266 results about "Tumor Sample" patented technology

The invention discloses a somatic cell structure variation detection method based on a monomolecular long-read length sequence chart hybrid model, which comprises the following steps of: extracting a read length local sequence of a target structure variation interval and a flank region thereof, constructing a local chart genome by utilizing a partial sequence alignment chart algorithm, and encoding a multi-sequence alignment result. And then, a multi-category hybrid model is combined with an expectation maximization algorithm, and clustering analysis is performed on the comparison data, so that the somatic cell structure variation category only from the tumor sample is identified. And finally, generating a consensus sequence of a somatic cell structure variation region in the tumor sample, and taking the consensus sequence as an optimization result of a local genome. Compared with an existing short-read-length sequencing method, the method has the advantages that the problems of comparison errors, low-complexity sequences and genome heterogeneity can be effectively solved, and the detection precision of somatic cell structure variation is remarkably improved. Through the application of a single-molecule long-read-length sequencing technology, more comprehensive and accurate genome information can be provided.

The invention relates to an in vitro method for classifying a subject afflicted with a cancer as suffering from a cancer with (at risk of) a metabolic reprograming towards fatty acids oxidation including a step of assaying the activation of RelB in a tumor sample form said cancer. The inventor indeed identified the pivotal role of RelB in energy metabolism and more particularly mitochondrial respiration and fatty acid oxidation. Accordingly, the invention also relates to inhibitors of RelB activity or expression, as well as of lipid metabolism for use in the treatment of cancers showing an activated RelB.

The invention relates to the technical field of tumor data processing, in particular to a methylation-based tumor data processing system. The system comprises the following modules: a methylated sample sequencing module, a sequencing difference site recognition module, a tumor gene sequence analysis module and a tumor subtype classification module, performing high-throughput sequencing on the to-be-detected clinical tumor DNA sample to obtain methylated tumor sequencing data; performing methylation level quantification on the methylated tumor sequencing data, and performing tumor difference site analysis to generate tumor difference site data; performing tumor generation key gene sequence identification according to the tumor difference site data to generate tumor methylation characteristic data; and performing tumor subtype tag identification according to the tumor methylation characteristic data to generate tumor type tag data. According to the method, accurate tumor typing is realized on the basis of tumor DNA methylation characteristic analysis, and the false negative rate of low-concentration sample detection is effectively reduced.

The invention relates to the technical field of medical equipment, in particular to a lung cancer tumor sampling device and method.The lung cancer tumor sampling device comprises multiple needle cores and multiple sleeves in coaxial sliding fit with the needle cores, the multiple needle cores and the multiple sleeves are in one-to-one correspondence, and the multiple needle cores are parallel; the ends, back to the sampling groove, of the sleeves are jointly connected with a shell of a hollow structure, a push plate is slidably connected into the shell in the axial direction of the needle cores, and the ends, back to the sampling groove, of the needle cores penetrate through the shell and are inserted into the shell to be connected with the push plate; and an adjusting part for driving the push plate to slide in the shell is arranged between the shell and the push plate. The problem that in the prior art, single-point sampling may miss a key mutation area, and false negative is caused is solved.

The invention discloses a tumor phenotype analysis method and system based on a disease source database and machine learning assistance, and relates to the field of artificial intelligence, and the method comprises the steps: obtaining clinical, gene and image multi-modal feature vectors of a tumor sample, inputting a multi-modal feature fusion network, and extracting each modal path vector; performing long-distance dependency modeling on clinical and gene features to obtain a first dependency feature map, and generating a second dependency feature map in combination with the feature association strength feature map; and determining a target tumor phenotype feature vector based on the second dependency feature map and the image feature path vector, finally calculating a matching confidence degree with a to-be-selected phenotype feature vector in a tumor phenotype database, and selecting a phenotype corresponding to the highest confidence degree as a target result. Through cross-modal feature dependence modeling and disease source database matching, the accuracy and efficiency of tumor phenotype analysis are improved, and support is provided for clinical precise diagnosis and treatment.

