110 results about "Endometrial Carcinomas" patented technology

Endometrial cancer (EC) is the most common gynecologic cancer in developed countries and the fourth most common cancer affecting women in the US. In contrast to other cancers, rates of EC continue to rise, and there are indications that social determinants of health and race and / or ethnicity contribute to risk. Thus, the methods described herein provide a non-invasive means of measuring biomarkers in the local cervicovaginal microenvironment. These novel biomarkers may be used for diagnosing and / or predicting women who are "at risk" for the development and progression of endometrial cancer (EC; e.g., EC type 1). Specifically, the methods herein may include obtaining a cervicovaginal lavage (CVL) or vaginal swab sample from a patient and producing a profile of at least five or more biomarkers from the collected sample.

The invention discloses an early noninvasive endometrial cancer assessment method based on machine learning, and the method comprises the following steps: S1, obtaining the index data of a potential endometrial lesion patient in advance, and carrying out the data integration based on the index data according to a preset standard to obtain a feature set; s2, performing standardized preprocessing on the feature set in the step S1 to obtain a training set and a test set of standardized endometrial lesion data; s3, constructing a disease prediction model based on a preset multi-modal machine learning model and used for predicting an endometrial cancer result on the basis of the training set and the test set containing the endometrial lesion data obtained in the step S2; and S4, inputting endometrial lesion index data of a patient to be evaluated into the disease prediction model to implement early noninvasive endometrial cancer prediction evaluation so as to obtain an endometrial cancer prediction result of the patient. The method has the advantages that non-invasive screening can be met at the same time, the prediction accuracy is high, and the economic burden is small.

The invention discloses a specific metabolic marker combination for diagnosing ovarian cancer and application thereof, and belongs to the field of markers for detecting ovarian cancer. The invention discloses a specific metabolic marker combination for diagnosing ovarian cancer. The specific metabolic marker combination comprises phosphatidylcholine 36: 6, sphingomyelin d40: 2 and sphingomyelin d41: 2. According to the invention, a metabonomics technology is used to screen out a specific metabolism marker combination for diagnosing ovarian cancer, and the specific metabolism marker combination has high sensitivity in ovarian cancer diagnosis and has high diagnosis capability for ovarian cancer diagnosis. The specific metabolic marker combination also has high specificity in ovarian cancer diagnosis, but is not applicable to diagnosis of endometrial cancer and cervical cancer. In addition, the plasma sample acquisition mode has the advantages of non-invasiveness and convenience, and has a wide application prospect in the research of biomarkers.

The present disclosure is concerned with compounds and compositions for use in the prevention and treatment of cancer associated with FBOX21 mediated p85a ubiquitination such as, for example, cancer (e.g., sarcoma, a carcinoma, a hematological cancer, a solid tumor, breast cancer, cervical cancer, gastrointestinal cancer, colorectal cancer, brain cancer, skin cancer, prostate cancer, ovarian cancer, thyroid cancer, testicular cancer, pancreatic cancer, liver cancer, endometrial cancer, melanoma, a glioma, leukemia, lymphoma, chronic myeloproliferative disorder, myelodysplastic syndrome, myeloproliferative neoplasm, non-small cell lung carcinoma, renal cancer, lung cancer, colon cancer, cervical cancer, and plasma cell neoplasm (myeloma)). This abstract is intended as a scanning tool for purposes of searching in the particular art and is not intended to be limiting of the present invention.

The present disclosure is concerned with compounds and compositions for use in the prevention and treatment of cancer such as, for example, a primary or secondary tumor within a subject's brain, breast, kidney, pancreas, lung, colon, prostate, lymphatic system, liver, ovary, or cervix. Additional examples of cancers for which the disclosed compounds and compositions can be useful include, but are not limited to, sarcomas, carcinomas, hematological cancers, solid tumors, breast cancer, cervical cancer, gastrointestinal cancer, colorectal cancer, brain cancer, skin cancer, prostate cancer, ovarian cancer, thyroid cancer, testicular cancer, pancreatic cancer, liver cancer, endometrial cancer, melanomas, gliomas, leukemia, lymphoma, chronic myeloproliferative disorders, myelodysplastic syndrome, myeloproliferative neoplasm, non-small cell lung carcinomas, and plasma cell neoplasms (myelomas). This abstract is intended as a scanning tool for purposes of searching in the particular art and is not intended to be limiting of the present invention.

