79 results about "MRD Negative" 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 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 discloses a blood tumor fusion gene minimal residual focus monitoring method, system and equipment, and the key points of the technical scheme are as follows: obtaining fusion gene information and high-throughput sequencing data of all genetic information; under the condition that the high-throughput sequencing data is subjected to PCR without duplicate removal, comparing the high-throughput sequencing data to a reference genome to obtain a first comparison result, screening out a real fusion gene sequence from the first comparison result, and calculating to obtain a first copy number of a fusion gene according to the real fusion gene sequence; a real housekeeping gene sequence is screened out from the first comparison result, and a second copy number of housekeeping genes is calculated according to the real housekeeping gene sequence; dividing the first copy number by the second copy number to obtain the minimal residual focus ratio of the fusion gene. According to the invention, high-sensitivity and high-specificity monitoring of MRD can be realized.

The invention belongs to the technical field of tumor molecular diagnosis and biological information analysis, and relates to a high-throughput sequencing method and system for monitoring acute lymphocytic leukemia (MRD). Through targeted sequencing with a unique molecular identifier and / or a double-chain tag, error modeling based on a background noise spectrum and statistics / machine learning pseudo variation filtering, ultra-deep accurate detection of IG / TCR cloning and related gene low-frequency variation is realized. And an artificial intelligence recurrence risk prediction model is established by combining a time sequence MRD index, cloning diversity and clinical information, and a structured clinical report is output and docked with LIS / HIS. According to the method, the sensitivity and the specificity of ALL minimal residual disease detection can be remarkably improved, dynamic evaluation on leukemia cloning evolution and recurrence risks is realized, and a reliable basis is provided for individualized treatment decision and long-term follow-up visit.

Disclosed herein are methods, compositions, and devices for use in early detection of cancer. The claimed methods include the detection of minimal residual disease (MRD) by analysis of urine samples. The method may involve the use of methyl binding domain proteins or by direct sequencing and may involve detection of somatic variants or detection of methylated cytosines. Also claimed is a method which determines a cancer status by generating an input vector based on quantitative measures created from urine sequence reads and analysing the input vector with a machine learning based model.

The present invention relates to a system and a method for measuring and analyzing minimal residual disease (MRD) in pediatric B-cell precursor acute lymphoblastic leukemia (B-ALL) using multiparameter flow cytometry (MPFC). The invention finds application in clinical diagnostics and hematology-oncology for quantifying MRD in B-ALL patients with high sensitivity and specificity, needed for risk stratification, monitoring treatment response, and informing therapeutic decisions. The system comprises interconnected subsystems including an acquisition subsystem with an MPFC instrument, a control and file generation subsystem, and an analytical subsystem. The analytical subsystem incorporates modules for sequential data reduction, automated data cleaning, automated unsupervised data clustering, and interactive cluster analysis. Key advantages include high MRD detection sensitivity (e.g., 10⁻⁵ or 0.001%) and high specificity, without reliance on reference samples or supervised machine learning models, making it applicable in laboratories with different measuring equipment and using different panels of antibodies for identification of leukemic cells.

The invention provides a reagent composition for detecting minimal residual diseases of acute megakaryocytic leukemia and application of the reagent composition. The reagent composition comprises two groups of antibodies and is a flow cytometry detection composition for follow-up visit of minimal residual diseases after acute megakaryocytic leukemia treatment, a two-tube parallel scheme is used during application, and the first group of antibodies and the second group of antibodies are respectively used for different tube samples. The reagent composition can be applied to flow cytometry to detect minimal residual diseases after acute megakaryocytic leukemia treatment.

