79 results about "Carcinogenesis" patented technology

The invention relates to the technical field of novel biological nanomaterials, in particular to a lung-targeted exosome complex as well as a preparation method and application thereof. The lung targeting type exosome complex is prepared from an NK cell exosome, lipid nanoparticles and an entrapped anti-tumor nucleic acid drug, the NK cell exosome is obtained by extracting a natural killer cell NK-92MI of a human malignant non-Hodgkin lymphoma patient through a differential centrifugation method. The anti-tumor nucleic acid drug is a specific nucleic acid drug targeting a key canceration driving gene in non-small cell lung cancer. The lung targeting type exosome complex prepared by the invention is an excellent and stable drug delivery carrier, has a good lung tissue targeting function, enhances the tumor targeting effect of the exosome, also exerts the tumor cell killing function of the exosome, and has important significance for the treatment of non-small cell lung cancer.

Described herein are methods such as multi-omic methods for assessing a disease such as cancer. The multi-omic methods may integrate proteomic, transcriptomic, genomic, lipidomic, or metabolomic data. The method screening diseases or disease states. Also described herein are methods for screening for diseases or disease states from biological samples. The methods may include assessing whether a nodule, mass, or cyst is cancerous.

This disclosure describes how to treat and / or improve pancreatic cancer using a novel proteomic profile of the pancreatic cancer. In some embodiments, the treatment includes removing cancerous tissue after taking a biopsy from the patient. Optionally, the treatment includes administering anticancer agents to suppress the progression of pancreatic cancer. In further or alternative embodiments, the novel proteomic profile is used to monitor disease progression or remission.

The application discloses a liver-targeted gene editing system based on endogenous promoter hijacking and application, and belongs to the field of biological medicine. The system is composed of an LNP-wrapped modified Cas nuclease mRNA (first component) and a promoter-free viral vector carrying a therapeutic transgene donor (second component). The system uses LNP to realize the transient burst expression of Cas nuclease in the liver, mediates the generation of double-strand breaks at the site of endogenous high-expression genes, induces the site-specific integration of therapeutic transgenes without exogenous promoters, and hijacks the expression driven by endogenous promoters by using the splice acceptor (SA) mechanism. The application solves the risk of carcinogenesis caused by random integration of exogenous strong promoters and the immunotoxicity of long-term expression of nucleases through a "double safety lock" design. Experimental results prove that the system has high editing efficiency, long-term stability and no off-target, and can be used for various liver-derived metabolic diseases such as hemophilia, hypercholesterolemia and the like.

The invention belongs to the technical field of medical biological detection, and particularly relates to a gene marker combination for oral mucosa leukoplakia canceration risk and application of the gene marker combination. The gene marker combination is a combination of TP53, CASP8 and CYP2B6 genes and is obtained by screening through a WES technology, the predicted AUC of the gene marker combination reaches 0.813 (95% CI: 0.710-0.916), and the performance of the gene marker combination is remarkably superior to that of traditional pathological grading. Through Cox risk regression analysis, a high-risk group as an independent factor has significant statistical significance and is superior to traditional indexes such as age and diseased regions. The invention further provides an oral mucosa leukoplakia canceration risk prediction kit and prediction system derived from the gene combination.

Systems and methods for identifying a diagnosis of a cancerous state for a somatic tumor specimen of a subject are provided.SOLUTION: The method receives sequencing information comprising an analysis of a plurality of nucleic acids from a somatic tumor specimen. The method identifies a plurality of features from the sequencing information including two or more of RNA, DNA, RNA splicing, viral, and copy number features. The method provides a first subset of features and a second subset of features from the identified plurality of features as input to a first classifier and a second classifier, respectively. The method generates two or more predictions of cancer status based at least in part on the identified plurality of features from the two or more classifiers. The method combines the two or more predictions with a final classifier to identify a diagnosis of cancer status for the subject's somatic tumor specimen.SELECTED DRAWING: Figure 1

The application relates to a method for predicting gene mutation based on deep learning using multi-modal slices, image block division is performed on a digestive tract HE slice, and based on the image block division result, each image block of the digestive tract HE slice is classified into a cancerous region; the digestive tract HE slice and an immunohistochemical slice are registered; based on the digestive tract HE slice and the registered immunohistochemical slice, a gene mutation prediction training sample set is constructed, a multi-instance learning model is trained, the training standard is whether a gene is mutated, and a gene mutation prediction model is obtained; gene mutation prediction is performed according to the obtained gene mutation prediction model, a model for predicting gene mutation in combination with multi-modal pathological data of a patient is used, high specificity of the model is ensured, compared with a pathological gene prediction model using single modal data, more modal data is introduced, and the prediction accuracy is effectively improved.

