Spatially Co-Registered Genomes and Imaging (SCORGI) Data Elements for Fingerprinting Microdomains

Abstract

A method for generating a plurality of spatially co-registered data elements, each spatially co-registered data element being associated with and generated from a pair of co-registered tissue portions, the pair of co-registered tissue portions being obtained from adjacent locations of a core taken from a tissue sample and comprising an image data portion and a genomic data portion. For each pair of co-registered tissue portions, the method comprises: (i) obtaining a plurality of multiplexed to super-images from the imaging data portions of the co-registered tissue portions and storing them as a portion of the data element, (ii) generating image data from the plurality of multiplexed to super-images and storing them as a portion of the data element, and (iii) generating genomic data from the genomic data portions of the associated co-registered tissue portions and storing them as a portion of the data element.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority under 35 U.S.C. §119(e) to U.S. Provisional Patent Application No. 62 / 721,018, entitled “Spatially CO-Registered Genomic and Imaging (SCORGI) Data Elements for Fingerprinting Microdomains,” filed on August 22, 2018, the disclosure of which is incorporated herein by reference.

[0003] Government Contracts

[0004] This invention was made with government support under Grant No. CA204826 awarded by the National Institutes of Health (NIH). The government has certain rights in this invention. Technical Field

[0005] The present invention relates to digital pathology, and in particular to a method for creating spatially co-registered genomic and imaging (SCORGI) data elements to fingerprint microdomains in tumors and / or related tissues, including new tumor sampling strategies for characterizing spatial heterogeneity in solid tumors, and to digital pathology systems employing such methods. Background Art

[0006] Digital pathology refers to the acquisition, storage, and display of histologically stained tissue samples, and is initially gaining traction in niche applications such as second opinion telepathology, immunointerpretation, and intraoperative telepathology. Typically, large amounts of patient data are generated from biopsy samples, consisting of 3-50 slides, and visually evaluated by a pathologist under a microscope, but with digital technology by viewing on a high-definition monitor. Current workflow practices are time-consuming, error-prone, and subjective due to the manual labor involved.

[0007] Cancer is a heterogeneous disease. In hematoxylin and eosin (H&E) stained tissue images, heterogeneity is characterized by the presence of various histological structures, such as carcinoma in situ, invasive carcinoma, adipose tissue, blood vessels and normal ducts. Moreover, for many malignant tumors, molecular and cellular heterogeneity is a significant feature between tumors of different patients, between different parts of a single patient's tumor, and within a single tumor. Intratumoral heterogeneity involves phenotypically unique clonal subpopulations of cancer cells and other cell types including tumor microenvironment (TME). These clonal subpopulations of cancer cells and other cell types include local and bone marrow-derived stromal stem cells and progenitor cells, subclasses of immune inflammatory cells that promote or kill tumors, fibroblasts associated with cancer, endothelial cells and pericytes. TME can be viewed as an evolving ecosystem in which cancer cells interact with these other cell types in a heterotypic manner and use available resources to reproduce and survive. Consistent with this view, the spatial relationship between cell types in TME (i.e., spatial heterogeneity) appears to be one of the main drivers of disease progression and treatment resistance. Therefore, it is imperative to define the spatial heterogeneity within the TME to correctly diagnose specific disease subtypes and identify the optimal course of treatment for individual patients.

[0008] To date, intratumor heterogeneity has been explored using three main approaches. The first approach is to sample cores from specific tumor regions to measure overall averages. Heterogeneity within a sample is measured by analyzing multiple cores within the tumor using a variety of techniques, including whole exome sequencing, epigenetics, proteomics, and metabolomics. The second approach involves "single-cell analysis" using the above methods, RNASeq, imaging of cells after isolation from tissue, or flow cytometry. The third approach uses the spatial resolution of light microscopy imaging to maintain spatial context and is combined with molecule-specific labels to measure biomarkers in situ in cells. While each of these approaches offers some degree of validity, they all have various drawbacks and limitations.

[0009] Furthermore, one of the greatest challenges in assessing the clinical significance of tumor heterogeneity is the lack of tools to spatially profile samples at the single-cell level and the limited tools to integrate genomic and proteomic measurements in appropriate clinically and molecularly annotated sample sets.

