23 results about "Observed Survival" patented technology

The invention relates to the field of biological medicines, and discloses application of serum EPSTI1 in preparation of a product for diagnosing liver cancer and evaluating whether a liver cancer patient is resistant to a revatinib or not. The invention provides a detection means which is convenient and rapid in sampling, small in risk and relatively low in cost, the content of EPSTI1 in serum is detected through an enzyme-linked immunosorbent assay, a liver cancer patient and a non-liver cancer patient can be effectively distinguished, and a lovatinib drug-resistant liver cancer patient and a non-drug-resistant liver cancer patient can be effectively distinguished. Prognosis analysis shows that the serum EPSTI1 can be used as a marker for evaluating the prognosis state of the liver cancer patient taking the lenvatinib, and has important significance in improving the survival rate of the liver cancer patient.

The application discloses application of a reagent for detecting AHSP protein in preparation of a product for diagnosing prostate cancer, and relates to the technical field of biological medicine; through proteomic analysis, ELISA test on urine protein of prostate cancer patients, clear cell renal cell carcinoma patients and normal healthy men, and immunohistochemical analysis on file wax blocks of the prostate cancer patients, normal prostate tissues around the cancer, prostate tissues of prostatic hyperplasia and clear cell renal cell carcinoma tissues, it is found that the AHSP protein has a certain relationship with the occurrence and development of prostate cancer, and can be used for assisting diagnosis of the prostate cancer; and in urine detection, AHSP has higher sensitivity than PSA, and when PSA is negative or serum PSA is low, AHSP can form complementation with ASHP, thereby helping to improve the diagnosis rate and non-invasive screening ability; through research on the relationship between the AHSP protein and the prostate cancer, the diagnosis rate of patients can be improved, non-invasive reexamination after treatment is facilitated, drug use is guided, and the survival rate is improved.

The present disclosure relates to predicting a survival rate of a patient with cancer following a treatment. In some embodiments, one or more processors: apply a large language model to a clinical report to extract a plurality of clinical features; acquire a pre-treatment image and a post-treatment image of the patient with cancer; apply a segmentation algorithm on an annotated volume of interest (VOI) of the pre-treatment image to obtain a first segmented VOI; apply the segmentation algorithm on the annotated VOI of the post-treatment image to obtain a second segmented VOI; determine a plurality of radiomics features and a plurality of deep learning features from the first segmented VOI and the second segmented VOI; and apply a machine learning model to the plurality of clinical features, the plurality of radiomics features, and the plurality of deep learning features to predict the survival rate of the patient with cancer.

The application discloses a methylation marker combination for detecting early gastric cancer and application thereof. The marker combination comprises 146 methylation sites of 11 DNA regions and a transformation rate control marker region, and the methylation levels of the target regions are significantly different between early gastric cancer patients and healthy people. The kit of the application contains reagents for detecting the methylation degree of the above sites, and supports various high-throughput sequencing methods. The detection system adopts a logistic regression model to calculate a prediction value, multiplies the average methylation rate of each region by a corresponding weight coefficient, adds them together, and compares the sum with a threshold value to make a positive judgment. The application realizes high sensitivity and high specificity for non-invasive early detection, is particularly suitable for non-invasive screening of plasma free DNA samples, can effectively improve the survival rate of gastric cancer patients, can significantly reduce medical expenses, and has a wide clinical application and industrial utilization prospect.

The invention relates to the technical field of biological medicines, in particular to application of a ZNF710 gene in preparation of a preparation for hepatocellular carcinoma diagnosis and / or prognosis evaluation. The invention finds and verifies that ZNF710 is closely related to prognosis of liver cancer for the first time and is a key gene for occurrence and development of tumors, and patients with low expression of the ZNF710 gene have higher survival rate. Therefore, compared with the prior art, a novel liver cancer diagnosis and treatment scheme taking the ZNF710 gene as the molecular marker has relatively high clinical application value and potential.

The application discloses application of a sugar chain marker combination in preparation of a product for diagnosing and predicting prognosis of pancreatic cancer, and the marker combination comprises the following N-glycan chains: NGA2F, NG1A2F-1, NG1A2F-2, NA2, NA2F, NA2FB, NA3 and NA3Fb. The application analyzes the correlation between the change of the sugar chain on the serum glycoprotein and the disease, establishes a prediction model of the sugar chain marker combination to detect the pancreatic cancer, thereby assisting in diagnosing and distinguishing the pancreatic cancer from non-pancreatic cancer, and meanwhile, the prognosis state of the pancreatic cancer patient treatment can be evaluated. The method for detecting the sugar chain marker combination has high sensitivity and high specificity for the pancreatic cancer, can help the pancreatic cancer patient to be found and treated early, and can predict and evaluate the prognosis state of the pancreatic cancer patient, thereby improving the overall cure rate and survival rate of the patient.

