555 results about "Lung cancer" patented technology

There is provided herein compounds of formula (I), (XXI), (XXII) and (XXIII) as defined herein, and salts thereof, for use in the treatment of colorectal and / or lung cancer.

There is provided herein a compound of formula (I) wherein R1, R2, R3, R4, A, X1, Y, L, Z, R5, R6a, R6b, W and R7 are as defined herein, for use in the treatment of colorectal and / or lung cancer.

The invention belongs to the technical field of medicines, and relates to tetrahydropyridopyrimidine compounds as well as a preparation method and application thereof, in particular to tetrahydropyridopyrimidine compounds or pharmaceutically acceptable salts thereof as well as a preparation method and application thereof in preparation of antitumor drugs. The structure of the tetrahydropyridopyrimidine compound or the pharmaceutically acceptable salt thereof is as shown in a general formula (I), and R1-R4 are as shown in the specification and claims. The compound provided by the invention can be used for preparing a KRAS G12C inhibitor, is used for inhibiting G12C mutation of KRAS, has an obvious inhibiting effect on lung cancer, pancreatic cancer or colon cancer, and can be used for preparing antitumor drugs. # imgabs0 #

The present invention is directed to the compounds of Formula (A) inhibitors of KRAS(G12D). The inhibitors described herein can be useful in the treatment of diseases or disorders associated with KRAS(G12D), such as Lung cancer, Pancreatic cancer, Colorectal cancer et al. In particular, the invention is concerned with compounds and pharmaceutical compositions inhibiting KRAS(G12D), methods of treating diseases or disorders associated with KRAS(G12D), and methods of synthesizing these compounds.

The invention relates to the technical field of image segmentation, in particular to a PET-CT lung cancer image segmentation method and system based on deep learning. The method comprises the following steps: acquiring PET lung cancer image data and CT lung cancer image data, and performing multi-scale feature extraction on the PET lung cancer image data and the CT lung cancer image data by using a multi-scale feature encoder to obtain image feature data; performing image feature fusion based on a cross-modal attention mechanism according to the image feature data to obtain bimodal image fusion data; and carrying out interpretable attention module design according to bimodal image fusion data, marking attention intensity through color gradients, and generating a pixel-by-pixel attention thermodynamic diagram. Through multi-modal fusion, multi-scale feature extraction and an interpretable attention mechanism, the method has significant advantages in the aspects of improving the lung cancer image segmentation accuracy and enhancing the clinical interpretability.

The present invention is directed to the compounds of Formula (IV) inhibitors of KRAS(G12D). The inhibitors described herein can be useful in the treatment of diseases or disorders associated with KRAS(G12D), such as Lung cancer, Pancreatic cancer, Colorectal cancer et al. In particular, the invention is concerned with compounds and pharmaceutical compositions inhibiting KRAS(G12D), methods of treating diseases or disorders associated with KRAS(G12D), and methods of synthesizing these compounds.

The invention provides an atomizing agent containing stem cell exosomes as well as a preparation method and application of the atomizing agent, and belongs to the technical field of exosomes. Ferroferric oxide magnetic particles are prepared, the surfaces of the ferroferric oxide magnetic particles are modified through tannic acid, berberine and adriamycin are loaded, then the ferroferric oxide magnetic particles and the exosome secreted by adipose-derived mesenchymal stem cells are mixed, incubated and centrifuged, the mixture is added into normal saline, uniform ultrasonic dispersion is conducted, and the atomizing agent containing the stem cell exosome is prepared. The prepared atomizing agent containing the stem cell exosome is simple in preparation method and wide in raw material source, the prepared atomizing agent directly enters the lung through spray administration, the unique performance of magnetic targeting drug delivery is achieved, drugs are released in a targeted and fixed-point mode, the drug effect is improved, and the effects of efficiently promoting tumor cell apoptosis and resisting lung cancer and pneumonia are achieved.

The invention belongs to the technical field of histopathology full-slice image analysis, and relates to a gene mutation prediction method and system based on a pathological report and full-slice cross-modal representation learning, and the method comprises the steps: obtaining a histopathology full-slice image and a data set of a corresponding pathological and molecular detection report, and carrying out the preprocessing and coding; performing word segmentation and feature extraction on the pathological diagnosis report and the molecular detection report; cross-modal representation learning is realized through reconstruction of pathological report features and comparative learning based on a category refinement queue; designing a loss function and training the model offline by using a sample data set with a label; and performing lung cancer gene mutation prediction on the histopathology full-slice image by using the trained model. According to the method, the defects that detailed annotations of histopathology full-slice image data are difficult to obtain and the single-modal information expression ability is insufficient can be overcome, and slice image level mutation tag classification is effectively completed by using a cross-modal information guide weak supervision method of a pathological report and a molecular detection report.

