from urine samples and cell culture supernatants without the need for isolation. The captured-EVs were detected either with Eu 3+ -chelate or Eu 3+ -doped nanoparticle-based labels conjugated either to antibodies against the tetraspanins or lectins targeting the glycan moieties on EVs surface. The NP-TRFIA demonstrated specific capturing and detection of EVs by antibodies and lectins. Lectin-nanoparticle based assays showed 2–10 fold higher signal-to-background ratio compared with lectin-chelate assays. The nanoparticle assay concept allowed surface glycosylation profiling of the urine derived-EVs with lectins. It was also applied to establish an assay showing differential expression of tumor-associated proteins on more aggressive (higher ITGA3 on DU145- and PC3-EVs) compared to less aggressive (higher EpCAM on LNCaP-EVs) PCa- cell lines derived-EVs. This NP-TRFIA can be used as a simple tool for analysis and characterization of EVs in urine and cell culture supernatants. Such approach could be useful in identification of disease-specific markers on the surface of patient-derived urinary EVs.

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.

No abstract

BackgroundThe simplicity and potential of minimal invasive testing using serum from patients make auto-antibody based biomarkers a very promising tool for use in diagnostics of cancer and auto-immune disease. Although several methods exist for elucidating candidate-protein markers, immobilizing these onto membranes and generating so called macroarrays is of limited use for marker validation. Especially when several hundred samples have to be analysed, microarrays could serve as a good alternative since processing macro membranes is cumbersome and reproducibility of results is moderate.MethodsCandidate markers identified by SEREX (serological identification of antigens by recombinant expression cloning) screenings of brain and lung tumour were used for macroarray and microarray production. For microarray production recombinant proteins were expressed in E. coli by autoinduction and purified His-tag (histidine-tagged) proteins were then used for the production of protein microarrays. Protein arrays were hybridized with the serum samples from brain and lung tumour patients.ResultMethods for the generation of microarrays were successfully established when using antigens derived from membrane-based selection. Signal patterns obtained by microarrays analysis of brain and lung tumour patients' sera were highly reproducible (R = 0.92-0.96). This provides the technical foundation for diagnostic applications on the basis of auto-antibody patterns. In this limited test set, the assay provided high reproducibility and a broad dynamic range to classify all brain and lung samples correctly.ConclusionProtein microarray is an efficient means for auto-antibody-based detection when using SEREX-derived clones expressing antigenic proteins. Protein microarrays are preferred to macroarrays due to the easier handling and the high reproducibility of auto-antibody testing. Especially when using only a few microliters of patient samples protein microarrays are ideally suited for validation of auto-antibody signatures for diagnostic purposes.

No abstract