The application discloses a plasma metabolic marker composition and a screening method and application thereof, and relates to the technical field of biomedicine. The plasma metabolic marker composition comprises glycyl-L-glutamic acid, phosphatidylcholine 38:7, pyrrole-2-formic acid and phosphatidylethanolamine 36:2p. The metabolic marker composition is significantly different in different cancer types, can distinguish different cancer types of cancer patients, and realizes the detection of pan-cancer. The metabolic marker composition is non-invasive and minimally invasive when used for the detection of pan-cancer, is more suitable for the screening and detection of a large number of ordinary people, has high sensitivity and specificity, is more suitable for the early screening of cancer, and is helpful for the early screening, early diagnosis and early treatment of cancer, and is helpful for improving the survival rate and cure rate of cancer patients.

The application discloses a method for predicting immunogenic peptide segments of tumor intratumoral microorganisms and application thereof, and mainly comprises the following steps: collecting tumor tissue RNA-seq data, screening microorganism markers related to tumor immunity, and predicting immunogenic peptide segments in microorganisms. The application first proposes a method for predicting immunogenic peptide segments in tumor microorganisms based on sufficient mining of tumor RNA-seq data, so that new targets for tumor immunotherapy are provided, and the possibility of improving the survival rate and prognosis effect of tumor patients is realized.

The invention discloses a colorectal cancer multi-target prognosis risk assessment model construction method based on palmitoylation related lncRNA, and relates to the technical field of colorectal cancer prognosis model construction. The method comprises the following steps: step 1, data acquisition; step 2, identifying lncRNA (long non-coding ribonucleic acid) related to S-palmitoylation; step 3, determining a key lncRNA (long non-coding RNA) for constructing a prognosis model; 4, establishing a risk scoring model; and 5, testing the prognosis model. Based on a TCGA database, palmitoylation related genes and CRC transcriptome data are integrated, lncRNA significantly related to the palmitoylation related genes and the CRC transcriptome data is screened through co-expression analysis, and a multi-target prognosis risk assessment model based on the palmitoylation related lncRNA is constructed. And further model testing and mechanism exploration, immune infiltration and mutation load evaluation, drug sensitivity prediction and the like are carried out, so that a more accurate prognosis evaluation tool is expected to be provided for CRC patients, the development of mechanism-driven individualized treatment strategies is promoted, and the method has important significance in improving treatment of the patients and increasing the survival rate.

The application discloses a biomarker related to bladder cancer and application thereof, the biomarker is tRF-1:28-chrM.Ser-TGA and / or tiRNA-1:34-Glu-CTC-1-M2, which can be used for preparing a bladder cancer early high-risk patient diagnosis and / or prognosis evaluation product, and belongs to the technical field of biological medicine. The biomarker is screened through RNA sequencing, has higher sensitivity and specificity as a biomarker, and is verified through qRT-PCR and ROC curve analysis, and it is proved that tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 can excellently distinguish bladder cancer patients from normal people, and can be used as an early diagnostic biomarker and a new treatment target of bladder cancer patients, which has great clinical value and practical significance for early clinical diagnosis of bladder cancer, related treatment target evaluation and improvement of the survival rate of patients.

The invention provides a culture medium and a culture method of normal oral fibroblasts. The culture medium comprises a DMEM (Dulbecco's Modified Eagle Medium) and the following components based on the volume of the DMEM: 10v% of Australian fetal calf serum, 2.5 ng / ml of bFGF (Basic Fibroblast Growth Factor), 1v% of a penicillin-streptomycin solution, 2.0 ug / ml of hydrocortisone and 0.05 ug / ml of FGF10 (Fibroblast Growth Factor 10). The invention solves the problems of high NF culture difficulty, easy pollution, low survival rate, incapability of permanent passage and the like, provides a basis for further exploring a mechanism for activating the NF into CAFs, is beneficial to finding and finding new therapeutic targets, and provides a new clinical diagnosis and treatment idea for treating and preventing the deterioration of the salivary gland benign tumor.

The present application relates to the biomedical technology field, and more particularly to a diagnostic kit based on acute leukemia prognosis and drug sensitivity prediction, comprising prediction module I and prediction module II.Prediction module I is used for predicting the clinical survival rate of patients, and one or more of 32 molecules such as CCND3, FERMT3 and PLD4 is used as a prognostic marker; prediction module II is used for predicting the sensitivity of the body to drugs, and one or more molecules of BMP8B, IGF1R, OTULINL, SLC22A15, CERS1 and PDE4A are used as drug sensitivity markers.The present application breaks through the limitations of single biomarker prediction efficiency by constructing a double prediction model, realizes the functional coupling of survival prognosis and multiple drug sensitivity prediction, and provides an integrated tool for clinical transformation for AML precise treatment.

