266 results about "Neo antigens" patented technology

The invention relates to the technical field of biological information, in particular to an immunoreaction evaluation method based on tumor neoantigen activity sorting. The method comprises the following steps: obtaining genome data of tumor and normal tissues through whole exon sequencing, extracting multi-dimensional features of candidate somatic mutation, and screening by combining a Gaussian mixture model and a Transform model to obtain a high-confidence mutation genome set; predicting the HLA genotype of a patient based on sequencing data, translating and mutating into a peptide fragment, predicting the binding affinity of the peptide fragment and an MHC molecule by using an XGBoost model, and calculating a new antigen activity score sequence in combination with various parameters; and finally, synthesizing a new antigen peptide fragment according to a sorting result, carrying out in-vitro co-culture to detect an IFN-gamma secretion result, and dynamically optimizing a characteristic combination coefficient through a PPO algorithm to realize intelligent iterative updating, so that the accuracy of new antigen screening and the immunoreaction prediction capability are remarkably improved.

The invention belongs to the field of biological medicine, and particularly relates to a mouse MC38 colorectal cancer neoantigen polypeptide and immunologic adjuvant composition and application of the mouse MC38 colorectal cancer neoantigen polypeptide and immunologic adjuvant composition in tumor treatment, and amino acid sequences of the neoantigen polypeptide are shown as SEQ ID No.2, 13, 16 and 17. Four tumor neoantigen polypeptides really having immunogenicity are obtained through screening, the obtained tumor neoantigens are compatible with PolyI: C to prepare the vaccine preparation, and after mice are treated by the MC38 tumor vaccine preparation, the growth of tumors can be effectively inhibited; and the survival time of the mouse is prolonged, and the new antigen vaccine preparation generates very effective T cell reaction in the tumor-bearing mouse body.

The present invention relates to bispecific antigen binding molecules specific for both the receptor tyrosine kinase-like orphan receptor 1 (ROR1) and the epidermal growth factor receptor (EGFR), as well as related fusion proteins and conjugates. In another aspect, the invention relates to conjugated immunoglobulin-like shark variable neoantigen receptors (VNARs).

Disclosed herein are chimpanzee adenoviral vectors that include neoantigen-encoding nucleic acid sequences derived from a tumor of a subject. Also disclosed are nucleotides, cells, and methods associated with the vectors including their use as vaccines.

The present invention relates to methods for predicting whether peptides or polypeptides comprising disease specific amino acid modifications, in particular tumor-associated neo-antigens, comprise epitopes, in particular tumor-associated neo-epitopes, which are useful for immunotherapy such as for vaccination. The methods of the invention may be used, in particular, for the provision of vaccines which are specific for a patient's tumor and, thus, in the context of personalized cancer vaccines.

Drug delivery nanoparticle compositions and methods for the treatment of a cancer are provided that can be used individually or in combination. These compositions and methods include: (1) exogenous vaccination using neoantigens or tumor-associated antigens to potentiate an anti-tumor immune response; (2) nanoparticle-based drug delivery targeting the liver, aimed at reprogramming the hepatic immune environment to reduce or eliminate tumor antigen tolerance, thereby enhancing the immune system's ability to combat metastatic cancer; and (3) expansion of the liver metastasis treatment platform to target tumor-associated lymphoid structures, supporting the immune response at the primary tumor site. Any of these methods may be optionally combined with chemo-immunotherapy for enhanced efficacy.

The invention belongs to the technical field of biomedicine, and particularly relates to tumor neoantigen polypeptide based on EGFR gene mutation and application of the tumor neoantigen polypeptide. According to the effective method for predicting and screening the tumor neoantigen by using the tumor neoantigen prediction platform, the specific mutation of tumor tissues is obtained, and the neoantigen polypeptide with high immunogenicity, high affinity and high activation effect is more accurately predicted; the screened new antigen polypeptide makes up the blank of individualized antigen peptide in treatment of lung cancer NSCLC patients with EGFR-L858R somatic mutation, can be synthesized in a large scale, is used for subsequent standardized and individualized immunotherapy of EGFR-L858R mutation tumor patients, and has a good clinical application prospect.

An antigen peptide is provided specifically for treating individuals suffering from ovarian cancer, preferably based on BRCA1 gene c. 5470_5477del8 mutation. It is selected from amino acid sequences of SEQ ID NO. 1 to SEQ ID NO. 6, or derived by substitution, deletion and / or addition of at least one amino acid. The neoantigen polypeptides of the present disclosure can significantly activate T lymphocytes specific to the BRCA1 gene c. 5470_5477del8 mutation in vitro, stimulating the release of the cytokine IFN-y, indicating notable immunogenicity. This enhances T lymphocytes' ability to target and kill cancer cells from ovarian cancer patients carrying the BRCA1 gene c. 5470_5477del8 mutation. Additionally, the antigen peptide can activate and expand human T lymphocytes specific to the BRCA1 gene c. 5470_5477del8 mutation in vitro for adoptive cell therapy. The antigen peptide of the present disclosure addresses the gap in personalized antigen peptide therapies for ovarian cancer patients with BRCAl-c. 5470_5477del8 somatic mutations.