[0010] Therefore, there is room for improvement in the area of ​​characterization of intratumor heterogeneity. Summary of the invention

[0011] In one embodiment, a method of creating multiple tissue sections for imaging and genomic analysis is provided. The method includes obtaining multiple cores from a tissue sample, and for each core, obtaining multiple imaging data sections and multiple genomic data sections from the core in an alternating manner along the length of the core, such that each imaging data section is associated with a corresponding one of the genomic data sections to form multiple serial pairs of adjacent tissue sections.

[0012] In another embodiment, a plurality of tissue microarray (TMA) slides are provided, which include tissue portions for imaging and genomic analysis. The plurality of TMA slides include: a plurality of first TMA slides having a plurality of imaging data portions for each of a plurality of cores in a tissue sample fixed thereto; and a plurality of second TMA slides having a plurality of genomic data portions for each of a plurality of cores in a tissue sample fixed thereto. For each core, the plurality of imaging data portions and the plurality of genomic data portions are from alternating portions along the length of the core, such that each imaging data portion is associated with a corresponding one of the genomic data portions for the core to form a plurality of continuous pairs of adjacent tissue portions.

[0013] In yet another embodiment, a method for generating a plurality of spatially co-registered data elements from a tissue sample is provided. The method includes obtaining a plurality of cores from the tissue sample, and for each core, obtaining a plurality of imaging data portions and a plurality of genomic data portions from the core in an alternating manner along the length of the core, such that each imaging data portion is associated with a corresponding one of the genomic data portions to form a plurality of series pairs of adjacent, co-registered tissue portions. The method also includes, for each imaging data portion: (i) obtaining a plurality of multiplexed to hyperplexed images by repeated labeling with a plurality of fluorescent labels, (ii) analyzing the multiplexed to hyperplexed images to obtain image data therefrom, and (iii) identifying a plurality of regions of interest in the genomic data portion associated with the imaging data portion based on the image data obtained for the imaging data portion. The method also includes, for each genomic data portion, performing a genomic analysis on each region of interest in the genomic data portion to generate genomic data for the genomic data portion; and for each co-registered tissue portion, associating the following items with each other as co-registered imaging and genomic data elements: (i) a multi-path to super-path image of the imaging data portion of the co-registered tissue portion, (ii) image data of the imaging data portion of the co-registered tissue portion, and (iii) genomic data of the genomic data portion of the co-registered tissue portion.

[0014] In yet another embodiment, a non-transitory computer-readable medium storing a plurality of spatially co-registered data elements is provided. Each spatially co-registered data element is associated with and generated from a pair of co-registered tissue portions, the pair of co-registered tissue portions being obtained from adjacent locations of a core taken from a tissue sample and including an image data portion and a genomic data portion, each spatially co-registered data element comprising: (i) a plurality of multiplexed to super-images obtained from the imaging data portion of the associated pair of co-registered tissue portions, (ii) image data generated from the plurality of multiplexed to super-images obtained from the imaging data portion of the associated pair of co-registered tissue portions, and (iii) genomic data generated from the genomic data portion of the associated pair of co-registered tissue portions.

[0015] In another embodiment, a method for generating a plurality of spatially co-registered data elements is provided, each spatially co-registered data element being associated with and generated from a pair of co-registered tissue portions obtained from adjacent locations of a core taken from a tissue sample and comprising an image data portion and a genomic data portion. The method comprises, for each pair of co-registered tissue portions, (i) obtaining a plurality of multiplexed to super-images from the imaging data portions of the co-registered tissue portions and storing them as a portion of the data element, (ii) generating image data from the plurality of multiplexed to super-images and storing them as a portion of the data element, and (iii) generating genomic data from the genomic data portions of the associated co-registered tissue portions and storing them as a portion of the data element.

[0016] In yet another embodiment, a system for generating and storing spatially co-registered data elements is provided. The spatially co-registered data elements are associated with and generated from a pair of co-registered tissue portions obtained from adjacent locations of a core taken from a tissue sample, the pair of co-registered tissue portions comprising an image data portion and a genomic data portion. The system includes a processing device, which includes: (i) an image data generation component, which is constructed and configured to generate image data from multiple multi-channel to super-channel images, which are obtained from the imaging data portion of an associated pair of co-registered tissue portions; (ii) a region of interest identification component, which is constructed and configured to identify multiple regions of interest in the genomic data portion of the associated pair of co-registered tissue portions based on the generated image data, wherein the genomic data is generated from the genomic data portion of the associated co-registered tissue portions based on the identified multiple regions of interest; and (iii) a data element generation component, which is constructed and configured to generate and store spatially co-registered data elements, which spatially co-registered data elements include the multiple multi-channel to super-channel images, the generated image data and the generated genomic data. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 is a flow chart illustrating a sample preparation method according to an exemplary embodiment of an aspect of the disclosed concept;

