720 results about "Prostate cancer" patented technology

The invention discloses a polypeptide and application thereof in preparation of a medicine for preventing and / or treating cancers. The amino acid sequence of the polypeptide is shown as SEQ ID No. 1 or SEQ ID No. 2. The cancer is at least one of breast cancer, colorectal cancer, leukemia, esophageal cancer, pancreatic cancer, brain glioma, kidney cancer, skin cancer, osteosarcoma, ovarian cancer and prostate cancer. The invention designs and synthesizes the polypeptide of a targeted staphylococcus tumor protein compound SND1-MTDH containing a nuclease structural domain 1 (SND1 and a heteromucin (MTDH), finds that the polypeptide has excellent inhibitory activity on various different types of human cancer cells for the first time, and provides an optional scheme for broad-spectrum anti-cancer drugs. The polypeptide applied in the invention is simple in synthesis process and low in production cost.

The invention discloses a prostate cancer three-classification risk layering method based on an integrated learning model, and relates to the technical field of data processing and analysis. The method comprises the following steps: collecting clinical information and pathological data of a patient with increased PSA, and dividing the data into a training set and a test set; the training set is preprocessed, and prediction features are screened through LASSO regression; constructing a plurality of machine learning base models based on the features, and training and optimizing through cross validation; soft voting is constructed through an integration strategy, and an integration model is stacked; setting double thresholds according to the integrated model prediction probability, and establishing a layering rule; combining an integrated model and rules to form a three-classification model, and judging low, high and medium risks according to probabilities; and finally verifying the model diagnosis performance in the test set. According to the method, through cross-modal feature integration and ensemble learning, the method is PSAlt; accurate risk stratification is provided for 30 ng / mL people, biopsy decision-making efficiency is optimized, and excessive puncture and missed diagnosis risks are reduced.

The invention discloses a prostate cancer endocrine therapy drug resistance prediction system based on multi-model artificial intelligence. The prostate cancer endocrine therapy drug resistance prediction system comprises a data acquisition and preprocessing module, a single omics prediction module, a multi-modal feature integration module, a model training module and a prediction result output module. Multi-omics data of a patient is collected and preprocessed, data representations of omics data of different labels are generated by using priori knowledge, and an optimal single-omics prediction model is matched for the omics data of different labels based on the data representations after knowledge enhancement. And constructing a multi-omics prediction model of the prostatic cancer endocrine treatment drug resistance by using the optimal single-omics prediction model corresponding to the different label medical data by adopting Stacking, predicting the drug resistance risk of the patient within a preset time, outputting an early warning, and adjusting the treatment scheme of the patient according to the drug resistance risk. According to the method, the multi-omics data are integrated, the accurate multi-omics prediction model for the drug resistance of the endocrine therapy of the prostate cancer is constructed, and the accuracy and clinical applicability of drug resistance prediction are improved.

Provided in the present invention is a qualitative assessment and data scoring system for predicting prostate cancer in a PSA gray zone. The system comprises a magnetic resonance device, wherein a port thereof is electrically connected to a data temporary storage module, the data temporary storage module sends data to an imaging detection module by means of a network connection module, the imaging detection module is connected to a background system, and the background system comprises a scoring module and a PC unit; the scoring module acquires the value of the volume ratio of central gland prostate to total prostate on the basis of magnetic resonance imaging, so as to obtain a scoring result; and the scoring module is connected to an association result output module and a storage module, the storage module is used for storing the scoring result, and the association result output module is used for matching the scoring result with a disease risk, and outputting a matching result. The present invention can improve the accuracy of tumor detection, thereby reducing unnecessary prostate puncturing.

The invention provides a prostate cancer multi-modal data federal learning method and system, and relates to the technical field of intelligent medical treatment and distributed artificial intelligence cross, and the method comprises the steps: selecting a plurality of key feature regions in a feature space as a reference basis based on updated global feature parameters, and constructing a feature distribution topological structure; performing partition division on the feature distribution topological structure to generate a plurality of feature subspaces; calculating a spatial characteristic index according to the characteristic density and the distribution characteristic of each characteristic subspace, and generating a weight adjustment coefficient based on the spatial characteristic index; and dynamically optimizing the updated global feature parameters by using the weight adjustment coefficient to obtain optimized federal learning model parameters. Through multi-modal data feature alignment, gradient compression transmission, global gradient aggregation and parameter dynamic optimization, a complete prostate cancer multi-modal data federated learning framework is constructed, and model performance and cross-mechanism cooperation efficiency are improved.