A method of analyzing a tumor sample comprising:(a) acquiring a library comprising a plurality of tumor members from a tumor sample;(b) contacting the library with a bait set to provide selected members;(c) acquiring a read for a subgenomic interval from a tumor member from said library;(d) aligning said read; and(e) assigning a nucleotide value (e.g., calling a mutation) from said read for the preselected nucleotide position, thereby analyzing said tumor sample.

Disclosed herein are systems, methods, and compositions for treating a subject diagnosed with, or suffering from cancer. In some embodiments, the method comprises determining whether a tumor sample from the subject includes a cytotoxic gene signature, and treating the subject based on the determination. In some embodiments, the subject has or is suspected of having a loss of heterozygosity in human leukocyte antigen (HLA) class I genes. In some embodiments, the therapy comprises one or more checkpoint inhibitors. In some embodiments, the cancer is colorectal, uterine, stomach, lung, skin, head or neck, or non-small cell lung carcinoma.

This disclosure is directed to two cancer-associated fibroblast (CAP) subtypes, namely permissive (permCAF) and restraining (restCAF), in pancreatic ductal adenocarcinoma (PDAC), mesothelioma, urothelial carcinoma, or renal cell carcinoma. Methods are disclosed that describe how to identify a tumor sample as a perCAF or a restCAF subtypes. Methods are also disclosed that use the subtypes for diagnosis, prognosis, differential treatment, and treatment.

The invention relates to a molecular typing model construction and identification method of BRCA mutation breast cancer. The method comprises the following steps: performing unsupervised clustering analysis on a gene with most significant change in a common transcriptome expression profile of BRCA1 / 2 mutant breast cancer to obtain an optimal clustering number, and dividing the optimal clustering number into subtypes with different clinical prognosis and molecular characteristics of the optimal clustering number; based on the clustering result, a random forest algorithm is utilized to construct a molecular typing model, the model comprises a plurality of key classification genes, and the molecular typing model is verified through a verification set and an external data set so as to ensure the accuracy, the stability and the clinical applicability of the molecular typing model. Molecular typing can be rapidly and accurately carried out according to common transcriptome sequencing data of a BRCA1 / 2 mutant breast cancer patient tumor sample, and a scientific basis is provided for selection of an individualized treatment scheme.

The invention discloses a somatic mutation recognition method and system based on a residual network in combination with a channel attention mechanism, and the method comprises the steps: scanning a sequence comparison result of a tumor sample and a paired normal sample, and constructing a multi-channel feature matrix representation; a somatic mutation recognition model combining a residual network (ResNeXt) and a channel attention mechanism (SE module) is constructed, verification and fine tuning are performed by using a test set, and then the somatic mutation recognition model which is excellent in performance and suitable for resource-constrained environment deployment is obtained. The invention provides a new hybrid neural network, the network fully utilizes sequence comparison result information of a tumor sample and a paired normal sample, somatic mutation information can be extracted and learned more effectively, and mutation recognition accuracy is improved.

The invention discloses a trophoblast-free one-step culture method and application of tumor infiltrating lymphocytes, and particularly discloses a one-step amplification method of tumor infiltrating lymphocytes, which comprises the following steps: treating a tumor sample obtained from a subject into tumor segments; the tumor segments are cultured in a culture medium containing a CD3 agonist, a 4-1BB agonist and IL-2, so that an amplified tumor infiltration lymphocyte population is obtained, and the culture medium does not contain trophoblastic cells. Compared with the prior art, the method has the advantages that the required period for amplifying the tumor infiltrating lymphocytes is shorter, the cost is lower, the cell effect function is stronger, and the clinical application range of the tumor infiltrating lymphocyte therapy is widened.

The invention relates to a PDC (Polycrystalline Diamond Compact) cell carrying a bar code DNA (Deoxyribose Nucleic Acid) tag convenient to track as well as a preparation method and application thereof, and belongs to the technical field of The invention provides an isolated culture method of PDC primary cells, and provides a method for constructing recombinant PDC cells containing bar code DNA tags. According to the PDC primary cell culture system, the cell caking rate is reduced, the cell viability and the adherence rate are improved, and continuous passage to 20 generations or above can be achieved. The PDC primary cells faithfully retain the heterogeneity of clinical tumor samples in the aspects of mutation types, tumor generation and development mechanisms and the like. The bar code DNA tag introduced into the PDC cell can be detected by carrying out targeted sequencing and single cell RNA sequencing on a bar code DNA tag sequence in cell genome DNA, so that different clone groups reserved from PDX of the PDC cell line are conveniently distinguished and tracked in a high-throughput manner.