[0018] Figure 2 It is a graphic Figure 1 Schematic diagram of the sample preparation method shown in;

[0019] Figure 3 is a flow chart illustrating a method for generating SCORGI data elements from co-registered and co-localized pairs of an imaging data portion and a genomic data portion according to an exemplary embodiment of another aspect of the disclosed concept;

[0020] Figure 4 Is a diagram used to generate Figure 3 Schematic diagram of the approach to SCORGI data elements;

[0021] Figure 5 is a schematic diagram of an exemplary digital pathology system according to one specific, non-limiting exemplary embodiment of the disclosed concepts:

[0022] Figure 6 is a schematic diagram illustrating the generation of a tumor atlas in accordance with one non-limiting aspect of the disclosed concept. DETAILED DESCRIPTION

[0023] As used herein, the singular forms "a," "an," and "the" include plural forms unless the context clearly indicates otherwise.

[0024] As used herein, the statement that two or more parts or components are "coupled" shall mean that, so long as a link occurs, the parts are joined or operate together, either directly or indirectly (ie, through one or more intermediate parts or components).

[0025] As used herein, "directly coupled" means that two elements are directly in contact with each other.

[0026] As used herein, the term "number" shall mean one or an integer greater than one (ie, a plurality).

[0027] As used herein, the terms "component" and "system" are intended to refer to a computer-related entity, either hardware, a combination of hardware and software, software, or software in execution. For example, a component can be, but is not limited to, a process running on a processor, a processor, an object, an executable program, an execution thread, a program, and / or a computer. As an illustration, both an application running on a server and a server can be a component. One or more components can reside within a process and / or execution thread, and a component can be located on one computer and / or distributed between two or more computers. Although certain ways of displaying information to a user are shown and described as screen shots with respect to certain figures or graphs, those skilled in the relevant art will recognize that various other alternatives can be used.

[0028] As used herein, the term "multiplex imaging" shall refer to imaging techniques that employ up to seven biomarkers, and a "multiplex image" shall refer to an image created using multiplex imaging.

[0029] As used herein, the term "superconducting imaging" shall refer to imaging techniques that employ greater than seven biomarkers, and a "superconducting image" shall refer to an image created using superconducting imaging.

[0030] As used herein, the term "multiplex to superplex imaging" shall include multiplex imaging and / or superplex imaging, and "multiplex to superplex image" shall include multiplex image and / or superplex image.

[0031] Directional phrases used herein, such as, for example, but not limited to, top, bottom, left, right, upper, lower, front, back and their derivatives, relate to the orientation of elements shown in the drawings, and are not limited to the stated orientation unless explicitly stated therein.

[0032] For the purpose of explanation, the disclosed concepts will now be described in conjunction with numerous specific details in order to provide a thorough understanding of the present invention. However, it will be apparent that the disclosed concepts can be practiced without these specific details without departing from the spirit and scope of the present invention.

[0033] On the one hand, the disclosed concepts provide a new tumor sampling strategy for characterizing spatial heterogeneity in solid tumors based on what the inventors call "SCORGI". As described in more detail herein, SCORGI is a spatially co-registered genomic and imaging data element generated from spatially co-registered adjacent tissue samples obtained from, for example, but not limited to, matched primary tumors, regional lymph nodes, and distant metastases. SCORGI integrates region-specific genomic information (such as, but not limited to, whole exome sequencing obtained via next-generation sequencing methods, in situ transcriptomics, epigenomics, etc.) and imaging information obtained from a large number of individual sample cores distributed within such tissue samples (for example, but not limited to, obtained via a large number of fluorescently labeled antibody biomarkers). The unprecedented SCORGI-based tumor sampling strategy of the disclosed concept enables digital fingerprinting of microdomains representing spatial, functional and genomic intratumor heterogeneity (ITH) among malignant cells, non-malignant cells (e.g., but not limited to immune cells, cancer-associated fibroblasts (CAFs) and endothelial cells) and their local interactions within the tumor microenvironment (TME), which is considered a key determinant of metastatic disease progression. In addition, digital fingerprinting of microdomains based on SCORGI according to the disclosed concept will enable identification and characterization of pathogenic signaling networks within the TME, potentially leading to improved therapeutic strategies.

