42 results about "Complete remission" patented technology

The invention discloses a group of gene markers for predicting or evaluating neoadjuvant chemotherapy response of breast cancer and application of the gene markers. The gene markers comprise CCNA2, CCND1, CD52, ESR1 and FAM234B. The system for predicting or evaluating the neoadjuvant chemotherapy reaction of the breast cancer is constructed on the basis of the gene marker, and can accurately predict or evaluate whether the breast cancer patient has the risk that complete remission cannot be achieved after neoadjuvant chemotherapy, and discriminate whether the breast cancer patient can benefit from the neoadjuvant chemotherapy reaction; therefore, whether the breast cancer patient can be subjected to neoadjuvant chemotherapy or not is accurately predicted, medical intervention is performed in time, and the method has important clinical reference value.

The invention discloses an esophageal cancer neoadjuvant chemotherapy and post-immunization pathology complete remission prediction system and method, and relates to the field of medical image processing, and the system comprises an image processing module which is used for carrying out the standardized processing of an input image, and segmenting a tumor region in the image; the feature extraction module is used for extracting voxel-level radiomics features from the tumor area; the feature screening module is used for screening out a plurality of voxel-level radiomics features with the most predictive capability; and the pathology prediction module is used for generating a comprehensive feature vector according to the segmented input image and the screened voxel-level radiomics features, and predicting the curative effect of the combination of neoadjuvant chemotherapy and immunotherapy according to the comprehensive feature vector. According to the technical scheme provided by the invention, the accuracy of predicting complete pathologic remission after neoadjuvant chemotherapy and immunotherapy of esophageal cancer can be improved, the defect that the heterogeneity in tumors cannot be considered in a traditional imaging omics technology is overcome, and the method has a relatively high application value.

Provided are adoptive cell therapy methods involving the administration of doses of cells for treating B cell malignancies. The cells generally express recombinant receptors such as chimeric antigen receptors (CARs). In some embodiments, the methods are for treating subjects with chronic lymphocytic leukemia (CLL). In some embodiments, the methods are for treating subjects with non-Hodgkin lymphoma (NHL). In some embodiments, the methods involve prior administration of a lymphodepleting therapy, such as prior administration of fludaribine and / or another lymphodepleting chemotherapeutic agent, for example cyclophosphamide. In some embodiments, features of the methods include an increase in complete remission, overall survival and / or progression free survival of subjects treated in accord with the provided methods.

The invention discloses a longitudinal CT image-assisted rectal cancer neoadjuvant radiotherapy and chemotherapy treatment reaction evaluation device, which comprises a focus area segmentation module, a rectum focus area detection module, a rectum focus area detection module, a rectum focus area detection module, a rectum focus area detection module, a rectum focus area detection module, a rectum focus area detection module, a rectum focus area detection module and a rectum focus area detection module, obtaining a standardized three-dimensional tumor area; a feature fusion module extracts deep learning features of a focus area after segmentation at two time points before neoadjuvant radiotherapy and chemotherapy and before an operation from the three-dimensional tumor area, and performs weighted fusion on the deep learning features at the two time points through a dynamic attention weight layer to obtain longitudinal comprehensive features representing tumor treatment response changes; and the prediction module fuses the longitudinal comprehensive characteristics and clinical baseline data to construct a multi-modal prediction model, and outputs a treatment response prediction result of the rectal cancer patient on neoadjuvant chemoradiotherapy, so that the prediction accuracy of pathological complete remission of the rectal cancer patient can be improved, and the prognosis of the patient and the utilization efficiency of medical resources can be improved.

