64 results about "Progression-free survival" patented technology

Provided are adoptive cell therapy methods involving the administration of doses of cells for treating B cell malignancies. The cells generally express recombinant receptors such as chimeric antigen receptors (CARs). In some embodiments, the methods are for treating subjects with chronic lymphocytic leukemia (CLL). In some embodiments, the methods are for treating subjects with non-Hodgkin lymphoma (NHL). In some embodiments, the methods involve prior administration of a lymphodepleting therapy, such as prior administration of fludaribine and / or another lymphodepleting chemotherapeutic agent, for example cyclophosphamide. In some embodiments, features of the methods include an increase in complete remission, overall survival and / or progression free survival of subjects treated in accord with the provided methods.

The present application describes uses for Pertuzumab, a first-in-class HER2 dimerization inhibitor. In particular, the application describes methods for extending progression free survival in a HER2-positive breast cancer patient population; and combining two HER2 antibodies to treat HER2-positive cancer without increasing cardiac toxicity.

The invention provides a method of treating a melanoma comprising (i) identifying a patient having a PD-L1-negative melanoma and (ii) administering to the patient a combination of an anti-PD-1 antibody or an antigen-binding portion thereof and an anti-CTLA-4 antibody or an antigen-binding portion thereof. The methods of the invention can extend progression-free survival for over 8 months and / or reduces the tumor size at least about 10%, about 20%, about 30%, about 40%, or about 50% compared to the tumor size prior to the administration.

The invention discloses a risk score prediction curve of objective remission rate (ORR), disease control rate (DCR), progression-free lifetime (PFS) and total lifetime (OS) of a patient with advanced gastric or gastroesophageal junction adenocarcinoma after first-line chemotherapy and immunotherapy based on clinical inflammation indexes and application of the risk score prediction curve. The risk score is established based on clinical inflammation indexes and used for drawing a prediction curve of PFS and OS after first-line chemotherapy and immunotherapy and ORR and DCR, common inflammation-related laboratory indexes are integrated, the calculation method is simple, and clinical doctors and patients can conveniently operate to predict ORR, DCR, PFS and OS after treatment. Meanwhile, the risk score prediction model can provide certain help for selection of treatment schemes of later gastric or gastroesophageal junction adenocarcinoma patients in the future.

The present disclosure provides methods for improving the median progression-free lifetime (PFS) and improving the overall lifetime of a never-treated subject or a population of never-treated subjects having EGFR-positive non-small cell lung cancer (NSCLC).

Disclosed herein are compositions and methods for treating cancer, specifically extensive-stage small-cell lung cancer (ES-SCLC), through the administration of a combination therapy. In some embodiments, the method comprises administering plinabulin, one or more immune checkpoint inhibitors, including but not limited to pembrolizumab, and a regimen of etoposide with a platinum-based agent (EP). The disclosed methods enhance tumor reduction, prolong progression-free survival, and improve overall treatment efficacy compared to traditional therapies.

A method for estimating tumor growth dynamics includes acquiring, by one or more processors, progression-free survival (PFS) data for a plurality of patients, the PFS data indicating (i) a plurality of observation times and (ii) the number of patients among the plurality of patients who experienced a PFS event within a most recent time window at each of the plurality of observation times; determining, by the one or more processors, a population distribution of one or more patient-specific parameters based on the PFS data; acquiring, by the one or more processors, measured tumor growth data for a particular patient receiving drug treatment; estimating, by the one or more processors, tumor growth for the particular patient based on (i) the measured tumor growth data and (ii) the population distribution of the one or more patient-specific parameters; and causing, by the one or more processors, a visual representation of the estimated tumor growth for the particular patient to be presented on a display.