[0034] Figure 1 is a flow chart, and Figure 2 is a schematic diagram illustrating a sample preparation method according to an exemplary embodiment of an aspect of the disclosed concept. As described herein, Figure 1 and Figure 2 The sample preparation method shown in provides a plurality of tissue samples, which can then be used to generate SCORGI data elements as described herein.

[0035] refer to Figure 1 and Figure 2 , the method starts from step 5, where the Figure 2 The solid tumor sample 2 shown in FIG. In a non-limiting exemplary embodiment, the tumor sample 2 is approximately 1.5 cm 2 Also in step 5, the solid tumor sample 2 is cut into six individual tumor slices 4. Figure 2 In the exemplary embodiment, the tumor sections 4a-4f are processed into formalin-fixed paraffin-embedded (FFPE) sections. Next, at step 10, seven individual core samples or "cores" are obtained from the distribution areas in each tumor section 4a-4f. Figure 2Each of the cores 6 is labeled 6. In a non-limiting exemplary embodiment, each core 6 is a large-pore 5 mm core. Therefore, after step 10, a total of forty-two cores 6 will be obtained from the tumor slices 4a-4f.

[0036] Next, at step 15, forty-two cores 6 are used to create three macrowell tissue microarray (TMA) cassettes 8, Figure 2 One of them is shown in FIG. Figure 2 As shown in , each TMA box 8 will include seven cores 6 from corresponding two tissue tumor sections 4a-4f (e.g., the first TMA box 8 may include cores 6 obtained from tumor sections 4a and 4b, the second TMA box 8 may include cores 6 obtained from tumor sections 4c and 4d, and the third TMA box 8 may include cores 6 obtained from tumor sections 4e and 4f).

[0037] The method then proceeds to step 20, where in this non-limiting exemplary embodiment, each TMA cassette 8 is used to create three pairs of TMA slides (for a total of nine pairs of TMA slides) containing multiple pairs of co-registered and co-located portions from the core 6. More specifically, Figure 2 As shown in , in a non-limiting exemplary embodiment, three imaging data portions 12 and three genomic data portions 14 are obtained from each core 6 in each TMA box 8. In a non-limiting exemplary embodiment, each imaging data portion 12 is a 5 μm thick, 5 mm diameter tissue portion, and each genomic data portion 14 is a 10-20 μm thick, 5 mm diameter tissue portion (the genomic data portions 14 are thicker than the imaging data portions 12 in the exemplary embodiment because typically more tissue is required to perform genomic analysis on the genomic data portions 14 than to perform imaging on the imaging data portions 12, as described herein). Figure 2 As shown in , three imaging data portions 12 and three genomic data portions 14 are obtained from each core 6 in an alternating manner such that each imaging data portion 12 will be directly adjacent to a genomic data portion 14, so that they form a continuous / series pair of adjacent tissue portions (i.e., SCORGI tissue portions) that can be used to create multiple SCORGI data elements as described herein. Therefore, in the current non-limiting exemplary embodiment, a total of forty-two imaging data portions 12 and a total of forty-two genomic data portions 14 are obtained from the fourteen cores 6 provided on each TMA box 8. Therefore, for the three TMA boxes 8 of the exemplary embodiment, a total of one hundred and twenty-six imaging data portions 12 and a total of one hundred and twenty-six genomic data portions 14 are obtained.

[0038] In addition, if Figure 2As shown in , for each TMA box 8, the obtained imaging data portion 12 is sequentially positioned on three imaging data TMA slides 16a, 16b, 16c, and the obtained genomic data portion 14 is sequentially positioned on three genomic data TMA slides 18a, 18b, 18c. Therefore, the above-mentioned three pairs of TMA slides are formed for each TMA box 8, wherein the first pair includes the imaging data TMA slide 16a and the genomic data TMA slide 18a, the second pair includes the imaging data TMA slide 16b and the TMA carrier 18b, and the third pair includes the imaging data TMA carrier 16c and the genomic data TMA slide 18c. In addition, as will be appreciated, for each TMA box 8, each pair of TMA slides will include fourteen pairs of co-registered imaging data portions 12 and genomic data portions 14, wherein the imaging data portion 12 is provided on the TMA slide 16 and the corresponding genomic data portion 14 is provided at a corresponding position on the TMA slide 18. Thus, at the completion of step 20, a total of nine pairs of TMA slides (nine TMA slides 16 and nine TMA slides 18) will be formed by the three TA cassettes 8 of the present embodiment, resulting in a total of one hundred and twenty-six pairs of co-registered and co-located imaging data portions 12 and genomic data portions 14 (i.e., one hundred and twenty-six SCORGI tissue portions). As described above, those co-registered and co-located pairs of imaging data portions 12 and genomic data portions 14 can be used to create a plurality of data elements referred to as SCORGI as described herein.

