102 results about "Brain metastasis" patented technology

The present invention discloses substituted 2-amino-9-(3,3-difluoropiperidin-4-yl)-7,9-dihydro-8H-purin-8-one compounds compounds having the structural formula represented by formula (I)： The substituted 2-amino-9-(3,3-difluoropiperidin-4-yl)-7,9-dihydro-8H-purin-8-one compounds, derivatives and pharmaceutically acceptable salts thereof of the present invention are capable of acting as a drug characteristic of a protein kinase inhibitor, in particular for the expression of a protein through a DNA-dependent protein kinase (DNA-PK) and can be used to treat or prevent disorders associated with abnormal protein kinase activity, such as cancer, cancer with brain metastases, cancer with meningeal metastases, glioma, glioblastoma, DIPG, and the like either as monotherapy or combination with other treatments, such as radiation therapy or chemotherapy.

The present disclosure relates generally to methods for treating or preventing central nervous system (CNS) metastases with a KRAS inhibitor, and more specifically to treating CNS metastases with a pyridopyrimidine derivative.

The invention discloses a multi-task lung cancer brain metastasis lifetime prediction method based on multi-modal data fusion, and relates to the field of medical image processing, and the method comprises the steps: obtaining non-small cell lung cancer CT image data, gene data and clinical data; performing focus segmentation on the non-small cell lung cancer CT image data; feature extraction is carried out based on the focus segmentation result, and radiomics features and depth image features are obtained; performing feature extraction on the gene data to obtain gene features; missing value deletion and numeralization preprocessing are carried out on the clinical data to obtain clinical features; local cross-modal attention fusion is carried out on the radiomics features and the depth image features; performing global cross-modal attention fusion on the preliminary mixed image features, the gene features and the clinical features to obtain original mixed features; and performing conditional guidance diffusion based on the original mixed features to obtain a lung cancer brain metastasis classification judgment result and a lifetime prediction risk. According to the invention, the lifetime prediction accuracy and stability can be improved.

The invention discloses a non-small cell lung cancer brain metastasis prediction method and device, and relates to the field of non-small cell lung cancer brain metastasis prediction. The method comprises the following steps: acquiring two-dimensional non-small cell lung cancer CT image data; inputting two-dimensional non-small cell lung cancer CT image data into the trained focus boundary segmentation model, and outputting a focus region segmentation image; the focus boundary segmentation model adopts an alternating network architecture based on a transformer block and a double-current Mangbar-transformer block; according to the focus area segmentation image, utilizing the trained non-small cell lung cancer brain metastasis prediction model to obtain a prediction result of whether the non-small cell lung cancer CT image data is a brain metastasis label or not according to the non-small cell lung cancer CT image data; the non-small cell lung cancer brain metastasis prediction model is a deep learning classification network of a heterogeneous axial cross attention mechanism with discrete wavelet transform processing. According to the method, the accuracy of predicting the brain metastasis result by using the non-small cell lung cancer CT image data can be improved.

The invention provides a lung cancer brain metastasis identification method and system based on multi-modal data, and the method comprises the steps: obtaining clinical pathology data, lung CT image data and brain multi-parameter MRI image data of a user, and carrying out the data preprocessing; performing anomaly detection on the preprocessed data to obtain a corresponding anomaly score; weighting various abnormal scores, and performing normalization processing to obtain a comprehensive abnormal score; determining a prediction threshold value of the brain metastasis risk of the lung cancer according to the maximum Youden index; comparing the comprehensive abnormal score with a prediction threshold, and determining a prediction result; when the prediction result shows that the user is a lung cancer brain metastasis patient, dividing the preprocessed brain multi-parameter MRI image data into a plurality of areas with preset sizes, and respectively calculating reconstruction errors; and mapping the reconstruction error of each region to generate an error mapping graph so as to reflect the high-risk region of the lung cancer brain metastasis.

The invention discloses a construction method, a recognition method and a system for simulating lung cancer metastasis cells in cerebrospinal fluid based on diffraction imaging and a deep learning technology. The construction method comprises the following steps: culturing a plurality of lung cancer cell lines which are easy to cause brain metastasis, collecting whole blood of a healthy person and splitting red blood cells; the method comprises the following steps: respectively acquiring diffraction images of cultured cells through a polarization diffraction imaging flow cytometry with a TDI camera to obtain a pair of diffraction image pairs with S polarization and P polarization; performing image processing on the obtained diffraction cell image pair, and establishing a training image data set and a test image data set; and establishing a convolutional neural network, and training the convolutional neural network according to the training image data set to obtain a model for identifying the lung cancer metastatic cells in the cerebrospinal fluid. When in use, a cerebrospinal fluid sample of a patient is collected, S polarization and P polarization image pairs are obtained, and the trained model is input to respectively extract S polarization and P polarization image features of cells for feature recognition, so that whether the current sample contains lung cancer cells or not is predicted.