The invention discloses a method for predicting small cell lung cancer immunotherapy effect based on CT radiomics. The method comprises the following steps: firstly, carrying out lung enhancement CT scanning on a small cell lung cancer patient receiving immunotherapy before and after treatment, extracting radiomics characteristics and calculating delta-RF; in the aspect of model construction, 1037 radiomics features are extracted, and the model is constructed through a series of processing. The model display includes a variety of predictive indicators, such as an overall lifetime (OS), a progression-free lifetime (PFS), a complete remission (CR), a partial remission (PR), a column diagram, a consistency index, a subject working characteristic curve and its underlying area, a calibration curve, and a clinical decision curve. The model has a high C index and an AUC value for PFS and OS prediction, the AUC for curative effect prediction is 0.913, and a calibration curve is close to an ideal line. Compared with a prediction scheme based on NGS sequencing, the method has the advantages of being low in cost, non-invasive, efficient, dynamic, accurate and the like, and the image omics concept is used for predicting the curative effect of SCLC immunotherapy for the first time.

The invention discloses a CCNE1 gene-based kit for evaluating the progress of bile duct cancer, belongs to the technical field of biomedical detection, and is used for evaluating the progress of bile duct cancer. The kit comprises a specific fluorescent probe, a hybridization buffer solution, a washing buffer solution, a positive reference substance, a DAPI dye solution and an anti-fluorescence quenching agent. Wherein the specific fluorescent probe is formed by coupling a fluorescent probe and amino-modified CCNE1 specific nucleic acid, and the fluorescent probe constructs a conjugated structure based on 5-methoxy-2, 3, 3-trimethylindole and 4-(9H-carbazole-9-yl) benzaldehyde. The CCNE1 gene expression level can be accurately reflected by detecting the intensity of fluorescence signals excited by 650 nm and emitted by 690 nm, then the malignant degree, metastasis potential and patient prognosis of the bile duct cancer are evaluated, the CCNE1 gene can be used for predicting the progression-free lifetime of a patient and the tumor metastasis risk, and a reliable tool is provided for diagnosis and treatment of the bile duct cancer.

Trastuzumab, a second anti-HER2 antibody and a chemotherapeutic agent are combined to treat HER2-positive advanced gastric cancer. Compared with existing first-line treatment solutions for HER2-positive advanced gastric cancer, the combined treatment method of trastuzumab, the second anti-HER2 antibody and the chemotherapeutic agent (XELOX) prolongs the progression free survival (PFS) and / or the overall survival (OS) of patients.

The invention discloses a prognosis marker and a dynamic prognosis prediction method for colorectal cancer liver metastasis. The method comprises the following steps: S1, acquiring clinical pathological characteristic data of a patient with colorectal cancer liver metastasis and a longitudinal laboratory marker measured during post-operation follow-up visit; s2, extracting a change trend of the longitudinal laboratory marker by utilizing multivariable function principal component analysis to obtain a principal component score; s3, training a random survival forest model by using the principal component score and the clinical pathological feature data to obtain a dynamic prediction model; s4, dynamically updating the score of the principal component based on a newly collected laboratory marker of postoperative follow-up visit of the patient, and outputting dynamic risk assessment results of the progression-free lifetime and the total lifetime of the patient through a dynamic prediction model; according to the method, the prediction model capable of dynamically evaluating the survival risk of the patient is constructed and updated by fusing the dynamic longitudinal laboratory marker and the static clinical pathological characteristics.

Targeted therapy using osimertinib (an EGFR tyrosine kinase inhibitor), is the first choice for patients with metastatic or recurring lung cancer. However, most patients develop resistance. Because the options after failure of TKls such as osimertinib are limited, improving EGFR-targeted therapy is an unmet need. Here, EGFR mutant patient-derived xenograft tumors responded partially to osimertinib despite near complete inhibition of EGFR activation. Many tumor cells escaped drug killing and regained growth following about 35 days of continuous osimertinib dosing. However, when an antibody to hepatoma-derived growth factor was given concurrently with osimertinib, tumors showed complete or near complete responses with significant prolongation of progressionfree survival of tumor bearing mice. The data support the idea that increased suppression of the AKT / mTOR and MAPK pathways is a mechanism that enhances efficacy of osimertinib when it is combined with an anti-HDGF antibody.

