43 results about "Circulating DNA" patented technology

The invention discloses a tiny residual focus detection method and system based on ultra-high depth sequencing, and relates to the technical field of tiny residual focus intelligent detection.The tiny residual focus detection method comprises the following steps that on the basis of a sequencing library, splitting is conducted according to a sample index to obtain a to-be-detected sample, and a consensus sequence is obtained according to a molecular identifier of the to-be-detected sample; based on a consensus sequence, filtering out the consensus sequence of which the mass value is less than 25 or the family size is less than 3, and combining a variation type and a distance from a fragment edge as noise introduced into an original nucleic acid molecular chain; a context sequence (context) and a chain direction are used as noise for introducing the capture level of PCR amplification; on the basis of the noise level, the circulating tumor DNA level is estimated in combination with tumor priori knowledge, and the MRD state is determined by detecting the significance of molecular signal sources. According to the invention, the sensitivity and specificity of MRD detection are improved.

The invention relates to the technical field of biomedicine, in particular to a method for constructing a plasma ctDNA organ distribution characteristic spectrum of advanced colorectal cancer. The method comprises the following steps: collecting a peripheral blood sample at multiple time points, separating plasma by adopting a double-centrifugal method, and extracting circulating tumor DNA (Deoxyribose Nucleic Acid); carrying out whole exome sequencing based on ctDNA to obtain genome variation information and calculating variation allele frequency, and synchronously detecting the expression quantity of immune-related proteins by adopting an Olink proteomics technology; integrating the genome data, the protein expression data and the clinical pathological features, and constructing a multi-dimensional feature data matrix; and taking the organ metastasis condition confirmed by iconography as a supervision label, training a model by applying a machine learning algorithm, screening key prediction factors, constructing a quantitative prediction model, and finally generating a visual organ metastasis tendency prediction map. According to the method, early and accurate prediction of the advanced colorectal cancer organ metastasis tendency is realized through multi-omics data collaborative analysis and machine learning modeling.

The invention discloses a high-specificity minimal residual disease (MRD) monitoring method and system based on circulating tumor DNA (ctDNA). The method comprises the following steps: receiving tumor tissue sequencing data of an UTUC patient, and generating a double-Panel target list containing personalized and fixed Panel; respectively extracting plasma cfDNA and leukocyte gDNA; performing vacuum concentration, hybrid capture and sequencing on the cfDNA library by using the double Panel lists, and performing deep sequencing on the leukocyte gDNA; constructing an individualized clonal hematopoietic mutation filtering database; actively filtering and rejecting clonal hematopoietic background mutation by utilizing a filtering database; and calculating an MRD load score based on the filtered tumor-derived mutation and outputting a report. The system comprises corresponding modules which are used for automatically executing the process. According to the invention, through cooperation of four major technologies of double-Panel design, process optimization, UMI error correction and active clonal hematopoietic filtration, MRD monitoring with extremely high sensitivity and specificity on UTUC is realized, false positive is significantly reduced, and the kit has drug resistance early warning potential.

The invention provides a method and a system for predicting early gastric cancer prognosis by a circulating marker, and relates to the technical field of auxiliary diagnosis. The method comprises the following steps: performing multi-omics detection on a blood sample based on a preset sampling time sequence to obtain a multi-dimensional time sequence characteristic data set containing three groups of heterogeneous data of circulating tumor DNA, exosomes and protein markers; calculating a change slope and a fluctuation variance of the heterogeneous data in adjacent time sequence intervals, constructing a dynamic variation feature matrix in combination with a standard attenuation weighting factor, and deeply mining spatial cross-correlation and sequence dependence features of the matrix to generate a multi-modal fusion feature fingerprint; and performing regression operation on the feature fingerprints by using an integrated learning stack model to obtain a dynamic prognosis risk score, and further retrieving a risk hierarchical mapping table to generate a prognosis evaluation result containing a survival curve. According to the method, multi-modal heterogeneous data can be effectively fused, the biological dynamic characteristics in the tumor postoperative recovery phase are captured, and the accuracy and timeliness of early gastric cancer prognosis prediction are remarkably improved.