The invention discloses a pathological complete remission prediction method and device for non-small cell lung cancer neoadjuvant chemotherapy, and relates to the field of medical imagines.The method comprises the steps that a preoperative medical image and preoperative clinical data of a patient to be predicted are obtained; inputting the preoperative medical image and the preoperative clinical data into the trained pathology complete remission prediction model, and outputting a pathology complete remission result of the patient to be predicted by the pathology complete remission prediction model; the pathologic complete remission prediction model is constructed by using pre-treatment radiomics features, post-treatment radiomics features, difference-radiomics features, deep learning features and sample clinical data. Whether a non-small cell lung cancer patient receiving neoadjuvant chemotherapy reaches complete pathological remission or not is represented in a non-invasive mode, so that medical staff are assisted in formulating a personalized treatment scheme, and the clinical result of the patient is improved.

The invention discloses a pathological complete remission prediction method and device based on difference radiomics, and relates to the field of medical images.The method comprises the steps that a preoperative medical image and preoperative clinical data of a patient to be predicted are obtained; inputting the preoperative medical image and the preoperative clinical data into the trained pathology complete remission prediction model, and outputting a pathology complete remission result of the patient to be predicted by the pathology complete remission prediction model; the pathology complete remission prediction model is constructed by a joint prediction model and prediction factors screened from sample clinical data, and the joint prediction model is constructed by utilizing pre-treatment radiomics characteristics, post-treatment radiomics characteristics and difference-radiomics characteristics. Whether a non-small cell lung cancer patient receiving neoadjuvant immunochemotherapy reaches complete pathological remission or not is represented in a non-invasive mode, so that medical staff are assisted in formulating a personalized treatment scheme, and the clinical result of the patient is improved.

According to the breast cancer prediction model construction system based on the MRI image and the storage medium provided by the invention, the model for predicting the neoadjuvant chemotherapy pathological alleviation condition and prognosis of the breast cancer patient is constructed by combining the dynamic change of the blood vessel characteristics and the clinical pathological characteristics, so that the system has relatively high accuracy and clinical practicability, and is suitable for popularization and application. And making of an individualized adjuvant therapy scheme is facilitated. The method can early predict breast pathology remission and long-term prognosis, and can early and accurately predict neoadjuvant chemotherapy curative effect and long-term prognosis of breast cancer patients. The model predicts whether a patient can achieve complete relieving of breast pathology or not by analyzing changes of breast tumor blood vessel characteristics in the chemotherapy process and correlation with clinical factors, and further predicts the recurrence-free lifetime of the patient, so that a reference basis is provided for individualized treatment.

The invention provides a breast cancer adjuvant therapy pathology complete remission prediction method and electronic device.The breast cancer adjuvant therapy pathology complete remission prediction method comprises the steps that at the first stage, based on multi-time-point and multi-parameter MRI images of a patient before and after adjuvant therapy, the breast cancer adjuvant therapy pathology complete remission prediction result is obtained; training an image feature encoder with a tumor dynamic change identification capability through a dynamic supervision pre-training mode; and a second stage of constructing a multi-modal deep fusion network based on the image feature encoder to integrate the image features, radiomics features and clinical pathological features of the patient, and outputting a prediction result of complete pathology remission, the radiomics features being extracted from the MRI image. And the purposes of high precision and strong generalization capability are achieved.

The invention relates to application of a PARP inhibitor in cancer treatment, in particular to application of the PARP inhibitor in ovarian cancer maintenance treatment. More specifically, the present invention provides a maintenance therapy for an ovarian cancer patient comprising administering an effective amount of 5-fluoro-1-(4-fluoro-3-(4-(pyrimidin-2-yl) piperazine-1-carbonyl) benzyl) quinazoline-2, 4 (1H, 3H)-dione, a hydrate or a pharmaceutically acceptable salt thereof, to an ovarian cancer patient who has undergone a first-line platinum-containing regimen treatment and achieves complete or partial remission, or a pharmaceutical composition containing 5-fluoro-1-(4-fluoro-3-(4-(pyrimidin-2-yl) piperazine-1-carbonyl) benzyl) quinazoline-2, 4 (1H, 3H)-dione, a hydrate thereof, or a pharmaceutically acceptable salt thereof, or a medicament containing the pharmaceutical composition.

