64 results about "Tumor heterogeneity" patented technology

A frequency of somatic mutations in a biological sample (e.g., plasma or serum) of a subject undergoing screening or monitoring for cancer, can be compared with that in the constitutional DNA of the same subject. A parameter can derived from these frequencies and used to determine a classification of a level of cancer. False positives can be filtered out by requiring any variant locus to have at least a specified number of variant sequence reads (tags), thereby providing a more accurate parameter. The relative frequencies for different variant loci can be analyzed to determine a level of heterogeneity of tumors in a patient.

Method and apparatus for monitoring a patient having a tumor to determine perfusion tumor heterogeneity wherein a solution containing a tracer, preferably a <2>H-saline solution is infused into the patient's bloodstream at a predetermined slow rate to effect perfusion into the tumor. An MRI machine is adjusted to acquire a set of dynamic <2>H magnetic resonance images of the tumor. The <2>H-images are obtained before infusion, during infusion and post infusion. First, the obtained images are processed to quantitatively determine perfusion per voxel of the images. Next, maps of perfusion parameters are generated to indicate spatial distribution of tumor perfusion. The maps are displayed in color code and analyzed.

The invention belongs to the technical fields of immunology and tumor therapy, and relates to a preparation method and a use of a TCR gene modified CD8+T memory stem cell. The method comprises the following steps: co-incubating a tumor antigen and an immature dendritic cell to obtain a specific tumor antigen-supported mature dendritic cell, co-culturing the specific tumor antigen-supported maturedendritic cell and a CD8+ naive T cell, and adding a stem cell differentiation inhibitor to promote the generation of a CD8+ stem cell-like memory T lymphocyte; separating the CD8+ stem cell-like memory T lymphocyte; and cloning a T cell receptor gene (TCR) for specifically identifying a specific antigenic epitope, and carrying out lentivirus packaging or retroviral vector cotransfection on an autologous CD8+ Tscm cell to in-vitro prepare a CD8+ TCR-Tscm cell specific for different tumor specific antigens. The CD8+ TCR-Tscm cell prepared by the method has the advantages of overcoming of the tumor heterogeneity, high specificity, few adverse reactions, and highly-efficient and lasting tumor preventing and treating effects.

The invention discloses a method and a device for identifying tumor purity and absolute copy number based on sequencing data. The method comprises the following steps: comparing offline data after quality control to a reference genome, and carrying out variation detection and population database annotation; testing the preprocessed data of the tumor and the normal sample by using purity predictionsoftware to obtain a purity and copy number information model; and for the model conforming to normal distribution, further screening out the model with the maximum probe support number in the high tumor cell fraction subcloning region, and defining an optimal model in combination with the matching rate of BAF and alle1 and alle2 copy numbers. According to the method, the model of purity detection software is rapidly and efficiently corrected, and the purity and absolute copy number information of tumors can be obtained more accurately; the accuracy is guaranteed, the tedious process of manual verification is avoided, the labor cost is saved, and a foundation is laid for follow-up tumor genome evolution and tumor heterogeneity research.

This disclosure provides, among other things, methods for generating and applying therapeutic interventions. The methods involve, for example, (a) sequencing polynucleotides from cancer cells from a subject; (b) identifying and quantifying somatic mutations in the polynucleotides; (c) developing a profile of tumor heterogeneity in the subject indicating the presence and relative quantity of a plurality of the somatic mutations in the polynucleotides, wherein different relative quantities indicates tumor heterogeneity; and (d) determining a therapeutic intervention for a cancer exhibiting the tumor heterogeneity, wherein the therapeutic intervention is effective against a cancer having the profile of tumor heterogeneity determined.