This invention relates to the field of medical technology, specifically to a method for preoperative risk assessment and prediction in liver transplant patients with hepatocellular carcinoma, comprising the following steps: Sample collection: selecting plasma samples and corresponding clinicopathological information from liver transplant recipients of hepatocellular carcinoma, and clarifying the inclusion and exclusion criteria for samples; Plasma cell-free DNA extraction and whole-genome sequencing: extracting and quality-controlling cell-free DNA from the plasma samples collected in step S1, constructing a sequencing library, and performing low-coverage whole-genome sequencing. This invention utilizes plasma-extracted cfDNA for whole-genome sequencing, combined with clinical testing information, to construct a preoperative risk assessment and prediction model for postoperative recurrence in liver transplant recipients of hepatocellular carcinoma based on non-invasive testing. This model can be used to predict the probability of recurrence-free survival before liver transplantation. The model derivation cohort integrates clinical records and circulating tumor DNA data for preoperative recurrence risk prediction.

The invention provides methods for detecting single nucleotide variants in breast cancer, bladder cancer, or colorectal cancer. Additional methods and compositions, such as reaction mixtures and solid supports comprising clonal populations of nucleic acids, are provided. For example, provided here is a method for monitoring and detection of early relapse or metastasis of breast cancer, bladder cancer, or colorectal cancer, comprising generating a set of amplicons by performing a multiplex amplification reaction on nucleic acids isolated from a sample of blood or urine or a fraction thereof from a patient who has been treated for a breast cancer, bladder cancer, or colorectal cancer, wherein each amplicon of the set of amplicons spans at least one single nucleotide variant locus of a set of patient-specific single nucleotide variant loci associated with the breast cancer, bladder cancer, or colorectal cancer; and determining the sequence of at least a segment of each amplicon of the set of amplicons that comprises a patient-specific single nucleotide variant locus, wherein detection of one or more patient-specific single nucleotide variants is indicative of early relapse or metastasis of breast cancer, bladder cancer, or colorectal cancer.

Disclosed herein are methods and systems for targeted detection of circulating tumor DNA (ctDNA) molecules. In some cases, a methylated DNA depleted molecular sequencing library can be generated and used to reliably detect ctDNA in cell-free DNA samples at lower sequencing depths and at lower costs than existing methods.

The invention belongs to the technical field of biology, and provides a method for detecting low-frequency gene mutation based on PNA-PCR combined with a Cas13a system and application of the method. According to the method, a target mutation sequence is enriched through PNA-mediated allele specific amplification, a Cas13a / crRNA system is used for carrying out high-specificity recognition and fluorescence signal amplification on an amplification product, and the high-frequency gene mutation is detected through the Cas13a / crRNA system. High-sensitivity detection of low-frequency gene mutation in plasma circulating tumor DNA (ctDNA) is achieved, and the lower detection limit can reach 0.1%-0.01% VAF. The invention solves the problems of insufficient sensitivity, complex operation, high cost or strong equipment dependence and the like in the prior art such as next-generation sequencing, digital PCR and the like during low-frequency mutation detection, and is suitable for noninvasive rapid screening and precise diagnosis and treatment of clinical tumor gene mutation.

Techniques for predicting expression of cancer cells based on the methylation status of a region of DNA are described. An example method includes identifying data indicative of cell free DNA (cfDNA) from a sample derived from a subject. A methylation status of one or more regions of circulating tumor DNA (ctDNA) among the cfDNA is identified by analyzing the data. The example method further includes inputting input data including the methylation status of the one or more regions into at least one model configured to generate a probability that cancer cells of the subject express a predetermined sequence. In addition, the example method includes generating a report based on the probability that the cancer cells of the subject express the predetermined sequence.

The present disclosure relates to methods, devices, electronic devices and program products for detecting the circulating tumor desoxyribonucleic acid (ctDNA) content of a blood sample. The method includes determining a likelihood function of mutation sites of the blood sample. The method further includes determining a priori distribution of ctDNA content of the mutation site based on the sequencing readings of the mutation site. The method further comprises determining the ctDNA content of the blood sample based on the likelihood function of the mutation sites and a priori distribution of the ctDNA content of the mutation sites. By means of the method, the content of the circulating tumor deoxyribonucleic acid ctDNA of the blood sample can be detected, and the detection accuracy or sensitivity is improved.

