27 results about "Immunophenotyping" patented technology

Described herein are methods, systems, and programming for determining a tumor immunophenotype of an image of a tumor. Some embodiments include dividing an image into tiles depicting tumor epithelium and / or tumor stroma. For each tile, an epithelium-immune cell density and a stroma-immune cell density may be calculated based on a number of immune cells identified in the tumor epithelium and the tumor stroma, respectively. Based on the epithelium-immune cell density and the stroma-immune cell density, an inflammation type of the type may be determined, and a tumor immunophenotype may be determined based on each tile's inflammation type.

Compositions and methods for treating inflammation associated with Farber disease in a subject in need thereof by administering to the subject a pharmaceutical composition comprising a recombinant human acid ceramidase in a therapeutically effective amount of about 0.1 mg / kg to about 50 mg / kg to inhibit inflammation and / or to inhibit or reduce pro-inflammatory potential of neutrophils and / or monocytes in the subject.

Provided relates to the field of cytometry, specifically to flow cytometric methods and kits for improved diagnosis, prognosis and monitoring of tumors and other lesions involving immune cell infiltration. Further provided are embodiments of the subject matter which relate to compositions and methods providing high resolution quantitative means for immunophenotyping and immune modeling, and for identification of disease prognostic and therapy predictive biomarkers.

The invention relates to an acute leukemia (ALL) high-throughput flow cytometry kit, and belongs to the field of leukemia detection.16 ALL cell antigens are added on the basis of an original 8-color flow cytometry, 24 antigens in the same cell can be detected at the same time, the detection precision of minimal residual focus (MRD) is greatly improved, and the detection sensitivity is improved. The ALL cells are divided into 12 developmental stages, so that immunological typing during primary diagnosis and immunophenotype variation after bone marrow transplantation and CAR-T cell treatment can be more accurately recognized, and the method has very important guiding significance on evaluation of treatment effects of patients and adjustment of treatment schemes.

Method and systems for sorting potential hematopoietic stem cell transplant (HSCT) donors as a donor or non-donor using immunophenotyping of blood samples. The methods and systems can be used to identify a donor for a HSCT or to choose a donor to generate a HSCT blood product that is not likely to result in bad outcomes for a recipient. Also provided herein are methods and systems for training machine learning models that can be used in methods and systems for sorting potential HSCT donors.

Monitoring active disease or progressive disease under therapy in chronic lymphocytic leukemia (CLL) represents a challenge to earlier and better adapt therapeutic strategy, notably in the era of targeted therapies in which minimal residual detection or mutations are sometimes not associated to poor clinical outcome. By following CLL patients before treatment (Binet stages A and B / C) or during targeted therapy, the Inventors developed a new flow cytometric method, based on CD69, CD49d, CD20 and CD279 expression at the surface of CD19+ / CD5+ B leukemic cells. Analyses of these markers alone or in combination show that CD69 / CD49d / CD20 / CD279 co-expression (quadruple population, QP) > 0.5% is the best criterion predicting CLL active disease or progression under therapy. This new flow cytometry immunophenotyping could help clinicians to monitor CLL evolution and quickly adapt their therapeutic strategy. Accordingly, the present invention relates to an ex vivo method for predicting active Chronic Lymphocytic Leukemia (CLL) or progressive CLL under therapy in a subject suffering from CLL, comprising the step of quantifying a population of CD69+ / CD49d+ / CD20+ / CD279+ cells in a sample obtained from the subject.

The application provides a bladder cancer immunophenotyping recognition method and system, comprising: preprocessing pathological image data to obtain preprocessed pathological image data; constructing a tumor and stroma region segmentation model based on a semantic segmentation network TransUNet, training the tumor and stroma region segmentation model using the preprocessed pathological image data and label data, and obtaining a trained tumor and stroma region segmentation model; constructing a TIL recognition neural network model classification model based on Resnet50 using a tumor and stroma segmentation result output by the trained tumor and stroma region segmentation model; and obtaining a bladder cancer immunophenotyping result based on a lymphocyte infiltration score output by the TIL recognition neural network model classification model. The application automatically recognizes a tumor region and immune cell distribution using digital pathological images, constructs a standardized immunoscore and typing method, and improves the individual decision-making ability of clinical immunotherapy.

The invention relates to a method for predicting the evolution of an immune response in a subject towards an effector or suppressor response, based on cellular plasticity determined by the cytokine milieu generated after antigenic stimulation. The invention also allows for evaluating the generation of antigen-specific memory regulatory T cells in the evolution of the immune response. The invention also relates to a kit for carrying out the method according to the invention.

