137 results about "Neo antigens" patented technology

The present invention relates to neoplasia vaccine or immunogenic composition administered in combination with other agents, such as checkpoint blockade inhibitors for the treatment or prevention of neoplasia in a subject.

Disclosed herein in one aspect is a pharmaceutical composition comprising a plurality of neoantigenic peptides and a pharmaceutically acceptable carrier, each neoantigenic peptide comprising a tumor-specific neoepitope capable of binding to an HLA protein in a subject, each tumor-specific neoepitope comprising a tumor-specific mutation present in a tumor, wherein (a) the composition comprises neoantigenic peptides comprising tumor-specific mutations present in at least 1% of subjects in a population of subjects suffering from cancer; (b) the composition comprises neoantigenic peptides comprising tumor-specific neoepitopes which bind to HLA proteins present in at least 5% of subjects in the population; and (c) the composition comprises at least one neoantigenic peptide capable of eliciting an immune response against a tumor present in at least 5% of the subjects in the population of subjects suffering from cancer.

The present invention relates to methods for predicting T cell epitopes. In particular, the present invention relates to methods for predicting whether modifications in peptides or polypeptides such as tumor-associated neoantigens are immunogenic or not. The methods of the invention are useful, in particular, for the provision of vaccines which are specific for a patient's tumor and, thus, in the context of personalized cancer vaccines.

Disclosed herein is a system and methods for determining the alleles, neoantigens, and vaccine composition as determined on the basis of an individual's tumor mutations. Also disclosed are systems andmethods for obtaining high quality sequencing data from a tumor. Further, described herein are systems and methods for identifying somatic changes in polymorphic genome data. Finally, described herein are unique cancer vaccines.

The present invention relates to polymers associated with (e.g., complexed, conjugated, encapsulated, absorbed, adsorbed, admixed) bio macromolecule agents (e.g., peptides, neo-antigens, adjuvant molecules, nucleic acids, etc.) configured for treating, preventing or ameliorating various types of disorders, and methods of synthesizing the same. In particular, the present invention is directed to compositions comprising polymer moieties (e.g., poly(L-glutamic acid moieties)) associated with biomacromolecule agents, methods for synthesizing such polymer conjugates, as well as systems and methods utilizing such polymer conjugates.

The present invention is concerned with a novel antigens associated with human tumors, including carcinomas of the colon or lung, as well as novel monoclonal antibodies which specifically bind to said antigen. The antibodies bind to normal human cells to a much lesser degree than to tumor cells. The antigens include 100 kDa glycoprotein that has a colorectal cancer membrane bound and a soluble form, has a UV absorbance peak at about 228 nm, an isoelectric point of about 3.5 to 4, a sialic acid content of about 20%, and does not substantially bind to an antibody specific for ACT. The antibodies find use both in methods such as the detection of malignant cells associated with tumors and in monitoring therapeutic treatment of humans with tumors.

Disclosed are methods of isolating paired T cell receptor (TCR) alpha and beta chain sequences, or an antigen-binding portion thereof. Also disclosed are methods of automatically identifying the TCR alpha and beta chain V segment sequences and CDR3 sequences of a TCR having antigenic specificity for a mutated amino acid sequence encoded by a cancer-specific mutation. Methods of preparing a population of cells that express paired TCR alpha and beta chain sequences, or an antigen-binding portion thereof, are also disclosed. Isolated pairs of TCR alpha and beta chain sequences and isolated populations of cells prepared by the methods are also disclosed.

Mutant epitopes encoded by cancer genes are virtually always located in the interior of cells, making them invisible to conventional antibodies. We generated single chain variable fragments (scFvs) specific for mutant peptides presented on the cell surface by human leukocyte antigen (HLA) molecules. These scFvs can be converted to full-length antibodies, termed MANAbodies, targeting “Mutation Associated Neo-Antigens” bound to HLA. A phage display library representing a highly diverse array of single-chain variable fragment sequences was first designed and constructed. A competitive selection protocol was then used to identify clones specific for peptides bound to pre-defined HLA types. In this way, we obtained scFvs, including one specific for a peptide encoded by a common KRAS mutant and another by a common EGFR mutant. Molecules targeting MANA can be developed that specifically react with mutant peptide-HLA complexes even when these peptides differ by only one amino acid from the normal, wild-type form.