To provide a method for extending progression-free survival (PFS) in a patient with extensive-stage small cell lung cancer (ES-SCLC).SOLUTION: This method comprises treating a patient with extensive-stage small cell lung cancer with a) a human anti-PD-L1 antibody and b) etoposide and a platinum-based therapeutic agent (EP).SELECTED DRAWING: None

The invention discloses an infant AML prognosis model constructed by integrating transcriptomics and machine learning and a construction method of the infant AML prognosis model. The method comprises the following steps: collecting clinical data and whole genome transcriptome data of an infant AML patient; identifying difference up-regulation expression genes of infant AML relative to healthy control and old children AML in the discovery set, and screening intersection genes of the genes and an external verification set; carrying out model construction on the obtained gene by taking the progression-free lifetime of the patient as an outcome, generating a plurality of algorithm combinations based on a machine learning algorithm, and calculating a C-index index of each combination; determining a model with the highest C-index mean value in the internal verification set and the external verification set as an optimal model, calculating a risk score IPScore of each patient by using the model, and performing evaluation in the verification set; and dividing the patients into a low-risk group and a high-risk group according to IPScore by utilizing the optimal cutoff value 0.42, namely an IPGroup model. The model can accurately and effectively predict the prognosis of the infant AML patient, and has good clinical practicability.

Described herein are methods and compositions related to using genomic and / or methylation-based TF from a genomic, epigenomic detection platform to predict clinical benefit to therapies, including through evaluation of real-world patients. Tumor detection, methylation-based tumor fraction, and methylation-based molecular response are prognostic and predictive of outcomes, Prolonged treatment of patients not deriving benefit risks increased toxicity, may reduce chance of success for targeted treatments, and may increase clonal hematopoietic burden, wherein methylation based detection largely eliminates noise in determining genomic molecular response (gMR), thereby demonstrating advantageous use of methylation based molecular response (mMR).

The invention relates to a predictive gene expression signature of response to antiangiogenic drugs, such as axitinib, in gastro-enteric-pancreatic and pulmonary neuroendocrine tumours. The signature is formed by the gene expression of three genes (SPP1, ATXN7 and REXO1L2P), which is converted by means of a bioinformation packet into a unique score that can predict which patients will benefit from treatment with the drug, this benefit being understood as longer survival without progression and larger tumour volume reductions in response to treatment.

Potential prognostic biomarkers for CD26-targeted therapy were identified based on phase I study data of a humanized anti-CD26 monoclonal antibody YS110 against CD26-expressing tumors. Using boxplot analysis, scatter plot analysis, Pearson's product-moment correlation / Spearman's rank-difference correlation, bar graph analysis, and receiver operating characteristic (ROC), a correlation between soluble CD26 titer variation and tumor volume variation by YS110 administration, RECIST criteria evaluation, and progression-free survival (PFS) were examined. Further, mechanism of serum soluble CD26 titer variation was confirmed by in vitro experiments. As a result, serum soluble CD26 / DPP4 titer variation at an early stage of YS110 treatment was found for the first time as a predictive biomarker to evaluate a therapeutic effect.

Immune context scores are calculated for stage III colorectal tumor tissue samples using continuous scoring functions. Feature metrics for at least one immune cell marker are calculated for a region or regions of interest, the feature metrics including at least a density of human CD3+ cells in a region of interest including an invasive margin. A continuous scoring function is then applied to a feature vector, the output of which is an immune context score. The immune context score may then be plotted as a function of a diagnostic or treatment metric, such as a prognostic metric (e.g. overall survival, disease-specific survival, progression-free survival) or a predictive metric (e.g. likelihood of response to a particular treatment course). The immune context score may then be incorporated into diagnostic and / or treatment decisions.