The invention provides a new antigen immunogenicity prediction method and system based on multi-feature fusion, and belongs to the technical field of machine learning, and the method comprises the steps: inputting a candidate peptide fragment sequence into an antigen intracellular processing prediction model to obtain a score representing the intracellular processing capability; inputting the candidate peptide fragment sequence into a pre-trained Transform model to obtain a sequence vector representation of the candidate peptide fragment; training an immunogenicity prediction model by taking the immunogenicity related characteristics, the sequence vector representation of the candidate peptide fragment and the score representing the intracellular processing capacity as a training sample; and screening the target candidate peptide fragment sequence by using the immunogenicity prediction model to obtain the tumor neoantigen. According to the method, the scoring model special for evaluating the intracellular processing and presentation capacity of the antigen peptide is constructed, the scoring model is output as a key feature, efficient fusion and learning are carried out on the key feature, multiple immunogenicity-related biological features and sequence vector representation of candidate peptide fragments, and the accuracy and reliability of tumor neoantigen immunogenicity prediction can be remarkably improved.

The invention relates to the field of intelligent medical treatment, in particular to a new antigen screening method, equipment and a program product. Comprising the following steps: S1, acquiring tumor slice data and serum data of a patient; s2, performing data processing on the tumor slice data and the serum data to obtain an HLA / MHC pseudo sequence, antigen peptide data and an antigen gene expression level; the data processing comprises data sequencing, HLA / MHC typing, somatic mutation calculation, fusion gene calculation and gene expression profile calculation; s3, screening new antigens based on the HLA / MHC pseudo sequence, the antigen peptide data and the antigen gene expression level data to obtain the new antigens, the application can perform new antigen screening, and has good clinical value.

The invention discloses an HLA and antigen peptide combination prediction method based on interactive attention, and belongs to the technical field of computational biology. The method comprises the following steps: 1, collecting HLA allele and unique peptide fragment data, and constructing an HLA and antigen peptide binding data set; 2, constructing an HLA and antigen peptide binding prediction model, and training the prediction model by using the HLA and antigen peptide binding data set to obtain a trained prediction model; and step 3, inputting the HLA sequence and the antigen peptide sequence into the prediction model to obtain a prediction result of combination of the HLA and the antigen peptide. According to the method, prediction tasks based on a sequence and a structure are integrated into a unified model, and the potential of the pHLA about the sequence and the structure is analyzed and predicted. Compared with an existing method, the two-dimensional evaluation provides a more comprehensive antigen immunogenicity view angle, and a new insight is provided for the quality of a new antigen for triggering an immunoreaction.

The present disclosure provides compositions and methods for targeting neoantigens, for example, to treat or prevent cancer. The disclosed embodiments include binding proteins, such as T cell receptors, that bind to the neoantigen: HLA complex. The binding protein further comprises a construct comprising a fusion protein of the CD95 extracellular domain and the CD137 intracellular signaling domain (Fas-41BB), and a CDS coreceptor alpha or beta chain. The disclosed binding proteins are highly sensitive to antigens and are capable of inducing activation of host T cells at low concentrations of peptide antigens. In certain embodiments, binding proteins of the present disclosure (i) have no alloreactivity, substantially no alloreactivity, and / or low risk of alloreactivity, to amino acid sequences from human proteomes and / or (ii) to human HLA alleles. Polynucleotides encoding such binding proteins can be introduced into host cells, such as T cells, and the cells can be used in immunotherapy for the treatment of various cancers.

The invention relates to the technical field of bioinformatics, and discloses a method, a system, equipment and a medium for searching for base mutation aiming at third-generation full-length transcript sequencing data, the base mutation is accurately positioned to a specific transcript by directly processing the third-generation full-length transcript sequencing data, and the method and the system for searching for the base mutation aiming at the third-generation full-length transcript sequencing data are provided. The co-occurrence relation of a plurality of mutations on the same transcript is accurately analyzed, and the defects of calculation redundancy, function misjudgment and the like caused by the fact that a mutation transcript source cannot be determined due to fragmentation splicing and the co-occurrence is simulated by depending on permutation and combination in a second-generation short-read-long sequencing technology are effectively overcome; the recall rate of transcripts which are not mapped due to a high-variation region is improved through mapping correction assisted by structural variation, and false positive is effectively inhibited through a multi-dimensional filtering condition, so that the sensitivity and reliability of mutation detection are remarkably improved; particularly, mutation events with function remodeling due to reading frame change can be accurately recognized in scenes such as neoantigen prediction where mutation function consequences need to be accurately evaluated, and the method has important value in application in the fields of precision medical treatment and the like.