The present invention relates to methods of treating previously untreated diffuse large B-cell lymphoma (DLBCL), which is defined as high risk according to circulating tumor DNA (ctDNA), by administering gphentumab and in combination with chemotherapy.

The present disclosure includes a method comprising: (a) obtaining free DNA (cfDNA) from a sample from a subject; (b) selectively enriching a subset of the cfDNA or derivatives thereof from (a) having one or more target regions to obtain an enriched DNA, wherein the target regions are differentially methylated in cancer; (c) sequencing the enriched DNA from (b) to obtain a sequence read; and (d) dividing a plurality of said sequence reads into two or more groups based on the methylation status thereof, and determining the fragment length distribution of said sequence reads in at least one of said groups.

The present disclosure relates to a laboratory execution system that provides for automation of laboratory processes. A centralized data management system may be dynamically updated and used to facilitate management of components of the laboratory execution system, such as an automation system and an analytics results management system that may facilitate complex analytical functions, such as synthesizing raw test data. Potential workflows include the detection of specific molecules of interest.

The invention belongs to the technical field of intelligent drug delivery control, and particularly discloses a colon tumor drug delivery method and system based on AI control, and the method comprises the steps: collecting and preprocessing whole genome sequencing, radiomics, clinical pathology and historical drug treatment response data of a patient, extracting tumor image features, and carrying out drug delivery. The method comprises the following steps: screening oxaliplatin response related gene mutation markers by combining Lasso regression with a Cox model, forming feature vectors by t-SNE dimensionality reduction clinical pathological data, training a model through a gradient boosting tree and deep neural network fusion algorithm, taking oxaliplatin response probability as output, and recommending an FOLFOX scheme or an FULV scheme according to a model result. According to the method, precision and individuation of chemotherapy are achieved, unnecessary toxic and side effects are reduced, the life quality and lifetime of a patient are improved, and the problems that in the prior art, dependence on experience, single data dimension, no dynamic adjustment mechanism and poor stability are solved. Therefore, the problems of low response rate of oxaliplatin and obvious side effect are solved.

The disclosure relates to systems, software and methods for diagnosing tumor diseases in a patient.

For various purposes, a nucleosome signal pattern using fragmentation at a location around a target site is provided. For example, a nucleosome signal pattern may be used to determine methylation levels of a target site (e.g., a CpG site). The signal may be associated with a nucleosome pattern of a cfDNA molecule within a genomic region that is differentially methylated in a target tissue type by having different methylation levels (or levels, e.g., as a pattern) relative to one or more other tissue types (e.g., blood cells). The nucleosome signal pattern can be compared to one or more reference patterns with known methylation levels. Another exemplary method may determine a lesion level in a subject. Another example may determine a proportional concentration of DNA for a particular tissue type.

Provided herein are compositions, methods, and kits for detecting, amplifying, and / or quantifying analytes in various samples. For example, the present disclosure provides a composition, method, and kit capable of detecting, amplifying, and / or quantifying human papilloma virus (HPV)-associated cancer circulating tumor DNA (ctDNA).

The invention belongs to the technical field of medicines, and particularly relates to a construction method of a peripheral blood circulating tumor DNA and RNA co-construction library and a kit for detecting tumor mutation. The invention provides a peripheral blood circulating tumor DNA and RNA co-construction library and a construction method thereof. By adopting the ctDNA and ctRNA co-established library, more tumor-derived mutations can be detected, mutation types missed by the ctDNA library are found, and mutation characteristic identification of tumor cells of tumor patients is realized more accurately and sensitively.

The invention provides methods for detecting single nucleotide variants in breast cancer, bladder cancer, or colorectal cancer. Additional methods and compositions, such as reaction mixtures and solid supports comprising clonal populations of nucleic acids, are provided. For example, provided here is a method for monitoring and detection of early relapse or metastasis of breast cancer, bladder cancer, or colorectal cancer, comprising generating a set of amplicons by performing a multiplex amplification reaction on nucleic acids isolated from a sample of blood or urine or a fraction thereof from a patient who has been treated for a breast cancer, bladder cancer, or colorectal cancer, wherein each amplicon of the set of amplicons spans at least one single nucleotide variant locus of a set of patient-specific single nucleotide variant loci associated with the breast cancer, bladder cancer, or colorectal cancer; and determining the sequence of at least a segment of each amplicon of the set of amplicons that comprises a patient-specific single nucleotide variant locus, wherein detection of one or more patient-specific single nucleotide variants is indicative of early relapse or metastasis of breast cancer, bladder cancer, or colorectal cancer.

