50 results about "Tissue microarray" patented technology

A method and apparatus are disclosed for a high-throughput, large-scale molecular profiling of tissue specimens by retrieving a donor tissue specimen from an array of donor specimens, placing a sample of the donor specimen in an assigned location in a recipient array, providing substantial copies of the array, performing a different biological analysis of each copy, and storing the results of the analysis. The results may be compared to determine if there are correlations or discrepancies between the results of different biological analyses at each assigned location, and also compared to clinical information about the human patient from which the tissue was obtained. The results of similar analyses on corresponding sections of the array can be used as quality control devices, for example by subjecting the arrays to a single simultaneous investigative procedure. Uniform interpretation of the arrays can be obtained, and compared to interpretations of different observers.

A method and apparatus are disclosed for processing regions of interest for objects comprising biological material. A region of interest can be denoted for a physical object and information indicating the region of interest can be stored in a computer-readable medium for later retrieval. Subsequently, when the object is retrieved, the information indicating the region of interest can be used to generate information specifying a physical location within the region of interest. An operation can then be performed on the physical location within the region of interest. Reference pints within the object can assist in regeneration of the region of interest, and the reference points can be arranged in such a fashion that processing can take rotation of the object into account. The invention includes various features advantageous for constructing tissue microarrays.

A system and methods for co-registering multi-channel images of a tissue micro array, comprising the steps of, providing a biological material on a substrate; applying one or more molecular probes, adapted to provide fluorescent molecular markers, to the biological material; obtaining a first digital image of the biological material and the fluorescent molecular markers; applying a morphological stain to the biological material; obtaining a second digital image of the biological material, computing information common to the first and second images; and co-registering the second image with the first image based on one or more registration metrics.

Systems and methods for image pattern recognition comprise digital image capture and encoding using vector quantization (“VQ”) of the image. A vocabulary of vectors is built by segmenting images into kernels and creating vectors corresponding to each kernel. Images are encoded by creating a vector index file having indices that point to the vectors stored in the vocabulary. The vector index file can be used to reconstruct an image by looking up vectors stored in the vocabulary. Pattern recognition of candidate regions of images can be accomplished by correlating image vectors to a pre-trained vocabulary of vector sets comprising vectors that correlate with particular image characteristics. In virtual microscopy, the systems and methods are suitable for rare-event finding, such as detection of micrometastasis clusters, tissue identification, such as locating regions of analysis for immunohistochemical assays, and rapid screening of tissue samples, such as histology sections arranged as tissue microarrays (TMAs).

The present disclosure is directed to devices, arrays, kits and methods for detecting biomolecules in a tissue section (such as a fresh or archival sample, tissue microarray, or cells harvested by an LCM procedure) or other substantially two-dimensional sample (such as an electrophoretic gel or cDNA microarray) by creating “carbon copies” of the biomolecules eluted from the sample and visualizing the biomolecules on the copies using one or more detector molecules (e.g., antibodies or DNA probes) having specific affinity for the biomolecules of interest. Specific methods are provided for identifying the pattern of biomolecules (e.g., proteins and nucleic acids) in the samples. Other specific methods are provided for the identification and analysis of proteins and other biological molecules produced by cells and / or tissue, especially human cells and / or tissue. The disclosure also provides a plurality of differentially prepared and / or processed membranes that can be used in described methods, and which permit the identification and analysis of biomolecules.

The invention disclosed herein improves upon existing tissue microarray technology by using frozen tissues embedded in tissue embedding compound as donor samples and arraying the specimens into a recipient block comprising tissue embedding compound. Tissue is not fixed prior to embedding, and sections from the array are evaluated without fixation or post-fixed according to the appropriate methodology used to analyze a specific gene at the DNA, RNA, and / or protein levels. Unlike paraffin tissue arrays which can be problematic for immunohistochemistry and for RNA in situ hybridization analyses, the disclosed methods allow optimal evaluation by each technique and uniform fixation across the array panel. The disclosed arrays work well for DNA, RNA, and protein analyses, and have significant qualitative and quantitative advantages over existing methods.