The invention provides a lung cancer brain metastatic tumor preoperative risk prediction method based on a hybrid model, and relates to the field of medical image analysis and preoperative prediction, and the method comprises the steps of data preprocessing, model building, model training, model prediction and model evaluation. Wherein the construction of the model VKT is combined with KAN and Attention, and the model VKT is designed into a unique double-branch model, namely a ConvKan branch and an LGAttention branch. A ConvKan branch adopts a convolution BCBR module and a TCKan module, cross-channel information interaction is enhanced through parallel Token Kan and Channel Kan processing, and deep feature learning is promoted through residual connection. The LGAttention branch introduces local attention and global attention, so that the fine-grained structure and the overall semantics of the image can be effectively captured. By fusing the output features of the two branches, the VKT architecture not only retains the powerful capability of CNN in local feature extraction, but also gives full play to the advantages of Transform in global information modeling, and improves the interpretability of the model by means of KAN, thereby becoming an ideal choice for medical image analysis.

The invention provides a lung cancer brain metastasis risk prediction method and system, and the method comprises the steps: obtaining the brain MRI image data of a user, and carrying out the data preprocessing; whole-brain feature extraction and partition feature extraction based on an AAL template are carried out on the preprocessed data, and whole-brain features and partition features are combined to obtain a feature matrix; according to the preprocessed brain MRI image data of the user suffering from lung cancer brain metastasis, training an auto-encoder to obtain a trained auto-encoder; inputting the feature matrix into the trained auto-encoder, and calculating a reconstruction error; according to the reconstruction error, an isolated forest method is adopted to further screen abnormal areas, and an abnormal score is generated for each sample; according to the reconstruction error and the abnormal score, the abnormal score of the whole brain feature and the abnormal score of the partition feature are calculated, the high-risk region of the brain can be accurately marked by combining the abnormal detection of the whole brain feature and the partition feature, and a basis is provided for personalized PCI treatment.

The invention provides a method and system for analyzing lung cancer brain metastasis organoid cell subpopulation and functional characteristics, and the method comprises a series of steps: data quality control, batch effect removal, cell grouping, copy number variation inference, quasi-time sequence analysis, function enrichment analysis, and drug sensitivity analysis before and after radiotherapy. Single cell transcriptome sequencing data obtained after organoid culture is subjected to personalized analysis, heterogeneity of tumor cells and sensitivity of the tumor cells to drugs after radiotherapy are described, and the characteristics of all cell subgroups in the lung cancer brain metastasis organoid and the effect of the cell subgroups in the tumor microenvironment can be accurately analyzed; powerful support is provided for mechanism research and precise medicine of lung cancer brain metastasis.

The invention discloses a human small cell lung cancer brain metastasis organoid culture medium and a culture method. According to the culture medium, an advanced DMEM / F12 culture medium is used as a basic culture medium, and the following components are added: 2 to 5 [mu] M of GlutaMax, 8 to 10 [mu] M of HEPES, 1 * to 2 * of B27, 500 [mu] M of SB202190, 5 to 10 [mu] M of Y-27632, 0.5 [mu] M of A83-01, 0.5 to 2 [mu] M of N-Acetyl-L-cysteine, 5 mM of Nicotinamide, 25 to 100 ng / ml of recombinant human FGF7, 100 to 500 ng / ml of recombinant human FGF10, 100 to 200 ng / ml of Human Noggin, 50 to 500 ng / ml of Human R-Spondin-1, 50 to 100 ng / ml of According to the culture method, TryPLE Express is used for dissociation, the time is short, the activity of dissociated single cells is high, and the success rate of organoid culture can be increased to the maximum extent. Meanwhile, by combining with a culture medium with an optimized formula proportion, formation and growth of brain metastatic organs of the human small cell lung cancer can be promoted, and the construction success rate is increased.

