A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä

Evaluation of autoantibody signatures in meningioma patients using human proteome arrays




TekijätGupta S, Mukherjee S, Syed P, Pandala NG, Choudhary S, Singh VA, Singh N, Zhu H, Epari S, Noronha SB, Moiyadi A, Srivastava S

KustantajaIMPACT JOURNALS LLC

KustannuspaikkaNew York

Julkaisuvuosi2017

JournalOncotarget

Tietokannassa oleva lehden nimiONCOTARGET

Lehden akronyymiONCOTARGET

Vuosikerta8

Numero35

Aloitussivu58443

Lopetussivu58456

Sivujen määrä14

ISSN1949-2553

eISSN1949-2553

DOIhttps://doi.org/10.18632/oncotarget.16997

Verkko-osoite10.18632/oncotarget.16997


Tiivistelmä
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 (similar to 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.



Last updated on 2024-26-11 at 18:11