To provide methods and systems for molecular disease assessment through the analysis of circulating tumor DNA. [Solution] A method for evaluating the tumor status of a subject (e.g., progression, regression, recurrence, etc.) may include: determining (i) a plurality of first and second CNAs and (ii) a plurality of first and second fragment lengths based on first and second WGS data of the subject's cfDNA molecule at different time points; processing the plurality of first and second CNAs to determine changes in the CNA profile; comparing the plurality of first and second fragment lengths to determine changes in the fragment length profile; determining the first or second tumor percentage of the subject at a first or second time point, at least in part, based on the changes in the CNA profile and the changes in the fragment length profile; and detecting the tumor status of the subject, at least in part, based on the first or second tumor percentage.

This disclosure relates to methods of predicting the probability that a circulating tumor DNA (ctDNA) structural variant (SV) is present in tumor tissue using a machine learning model. The methods can further include training and validating the machine learning model using paired ctDNA-derived SVs and tumor tissue-derived SVs. The training set data can include multiple passes of quantified sensitivity values and positive predictive values calculated from known true positive SVs, false positive SVs or false negative SVs until a favorable sensitivity values and / or favorable positive predictive value is achieved.

The invention discloses a biological optical sensor based on a super-structure grating, and a preparation method and application thereof, relates to the technical field of biology, and aims to solve the problems of complex detection, low sensitivity, poor specificity, easy error introduction and high cost in existing ctDNA sequencing. The biological optical sensor comprises a super-structure grating which comprises an etching area and a non-etching area which are regularly distributed on a metal substrate, and a metal layer coated on the lower end surface of the etching area and the upper end surface of the non-etching area; the DNA tetrahedron carrying sulfydryl is fixed on the metal layer; and the gold nanoparticle-detection probe is immobilized on the DNA tetrahedron. The biological optical sensor disclosed by the invention can be combined with a ctDNA solution with an extremely low concentration, and label-free, specific and ultra-trace detection of ctDNA is realized by utilizing CRISPR cutting and detection of the change of the light refractive index of the biological optical sensor.

The invention discloses a tumor metastasis risk assessment method and system based on circulating tumor DNA (ctDNA) spatial heterogeneity. The core of the method is as follows: blood samples of at least two different anatomical sites (such as peripheral veins and tumor drainage veins) of the same subject are obtained at the same time, and ctDNA in the samples is subjected to sequencing analysis; calculating characteristic data (such as a relative abundance ratio) representing ctDNA spatial distribution based on the mutation abundance difference between different parts; and finally, inputting the feature data into a pre-trained metastasis risk assessment model, and outputting a quantitative tumor metastasis risk score. According to the method, the limitation of traditional single-point liquid biopsy is broken through, the detection sensitivity of tiny metastases can be remarkably improved by utilizing the spatial distribution information of the ctDNA, potential metastasis positioning information is provided, and powerful technical support is provided for accurate diagnosis and treatment decision of tumor patients.

The application relates to the field of biomedical detection technology, in particular to a bladder cancer postoperative recurrence monitoring method based on a ctDNA methylation spectrum, which comprises the following steps: collecting postoperative patient cell-free plasma and extracting circulating tumor DNA; performing bisulfite conversion treatment on the DNA; performing targeted amplification using a multiplex PCR primer group designed for a group of predetermined genomic methylation regions related to recurrence, constructing a sequencing library; performing high-throughput sequencing on the library, obtaining methylation level data of a plurality of CpG sites to form a sample methylation spectrum data matrix; the core of the application is that tumor heterogeneity is overcome through multi-marker combination detection, and a machine learning model is used to integrate multidimensional data to realize precise risk stratification, which has the advantages of non-invasiveness, high sensitivity, high specificity and quantifiable output, and provides an effective tool for individualized follow-up management of bladder cancer postoperation.