The present invention discloses the application of SREBF1 in the preparation of chemotherapeutic drugs for treating acute T-lymphoblastic leukemia, belonging to the technical field of biomedicine. The present invention clarifies the changes in the bone marrow microenvironment of T-ALL patients before and after chemotherapy and inhibits its protective effect on minimal residual disease, clarifies the role of SREBF1 in the abnormal lipidation of the bone marrow microenvironment after T-ALL chemotherapy, and inhibiting the function of SREBF1 can inhibit the generation of adipocytes induced by DEX, thereby reversing the protective effect of adipocytes on residual T-ALL cells. Therefore, inhibiting SREBF1 may be a feasible strategy to solve the recurrence dilemma of T-ALL, which is beneficial to the development of clinical therapeutic drugs for clearing minimal residual T-ALL, provides new treatment ideas and drugs for effectively clearing minimal residual disease of T-ALL and further improving the treatment of T-ALL, and has very important clinical significance.

Provided herein are systems and methods for determining a level of disease, methylation, minimal residual diseases (MRDs) in an individual. Provided herein are systems and methods for retaining double-stranded context of a double-stranded nucleic acid molecule during sequencing.

This disclosure relates to a method for detecting minimal residual disease using tumor information. [Solution] A minimal residual disease detection method utilizing tumor information includes the steps of: acquiring first sequencing data associated with a first sample of the patient; acquiring second sequencing data associated with a second sample of the patient; acquiring third sequencing data associated with a third sample of the patient; and performing minimal residual disease detection for the patient based on the first sequencing data, the second sequencing data, and the third sequencing data.

Described herein are methods of treating a hematological malignancy, including minimal residual disease in hematological malignancies, and methods of preventing relapse of hematological malignancies, the methods comprising administering an inflammasome modulator. In some embodiments the method of treatment comprises administering a compound of formula (I) or a pharmaceutically acceptable salt or solvate thereof, wherein the variables are as defined herein.

The present disclosure provides a probabilistic model for accurate and sensitive somatic single nucleotide variant (SNV) detection in cell-free nucleic acid samples comprising a set of sequence data. A joint genotype may be determined for each locus in the set of sequence data, and germline mutations may be intrinsically removed. A set of filtrations can be applied to eliminate low quality somatic variant calls. Further, a global tumor cell-free deoxyribonucleic acid (cfDNA) fraction and overlapping read mates can be considered, thereby enabling accurate SNV detection and variant allele frequency estimation from samples with low tumor cfDNA fraction. A sensitive early detection of minimal residual disease (MRD) is designed by using the probabilistic model and the machine learning model for distinguishing true variants from sequencing errors.

The invention relates to a primer and a probe for quantitatively detecting MYB-PLAGL1 and PLEKHG1-ABL1 fusion genes, a kit and a use method of the kit. The kit is characterized in that 1, the kit comprises an MYB-PLAGL1 primer, a PLEKHG1-ABL1 primer and an ABL1 internal reference primer; the nucleotide sequences of the MYB-PLAGL1 primer comprise SEQ ID NO: 1 and SEQ ID NO: 2, and the nucleotide sequences of the PLEKHG1-ABL1 primer comprise SEQ ID NO: 3 and SEQ ID NO: 4. The invention finds and verifies that a T-ALL patient carries two new fusion genes of MYB-PLAGL1 and PLEKHG1-ABL1, and the fusion genes can be used as molecular markers of the T-ALL patient and are applied to disease diagnosis, treatment scheme selection and minimal residual focus monitoring.

Described herein are Methods, systems, compositions, and macromolecule complexes, for detecting, analyzing, evaluating, screening for, prognosing, diagnosing, and / or monitoring, pre-cancerous and cancerous conditions with abnormal cell growth in a patient, including patients having Minimal Residual Disease (MRD).

The invention discloses a gene marker panel for diagnosing PCNSL based on cerebrospinal fluid ctDNA, and relates to the technical field of gene detection, the technical key point is that the gene marker panel comprises MYD88, PIM1, CD79B, GNA13, IRF4, DTX1, KMT2D and B2M genes, and PCNSL diagnosis and prognosis evaluation are realized through targeted capture sequencing and a machine learning model. The specificity of the kit in MYD88 wild type PCNSL cases reaches 100%, the BTK inhibitor treatment response and the total lifetime of patients can be predicted, tiny residual focuses can be detected, and recurrence can be warned in advance. The invention further provides a detection kit, a prognosis evaluation system and online webpage application, the quantity demanded of samples is small, the detection sensitivity is high, the specificity is high, and a powerful tool is provided for PCNSL diagnosis and treatment.