The present disclosure provides compositions and methods for distinguishing between non-cancerous, pre-cancerous, and cancerous conditions in the esophagus. In particular, the present disclosure provides compositions and methods for distinguishing non-dysplastic Barrett's esophagus (NDBE) samples from pre-cancerous (e.g., low-grade or high-grade dysplasia) and / or cancerous (e.g., esophageal adenocarcinoma) samples based on methylation status and / or DNA copy number abnormalities.

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.

The invention relates to the technical field of near-field imaging, in particular to a papillary thyroid carcinoma identification method based on terahertz imaging. According to the technical scheme, the method comprises the following steps that two sets of sections at the same position of the thyroid tissue of a patient are obtained, one set is stained sections, and the other set is unstained sections; and comparing the two groups of slices through an optical microscope, observing the position corresponding relation of the two groups of slices, and selecting an observation area based on cell morphological characteristics. According to the invention, synchronous acquisition of tissue apparent morphology and internal structure under nanoscale resolution is realized through the terahertz near-field imaging system, automatic analysis of an undyed thyroid section can be completed within 30 minutes by combining multi-modal feature fusion and a target detection algorithm, objective positioning and diagnosis scores of a cancerous region are directly output, and the accuracy and accuracy of diagnosis of the cancerous region are improved. And rapid, lossless and quantitative papillary thyroid carcinoma identification is realized.

The invention discloses an application of a TNFRSF12A inhibitor in preparation of a medicine for treating oral squamous cell carcinoma. Based on single cell transcriptome data, oral squamous cell canceration related tissues are divided into four tissue ecological subtypes, and a tumor sample is divided into two subtypes ET3 and ET4. The ET3 subtype is a lymphocyte infiltration type, and shows CD8 + T cell infiltration, immune activation pathway activity enhancement and high expression of CD3, CD8A and PDCD1; the ET4 subtype is a lymphocyte rejection type, is enriched with COL1A1 + fibroblasts, and is accompanied by high expression of TNFRSF12A, COL1A1 and CD276. According to the application disclosed by the invention, the expression of the TNFRSF12A in the ET4 subtype is obviously improved, in-vivo experiments prove that knockout or blocking of the TNFRSF12A can promote lymphatic T cell infiltration and inhibit tumor growth, and a stronger inhibition effect is shown when the knockout or blocking of the TNFRSF12A is combined with an immune checkpoint inhibitor. The invention provides a system for typing oral squamous cell carcinoma.

This invention relates to the field of pharmaceutical technology, specifically proposing the application of ligustilide in the preparation of drugs for inhibiting and / or preventing and / or alleviating and / or treating lung tumors to address the current lack of natural drugs for lung cancer prevention. Lung tumors are nitrosamine-induced carcinogenesis of lung tissue. The invention relates to a pharmaceutical preparation for inhibiting and / or preventing and / or alleviating and / or treating lung tumors, comprising an active ingredient and pharmaceutically acceptable excipients; wherein the active ingredient is ligustilide. Ligustilide directly targets the STING protein, activates the cGAS-STING pathway, promotes STING phosphorylation and cell-mediated immune surveillance, while simultaneously regulating ROS homeostasis and the inflammatory microenvironment, reducing nitrosamine damage to lung epithelial cells, and preventing nitrosamine-induced lung carcinogenesis.

This invention discloses a high-performance computing-based system and method for evaluating colorectal cancer screening strategies, belonging to the field of medical information processing technology. It includes: a dual-pathway disease model module supporting both adenoma-carcinoma pathways and serrated adenoma pathways, modeled using age-dependent normal distribution progression time; an individualized risk scoring module integrating risk factors such as family history, inflammatory bowel disease, obesity, and diabetes; a screening strategy simulation module supporting combined screening strategies using different tools, employing compliance parameters specific to the Chinese urban population; a high-performance computing module using Numba JIT compilation technology for acceleration, multi-process parallel processing for further acceleration, and data structure optimization such as integer age to reduce memory usage; and a health economics evaluation module calculating indicators such as QALY, LYG, and ICER. This invention achieves significant performance improvements while maintaining model accuracy, greatly reducing simulation time for large-scale populations.