The invention relates to prostate specific membrane antigen antibodies (anti-PSMA) and anti-PSMA antibody drug conjugates (ADCs). The invention provides a method for treating a subject using anti-PSMA ADCs in inhibiting, preventing or treating PSMA-related diseases or cancers, including prostate cancer. The disclosure also provides pharmaceutical compositions containing anti-PSMA ADCs suitable for administration to human subjects.

The invention belongs to the technical field of medical image processing, and particularly relates to a multimodal prostate cancer detection method fusing a memory mechanism and a space Transform, which comprises the following steps: constructing a multimodal prostate cancer detection network, and realizing prostate cancer detection through the multimodal prostate cancer detection network; according to the method, a Triad structured path is designed, efficient cooperation and guide fusion of multi-modal information is realized through division cooperation of dominant, auxiliary and control modalities, an encoder adopts a Swinin-Unet architecture, a window attention mechanism is combined, local details are kept, and meanwhile, the global modeling capability is enhanced; a dynamic memory unit DMU is further introduced, historical features are fused, a space gating mechanism is introduced, and the consistency and continuity of semantic expression are enhanced; in the decoding stage, an MESTrans module is embedded, and semantic alignment and boundary enhancement between modals are realized under multiple scales.

The invention relates to the technical field of computers, and discloses an automatic segmentation and intelligent plan generation method and device suitable for self-adaptive radiotherapy of prostate cancer. Comprising the following steps: acquiring medical image data of a treated object, clinical dose data of a target area and an organ at risk in a focus area of the treated object, and clinical treatment data of a preset priority level; performing automatic segmentation based on the medical image data to obtain target segmentation data; performing dose distribution prediction according to the target segmentation data to obtain initial dose distribution data, and performing iterative optimization on the initial dose distribution data by using clinical treatment data to obtain target dose distribution data of the treated object; and performing iterative optimization of a radiotherapy plan based on the target dose distribution data, and generating a target radiotherapy plan of the treated object. Therefore, on the basis of realizing accurate, efficient and automatic segmentation of the prostate cancer target region and the endangered organ, multi-round iterative optimization of dose distribution and the radiotherapy plan is carried out, and finally a high-quality target radiotherapy plan is obtained.

The present invention relates to a hetero (aromatic) ring-substituted cyclic diamine compound, the preparation thereof and the use thereof in the preparation of a drug for treating and / or preventing tumors. The structural formula of the compound is as shown in (I). The compound has a significant inhibitory effect on the growth of cells of tumors such as leukemia, lymphoma, breast cancer, melanoma, ovarian cancer, colorectal cancer, cervical cancer, lung cancer, prostate cancer, esophageal cancer, glioma, kidney cancer, nasopharyngeal carcinoma, liver cancer, gastric cancer and pancreatic cancer. Compared with the prior art, the compound of the present invention has a broad-spectrum anti-tumor activity, has a good effect on inhibiting tumors, and has an effect of degrading PD-L1 proteins, and is thus a PD-L1 immunomodulator.

The invention provides a prostate cancer biochemical recurrence prediction system based on pathological sections and a construction method. Based on a high-definition panoramic pathological section scanning image of a pathological section after a radical operation, a multi-instance algorithm based on a cyclic cross attention module and a pseudo-packet strategy is adopted, deep features of tumor images with different objective lens multiples are extracted firstly, and then feature representation of a panoramic pathological section scanning image level is generated in a weak supervision network; postoperative biochemical recurrence risk prediction results under different multiples are obtained; and then integrating model results under different scales, and predicting whether the patient finally has biochemical recurrence or not through multi-center verification. According to the system, multi-center, multi-slice and multi-scale panoramic pathological section scanning images are creatively used for training and verification, the risk of prostate cancer recurrence of a patient is predicted through pathological sections after radical treatment, the risk of recurrence of the patient within 3 years and longer time after the radical treatment is accurately predicted, and more personalized treatment is achieved.