The invention discloses a liver cancer image omics data processing method, system and device and a storage medium. The method comprises the steps of obtaining an upper abdomen CT image of a liver cancer patient, calculating image omics data corresponding to the upper abdomen CT image, calculating a linear combination of the plurality of image omics characteristic values, and dividing the liver cancer patient into a hepatic artery chemoembolization reaction group or a hepatic artery chemoembolization reaction-free group according to a magnitude relation between the predicted value and a presetthreshold value. The used imaging omics technology can extract the tumor feature information contained in the CT image from the three-dimensional perspective in an omnibearing mode, and the defect that tumor heterogeneity is not considered in an existing method is overcome; and patients are divided into a reaction group and a non-reaction group according to scores of the imaging characteristics ofpatients, so that the clinical guiding significance is good, and a better decision reference is provided for clinical workers. The method is widely applied to the technical field of data processing.

The invention discloses a system and a method for tumor heterogeneity assessment and particularly provides a molecular clone analysis method. On the basis of various types of variation detection results of high-throughput sequencing in circulating tumor DNA, all variations are divided into different molecular clones to realize tumor heterogeneity assessment by molecular clone levels. By adoption of the method, tumor heterogeneity assessment based on ctDNA high-throughput variation detection is realized to effectively assist in making of tumor prognosis and treatment schemes.

The invention relates to bioinformatics, in particular to a receptor-ligand system analysis method influencing intercellular communication. The invention provides an analysis method which comprises the following steps: carrying out primary clustering analysis on cells according to provided gene expression quantitative data; carrying out differential gene expression analysis on the provided cell population; screening the provided differential genes; providing enriched pathways and / or biological processes according to the provided relationship pairs of ligands and receptors; and / or, according tothe provided differential genes and the provided relationship pairs of the ligands and the receptors, providing the inter-cell population communication relationship corresponding to the relationshippairs of the ligands and the receptors. The analysis method provided by the invention is based on single cell sequencing instead of traditional RNA-seq, can deeply understand transcriptome under single cell resolution, can deeply understand tumor heterogeneity, and can further construct a prognosis risk model in combination with an external common data set.

The invention provides a method and system for detecting the degree of tumor heterogeneity. The method comprises the following steps: acquiring sequencing data of a tumor tissue sample and a control sample, carrying out somatic variation detection, and acquiring somatic variation sites; clustering the somatic cell variation sites according to clusters; judging a main cloning mutation cluster and asubcloning mutation cluster according to a clustering result; and calculating a ratio of the number of somatic cell variations in the subcloning mutation cluster in the tumor tissue sample to the number of all the somatic cell variations, wherein the ratio is the value of tumor heterogeneity. According to the method, mutation frequency detected at each mutation site of the sample is fully utilized to estimate the cell proportion of corresponding tumor cloning, so the specific numerical value of a tumor heterogeneity degree is calculated; and thus, a numerical reference basis is provided for subsequent prediction of immunotherapy effect.

The invention discloses a fractal-theory-based tumor heterogeneity analysis method. The method comprises the steps: marking out a tumor range on a maximum tumor cross-section of a CT or MRI image of a sufferer; carrying out gray scale processing on the CT or MRI image of the sufferer, and marking a tumor region; carrying out gray scale processing on a standard photograph of a postoperative cut maximum tumor cross-section, and marking the interior of a tumor; calculating the CT or MRI tumor image and the standard photograph subjected to gray scale processing by employing a box-counting method, so as to figure out a preoperative congested fractal dimension and a postoperative bloodless fractal dimension of the tumor; inputting the fractal dimensions and clinical data of the sufferer into a tumor evaluation model for evaluation, and outputting a weighting-processed tumor fractal dimension; evaluating characteristics of the tumor according to the tumor fractal dimension, and evaluating a treatment effect; and evaluating heterogeneity of the tumor according to the tumor fractal dimension. According to the method, tumor heterogeneity information on a focus can be accurately provided, so as to assist doctors to accurately analyze tumor heterogeneity of a tumor focus.