This document relates to methods and materials for assessing and / or treating mammals (e.g., humans) having endometrial cancer. For example, methods and materials for identifying endometrial cancers likely to respond to a particular cancer treatment (e.g., a platinum based cancer therapy) are provided. This document also relates to materials and methods for using one or more cancer treatments to treat a mammal (e.g., a human) identified as likely to respond to a particular cancer treatment.

Provided is a use of an anti-PD-1 antibody combined with a chemotherapeutic agent in the treatment of tumors such as cervical cancer or endometrial cancer. In some embodiments, the chemotherapeutic agent comprises a taxane drug and / or a platinum drug. In some embodiments, the use further comprises a use of the anti-PD-1 antibody combined with bevacizumab.

The present invention relates to a primer-probe combination for early detection of endometrial cancer, a methylation detection kit, and the use thereof. Provided in the present invention is a methylation gene marker for endometrial cancer detection, which specifically comprises at least one of VSX1, SYT1, ZNF132 and VWC2 genes. Measuring the methylation levels of the genes can remarkably distinguish subjects with endometrial cancer from subjects without cancer. The gene marker of the present invention can well identify subjects with endometrial cancer and subjects without cancer from each of tissue / urine / brush smear / swab / blood / lavage fluid specimens, and can achieve a good detection effect simply by means of a single index and further improve the detection efficiency by means of multi-index combination.

The present disclosure provides novel compounds, compositions, and methods for modulating one or more septin proteins, e.g., septin-2. Such compounds and compositions are useful for the treatment of a cancer, e.g., endometrial, pancreatic, lung, breast or ovarian cancer, such as serous and ovarian clear cell carcinoma.

The invention discloses a multiplex PCR (Polymerase Chain Reaction) detection kit based on microsatellite instability sites of endometrial cancer. The kit comprises a primer group and a premixed solution, the primer group comprises a primer for detecting at least one of a site BAT-25, a site BAT-26, a site NR-24, a site MONO-27, a site CAT-25, a site BAT-59 and a site BAT-60, and the primer contains two inosine (I) and a stem-loop structure (SEQ ID NO.22) so as to simultaneously detect different states of MSI Del and Ins; according to the kit, when MSI detection is used for carrying out microsatellite instability judgment on endometrial cancer on seven combination sites and corresponding target coverage sections, capillary electrophoresis detection and common PCR (Polymerase Chain Reaction) and digital PCR detection can be carried out at the same time, so that the gradient among detection result numerical values is more refined, and the MSI state is accurately defined as high, low or stable; the kit has the advantages that reagent material cost is saved, detection period is shortened, detection in an extreme period is achieved, clinical multi-sample detection requirements are met, and the kit has the advantages of high sensitivity, specificity and repeatability.

The invention provides a construction method and application of an endometrial cancer CT image segmentation model. The construction method comprises the following steps: acquiring a plurality of endometrial CT images marked with canceration regions as a training data set; constructing an endometrial cancer CT image segmentation framework, wherein the endometrial cancer CT image segmentation framework is of a U-Net structure comprising a coding unit, a bottleneck layer and a decoding unit; and training the endometrial cancer CT image segmentation architecture by using the training data set to obtain an endometrial cancer CT image segmentation model. According to the scheme, multi-scale structure change information is explicitly captured by constructing a multi-direction coding structure response operator and generating a coding structure gradient field, and representation of thin and weak boundaries and small lesions is enhanced to improve the segmentation accuracy of the model.

Antibody drug conjugate (ADC) comprising a drug moiety conjugated to antibody or antigen binding fragments thereof that bind to TROP2 disclosed herein, as well as methods of use thereof. Methods of use include, without limitation, cancer therapies and diagnostics. The ADC of the disclosure can bind to certain cancer cell surfaces. Exemplary targets of the ADC disclosed herein can include carcinomas, such as lung cancer, breast cancer, head-and-neck cancer, esophagus cancer, stomach cancer, bladder cancer, pancreatic cancer, colorectal cancer, cervix cancer, endometrial cancer, ovarian cancer, laryngeal cancer, prostate cancer, thyroid cancer and oral cancer.

The present technology relates to methods for excluding Lynch syndrome as a possible diagnosis in patients suffering from colorectal cancers or endometrial cancers. These methods are based on detecting the methylation status of the MLH1 promoter ‘C’ region in colorectal and endometrial cancer patients using an improved and highly sensitive methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA) assay.