Disclosed herein are methods of treating androgen-dependent cancers, including androgen dependent prostate cancer.

A biomimetic nano immunosubstrate material, a preparation method therefor and a use thereof. The biomimetic nano immunosubstrate material comprises a PDMS@AgNPs@ZIF-67 biomimetic immunosubstrate and a gold nanorod immunoprobe. The preparation method comprises the following steps: (S10) preparing a ZIF-67 nanomaterial; (S20) preparing a PDMS@AgNPs@ZIF-67 biomimetic polymeric material; (S30) preparing a PDMS@AgNPs@ZIF-67 biomimetic immunosubstrate material; and (S40) synthesizing a gold nanorod immunoprobe. A SERS substrate having both a synergistic enhancement effect and a molecular anchoring capability is constructed on a MOFs-modified biomimetic substrate, thereby improving the efficiency and sensitivity of prostate cancer tests.

The invention belongs to the field of chemical medicines, and particularly relates to a combined medicine for preventing and / or treating prostatic cancer, application of the combined medicine and a medicine composition. The combined medicine disclosed by the invention comprises immune cells with enhanced infiltration degree and a galectin-1 inhibitor; the immune cells with enhanced infiltration degree are natural killer (NK) cells with TTTY15-USP9Y chimera RNA knocked out, the infiltration degree and anti-tumor activity of the NK cells in a prostate cancer microenvironment can be improved, and the activated NK cells have a stronger killing effect on tumor cells in vitro. The immune cells with enhanced infiltration degree and the galectin-1 inhibitor are combined for use, so that the composition shows a synergistic effect in treatment of prostatic cancer, and has a wide application prospect.

The invention discloses a novel polypeptide, a polypeptide derivative and application thereof, and belongs to the technical field of biological medicine. The invention specifically relates to a specific sequence, a discovery process, a specific anti-tumor type, a long-acting modification mode and application of the novel polypeptide. The tumors comprise one or more of brain glioma, neuroblastoma, head and neck cancer, esophagus cancer, thyroid cancer, lung cancer, liver cancer, kidney cancer, breast cancer, cervical cancer, uterine cancer, ovarian cancer, colon cancer, small intestinal cancer, ileocecum cancer, stomach cancer, bladder cancer, pancreatic cancer, prostate cancer, bile duct cancer, melanoma, sarcoma, myeloma, lymphoma and leukemia; the compound has the specific effect of inhibiting proliferation and / or metastasis of tumor cells, is wide in treatment spectrum and has important treatment value in various tumors.

A method for treating prostate cancer by administering a first dose of a polyamine inhibitor for a first interval at a beginning of a first treatment cycle; a second dose of the polyamine inhibitor in combination with a dose of an androgen, or a derivative thereof, at a second interval during the first treatment cycle; and a dose of an antiandrogen at a third interval during the first treatment cycle is disclosed.

The invention provides a group of marker combinations related to the prostatic cancer, wherein the marker combinations comprise hsa-miR-12125, hsa-miR-21, hsa-miR-103 and hsa-miR-9903, and the application of the marker combinations in preparation of a prostatic cancer detection reagent and a prostatic cancer treatment medicine is researched and developed at the same time. The prostate cancer detection reagent provided by the invention comprises specific primers designed for the four markers, has high sensitivity and specificity, and improves the accuracy of prostate cancer diagnosis by jointly detecting and diagnosing the prostate cancer through the four markers. The medicine for treating the prostatic cancer, provided by the invention, comprises an hsa-miR-12125 inhibitor, an hsa-miR-21 inhibitor, an hsa-miR-103 analogue and an hsa-miR-9903 analogue, and can be used for effectively inhibiting the occurrence and development of the prostatic cancer.

The present invention relates to methods of treating prostate cancer in a subject in need thereof, comprising administering a therapeutically effective amount of a KLK2xCD3 bispecific antibody or bispecific binding fragment thereof to the subject to treat the prostate cancer.

