Gerarduzzi, C. | Search bioRxiv

bioRxiv2023

Identification of inflammatory biomarkers in IgA nephropathy using the NanoString technology: a validation study

Objective and designImmunoglobulin A nephropathy (IgAN) is a kidney disease characterized by the accumulation of IgA deposits in the glomeruli of the kidney, leading to inflammation and damage to the kidney. The inflammatory markers involved in IgAN remain to be defined. Gene expression analysis platforms, such as the NanoString nCounter system, are promising screening and diagnostic tools, especially in the oncology field, but its role as a diagnostic and prognostic tool in IgAN remains scarce. In this study, we aimed to validate the use of NanoString technology to identify potential inflammatory biomarkers involved in the progression of IgAN. SubjectsA total of 30 patients with biopsy-proven IgAN and 7 cases of antineutrophil cytoplasmic antoantibodies (ANCA) associated pauci-immune glomerulonephritis were included for gene expression measurement. For the immunofluorescence validation experiments, a total of 6 IgAN patients and 3 healthy controls were included. MethodsTotal RNA was extracted from formalin-fixed-paraffin-embedded kidney biopsy specimens, and a customized 48-plex human gene CodeSet was used to study 29 genes implicated in different biological pathways. Comparisons in gene expression were made between IgAN and ANCA-associated pauci-immune glomerulonephritis patients to delineate an expression profile specific to IgAN. Gene expression was compared between patients with low and moderate risk of progression. Genes for which RNA expression was associated with disease progression were analyzed for protein expression by immunofluorescence, and compared with healthy controls. ResultsIgAN patients had a distinct gene expression profile with decreased expression in genes IL-6, INFG and C1QB compared to ANCA patients. C3 and TNFR2 were identified as potential biomarkers for IgAN progression in patients early in their disease course. Protein expression for those 2 candidate genes was upregulated in IgAN patients compared to controls. Expression of genes implicated in fibrosis (PTEN, CASPASE 3, TGM2, TGFB1, IL2, and TNFRSF1B) was more pronounced in IgAN patient with severe fibrosis compared to those with none. ConclusionsOur findings validate our NanoString mRNA profiling by examining protein expression levels of two candidate genes, C3 and TNFR2, in IgAN patients and healthy controls. We were also able to identify several upregulated mRNA transcripts implicated in the development of fibrosis that may be considered as fibrotic markers within IgAN patients.

genomics↗

bioRxiv2022

Seq2Neo: a comprehensive pipeline for cancer neoantigen im-munogenicity prediction

Neoantigens derived from somatic DNA alterations are ideal cancer-specific targets. In recent years, the combination therapy of PD-1/PD-L1 blockers and neoantigen vaccines shows clinical efficacy in original PD-1/PD-L1 blocker non-responders. However, not all somatic DNA mutations can result in immunogenicity in cancer cells, and efficient tools for predicting the immunogenicity of neoepitope are still urgently needed. Here we present the Seq2Neo pipeline, which provides a one-stop solution for neoepitope features prediction from raw sequencing data, and neoantigens derived from different types of genome DNA alterations, including point mutations, insertion deletions, and gene fusions are supported. Importantly a convolutional neural networks (CNN) based model has been trained to predict the immunogenicity of neoepitope. And this model shows improved performance compared with currently available tools in immunogenicity prediction in independent datasets. We anticipate that the Seq2Neo pipeline will become a useful tool in prediction of neoantigen immunogenicity and cancer immunotherapy. Seq2Neo is an open-source software under an academic free license (AFL) v3.0 and it is freely available at https://github.com/XSLiuLab/Seq2Neo.

bioinformatics↗