The present application relates to the technical field of biological medicine, and provides a lung cancer marker detection method based on induced sputum cells combined with flow cytometry. The lung cancer marker detection method includes TTF-1 protein, CK7 protein and P63 protein. Antibodies for specifically recognizing and detecting the lung cancer marker include TTF-1 antibody, CK7 antibody and P63 antibody. The amino acid sequence of the light chain variable region of the TTF-1 antibody is shown in SEQ ID NO. 1, and the amino acid sequence of the heavy chain variable region is shown in SEQ ID NO. 5. The amino acid sequence of the light chain variable region of the CK7 antibody is shown in SEQ ID NO. 9, and the amino acid sequence of the heavy chain variable region is shown in SEQ ID NO. 13. The amino acid sequence of the light chain variable region of the P63 antibody is shown in SEQ ID NO. 17, and the amino acid sequence of the heavy chain variable region is shown in SEQ ID NO. 21. The present application can obtain an induced sputum sample in a non-invasive or minimally invasive manner, can reduce the pain of patients, can avoid misdiagnosis due to high specificity, can facilitate early diagnosis of lung cancer due to high sensitivity, and early diagnosis is a key to improving the cure rate and survival rate.

Provided is a methylation marker for gastric cancer detection. Provided are 28 differentially methylated regions (DMRs) for diagnosing or assisting with the diagnosis of cancer, and an ELMO1 gene and a KCNA3 gene with a better performance are selected from these 28 DMRs as preferred methylation markers for detecting gastric cancer. Provided is an accurate, simple and economical means for the early screening of gastric cancer, which can improve the detection rate of gastric cancer, particularly early gastric cancer, in gastric cancer high-risk populations and populations undergoing routine physical examinations, thereby improving the survival rate of gastric cancer patients, while saving on substantial medical expenses and alleviating the medical burden.

This invention discloses a prognostic assessment model for endometrial cancer based on DUSP1, BUB1, and MCM7, and its application. The prognostic assessment model includes an endometrial cancer prognostic risk scoring model and an endometrial cancer overall prognostic scoring model. The endometrial cancer prognostic risk scoring model includes a recurrence-free survival risk scoring model and an overall survival risk scoring model; the overall prognostic scoring model includes a recurrence-free survival overall score model and an overall survival overall score model. Experiments have demonstrated that the prognostic assessment models for endometrial cancer based on this invention can effectively predict the recurrence-free survival rate and overall survival rate of endometrial cancer patients. The prognostic assessment models for endometrial cancer provided by this invention facilitate stratified management of endometrial cancer patients, reduce overtreatment, accurately predict recurrence, and provide theoretical and clinical basis for guiding individualized clinical treatment of endometrial cancer patients.

The invention provides a plasma metabolism marker for kidney cancer diagnosis and application thereof, and belongs to the technical field of disease diagnosis. According to the invention, through comprehensive analysis and comparison of metabolic profiles of healthy people, kidney benign disease patients and kidney cancer patients, a group of metabolic marker combination with high specificity and significant difference is screened out, and the metabolic marker combination comprises 14 metabolic markers. As an end product of cell metabolic activity, the metabolic marker can more directly and sensitively reflect the abnormal metabolic state of tumor cells, so that early accurate recognition of kidney cancer and precancerous lesions is realized, the sensitivity of early diagnosis is remarkably improved, and the current clinical dilemma of'late stage once found 'is fundamentally reversed. The strategy is expected to greatly improve the survival rate and life quality of patients with kidney cancer, and a brand new path is provided for promoting precise medical treatment of kidney cancer.

The invention discloses an ovarian cancer prognosis analysis method, system and device, and the method comprises the following steps: 1, obtaining case data of an ovarian cancer patient, and removing case data without patient survival information, the case data comprising patient clinical data and ovarian cancer gene expression data; 2, carrying out clustering analysis on the gene expression data and inflammation genes of the ovarian cancer patients meeting the requirements in the step 1, and screening out differentially expressed inflammation related genes; 3, performing univariate Cox regression analysis on the differential gene expression level obtained in the step 2 and the survival rate of the ovarian cancer patient, and screening inflammation-related genes with prognosis value; through multivariable Cox regression analysis, inflammation-related genes with remarkable ovarian cancer prognosis are screened; 4, establishing an ovarian cancer prognosis model based on the ovarian cancer prognosis significant inflammation related genes screened in the step 3; and 5, based on the prognosis model constructed in the step 4, performing prognosis analysis on the case data of the ovarian cancer patient. Through verification, the prognosis model constructed by the invention can be used for prognosis of ovarian cancer patients.