The invention discloses an application of a training immune agonist in preparation of a drug for sensitizing radiotherapy treatment of tumors, and researches show that the training immune agonist significantly activates immune response of a body by promoting expression of inflammatory cytokines, enhancing phagocytic ability of macrophages, recruiting immune cells and amplifying an immune activation effect, so that the immune response of the body is enhanced. The sensitivity of tumor cells to radiotherapy is improved, and a dual mechanism of'radiotherapy sensitization-immune synergy 'is formed, so that the bottleneck of the traditional radiotherapy curative effect is broken through, the local control rate of radiotherapy is improved, and the recurrence risk is reduced. Experiments prove that the training immune agonist combined with radiotherapy has a remarkable treatment effect on various highly invasive tumors (such as brain glioma and lung cancer brain metastasis) and common malignant tumors (such as colon cancer and lung cancer), and shows wide applicability. The invention provides a new combined therapy direction for tumor treatment, is expected to improve the prognosis of patients, prolong the lifetime and improve the life quality, and has important clinical transformation value.

In one aspect, antibodies that bind to subdomain II of human HER2 are provided. In another aspect, antibodies comprising a light chain polypeptide that pairs with both a heavy chain polypeptide for binding to subdomain II of human HER2 and a heavy chain polypeptide for binding to subdomain IV of human HER2 are provided. In a further aspect, antibodies that bind to both subdomain II and subdomain IV of human HER2 comprising a common light chain polypeptide are provided. Methods of treating a cancer or treating brain metastasis of a cancer using these antibodies are also provided.

The invention discloses construction and application of a lung cancer brain metastasis prognosis model based on a plasma miRNA combined marker. A prognosis model of lung cancer brain metastasis is constructed based on plasma miRNA combined markers, the plasma miRNA combined markers comprise miR-31-5p, miR-219-5p, miR-1-3p, miR-130a-5p, miR-452-3p, miR-598-3p, miR-9-5p, miR-1246, miR-196a-5p and miR-210-3p, the prognosis model obtains a miRNA expression index according to the expression quantity of each plasma miRNA, and a predicted survival rate is obtained according to the miRNA expression index and clinical information and serves as a prognosis prediction result; the prognosis model is used for prognosis prediction of lung cancer brain metastasis. The prediction model and the prognosis prediction system both have high sensitivity and accuracy.

A quinazoline derivative (represented by the formula (I)) salt's crystal form, a preparation method and application are provided; specifically, the hydrochloride crystal form A, B, C, D, F, H, I, Sulphate crystal form A, Maleate crystal form A, Succinate crystal form A, Adipate crystal form A, Glycolate crystal form A, Malate crystal form A, Fumarate Salt crystal form A, besylate crystal form A, B, C, benzoate crystal form A, hippurate crystal form A and oxalate crystal form A of the quinazoline derivative represented by formula (I). The salt crystal form provided by the present invention has good stability, which can be used in the treatment of non-small cell lung cancer brain metastasis, meningeal metastasis, primary brain cancer or glioma, etc., and has good bioavailability, which is of great significance for further research on the efficacy of such solid drugs.

The invention discloses an application of pegylated irinotecan in preparation of a medicine for preventing and / or treating triple-negative breast cancer brain metastasis diseases, which is shown by in-vivo imaging observation and lifetime observation of high, medium and low dose groups of pegylated irinotecan with a specific structure. The high-dose group, the medium-dose group and the low-dose group all have a definite anti-tumor effect, bioluminescence signal values are inhibited to different degrees, the lifetime is prolonged, and the lifetime of the high-dose group and the lifetime of the medium-dose group are remarkably longer than that of the NKTR-102 group.

The invention provides application of an arsenene nano preparation and / or beta-elemene in preparation of a product for treating brain tumors, and belongs to the technical field of biology. The arsenene nano preparation and / or beta-elemene are / is applied to brain glioma and lung cancer brain metastatic tumor model mice, so that tumor cells can be effectively killed, tumor metastasis can be inhibited, in-vivo immune response can be activated, maturation of dendritic cells can be promoted, NK cells and CD8 + T cells can be effectively activated, and the secretion amount of tumor suppression cell factors can be increased. Meanwhile, the beta-elemene effectively reduces cardiotoxicity caused by accumulation of the arsenene nano preparation in vivo.