The invention discloses an oral potential malignant disease canceration time prediction system, electronic equipment and a medium, and the system comprises a data acquisition module, a data division module, a model construction module, a model training module and a time prediction module. And the risk prediction module is used for predicting the cancerization risk of the patient by using the artificial intelligence model with the best prediction accuracy, and determining the risk values of cancerization in the first time period and the second time period, or determining the time period with the higher cancerization possibility. According to the technical scheme, the canceration risk prediction probability values of the patient in multiple time periods are innovatively output by adopting the artificial intelligence model in combination with an oversampling technology and ending weight adjustment, a more comprehensive and specific prediction result can be provided for the patient, and personalized follow-up visit and formulation of a treatment scheme are facilitated.

The present application belongs to the technical field of medical image detection, and particularly relates to an esophageal flora image intelligent detection method for gastroesophageal reflux disease risk prediction, wherein flora image and clinical data are acquired to construct a perception network; flora displacement features are quantified by image registration; flora density, aggregation degree and fluorescence gradient features are extracted by improved U-Net++ segmentation; flora and epithelial cell lesion features are fused by space-time attention to generate flora-host correlation atlas; flora dynamic evolution model is constructed by space-time graph convolution network to predict Barrett esophagus occurrence probability and flora diffusion trend; lesion risk grade is calculated by flora imbalance quantification algorithm; in combination with reflux frequency and pH fluctuation, flora-environment interaction model is used to simulate colonization coefficient and correct parameters, which are transmitted to a diagnosis platform to deduce cancer risk, trigger grading suggestions and generate a visual report. Thus, the problems of long detection cycle and weak microscopic analysis capability in the prior art are solved.

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 present application relates to the field of cancer cell identification, and particularly relates to a method and system for identifying different types of cancer cells of a renal pelvis cancer patient based on urine, the method comprising: collecting a urine sample, obtaining a detection sample by using the urine sample; sequencing the detection sample to obtain a cell expression profile of the detection sample; obtaining cell expression profile data of a mixed urothelial cell subpopulation by using the cell expression profile, the mixed urothelial cell subpopulation comprising normal urothelial cells and cancerous urothelial cells; extracting different proto-oncogene expression data from the cell expression profile data of the mixed urothelial cell subpopulation; analyzing the different proto-oncogene expression data to obtain a cancer cell ratio and identify different types of cancer cells. The present method quickly and accurately obtains different types of cancerous urothelial cells through non-invasive examination and proto-oncogene expression profile data, and provides a reference and basis for preoperative neoadjuvant therapy of renal pelvis cancer.

The present invention concerns the field of cancer and methods for early detection of cancerous lesions. Specifically, the invention relates to a method for early detection of cancerous lesions through the analysis of microsatellite instability in the genome of an individual from a liquid biopsy.

The application provides a method for constructing an endometrial carcinoma CT image segmentation model and application thereof, including the following steps: acquiring multiple endometrial CT images labeled with cancerous regions as a training data set; constructing an endometrial carcinoma CT image segmentation architecture, wherein the endometrial carcinoma CT image segmentation architecture is a U-Net structure including an encoding unit, a bottleneck layer and a decoding unit; and training the endometrial carcinoma CT image segmentation architecture with the training data set to obtain an endometrial carcinoma CT image segmentation model. The scheme explicitly captures multi-scale structural change information by constructing a multi-directional coding structure response operator and generating a coding structure gradient field, thereby strengthening the representation of thin and weak boundaries and small lesions to improve the segmentation accuracy of the model.

The invention discloses a polysaccharide-polyphenol-metal compound for preventing colorectal cancer related to colitis, the polysaccharide-polyphenol-metal compound is formed by compounding a metal-polyphenol nano ligand and polysaccharide molecules, and the metal-polyphenol nano ligand is a nano complex formed by tea polyphenol and metal ions through coordination. The invention also discloses a preparation method and application thereof. The compound has the functions of oxidation resistance, inflammation resistance, immune metabolism reprogramming, intestinal flora steady-state regulation and control and the like, and can activate an Nrf2-ARE antioxidant pathway and restore expression of epithelial tight junction protein by adjusting polarization of macrophages and inhibiting NF-kB / STAT3 proinflammatory signals, thereby promoting reconstruction of beneficial flora (such as Lactobacillus and Akkermansia). The composite system can also achieve the synergistic effect of immunoregulation and chemotherapy combined cancer prevention under the drug loading condition, and the canceration process of colitis is remarkably delayed.