Provided are methods for the treatment of SCLC patients by administering therapeutic amounts of lurbinectedin by intravenous infusion. Also provided are methods of treating cancer by administering lurbinectedin in combination with other anticancer drugs, in particular topoisomerase inhibitors. The invention further relates to the administration of lurbinectedin in combination with anti-emetic agents for effective control of symptoms related to nausea and vomiting, reduced lurbinectedin dosages to achieve a safer administration and an increase in the number of treatment cycles. Stable lyophilized formulations of lurbinectedin are also provided.

The invention discloses a lung cancer gene mutation classification method based on frequency domain multi-scale fusion guidance, and relates to the technical field of medical image processing and gene detection. According to the MFHA mechanism provided by the invention, the pathological image is decoupled into low-frequency global and high-frequency detail sub-bands through wavelet transform, and extraction of key high-frequency features such as cell nucleus morphology and local texture is enhanced by combining multi-scale convolution and up-sampling guided by high-frequency information; the problems of insufficient feature detail mining and low feature fusion efficiency in a traditional pathological image analysis method are solved; key features are screened and focused through a channel, frequency domain-space feature deep fusion is realized through up-sampling, robust representation is constructed by combining space attention with cosine similarity and multi-dimensional statistical features, a frequency domain analysis-space focusing collaborative optimization mechanism is formed, information redundancy caused by simple feature splicing is avoided, and the robustness of the system is improved. And the classification stability of the model in a complex pathological scene is improved.

The current disclosure is centered on the hypothesis that a better understanding of the neuroendocrine transdifferentiation (NEtD) process will provide therapeutic targets for inhibiting this transition and thus improving standard of care therapies. Accordingly, the current disclosure provides for a method for treating cancer in a subject, the method comprising administering an inhibitor of a gene, wherein the gene comprises one or more of tenascin C (TNC), advillin (AVIL), S100A7, PPARG, LOX lysyl oxidase, KLF5, APOBEC2, FOSL1, FOXM1, hedgehog, RELA, p65, IKK complex, JAK, STAT, TFAP4, geminin, OCA-1, OCA-2, Nf-kB, Nf-kB family and associated regulators, angiogenesis regulators such as BMX kinase, TEK kinase, periostin (POSTN), and VEGF family, stress genes, such as the JUN / FOS family, a gene from the S100 family, and cell state regulators such as ASCL1, POU2F3, NEUROD1, ASCL2, and YAP1.

The invention discloses an enzyme response type KRAS targeted protein degradation chimera as well as a preparation method and application thereof, and belongs to the technical field of tumor targeted therapy. The enzyme response type KRAS targeted protein degradation chimera disclosed by the invention is obtained by covalently linking three parts, namely a KRAS targeted protein degradation chimera, an enzyme response type amino acid sequence and a cell penetrating peptide amino acid sequence, wherein the KRAS targeted protein degradation chimera is obtained by linking a KRAS targeted peptide and a VHL E3 ligase ligand through succinic acid. The enzyme response type KRAS targeted protein degradation chimera releases the KRAS targeted protein degradation chimera under the action of ATG4 enzyme shearing, and shows a relatively strong lung cancer resisting effect in vitro and in vivo. The invention has significant advantages in the aspect of antitumor drugs, and opens up a new field for the development of targeted protein degradation chimera drugs. Enzyme response type KRAS targeted protein degradation chimera molecular structural formula as follows: # imgabs0 #

The invention relates to the technical field of medical artificial intelligence, in particular to a lung cancer diagnosis method, which comprises the following steps: data acquisition and preprocessing: acquiring CT image data and text data, and preprocessing the data, including image normalization, text standardization and weighting processing; image feature extraction: based on a pre-trained ResNet50 network, deep features of the CT image are extracted, and key features are enhanced through an attention mechanism; text feature processing: performing feature extraction on the preprocessed text data to generate a text feature vector; multi-modal feature fusion: fusing the image features and the text features, and extracting fusion features through a full connection layer and a regularization layer; and classification: model integration. Through the method, the contribution of each index to the classification result is clearer, so that the prediction stability and generalization ability are improved, the accuracy rate, the precision rate, the recall rate, the F1 score and the discrimination ability of the model are comprehensively evaluated, and the model effect is conveniently and objectively judged.

