| Literature DB >> 31651220 |
Vishal Shinde1, Nan Hu1, Santosh Renuse2, Alka Mahale3, Akhilesh Pandey2, Charles Eberhart4, Donald Stone5, Samar A Al-Swailem6, Azza Maktabi7, Shukti Chakravarti1,8.
Abstract
Keratoconus (KCN) is a leading cause for cornea grafting worldwide. Keratoconus is a multifactorial disease that causes progressive thinning of the cornea and whose etiology is poorly understood. Several studies have used proteomics on patient tear fluids to identify potential biomarkers. However, proteome of the cornea itself has not been investigated fully. We report here new findings from a case-control study using multiplexed mass spectrometry (MS) on individual (unpooled) corneas to gain deeper insights into proteins and biomarkers relevant to keratoconus. We employed a high-pressure approach to extract total protein from individual corneas from five cases and five controls, followed by trypsin digestion and tandem mass tag (TMT) labeling. The MS-derived data were searched using the Human NCBI RefSeq protein database v92, with peptides and proteins filtered at 1% false discovery rate. A total of 3132 proteins were detected, of which 627 were altered significantly (p ≤ 0.05) in keratoconus corneas. The increases were overwhelmingly in the mTOR/PI3/AKT signal-mediated regulations of cell survival and proliferation, nonsense-mediated decay of transcripts, and proteasomal pathways. The decreases were in several extracellular matrix proteins and in many members of the complement system. Importantly, this multiplexed proteomic study of keratoconus corneas identified, to our knowledge, the largest number of corneal proteins. The novel findings include changes in pathways that regulate transcript stability, proteasomal degradation, and the complement system in corneas with keratoconus. These observations offer new prospects toward future discovery of novel molecular targets for diagnostic and therapeutic innovations for patients with keratoconus.Entities:
Keywords: ER stress; complement; cornea; keratoconus; proteasomal degradation; proteomics
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Year: 2019 PMID: 31651220 PMCID: PMC6857467 DOI: 10.1089/omi.2019.0143
Source DB: PubMed Journal: OMICS ISSN: 1536-2310