The invention provides a compound containing a nitrogen heterocyclic derivative PARP1 inhibitor or a pharmaceutically acceptable salt, a stereoisomer, a solvate, a polymorphic substance, an isotope derivative or a prodrug of the compound, a preparation method of the compound, and medical application of the compound in prevention or treatment of diseases or symptoms related to PARP1 expression increase. The present invention provides methods of treating cancers such as prostate cancer, pancreatic cancer, breast cancer, ovarian cancer, and the like. # imgabs0 #

The invention discloses an ROS-responsive prostate cancer targeting prodrug as well as a preparation method and application thereof, and belongs to the technical field of biological medicines. The prodrug is formed by covalently linking a prostate cancer targeting peptide SYEELR, a ROS (reactive oxygen species) response type ketal thiol (TK) connexon and an active molecule Devimistat. The preparation method comprises the following two steps: firstly, coupling Devimistat with a TK linker to obtain an intermediate Dev-TK, and then coupling the intermediate Dev-TK with an SYEELR peptide fragment to obtain a target product. The prodrug can specifically break and release Devimistat in a tumor high active oxygen microenvironment, and active targeting delivery is realized by virtue of the SYEELR peptide. The invention provides a novel prostatic cancer treatment strategy with accurate targeting, controllable release, enhanced curative effect and toxicity reduction potential.

The invention provides a prostate Glison automatic grading method based on multi-level visual basic model feature fusion. The prostate Glison automatic grading method comprises the following steps: step 1, collecting and preprocessing data; 2, training a basic model; 3, extracting image features under multiple resolutions by using the trained model, and extracting single cell features by using a single cell morphology and topology atlas framework sc-MTOP; and step 4, finishing automatic grading of the prostate Glison by adopting the Glison grading prediction model. According to the method, the multi-resolution image features and the single cell features are fused, so that more accurate Glison grading of the prostatic cancer pathological image is realized. By means of multi-center data collection and self-supervised training, the adaptability and generalization ability of the model to different data sources are improved. A cross attention module is introduced, multi-level features are fully integrated, and the classification accuracy is improved. And in combination with expert correction feedback and a pre-training basic model, the utilization efficiency and the model performance of the label-free data are further optimized.

The present invention relates to a pharmaceutical composition for oral administration, for example in the form of a tablet or a powder suitable to be filled into a capsule shell, comprising 2-(isoindolin-2-ylmethyl)-5-((1-(methylsulfonyl)- piperidin-4-yl)methoxy)-4H-pyran-4-one (I) or a pharmaceutically acceptable salt thereof as an active ingredient. Compound (I) or a pharmaceutically acceptable salt thereof is a selective inhibitor of CYP11A1 enzyme and is useful in the treatment of hormonally regulated diseases such as cancer including prostate cancer and breast cancer.

The present provides a method of treating ovarian cancer, breast cancer, gastrointestinal cancer, lung cancer, cancer of the brain or prostate cancer in a subject in need thereof, comprising administering to the subject a first amount of a selective PARP1 inhibitor or a pharmaceutically acceptable salt thereof, and a second amount of an ATR inhibitor or a pharmaceutically acceptable salt thereof. Also disclosed are compositions and kits comprising a PARP inhibitor and ATR inhibitor.

The present invention relates to methods, systems and kits for the diagnosis, prognosis and the determination of cancer progression of prostate cancer in a subject. The invention also provides clinically useful genomic classifiers for predicting prostate cancer metastasis and identifying tumor aggressiveness. The methods, systems and kits can provide expression-based analysis of biomarkers for purposes of predicting metastatic disease and lethal prostate cancer in a subject. Further disclosed herein, in certain instances, are probe sets for use in predicting prostate cancer metastasis in a subject. Classifiers for predicting prostate cancer metastasis are provided. Methods of treating cancer based on tumor aggressiveness are also provided. The methods and classifiers of the present invention are also useful for predicting early prostate cancer metastasis.

Disclosed herein is Differential Subclone Eradication and Resistance Analysis (DSER), a method developed to identify molecular targets for improved therapy by direct comparison of genomic features of eradicated and resistant subclones in pre-and post-treatment samples from a patient with BRCA2-deficient metastatic prostate cancer. FANCI and EYA4 were identified as candidate DNA repair-related targets for converting subclones from resistant to eradicable, and RNAi-mediated depletion of FANCI confirmed it as a potential target. The EYA4 alteration was associated with adjacent L1 transposon insertion during cancer evolution upon treatment. L1 activation was inhibited by the antiretroviral drug azidothymidine. In conclusion DSER provides an informative intermediate step toward effective precision cancer medicine, especially in cases with dramatic but temporary metastatic tumor regression. L1 transposon activation may be a modifiable source of cancer genomic heterogeneity, suggesting the potential of leveraging newly discovered triggers and blockers of L1 activity to overcome therapy resistance.

