1119 results about "Pulmonary Cancers" patented technology

The invention belongs to the technical field of medicines, and particularly relates to quinazoline stilbene derivatives as well as a preparation method, a composition and application thereof. The quinazoline stilbene derivative is synthesized by combining quinazoline with pharmacophores such as a styrene skeleton, and the quinazoline stilbene derivative structurally contains functional units such as a quinazoline functional unit and the pharmacophores such as the styrene skeleton, so that the compound is endowed with good anti-tumor activity. Researches show that the quinazoline stilbene derivative has a good anti-tumor effect including KRASG12C mutation non-small cell lung cancer, has the advantage of multi-target action, has an adjusting effect on Src kinase and related downstream signal channels of Statat, mTOR, Akt and PI3k, and is beneficial to reduction of tumor drug resistance. Compared with a complex structure modified compound, the quinazoline stilbene derivative disclosed by the invention is simple in structure and easy to prepare, and has a good application prospect.

The invention discloses a multi-task lung cancer brain metastasis lifetime prediction method based on multi-modal data fusion, and relates to the field of medical image processing, and the method comprises the steps: obtaining non-small cell lung cancer CT image data, gene data and clinical data; performing focus segmentation on the non-small cell lung cancer CT image data; feature extraction is carried out based on the focus segmentation result, and radiomics features and depth image features are obtained; performing feature extraction on the gene data to obtain gene features; missing value deletion and numeralization preprocessing are carried out on the clinical data to obtain clinical features; local cross-modal attention fusion is carried out on the radiomics features and the depth image features; performing global cross-modal attention fusion on the preliminary mixed image features, the gene features and the clinical features to obtain original mixed features; and performing conditional guidance diffusion based on the original mixed features to obtain a lung cancer brain metastasis classification judgment result and a lifetime prediction risk. According to the invention, the lifetime prediction accuracy and stability can be improved.

The disclosure provides a method for treating a subject afflicted with a tumor, e.g., derived from a non-small cell lung cancer (NSCLC), comprising administering to the subject a combination of a (a) chemotherapy, (b) an anti-PD-1 antibody or an anti-PD-L1 antibody, and (c) an anti-CTLA-4 antibody, wherein the chemotherapy is administered for a period of time that is less than the standard.

The application relates to a compound of formula (I) containing a thiazole ring, an indazol ring and a 6,7-dihydro-5H-pyrrolo[1,2-c]imidazole ring system, to pharmaceutical compositions containing it and its medical use. The compounds are described as selective allosteric inhibitors of T790M / L858R, T790M / L858R / C797S, L858R, L858R / C797S containing EGFR mutants and thus useful for the treatment of cancer, in particular non-small cell lung cancer.

The disclosure provides a method of treating a human subject afflicted with lung cancer (e.g., non-small cell lung cancer (NSCLC)) with a programmed death-1 (PD-1) pathway inhibitor (e.g., an anti-PD-1 antibody) and a concurrent chemoradiotherapy (CCRT, e.g., a platinum doublet chemotherapy (PDCT) and a radiation therapy) followed by a combination of a PD-1 pathway inhibitor (e.g., an anti-PD-1 antibody) and a lymphocyte activation gene-3 (LAG-3) antagonist (e.g., an anti-LAG-3 antibody). In some aspects, the method comprises a recovery period that begins upon completion of the treatment with the PD-1 pathway inhibitor and the CCRT and ends at the start of the treatment with the combination of the PD-1 pathway inhibitor and the LAG-3 antagonist.

A three-dimensional scaffold for use in engineered tissue includes a repeated 3D geometry; and at least one of a hydrogel, a biocompatible polymer, and a bioprintable polymer. The repeated 3D geometry may include an open geometry including a plurality of interconnected nodes configured to be seeded with living cells. The scaffold may be formed via bioprinting. The three-dimensional scaffold may also be used for (1) 3D tissue modelling (for liver, kidney, gut, pancreas, heart, lung, spleen, etc.), (2) disease modeling of different tumor types such as breast, colorectal, lung, liver, brain, ovarian and others, (3) drug testing / therapeutic screening of small molecule drugs, peptides, proteins, antibodies, ADCs, gene therapies, RNA-based therapeutics, cell therapies, and tissue therapies, and (4) therapeutic / drug delivery (i.e., via delivery device that can be used to control drug release based on different patterns).

