50 results about "Immune infiltration" patented technology

The invention discloses a glioma T cell prediction and prognosis evaluation method based on pathological images, particularly relates to the field of patient prognosis health evaluation, and aims to solve the problems that existing pathological evaluation is difficult to combine with tumor structure heterogeneity and immune infiltration distribution, and the future progress risk of a patient cannot be predicted based on follow-up visit pathological data. A spatial heterogeneity map of a tumor core area and an invasion edge is constructed in a digital pathological section, density gradients of T cells in different areas are calculated to generate a distribution heterogeneity coefficient, interaction processing is performed on the two types of characteristics in combination with historical follow-up visit records, and a time sequence neural network constructed based on a gating structure is combined to obtain a high-efficiency characteristic of the tumor. And outputting disease progress probabilities of a plurality of follow-up visit time points in the future to form a prognosis trajectory prediction curve, calculating a quantitative recurrence risk score according to curve slope change and an immune fluctuation mode, and finally generating an individualized management scheme, thereby realizing quantitative prediction evaluation and risk management of the prognosis trend of the glioma patient.

The invention relates to the technical field of organoid culture, in particular to a pulmonary fibrosis organoid model and a construction method and application thereof. The pulmonary fibrosis organ-like model is obtained by co-culturing lentivirus stably transfected alveolar epithelial cells, human embryonic lung fibroblasts MRC-5 and macrophages. According to the invention, macrophages are innovatively introduced, a ternary co-culture system of lentivirus stably transfected alveolar epithelial cells, human embryonic lung fibroblasts MRC-5 and macrophages is constructed, and a key'epithelial injury-immune infiltration-fibroblast activation 'pathological triangle in a pulmonary fibrosis pathogenesis process can be more comprehensively simulated; the finally obtained pulmonary fibrosis organ-like model provides an efficient tool for pulmonary fibrosis mechanism research and research, development and screening of anti-pulmonary fibrosis drugs.

The invention relates to a co-culture microsphere model with a core-shell structure and a preparation method of the co-culture microsphere model. The co-culture microsphere model comprises a core-shell microsphere, the core-shell microsphere is composed of an inner core and an outer shell, the inner core is an organoid loaded by matrigel, the outer shell is formed by crosslinking a photo-crosslinking hydrogel material, co-culture cells are doped in the photo-crosslinking hydrogel material, and the inner core is wrapped by the outer shell. According to the co-culture microsphere model, double-layer structure microspheres of co-culture cell wrapped organoids are formed, immune infiltration and in-vivo characteristics can be simulated, and a similar in-vivo three-dimensional tumor immune microenvironment is provided. And the types of cells loaded on the inner layer and the outer layer can be flexibly replaced to form a microsphere model for co-culture of single or multiple cells and organoids. The co-culture microsphere model is more stable in structure, the size of the diameter of the core-shell microsphere can be optimized by changing 3D printing parameters, the operability of subsequent research is high, and the co-culture microsphere model is suitable for different research application scenes.

The application discloses a new application of a JAK inhibitor and a medicine for promoting skin stretch regeneration, and application of the JAK inhibitor in preparation of the medicine for promoting skin stretch regeneration; the medicine for promoting skin stretch regeneration comprises the following components: a JAK inhibitor and a carrier, wherein the carrier comprises sodium hyaluronate and propylene glycol; the application provides a new application of the JAK inhibitor, and the JAK inhibitor can promote skin stretch regeneration, in particular, can promote increase of hair follicle density, increase of epidermis thickness, increase of dermis thickness, reduction of fibrosis degree, reduction of immune infiltration degree and reduction of myofibroblast quantity after skin expansion.

The present application relates to the field of biomedical technology, and discloses an immune infiltration desert tumor benefit ICI treatment method based on a weighting strategy. The method obtains spatial transcriptome data of tumor tissue of a patient, divides the tumor microenvironment into functional regions through an adaptive grid division algorithm, and extracts a multi-scale feature vector; calculates dynamic weight coefficients of each functional region using a graph attention network, and generates a comprehensive response index after weighted integration; and finally outputs an individualized ICI treatment decision according to the comparison result of the index and a preset threshold. The present application realizes dynamic evaluation of tumor microenvironment heterogeneity based on spatial transcriptome data, and provides ICI treatment response prediction and clinical decision support for patients with immune infiltration desert tumors.