In the disclosed systems and methods for characterizing a cancer condition of a tissue in a subject, a computer system inputs information into an ensemble model. The information includes, for each respective class of radiomics features in a plurality of classes of radiomics features, a corresponding value for each respective radiomic feature in a corresponding plurality of radiomics features of the respective class of radiomics features obtained from a medical imaging dataset. The ensemble model comprises a plurality of component models. The computer system obtains as output from each respective component model in the plurality of component models a corresponding component prediction for the cancer condition, thereby obtaining a plurality of component predictions for the cancer condition. The computer system combines the plurality of component predictions to obtain as output of the ensemble model a characterization of the cancer condition.

The application belongs to the technical field of biological pharmacy, and provides a set of esophageal cancer methylation early screening markers and application thereof, the markers being any one or a combination of two or more of ZNF693, MMP14, JAG1, RUNX1 or NOTCH1 gene sequences or gene fragments containing at least one CpG methylation site; the application also discloses application of the set of biomarkers in preparation of a detection kit for diagnosing and / or evaluating the methylation degree of esophageal cancer or in screening of drugs for treating and / or relieving esophageal cancer. The application can effectively identify cancer patients by quantifying the dynamic change of the methylation level, and reduce the risk of missed detection caused by tumor heterogeneity; by establishing a high-throughput and standardized detection process, the application can provide a precise molecular typing tool for early intervention of esophageal cancer; the application overcomes the limitations of traditional technology, such as insufficient detection sensitivity for early cancer and dependence on invasive operation, and can promote clinical transformation of "early screening and early diagnosis".

The present inventions provide improved solution compositions and methods for detecting cancerous and dysplastic lesions in mucosal tissue in vivo. Specifically, the disclosed pretreatment solution results in enhanced removal of mucous and tissue debris. The disclosed detection solution compositions (nuclear stain-based and lectin-based) provide enhanced disease detection, when used individually or sequentially, tissue permeation, fluorescent signal, and shelf stability. Lectin fragmentation methods and processes of manufacturing are also disclosed. Additionally, various methods utilizes the disclosed inventive solution compositions are disclosed for accurate disease detection in vivo yielding high sensitivity and specificity values.

The invention relates to the technical field of animal model construction methods, in particular to a construction method of a BBN (N-butyl-N-(4-hydroxybutyl) nitrosamine) induced upper urinary tract urothelial carcinoma animal model, according to the method, BBN (N-butyl-N-(4-hydroxybutyl) nitrosamine is used for conducting drinking water administration treatment at different stages and with different concentrations on a mouse, and the in-situ tumorigenesis upper urinary tract urothelial carcinoma animal model is formed through induction. According to the technical scheme, the problem that in the prior art, BBN can only induce urothelium carcinoma mainly including bladder cancer can be solved, the whole development stage of animal pelvis cancer and ureteral cancer from early abnormality to advanced cancerization can be observed through the upper urothelium carcinoma animal model constructed through the technical scheme, and the mechanism of different disease courses can be researched conveniently. The animal model is expected to further explain the occurrence and development mechanism of the upper urinary tract epithelial cancer and screen new therapeutic drugs, and has ideal application prospects.

Provided are an artificial intelligence-based early cancer diagnosis method and device using a method of inputting information on a cell-free DNA distribution of a tissue-specific regulatory region to an artificial intelligence model learned to early diagnose cancer and analyzing the information, and an information providing device and a storage medium.SOLUTION: A method for providing information for early cancer diagnosis based on artificial intelligence includes extracting a nucleic acid from a biological sample to obtain sequence information, arranging the obtained sequence information in a reference chromosome sequence database, selecting a nucleic acid fragment of a regulatory region based on the arranged sequence information, generating the selected nucleic acid fragment as image data, and inputting the generated image data to an artificial intelligence model learned to distinguish a normal image and a cancer image, analyzing the image data, and comparing the image data with a reference value to determine the presence or absence of cancer.SELECTED DRAWING: Figure 1

The application discloses a marker for diagnosing, treating and / or prognosing prostate cancer bone metastasis and application thereof. The application discloses the relationship between LCAL4 and prostate cancer bone metastasis for the first time. The application verifies that LCAL4 is highly expressed in bone metastatic tumor tissues by using fluorescent quantitative PCR, and indicates a shorter bone metastasis-free survival time. In addition, it is also proved by in-vivo and in-vitro experiments that the down-regulation of LCAL4 gene expression can significantly inhibit the'stem cell characteristics' of prostate cancer cells, thereby inhibiting the bone metastasis of tumor cells. The application also designs an ASO sequence for inhibiting the expression of LCAL4 gene, and adopts a gene therapy method to make LCAL4 to silence the expression of LCAL4 at a cancerous site, so that the application can be used for preparing a drug for preventing and / or treating prostate cancer bone metastasis.