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

The invention belongs to the technical field of biology, and relates to a biomarker for early diagnosis of non-small cell lung cancer and application of the biomarker. The biomarker comprises a combination of secretory phosphoprotein 1, epithelial cell adhesion molecules and matrix metallopeptidase 14, and / or a combination of coding nucleic acid of the secretory phosphoprotein 1, coding nucleic acid of the epithelial cell adhesion molecules and coding nucleic acid of the matrix metallopeptidase 14. The coding nucleic acid comprises mRNA or cDNA. In a test set, a non-small cell lung cancer circulating tumor cell scoring diagnosis model constructed by taking the biomarker as the characteristic has the diagnosis accuracy of 87.5% and the sensitivity and specificity of 92.5% and 82.5% respectively. Compared with existing clinical tumor indexes, cancer can be found more early, and early screening of the non-small cell lung cancer is facilitated.

Disclosed herein is use of a combination of Compound (A) (azenosertib), or a pharmaceutically acceptable salt thereof, and a KRAS G12C inhibitor, such as sotorasib or adagrasib, or a pharmaceutically acceptable salt thereof, for treating a disease or condition, such as a colorectal, pancreatic and / or non-small cell lung cancer.

The invention relates to a biomarker for predicting the curative effect of non-small cell lung cancer immunotherapy and application of the biomarker. The biomarker for predicting the curative effect of the non-small cell lung cancer immunotherapy, disclosed by the invention, comprises phosphoglycerate kinase 1 (PGK1), chromogranin A (CHGA), elastin (ELN), heterogeneous ribonucleoprotein H3 (HNRNPH3) and SERPINE1 mRNA binding protein 1 (SERBP1). The biomarkers for predicting the non-small cell lung cancer immunotherapy curative effect can be detected by adopting a mass spectrum method, and the non-small cell lung cancer immunotherapy curative effect of a patient is judged by the markers.

The invention discloses a non-small cell lung cancer brain metastasis prediction method and device, and relates to the field of non-small cell lung cancer brain metastasis prediction. The method comprises the following steps: acquiring two-dimensional non-small cell lung cancer CT image data; inputting two-dimensional non-small cell lung cancer CT image data into the trained focus boundary segmentation model, and outputting a focus region segmentation image; the focus boundary segmentation model adopts an alternating network architecture based on a transformer block and a double-current Mangbar-transformer block; according to the focus area segmentation image, utilizing the trained non-small cell lung cancer brain metastasis prediction model to obtain a prediction result of whether the non-small cell lung cancer CT image data is a brain metastasis label or not according to the non-small cell lung cancer CT image data; the non-small cell lung cancer brain metastasis prediction model is a deep learning classification network of a heterogeneous axial cross attention mechanism with discrete wavelet transform processing. According to the method, the accuracy of predicting the brain metastasis result by using the non-small cell lung cancer CT image data can be improved.

The invention relates to a plasma biomarker for predicting the curative effect of non-small cell lung cancer immunotherapy and application of the plasma biomarker. The biomarker for predicting the curative effect of the non-small cell lung cancer immunotherapy, disclosed by the invention, comprises phosphoglycerate kinase 1 (PGK1), fibronectin 1 (FN1), chromogranin A (CHGA), elastin (ELN), heterogeneous ribonucleoprotein H3 (HNRNPH3) and an Aly / REF output factor (ALYREF). The plasma biomarkers for predicting the non-small cell lung cancer immunotherapy curative effect can be detected by adopting a mass spectrum method, and the non-small cell lung cancer immunotherapy curative effect of a patient is judged by the markers.

The invention discloses an application of a polysaccharide monomer separated from schisandra chinensis in preparation of a PD-L1 + TAMs activator. A large number of experiments show that the polysaccharide monomer schisanan B separated from schisandra chinensis can effectively activate PD-L1 + TAMs cell subsets, so that the phagocytosis of TAMs is enhanced, and the proliferation of tumor cells is inhibited; therefore, it is determined that the polysaccharide monomer schisanan B separated from schisandra chinensis can serve as a natural PD-L1 + TAMs cell subset activator to be used for treating cancers such as non-small cell lung cancer, intestinal cancer, melanoma, urothelial carcinoma or liver cancer, and the polysaccharide monomer schisanan B has the advantages of being free of toxic and side effects, low in price, wide in adaptive patient population and the like.

