Biology subjects

Guo, A.-Y.

Publications and source records attributed to Guo, A.-Y..

2 recordsLinked to original sources

bioRxiv2019

Systematical analysis reveals the novel function of Cyp2c29 in liver injury

As a severe lethal cancer, hepatocellular carcinoma (HCC) usually originates from chronic liver injury and inflammation, in which the discovery of key genes is important for HCC prevention. Here, we analyzed the time serial (from 0 week to 30 weeks) transcriptome data of liver injury samples in diethylnitrosamine (DEN)-induced HCC mouse model. Through expression and function analyses, we identified that Cyp2c29 was a key gene continuously downregulated during liver injury. Overexpression of Cyp2c29 suppressed the NF-{kappa}B activation, proinflammatory cytokine production and hepatocyte proliferation by increasing its production 14,15-epoxyeicosatrienoic acid (14,15-EET). Furthermore, in vivo Cyp2c29 protected against liver inflammation in liver injury mice models by reversing the expression on functions of cell proliferation, metabolism and inflammation including suppressing NF-{kappa}B pathway and compensatory proliferation. CYP2C8 and CYP2C9, two human homologs of mouse Cyp2c29, were decreased in human HCC progression and positively correlated with HCC patient survival. Therefore, through systematical analysis and verification, we identified that Cyp2c29 is a novel gene in liver injury and inflammation, which may be a potential biomarker for HCC prevention and prognosis.

bioinformatics↗

bioRxiv2019

An ultra-sensitive T-cell receptor detection method for TCR-Seq and RNA-Seq data

T-cell receptors (TCRs) recognizing antigens play vital roles in T-cell immunology. Surveying TCR repertoires by characterizing complementarity-determining region 3 (CDR3) can provide valuable insights into the immune community underlying pathologic conditions, which will benefit neoantigen discovery and cancer immunotherapy. Here we present a novel tool named CATT, which can apply on TCR sequencing (TCR-Seq), RNA-Seq, and single-cell TCR(RNA)-Seq data to characterize CDR3 repertoires. CATT integrated maximum-network-flow based micro-assembly algorithm, data-driven error correction model, and Bayes classification algorithm, to self-adaptively and ultra-sensitively characterize CDR3 repertoires with high accuracy. Benchmark results of datasets from in silico and real conditions demonstrated that CATT showed superior recall and precision compared with other prevalent tools, especially for datasets with short read length and small data size. By applying CATT on a TCR-Seq dataset from aplastic anemia patients, we found the skewing of TCR repertoire was due to the oligoclonal expansion of effector memory T-cells. CATT will be a powerful tool for researchers conducting TCR and immune repertoire studies. CATT is freely available at http://bioinfo.life.hust.edu.cn/CATT.

bioinformatics↗