65 results about "Small-cell carcinoma" patented technology

The invention relates to an intelligent lung cancer early cell pathological image recognition processing method, which comprises image pretreatment, image segmentation, laminate cell separation and reconstruction, cell character extraction and cell classification. The invention has the advantages that the image segmentation based on reinforcement learning uses incremental learning and continuous interaction with environment to search for optimized segmentation threshold value to obtain the segmentation effect which average value is 91%, the laminate cell separation and reconstruction uses B spline and modified deBoor-Cox method to simulate true cell edge better, the classifier uses general vote method to avoid low classifying accuracy of single classifier and improve total classifying accuracy, the application of two-stage classifier can reduce the possibility of false positive and false negative. Tests prove that the classifying accuracy of cancer or no cancer can average reach 93.8%, the classifying accuracy of squamous cell carcinoma, adenocarcinoma and small cell carcinoma average reaches 75%, and the false positive and negative average reach 4-6%.

The present invention relates to monoclonal antibody 1A7. This is an anti-idiotype produced by immunizing with an antibody specific for ganglioside GD2, and identifying a hybridoma secreting antibody with immunogenic potential in a multi-step screening process. Also disclosed are polynucleotide and polypeptide derivatives based on 1A7, including single chain variable region molecules and fusion proteins, and various pharmaceutical compositions. When administered to an individual, the 1A7 antibody overcomes immune tolerance and induces an immune response against GD2, which comprises a combination of anti-GD2 antibody and GD2-specific T cells. The invention further provides methods for treating a disease associated with altered GD2 expression, particularly melanoma, neuroblastoma, glioma, soft tissue sarcoma, and small cell carcinoma. Patients who are in remission as a result of traditional modes of cancer therapy may be treat with a composition of this invention in hopes of reducing the risk of recurrence.

The present invention relates to polyethylene glycol derivatives of thymosin alpha-1, their preparation process, the medicine composition containing them, and their application in the medicine for preventing and treating diseases related with immune deficiency and hypoimmunity, including hepatitis B, hepatitis C, malignant melanoma, non-small cell lung carcinoma, SARS, etc.

The present invention provides fusion proteins for the detection and treatment of neuroectodermal tumors. Previous work demonstrated that chlorotoxin is specific for glial-derived or meningioma-derived tumor cells. The current invention has extended the use of chlorotoxin-cytotoxin fusion proteins to treat the whole class neuroectodermal tumors such as gliomas, meningiomas, ependymonas, medulloblastomas, neuroblastomas, gangliomas, pheochromocytomas, melanomas, PPNET's, small cell carcinoma of the lung, Ewing's sarcoma, and metastatic tumors in the brain. Also, diagnostic methods are provided for screening neoplastic neuroectodermal tumors.

The invention belongs to the field of medical embolization devices, relates to a sodium alginate microsphere targeted vascular embolization agent containing an antineoplastic drug and a preparation method thereof. Alginic acid is taken as a pharmaceutical carrier, the antineoplastic drug etoposide is a pharmaceutical active ingredient, divalent metal cation or calcium ion solution is taken as a solidifying agent, and the sodium alginate encapsulates the etoposide to prepare ideal particle size-controllable sodium alginate microspheres comprising the etoposide, thus avoiding toxic side effect of traditional etoposide administration such as anaphylaxis and inconvenience. The vascular embolization agent changes the dosage form and route of administration way of the antineoplastic drug etoposide, has high efficacy and low toxicity, and is safely and effectively applied to clinical application. The vascular embolization agent has the advantages of mild preparation condition and simple and convenient operation, and is fit for large-scale production. The vascular embolization agent can be used for vascular embolization, local targeted tumor treatment, and treating small-cell carcinoma of the lung, oophoroma, carcinoma of testis, gastric cancer and liver cancer by administering the vascular embolization agent during operations.

Methods and compositions are provided for the molecular subtyping of lung cancer samples. Specifically, a method of assessing whether a patient's lung cancer subtype is adenocarcinoma, squamous cell carcinoma, or a neuroendocrine (encompassing both small cell carcinoma and carcinoid) is provided herein. A method for assessing whether a patient's lung cancer subtype is adenocarcinoma, squamous cell carcinoma, small cell carcinoma or carcinoid lung cancer is also provided. The methods provided herein entail probing the levels of the classifier biomarkers of Table 1-Table 6 or a subset thereof at the nucleic acid level, in a lung cancer sample obtained from the patient. Based in part on the levels of the classifier biomarkers, the lung cancer sample is classified as a particular lung cancer subtype.

Methods of treating cancer using 4-amino-5-fluoro-3-[6-(4-methylpiperazin-1-yl)-1H-benzimidazol-2-yl]quinolin-2(1H)-one are provided. In particular, the methods are effective for the treatment of solid tumors or leukemias, including prostate, colorectal, breast, multiple myeloma, pancreatic, small cell carcinoma, acute myelogenous leukemia, chronic myelogenous leukemia, or myelo-proliferative disease. Further provided are methods of measuring the amount of 4-amino-5-fluoro-3-[6-(4-methylpiperazin-1-yl)-1H-benzimidazol-2-yl]quinolin-2(1H)-one and determining a metabolic profile therefore.

The invention relates to a biomarker for typing non-small cell lung cancer, and application thereof, and belongs to the technical field of medical detection. The biomarker comprises at least five genes such as TP53, STK11, PTEN, NFE2L, KRAS and the like. When squamous cell carcinoma and adenocarcinoma in small cell carcinoma of lung are subjected to typing by utilizing the biomarker, the AUC of a typing diagnosis ROC curve is 0.700 when the at least five markers are used, the AUC of the typing diagnosis ROC curve is 0.734 when the number of the markers is further increased to 10, and the AUC can reach 0.786 when all the biomarkers are used, so that the biomarkers have excellent diagnosis capability.

The invention discloses an early specific autoantibody panel diagnosis kit for small cell carcinoma of the lung. The kit is prepared from an antigen producing KRT8, CDC20 and POLDIP3 antibodies, a 1Msodium bicarbonate buffer solution, a PBST buffer solution, an enzyme-labeled antibody, a TMB substrate and a stop solution. The kit is high in sensitivity, strong in specificity, simple in operationand convenient in detection and has certain significance for diagnosis of the small cell carcinoma of the lung by being popularized clinically.

The invention belongs to the field of image analysis, particularly relates to a lymph node metastasis image analysis system, method and equipment based on deep learning, and aims to solve the problem that in the prior art, whether lymph node metastasis occurs in a non-small cell carcinoma image cannot be well predicted noninvasively. The method comprises the steps of obtaining a to-be-analyzed CT image containing a lesion microenvironment, obtaining an imaging sign and clinical information of the same subject as the CT image, extracting one-dimensional CT image features and one-dimensional clinical information features respectively, performing feature enhancement and normalization processing, performing fusion through a full connection layer to generate a fusion feature vector, and classifying the fused feature vectors to obtain an analysis result. The non-small cell lung cancer lymph node metastasis image data classification method achieves classification of non-small cell lung cancer lymph node metastasis image data, has good robustness and generalization ability compared with an existing traditional vector model based on predefined image features, and effectively improves the prognosis effect of a patient.

The disclosure provides a method of treating a malignant rhabdoid tumor in a subject in need thereof including administering to the subject a therapeutically-effective amount of an enhancer of a zestehomolog 2 (EZH2) inhibitor. In certain embodiments of this method the malignant rhabdoid tumor is small cell cancer of the ovary of the hypercalcemic type (SCCOHT) and the EZH2 inhibitor is tazemetostat (also known as Tazemetostat).