The invention discloses a lung adenocarcinoma prognosis and immune infiltration related prediction model. By deeply mining data in TCGA and GEO databases, a prognosis model based on eight pyroptosis related genes is constructed, and compared with a traditional method, the five-year survival prognosis of a lung adenocarcinoma patient can be more accurately predicted. A verification result shows that the model has relatively high accuracy (AUC = 0.687) in prediction of the total survival of one year, and through Kaplan-Meier analysis and Log-Rank inspection, survival differences of patients in high and low risk groups in a training set and a verification set are remarkably distinguished. The research method and the model have strong universality, provide important reference for research and application of a pyroptosis related mechanism in other cancer types, promote the progress of the oncology field in the research related to the pyroptosis mechanism, and have wide clinical application value.

The invention relates to a cerebral arterial thrombosis diagnosis model based on neutrophil extracellular trap genes, and belongs to the field of clinical medicine. The method is high in sensitivity and good in diagnosis effect, complex gene expression data is converted into a visual scoring tool, and the clinical applicability is improved; gene expression, immune infiltration and single cell sequencing data are integrated through multi-omics data fusion, an IS pathological mechanism is comprehensively analyzed, a high-specificity gene combination is screened through a Boruta algorithm and CytoHubba, traditional single-gene limitation is broken through, meanwhile, it is revealed for the first time that NETs influences IS progress by regulating neutrophil infiltration, a new target is provided for immunotherapy, and the method has the advantages of being high in specificity and good in immunotherapy effect. Compared with the prior art, the method is obviously improved.

According to the osteoporosis collagen related biomarker and the application thereof, the collagen related biomarkers RANBP1 and SOCS3 are found in OP through multi-omics analysis, an ROC curve model with excellent performance is constructed based on the two biomarkers, and the onset risk of OP can be effectively predicted; the invention relates to an OP diagnosis marker, in particular to an application of RANBP1 and SOCS3 in bone metabolism, which covers function enrichment analysis, immune infiltration evaluation, regulation network construction, drug prediction and molecular docking analysis, reveals the potential of RANBP1 and SOCS3 as OP diagnosis markers, clarifies the effect of RANBP1 and SOCS3 in bone metabolism through a JAK-STAT pathway and an immune regulation network, and provides molecular and clinical basis for early diagnosis and targeted therapy of OP.

The invention provides a method for analyzing and identifying an autophagy biomarker related to atherosclerotic plaque progress, and belongs to the technical field of analysis. Comprising the following steps: (1) data acquisition and processing; (2) identifying differentially expressed genes and autophagy related genes; (3) key gene verification and prediction efficiency evaluation; (4) immune infiltration analysis; (5) single cell RNA sequencing analysis; and (6) expression of the three genes in macrophages. According to the invention, autophagy related genes related to AS are identified, and the expression mode, spatial distribution and immune infiltration characteristics of key differential expression genes are clarified by adopting a multi-omics method. The research result of the invention provides a new insight and potential intervention treatment target for understanding the molecular mechanism of AS.

The invention discloses application of nintedanib in preparation of a medicine for treating plant migration and plant mineralization, and belongs to the technical field of biological medicine. The research shows that the nintedanib has the effects of reducing deposition of extracellular matrix of an allogeneic kidney transplantation model mouse, improving renal tubular atrophy, relieving mouse CD206 + macrophage infiltration and reducing rejection injury degree and immune infiltration degree of kidney grafts after being administered under the administration dosage without generating liver and kidney toxicity and intestinal side effects; the lesion process of mouse chronic transplanted kidney rejection is obviously slowed down, and the damage of excessively activated inflammatory cells to the transplanted kidney is reduced. The results show that nintedanib can delay the progress of chronic transplantation renal fibrosis.

Multi-modal approaches to predict tumor immune infiltration are based on integrating gene expression data and imaging features in a neural network-based framework. This framework is configured to estimate percent composition, and thus immune infiltration score, of a patient tumor biopsy sample. Multi-modal approaches may also be used to predict cell composition beyond immune cells via integrated multi-layer neural network frameworks.