The present invention relates to the field of biomedicine, and specifically is a method for detecting platelet markers of non-small cell lung cancer, comprising the steps of: A. acquiring a gene data source; B. preprocessing gene data; C. analyzing gene differences; D. screening prognostic genes; E. selecting prognostic characteristic genes; and F. displaying analysis results. The present invention can determine characteristic genes that are closely related to the prognosis of patients with non-small cell lung cancer: by analyzing differential genes between different subtypes, the present invention determines ten characteristic genes that are closely related to the prognosis of patients with non-small cell lung cancer, providing new clues for further prognosis evaluation.

The invention relates to the technical field of biological medicine, and particularly discloses a plant exovesicle combined preparation for treating non-small cell lung cancer and a preparation method and application thereof, and the plant exovesicle combined preparation comprises ginseng exovesicles and turmeric exovesicles. The plant external vesicle combined preparation provided by the invention is used for inhibiting non-small cell lung cancer cells and promoting apoptosis of the non-small cell lung cancer cells, and can be used for preparing medicines for treating the non-small cell lung cancer.

The present invention discloses an anti-non-small cell lung cancer active birch inonotus polysaccharide IOP-1 and its application, belonging to the field of biomedicine. The present invention adopts a method of boiling water extraction and ethanol precipitation of birch inonotus polysaccharide, and combines DEAE cellulose column purification technology, and utilizes the principle that macromolecular polysaccharides are insoluble in organic solvents to successfully achieve the separation of birch inonotus polysaccharide and obtain a birch inonotus polysaccharide IOP-1 with anti-non-small cell lung cancer activity, wherein the monosaccharide composition of the birch inonotus polysaccharide IOP-1 includes fucose, rhamnose, arabinose, galactose, glucose, xylose and mannose with a molar mass ratio of 2.41:0.58:1.03:2.17:82.20:4.33:7.29. Its significant effect against non-small cell lung cancer was verified by in vitro and in vivo experiments, providing a new treatment method for the clinical treatment of non-small cell lung cancer.

The invention relates to an application of an intervention SNRK-MTA1 signal channel axis in preparation of a non-small cell lung cancer targeted therapy drug. The nucleotide sequences of the mRNA of the SNRK gene and the mRNA of the MTA1 gene are respectively as shown in SEQ ID NO.1-2. The invention innovatively provides a strategy for treating the non-small cell lung cancer through double-target combined intervention. According to the strategy, SNRK gene expression is improved through exogenous gene overexpression plasmids, and meanwhile MTA1 gene expression is silenced through the siRNA technology. In a non-small cell lung cancer model, the strategy of combined application of the SNRK-OE plasmid and siMTA1 can specifically up-regulate the SNRK mRNA level and knock down the MTA1 mRNA level at the same time, and the combined strategy shows a better anti-tumor effect than single intervention, and can more effectively inhibit the growth and migration of tumor cells. Based on the discovery, the SNRK-MTA1 signal pathway axis can be developed into a novel therapeutic target for non-small cell lung cancer, and is used for designing a drug combination scheme or a composite targeted drug.

The present invention provides improved and / or shortened processes and methods for preparing TILs in order to prepare therapeutic populations of TILs with increased therapeutic efficacy for the treatment of non-small cell lung carcinoma (NSCLC), wherein the NSCLC is refractory to treatment with an anti-PD-1 antibody and / or anti-PD-L1 antibody and / or VEGF inhibitor, or wherein the NSCLC has a predetermined tumor proportion score (TPS).

The invention relates to a biomarker combination for clinical benefit of non-small cell lung cancer immunotherapy and application of the biomarker combination. The biomarker for predicting the clinical benefit of the non-small cell lung cancer immunotherapy comprises an immune globulin kappa light chain variable region 1-27 (IGKV1-27), a human leukocyte antigen H (HLA-H), an S100 calcium binding protein A8 (S100A8), a chromogranin A (CHGA), an elastin (ELN) and a nephronectin (NPNT). The biomarkers for predicting the clinical benefit of the immunotherapy of the non-small cell lung cancer can be detected, and the clinical benefit effect of the immunotherapy of the non-small cell lung cancer of a patient is judged by the markers.