The invention discloses a method and a system for selecting an individualized tumor neoantigen based on an expected curative effect. The method comprises the following steps: establishing and optimizing a cell selectivity model; establishing and optimizing a treatment effect model, carrying out auxiliary selection on individualized tumor neoantigens and the like, and can maximize the utilization of biological experiments to carry out trial and error, establish the most accurate cell selectivity model and maximize the utilization of the biological experiments to improve the effect on individual patients under the condition of not involving the patients; the method further considers the correlation between the selectivity of new antigen cells and the immune state of patients, builds a complete curative effect prediction model, evaluates the applicability of a specific new antigen to a specific patient according to an actual curative effect, provides high-value reference information for a doctor to select an appropriate new antigen for immunotherapy, utilizes the actual effect feedback of doctor treatment to the maximum extent, and continuously improves the prediction precision of the overall effectiveness of new antigen immunotherapy.

The present systems and workflows identify neoantigens for cancer immunotherapy by introducing deep learning to de novo peptide sequencing from tandem mass spectrometry data. The systems and workflow allows for patient specific identification of neoantigens for personalized immunotherapy.

A method for identifying neoantigens that are likely to be presented on a surface of tumor cells of a subject. Peptide sequences of tumor neoantigens are obtained by sequencing the tumor cells of thesubject. The peptide sequence of each of the neoantigens is associated with one or more k-mer blocks of a plurality of k-mer blocks of the nucleotide sequencing data of the subject; The peptide sequences and the associated k-mer blocks are input into a machine- learned presentation model to generate presentation likelihoods for the tumor neoantigens, each presentation likelihood representing the likelihood that a neoantigen is presented by an MHC allele on the surfaces of the tumor cells of the subject. A subset of the neoantigens is selected based on the presentation likelihoods.

Methods for personalized neoantigen or neoepitope selection for a patient having cancer, whereby the patient can be treated in a personalized manner using a patient-specific cocktail of suitable neoantigen or neoepitope peptides and a pharmaceutically acceptable excipient, wherein the selection of suitable neoantigens or neoepitopes is based on properties of the patient-specific neoantigens or neoepitopes which are predicted or evaluated based on information derived from databases which in turn are derived from prior measurements and observations, and wherein the method reduces the influence of any errors in the underlying databases by binning certain descriptors of neoantigen or neoepitope properties and by improved ranking of the neonantigens or neoepitopes according to the binning of the descriptors; and pharmaceutical preparations selected by said methods, and data carriers and kits for carrying out said methods.

Disclosed herein are alphavirus 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 invention provides an immunocyte medicine containing a B cell vaccine (neoB) loaded with a tumor new antigen, and a medicine combination for united use of neoB and tumor specificity T cells. The neoB vaccine can have higher ex vivo expansion properties than a DC vaccine, has higher effect of continuous activating of in vivo T cells under the condition of repeated infusion, and can become a preventive or therapeutic vaccine or an immunocyte medicine to be applied to tumor resisting treatment suitable for any cancer kind. According to the medicine combination for united use of neoB and tumor specificity T cells, disclosed by the invention, the neoB can be used for further stimulating the tumor specificity T cells in bodies, so that the number of the tumor specificity T cells in bodies can be amplified, and the treatment effect is increased.

The invention discloses a method and a device for extracting a gene fusion immune treatment neoantigen by integrating deep sequencing data of DNA and RNA. The method comprises the following steps: S10, acquiring a genome gene fusion sequence of a sample; S20, acquiring a transcriptome gene fusion sequence of the sample; S30, constructing a gene fusion proteome; and S40, obtaining a sample neoantigen. The tumor specific neoantigens discovered by the scheme of the invention are all from gene fusion, so that the screening range of the neoantigens is expanded, and an ammunition library of an immune treatment method based on the neoantigens is enriched. Through analysis and integration of tumor sample whole exome sequencing data and transcriptome sequencing data, gene fusion events in tumor tissues are comprehensively detected, the false positive rate of neoantigens generated by fusion is reduced, the effectiveness of neoantigen vaccine is improved, and the method is of great significance to improvement of the clinical immune treatment effect.

The present disclosure relates to immune cells that express an exogenous neoantigen and an immunogenicity enhancer, or to T cells that express an exogenous neoantigen, and their use in treating a disease or disorder, such as cancer for tumor associated neoantigens. Related expression constructs, kits, host cells, pharmaceutical compositions, and methods are also provided.

The invention relates to a tumor neoantigen prediction method and prediction device based on chromatin high-level conformation and deep sparse learning, and a storage medium, and the method comprisesthe steps: building a deep neural network prediction model based on group selection, and carrying out the training of the model through training data to obtain an immunogenicity predicted value of a to-be-predicted object (namely, a potential tumor neoantigen peptide), wherein each sample adopted when the deep neural network prediction model is trained comprises chromatin 3D conformation information and features generated based on a polypeptide amino acid sequence. Compared with the prior art, the method has the advantages of high prediction precision, convenience in prediction and the like.