Exosomal STK39 is a Predictive Biomarker for Anti-VEGF Treatment Response in Neovascular Age-Related Macular Degeneration
Background: Age-related macular degeneration (AMD) is the leading cause of blindness worldwide, predominantly affecting individuals over 60. AMD is classified into two clinical forms: dry (DAMD) and neovascular (NAMD). NAMD, characterized by choroidal neovascularization and increased vascular endothelial growth factor (VEGF) levels, is treated with anti-VEGF therapy, the gold standard for preventing vision loss. However, challenges including non-response to treatment, persistent disease activity, and unnecessary anti-VEGF administration necessitate the identification of predictive biomarkers to optimize therapy. Exosomes (exo) are extracellular vesicles known for their stability and role in cellular communication, carrying diverse molecular contents, including RNA. Although the role of exo-RNA in AMD pathogenesis is well known, their role in the response to anti-VEGF treatment has not yet been investigated. Current study aim to investigate the role of exo-RNAs as potential biomarkers for predicting anti-VEGF treatment response in NAMD patients. Methods: Plasma-derived exo-RNA were analyzed pre- and post-treatment to identify predictive biomarkers from 41 NAMD patients treated with intravitreal bevacizumab. Exo were isolated using exoRNAeasy midi kit and characterized by TEM, NTA, and Western blot. Then, RNA-seq was performed to profile exo-RNAs and key candidates were validated using RT-qPCR. Results: Following anti-VEGF therapy, 68.3% of NAMD patients (mean age: 70.8 ± 6.14), demonstrated anatomical success, while 53.7% achieved functional success. Based on RNA-seq comparative analysis between the two groups revealed that translation mechanisms were significantly regulated, particularly within the context of upregulated pathways. Genes associated with molecular functions such as insulin response, transport, angiogenesis, and oxygen transport were prominently implicated. Conversely, the evaluation of downregulated pathways indicated substantial alterations in RNA catabolic processes and the regulation of gene expression. RNA-seq revealed BMP6 and STK39 as key candidate genes, with post-treatment dysregulation in hsa-miR-4692 expression, a microRNA targeting STK39. Finally, RT-qPCR validation show that elevated pre-treatment exo-STK39 levels were significantly associated with anatomical success (*p=0.04). Overall design: RNA-seq analysis was performed to evaluate the effect of anti-VEGF treatment on exo-RNA regulation in NAMD patients. For RNA-seq analysis, a cohort of 5 anti-VEGF(-) and 4 anti-VEGF(+) patients were selected to evaluate the treatment response at the exo-mRNA and exo-miRNA levels. Following treatment, one patient was excluded from the analysis due to suboptimal read quality, resulting in a final analysis of 5 anti-VEGF(-) and 4 anti-VEGF(+) patients. For the miRNA analysis, 3 anti-VEGF (-) and 3 anti-VEGF(+) patients were selected, based on the quality of small RNA sequencing data, ensuring comparable read quality across both groups. The most optimal exo- RNA candidate at the mRNA level was identified by analyzing the pathways, interactions, and external regulations associated with the obtained miRNA data. This approach allowed for the  determination of key biological processes and regulatory networks in which the miRNA- derived exo-RNAs were involved, thereby facilitating the identification of the most relevant candidate for further investigation. Total RNA isolation was performed using the QIAGEN exoRNeasy Midi kit (Qiagen, Hilden, Germany). RNA quality and concentrations were analyzed using Agilent Technologies 4200 TapeStation (Agilent Technologies, Santa Clara, California, USA). To perform RNA sequencing, mRNA and small RNA libraries were generated using the Illumina NextSeq 500 platform with the SMARTer smRNA-Seq Kit (Illumina, Takara Bio, Shiga, Japan) based on the manufacturer's instructions. The libraries were gel-purified using the D1000 ScreenTape System (Agilent Technologies, Waldbronn, Germany). Then, RPKM-normalized count were used for analysis to identify differentially expressed genes and mature miRNAs between anti- VEGF (-) vs anti-VEGF (+). A p-value correction was performed using the false discovery rate (FDR) correction determined for each gene or miRNA. The cut- off value for the adjusted p- value was accepted at 0.05, Dysregulated genes/miRNAs were determined by fold changes.