The invention discloses a tumor main clone allele frequency dynamic monitoring and closed-loop control method, and belongs to the field of biological gene detection and data processing. The method comprises the following steps: firstly, constructing a state space dynamic model containing state parameters of a master clone and a slave clone, introducing a molecular regulatory factor, then setting a main clone allele frequency monitoring threshold interval, synchronously acquiring abundance of the master clone and the slave clone detected by digital PCR at multiple rates, CRP, albumin and other hematopathology indexes as observation parameters, and carrying out quantitative analysis on the observation parameters. According to the method, observation parameters are predicted based on an extended Kalman filtering fusion model, the main clone allele frequency is accurately estimated in real time, and according to a comparison result of the main clone allele frequency and a monitoring threshold interval, the number of days for taking or stopping the targeted drug is dynamically adjusted, so that closed-loop control of the main clone allele frequency is realized. Closed-loop fusion of tumor monitoring and drug administration regulation is achieved, drug resistance germination is intervened in advance, and the progression-free lifetime of a patient is remarkably prolonged.

To provide uses of pertuzumab, which is a first in-class HER2 dimerization inhibitors, and articles of manufacture comprising the same.SOLUTION: A method for extending progression free survival in a population of HER2 + breast carcinoma patients; a method for combining two HER2 antibodies to treat HER2 + breast carcinoma without increasing cardiotoxicity; a method for treating early HER2 + breast carcinoma; a method for treating HER2 + breast carcinoma by co-administering a mixture of pertuzumab and trastuzumab from the same I. v. bag; a method for treating HER2 + metastatic gastric carcinoma; a method for treating HER2 + breast carcinoma with pertuzumab, trastuzumab and vinorelbine; Methods for treating HER2 positive breast cancers with trastuzumab and aromatase inhibitors; and methods for treating low HER3 ovarian, primary peritoneal, or fallopian tube cancers are provided.SELECTED DRAWING: None

The invention relates to the technical field of biological medicine, and discloses a co-crystal medicine ZM888 and application thereof in lung cancer resistance, a preparation method of the co-crystal medicine ZM888 comprises the following steps: mixing osimertinib, naringenin and a mixed solvent, heating, stirring and dissolving, then adding n-hexane, and precipitating a yellow solid, namely the co-crystal medicine ZM888. The eutectic drug ZM888 disclosed by the invention shows a remarkable inhibition effect on an osimertinib drug-resistant cell strain in an in-vitro experiment, which indicates that the eutectic drug ZM888 possibly provides a new treatment scheme for clinical treatment of lung cancer patients. The application of the eutectic drug ZM888 is expected to improve the treatment effect and prolong the progression-free lifetime of patients.

Disclosed are means for predicting (i) multi-organ metastasis and / or multifocal metastatic disease, and (ii) overall survival (OS) and progression-free survival (PFS) of subjects suffering from cancer, the predictions being based on the number and size of circulating cancer-associated macrophage-like cells (CAML) found in a biological sample, such as the blood, of the subject.

The invention discloses a biomarker for predicting tumor immunotherapy effect and application of the biomarker, and belongs to the technical field of medical technology and biological detection. The biomarker is composed of the following proteins: CXCR4 and CD4, it is found that the infiltration level of CXCR4 + CD4 + T cells is significantly related to the clinical response of tumor immunotherapy, patients can be divided into a high-expression group and a low-expression group by detecting the relative expression quantity of the CXCR4 + CD4 + T cells in tumor tissue, the patients in the high-expression group are sensitive to immunotherapy, the curative effect is significant, and the patients in the low-expression group are sensitive to immunotherapy. The total survival time and the progression-free survival time are superior to those of a low-expression group. The invention provides important technical support for prediction of curative effect of tumor immunotherapy patients and formulation of a precise treatment scheme, has the advantages of high sensitivity and high specificity, and significantly promotes clinical application of immunotherapy.

This disclosure provides a method for improving median progression-free survival (PFS) and overall survival in treatment-naive subjects or a treatment-naive population with EGFR-positive non-small cell lung cancer (NSCLC).