The invention discloses a CAR-T cell based on a secretion enhancement strategy as well as a preparation method and medical application thereof. The constructed asCAR-T cell contains a secretion-enhanced chimeric antigen receptor (asCAR for short) and small interfering nucleic acid of DDR1 protein. The asCAR sequentially comprises a single-chain variable fragment scFv, a hinge region, a transmembrane domain, a costimulatory factor, a signal transduction structural domain CD3 zeta and TNFRSF1B ICD from an extracellular structure to an intracellular structure, wherein the TNFRSF1B ICD is a TRAF2 binding structural domain in a TNFR2 cell; the small interfering nucleic acid of the DDR1 protein comprises shRNA-DDR1 (short hairpin ribonucleic acid) or miRNA-DDR1 (micro ribonucleic acid). After the antigen activates the asCAR-T cells, the ICD of the TNFRSF1B enhances the expression of the PD-1 through the NF-kappa B pathway and releases the extracellular vesicles loaded with the shRNA-DDR1 or the miRNA-DDR1. The extracellular vesicles released by the asCAR-T cells degrade PD-L1 on the surfaces of tumor cells and inhibit DDR1 expression, and the immune infiltration and anti-tumor effects of the asCAR-T cells are enhanced based on the positive feedback loop.

Aspects of the disclosure relate to methods, systems, and computer-readable storage media that are useful for characterizing subjects having certain cancers, for example cancers typified by solid tumors. The disclosure is based, in part, on methods for determining a tumor microenvironment (TME) type of a cancer subject and determining the subject's prognosis and / or likelihood of responding to one or more therapies based upon the TME type determination.

The application discloses a bioinformatics analysis method for identifying a brain hemorrhage prognosis-related gene target point, and the method comprises the following steps: obtaining brain hemorrhage transcriptome expression data, performing quality filtering and batch correction to generate a standardized expression matrix, performing differential expression analysis on the basis of the standardized expression matrix, screening prognosis-associated differential genes in combination with survival regression, constructing a weighted co-expression network to identify a prognosis key gene cluster, screening and verifying a core hub gene through hub degree, taking the intersection of the prognosis-associated differential genes and the core hub gene, filtering and interaction network clustering a core target gene through a pathological pathway, performing immune infiltration correlation analysis and survival analysis on the basis of the core target gene, and outputting the brain hemorrhage prognosis-related gene target point according to an immune correlation marker and a survival correlation index. The application integrates a differential analysis and a network analysis double strategy, confirms mechanism correlation through pathway verification and immune correlation analysis, and the screening result has statistical reliability and biological interpretability.

The invention discloses a colorectal cancer multi-target prognosis risk assessment model construction method based on palmitoylation related lncRNA, and relates to the technical field of colorectal cancer prognosis model construction. The method comprises the following steps: step 1, data acquisition; step 2, identifying lncRNA (long non-coding ribonucleic acid) related to S-palmitoylation; step 3, determining a key lncRNA (long non-coding RNA) for constructing a prognosis model; 4, establishing a risk scoring model; and 5, testing the prognosis model. Based on a TCGA database, palmitoylation related genes and CRC transcriptome data are integrated, lncRNA significantly related to the palmitoylation related genes and the CRC transcriptome data is screened through co-expression analysis, and a multi-target prognosis risk assessment model based on the palmitoylation related lncRNA is constructed. And further model testing and mechanism exploration, immune infiltration and mutation load evaluation, drug sensitivity prediction and the like are carried out, so that a more accurate prognosis evaluation tool is expected to be provided for CRC patients, the development of mechanism-driven individualized treatment strategies is promoted, and the method has important significance in improving treatment of the patients and increasing the survival rate.

The invention discloses application of an ICAT gene as a treatment target in cervical cancer, and relates to the technical field of biomedicine and oncology. The prognosis of the patient is evaluated by detecting the expression level of ICAT in cervical cancer tissues; the detection method comprises the following steps: S1, analyzing correlation between ICAT and CC immune infiltration by a clinical sample; s2, identifying that ICAT promotes the malignant progression of cervical cancer through glycolysis; s3, determining a molecular mechanism for regulating and controlling ENO1 expression by ICAT to remodel cervical cancer glycolysis reprogramming; s4, determining a molecular mechanism of ICAT-dependent lactic acid accumulation for triggering polarization of tumor-associated macrophages; and S5, evaluating a result. According to the invention, ICAT remodeling cervical cancer metabolism reprogramming is taken as an entry point, and ICAT is revealed from the aspects of cells, animals and tissues to promote the activity of cervical cancer tumors, and has clinical value.

Aspects of the disclosure relate to methods, systems, and computer-readable storage media that are useful for characterizing subjects having certain cancers, for example cancers typified by solid tumors. The disclosure is based, in part, on methods for determining a tumor microenvironment (TME) type of a cancer subject and determining the subject's prognosis and / or likelihood of responding to one or more therapies based upon the TME type determination.