This application belongs to the field of biomedicine technology, and in particular relates to the use of a KAT5 inhibitor in a cancer treatment drug, as well as a drug for treating endometrial cancer. The use of a KAT5 inhibitor in a cancer treatment drug includes applying a KAT5 inhibitor to a drug for treating cancer. This application applies a KAT5 inhibitor to a drug for treating cancer. The small molecule KAT5 inhibitor can achieve anti-tumor activity by inducing accumulation of cellular DNA damage. Furthermore, the KAT5 inhibitor can significantly inhibit the growth of cancer cells both in vitro and in vivo. This application, through verification experiments, has for the first time clarified the anti-tumor effect of a KAT5 inhibitor, which has important pharmaceutical development value and market benefits.

The present disclosure relates to RNAi agents useful in methods of treating KRAS-related diseases such as a proliferative disease, including without limitation a solid or liquid cancer, adenocarcinoma, colorectal cancer, advanced and / or metastatic colorectal cancer, colon cancer, lung, non-small cell lung cancer and lung adenocarcinoma, acute myelogenous lung, bladder, brain, breast, cervical, endometrial, gastric, head and neck, kidney, leukemia, myelodysplastic syndrome, myeloid leukemia, liver, melanoma, ovarian, pancreatic, prostate, testicular, thyroid cancers, and cardio-facio-cutaneous (CFC) syndrome and Noonan syndrome, and similar and related diseases, using a therapeutically effective amount of a RNAi agent to KRAS.

The invention provides a deep learning-based endometrial cancer detection method and system, and relates to the technical field of cancer detection, and the method comprises the steps: obtaining preliminary survey data; determining a preliminary survey result; determining whether histopathology detection is needed or not; if histopathology detection needs to be carried out, hysteroscope guided biopsy data of the patient to be detected are obtained, and a histopathology definite diagnosis result is determined; determining whether further detection is needed or not; if further detection is needed, acquiring patient physiological state data, medical image data and laboratory detection data of the to-be-detected patient; determining a physiological state influence coefficient of the patient; processing the medical image data, the laboratory detection data and the physiological state influence coefficient of the patient through a trained tumor deterioration time prediction model, and determining predicted tumor deterioration time; determining an endometrial cancer danger coefficient; and generating a detection report. According to the invention, the accuracy of the detection result of the endometrial cancer can be improved.

Disclosed herein are novel compounds that are Mpsl / TTK inhibitors. Also disclosed are compositions comprising the compounds and methods of using the compounds in treating various diseases. In some embodiments, some such compounds, compositions, and their uses may be useful for the treatment of cancer. In some implementations, the cancer is brain cancer, glioblastoma multiforme, head and neck cancers, colorectal cancer, stomach or gastric cancer, pancreatic cancer, melanoma, bladder cancer, kidney cancer, renal cell carcinoma, breast cancer, ovarian cancer, lymphoma, thyroid cancer, mesothelioma, sarcoma, lung cancer, non-small cell lung cancer, small cell lung cancer, or endometrial cancer.

The present disclosure provides methods, compositions, uses, and kits for treatment of solid cancer (e.g., urothelial cancer (UC), head and neck squamous cell carcinoma (HNSCC), cervical cancer (CC), endometrial carcinoma (EC), or triple-negative breast cancer (TNBC)) using anti-human Nectin-4 therapeutics.

The present application relates to a kind of small sample endometrial carcinoma target delineation method, belong to target delineation technical field, solve the problem of low segmentation accuracy caused by small sample data training model in prior art.The method comprises the following steps: constructing multiple data centers, each data center includes multiple-channel segmentation model and multiple modal endometrial carcinoma sample set;The pre-training of the multiple-channel segmentation model is carried out based on the multiple data centers, and the pre-trained endometrial carcinoma target segmentation model is obtained;The pre-trained endometrial carcinoma target segmentation model is fine-tuned on target data set, and the trained endometrial carcinoma target segmentation model is obtained;Based on the trained endometrial carcinoma target segmentation model, the multiple modal endometrial carcinoma image to be segmented is segmented, and the target delineation result of the multiple modal endometrial carcinoma image to be segmented is obtained.The high-efficiency and accurate endometrial carcinoma target delineation is realized.

