Abstract: A method and a system for calculating tumor neoantigen burden (TNB) are provided. The method includes: step S1: processing a normal sample and a tumor sample, sequencing a specific region and detecting somatic mutations in the sample; step S2: annotating and filtering the somatic mutations, and translating to obtain mutant peptide sequences of a patient; step S3: filtering the mutant peptide sequences to obtain neopeptide sequences based on a proteome of the normal sample; step S4, performing a human leukocyte antigen (HLA) typing analysis based on alignment data of the normal sample to obtain HLA genotypes of the sample; step S5, predicting binding affinities between the neopeptide sequences and the HLA genotypes to obtain specific neoantigens of the sample, and performing a weighted scoring on each of the specific neoantigens and calculating the TNB of the sample.

Abstract: A method and a platform for detecting an immunogenicity of a tumor neoantigen are provided. Specifically, the detection method includes the following steps: culturing human peripheral blood monocytes ex vivo for 13 days, adding an antigenic peptide fragment of human influenza virus and stimulating and activating cytokines, antigenic peptides, and immunoadjuvants during the 13 days, and finally conducting enzyme-linked immunospot (ELISPOT) chromogenic reaction and instrument-based scanning, counting, and analysis to detect the immunogenicity of tumor neoantigen. An application of the detection method and platform in biomedicine is provided. Compared with the prior art, the detection method and platform have advantages and characteristics of a short detection period, high convenience, low consumption of experimental cells, and low detection cost. Therefore, the detection method and platform can be used for ex vivo high-throughput assay for the immunogenicity of the tumor neoantigen.

Abstract: A method and a system for calculating tumor neoantigen burden (TNB) are provided. The method includes: step S1: processing a normal sample and a tumor sample, sequencing a specific region and detecting somatic mutations in the sample; step S2: annotating and filtering the somatic mutations, and translating to obtain mutant peptide sequences of a patient; step S3: filtering the mutant peptide sequences to obtain neopeptide sequences based on a proteome of the normal sample; step S4, performing a human leukocyte antigen (HLA) typing analysis based on alignment data of the normal sample to obtain HLA genotypes of the sample; step S5, predicting binding affinities between the neopeptide sequences and the HLA genotypes to obtain specific neoantigens of the sample, and performing a weighted scoring on each of the specific neoantigens and calculating the TNB of the sample.

Abstract: A deep learning-based method for predicting a binding affinity between human leukocyte antigens (HLAs) and peptides includes: step S101: encoding HLA sequences; step S102: constructing a sequence of an HLA-peptide pair; step S103: constructing an encoding matrix of the HLA-peptide pair; step S104: constructing an affinity prediction model for HLA-peptide binding. The new method considers the effects of the protein sequences of HLAs and the sequences of the peptides on affinity strength and develops a deep learning-based method for predicting a binding affinity between HLAs and peptides.

Abstract: A method is disclosed for integrating multi-omics data to extract a microsatellite instability (MSI)-based neoantigen for immunotherapy. The method includes the following steps: S1, integrating DNA and RNA sequencing data of a patient to detect the microsatellite instability (MSI) of the patient accurately; S2, translating open reading frames (ORFs) influenced by the detected MSI to acquire an MSI proteome; S3, mapping the MSI proteome against a normal human proteome to acquire a sample-specific proteome; and S4, acquiring a sample neoantigen. The new method reduces the rate of false positives in MSI detection, which is especially relevant for improving the efficacy of current clinical immunotherapy.

Abstract: A plasmid vector for expressing mRNA in vitro, a construction method and an application thereof are provided. The plasmid vector includes a poly(adenyl deoxyribonucleotide) (poly(dA)) fragment formed by more than 30 adenyl deoxyribonucleotides at the 3?-end tail of a gene to be inserted for expression. The plasmid vector for expressing mRNA in vitro in the present invention can express a target protein gene and a poly(A) formed by 60 adenyl ribonucleotides, and the expressed mRNA directly possesses the poly(A) without additional tailing operation. In addition, the mRNA transcribed in vitro shows stronger mRNA stability and higher protein expression ability after being transfected into cells.

Abstract: A delivery system for mRNA nucleic acid drugs, a preparation method and an application thereof are provided. The delivery system includes lipid nanoparticles for loading one or more kinds of mRNA molecules, wherein the lipid nanoparticles are prepared from raw materials including an ionizable cationic lipid, a phospholipid auxiliary lipid, cholesterol, and a polyethylene glycol-derivatized phospholipid. In the mRNA nucleic acid drug targeted intracellular delivery system based on the non-viral carrier of the present invention, the mRNA is concentrated and loaded by the electrostatic interaction between the ionizable cationic lipid and the mRNA. Phospholipid auxiliary lipid component-mediated pH sensitivity and late endosomal escape enable mRNA nucleic acid drugs to be efficiently delivered to target cells and then released into the cytoplasm of the target cells for exerting a pharmacodynamic effect.

Abstract: A method and system for extracting neoantigens for immunotherapy includes the following steps: step S1: acquiring conventional proteomes of tumor tissue and normal tissue samples; step S2: acquiring nucleotide polymer sequence libraries of the tumor tissue and normal tissue samples and a specific proteome of the tumor tissue sample; step S3: acquiring a plurality of candidate tumor-specific neoantigens based on the conventional and specific proteomes of the tumor tissue sample and molecular human leukocyte antigen (HLA) typing; and step S4: calculating the presence of the plurality of candidate tumor-specific neoantigens in the conventional proteomes and the nucleotide polymer sequence libraries of the tumor tissue and normal tissue samples, and acquiring tumor-specific neoantigens with a multiple of gene expression changes as a filter rule.

Abstract: A method and a platform for detecting an immunogenicity of a tumor neoantigen are provided. Specifically, the detection method includes the following steps: culturing human peripheral blood monocytes ex vivo for 13 days, adding an antigenic peptide fragment of human influenza virus and stimulating and activating cytokines, antigenic peptides, and immunoadjuvants during the 13 days, and finally conducting enzyme-linked immunospot (ELISPOT) chromogenic reaction and instrument-based scanning, counting, and analysis to detect the immunogenicity of tumor neoantigen. An application of the detection method and platform in biomedicine is provided. Compared with the prior art, the detection method and platform have advantages and characteristics of a short detection period, high convenience, low consumption of experimental cells, and low detection cost. Therefore, the detection method and platform can be used for ex vivo high-throughput assay for the immunogenicity of the tumor neoantigen.

Abstract: A tumor neoantigen prediction platform and an application thereof in a neoantigen vaccine development system are provided. The present invention selects 55 HLA-A and HLA-B subtypes with a high proportion of Chinese population from a common database, then establishes a method for constructing cell lines expressing associated HLA subtypes, and subsequently analyzes the resulting HLA subtype cell line binding proteomes by protein mass spectrometry at an attomolar (10?18 molar) level; through very high-precision mass spectrometry of protein profiling presented on the surface of a single cell, the present invention builds a high-frequency HLA-binding polypeptide database for Chinese population; subsequently, a tumor neoantigen prediction algorithm is optimized by a prediction platform including the HLA-binding polypeptide database, thereby significantly improving the tumor neoantigen prediction accuracy.

Abstract: Methods for treating, or reducing risk of development or progression of, a tissue-resident memory T cells (TRM)-mediated disease, comprising administering a therapeutically effective amount of one or more inhibitors of exogenous lipid and free fatty acid uptake or of mitochondrial beta oxidation of internalized exogenous FFA (e.g., inhibitors of CD36 and/or FABP antagonists, e.g., inhibitors of FABP4 and/or FABP5, and/or CPT1) to a subject in need thereof.