[0006] Methods and systems for generating an immune profile for a subject are described. Optionally, the methods include contacting at least a first aliquot of a sample from the subject with at least a first immunophenotyping panel to fluorescently label cells contained in the sample; processing the fluorescently labeled cells using a full-spectrum flow cytometer to generate fluorescence intensity data or derived data for the fluorescently labeled cells from the sample; providing at least a subset of the fluorescence intensity data or derived data for the fluorescently labeled cells as input to an ensemble machine learning model configured to process the data and classify individual cells as belonging to one of a plurality of distinct immune cell subpopulations; and outputting a total cell number or cell frequency for each of a plurality of distinct immune cell subpopulations in the sample as part of the immune profile for the subject.

A microfluidic device for particle analysis, such as immunophenotyping, includes a plurality of microfluidic channels for the passage of a particle-laden fluid flow, a plurality of dedicated impedance sensors for generating impedance signals relative to each microfluidic sensor. The impedance sensors are CODES Coulter sensors, each having a distinct coded sequence for generating mutually orthogonal signals. The system uses a multi-frequency excitation signal for driving the Coulter sensors, such that the Coulter sensors generate multi-frequency impedance signals. The system outputs the multi-frequency signals of the plurality of impedance sensors as a single multi-frequency multiplexed signal, which is subsequently separated into a plurality of single-frequency multiplexed signals, which are then demodulated into single-frequency component signals corresponding to each of the Coulter sensors.

The invention relates to the technical field of prostate cancer treatment, in particular to an individualized precise treatment method for advanced prostate cancer, which comprises the following steps: S1, performing biopsy, namely pathological and immunohistochemical detection, on CRPC patients, and performing next-generation sequencing, namely sequencing of oncogene exon mutation sites; s2, determining whether the converted immunophenotype is a CRPC-Adeno adenocarcinoma type or a CRPC-NEPC neuroendocrine type, and respectively determining whether gene mutation exists or not; s3, carrying out standard treatment if no gene mutation exists, matching a corresponding targeted drug if gene mutation exists, and giving an individualized targeted drug scheme; s4, constructing a miniPDX model, namely a function prediction model for accurate treatment of CRPC prostate cancer, and efficiently modeling and rapidly testing drug efficacy through capsule implantation; s5, mainly recording the PFS, and secondarily recording the relationship between the OS and different drug resistance mechanisms and the OS of the patient. The detection technology is simple and convenient, the clinical application popularity is relatively high, the miniPDX model can be used for efficiently modeling and rapidly testing the drug efficacy, and the application value of the miniPDX model in personalized cancer treatment is powerfully enhanced.

A cancer vaccine technology is provided which knocks out expression of cell surface immune checkpoint proteins, to facilitate their processing by immune cells, and optionally by knocking-in the expression of cytokines to boost immune response. Non-replicating tumor cells lacking cell surface CD47 are highly effective immunizing agents against subcutaneous mouse melanoma. Whole-cell vaccines inhibited tumor growth, and immunophenotyping showed a dramatic increase in activated effector cell subsets and M1-type macrophages aided by a significant reduction in the tumor-associated macrophage and myeloid derived suppressor cell compartments. A remarkable downregulation of cell surface CD47 was observed in the tumors that did escape after vaccination with genetically modified cells, suggesting the intricate involvement of CD47 in a prophylactic situation. An effective vaccination strategy to increase tumor-specific immune response in solid tumors is provided to improve the outcome of cancer immunotherapy.

Provided herein are compositions comprising protein encapsulated nanoparticles, and methods of making said compositions. In an aspect, provided herein are compositions comprising cytokine encapsulated nanoparticles, and methods of making said compositions. Further provided herein are methods of monitoring an immunophenotype of a subject and associated immunodiagnostic assays and immunodiagnostic compositions.

The present application relates to a kind of acute leukemia (ALL) high flux flow detection kit, belong to leukemia detection field, the present application is based on the original 8 color flow to increase 16 kinds of ALL cell antigen, can realize the simultaneous detection of 24 kinds of antigens in the same cell, not only greatly improve the detection precision of micro residual lesion (MRD), and by being divided into 12 development stages to ALL cell, can more accurately identify immunotyping when first diagnosis, and immunophenotypic aberration after bone marrow transplantation and after CAR-T cell therapy, this has very important guiding significance to the evaluation of patient treatment effect and the adjustment of treatment scheme.