The invention belongs to the field of biological medicines, and discloses an (R)-3-(1-([1, 1 '-biphenyl]-2-yl) ethyoxyl) pyridine-2-amine derivative as well as a synthesis method and application thereof. A compound with a structure as shown in a general formula I of the derivative or pharmaceutically acceptable salt, hydrate, solvate, polymorphic substance, tautomer, stereoisomer, isotope derivative or prodrug thereof has higher ROS1 or ALK protein kinase inhibitory activity; the compound has high anti-proliferative activity on human non-small cell lung cancer and solid tumors such as brain metastatic tumors, glioblastoma and breast cancer, and can be used for preparing drugs for treatment and / or prevention and / or delay and / or adjuvant treatment and / or treatment of tyrosine protein kinase, especially diseases mediated by ROS1 and ALK kinase and mutant kinase thereof.

The invention discloses a lung cancer cell brain metastasis prediction system and method, and belongs to the field of computer image processing.The lung cancer cell brain metastasis prediction method comprises the steps that a primary lung cancer CT image sequence, a same-period pathological examination result and a brain nuclear magnetic report are collected; preprocessing the primary lung cancer CT image sequence, and marking the preprocessed CT image sequence as a first image sequence; obtaining a prediction classification result according to a lung cancer brain metastasis sniping model BM-Sniper; the aggregation feature vector is analyzed and processed, linear classification is executed, a classification prediction result is obtained, and linear classification is obtained through a support vector machine model or a Bayesian classifier. Through primary lung cancer CT image sequence processing, feature extraction of a lung scanning image is carried out according to an image feature extraction mode to obtain an aggregation feature vector, and the aggregation feature vector is input into a classification module of a prediction model to output a classification result, so that whether a detected object is subjected to lung cancer brain metastasis is predicted; and an intermediate result with high accuracy is provided for auxiliary diagnosis of a doctor.

The application belongs to the technical field of biology and particularly relates to application and a kit of CoL10A1. CoL10A1 is highly expressed in BC tissues and lowly expressed in normal tissues, CoL10A1 is highly expressed at mRNA and protein levels in BCBM tissues, therefore, application of a reagent for detecting CoL10A1 expression in preparation of a breast cancer brain metastasis diagnosis product is proposed, and the diagnosis product can also be used for diagnosing breast cancer.

The invention discloses treatment of EGFR mutation positive non-small cell lung cancer brain metastasis by administering an effective dose of an EGFR inhibitor. The EGFR inhibitor is N-(2-((2-(dimethylamine) ethyl) (methyl) amine)-4-methoxy-5-((4-(1-deuterated methyl-1H-indol-3-yl) pyrimidine-N '-2-yl) amine) phenyl) acrylamide mesylate.

Targeting Metabolic Pathways with MNK Inhibitors The invention belongs to the field of medicine and concerns the treatment of diseases related to aberrant upregulated de novo lipid biosynthesis using a MAPK interacting kinase (MNK) inhibitor, especially for the prophylaxis or treatment of breast cancers, prostate cancers, obesity, atherosclerosis, diabetes mellitus, nonalcoholic fatty liver disease, nonalcoholic steatohepatitis, chronic kidney disease, and neurological disorders. An aspect of the invention relates to the use of an MNK inhibitor designated (4-(3-((2- (dimethylamino)pyridin-4-yl)ethynyl)pyrazolo[1,5-a]pyrimidin-5-yl)phenyl)(morpholino) methanone, for the prophylaxis or treatment of triple-negative breast cancer and brain metastases therefrom.

The invention relates to application of GC7 in inhibiting proliferation or metastasis of cancer cells, in particular to inhibition of proliferation or metastasis of lung adenocarcinoma cells, and more particularly inhibition of proliferation or metastasis of the lung adenocarcinoma cells in the brain. On the basis, the GC7 can be developed into a medicine for inhibiting proliferation or migration of lung cancer cells, particularly a medicine for inhibiting brain metastasis of the lung cancer cells.

The application discloses application of tenapanol in preparation of a medicine for inhibiting tumor brain metastasis. The application targets neutrophils which are recruited in brain metastasis foci and promote tumor growth, screens out an inhibitor tenapanol for a neutrophil chemotactic receptor FPR2, inhibits the neutrophil recruitment to the brain and the subsequent promotion of tumor cell clonal growth by inhibiting the combination of the receptor and SAA1 which is specifically up-regulated in metastatic tumor cells, and thus the therapeutic effect of inhibiting the progression of intracranial lesions is achieved.