The present invention discloses systems and methods for measuring intra-tumor heterogeneity based on genetic information of a tumor. Such systems and methods may indentify genetic information of mutation specific to the tumor, determine a mutant-allele fraction for each mutated locus, calculate mutant-allele tumor heterogeneity (MATH), and measure the distribution of mutant-allele fractions among tumor-specific mutated loci of the tumor.

The invention relates to the field of biotechnology and medicine and specifically discloses a primer combination for detecting mutation of single cell EGFR gene and application of the primer combination. According to the invention, by adopting a high-specificity amplification primer and a multiple-amplification system, all common mutations on exons 18, 19, 20 and 21 of the EGFR gene are obtained at a time, and new type of mutation can be discovered in time. By adopting the primer combination disclosed by the invention to detect the mutation of single cell EGFR gene, the specificity and sensitivity are high, DNA extraction is not needed, two copies in as few as single cell can be amplified, and more systematic research of tumor heterogeneity is facilitated.

The invention discloses a miRNA composition for detecting breast cancer brain metastases and a kit with same. The miRNA composition comprises miR-10b and one or more of miR-200a, miR-122, miR-21 and miR-181c. The kit comprises forward and reverse primers of the miRNA composition, forward and reverse primers of an external reference U6 RNA, a cerebrospinal fluid RNA extraction system, a reverse transcription reagent, a PCR amplification reagent and a cDNA mixed positive reference product. According to the miRNA composition, a group of miRNAs are adopted as novel breast cancer brain metastases markers, low specificity and low sensitivity caused by tumor heterogeneity are hard to overcome by using a single marker can be alleviated, prognosis effectiveness evaluation of a patient suffering from breast cancer can be effectively improved, and thus clinical treatment can be instructed. The miRNA composition is used for preparing a kit or a biological chip for prognosis inspection on breast cancer by using a fluorescent quantitative / digital PCR method, low specificity and low sensitivity caused by tumor heterogeneity can be avoided, the prognosis effectiveness evaluation of the patient suffering from breast cancer can be effectively improved, and thus clinical treatment can be instructed.

The invention discloses primary cell culture of gliomas, and construction of a PDX model. The PDX model has high fidelity and reserves the histopathological and genetic characteristics and tumor heterogeneity of primary gliomas and is a tumor model with the closest relevance to clinical research at present. The PDX model that simulates the specificity of human gliomas has important transformationsignificance to preclinical evaluation, treatment and prognosis of tumors and is expected to bring new breakthroughs in individualized treatment of patients with gliomas.

The invention belongs to the field of the medical image analysis, specifically a quantitative description method of PET image nasopharyngeal carcinoma intra-tumor heterogeneity. The method comprises the following steps: acquiring PET / CT scanning data of a patient, and converting the PET / CT scanning data into a standard SUV image; performing three-dimensional segmentation on the primary focus at the nasopharynx; performing discretization processing on the focus, and constructing four image omics matrixes for the processed focus, and comprehensively considering five parameter settings of symmetry, the average policy, the distance, the neighborhood number and window width size in the matrix construction process; extracting 415 texture features from the constructed matrix, and realizing the quantitative description of the intra-tumor metabolic heterogeneity by combining five traditional SUV features. The intra-tumor metabolic heterogeneity is described more comprehensively by sufficientlymining the information contained in the non-invasive PET image, thereby providing the quantitative evaluation index for precisely identifying the nasopharyngeal carcinoma by the doctor.

The invention relates to a model construction method for predicting the prognosis risk of an early-stage colon cancer patient. The model construction method specifically comprises the following steps: firstly, obtaining a tumor tissue specimen of the patient through an operation; detecting the expression of the gene content in a tumor tissue sample of a patient by using difference analysis; then screening genes for constructing a risk model by using single-factor Cox regression analysis and LASSO regression analysis, and establishing a calculation formula of the risk model; finally, using Kaplan-Meier prognosis analysis and ROC analysis to verify the accuracy of the prognosis risk model for prognosis prediction in early-stage colon cancer patients. The method can better guide clinical design of a more targeted treatment scheme for a patient with poor early colon cancer prognosis, and realizes precise medical treatment; The number of genes for constructing the prediction model is large, the influence caused by tumor heterogeneity can be reduced to the maximum extent, and the accuracy is high; The gene detection method is simple and easy to implement.