Techniques for classifying cancers using fragmentomic features are described. An example method includes identifying data indicative of circulating tumor DNA (ctDNA) from a sample derived from a subject. The example method further includes identifying fragmentomic features based on the data. Input data, including the fragmentomic features, is input into a model configured to generate at least one probability that a tumor is within at least one category. The example method further includes generating a report based on the at least one probability that the tumor is within the at least one category.

A marker group for detecting osteosarcoma circulating tumor cells (CTCs), characterized in that the marker group is COL1A2 isoforms, and the COL1A2 isoforms include at least one of ENST00000620463 and ENST00000297268. Compared with the prior art, the COL1A2 isoforms provided by the present application have a high prevalence in osteosarcoma tissues, a combined detection rate of 98.56%, and a detection rate of 85.71% in metastatic patients; the area under the ROC curve (AUC) of CTCs detection for predicting osteosarcoma metastasis is 0.833, which is better than traditional markers; longitudinal follow-up can detect metastasis 5.11 months earlier than imaging; it can distinguish metastatic patients before operation, and has unique applicability to osteosarcoma with low mutation burden. In addition, the COL1A2 isoforms can complement tumor-aware detection, and can be used for prognosis and monitoring of metastasis and recurrence of osteosarcoma patients who cannot successfully customize circulating tumor DNA detection panel (ctDNA panel).

The application provides a multi-omics joint detection system for prostate cancer recurrence risk assessment, the application synchronously acquires genomic, transcriptomic, epiproteomic and metabolomic data of different regions of a tumor through spatially resolved in situ capture technology, and integrates multi-dimensional information such as circulating tumor DNA epigenetic memory, urological microbiome-host interaction, single-cell clone evolution and tumor microenvironment three-dimensional topology. The system uses a dynamic Bayesian fusion engine to perform probabilistic risk calculation, combines digital twin technology to simulate treatment response, and realizes model adaptive updating through longitudinal follow-up data. The output result has high interpretability and can directly show key driving factors and their clinical interventional properties. The system breaks through the limitations of traditional static and single-omics models, significantly improves the prediction accuracy of recurrence, especially in low-risk populations, and provides intelligent support for individualized auxiliary treatment decisions.

Methods and systems for determining a tumor DNA fraction for a sample from a subject are described. In some instances, the methods comprise receiving sequence read data for a plurality of sequence reads derived from the sample from the subject; determining a variant allele frequency (VAF) for one or more variants detected in the sample based on the sequence read data; generating an empirical distribution of tumor DNA fraction values as a function of the determined VAF for the one or more variants; fitting a model to the empirical distribution of tumor DNA fraction values; and determining a tumor DNA fraction for the sample based on the model.

To provide a method for identifying or selecting a patient.SOLUTION: A method for identifying or selecting patients with elevated Nectin-4 proteins and / or RNA expression levels in tumor tissues, comprising measuring Nectin - 4DNA copy number in tumor tissues or circulating tumor DNA of patients, and selecting patients with elevated Nectin - 4DNA copy number in the tumor tissues, wherein in one embodiment, the step of measuring the Nectin - 4DNA copy number in tumor tissues or circulating tumor DNA of patients comprises using next-generation sequencing technology or sequence-based sequence capture.SELECTED DRAWING: None

Pancreatic adenocarcinoma has the worst overall mortality of any solid tumor, with only 7% of patients surviving after 5 years. To evaluate the clinical implications of genomic alterations in this low cellularity tumor type, we deeply sequenced the genomes of 101 enriched pancreatic adenocarcinomas from patients who underwent potentially curative resections and used non-invasive approaches to examine tumor specific mutations in the circulation of these patients. These analyses revealed somatic mutations in chromatin regulating genes including MLL and ARID1A in 20% of patients that were associated with improved survival. Liquid biopsy analyses of cell free plasma DNA revealed that 43% of patients with localized disease had detectable circulating tumor DNA (ctDNA) in their blood at the time of diagnosis. Detection of ctDNA after resection predicted clinical relapse and poor outcome, and disease recurrence by ctDNA was detected 6.5 months earlier than with standard CT imaging.