85 results about "Lymph node metastasis" patented technology

The invention discloses a method of identifying a gene associated with stage III primary cancer or lymph node metastasis. The genes so identified include CAV1, CST3, LIMK1, MMP2, MMP15, VEGF, ETV4, MMP9, PIK3C2B, and SERPIN1. Also disclosed are methods for diagnosis, prognosis, and treatment of cancer. The invention further discloses compositions for preventing and treating diseases.

Objective methods for detecting and diagnosing intestinal-type gastric cancers are described herein. Also described is method for predicting the presence or absence of lymph node metastasis (i.e., identifying the metastatic phenotype). In one embodiment, the diagnostic method involves the scoring of gene expression profiles that discriminate between lymph node positive tumors and lymph node negative tumors. The predictive score calculated acts as diagnostic indicator that can objectively indicate whether a sample tissue has the metastatic phenotype. The present invention further provides methods of diagnosing intestinal-type gastric cancer in a subject, methods of screening for therapeutic agents useful in the treatment of intestinal-type gastric cancer, methods of treating intestinal-type gastric cancer and method of vaccinating a subject against intestinal-type gastric cancer.

The invention provides a pathological image automatic identification system training method based on deep learning, which is characterized by comprising the following steps: step (a), performing imagesegmentation; (b) acquiring a tumor region of interest and a lymph node region of interest; (c) extracting imaging omics characteristics in the tumor region of interest and the lymph node region of interest; (d) eliminating redundant image omics characteristics; (e) determining optimal imaging omics characteristics in the tumor region of interest and the lymph node region of interest; (f) constructing a training set by using the optimal image omics characteristics, and predicting lymph node metastasis; (g) constructing an independent verification set to verify the training set; (h) when the prediction effectiveness of the training set reaches a preset value, ending the training; and when the prediction effectiveness of the training set is lower than a preset value, reconstructing the training set for training. The training method can improve the effectiveness of predicting gastric cancer lymph node metastasis.

The invention discloses a reagent for auxiliarily diagnosing lung cancer lymph node metastasis, comprising 8 antibodies which are used for detecting 8 protein markers which are MMP1 (matrix metalloproteinase-1), TIMP1 (tissue inhibitor of metalloproteinases metallopeptidase inhibitor 1), IQGAP1 (IQ motif containing GTPase activating protein 1), TPX2 (targeting protein for Xklp2), uPA (Urokinase-type plasminogen activator), Cathepsin-D, Fascin and pIgR/SC (polymeric immunoglobulin receptor/secretory component). By adopting the 8 antibodies and an immunohistochemical staining result, lung cancer lymph node metastasis can be auxiliarily diagnosed, and the reagent is expected to be used for the risk estimation of lung squamous cell cancer lymph node metastasis and the prognostic prediction. The reagent has high creditability, strong practicability and clinical use value based on the clinical routine immunohistochemical staining technology when the reagent is used for auxiliary diagnosis.

The invention discloses an MDM2 gene which is a novel predisposing gene of nasopharyngeal darcinoma by relating the SNP 309 polymorphic loci of the MDM2 gene with the risk of the nasopharyngeal darcinoma and the more serious lymph node metastasis, thereby providing new genetic counseling contents and the molecule criterion for people to prevent and control the nasopharyngeal darcinoma. In addition, the invention also relates to a method for detecting the SNP309 polymorphic loci and the corresponding detecting kit, wherein, the detecting method is the PCR product direct sequencing method that is the polymerase chain reaction-sequencing method.

Disclosed herein are compositions and methods relating to the diagnosis, prognosis, and treatment of colorectal cancer. The compositions and methods generally relate to the differential expression of transgelin in colorectal cancer cells with metastatic potential.

The invention discloses an automatic staging system based on mammary gland lymph node panoramic image calculation, and belongs to the technical field of medical image information processing. The method comprises: establishing two positive and negative samples required by the deep convolutional network according to the marked lymph node cancer metastasis region, training the deep convolutional network to obtain a model required by classification of the positive and negative samples, sending each block in the image tissue region into the model to obtain the probability of cancer metastasis at the position of the block, and establishing a probability calorific value graph; Secondly, extracting pathological omics characteristics according to a segmentation area of lymph node cancer metastasis,training a random forest classifier, constructing an automatic classification model of lymph node metastasis states, and constructing a staging system by integrating multiple lymph node cancer metastasis states of the same patient. The problems of time consumption, labor consumption, high error and the like when breast cancer staging is judged by pathology experts according to experience can be effectively solved.