The present invention relates to the technical field of tumor immune microenvironment detection and analysis, and discloses an apparatus and method for detecting and analyzing the immune microenvironment of solid tumors. The apparatus for detecting and analyzing the immune microenvironment of solid tumors includes: a detection mechanism: used to contact with a tumor sample or puncture a part of the tumor sample and upload data for operators to analyze; a transportation and cleaning mechanism integrating transportation, cleaning and adjustment functions: cleaning both sides of the sample synchronously during transportation and adapting to different sample sizes; a clamping and turning mechanism: clamping the sample and turning it to position to expose the cleaning surface; a collection component: detachably recovering the shed impurities; a wiping component: used to clean the detection area of the detection mechanism after detection to prevent residual substances from affecting subsequent detection results. The transportation and cleaning mechanism of the present invention can automatically clean the impurities outside the sample while transporting the tumor sample, and can also adjust according to samples of different sizes, improving the accuracy of subsequent detection.

The disclosure provides a method for treating a subject afflicted with a tumor comprising administering to the subject a therapeutically effective amount of an anti-PD-1 antibody or antigen-binding portion thereof or an anti-PD-L1 antibody or anti-gen-binding portion thereof, wherein the subject is identified as having a high inflammatory gene signature score. In some embodiments, the high inflammatory gene signature score is determined by measuring the expression of a panel of inflammatory genes in a tumor sample obtained from the subject, wherein the inflammatory gene panel comprises CD274 (PD-LI), CD8A, LAG3, and STAT1.

The invention discloses a microsatellite instability detection method based on single-sample high-throughput sequencing for microsatellite site micro-offset, and relates to the technical field of bioinformatics, and the microsatellite instability detection method comprises the following steps: processing a sequencing sequence of a to-be-detected sample obtained by a high-throughput sequencing technology to obtain a comparison file; according to the method, selection and quality control of microsatellite sites are strictly controlled, a microsatellite instability detection method based on single-tumor sample high-throughput sequencing can be used for analyzing the repetition times of candidate microsatellite site repetition units without depending on a control sample, and meanwhile, the method has very good sensitivity to a sample with relatively large offset, so that the accuracy of the microsatellite instability detection is greatly improved. The method can also be applied to other cancer species with MSI characteristics, and can adapt to detection requirements of different cancer species by adjusting candidate microsatellite loci no matter whether a micro-migration condition exists or not, provide visualization, assist in seeing the degree of microsatellite migration, facilitate manual recheck and reduce misjudgment.

The invention discloses a bioelectrical impedance tumor identification method based on multi-modal fusion. The method comprises the following steps: S1, acquiring electrical impedance signal data and tissue slice image data of a tumor sample; the tissue slice image data are pathological slice images corresponding to tumor tissues; s2, inputting the electrical impedance signal data and the tissue slice image data into a multi-modal feature coding module for asymmetric feature coding; s3, performing splicing and weighted fusion on the global semantic feature vector and the image semantic feature vector to form a multi-modal feature vector; and S4, inputting the multi-modal feature vector into a decoding network for classification prediction, and outputting a tumor identification result. According to the method, an asymmetric coding structure and a weighted fusion mechanism are constructed by fusing the electric signal modality and the image modality, so that the utilization efficiency and the feature discrimination capability of multi-modal information can be effectively improved, and the accuracy and the reliability of tumor recognition are remarkably improved.

Described herein are techniques for determining tumor mutational burden (TMB) of a tumor sample previously obtained from a subject. In some embodiments, the techniques include obtaining sequence reads, the sequence reads having been previously obtained by sequencing the tumor sample; aligning the sequence reads to a population- specific genomic reference graph representing a linear reference sequence and population- specific variants relative to the linear reference sequence, wherein the population- specific variants are variants associated with at least one population to which the subject belongs; identifying, based on a result of aligning the sequence reads to the population- specific genomic reference graph, a plurality of somatic variants; and determining the TMB of the tumor sample using the identified plurality of somatic variants.