Provided are methods for combination treatment of a cancer using an antibody-drug conjugate (ADC) targeting CEACAM5 and an anti-PD-1 antibody or anti-PD-L1 antibody, optionally together with a platinum-containing agent such as cisplatin or carboplatin with or without pemetrexed. In certain embodiments the ADC is tusamitamab ravtansine. In certain embodiments the anti-PD-1 antibody is pembrolizumab. In certain embodiments, the cancer is nonsquamous non-small cell lung cancer (NSQ NSCLC). In certain embodiments, the cancer is advanced or metastatic NSQ NSCLC.

The invention belongs to the technical field of traditional Chinese medicine biology, and particularly relates to a phenolic compound and a preparation method and application thereof.The phenolic compound is a pair of diastereoisomers, the formula I of the phenolic compound is dextroisomer and is named as (+)-fresh bamboo juice phenol B, and the formula II of the phenolic compound is levoisomer and is named as (-)-fresh bamboo juice phenol B. A pair of diastereoisomer phenolic compounds (+)-fresh bamboo juice phenol B and (-)-fresh bamboo juice phenol B are successfully obtained from fresh bamboo juice, and the diastereoisomer phenolic compounds (+)-fresh bamboo juice phenol B and (-)-fresh bamboo juice phenol B have remarkable inhibition effects on gastric cancer cells, liver cancer cells, colorectal cancer cells, bladder cancer cells and lung cancer cells of a human body through in-vitro cell tests; the compound can be used for preparing medicines for preventing or treating tumors, and has a wide application prospect.

The invention belongs to the field of biomedicine, and particularly relates to polypeptide for targeted blocking of combination of TRIM25 and BRD7 protein and application of the polypeptide. According to the present invention, based on the minimum binding region PRYSPRY structural domain (439 aa-630 aa) of the TRIM25 and the BRD7 protein, the blocking peptide TB16 capable of specifically blocking the mutual binding of the TRIM25 and the BRD7 protein is screened, such that the ubiquitination degradation of the BRD7 is inhibited, and the stability of the BRD7 tumor inhibition protein is improved. The polypeptide drug TB16 can effectively inhibit breast cancer, nasopharynx cancer, ovarian cancer, lung cancer and liver cancer cell proliferation and breast cancer in-vivo tumor growth, has good anti-solid tumor activity, and is expected to become a new anti-tumor targeting drug.

The invention provides a platelet membrane bionic nano-drug delivery system as well as a preparation method and application thereof, and relates to the technical field of medicines. According to the invention, through membrane engineering modification, a wrapping material obtained through hybridization of a platelet membrane and an NK cell exosome is used for loading ginsenoside Rg3 for the first time, a ginsenoside Rg3 delivery system with high encapsulation efficiency and high drug loading capacity is obtained, and the system has excellent stability and can be stored for a long time in normal-temperature and high-temperature environments; the ginsenoside Rg3-loaded platelet membrane bionic nano-drug delivery system is simple in preparation method and suitable for wide popularization and application; according to the ginsenoside Rg3-loaded platelet membrane bionic nano-drug delivery system, the lung cancer treatment effect of ginsenoside Rg3 can be effectively improved, a novel drug is provided for lung cancer treatment, and the drug is high in safety, high in biocompatibility, free of adverse reaction in the treatment process and obvious in anti-inflammatory effect.

The invention discloses an EGFR L858R mutation site gene detection kit and application thereof, and belongs to the technical field of molecular biology. The kit comprises an LAMP primer group and a strand displacement probe, wherein the LAMP primer group comprises a pair of outer primers F3 / B3, a pair of inner primers FIP / BIP and a loop primer LP; the strand displacement probe comprises an F strand and a Q strand, the 3'end of the nucleotide sequence of the F strand is modified by a fluorophore, and the 5 'end of the nucleotide sequence of the Q strand is modified by a quenching group. According to the invention, an improved loop-mediated isothermal amplification-nucleic acid molecule line technology is utilized, a novel primer design method is utilized to reduce non-specific amplification, a blank chain segment or mismatch repair is introduced to adjust multiple probe dynamics, and an easily programmed logic line is utilized to realize intelligent analysis. A novel sensitive, rapid and portable EGFR-TKIs series mutant gene multiple + heavy and intelligent detection principle is obtained; in combination with clinical sample analysis, the lung cancer EGFR liquid biopsy gene detection kit with low cost, high efficiency and high precision is developed.