The present application relates to the field of biotechnology, and more particularly to an inhibitory peptide targeting p53 protein and application thereof. The present application uses IDProMat to design and obtain the inhibitory peptide targeting p53 protein according to the core binding site of the binding interface of the p53 protein core domain and ASPP2, TSPYL5, iASPP and the like; the inhibitory peptide can bind to p53 protein, competitively block the interaction between E3 ubiquitin ligase COP1 and p53, inhibit the ubiquitination degradation of p53, restore the anticancer function of p53, and has good biological safety and metabolic stability, and is expected to be used for clinical treatment of ovarian cancer, cervical cancer, endometrial cancer, pancreatic cancer and the like.

The present technology provides compounds, as well as compositions including such compounds, useful for imaging and / or treatment of a glioma, a breast cancer, an adrenal cortical cancer, a cervical carcinoma, a vulvar carcinoma, an endometrial carcinoma, a primary ovarian carcinoma, a metastatic ovarian carcinoma, a non-small cell lung cancer, a small cell lung cancer, a bladder cancer, a colon cancer, a primary, gastric adenocarcinoma, a primary colorectal adenocarcinoma, a renal cell carcinoma, and / or a prostate cancer.

The application provides a novel DNA methylation marker TAGMe-5 for tumor identification and use thereof. The tumor marker TAGMe-5 of the application shows significant DNA methylation difference between cancer adjacent tissue and cancer tissue, and the difference has significant statistical significance, and the difference is shown in numerous tumors such as solid tumors and non-solid tumors. The solid tumors include lung cancer, liver cancer, prostate cancer, cervical cancer, endometrial cancer, urothelial carcinoma, biliary tract tumor, etc. The non-solid tumors include hematological tumors, lymphoma, etc. Therefore, the tumor marker of the application can be used for clinical screening of pan-cancer, molecular diagnosis, prognosis and efficacy evaluation.

The present invention relates to 1,2-dicarboxamide compounds of Formula (I); pharmaceutically acceptable salts, pharmaceutically acceptable stereoisomers, N-oxides or combination thereof, wherein 'X', 'Y', 'Z', ring A, ring B, R1, R2, R3, R4, R5, R6, 'm' and 'n' are as defined herein. The present invention also relates to 1,2-dicarboxamide compounds that modulate cellular activities like proliferation, differentiation, adhesion, migration and apoptosis by modulating protein kinase enzymatic activity. In particular the invention relates to compounds which inhibit, regulate, and / or modulate tyrosine kinases such as FLT1 (VEGFR1), FLT4 (VEGFR3), KDR (VEGFR2), MET (C-Met), MERTK (c-Mer), RET, AXL, TEK (TIE 2) and EGFR. The present disclosure relates to 1,2-dicarboxamide compounds for use in modulating kinase enzymatic activity and accordingly modulating kinase-dependent associated diseases and conditions such as cancers like Thyroid carcinoma, Ovarian carcinoma, Pancreatic carcinoma, Prostatic carcinoma, Renal cell carcinoma, Hepatocellular carcinoma, Breast carcinoma, Colorectal carcinoma, Oral squamous cell carcinoma, Colorectal, Lung adenocarcinoma or Endometrial cancer.

The invention discloses a large model analysis system and method for endometrial cancer data management, and relates to the technical field of data large model analysis, and the method comprises the steps: determining the total amount of sample data; each group of sample data comprises characteristic data information of the patient and a judgment result of molecular typing data determined by adopting an immunohistochemical method; the features are divided based on the feature data information of the patient, the coincidence rate under each feature division is calculated, and a plurality of coincidence subintervals are formed based on the coincidence rates; and constructing a training model, forming the probability that the coincidence rate is in different coincidence subintervals based on different feature data information, forming a recommendation decision, and feeding back the recommendation decision to an administrator port. The method can solve the problem of significant subjectivity existing in a traditional mode of selecting a detection method only depending on the personal experience of doctors, establishes an objective decision standard through data driving, and reduces the selection deviation caused by the experience difference of the doctors.

The embodiment of the invention provides a primer probe combination for endometrial cancer gene methylation detection and application of the primer probe combination. According to the PCR primer probe combination for endometrial cancer gene methylation detection provided by the embodiment of the invention, the specific primers and probes are designed, so that different cancerization stages and subtypes of endometrial cancer can be covered, and meanwhile, the sensitivity and specificity of the kit are ensured; therefore, a basis is provided for early screening, accurate detection and individualized treatment of the endometrial cancer. The PCR primer probe combination provided by the embodiment of the invention has the advantages of covering different canceration stages and subtypes of endometrial cancer and ensuring the sensitivity and specificity of the kit.