The application discloses a data processing device computer program product and application for ctDNA variation detection in the field of bioinformatics. The technical problem to be solved by the application is how to detect ctDNA variation in early cancer or postoperative minimal residual disease under the conditions of no UMI library construction and medium sequencing depth. The application constructs a support sequence set of a candidate variation site, generates a sequence feature tensor and a fragment physical feature vector (including a normalized fragment length); the former is input into a first neural network branch to extract sequence features, and the latter is input into a second neural network branch to extract physical features; through a fusion module, the sequence features and the physical features are combined, a gating weight is calculated according to the physical features by using a gating unit, and the contribution degree of the sequence features is dynamically adjusted, and a real ctDNA variation probability is output. The application utilizes physical laws to suppress sequencing noise and can be applied to monitoring of tumor minimal residual disease under the condition of no molecular bar code.

The present application provides a kind of acute megakaryocyte leukemia micro residual disease detection reagent composition and its application.The reagent composition includes two groups of antibodies, and is used for the composition of flow cytometry detection for following-up micro residual disease after the treatment of acute megakaryocyte leukemia, and when used, 2 tubes are used in parallel, wherein the first group of antibodies and the second group of antibodies are used for different tube samples respectively.The reagent composition of the present application can be applied to flow cytometry detection of micro residual disease after the treatment of acute megakaryocyte leukemia.

A lymphoma recurrence risk prediction method, device and equipment based on MRD are disclosed, comprising: acquiring clinical feature information related to diffuse large B-cell lymphoma; in response to the clinical feature information, calculating a plurality of baseline clinical features through a structured constraint target Bayesian network model to obtain an initial recurrence risk probability of diffuse large B-cell lymphoma of a target object; the structure constraint is used to prohibit direct connection between each baseline clinical feature; according to the initial recurrence risk probability, the state of minimal residual disease related to diffuse large B-cell lymphoma and high-risk pathological factors, the multidimensional calculation of recurrence risk is carried out through the target random forest model to obtain the final recurrence risk probability of the target object; according to the final recurrence risk probability, the recurrence risk information of diffuse large B-cell lymphoma of the target object is generated. To improve the interpretability and accuracy of lymphoma recurrence risk prediction.

The present invention relates to a DNA methylation marker for acute lymphoblastic leukemia and an application thereof. The marker comprises genes ARHGEF3, ATP7B, C14orf102, CoL2A1, LCP2, MAD1L1, MAPK1, LOC100134868, HTR7, BANP, LDLRAD4, NCAM2, PALM2-AKAP2, RRBP1 and SPPL2B, as well as PFKP, PRDM8, PRDM16 or a combination thereof. DNA fragments of the above genes, when used alone or in combination, can be used for detection, diagnosis, classification or prediction, treatment monitoring, prognosis or other evaluation of acute lymphoblastic leukemia. Moreover, the inventors further found 24 more representative DNA fragments related to acute lymphoblastic leukemia among these 18 genes. Their methylation levels were highly correlated with the diagnosis, remission and relapse of acute lymphoblastic leukemia. It was found that the above genomic fragments or their combinations can serve as diagnostic markers for ALL and can effectively distinguish between ALL remission and relapse patients, indicating that they can further serve as screening markers for monitoring minimal residual disease in ALL patients after treatment.

The present application relates to the field of flow cytometry, in particular to a flow cytometry kit and a monitoring method for monitoring acute B lymphocyte leukemia minimal residual disease, the kit comprises 15 antibodies, aiming at the development mode of bone marrow B cells and common abnormal expression of ALL-B, combined with a full spectrum flow cytometer, all the above detections can be completed by one tube panel, which is convenient, fast, time-saving and labor-saving, and simple to operate.

The invention relates to a minimal residual lesion detection method using tumor information. The minimal residual lesion detection method using tumor information comprises the following steps: acquiring first sequencing data related to a first sample of a patient; acquiring second sequencing data associated with a second sample of the patient; acquiring third sequencing data associated with a third sample of the patient; and performing minimal residual lesion detection on the patient based on the first sequencing data, the second sequencing data and the third sequencing data.