The invention relates to a bioinformatics analysis method for identifying cerebral hemorrhage prognosis related gene targets. The method comprises the following steps: acquiring cerebral hemorrhage transcriptome expression data and implementing quality filtering and batch correction to generate a standardized expression matrix; performing differential expression analysis according to the standardized expression matrix, and screening prognosis associated differential genes in combination with survival regression; constructing a weighted co-expression network to identify a prognosis key gene cluster, and obtaining a core hub gene through hub degree screening and cross-dataset verification; after intersection of the prognosis associated differential genes and the core hub genes is obtained, core target genes are recognized through pathological pathway filtering and interaction network clustering; and carrying out immune infiltration correlation analysis and survival analysis based on the core target gene, and outputting cerebral hemorrhage prognosis related gene targets according to immune correlation markers and survival correlation indexes. According to the method, dual strategies of difference analysis and network analysis are integrated, mechanism relevance is confirmed through pathway verification and immune relevance analysis, and a screening result has statistical reliability and biological interpretability.

The invention discloses novel application of a JAK inhibitor and a medicine for promoting skin stretching and regeneration, and relates to application of the JAK inhibitor in preparation of the medicine for promoting skin stretching and regeneration. The medicine for promoting skin stretching and regeneration comprises the following components: a JAK inhibitor and a carrier, wherein the carrier comprises sodium hyaluronate and propylene glycol; the invention provides a novel application of a JAK inhibitor, the JAK inhibitor can promote skin stretching and regeneration, and specifically, the JAK inhibitor can promote hair follicle density increase, epidermis thickening, dermis thickening, fibrosis degree reduction, immune infiltration degree reduction and myofibroblast number reduction after skin expansion.

The invention provides a method for treating hepatocellular carcinoma (HCC) by utilizing cytokines to recruit eosinophilic granulocytes. According to the invention, single sample gene set enrichment analysis (ssGSEA) is adopted to calculate a hepatocellular carcinoma immune infiltration score, and eosinophilic granulocyte infiltration is screened out, so that the lifetime of an HCC patient can be prolonged. Experiments prove that by collecting eosinophilic granulocytes through cytokines, activation and proliferation of NK cells, CD8 T cells and CD4 T cells in the liver can be directly or indirectly promoted, and secretion of IFN-gamma can be promoted, so that liver cancer cells are killed. Therefore, the invention provides application guidance for accurate and effective treatment of HCC.

The invention discloses a sepsis risk prediction method based on intestinal flora exposure factors and a multi-machine learning algorithm, and belongs to the field of sepsis risk prediction.The sepsis risk prediction method comprises the steps that 473 intestinal flora SNP data sets and sepsis data sets are obtained from a GWAS database, a sepsis patient expression microarray data set is downloaded from a GEO database, and a sepsis risk prediction result is obtained; the method comprises the following steps: acquiring positioning information of a gene on a chromosome from a GeneCards database, and acquiring immune infiltration abundance data from CIBERSORT; according to the method, a Mendel randomization method is combined with multiple machine learning algorithms, a sepsis risk prediction model is constructed based on intestinal flora exposure factors, and the intestinal flora exposure factors and target genes closely related to sepsis are screened out through Mendel randomization analysis. A plurality of machine learning algorithms are utilized to construct a model and screen out an optimal model, the accuracy and sensitivity of sepsis early diagnosis are improved, characteristic genes are analyzed, targeted drugs are predicted, and a theoretical basis is provided for precise treatment of sepsis.

The invention relates to the technical field of medical images, in particular to a method for predicting liver cancer TACE treatment prognosis through immune infiltration related image group scoring based on transfer learning, which comprises the following steps of: acquiring a preoperative MRI image and constructing a pattern label, extracting an evolution feature block, establishing a co-occurrence relation between the image and immune expression, and establishing a TACE treatment prognosis model according to the co-occurrence relation between the image and the immune expression. The fusion gene and the pathway sequence form a splicing structure, and a prognosis distribution diagram is generated by mapping layer levels. According to the method, pattern labels are constructed based on image gray and boundary directions, evolution blocks are formed in combination with signal trends and structural stability, spatial mapping is established by using block numbers and immune expression positions, expression trends and gene identifiers are fused to construct a path aggregation structure, and survival levels are mapped according to a layer sequence. Cooperative association of image features, immune response and molecular pathways in the spatial dimension is achieved, and the focus structure recognition definition, the expression position corresponding precision and the prognosis prediction stability under multi-layer information linkage are improved.