The invention discloses a method for predicting small cell lung cancer immunotherapy effect based on CT radiomics. The method comprises the following steps: firstly, carrying out lung enhancement CT scanning on a small cell lung cancer patient receiving immunotherapy before and after treatment, extracting radiomics characteristics and calculating delta-RF; in the aspect of model construction, 1037 radiomics features are extracted, and the model is constructed through a series of processing. The model display includes a variety of predictive indicators, such as an overall lifetime (OS), a progression-free lifetime (PFS), a complete remission (CR), a partial remission (PR), a column diagram, a consistency index, a subject working characteristic curve and its underlying area, a calibration curve, and a clinical decision curve. The model has a high C index and an AUC value for PFS and OS prediction, the AUC for curative effect prediction is 0.913, and a calibration curve is close to an ideal line. Compared with a prediction scheme based on NGS sequencing, the method has the advantages of being low in cost, non-invasive, efficient, dynamic, accurate and the like, and the image omics concept is used for predicting the curative effect of SCLC immunotherapy for the first time.

The invention provides a nano delivery system based on copper death induction and application of the nano delivery system in preparation of tumor immunotherapy drugs, according to the novel copper death induction nano drug Cu / ZIF-90 (at) DSF, 30 mol% of Cu (acac) 2 and disulfiram are loaded through a high-porosity structure of ZIF-90, and pH / ROS dual-responsiveness copper ion release is achieved. Animal experiments show that the Cu < 2 + > accumulation concentration of the nano-drug at a tumor site reaches 23.7 mu M, and efficient copper death is induced (the apoptosis rate is 41.3% vs and the control group is 9.2%). More importantly, by releasing HMGB1 and ATP, the CD8 < + > T cell infiltration in a tumor microenvironment is increased by 5.8 times, and the CD8 < + > T cell infiltration and the alphaPD-1 antibody generate a synergistic effect, so that the complete remission rate is increased from 18% to 67%. According to the technical breakthrough, a brand new solution is provided for solving the cold tumor immunotherapy drug resistance.

The invention discloses Fe (at) MoS2 hydrogel for sensitizing immunotherapy and a preparation method of the Fe (at) MoS2 hydrogel. The hydrogel comprises ferrous sulfate, molybdenum disulfide and a hyaluronic acid hydrogel matrix. The hydrogel can continuously release iron ions in a tumor slightly acidic environment, Fe is reduced into Fe by utilizing the catalytic action of MoS, and circular supply of Fe is realized, so that tumor cells are efficiently and enduringly induced to generate ferroptosis. More importantly, it is found that the Fe-coated MoShydrogel can specifically up-regulate expression of IL-36 gamma and CXCL2 in a tumor microenvironment for the first time, and by activating an IL36 gamma / CXCL2 / CXCR2 signal axis, mononuclear macrophages are recruited and remodeled, and the immunosuppression microenvironment is reversed. In-vivo experiments show that when the hydrogel is combined with an immune checkpoint inhibitor (such as an alphaPD-1 antibody), a remarkable synergistic anti-tumor effect can be generated, and the complete remission rate is greatly improved.

The invention provides a use of a marker or a combination thereof in preparation of a product for prediction, diagnosis or auxiliary diagnosis of measurable residual diseases, the measurable residual diseases occur after clinical complete remission of acute myelogenous leukemia patients, and the marker or the combination thereof comprises a C-X-C chemokine receptor 4 gene. According to the method, a multi-parameter flow sorting technology is adopted, leukemia cell populations are separated from bone marrow samples of patients in the first diagnosis stage and the AML MRD stage, and a sufficient number of residual disease cells are successfully captured through a single cell transcriptome sequencing technology. The CXCR4 low-expression cell is identified to be capable of being used as a common marker of an MRD cell, and is verified in a clinical AML patient specimen. And an innovative scheme is provided for MRD monitoring of AML patients lacking clear molecular markers. And meanwhile, a CXCR4 low-expression cell is provided as a function substitution model of the MRD cell, so that the technical limitation of insufficient residual cells in the traditional research is broken through, and a reliable research system is established for systematically exploring the biological characteristics of the MRD cell.