The invention relates to a prediction system for identifying key heterogeneity molecules for driving tumor metastasis. The prediction system comprises an input module, an analysis module and an output module, wherein the input module is used for inputting a pre-intervention protein quantitative analysis result and a post-intervention protein quantitative analysis result; the analysis module comprises a primary analysis sub-module, a secondary analysis sub-module and a calculation sorting sub-module, all the sub-modules are connected in sequence, and a sorting list of all the heterogeneity molecules is finally obtained; and the output module is used for outputting a sorting list of the heterogeneity molecules. According to the method, the key heterogeneous molecules for driving tumor metastasis can be more reasonably and accurately identified and sequenced, sequential intervention can be subsequently carried out according to the result in combination with the actual situation, and the curative effect is determined; and the research findings and evidences provide innovative ideas, specific algorithms and practical guidance for clinical treatment of drug resistance and metastasis caused by tumor heterogeneity.

The invention belongs to the technical field of chemical medicines, in particular to an anti-cancer drug medicine compound and the synthetic method. The invention relates to an anti-cancer medicine obtained by synthesizing a plurality of chemical raw materials in four steps. The chemical name is N-[4-chlorin-3-(trifluoromethyl) phenyl]-{[4-(N-methyl- carbamyl) (4-pyrimidine sulfur) phenyl] amido}-carboxamide, which is shown in the chemical structural formula. The product can effectively restrain the activity of Raf and VEGFR protein kinase, extensively control the growth of varied tumor cells, and further induce the apoptosis of tumor cells. In the study of tumor heterogeneity transplant model, the product has the huge potential of being developed into a new anti-liver cancer medicine.

The invention relates to an engineered immune cell for combined expression of CCR2b. In particular, the engineered immune cells of the present invention are T cells or NK cells. The CAR molecule containing the NKG2D extracellular domain and the CCR2b are jointly expressed in the CAR-T cell, so that the sensitivity of the CAR-T cell to chemotactic factors such as CCL2, CCL7 and the like can be improved through the CCR2b, the CAR-T cell efficiently migrates to focuses such as colorectal cancer, ovarian cancer, pancreatic cancer and the like, and the treatment efficiency is improved; and meanwhile, various target antigens on the surfaces of cells such as colorectal cancer, ovarian cancer, pancreatic cancer and the like can be recognized through NKG2D CAR molecules, the risk that the curative effect is reduced due to tumor heterogeneity or target antigen loss is reduced, and the tumor treatment effect is improved.

A target gene identifying method for tumor treatment according to the present invention comprises the steps of: taking multiple samples from a patient's tumor; analyzing the multiple samples for genetic variation; subjecting the multiple samples to drug screening to measure drug sensitivity of each sample; analyzing tumor heterogeneity on the basis of the genetic variation analysis result and thedrug sensitivity measurement result; and identifying a target gene of the tumor on the basis of the tumor heterogeneity analysis result.

The invention relates to the field of data mining in bioinformatics, in particular to a multi-source data fusion framework for revealing a breast cancer immune escape regulation mechanism. The framework is implemented mainly according to the following steps of: (1) collecting related data of breast cancer samples and normal samples; (2) clustering the breast cancer samples by using NMF (Non-negative Matrix Factorization) to obtain sample subgroup types; (3) comparing the breast cancer samples with the normal samples obtained from GTEx, and finding out differentially expressed related genes; (4) designing a regulation and control analysis algorithm based on ATAC-SEQ data to find immune related genes; (5) verifying the relationship between the TF and the immune gene by using five general databases; and (6) analyzing whether the immune gene obtained according to the framework affects the survival of the patient. The invention provides a multi-source data fusion framework for revealing a breast cancer immune escape regulation mechanism, and the framework has important significance for researching drug relocation and realizing precise medical treatment. The biological significance of the research process and the research result can be effectively improved. More importantly, the single-sample law analysis method can be used for deeply exploring the heterogeneity of a tumor, and has important significance on precise medical practice.