The invention discloses an endometrial cancer typing system based on a multi-dimensional molecular marker, and the system comprises a data input module which is used for receiving multi-dimensional molecular marker state information which is inputted by a user and is related to an endometrial cancer sample, and the information contains genomics, apparent and expressive data and clinical pathology data; the data processing module is configured to sequentially execute multi-level typing logic based on the state information, and the logic comprises the following steps: typing based on POLE gene mutation state preferentially, then typing based on mismatch repair function and p53 function state in sequence aiming at an unshaped sample, and finally carrying out joint layering based on prognosis association indexes; and the typing result output module is used for outputting the final molecular subtype. Through multi-dimensional data cross validation and dynamic layering, the problems that an existing typing technology is single in dimension and poor in clinical applicability are solved, accurate and efficient typing of endometrial cancer is achieved, and reliable technical support is provided for individualized diagnosis and treatment.

Aiming at the problems existing in the prior art, the invention provides the biomarker for predicting the recurrence or metastasis risk of the endometrial cancer and the application of the biomarker, a proteomics method is utilized, and by analyzing the abundance difference of proteins in blood of patients with recurrence and non-recurrence of the endometrial cancer after operative treatment of the patients with the endometrial cancer, the risk of recurrence or metastasis of the endometrial cancer is predicted, and the risk of recurrence or metastasis of the endometrial cancer is predicted. According to the method, the biomarker capable of predicting the recurrence risk of the endometrial cancer is screened out, the model for predicting the recurrence risk of the endometrial cancer is further constructed, the recurrence risk of the endometrial cancer can be accurately, noninvasively and efficiently predicted, a new tool is provided for management of endometrial cancer patients, and treatment and prognosis monitoring of the patients are improved.

The present invention relates to novel compounds, diagnostic markers for use in medicine, more particularly in the diagnosis of cancer, especially endometrial cancer. The present invention also relates to an in vitro method for detecting, using the compounds, the enzymatic activity present in a biological fluid of a subject, especially originating from endometrial cancer cells. The present invention further relates to an in vitro diagnostic method for endometrial cancer using the compounds, a kit comprising the compounds, and the use of the compounds for detecting enzymatic activity specific for endometrial cancer, as well as the use of the compounds for the diagnosis of endometrial cancer. The present invention also relates to a method for treating endometrial cancer, which comprises using the compounds as a diagnostic marker for endometrial cancer and a procedure for carrying out the diagnostic method for endometrial cancer as described above using the compounds.

The application provides a training method and application of a tumor lesion target detection model for endometrial carcinoma CT images, and comprises the following steps: acquiring endometrial carcinoma CT images labeled with real lesion boundary boxes as training images; constructing a tumor lesion target detection model; grouping multiple training images into a training data set; iteratively training the tumor lesion target detection model using the training data set; constructing a total loss function based on a classification loss and a lesion-aware boundary box loss; and training the tumor lesion target detection model based on the total loss function until the tumor lesion target detection model converges. In the scheme, the risk weight is calculated based on the lesion area and the local contrast of the real lesion boundary box, the lesion-aware boundary box loss is obtained by weighting the boundary box regression loss using the risk weight, the positioning supervision intensity of high-miss-risk lesions such as small-scale and low-contrast lesions is oriented and strengthened, and the feature attention of the model to difficult lesions is improved.

The invention discloses an endometrial cancer molecular typing and prognosis prediction system and method based on a digital pathological image, and the system comprises an image preprocessing module which is used for receiving a full-view HE slice digital pathological image of an endometrial cancer patient, and carrying out the quality enhancement of the image through a super-resolution reconstruction model which is SRResGAN; and the region segmentation module is used for automatically segmenting the tumor region in the enhanced image by using a medical image segmentation model MedSAM, and the patch size is 256 * 256 and the threshold value is 0.5 in the segmentation so as to obtain the ROI of the tumor region. When in use, the method has the advantages of low cost and high accessibility: typing can be completed only through HE slicing, expensive NGS detection is avoided, and the method is suitable for being popularized in base layers and resource-limited regions; and under the conditions of different hospital section scanning devices and dyeing, the model performance is kept stable, and the cross-platform generalization ability is high.