Methods and uses of immunoconjugates that bind to CD123 (e.g., pivekimab sunirine) in patients with acute myeloid leukemia (AML) are provided. Such immunoconjugates can be used as monotherapies or can be used in combination with BCL-2 inhibitors (e.g., venetoclax), and / or hypomethylating agents (e.g., azacitidine or decitabine) to prepare patients with AML for hematopoietic stem cell transplant and / or to achieve complete remissions in patients with AML, including those with poor prognostic markers.

The invention relates to an NAC curative effect prediction method and system based on a multi-modal image and a dual-channel GCN-Transform, and the method comprises the steps: extracting the features of multi-modal images, such as an ultrasonic gray-scale image and a color Doppler blood flow image, through ViT, constructing a knowledge graph, and carrying out the aggregation of a graph attention network; meanwhile, an SVS pathological section is segmented into pixel patches, patch features are extracted, and global representation is obtained through a four-layer graph convolutional network; after deep learning of the two paths of Transformers, weighted soft voting fusion is adopted to predict the complete remission probability of neoadjuvant chemotherapy pathology, complementarity of image and histological information can be fully mined, and the prediction accuracy is remarkably improved. Compared with a plurality of existing optimization algorithms, the advantages of the algorithm in the aspect of improving the breast cancer NAC curative effect prediction accuracy are verified.

The invention discloses a prediction method and device for complete remission of an endometrial cancer patient, a medium and a product, and relates to the technical field of biologication.The method comprises the steps that feature extraction is conducted on an obtained data set, and a plurality of radiomics features are obtained; establishing an MR scoring model according to the plurality of radiomics features; performing prediction effectiveness evaluation on the MR scoring model to obtain an MR score; performing normal distribution test on the plurality of radiomics characteristics to obtain a plurality of radiomics characteristics converted into normal distribution; carrying out variance homogeneity analysis on the plurality of radiomics characteristics converted into normal distribution, and determining the difference of the plurality of radiomics characteristics converted into normal distribution and prediction factors related to complete remission of the patient; and constructing a column graph model according to the MR score and the prediction factor. According to the method, young EC patients suitable for retaining fertility can be accurately identified, the accuracy of a clinical decision-making process is improved, and unnecessary uterine cavity invasive operation is reduced.

The invention discloses a novel biomarker for predicting the probability that a breast cancer patient accepts NAC to obtain pCR and application thereof, relates to the technical field of biological medicine, and solves the technical problem that in the prior art, as breast cancer has high heterogeneity and different patients have huge reaction differences on NAC, the prediction accuracy of the existing biomarker for predicting pCR is low. The novel biomarker for predicting the possibility that a breast cancer patient obtains complete pathologic remission after receiving neoadjuvant chemotherapy is a change difference value delta THR of THR in serum of the patient before and after the breast cancer patient receives NAC. According to the method, the NAC efficacy prediction possibility of a patient is predicted by utilizing the dynamic change of lipid metabolism of the patient for the first time, the pathological complete remission possibility of the breast cancer patient after the breast cancer patient receives neoadjuvant chemotherapy can be dynamically, accurately and noninvasively predicted, and the NAC-induced THR dynamic change value delta THR has high clinical value in prediction of the pCR of the breast cancer patient.

Methods of treating cancers or precancerous conditions and treating cancers in partial or complete remission are disclosed. The methods involve topical application of topical contact sensitizers, such as squaric acid dibutylester.