Strategies for blocking anti-apoptotic proteins or activating proapoptotic proteins in combination with immune checkpoint blockade therapy to prevent or reverse acquired resistance are described, providing methods to detect, prevent, and / or reverse acquired resistance to ICB therapy. Anti-melanoma therapy can be enhanced by administering an effective amount of an activator of a pro-apoptotic protein, such as a BAX activator, and / or a downregulator of an anti-apoptotic protein, such as a BH3 mimetic. Also described is a method of detecting acquired resistance to anti-melanoma therapy by assaying a sample of tumor DNA for deletion and / or amplification of genes indicative of acquired resistance.

Methods for treating a patient having a solid tumor are disclosed, comprising: (a) obtaining a tumor sample from the patient; (b) assessing the sample for levels of biomarkers for at least one of innate immune cells and adaptive immune cells; and (c) administering an effective amount of an immunotherapy to the patient if the sample comprises elevated levels of CD68+ PD-L1+ macrophages and CD8+ T cells compared to control and / or elevated levels of CD20+ B cells compared to control and / or low levels of CD163 expression compared to control and PD-L1 expression of greater or equal to (≥) 50%.

A targeted panel with low sample input requirements from a tumor only sample may be processed to estimate mutation load in a tumor sample. The method may include detecting variants in nucleic acid sequence reads corresponding to targeted locations in the tumor sample genome; annotating detected variants with an annotation information from a population database; filtering the detected variants, wherein the filtering rule set retains the somatic variants and removes germ-line variants; counting the identified somatic variants to give a number of somatic variants; determining a number of bases in covered regions of the targeted locations in the tumor sample genome; and calculating a number of somatic variants per megabase, provides an estimate of the mutation load per megabase in the tumor sample genome.

Disclosed herein is a method of analyzing flow cytometry data for cells derived from homogenized whole tumor samples.

The invention relates to the field of medical auxiliary instruments, in particular to a hematologic tumor sample transfer box which comprises a box body, a partition plate capable of sliding up and down is arranged in the box body, a fixing assembly is arranged in the box body, and the fixing assembly comprises a first fixing frame, a second fixing frame and a connecting piece which are fixed to the bottom wall in the box body. The first fixing frame is used for limiting one side of the test tube rack; the second fixing frame is arranged in the box body and can slide horizontally; the second fixing frame corresponds to the first fixing frame and is used for limiting the other side of the test tube rack; a connecting piece is arranged between the partition plate and the second fixing frame, and when the partition plate slides upwards, the connecting piece pulls the second fixing frame back into the box body. A springback piece is arranged on one side of the second fixing frame, and when the partition plate resets downwards, the springback piece pops out the second fixing frame; the test tube rack for placing test tube samples can be integrally transferred into the box body and can be automatically locked, so that not only can quick transfer be realized, but also collision damage in the transfer process can be avoided.

The present invention provides novel human fms related tyrosine kinase 3 (FLT3) antigen binding proteins, such as antibodies, having improved FLT3 binding affinity, and / or anti-tumor activity. The FLT3 antibodies of the invention were generated by mutation of a parent FLT3 antibody and tested in in vitro in binding assays as well as in vivo in a mouse tumor model and in human patient tumor samples. The antibodies of the invention are provided as monospecific constructs or in a bispecific FLT3xCD3 antibody format and show excellent target affinity and / or tumor cell killing. The present invention also relates methods for producing the antigen binding proteins of the invention as well as nucleic acids encoding them, vectors for and host cells for their expression. The invention further relates to methods of treating or diagnosing a disease such as leukemia using an FLT3 antigen binding protein (ABP) of the invention.

The present disclosure encompasses methods for molecularly subtyping formalin-fixed paraffin-embedded tumor samples. The disclosure works particularly well for old and degraded (archival) samples for which standard methods are unfeasible. Further, the methods disclosed allow for the correlation of patient outcome data with the molecular subtype of the tumor and provides a wealth of information which will guide treatment decisions and / or selection of therapeutic agents.