The invention provides a small cell lung cancer organoid culture medium and an application method thereof. The small cell lung cancer organoid culture medium is prepared from the following components: 10 to 500 [mu] g / mL of R-spondin-1, 10 to 500 [mu] g / mL of Noggin, 0.01 to 0.2 mg / mL of EGF (Epidermal Growth Factor), 0.05 to 0.2 [mu] g / mL of FGFb (Fibroblast Growth Factor b), 0.1 to 10 [mu] g / mL of FGF10, 0.02 to 0.5 mM of A83-01, 0.5 to 20 mM of Y-27632, 1 to 500 mM of SB202190, 0.1 to 200 mM of Nicotinamide, 0.1 to 500 mM of Insulin, 0.1 to 50 nM of protodioscin, 1 to 100 [mu] All the components are dissolved in a DMEM / F12 culture solution. The small cell lung cancer organoid culture medium provided by the invention is suitable for small cell lung cancer tissue organoid culture after component concentration optimization design, good in stability, high in growth speed and remarkably improved in passage frequency, and can still maintain the same tissue structure and genome characteristics of primary tissues after multiple passages; and an ideal model can be provided for research on the occurrence and development mechanism of small cell lung cancer, detection and research on drug sensitivity and the like.

The invention relates to the technical field of medical artificial intelligence, and discloses a non-small cell lung cancer immunotherapy risk assessment method and system and a storage medium, and the method comprises the steps: constructing an optimal strategy tree model capable of dividing a patient into a plurality of subgroups based on a historical patient data set, and determining an initial optimal treatment strategy for each subgroup; determining a subgroup to which a new patient belongs and an initial treatment strategy thereof according to the model; in the treatment process, the deviation degree between the individual response trajectory of the patient and the average response trajectory of the subgroup to which the individual response trajectory belongs is calculated; and when the deviation degree exceeds a preset threshold value of the subgroup, triggering an adaptive adjustment mechanism, and outputting an updated treatment suggestion. By establishing a dynamic monitoring and closed-loop feedback mechanism based on the subgroup benchmark, the technical problem that an existing scheme is difficult to carry out prospective identification and dynamic intervention on individualized risks is solved, so that the accuracy, safety and individualized level of non-small cell lung cancer immunotherapy are improved.

The invention provides a non-small cell lung cancer auxiliary diagnosis composition and application and a kit thereof, and relates to the technical field of biological detection.The non-small cell lung cancer auxiliary diagnosis composition comprises a circular RNA ALG8 primer and a circular RNA CAMTA1 primer, circALG8 and circCAMTA1 can be used as markers of early non-small cell lung cancer liquid biopsy, and the non-small cell lung cancer auxiliary diagnosis composition can be applied to diagnosis of non-small cell lung cancer. According to the present invention, with the application of the circALG8 primer and the circCAMTA1 primer, the plasma circALG8 and circCAMTA1 combined diagnosis model can be successfully constructed, the NSCLC patient and the healthy control can be effectively distinguished, the area under the curve is up to 0.8987 when the circALG8 primer and the circCAMTA1 primer are combined to identify the efficiency of the early NSCLC, the identification result has extremely high accuracy, the diagnosis accuracy is significantly improved, the sensitivity reaches 91.78%, and the specificity reaches 75.53%.

An antibody-drug conjugate and a preparation method therefor and a use thereof, in particular, an antibody-drug conjugate for treating HER3-positive cancers. The antibody-drug conjugate contains a fully human HER3 antibody, has excellent binding activity to HER3-positive cells, and can efficiently deliver a drug to HER3-positive cells. The antibody-drug conjugate has a good drug-antibody coupling ratio, and has a good targeted killing effect on colon cancer, gastric cancer, breast cancer, and lung cancer (e.g., non-small cell lung cancer, specifically lung adenocarcinoma). Therefore, further provided are a method for preparing the antibody-drug conjugate and a use of the antibody-drug conjugate in treatment of HER3-positive cancers.

The invention provides an alkaloid compound as well as a preparation method and an application thereof in tumor resistance. The alkaloid compound provided by the invention shows a remarkable cytotoxic effect on human non-small cell lung cancer cells A549, mouse lung adenocarcinoma cells Lewis, human triple negative breast cancer cells MDA-MB-231 and mouse breast cancer cells 4T1, and can be used for preparing medicines for treating breast cancer, lung cancer and the like.

The invention provides an FTO (fluorine-doped tin oxide) inhibitor as well as a preparation method and application thereof, and particularly discloses 2-(substituted benzene miscellaneous group) aromatic formic acid as shown in the following general formula (I), derivative compounds of the 2-(substituted benzene miscellaneous group) aromatic formic acid and pharmaceutically acceptable salts, hydrates or solvates of the 2-(substituted benzene miscellaneous group) aromatic formic acid, which can be used as an FTO target inhibitor for treating diseases related to the FTO target. The compound can be used for treating human myelodysplastic syndrome, such as leukemia, lymphoma, myelodysplastic syndrome, obesity, metablic syndrome (MS), type II diabetes (Type 2 diabetes, T2D), Alzheimer's disease, breast cancer, kidney cancer, colorectal cancer, pancreatic cancer, liver cancer, small cell lung cancer, human bone marrow rhabdomyoma, pancreatic cancer, malignant glioblast brain tumor and the like. # imgabs0 #