The invention belongs to the technical field of medical treatment, and discloses an initial non-resectable hepatocellular carcinoma postoperative drug-free monitoring method based on complete pathology remission, and the method comprises the following steps: selecting a patient; all patients are subjected to systemic treatment or combined transarterial treatment; dosage adjustment and temporary interruption of treatment are allowed according to adverse reaction conditions; the transcatheter treatment comprises transcatheter arterial chemoembolization TACE and hepatic arterial perfusion chemotherapy HAIC; in assessing the tumor response, contrast enhanced computed tomography (CT) or magnetic resonance imaging (MRI) is used every 6 to 8 weeks, based on the mRECIST and RECIST 1.1 criteria; postoperative adjuvant therapy is usually started 4-8 weeks after an operation, and is usually based on a preoperative transformation treatment scheme; the adverse reactions are evaluated by comparing the baseline value changes during the first post-operative follow-up with the subsequent follow-up.

Methods and uses of immunoconjugates that bind to CD123 (e.g., pivekimab sunirine) in patients with blastic plasmacytoid dendritic cell neoplasm (BPDCN) are provided. Such immunoconjugates can be used, for example, to prepare patients with BPDCN for hematopoietic stem cell transplant, to achieve bone marrow remission in BPDCN patients with bone marrow involvement, and to achieve long-lasting complete remissions in patients with BPDCN as a result of a short treatment period.

The application relates to the technical field of detection kits, in particular to application of miRNA-142-3p in predicting treatment responsiveness of IgA nephropathy. The application finds that urine miRNA-142-3p is related to a complete remission group after treatment of IgA nephropathy patients and a non-complete remission group after treatment. More specifically, the application finds that the urine miRNA-142-3p expression amount of the non-complete remission group after treatment of the IgA nephropathy patients is significantly higher than that of the complete remission group. Moreover, the relative expression amount of miRNA-142-3p is used as a single index for detection, and the AUC is 0.847 (0.769, 0.925), which is similar to 0.84 (95% CI 0.81-0.88) of a current invasive method for predicting treatment responsiveness of IgA nephropathy in kidney tissues.

The present application provides a set of complete innovative technical solutions from target discovery to treatment intervention for the immune escape and drug resistance recurrence problems existing in the clinical treatment of multiple myeloma (MM). It is found that Siglec7 is mainly highly expressed on the surface of NK cells, and the proportion and expression intensity of Siglec7 positive NK cells are significantly higher than those of complete remission and non-tumor controls; further, Siglec7 monoclonal antibody is prepared, and when the anti-Siglec7+CD38 monoclonal antibody (such as daratumumab) is used, a significant synergistic anti-tumor effect can be produced in vitro and in vivo. The technical solution completely constructs the research and development chain of "marker discovery-target verification-drug development-treatment application", and provides a new target, specific antibody drug and innovative combined drug regimen for the precise diagnosis, prognosis and especially immunotherapy of refractory and relapsed patients with multiple myeloma, which has great clinical transformation value and market prospect.

The invention belongs to the field of biological medicines, and provides a device for predicting disease recurrence based on an ultrahigh-sensitivity mutation load, an MRD gene detection panel covering 28 hotspot mutation regions of acute myelogenous leukemia is designed by integrating famous tumor public databases such as COSMIC, a quantitative blocker displacement amplification QBDA technology is combined, and the disease recurrence is predicted. According to the method, ultra-low abundance mutation with the variation allele frequency lower than 0.01% can be detected, a set of device for predicting relapse in advance based on ultra-high sensitivity mutation load change in the complete remission period of an acute myelogenous leukemia patient is developed, and the important clinical application value is achieved.

The invention provides a treatment response model for acute myelogenous leukemia (AML) accompanied with myelodysplastic syndrome related genetic abnormality (MRGA) and application thereof, and the model combines clinical data, cytogenetics and molecular biology data of patients. Variables significantly related to the complete remission rate of the patient are screened out through Lasso regression and Cox multivariable regression analysis, a treatment response model for predicting the complete remission rate is constructed based on the variables, and a combined scoring system formed by the treatment response model and a constructed survival risk scoring model is used for predicting the response of the patient to induced treatment and 1-3-year survival prognosis. And an individualized basis is provided for clinical treatment decision-making of the AML patient.