The invention discloses a lung cancer bone metastasis marker, and belongs to the technical field of biomarkers. The lung cancer bone metastasis marker provided by the invention can realize early-stage, non-invasive and accurate detection of lung cancer bone metastasis, effectively improve the diagnosis sensitivity and specificity, provide reliable basis for clinical prognosis evaluation, relapse monitoring and individualized treatment, has the advantages of simplicity and convenience in operation, good repeatability, high cost effectiveness and the like, and has a wide application prospect. The life quality of a patient can be improved; the medical burden is reduced. According to the invention, the technical blank of lung cancer bone metastasis specific markers is filled, the crossing from image diagnosis to molecular early warning and from empirical treatment to accurate intervention is realized, and the marker has important clinical significance and application value for improving the survival rate and life quality of lung cancer patients.

The application discloses biomarkers in glioblastoma classification diagnosis or prognosis prediction, and the biomarkers are PLCH1 genes and EGFR genes. The PLCH1 genes and the EGFR genes in a to-be-detected ex vivo biological sample are detected by using reagents, and the marker genotypes are used for classification diagnosis or prognosis prediction of the glioblastoma. According to the biomarkers, GBM patients are classified, a survival prediction model of the glioblastoma patients is constructed through reasonable assignment of the classification, and the accuracy of the survival rate prediction of the GBM patients is greatly improved.

The application belongs to the technical field of biological medicine, and specifically discloses a use of mesencephalic astrocyte-derived neurotrophic factor (MANF) as a biomarker and a therapeutic target in sepsis. The application finds that MANF can be used as a new biological marker for predicting sepsis, and the expression level thereof is negatively correlated with the severity of the disease, so it is proposed that the MANF can be used as a diagnostic, prognostic and curative effect evaluation index of sepsis, for the diagnosis of sepsis and the reflection of the severity of the disease. Meanwhile, it is found that the administration of exogenous MANF recombinant protein to a sepsis mouse model can significantly improve the survival rate, so it is proposed that the MANF can be used as a potential therapeutic target for sepsis. The application provides a new technical means for the diagnosis, prognosis, curative effect evaluation and treatment of sepsis and related diseases.

The application discloses a gene combination, a kit and application thereof for early diagnosis of clear cell renal cell carcinoma, relates to the technical field of molecular diagnosis, and realizes noninvasive diagnosis by detecting the methylation level of specific genes in urine free DNA, greatly improves the accuracy of early disease identification, reduces the pain of patients and reduces the diagnosis cost, meanwhile, the noninvasive detection method is convenient to popularize and repeatedly perform, is not only suitable for initial screening, but also can continuously monitor the change of a disease in a treatment process, provides timely and reliable support for clinical decision-making, and thus effectively improves the treatment success rate and survival rate of patients.

The invention relates to application of UBR5 in treatment and prognosis evaluation of bladder cancer. According to the invention, the key carcinogenic regulation effect of the UBR5 in NMIBC is determined, the high expression of the UBR5 can predict early recurrence and poor prognosis, and the value of the UBR5 as a biomarker for guiding a future precise treatment strategy is highlighted. Targeted UBR5 can effectively inhibit tumor cell proliferation and movement ability, and manifests the potential of the targeted UBR5 as a therapeutic target. By inhibiting the UBR5 or reducing the biological activity of the UBR5, the development of the NMIBC disease can be obviously delayed, the prognosis is improved, the survival rate of a patient is prolonged, the prognosis is improved, and the potential of developing a personalized treatment strategy for a high-risk NMIBC patient by targeting the UBR5 is manifested; the invention provides sufficient scientific basis and theoretical basis for exploring new bladder cancer diagnosis, prognosis judgment and treatment molecular targets and developing new targeted drugs, is helpful for better realizing accurate treatment, and has important social value and scientific significance.

The invention belongs to the field of biological pharmacy, and particularly discloses application of long-chain non-coding RNA lncRNA ALLHET (the sequence is shown as SEQ ID NO: 1) in diagnosis, treatment and prognosis evaluation of acute lymphocytic leukemia (ALL). The ALLHET expression quantity in a bone marrow sample is detected through qRT-PCR (Quantitative Reverse Transcription-Polymerase Chain Reaction) (primers are as shown in SEQ ID NO: 2-3), and the ALLHET expression quantity can be used as an ALL diagnostic marker after being obviously Prognostic analysis based on expression level grouping shows that the event-free survival rate (EFS) of a high expression group is remarkably reduced. Meanwhile, the ALLHET inhibitor can effectively inhibit ALL cell proliferation, promote apoptosis and block the cell cycle, and obviously inhibit tumor growth in an animal model. The invention provides a novel diagnostic target, a therapeutic drug and a prognosis evaluation system for ALL.