The invention belongs to the technical field of biological medicine, and particularly relates to application of vitamin B12 in preparation of an auxiliary therapeutic agent for preventing or treating colorectal cancer precancerous lesions. The invention aims to solve the technical problem of providing a novel prevention and intervention means for colorectal cancer (CAC) caused by the cancerization process of colorectal adenoma and inflammatory atypical hyperplasia. The invention further provides a preparation method of the novel prevention and intervention means for the colorectal cancer caused by the cancerization process of the colorectal adenoma and the inflammatory atypical hyperplasia of the colorectal adenoma and the colorectal cancer caused by the inflammatory atypical hyperplasia of the colorectal adenoma. In a colorectal adenoma canceration process, the level of vitamin B12 in a circulatory system is reduced along with the development of diseases. In inflammatory and hereditary colorectal cancer mouse models, MHC-II signals can be enhanced by supplementing medicine vitamin B12, and CD4 effect memory T cell immunity can be reactivated. The invention provides a new thought for further researching the immune recovery strategy in the colorectal cancer precancerous lesion process and the medical application of the vitamin B12.

The invention belongs to the field of medicine and health, and particularly relates to application of fresh traditional Chinese medicine radix puerariae exosome-shaped vesicles P-ELNs in medicine or health food for preventing and treating irritable bowel syndrome, the P-ELNs serving as an active ingredient can improve expression of colonic intestinal mucus protein MUC2 and tight junction protein ZO-1 and improve mucous membrane barrier integrity; the inhibition of the expression level of proinflammatory factors (such as TNF-alpha, IL-6, IL-1beta and NF-kappa B) indicates that the action mechanism may involve the synergistic effect of inflammation inhibition and barrier repair. Toxicological experiments show that the P-ELNs have no toxicity after long-term intragastric administration, have no adverse effects on heart, liver, spleen, lung and kidney functions, and have good oral safety and tissue tolerance. The indications comprise anti-inflammatory treatment of active-stage UC patients; maintenance and barrier repair of patients in the UC remission period; the UC disease course is more than or equal to 8 years, and a preventive medicine is applied to high-risk people with cancerization family history and the like; the invention relates to auxiliary treatment of UC-CAC early cancerization patients.

In the present invention, the inventors reveal that noncoding RNA, a known source of noncanonical peptides (also called dark matter) and tumour-specific antigens, can shape the precancer immune contexture and are associated with polyp and cancer risk. Through the multimodal characterisation of a unique dataset of 135 well-annotated cancer and precancer lesions from patients developing polyps at low and high frequency, the inventors identified high expression of noncoding RNAs, as a major differentiator of polyp development rate. Noncoding RNAs were also associated with increased immunogenicity associated with increased mature tertiary lymphoid structures within the microenvironment of pre-cancer lesion, higher quantity and quality of adaptive immune cells, including B- and T-cells. Thus, the inventors propose that early carcinogenesis is shaped by noncoding RNA expression and immune microenvironment. These compelling findings reveal potential early biomarkers and targets for prophylactic immune modulation approaches in individuals at high risk of developing colorectal cancer.

The invention discloses a tissue transparentizing method and an immunostaining method for esophagus of a multi-stage canceration mouse. The tissue transparentizing method comprises a whole tissue immunostaining step, a transparentizing step, a three-dimensional imaging step, a histological staging step and an image analysis step, wherein the whole tissue immunostaining step comprises the step of carrying out whole tissue immunostaining on a mouse esophagus sample by adopting an antibody; and a histological staging step, including de-transparentizing the three-dimensional imaging sample, and then performing pathological staining to judge the pathological staging of the sample. According to the application, a mouse esophageal whole tissue immunostaining method and a post-transparentizing esophageal original tissue pathological staging method are researched and developed for the first time, and a basis is provided for researching three-dimensional space characteristics of multi-stage lesions of mouse esophageal squamous carcinoma; the invention constructs a set of tissue transparentizing technology flow to realize microenvironment three-dimensional characteristic analysis in the mouse esophageal squamous cell carcinoma progress process.