The present disclosure provides compositions and methods for targeting a Ras antigen to, for example, treat or prevent cancer. Disclosed embodiments include binding proteins, such as a T cell receptor or a chimeric antigen receptor, that bind to a Ras antigen:HLA complex. Polynucleotides encoding such binding protein can introduced into a host cell, such as a T cell, and the cell can be used in immunotherapy for treating various cancers. Also provided are immunogenic polypeptides that can be useful to, for example, induce an immune response against a mutated Ras or to identify a binding protein that binds to a Ras antigen.

Systems and methods for determining the likely responsiveness of a human cancer subject to a checkpoint blockade immunotherapy regimen are provided. Sequencing reads are obtained from samples from the subject representative of the cancer. A human leukocyte antigen type and a plurality of clones is determined from the sequencing reads. For each clone, an initial frequency Xα in the one or more samples is determined and a corresponding clone fitness score of the clone is computed, thereby computing clone fitness scores. Each such fitness score is computed by identifying neoantigens in the respective clone, computing a recognition potential for each neoantigen, and determining the corresponding clone fitness score of the respective clone as an aggregate of these recognition potentials. A total fitness, quantifying the likely responsiveness of the subject to the regimen, is computed by summing the clone fitness scores across the plurality of clones.

The present invention relates to methods for predicting T cell epitopes. In particular, the present invention relates to methods for predicting whether a modification in a peptide or polypeptide, such as a tumor-associated neoantigen, is immunogenic. The methods of the present invention are particularly suitable for providing a vaccine specific to a patient's tumor and, therefore, are suitable for use in the context of personalized cancer vaccines.

The present disclosure provides methods of determining whether a tumour-specific mutation is likely to be clonal in a subject. The method comprise determining, by a processor, a metric indicative of the probability that the mutation is clonal by combining evidence from sequence data obtained from the subject and an indication of whether the mutation is associated with one or more predetermined mutational signatures. The methods may be used to identify clonal mutations and clonal neoantigens in a subject, and to design immunotherapies that target clonal neoantigens. Related methods, systems and products are also described.

The invention relates to the technical field of tumor vaccines, and provides a novel mRNA (messenger Ribonucleic Acid) tumor vaccine for treating mouse liver cancer, which is prepared by the following steps: S1, specific neoantigen prediction: carrying out bioinformatics analysis on a next-generation sequencing database of tumor patients in the hospital, and selecting tumor specific neoantigens through the following steps; s11, low-quality readings are removed through a filtering step; s12, detecting single nucleotide variation by using a Mutect method and a VarScan method; s13, annotating missense mutation by using ANNOVAR software; in-vivo and in-vitro experiments prove that the vaccine has a remarkable anti-tumor effect, is designed and synthesized aiming at a newly screened new antigen mutation sequence and has high specificity and pertinence, and experimental results show that the vaccine can remarkably improve immune response of specific CTLs cells, induce T cell response of new antigen specificity, and has a good anti-tumor effect in a tumor-bearing mouse model. The vaccine has a remarkable inhibiting effect on tumor growth, and the problems in the prior art are solved through the technical scheme.

The invention relates to a tumor neoantigen prediction method and a tumor neoantigen prediction system. The method comprises the following steps: acquiring a plurality of amino acid sequences in a gene of a person to be tested as a plurality of test peptides to be compared with a plurality of human protein sequences in a protein sequence database so as to find out a plurality of similar peptides matched with the human protein sequences; filtering similar peptides from the test peptides, and respectively inputting the filtered test peptides into a plurality of trained human leukocyte antigen models to obtain a plurality of sequencing results of the test peptides; calculating the weighted sum of the sequencing of each test peptide in the sequencing result as the score of the test peptide; and selecting at least one of the test peptides as a neoantigen suitable for the subject according to the fraction.

A system and corresponding method are provided for identifying a subpopulation of cancer patients who are immunotherapy respondents using a more effective method of assessing neoantigen presentation. Such a method will also enable the creation of more effective therapies, such as vaccines, based on presented neoantigens.