The invention discloses a substituted 2-amino-9-(3, 3-difluoropiperidine-4-yl)-7, 9-dihydro-8H-purine-8-ketone compound with a structural formula as shown in formula (I): (I) The substituted 2-amino-9-(3, 3-difluoropiperidine-4-yl)-7, 9-dihydro-8H-purine-8-ketone compound disclosed by the invention as well as a derivative and pharmaceutically acceptable salt thereof, and a preparation method of the substituted 2-amino-9-(3, 3-difluoropiperidine-4-yl)-7, 9-dihydro-8H-purine-8-ketone compound. The compound can be used as a protein kinase inhibitor drug to play a role, especially can inhibit protein expression induced by DNA-PK, and can be used for treating or preventing diseases related to abnormal protein kinase activity. The compound can be used for treating cancer, such as cancer, cancer accompanied with brain metastasis, cancer accompanied with meningeal metastasis, glioma, glioblastoma, diffuse endogenous bridge glioma (DIPG) and the like, and can be independently applied or combined with other treatment modes (such as radiation therapy or chemotherapy).

The invention discloses an application of a small molecule compound in preparation of a medicine for treating breast cancer. The MEN 10207 is screened through molecular docking analysis, and the capability of the MEN 10207 for remarkably inhibiting proliferation, migration and invasion of breast cancer cells is verified in MDA-MB-231 cells, so that the MEN 10207 has the potential of serving as a breast cancer brain metastasis inhibitor. A further research discovers that the MEN 10207 does not show obvious toxicity in the zebra fish and also shows good tolerance in a mouse intravenous injection test. After the MEN 10207 treats the zebra fish transplanted with the breast cancer cells, the survival and migration capabilities of the breast cancer cells in the zebra fish body are obviously reduced; after the MEN 10207 treats a mouse model with breast cancer brain metastasis, the colonization of breast cancer cells in the mouse brain is also obviously reduced, which proves that the MEN 10207 has the activity of resisting breast cancer brain metastasis in vivo.

Described herein are methods of treating a MTAP-null lung cancer in a patient comprising administering to the patient a PRMT5 inhibitor and an anti-PD1 antibody, optionally in combination with carboplatin and either paclitaxel or pemetrexed. Further described herein are methods of treating a MTAP-null cancer in a patient also suffering from brain metastases comprising administering to the patient a PRMT5 inhibitor.

The present invention relates to the field of tumor therapy and molecular immunology, relates to a pharmaceutical use of an anti-PD-1-anti-VEGFA bispecific antibody, and in particular, to a use of the anti-PD-1-anti-VEGFA bispecific antibody or a pharmaceutical combination of said antibody and a chemotherapy drug in the preparation of a drug for treating non-small cell lung cancer with brain metastases. The bispecific antibody can effectively treat non-small cell lung cancer with brain metastases, has high safety, and has good prospects of application.

The invention belongs to the field of tumor treatment and molecular immunology, and relates to medical application of an anti-VEGFA-anti-PD-1 bispecific antibody. Specifically, the invention relates to application of an anti-VEGFA-anti-PD-1 bispecific antibody or a pharmaceutical composition of the anti-VEGFA-anti-PD-1 bispecific antibody and chemotherapeutic drugs in preparation of drugs for treating non-small cell lung cancer brain metastasis. The bispecific antibody can effectively treat non-small cell lung cancer brain metastasis, is high in safety and has a good application prospect.

To provide methods for treating cancer.SOLUTION: Provided is a drug for inhibiting tumor growth or causing tumor regression in a subject with estrogen receptor alpha-positive breast cancer brain metastasis, the subject having one or more estrogen receptor alpha mutations selected from the group consisting of Y537S, Y537C, Y537N, D538G, and S463P. The drug comprises, as an active ingredient, a therapeutically effective amount of RAD1901 having a given structure, or a salt or solvate thereof, which is used in combination with palbociclib.SELECTED DRAWING: None

Described is a method of preventing, reducing the risk of, or treating, brain metastases in a subject suffering from cancer. Described is also a method of preventing, reducing the risk of, or treating, invasive and / or metastatic brain cancer in a subject. Advantageously, the methods comprise administration of at least one blood-brain barrier permeable drug selected from the group consisting of Vaughan Williams Class 1d anti-arrythmia drugs, such as from ranolazine, eleclazine, GS561587 and CPD 458967.