The present disclosure provides a high-energy, low toxicity radiopharmaceutical composition comprising actinium that performs as an anti-tumor agent for targeted radionuclide therapy and has improved shelf-life stability. Specifically, the radiopharmaceutical composition may include 225Ac-PSMA I&T, sodium ascorbate, and optionally hydrochloric acid. The radiopharmaceutical composition may be suitable for administration to a patient in need thereof, such as for the purpose of treating prostate cancer.

The invention belongs to the technical field of medicines, and provides a preparation technology of a sterile injection of rerugolix, which comprises the following steps: redissolving freeze-dried powder consisting of raw material medicines and auxiliary materials by using sterile water for injection, slowly releasing the rerugolix within 2-8 weeks, maintaining the dynamic balance of blood concentration, and preparing the sterile injection of the rerugolix by using the freeze-dried powder to prepare the sterile injection of the rerugolix. Release of gonadotropin is effectively controlled, and the pharmaceutical composition is used for treating indications such as prostatic cancer, uterine fibroma and endometriosis.

The invention provides an organoid chip for screening micro-ecological drugs as well as application and a preparation method of the organoid chip, and relates to the technical field of biological medicines. The invention provides a chip integrating intestinal epithelium, a prostate cancer organ and a bladder cancer organ, which is used for researching how microecological preparations, such as probiotics, metabolites and the like, affect tumor microenvironment and immunotherapy effects. The chip can simulate interaction of intestinal tract-tumor axis, and provides an in-vitro evaluation system for precise tumor immunotherapy.

Diagnosing prostate cancer typically involves invasive measures such as biopsy in which tissue is removed and graded by pathologists. Non-invasive measures like multi-parametric MRI can be used to examine and grade lesions using the PI-RADS scale; however, the achievable image resolution is motion-limited. A new paradigm, magnetic resonance histopathology (MRH), is disclosed which aims to assess tissue texture at sub-millimeter resolution through rapid clinical acquisition procedures. MRH capability of identifying cancerous tissue in the prostate via an in silico analysis is demonstrated, recreating the MRH measurement process on a set of high resolution, pathologist-annotated histology slides. A dataset of spectral intensities at sub-millimeter wavelengths is created and a deep learning model trained to classify spectral data is underlying normal or tumor tissue. A set of spatial frequencies to optimize diagnostic power within the constraint of limited acquisition time is identified. Beyond single-region classification, the disclosed approach and architectures integrate spatial context and local information, the inclusion of which improves model performance and de-noises the inferential results. Applications of the trained models to unlabeled, high-resolution 3D MRI data is demonstrated in addition to algorithms for estimating the physical length scale of lesions identified by the model.

The present disclosure relates to novel deuterated retinoidal compounds and methods of preparing the deuterated retinoidal compounds. The present disclosure also provides pharmaceutical compositions including the deuterated retinoidal compounds, and uses of the deuterated retinoidal compounds to treat diseases including breast and prostate cancers.

The invention relates to a hetero (aromatic) ring substituted cyclic diamine compound, preparation thereof and application of the hetero (aromatic) ring substituted cyclic diamine compound in preparation of drugs for treating and / or preventing tumors. The structural formula of the compound is shown as (I). The compound has an obvious growth inhibition effect on tumor cells of leukemia, lymphoma, breast cancer, melanoma, ovarian cancer, colorectal cancer, cervical cancer, lung cancer, prostate cancer, esophagus cancer, glioma, kidney cancer, nasopharynx cancer, liver cancer, stomach cancer, pancreatic cancer and the like. The compound disclosed by the invention has broad-spectrum anti-tumor activity; the compound has a good tumor inhibition effect and a PD-L1 protein degradation effect, and is a PD-L1 immunomodulator.