Provided herein are methods and systems monitoring of cancer using minimal residual disease analysis. The methods may comprise assaying multiple nucleic acids to detect a set of biomarkers from samples. The methods may comprise sequencing of nucleic acids. The method may comprise the generation of a probe panel. The methods may comprise processing the set of biomarkers to determine the presence of a cancer or cancer parameters. The processing may be performed by an algorithm.

The present disclosure relates to target sequencing of T and B cell receptor gene rearrangements at the DNA level and using this technology to detect and quantify lymphoid malignant T or B cells (minimal residual disease, MRD) during and after therapy.

The present disclosure relates to target sequencing of T and B cell receptor gene rearrangements at the DNA level and using this technology to detect and quantify lymphoid malignant T or B cells (minimal residual disease, MRD) during and after therapy.

The application discloses a system and a kit for early auxiliary diagnosis of breast cancer and detection of micro residual lesions at various stages, and relates to the technical field of medical diagnosis.The system provided by the application uses the read value ratio of miRNA mature bodies and isomers to perform early auxiliary diagnosis of breast cancer and detection of micro residual lesions at various stages, and has high diagnostic sensitivity and specificity; and the system provides more accurate diagnostic basis for early adoption of treatment or intervention means by breast cancer patients.

Embodiments of the disclosure include methods and compositions for treating minimal residual disease in an individual. In specific embodiments, the disclosure concerns methods of treating an individual with minimal residual disease with one or more inhibitors of CSF-1R and / or one or more inhibitors of CSF-1. In specific embodiments, the individual is positive for the presence of mutated circulating tumor DNA (ctDNA), and / or the individual has colorectal cancer.

The invention relates to a mantle cell lymphoma BCL1-IGH rearrangement MRD detection system. The detection system comprises: (1) a sample module, which is used for extracting peripheral blood or marrow genome DNA of a sample to be detected; (2) an amplification sequencing module: performing amplification by taking the genome DNA as a template to obtain an amplification product, and performing high-throughput sequencing on the amplification product; and (3) the bioinformatics analysis module is used for carrying out BCL1-IGH rearrangement cloning identification and cloning tracking on the to-be-detected sample according to the sequencing result. According to the detection system provided by the invention, the detection process is remarkably simplified, the detection cost and the analysis difficulty are reduced, the detection rate of minimal residual focuses of mantle cell lymphoma is high, and the detection system can be applied to the fields of auxiliary clinical diagnosis and the like.

This invention discloses primer compositions, kits, and their applications for monitoring minimal residual disease in human leukemia. The primer compositions include upstream-specific primer compositions for IGH, IGK, and IGL, downstream-specific primer compositions for IGH, IGL, and IGK, as well as upstream and downstream adapter primers. The primer compositions are designed with careful consideration of primer TM value, GC content, fragment size, specificity, and coverage to ensure that the amplification products are uniform, specific, and comprehensively cover potential clonal forms.

Provided herein are methods and systems for cancer detection and monitoring. The methods may include minimal residual disease analysis. The methods may include using nucleic acids from a urine sample or a urine cell pellet sample. The methods may include assaying nucleic acids in urine to detect a set of biomarkers from the sample. The methods may include monitoring a subject after transurethral bladder tumor resection.

Described herein are methods of preparing an enriched library of nucleic acids, comprising: (a) identifying a panel of patient-specific somatic variants present in a tumor sample from a patient, wherein the somatic variants comprise one or more of (i) tumor somatic variants, (ii) non-tumor somatic variants, and (iii) germline sites incorrectly identified as somatic; (b) preparing a sample of cell- free DNA fragments from the patient for sequencing; (c) selectively enriching the cell-free DNA for the fragments comprising one or more of the somatic variants to generate an enriched library; and (d) analyzing the enriched library by generating sequencing reads for each somatic variant position, wherein analyzing comprises applying a classification model to the somatic variants to classify each somatic variant as either tumor, non-tumor, or germline variants.