Compositions, methods and kits are described for identifying biomolecules (e.g., proteins and nucleic acids) expressed in a biological sample that are associated with the presence, development, or progression of a disease (such as cancer), or more generally determination of the etiology or risk factors associated with a disease. Sample types analyzed by the disclosed methods include but are not limited to archival tissue blocks that have been preserved in a fixative, tissue biopsy samples, tissue microarrays, and so forth. The methods disclosed herein correlate expression profiles of biomolecules with various disease types, and allow for the determination of relative survival rates; in some embodiments, the methods permit determination of survival rates for a subject with cancer. In other embodiments, the disclosure relates to methods for evaluating therapeutic regimes for the treatment, such as treatment of cancer.

A system for analyzing tissue samples, that generally comprises, a storage device for at least temporarily storing one or more images of one or more cells, wherein the images comprise a plurality of channels; and a processor that is adapted to determine the extent to which a biomarker may have translocated from at least one subcellular region to another subcellular region; and then to generate a score corresponding to the extent of translocation.

A method and system for automated quantitation of tissue micro-array image (TMA) digital analysis. The method and system automatically analyze a digital image of a TMA with plural TMA cores created using a needle to biopsy or other techniques to create standard histologic sections and placing the resulting needle cores into TMA. The automated analysis allows a medical conclusion such as a medical diagnosis or medical prognosis (e.g., for a human cancer) to be automatically determined. The method and system provides reliable automatic TMA core gridding and automated TMA core boundary detection including detection of overlapping or touching TMA cores on a grid.

The present disclosure is directed to devices, arrays, kits and methods for detecting biomolecules in a tissue section (such as a fresh or archival sample, tissue microarray, or cells harvested by an LCM procedure) or other substantially two-dimensional sample (such as an electrophoretic gel or cDNA microarray) by creating "carbon copies" of the biomolecules eluted from the sample and visualizing the biomolecules on the copies using one or more detector molecules (e.g., antibodies or DNA probes) having specific affinity for the biomolecules of interest. Specific methods are provided for identifying the pattern of biomolecules (e.g., proteins and nucleic acids) in the samples. Other specific methods are provided for the identification and analysis of proteins and other biological molecules produced by cells and / or tissue, especially human cells and / or tissue. The disclosure also provides a plurality of differentially prepared and / or processed membranes that can be used in described methods, and which permit the identification and analysis of biomolecules.

A tissue microarray imaging system autonomously images, analyzes, and stores data for samples in a tissue microarray. The system may include a tissue microarray, a robotic microscope, and an imaging workstation that executes software to automatically control operation of the microscope to capture images from the microarray and analyze image results. A low magnification may be used to register samples within the microarray and obtain coordinates for each tissue specimen. Progressively higher magnifications may be used to analyze images of each registered specimen. Where multiple dyes are used to stain specimens, color separation techniques may be applied to independently measure and analyze each staining intensity. Images and quantitative data from the images may then be stored in a relational database for subsequent review. The system may be local, or may be Web-based for distributed control and sharing of results.

The invention provides microarrays comprising a plurality of frozen tissues and / or cell samples and methods of preparing and using the same. By using frozen samples, the microarrays provide optimal samples from which to detect the expression of both nucleic acids (e.g., mRNAs) and proteins in high throughput parallel analyses. The microarrays enable gene identification, molecular profiling, selection of promising drug targets, sorting and prioritizing of expressed sequence array data, and the identification of abnormal physiological processes associated with disease.

A method and apparatus for processing an image of a tissue sample microarray include placing a plurality of tissue samples in an array on a microscope slide. The tissue samples are then simultaneously and uniformly treated, as by staining. Images of the tissue making up the microarray are captured and stored together with identifying information related thereto. The images may be displayed from the digital storage medium using a programmed processor which can select various magnifications for display. The images also can be accessed by network and remotely.

The subject disclosure provides systems and methods for determination of Area of Interest (AOI) for different types of input slides. Slide thumbnails may be assigned into one of five different types, and separate algorithms for AOI detection executed depending on the slide type. Slide types include ThinPrep (RTM) slides, tissue micro-array (TMA) slides, control HER2 slides with 4 cores, smear slides, and a generic slide. The slide type may be assigned based on a user input. Customized AOI detection operations are provided for each slide type. If the user enters an incorrect slide type, operations include detecting the incorrect input and executing the appropriate method. The result of each AOI detection operations provides as its output a soft-weighted image having zero intensity values at pixels that are detected as not belonging to tissue, and higher intensity values assigned to pixels detected as likely belonging to tissue regions.