The invention discloses a method, a device, equipment and a medium for predicting the reaching of pCR of neoadjuvant chemotherapy of triple negative breast cancer, and relates to the technical field of medical data processing, and the method comprises the following steps: obtaining clinical pathological characteristics of a to-be-detected object and peripheral blood counting data before neoadjuvant chemotherapy; the peripheral blood count data comprises neutrophil count, lymphocyte count, platelet count and mononuclear cell count; the clinical pathological characteristics comprise a T staging characteristic, an N staging characteristic and a Ki-67 characteristic; determining a target biomarker related to pathologic complete remission pCR prediction based on the peripheral blood count data, and calculating an immune inflammation score according to the target biomarker; the clinical pathological features and the immune inflammation scores are processed through a trained XGB model, and a pCR prediction result of the to-be-detected object is obtained; and the XGB model is used for capturing a nonlinear relationship and an interaction effect among the data. According to the invention, the problem of poor detection timeliness can be avoided, and the pCR prediction accuracy is improved at the same time.

The application discloses a kind of longitudinal CT image auxiliary evaluation rectal cancer neoadjuvant radiotherapy treatment response device, the device includes focus area segmentation module obtains rectal cancer patient before neoadjuvant radiotherapy and before surgery CT enhanced image, carries out rectal focus area automatic segmentation to target image after pre-processing, obtains standardized three-dimensional tumor area;Feature fusion module extracts the deep learning feature of segmented focus area before neoadjuvant radiotherapy and before surgery from three-dimensional tumor area respectively, two time points deep learning features are weighted and fused by dynamic attention weight layer, obtain longitudinal comprehensive features representing tumor treatment response change;Predictive module fuses longitudinal comprehensive features and clinical baseline data to construct multimodal prediction model, outputs the treatment response prediction result of rectal cancer patient to neoadjuvant radiotherapy, can improve the prediction accuracy of rectal cancer patient pathological complete remission, improve patient prognosis and medical resource utilization efficiency.

The invention provides a preparation for targeted delivery of anti-miR410 antisense oligonucleotide by a nano-carrier as well as a preparation method and application of the preparation, and belongs to the technical field of biomedical materials. The preparation method comprises the following steps: firstly, providing folate receptor targeting nanoparticles, and then mixing and incubating the folate receptor targeting nanoparticles and antisense oligonucleotides to obtain the compound for targeted delivery of the antisense oligonucleotides. The compound for targeted delivery of antisense oligonucleotides has the effects of inhibiting proliferation and invasion migration of tumor cells while exerting the anti-miR410 specificity to enhance the radiotherapy sensitivity of the tumor cells, and is more beneficial to improving the complete remission rate of tumor patients, prolonging the lifetime and improving the life quality. The invention provides a theoretical basis and an experimental basis for developing a new strategy of lung cancer radiotherapy sensitization, and has important scientific significance and clinical value.

The invention belongs to the field of chemical medicines, and particularly relates to a combined medicine of a medicine for intervening E3 ubiquitin ligase and an anti-tumor medicine for targeting HER2. The medicine for intervening the E3 ubiquitin ligase can block HER2 protein degradation or promote HER2 gene transcription, can enhance HER2 expression on the surfaces of tumor cells, and can enhance the sensitivity of HER2 negative tumors to HER2-targeted antitumor medicines. According to the present invention, the E3 ubiquitin ligase intervening drug and the HER2 targeting antitumor drug are combined so as to target the tumor tissue, induce the tumor regression and improve the complete remission rate of the tumor, such that the good anti-HER2 negative tumor effect is provided, no significant side effect exists, and the new strategy is provided for the treatment of the HER2 negative tumor.

Methods and uses of immunoconjugates that bind to CD123 (e.g., pivekimab sunirine) in patients with blastic plasmacytoid dendritic cell neoplasm (BPDCN) are provided. Such immunoconjugates can be used, for example, to prepare patients with BPDCN for hematopoietic stem cell transplant, to achieve bone marrow remission in BPDCN patients with bone marrow involvement, and to achieve long-lasting complete remissions in patients with BPDCN as a result of a short treatment period.