A frequency of somatic mutations in a biological sample (e.g., plasma or serum) of a subject undergoing screening or monitoring for cancer, can be compared with that in the constitutional DNA of the same subject. A parameter can derived from these frequencies and used to determine a classification of a level of cancer. False positives can be filtered out by requiring any variant locus to have at least a specified number of variant sequence reads (tags), thereby providing a more accurate parameter. The relative frequencies for different variant loci can be analyzed to determine a level of heterogeneity of tumors in a patient.

The invention belongs to the technical field of STM2457 research, and particularly relates to novel application of STM2457. The invention relates to application of STM2457 in preparation of medicines for preventing and treating tumor diseases. In some embodiments, lung cancer is non-small cell lung cancer; and the action concentration of the STM2457 is 5 [mu]M. The invention also discloses application of the STM2457 in preparation of at least one selected from the group consisting of an NSCLC cell retardation proliferation preparation, an NSCLC cell transfer inhibitor and an NSCLC cell apoptosis promoting preparation. The invention also relates to application of the STM2457 in preparation of a CYP19A1 expression inhibitor. The expression of the CYP19A1 is a CYP19A1 protein; and the action concentration of the STM2457 is 5 [mu]M. The invention further relates to application of the STM2457 in preparation of an estrogen signal channel inhibitor. The estrogen signal channel is an NSCLC associated estrogen signal channel. The invention also relates to application of the STM2457 in preparation of an METTL3 activity inhibitor. The invention develops a novel therapeutic drug for NSCLC, provides a novel therapeutic scheme, and is expected to inhibit the progress of NSCLC on the basis of overcoming tumor heterogeneity; and an effective activity inhibitor is provided for METTL3, and the change rule of molecular targets and the potential mechanism of tumor inhibition are clarified. Meanwhile, other novel application of the STM2457 is researched.

The invention discloses a compound capable of simultaneously inducing EGFR and PARP protein degradation as well as a preparation method and an application thereof, and belongs to the field of medicinal chemistry. The invention provides an application of a series of novel dual-targeting degradation compounds with two independent inhibitor units and an E3 ligase ligand or pharmaceutically acceptable salts, hydrates, stereoisomers or prodrugs thereof in preparation of drugs for treating or preventing tumors. The compound provided by the invention can effectively induce E3 ligase dependent degradation of EGFR and PARP in pancreatic cancer cell lines and 1299 cells at the same time, and can effectively inhibit the growth of cancer cells. The target diversity of advanced cancers with tumor heterogeneity and reverse chemotherapy drug resistance can be solved. The method provided by the invention provides a new treatment mode for treatment of EGFR and PARP mediated tumors and / or other diseases.

The invention provides a gene for osteosarcoma typing and osteosarcoma prognosis evaluation and application thereof. Aiming at tumor heterogeneity, the difference of cytodynamics and molecular characteristics between conventional osteosarcoma and normal cancellous bone is compared, the obvious differentiation direction of osteosarcoma cells is detected based on a single-cell RNA sequencing (scRNA-seq) technology, or a gene detection kit, a gene detection chip technology or an immunohistochemical method, and the possible interaction between each cell type in the tumor microenvironment is researched. According to the differentiation direction of osteosarcoma cells, conventional osteosarcoma can be divided into three types, microenvironment characteristics of each type are described, and prognosis of type-B genotyping is verified according to cancer genome atlas (TCGA) data.