The invention discloses a preparation method of infiltrating lymphocytes with high proportion of neoantigen reactive T cells. The proportion of the reactive T cells with tumor neoantigen specificity can be increased without using a gene editing technology. In the TIL cell culture process, DC presents tumor neoantigen and TIL is sorted and cultured, the proportion of T cells with neoantigen reactivity in TIL is increased, the anti-tumor activity of the TIL cell preparation is enhanced, then the prepared infiltrated lymphocytes are rapidly and massively amplified, and the TIL cell preparation has the advantages that the tumor neoantigen reactivity is improved. And batch preparation of the neoantigen reactive TIL cell preparation with high reactivity to tumors is facilitated.

Disclosed herein are methods of treating an individual at risk for incidence or recurrence of cancer in need thereof. Methods can include the steps of identifying an individual at risk for incidence or recurrence of cancer based on a risk stratification parameter; analyzing a biological sample from using a multi-cancer detection (MCD) test to yield an MCD test result; and based on the MCD test result and optionally the risk stratification parameter, administering a neoantigen immunogenic composition to the individual in need thereof. Methods can include the steps of sequencing and analyzing of the biological sample from the individual or a new biological sample from the individual to identify neoantigens to be included in the neoantigen immunogenic composition; and analyzing a second biological sample from the individual at risk for incidence or recurrence of cancer using a second multi-cancer detection (MCD) test to determine efficacy of the neoantigen immunogenic composition.

Cancer immunology provides promising new avenues for cancer treatment but validation of potential neoantigens to target is costly and expensive. Analysis of MHC binding affinity, antigen processing, similarity to known antigens, predicted expression levels (as mRNA or proteins), self-similarity, and mutant allele frequency, provides screening method to identify and prioritize candidate neoantigens using sequencing data. Methods of the invention thereby save time and money by identifying the priority candidate neoantigens for further experimental validation.

Disclosed herein are methods of scoring predicted immunogenicity of neoantigens from biological samples of a subject. Methods can include the steps of preparing biological samples for nucleic acid sequencing; nucleic acid sequencing; evaluating the initial sequencing results by analyzing (e.g., comparing) sequencing parameters of the results; based on an analysis (e.g., a comparison) of sequencing parameters, combining the initial sequencing results to yield union sequencing results or selecting a representative biological sample; and scoring the predicted immunogenicity of neoantigens in the biological samples based on either the union sequencing results or the sequencing results of the representative sample. Methods can further include the step of comparing sequencing parameters of union sequencing results and the initial sequencing results. Methods can further include the steps of generating a neoantigen vaccine that contains or encodes for a neoantigen scored for predicted immunogenicity and administering the neoantigen vaccine to a subject.

The present disclosure provides methods for producing engineered immune cells, engineered immune cell populations, and methods of using the engineered immune cells for treating subjects with cancer and other conditions. The engineered immune cells provided herein can comprise antigen-specific T cells (e.g., neoantigen-specific T cells), TCR-T cells, or CAR-T cells. The engineered immune cells prepared by the methods provided herein can exhibit beneficial phenotypes, such as increased persistence, increased effector function, increased activation function, and / or lower dysfunction.

The invention discloses a tumor neoantigen accurate analysis method and system based on multi-dimensional evidence chain scoring, and relates to the cross technical field of bioinformatics, computational biology and tumor immunology, and the system comprises a multi-dimensional evidence chain scoring module which is used for evaluating the feasibility score of candidate neoantigens; the antigen extraction and verification module is used for identifying and verifying a tumor specific antigen according to the feasible degree score; the anchoring site identification and prediction module is used for scoring the amino acid of each site by using an amino acid frequency weighted BLOSUM62 coded value, obtaining a specific anchoring site and an anchoring site amino acid residue restriction set, and judging whether a certain peptide fragment is a non-binding peptide or not according to the specific anchoring site and the anchoring site amino acid residue restriction set so as to obtain a judgment result; the intelligent MHC retrieval module is used for enabling a user to input a character string at the front end according to the judgment result to conduct intelligent retrieval so as to obtain a retrieval result, and high-precision recognition and evaluation of the tumor neoantigen are achieved.

The present invention relates to methods for predicting whether peptides or polypeptides comprising disease specific amino acid modifications, in particular tumor-associated neo-antigens, comprise epitopes, in particular tumor-associated neo-epitopes, which are useful for immunotherapy such as for vaccination. The methods of the invention may be used, in particular, for the provision of vaccines which are specific for a patient's tumor and, thus, in the context of personalized cancer vaccines.

Indivi dualized neoantigen vaccines, as well as methods for their use in subjects to treat urothelial orbladder cancer are provided. In some embodiments, individualized neoantigen vaccines are used with an immune checkpoint inhibitor and optionally enfortumab vedotin to treat a urothelial or bladder cancer after surgical resection. Prior to surgical resection, in some embodiments, the subject is administered a neoadjuvant therapy comprising an immune checkpoint inhibitor, individualized neoantigen vaccines, and, optionally, enfortumab vedotin.