dbPepNeo: a manually curated database for human tumor neoantigen peptides.
Tan Xiaoxiu,Li Daixi,Huang Pengjie,Jian Xingxing,Wan Huihui,Wang Guangzhi,Li Yuyu,Ouyang Jian,Lin Yong,Xie Lu
Database : the journal of biological databases and curation
Neoantigens can function as actual antigens to facilitate tumor rejection, which play a crucial role in cancer immunology and immunotherapy. Emerging evidence revealed that neoantigens can be used to develop personalized, cancer-specific vaccines. To date, large numbers of immunogenomic peptides have been computationally predicted to be potential neoantigens. However, experimental validation remains the gold standard for potential clinical application. Experimentally validated neoantigens are rare and mostly appear scattered among scientific papers and various databases. Here, we constructed dbPepNeo, a specific database for human leukocyte antigen class I (HLA-I) binding neoantigen peptides based on mass spectrometry (MS) validation or immunoassay in human tumors. According to the verification methods of these neoantigens, the collection of peptides was classified as 295 high confidence, 247 medium confidence and 407 794 low confidence neoantigens, respectively. This can serve as a valuable resource to aid further screening for effective neoantigens, optimize a neoantigen prediction pipeline and study T-cell receptor (TCR) recognition. Three applications of dbPepNeo are shown. In summary, this work resulted in a platform to promote the screening and confirmation of potential neoantigens in cancer immunotherapy. Database URL: www.biostatistics.online/dbPepNeo/.
Intrinsic Genetic and Transcriptomic Patterns Reflect Tumor Immune Subtypes Facilitating Exploring Possible Combinatory Therapy.
Xu Yong,Li Daixi,Liu Zhenhao,Gibbs David L,Xie Lu,Qin Guangrong
Frontiers in molecular biosciences
The classification of immune subtypes was based on immune signatures highlighting the tumor immuno-microenvironment. It was found that immune subtypes associated with mutation and expression patterns in the tumor. How the intrinsic genetic and transcriptomic alterations contribute to the immune subtypes and how to select drug combinations from both targeted drugs and immune therapeutic drugs according to different immune subtypes are still not clear. Through statistical analysis of genetic alterations and transcriptional profiles of breast invasive carcinoma (BRCA) samples, we found significant differences in the number of somatic missense mutations and frameshift deletions among the different immune subtypes. The high mutation load for somatic missense mutations and frameshift deletions may be explained by the high frequency of mutations and high expression of DNA double-strand break repair pathway genes. Extensive analysis of signaling pathways in both the genetic and transcriptomic levels reveals significantly altered pathways such as tumor protein Tumor Protein P53 (TP53) and receptor tyrosine kinase (RTK)/RAS signaling pathways among different subtypes. Drug targets in the signaling pathways such as mitogen-activated protein kinase kinase kinase 1 (MAP3K1) and Phosphatidylinositol-4,5-Bisphosphate 3-Kinase Catalytic Subunit Alpha (PIK3CA) show genetic alteration in specific subtypes, which may be potential targets for patients of a specific subtype. More drug targets which show transcriptional difference among immune subtypes were discovered, such as cyclin-dependent kinase (CDK)4, CDK6, Erb-B2 receptor tyrosine kinase 2 (ERBB2), etc. Moreover, differences in functional activity between tumor growth and immune-related pathways also elucidate the extrinsic factors of differences in prognosis and suggest potential drug combinations for different immune subtypes. These results help to explain how intrinsic alterations are associated with the immune subtypes and provide clues for possible combination therapy for different immune subtypes.
An ultrahigh-throughput screening platform based on flow cytometric droplet sorting for mining novel enzymes from metagenomic libraries.
Ma Fuqiang,Guo Tianjie,Zhang Yifan,Bai Xue,Li Changlong,Lu Zelin,Deng Xi,Li Daixi,Kurabayashi Katsuo,Yang Guang-Yu
Uncultivable microbial communities provide enormous reservoirs of enzymes, but their experimental identification by functional metagenomics is challenging, mainly due to the difficulty of screening enormous metagenomic libraries. Here, we propose a reliable and convenient ultrahigh-throughput screening platform based on flow cytometric droplet sorting (FCDS). The FCDS platform employs water-in-oil-in-water double emulsion droplets serving as single-cell enzymatic micro-reactors and a commercially available flow cytometer, and it can efficiently isolate novel biocatalysts from metagenomic libraries by processing single cells as many as 10 per day. We demonstrated the power of this platform by screening a metagenomic library constructed from domestic running water samples. The FCDS assay screened 30 million micro-reactors in only 1 h, yielding a collection of esterase genes. Among these positive hits, Est WY was identified as a novel esterase with high catalytic efficiency and distinct evolutionary origin from other lipolytic enzymes. Our study manifests that the FCDS platform is a robust tool for functional metagenomics, with the potential to significantly improve the efficiency of exploring novel enzymes from nature.