The invention relates to a three-target-point composition capable of regulating and controlling CAR immune cells and application of the three-target-point composition. The composition of the CAR immune cells comprises three-target-point regulation and control molecules and the CAR immune cells, the three-target regulation molecule comprises a tag molecule and a target binding domain, the target binding domain can specifically bind to three different targets, and the targets are related to solid tumor treatment; the CAR immune cell can express a chimeric antigen receptor, and the chimeric antigen receptor comprises a tag molecule binding domain capable of specifically binding to the tag molecule. According to the invention, a strategy of combining Her2 / VEGFR1 / VEGFR2 targeted recognition and an adjustable switch is adopted for the first time, so that the composition capable of adjusting and controlling the CAR immune cells aiming at the Her2 / VEGFR1 / VEGFR2 three targets is constructed, the influence of factors such as tumor heterogeneity and microenvironment influence on immunotherapy can be better overcome, and the safety of a CAR-T therapy is improved.

The invention provides a HER2 and MESO combined double-target CAR-T vector as well as a construction method and application thereof in cancers. Specifically, the invention provides a bispecific chimeric antigen receptor (CAR), which comprises HER2scFv, MESO scFv, a 4-1BB co-stimulatory domain and a CD3 activation domain. The bispecific CAR-T cell has a remarkable killing effect on HER2 positive target cells and MESO positive target cells, the tumor killing effect of the T cell can be improved, generated cell factors have a super addition effect, and compared with single-target CAR-T, the bispecific CAR-T cell can better remove tumor cells and relieve the antigen escape phenomenon caused by tumor heterogeneity, and the tumor killing capability of the CAR-T cells is further enhanced.

The use of genomic tests shows variability between the primary tumor and the metastases in most circumstances referred to as tumor heterogeneity. Since it is unduly invasive and difficult to obtain samples from the primary and metastatic tumors within a patient, a need exists for a method of testing chemotherapeutic effectiveness in a patient that is applicable to both primary tumor and metastases. Provided are methods of using the MiCK assay to determine the most effective drug candidate(s) for an individual patient by testing a single tumor site. In a further embodiment, the kinetic unit (KU) value obtained by analysis of cancer cells from a tumor site in an individual patient in the presence of a drug candidate is within two standard deviations of the KU value obtained by analysis of a different tumor site in the patient in the presence of the same drug candidate.

According to a gene for osteosarcoma typing and osteosarcoma prognosis evaluation, and application thereof, aiming at tumor heterogeneity, the difference of cytodynamics and molecular characteristics between conventional osteosarcoma and normal cancellous bone is compared, and based on a single-cell RNA sequencing (scRNA-seq) technology or a gene detection kit, a gene detection chip technology or an immunohistochemical method, the obvious differentiation direction of osteosarcoma cells is detected, and possible interaction among all cell types in a tumor microenvironment is researched. According to the differentiation direction of osteosarcoma cells, conventional osteosarcoma can be divided into three types, the tumor microenvironment characteristics of each type are described, and prognosis of each type is verified according to cancer genome map (TCGA) data.

The invention discloses a method for constructing a breast cancer neoadjuvant chemotherapy effect classification model. The method comprises obtaining the plasma cfDNA sequencing data of a patient with a known curative effect and performing TSSs area coverage analysis; determining a coverage difference and then performing cluster analysis to obtain a classification model. The model constructed bythe method of the invention can realize the effect prediction of neoadjuvant chemotherapy for a breast cancer patient, determines the treatment strategy of the breast cancer, and guides the breast cancer neoadjuvant chemotherapy for. The data required by the model of the present invention derives from peripheral blood and belongs to the category of noninvasive detection. The method solves the poorclinical experience, the incapability of solving tumor heterogeneity, the puncture contraindications, and the risk of tumor spread and metastasis caused by the need for invasive puncture sampling ofan existing material for predicting the efficacy of the breast cancer neoadjuvant chemotherapy,.