The invention discloses a coumarin KRAS-G12C inhibitor as well as preparation and application of the coumarin KRAS-G12C inhibitor. The coumarin compound disclosed by the invention has a remarkable inhibition effect on non-small cell lung cancer cells (NCI-H23 and NCI-H358) with high expression of KRAS-G12C and pancreatic cancer cells (MIAPaCa-2), is particularly used for preparing medicines for treating and / or preventing non-small cell lung cancer and pancreatic cancer, and has a good prospect of development and application of antitumor medicines.

The invention discloses a multifunctional nano delivery system based on targeted ferritin as well as a preparation method and application of the multifunctional nano delivery system. According to the system, traditional Chinese medicine active ingredients, namely neogambogic acid GNA, a photosensitizer Ce6 and ferritin targeting peptide HKN15 are integrated through a self-assembly technology, a synergistic treatment system integrating photodynamic therapy PDT and ferroptosis induction is constructed, and the treatment effect on non-small cell lung cancer NSCLC can be remarkably enhanced. According to the nano delivery system, precise targeting of a tumor site is achieved through the ferritin targeting peptide HKN15, and a double anti-tumor mechanism is formed by utilizing the photodynamic effect of the photosensitizer Ce6 and the ferroptosis induction effect of GNA. The preparation process is based on a molecular self-assembly principle, and has the advantages of high tumor accumulation efficiency, low system toxicity, remarkable tumor inhibition effect and the like, and an innovative solution is provided for precise treatment of the non-small cell lung cancer.

The invention discloses a pharmaceutical composition for treating non-small cell lung cancer and application of the pharmaceutical composition. The composition comprises an IGF2BP3 inhibitor and a platinum chemotherapeutic drug. According to the combined medication scheme, the IGF2BP3 function is inhibited to block an ATF4 survival promoting signal channel mediated by the IGF2BP3 function, a synergistic effect is generated with a DNA damage mechanism of platinum drugs, the anti-tumor effect can be remarkably enhanced, chemotherapy drug resistance can be effectively reversed, toxic and side effects are expected to be reduced, and the application prospect is wide. And a new strategy is provided for overcoming the treatment problem of the non-small cell lung cancer, especially platinum-resistant non-small cell lung cancer.

The invention discloses a construction method of a non-small cell lung cancer classification prediction model. The construction method comprises the following steps: S1, acquiring data of a training set sample and clinical feature data corresponding to the sample; s2, acquiring immune related gene data; s3, extracting prognosis genes related to non-small cell lung cancer metastasis traits and expression conditions of the prognosis genes from the data of the training set samples in the step S1, and intersecting the prognosis genes and the expression conditions of the prognosis genes with the immune related gene data in the step S2 to obtain intersection genes as candidate genes; s4, screening the candidate genes in the step S3 to obtain immune characteristic genes and expression conditions thereof; and S5, constructing a model based on the immune characteristic gene in the step S4 to obtain a classification prediction model. The method comprises the following steps: screening out key immune characteristic genes and expression conditions thereof by combining immune-related gene data, and constructing a classification prediction model according to the key immune characteristic genes; and inputting gene expression data of a to-be-detected sample into the classification prediction model to classify the to-be-detected sample to be high-risk or low-risk.

The invention belongs to the technical field of data processing, and particularly discloses a method and system for predicting the lifetime of a non-small cell lung cancer patient after radiotherapy, and the method comprises the steps: collecting multi-time-point imaging and hematology follow-up visit data of the patient after radiotherapy, building a longitudinal follow-up visit sequence, and mapping the longitudinal follow-up visit sequence to a unified time axis; determining a bimodal first-time significant improvement point through preset rule judgment, and constructing and standardizing an asynchronous index according to the bimodal first-time significant improvement point; then inputting a feature vector at a follow-up time point, encoding a bimodal sequence through a Transform time sequence encoder, and generating joint representation through cross-modal interaction; and finally, inputting the standardized asynchronous index, the joint representation and the clinical and radiotherapy characteristics into a DeepHit model, and outputting a patient survival distribution prediction result. According to the method, bimodal indexes can be accurately captured, time dislocation is improved, prediction accuracy and individualization degree are improved, and a reliable basis is provided for clinical prognosis evaluation.