The invention discloses an antibody combination for detecting minimal residual disease and application thereof. The antibody combination comprises a CD45 antibody, a CD19 antibody, a CD33 antibody, a CD10 antibody, a CD20 antibody, a CD38 antibody, a CD34 antibody, a CD58 antibody, a CD66c antibody, a CD73 antibody, a CD81 antibody, a CD123 antibody and a CD304 antibody. A specific antibody combination for detecting the minimal residual disease is designed, a specific gate setting strategy is combined, 13-color flow analysis is realized, and target cells can be accurately locked and normal cells and differential cells can be effectively distinguished by combining composition and development process analysis of CD19 + cells and leukemia cell related immunophenotype (LAIP) analysis; the detection rate, the accuracy and the sensitivity are obviously improved.

This application discloses a combination of gene markers for predicting ovarian cancer prognosis, immunotherapy response, or immunophenotype, and their applications, belonging to the field of molecular diagnostic technology for ovarian cancer. The combination of gene markers includes... MMP1 , GJB2 , PLPP4 , MME , GREM1 , COL10A1 , CTHRC1 , CEMIP , MMP11 and NTM The combination of gene markers presented in this application can not only predict the prognostic risk of ovarian cancer, but also predict the immunotherapy response and immunophenotype of ovarian cancer samples, with excellent performance.

The present invention relates to a reagent panels for the measurement of minimal residual disease (MRD) associated with pediatric B-cell precursor acute lymphoblastic leukemia (B- ALL) by multiparametric flow cytometry. The reagent panel of the invention comprises a combination of antibodies directed against markers, wherein the combination of antibodies comprises i) antibodies targeting markers CD45, CD20, CD34, CD38, CD10, CD58, CD66c, CD73, CD81, CD123, CD304, CD44, CD86, CD99 and CD371, and ii) antibodies targeting markers CD19 and / or CD22, wherein the antibodies are conjugated with fluorochromes. The invention further relates to the use of said panels for detecting MRD associated with B-ALL and / or for identifying a subject at risk of developing B-ALL relapse. The invention also relates to methods of detecting MRD associated with B-ALL. Key advantages of the invention include achieving high MRD detection sensitivity (e.g., 10⁻⁵ or 0.001%) and high specificity.

The invention provides a system for predicting the curative effect of '3 + 7' induced chemotherapy of an acute myelogenous leukemia patient and application of the system, and belongs to the technical field of biomedicine. The system comprises a data acquisition module, a prediction module and a prediction result acquisition module, and is used for predicting the curative effect of induced chemotherapy based on the change of the peripheral blood leukemia immunophenotype cell count: compared with the prior art, the peripheral blood leukemia immunophenotype cell count is reduced by more than or equal to 1.5 log on the fourth day of induced chemotherapy; obtaining a result that the patient is sensitive to induced chemotherapy; compared with the induction chemotherapy, the number of the peripheral blood leukemia immunophenotype cells is reduced by less than 1.5 log on the fourth day of the induction chemotherapy, and the result that the patient is insensitive to the induction chemotherapy is obtained. The invention further provides a kit, computer equipment, a computer readable storage medium and a computer program product based on the system, patients sensitive and insensitive to induced chemotherapy can be effectively recognized, and accurate treatment guidance is provided for clinic.

Method and systems for sorting potential hematopoietic stem cell transplant (HSCT) donors as a donor or non-donor using immunophenotyping of blood samples. The methods and systems can be used to identify a donor for a HSCT or to choose a donor to generate a HSCT blood product that is not likely to result in bad outcomes for a recipient. Also provided herein are methods and systems for training machine learning models that can be used in methods and systems for sorting potential HSCT donors.

Disclosed herein are methods for treating a cancer comprising: a. administering a Btk inhibitor to a subject sufficient to result in an increase or appearance in the blood of a subpopulation of lymphocytes defined by immunophenotyping; b. determining the expression profile of one or more biomarkers from one or more subpopulation of lymphocytes; and c. administering a second agent based on the determined expression profile.

Method and systems for generating an immune profile for a subject are described. In some instances, the methods comprise contacting at least a first aliquot of a sample from the subject with at least a first immunophenotyping panel to fluorescently-label cells contained within the sample; processing the fluorescently-labeled cells using a full spectrum flow cytometer to generate fluorescence intensity data, or data derived therefrom, for fluorescently-labeled cells from the sample; providing at least a subset of the fluorescence intensity data, or data derived therefrom, for the fluorescently-labeled cells as input to an ensemble machine learning model configured to process the data and classify individual cells as belonging to one of a plurality of distinct immune cell sub-populations; and outputting a total cell count or cell frequency for each of the plurality of distinct immune cell sub-populations in the sample as part of an immune profile for the subject.