The invention discloses a preparation method and application of roasted barley and malt polysaccharide with an anti-cancer effect. The roasted barley malt polysaccharide is a neutral heteropolysaccharide which mainly takes-> 3)-beta-D-Glcp-(1-> and->-beta-D-Glcp-(1->) as main chains, branches exist at O-3 / O-4 positions, and the branch chains are mainly composed of-> 4)-beta-D-Xylp-(1->,-> 3, 4)-beta-D-Xylp-(1-> and alpha-D-Glcp-(1->. The monosaccharide composition comprises arabinose, glucose and xylose in a molar mass ratio of 1.86: 33.43: 1.00, and the molecular weight is 23.81 kDa. In-vitro activity experiments prove that the roasted barley malt polysaccharide disclosed by the invention has a remarkable inhibition effect on proliferation of liver cancer cells, lung cancer cells, breast cancer cells and colorectal cancer cells, particularly on the liver cancer cells, and shows outstanding anti-tumor activity, so that the roasted barley malt polysaccharide is expected to be developed and applied in the fields of foods, health-care products or medicines.

The disclosure relates to methods of assessing the success of treatment with durvalumab and chemotherapy for resectable non-small cell lung cancer (R-NSCLC) in patients based on circulating tumor DNA (ctDNA) detection, ctDNA clearance and / or partial clearance and / or variant allele fraction (VAF) before and after such treatment. The disclosure also relates to methods for treating patients with R-NSCLC based on ctDNA detection, ctDNA clearance and / or partial molecular clearance and / or VAF before and after such treatment.

The invention belongs to the field of biological pharmacy, and provides keratin YK93-4, a coding nucleic acid molecule thereof, an expression vector containing the nucleic acid molecule, a host cell containing the expression vector or genome integrated with the nucleic acid molecule, and a preparation method and a pharmaceutical composition of the keratin YK93-4. The invention also provides application of the keratin YK93-4 and related products thereof in preparation of medicines for treating lung cancer, lymphoma, breast cancer, melanoma, hysteromyoma, benign prostatic hyperplasia and the like.

The invention relates to a lung cancer cell drug resistance classification method and system based on high content imaging. The method comprises the following steps: carrying out fluorescent staining and multi-component labeling on cells to be detected; performing high-content imaging on the to-be-detected cells subjected to fluorescent staining to obtain a multi-channel cell image; carrying out drug resistance classification on the multi-channel cell image by utilizing an IRSNet network to obtain a classification result; wherein the IRSNet classification network comprises an Inception-v4 backbone network, an Inception-ResNet module, a Reduction module and a softmax function, and the Inception-v4 backbone network, the Inception-ResNet module, the Reduction module and the softmax function are connected in sequence. The Inception-v4 backbone network is used for extracting the image features of the multi-channel cell image; the Inception-ResNet module is used for improving the depth and the width of the Inception-v4 backbone network and introducing a residual error structure; the Reduction module is used for reducing the network structure of the image features; the softmax function is used for classifying the image features. Compared with the prior art, the method is higher in cell drug resistance classification precision and efficiency.

The invention relates to preparation of 10-trifluoromethoxy camptothecin compounds and application of the 10-trifluoromethoxy camptothecin compounds in antitumor drugs. The structural formula of the compounds is shown in the specification. In-vitro cytotoxic activity screening results show that the 10-trifluoromethoxy camptothecin compound has broad-spectrum anti-tumor activity, and shows relatively strong inhibitory activity on human liver cancer cells (HepG2), human non-small cell lung cancer cells (A549), human colon cancer cells (SW480), human bile duct cancer cells (QBC939), human breast cancer cells (MCF-7), human pancreatic cancer cells (PANC-1) and human pancreatic cancer cells (BxPC-3). The compound 10-trifluoromethoxy camptothecin I and the compound 7-ethyl-10-trifluoromethoxy camptothecin II have a relatively strong inhibition effect on the detected seven tumor cell lines, and the IC50 (half maximal inhibitory concentration) values of the compound 10-trifluoromethoxy camptothecin I and the compound 7-ethyl-10-trifluoromethoxy camptothecin II are respectively 0.913 to 0.0661 mu M and 4.932 to 0.0578 mu M, which are obviously superior to those of a contrast drug topotecan. Wherein the compound I and the compound II show the strongest inhibitory activity on a BxPC-3 cell line, and the IC50 values of the compound I and the compound II are 0.0661 + / -0.0065 [mu] M and 0.0578 + / -0.0043 [mu] M respectively. Therefore, the 10-trifluoromethoxy camptothecin compound is expected to be developed into a novel antitumor drug. # imgabs0 #