The invention discloses a platinum anti-tumor conjugate and a preparation method and application thereof.The conjugate is reduced into a bivalent platinum drug and an LOXL2 inhibitor in tumor cells, the bivalent platinum drug not only can directly damage DNA and promote cell apoptosis, but also can induce ICD and activate T cells; the LOXL2 inhibitor further promotes immune infiltration of tumor tissues by degrading collagenous fibers and softening rigid ECM (extracellular matrix) of tumors, and the LOXL2 inhibitor and the LOXL2 inhibitor cooperatively kill tumor cells.

The invention provides an immune sensitizer, the immune sensitizer comprises homing cells modified with a nucleic acid aptamer, and the nucleic acid aptamer is used for specifically targeting, recognizing and capturing immune cells. The immune sensitizer can realize selective targeting tumor infiltration and activation of specific immune cells, so that immunotherapy sensitization is realized, tumor suppression is further realized, and the effects of selective infiltration and activation of the immune cells are realized while the immune infiltration efficiency is improved.

The invention provides a composition for improving anti-tumor immunity of advanced non-small cell lung cancer. The composition comprises a mitochondrial extracting solution extracted in vitro and a platinum chemotherapeutic drug. Experiments prove that the composition can improve immune infiltration of T cells and NK cells of the advanced non-small cell lung cancer, promote infiltration of immune cells to tumor tissues, activate anti-tumor immune response and enhance the anti-tumor effect.

The invention belongs to the technical field of biological medicine, and particularly relates to an experimental method for regulating immune infiltration of a breast cancer mouse model, an immunomodulator for inhibiting breast cancer and application of the immunomodulator. The experimental method for regulating immune infiltration of the breast cancer mouse model comprises the following steps: applying dapagliflozin to the breast cancer mouse model; the experimental method is used for non-disease diagnosis and treatment purposes. According to the experimental method for regulating immune infiltration of the breast cancer mouse model, a new way for carrying out immune regulation on the breast cancer mouse model can be provided for researchers, so that the researchers can regulate the immune condition of the breast cancer mouse model as required, and further, deeper research on treatment of breast cancer is facilitated.

The present application belongs to the field of biotechnology, and provides a use of a drug combination in the preparation of a kit for treating tumors (including low immune infiltration tumors (also known as "cold tumors")). Specifically, the present application relates to the treatment of tumors (including low immune infiltration tumors) by combining immune cells with chemotherapy drugs. More specifically, the present application relates to the synergistic treatment of tumors (including low immune infiltration tumors) by combining NK cells with TMZ.

The application comprises a RAS gene cluster-based pediatric AML prognosis model construction method, which relates to the cross field of bioinformatics and medical technology. It comprises: S1: data acquisition and integration, standardization and integration processing of expression data; S2: sample typing, obtaining at least two subtypes with different prognoses; S3: prognosis model construction; S4: clinical correlation verification, constructing a visual prognosis evaluation system integrating risk stratification and clinical characteristics; S5: immune infiltration correlation verification, establishing the correlation between risk stratification and immune infiltration characteristics; S6: drug sensitivity correlation verification, determining the correlation between risk stratification and drug sensitivity; S7: key gene verification. The application realizes the precise risk stratification of pediatric AML patients by integrating RAS signal pathway gene characteristics and clinical data, and the prognosis model is verified by training set and verification set, which provides a standardized scientific research model framework and reliable data support, and provides an efficient auxiliary tool for pediatric AML related scientific research.

An immunophenotyping method and device, a storage medium, and a program product. The method comprises: performing immune infiltration analysis on sample data to obtain a proportion of a plurality of cell types; on the basis of at least one of the following: survival significance, variance, and correlation, screening for N cells from the plurality of cell types, wherein N>1; dividing the N cells into M fixed cells and (N-M) candidate cells, and performing clustering analysis on a plurality of cell combinations, wherein each cell combination at least comprises M fixed cells and q candidate cells, M≥1, M<N, and 0≤q≤(N-M); and selecting one of the cell combinations as a cell combination for immunophenotyping, and determining a characteristic cell type corresponding to each immunophenotyping group.

Disclosed are sustained biodegradable implant (a depot) that releases high drug doses directly into the tumor for treating cancer. The depot comprises a biodegradable polymer and a STING agonist and / or a PARP inhibitor (PARPi); wherein the STING agonist or the PARPi is distributed in the biodegradable polymer. The depot activates anticancer innate and adaptive immunity within the tumor microenvironment and promote immune infiltration of secondary, metastatic sites.