The present disclosure relates to methods of treating breast cancer in a patient, comprising administering to the patient a therapeutic combination comprising elacestrant, or a pharmaceutically acceptable salt thereof, and abemaciclib, or a pharmaceutically acceptable salt thereof. The present disclosure also relates to methods of treating breast cancer in a patient that produce a longer Progression Free Survival time as compared to other treatments.

The invention develops a prediction model based on pathomics characteristics of a conventional biopsy sample, and the prediction model is used for evaluating the recurrence risk of EGFR mutation LUAD patients receiving EGFR-TKI treatment. According to pathological omics data, five pathological omics features are found for the first time, and a patient scoring model pathomicScore is constructed based on the five features. The result shows that the pathomicScore model is in negative correlation with the progression-free lifetime of the disease. Besides, a comprehensive prediction model of the disease progression risk is developed by combining a pathomicScore model with a model based on clinical data, and the model has a good layering capability for the LUAD patient, so that a personalized treatment strategy can be guided. The method has an application prospect in the fields of risk assessment of EGFR targeted therapy and precise tumor.

The epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) osimertinib has significantly prolonged progression-free survival (PFS) in EGFR-mutant lung cancer patients, including those with brain metastases. However, osimertinib-treated patients often develop lethal metastatic relapse, often to the brain. The genetic repression of S100A9, ALDH1A1, or RA receptors (RAR) in cancer cells, or treatment with a pan-RAR antagonist, dramatically reduces brain metastasis. S100A9 expression in cancer cells correlates with poor PFS in osimertinib-treated patients, and is identified as a novel, therapeutically targetable S100A9-ALDH1A1-RA axis. A combination of osimertinib and AGN-194310, for example, treats such cancer while avoiding metastatic relapse.

Targeted therapy using osimertinib (an EGFR tyrosine kinase inhibitor), is the first choice for patients with metastatic or recurring lung cancer. However, most patients develop resistance. Because the options after failure of TKls such as osimertinib are limited, improving EGFR-targeted therapy is an unmet need. Here, EGFR mutant patient-derived xenograft tumors responded partially to osimertinib despite near complete inhibition of EGFR activation. Many tumor cells escaped drug killing and regained growth following about 35 days of continuous osimertinib dosing. However, when an antibody to hepatoma-derived growth factor was given concurrently with osimertinib, tumors showed complete or near complete responses with significant prolongation of progressionfree survival of tumor bearing mice. The data support the idea that increased suppression of the AKT / mTOR and MAPK pathways is a mechanism that enhances efficacy of osimertinib when it is combined with an anti-HDGF antibody.

This invention relates to the pharmaceutical field, and more specifically to a drug used for the treatment of locally advanced, unresectable or metastatic colorectal cancer, and its use. Compared to a two-drug regimen of cintirimab + tucidinostat, the tripartite regimen of cintirimab + tucidinostat + IBI305 provided by this invention can significantly extend progression-free survival in patients with MSS / MSI-L locally advanced, unresectable or metastatic colorectal cancer. Furthermore, in terms of indicators such as ORR, PR, PD, NE, and DCR, patients with MSS / MSI-L locally advanced, unresectable or metastatic colorectal cancer can obtain significant benefits from the tripartite regimen of cintirimab + tucidinostat + IBI305.

The application relates to the field of medical technology, in particular to application of PTPRT as a biomarker and target point for predicting the curative effect of lung cancer immunological checkpoint treatment. The application provides application of the expression amount of PTPRT in curative effect prediction or evaluation of immunological checkpoint treatment of cancer. The experiment of the application shows that low expression of PTPRT can accurately predict the progression-free survival (PFS) of lung cancer patients after receiving immunological checkpoint treatment as a marker for predicting the curative effect of lung cancer immunological checkpoint treatment. Inhibition of PTPRT can increase the proportion of CD8+ T cells infiltrating tumors, and synergistically enhances the anti-tumor effect of an immunological checkpoint inhibitor.