Provided are methods for expanding tumor-infiltrating lymphocytes (TILs), which include co-culturing an initial cell population containing TILs with first feeder cells to obtain a first expanded cell population; and then co-culturing the first expanded cell population with second feeder cells to obtain an expanded TIL population. The methods can quickly produce a large number of TILs from a small tumor sample.

The present invention relates to the provision of vaccines which are specific for a patient's tumor and are potentially useful for immunotherapy of the primary tumor as well as tumor metastases. In one aspect, the present invention relates to a method for providing an individualized cancer vaccine comprising the steps: (a) identifying cancer specific somatic mutations in a tumor specimen of a cancer patient to provide a cancer mutation signature of the patient; and (b) providing a vaccine featuring the cancer mutation signature obtained in step (a). In a further aspect, the present invention relates to vaccines which are obtainable by said method.

The invention discloses a method and device suitable for tumor glucose metabolism reprogramming driving factor analysis, and the method comprises the steps: generating a gene expression matrix for a biological pathway under a sample; performing dimension reduction processing on the gene expression matrix to obtain a first low-dimensional representation and a second low-dimensional representation; inputting the first low-dimensional representation and the second low-dimensional representation into a causal direction inference structure, and outputting a plurality of initial causal direction inference results; selecting from the plurality of initial causal direction inference results to obtain a target causal direction inference result corresponding to the sample; and finally, analyzing and comparing a target causal direction inference result under a normal sample and a target causal direction inference result under a tumor sample to obtain an analysis result, and indicating that Fenton reaction in cells drives tumor glucose metabolism reprogramming. Therefore, key factors of tumor glucose metabolism reprogramming can be quickly and accurately identified, and the fact that the Fenton reaction in cells is a main reason of tumor glucose glycolipid metabolism reprogramming is found.

Described herein are techniques for predicting whether a subject will respond to an immune checkpoint inhibitor (ICI) therapy based on RNA expression data and cytometry data obtained for the subject. In some embodiments, the techniques include: obtaining the RNA expression data, the RNA expression data having been previously obtained from a tumor sample from the subject; selecting, using the RNA expression data, an MF profile type for the tumor sample; obtaining the cytometry data, the cytometry data having been previously obtained from a blood sample from the subject; determining, using the cytometry data, a G2 score for the blood sample, wherein the G2 score is indicative a likelihood that the blood sample is of a Primed (G2) immunoprofile type of multiple immunoprofile types; and predicting, based on the selected MF profile type and the G2 score, whether the subject will respond to the ICI therapy.

The invention provides a fusion transcript recognition method, device and system based on transcriptome multiple comparison data and a medium, and the core of the method is to construct a set of full-chain analysis framework oriented to multiple mapping reads to realize fusion gene detection. Comprising a pairing read segment preliminary screening module based on a loose mapping strategy, a candidate fusion construction module based on an exon graph structure, a remapping module based on an enhanced reference transcriptome, a transcript abundance estimation module based on a probability generation model, and a fusion scoring module based on fusion site specificity support degree. And a false positive inhibition module based on coverage consistency and biological filtration. According to the method, the dependence of a traditional fusion gene detection method on a unique mapping read is broken through, multiple comparative analysis on the fuzzy mapping read abandoned due to sequence homology is proposed for the first time, and high sensitivity and low false positive rate of the fuzzy mapping read are verified in simulated data and real tumor samples; the method has remarkable technical advancement, clinical applicability and expandability.

The utility model discloses a tumor sample storage device which comprises a refrigerating box and a box cover arranged at the top of the refrigerating box, a plurality of placing holes for sample test tubes to be inserted are formed in the box cover, one side of each placing hole is provided with a sealing assembly used for sealing the placing hole, and when the sample test tubes are pulled out of the placing holes, the sealing assemblies can seal the placing holes. And the closing assembly can automatically close the placing hole. After a medical worker puts a sample test tube in the placing hole, the sealing assembly corresponding to the placing hole can automatically seal the placing hole, so that emission of cold air in the refrigerating box is effectively prevented, temperature rise in the refrigerating box is avoided, and storage of tumor samples is facilitated.