The present invention provides systems and methods for image recoloring and color standardization. The invention relates, in part, to standardization of digitized whole-slide histopathology images and digitized images of tissue microarrays (TMA). Various aspects of the invention are directed to the detection of color feature points from 3D histogram of a reference image (considered a well-stained image) and the region-based transference of color statistics between a reference image and a target image (image to be standardize). Another aspect of the present invention is an image / video colorfulness measure. A further aspect of the invention includes multimedia analytics application, including a retrieval application. Another aspect of the invention is directed to on-line viewing and recoloring of images, including but not limited to face and clothing.

A system and methods for co-registering multi-channel images of a tissue micro array, comprising the steps of, providing a biological material on a substrate; applying one or more molecular probes, adapted to provide fluorescent molecular markers, to the biological material; obtaining a first digital image of the biological material and the fluorescent molecular markers; applying a morphological stain to the biological material; obtaining a second digital image of the biological material, computing information common to the first and second images; and co-registering the second image with the first image based on one or more registration metrics.

The present invention provides a method of screening for markers useful in predicting the efficacy of a specified cancer that includes: (a) constructing a tissue microarray from a tissue bank comprising multiple tissue samples that are annotated with clinical follow up data; (b) labeling polynucleic acid probes specific for oncogenes or cancer associated genes known to be potential amplicons; (c) performing fluorescent in situ hybridization analysis on the tissue microarray; and (d) correlating the result of the fluorescent in situ hybridization with the clinical follow up data. The present disclosure also provides methods of treating breast cancer that include screening a breast cancer patient for amplification of one or more of the genes disclosed herein, and treating a patient having amplification of one or more of these genes with a therapeutically effective amount of a compound that interferes with HER2 signaling.

The systems described herein autonomously image, analyze, and store date for samples in a tissue microarray. The system may include a tissue microarray, a robotic microscope, and an imaging workstation that executes software to automatically control operation of the microscope to capture images from the microarray and analyze image results. A low magnification may be used to register samples within the microarray and obtain coordinates for each tissue specimen. Progressively higher magnifications may be used to analyze images of each registered specimen. Images and quantitative data from the images may then be stored in a relational database for subsequent review. The system may be local, or may be Web-based for distributed control and sharing of results.

The invention provides application of SMOC2 gene (SPARC related modular calcium binding2, with the Chinese name of secreting modular calcium binding protein 2; smooth muscle related protein 2) in preparation of medicine for detecting or treating endometrial cancer and ovarian cancer. A tissue chip comprising 157 endometrial cancer tissue specimens, 30 normal proliferative phase endometrium tissue specimens and 30 normal secretory phase endometrium tissue specimens is established by utilizing a tissue microarray technology, the expression conditions of SMOC2 in the specimens are detected by utilizing the immunohistochemical technique, the positive expression rate of the SMOC2 in the normal tissue of the endometrium is far lower than the positive expression rate in the endometrial cancer, and the expression intensity is positively correlated to muscular invasion depth of the endometrial cancer and tumor grading of the endometrial cancer. Therefore, the SMOC2 gene can be used for preparing the medicine for detecting or treating endometrial cancer. The medicine is reliable in experimental result and high in repeatability and has good clinical application prospect and good application values and social benefits.

Compositions, methods and kits are described for identifying biomolecules (e.g., proteins and nucleic acids) expressed in a biological sample that are associated with the presence, development, or progression of a disease (such as cancer), or more generally determination of the etiology or risk factors associated with a disease. Sample types analyzed by the disclosed methods include but are not limited to archival tissue blocks that have been preserved in a fixative, tissue biopsy samples, tissue microarrays, and so forth. The methods disclosed herein correlate expression profiles of biomolecules with various disease types, and allow for the determination of relative survival rates; in some embodiments, the methods permit determination of survival rates for a subject with cancer. In other embodiments, the disclosure relates to methods for evaluating therapeutic regimes for the treatment, such as treatment of cancer.