Methods of identifying an immunophenotype for a tumour are described, using one or more whole slide images of a sample of the tumour that has been stained using at least a CD8 label Related methods and systems are also described.

Methods and systems for generating an immune profile of a subject are described. In some examples, the method includes contacting at least a first aliquot of a sample from the subject with at least a first immunophenotyping kit to fluorescently label cells contained in the sample; processing the fluorescently labeled cells using a full spectrum flow cytometer to generate fluorescence intensity data from or derived from the fluorescently labeled cells of the sample; providing, as input to an integrated machine learning model, at least a subset of the fluorescence intensity data of the fluorescently labeled cells or data derived therefrom, the integrated machine learning model configured to process the data and classify individual cells as belonging to a different immune cell subset of a plurality of different immune cell subpopulations; and outputting the total cell count or cell frequency of each of the plurality of different immune cell subpopulations in the sample as part of an immune profile of the subject.

Screening methods are provided that are based on using ELISpot assays to measure the distribution profile of maximum spot intensity or mean spot intensity of spontaneous cytokine or chemokine or the number of "low intensity" spontaneous cytokine or chemokine producing cells as a clinically relevant measure of immune function for diagnosing patients with a particular disorder based on one or more of these measurements and for treating the particular disorder in the patient. In some embodiments, the cytokine is IFN-gamma or TNF-alpha. Patients can optionally be further evaluated to determine whether they are of an immunosuppressed or hyperinflammatory immune phenotype by quantifying cytokine and / or chemokine levels in a biological sample. Representative disorders include sepsis, autoimmune disease, autoimmunity, cancer, and lymphopenia.

This application relates to the field of biological tissue engineering technology and discloses a scoring method for the likelihood of tumor immune response based on dual-panel multiple biomarker analysis, comprising: staining multiple cells in a tumor tissue section with multiple affinity histochemical stains; obtaining a first and / or second eigenvalue group of cells in a target analysis area defined in a digital image; determining the immunophenotyping of the tumor tissue sample based on at least part of the second eigenvalues ​​in the inner and outer regions of the tumor boundary; obtaining multiple first eigenvalues ​​of the first eigenvalue group within the inner region of the tumor boundary of a tumor tissue sample determined by immunophenotyping as either immune infiltration or immune rejection, scoring each of the multiple eigenvalues, and summing the multiple scores to obtain a score. This scoring method uses 11 cell types as biomarkers to score immune responses to predict the likelihood of tumor patients responding to immunotherapy, and has wide adaptability and strong feasibility.

A multi-omics analysis method and device based on immunophenotyping, and a storage medium and a program product. The method comprises: performing immune infiltration analysis on gene expression data to obtain the proportions of a plurality of cell types; on the basis of at least one of survival significance, variance and correlation, selecting N types of cells from the plurality of cell types, wherein N>1; dividing the N types of cells into M types of fixed cells and (N-M) types of candidate cells, and performing clustering analysis on a plurality of cell combinations, wherein each cell combination at least comprises M types of fixed cells and q types of candidate cells, wherein M≥1 and M<N, and 0≤q≤(N-M); selecting one of the cell combinations as a cell combination for immunophenotyping, and determining characteristic cell types corresponding to each immunophenotyping group; and determining differentially expressed genes corresponding to each immunophenotyping group, and determining at least one of the following omics features corresponding to each immunophenotyping group: differentially mutated genes, differential copy number variations and differentially methylated sites.

The invention relates to a multi-target animal model construction method capable of repeatedly inducing multi-organ inflammatory response, and the method comprises the following steps: constructing an immune response coupling matrix among different organs by using an existing immunomics database and animal test data; screening out core inflammation targets which have a linkage effect in a plurality of organs and comprise TLR4, IL-6R and NLRP3; a composite induction strategy is constructed on the basis of a common target spot, so that one source is activated, and multiple organs respond; performing multi-organ positioning modeling driven by adopting a space-time difference induction strategy: adopting a time-sharing release platform comprising a microcapsule wrapping technology and an in-vivo degradation delivery system; according to an immune response time sequence, the inducer is released in vivo in a time-sharing and zoning manner, so that organs are sequentially activated to simulate an inflammation propagation path; blood and tissue samples are collected after each round of induction, and a rapid immunophenotype analysis module including multi-factor analysis and tissue scoring is constructed; adjusting the next round of induction dose and targeting strategy according to the inflammation grade; and introducing decision logic to optimize an induction path, so that the model induces a closed loop.