The invention belongs to the field of medicine, and particularly relates to new uses of a nanometer charcoal suspension injection, particularly to applications of the nanometer charcoal suspension injection in preparation of cancer diagnosis reagents and thermotherapy reagents matched with near-infrared light. According to the present invention, near-infrared light is used to heat the diagnosed tissue and the nanometer charcoal suspension injection can effectively absorb infrared rays to convert into heat, such that the great temperature difference between cancer cells and normal cells is produced; with a thermal imager, the cancer cells and the normal cells are distinguished, and the cancer cell distribution and the metastasis are adjusted, such that the new method for non-invasive diagnosis of cancer cell and malignant tumor draining lymph node cancer draining lymph node trending and distribution by using the nanometer charcoal suspension injection is provided for the public; and near-infrared ray is used to heat the place diagnosed as the cancer cell-containing tissue and location, such that the cancer cell temperature is rapidly increased, the cancer cells are subjected to high temperature killing at the temperature of about 50-56 DEG C, while the normal cells is at the human acceptable level in a short period so as to achieve the purposes of thermotherapy on the malignant tumor primary site and the draining lymph node metastasis.

The present invention discloses the nine biomarkers including HIF1A, FAM84B, CRIP2, GSN, RPL15, DLG1, MAT2A, PGBD2 and ID3 are respectively selected according to their specific and unique expression profile in the gastric cancer cells or gastric cancer tissue. Therefore, the nine biomarkers are related to diagnose gastric cancer, such as detecting early gastric cancer, staging gastric cancer, predicting prognosis of gastric cancer and diagnosing lymph node metastasis. By analyzing the expression value of at least one biomarker of a sample from a subject, the subject can be precisely diagnose the risk about gastric cancer.

The invention discloses a cancer marker, wherein the cancer is a prostate cancer, and the cancer marker is an expression product of an APMAP gene and/or an APMAP gene. The APMAP gene is highly expressed in prostate cancer, which can be used for early diagnosis of prostate cancer, and has the advantages of specificity and high sensitivity. The high expression of APMAP gene is closely related to thepoor prognosis, distant metastasis and lymph node metastasis of prostate cancer, suggesting that APMAP gene can be used as a prognostic marker to provide effective information for the metastasis diagnosis, prognosis evaluation and treatment effect monitoring of prostate cancer. The invention discloses an expression inhibitor of an APMAP gene, comprising siRNA and/or shRNA, which has good interference effect on the expression of the APMAP gene, and has the application potential of clinical gene therapy. The invention discloses a cell strain of stable knockdown APMAP gene, which is favorable for realizing further research on gene function.

The invention relates to the technical field of gene detection, and discloses a detection kit for oral squamous cell carcinoma lymph node metastasis prediction. The kit comprises forward primer and reverse primer sequences of 7 kinds of genes including PDGFRA, PLAU, SOX9, SPP1, CDKN2A, CASP1 and MAL. The invention also discloses a method for screening the gene or the gene combination for the oralsquamous cell carcinoma lymph node metastasis prediction. The detection kit can be used for objectively, accurately and sensitively predicting the oral squamous cell carcinoma lymph node metastasis condition, so that the survival rate of the oral squamous cell carcinoma patients can be favorably improved.

The invention provides a quantitative analysis result output method and apparatus of esophagus cancer lymph node metastasis. The quantitative analysis result output method of esophagus cancer lymph node metastasis includes the steps: establishing a lymph node database, performing image analysis and feature recognition on the data in a training set, calculating the likelihood ratio, and estimatingthe pre-test probability; using the data after image analysis and feature recognition and the likelihood ratio to perform index screening, and using the preliminary screening data and the estimated pre-test probability to calculate the post-test probability; establishing a discrimination model according to the preliminary screening data and the post-test probability; substituting the data in the test set into the discrimination model, and if the expected goal is achieved, establishing a quantitative analysis model for esophageal cancer lymph node metastasis; if the expected goal is not achieved, correcting the discrimination model and testing again until the expected goal is achieved, and establishing a quantitative analysis model for esophageal cancer lymph node metastasis; and substituting the lymph node data of the lymph node to be analyzed into the analysis model, obtaining a quantitative analysis result of esophageal cancer lymph node metastasis of the lymph node to be analyzed through calculation and outputting the quantitative analysis result.