The invention belongs to the field of biological pharmacy, and provides keratin YK93-5, a coding nucleic acid molecule thereof, an expression vector containing the nucleic acid molecule, a host cell containing the expression vector or genome integrated with the nucleic acid molecule, and a preparation method and a pharmaceutical composition of the keratin YK93-5. The invention also provides application of the keratin YK93-5 and other products in preparation of drugs for treating lung cancer, lymphoma, breast cancer, melanoma, hysteromyoma, prostatic hyperplasia and the like.

This disclosure provides a method for treating a subject afflicted with tumor, which method comprises administering to the subject an antibody or an antigen-binding portion thereof that specifically binds to a Programmed Death-1 (PD-1) receptor and inhibits PD-1 activity. In some embodiments, the tumor is derived from a non-small cell lung cancer (NSCLC). In some embodiments, the tumor expresses Programmed Death Ligand 1. In some embodiments, the subject carries a wild-type STK11 gene.

Disclosed herein are methods, compositions, and devices for use in diagnosis and treatment of cancer. The methods include sequencing a panel of regions in cell-free nucleic acid molecules and detecting one or more biomarkers that are indicative of a cancer and capability for cancer subtyping.

Provided herein are methods of determining a molecular response score for use in predictive models, including scoring based on epigenetic methylation based detection of mutant allele fraction. The molecular response score may be used to monitor and guide administration of treatment to a subject.

The application discloses a CT image lung cancer recognition method based on reinforcement learning, generates a lung structure mask, outputs an initial lesion candidate region, an initial lesion mask, a morphological confidence map and a boundary response map, obtains a focused feature map, obtains an initial lesion fine mask, a boundary probability map and an uncertainty heat map, encodes a reinforcement learning state vector, establishes a DSAC-T refining intelligent agent, obtains an updated lesion fine mask, calculates a reward value, trains the DSAC-T refining intelligent agent by using the reward value, repeats the steps until a preset convergence condition is met or a maximum iteration number is reached, and outputs a final lesion fine mask; consistent lesion masks are generated, and comprehensive evaluation results for clinical diagnosis and follow-up are formed. The application improves the fine segmentation stability under a fuzzy boundary, high noise and extreme samples, and improves the detection rate of micro-lesions and clinical applicability.

The invention provides a lung cancer image recognition method and system, and the method comprises the steps: obtaining a lung image of a patient, and carrying out the image correction processing of the lung image, so as to obtain a corrected lung image; performing iterative denoising processing on the corrected lung image to obtain a denoised lung image; performing feature image segmentation on the denoised lung image to obtain a lung feature image; the method comprises the following steps: acquiring a historical template lung cancer image set, inputting the historical template lung cancer image set into a preset recognition model for training, inputting a lung feature image into the trained preset recognition model for recognition, and outputting a recognition result. Noise and artifacts existing in the image are effectively removed, interference information existing in the image can be eliminated at the same time, and then the recognition accuracy is improved.

Disclosed herein are antibodies and compositions used for binding to Gal3. Some embodiments allow for disrupting interactions between Galectin-3 (Gal3) and cell surface markers and / or proteins associated with neurological diseases and / or proteopathies, such as Alzheimer's disease. Additionally, disclosed herein are methods of treatment and uses of the antibodies or binding fragments thereof for the treatment of fibrosis, liver fibrosis, kidney fibrosis, cardiac fibrosis, pulmonary fibrosis, non-alcoholic fatty liver disease, non-alcoholic steatohepatitis, sepsis, atopic dermatitis, psoriasis, cancer, brain cancer, breast cancer, colorectal cancer, kidney cancer, liver cancer, lung cancer, pancreatic cancer, bladder cancer, stomach cancer, hematological malignancy, neurological diseases and / or proteopathies. Furthermore, some embodiments provided herein can cross the blood-brain barrier and can be conjugated or otherwise associated with one or more payloads for the treatment of a neurological disease.