The invention discloses an HER2 image classification method and system based on convolution and a residual network. The method comprises the steps: obtaining a plurality of HER2 images with annotations from a tissue microarray database, and taking the HER2 images with annotations as an initial data sample; respectively cutting each initial data sample by adopting a cutting function, and establishing an extended data sample set; training the convolution and residual error network by using the extended data sample set to obtain a trained convolution and residual error network as an HER2 image classification model; and inputting the HER2 image to be classified into the HER2 image classification model to obtain a classification result of the HER2 image to be classified. According to the HER2 image classification method, more HER2 images are obtained by utilizing the clipping function, so that the technical defect that the data volume of the HER2 images cannot meet the training requirementis overcome. The HER2 image classification is realized by utilizing the convolution and residual network, the over-fitting phenomenon of an existing neural network model is avoided, and the HER2 imageclassification method is realized under the condition that the data volume is relatively small. The HER2 images are automatically and accurately classified by using the neural network model.

The invention provides a prostate cancer tissue microarray grading method based on a convolutional neural network. The method comprises the following steps: acquiring prostate cancer tissue microarrayimage data; preprocessing the prostate cancer tissue microarray image data; establishing an image segmentation model based on the preprocessed prostate cancer tissue microarray image data, and inputting the prostate cancer tissue microarray image data into the image segmentation model; restoring an output result of the image segmentation model in the size the same with that of the original image;and performing consistency check and comparison on the prediction result of the image segmentation model and the expert labeling result, and outputting a comparison result. According to the method, the characteristics of the deep layer and the shallow layer can be fused through the multi-scale self-attention network, meanwhile, the characteristics of each scale are supervised, network parameterscan be reduced, the calculation efficiency can be improved, and the effectiveness of the method is verified on a completely marked data set.

The invention discloses an application of ABHD6 in diagnosis, prognosis and treatment products of non-small cell lung cancer. The invention discloses a monoacylglycerol hydrolase ABHD6 (alpha / beta-hydrolase-domain-containing 6). The results of tissue microarray showed that the expression of ABHD6 in tumor tissues was significantly higher than that in adjacent tissues, and the high expression of ABHD6 was related to lymph node metastasis and TNM staging in non-small cell lung cancer, which was an independent factor of poor prognosis in NSCLC. The application of ABHD6 in diagnosis, prognosis andtreatment products of non-small cell lung cancer can influence the invasion and migration of non-small cell lung cancer cells in vitro by silencing ABHD6, and can slow down the growth speed of the tumor and slow down the process of the tumor migration to the lung.

The present invention provides a method of screening for markers useful in predicting the efficacy of a specified cancer that includes: (a) constructing a tissue microarray from a tissue bank comprising multiple tissue samples that are annotated with clinical follow up data; (b) labeling polynucleic acid probes specific for oncogenes or cancer associated genes known to be potential amplicons; (c) performing fluorescent in situ hybridization analysis on the tissue microarray; and (d) correlating the result of the fluorescent in situ hybridization with the clinical follow up data. In addition, the present invention provides a method of treating breast cancer that includes measuring the expression levels or amplification of HTPAP in a patient having breast cancer and then providing a patient having increased levels of HTPAP expression or HTPAP amplification with therapeutic quantities of at least one compound that interferes with the phosphatidic acid phosphatase activity of HTPAP. The present invention also encompasses a method of treating breast cancer that includes screening a breast cancer patient for amplification of the cMYC gene and then treating a patient having amplification of the cMYC gene with therapeutic quantities of a compound that interferes with HER2 signaling.

Disclosed are a mold for the preparation of recipient blocks, having a certain space at the top and containing multiple sample-receiving holes in the bottom thereof and a method for preparing a tissue microarray block, comprising: (1) arraying samples in the sample-receiving holes in the mold for the preparation of recipient blocks; (2) placing the mold for the preparation of recipient blocks in a base mold and pushing the samples toward the bottom of the base mold; (3) filling the base mold with a liquid base material for the recipient block and incubating the liquid base material at a predetermined temperature for a predetermined time period; and (4) separating the tissue microarray block from the mold for the preparation of recipient blocks, said tissue microarray block being formed as the liquid base material is solidified so that the samples are embedded in a microarray pattern within the solidified material.

A process for preparing paraffin wax embedded tissue microarray chip with oridinary microscope includes such steps as installing special perforating needle and sampling needle to the lens holder of the ordinary optical microscope, putting special paraffin wax block fixing box on object carrier, turning the lens holder and regulating the distance between lens and object carrier while perforating, sample and checking sample, and observing while locating. Its advantages are simple operation and low cost.