[0039] It should be noted that the exemplary numbers of various items described above, such as the number of tumor slices 4 (e.g., six), the number of cores 6 from each tumor slice 4 (e.g., seven), and the number of imaging data portions 12 and genomic data portions 14 from each core 6 (e.g., three), diameters, and / or thicknesses are merely exemplary, and other numbers of such items are contemplated within the scope of the disclosed concepts. For example, but not limited to, the size of the cores used for multiplexed to ultrasonography as described herein can be greater than 5 mm. Specifically, tumors are typically centimeters across (e.g., 1-5 cm), and within the scope of the disclosed concepts, an entire tumor can be sliced ​​to create sections of 1-5 cm diameter. In such an implementation, a whole slide image (WSI) of these sections can be made, and multiplexed to ultrasonography of the WSI can be performed.

[0040] Figure 3 is a flow chart, and Figure 4is a schematic diagram illustrating a method for generating SCORGI data elements from co-registered and co-localized pairs of imaging data portions 12 and genomic data portions 14 (referred to herein as SCORGI tissue portions) according to an exemplary embodiment of another aspect of the disclosed concept. In particular, as described in more detail below, SCORGI is generated by performing multiplexed to superpath imaging and region-specific genomics on each of the co-registered and co-localized pairs of imaging data portions 12 and genomic data portions 14, respectively.

[0041] refer to Figure 3 and Figure 4 The method begins at step 25, where for each imaging data portion 12 in the TMA slides 16a, 16b, and 16c, a plurality of high-resolution multiplexed to super-images 26 are generated from the imaging data portion 12 using a multiplexed to super-image processing 28, which in the exemplary embodiment includes repeatedly labeling each imaging data portion 12 with a plurality of fluorescent labels to image a plurality of biomarkers. In the exemplary embodiment shown, Figure 4 As shown in , each imaging data portion 12 is divided into sixty image fields 31, fifty different fluorescent labels are applied to the imaging data portions 12, and an image 26 is captured (e.g., at 20x) for each fluorescent label for each image field 28. Thus, in this exemplary embodiment, a total of 3,000 multiplexed to super-multiplexed images 26 will be captured for each imaging data portion 12. It will be appreciated that the number and selection of biomarkers used in step 25 may vary and may depend on the mechanism of tumor progression of interest.

[0042] Next, at step 30, for each imaging data portion 12 in the TMA slides 16a, 16b, and 16c, the generated multi-path to superpath image 26 is analyzed to obtain the following: Figure 4 32. In particular, the fluorescence multiplexed to super-path image 26 of each field 31 contains the intensity distribution of each biomarker. Therefore, in an exemplary embodiment, the multiplexed to super-path image 26 is processed to extract image data 32, which includes quantification of the information extracted from the multiplexed to super-path image 26. Such image data 32 may include, but is not limited to, quantitative information such as subcellular biomarker intensity and localization of each multiplexed to super-path image 26 in each cell, morphology such as the size and shape of a cell or subcellular region, and / or intensity distribution in a cell or subcellular region that can be characterized by a statistical measure or a texture measure.

[0043] In an exemplary embodiment, the multiplexed images 26 and image data 32 just described may be generated using a standard multiplexed machine, such as the PerkinElmer Vectra Polaris automated quantitative pathology system (http: / / www.perkinelmer.com / product / vectra-polaris-top-level-assembly-ship-cls143455) (in which case the standard multiplexed machine typically includes software for generating the image data 32). Alternatively, the standard multiplexed machine just described may be used to generate the multiplexed images 26, and the image data 32 may be generated therefrom using separate image analysis software, such as, but not limited to, the public domain THRIVE (Tumor Heterogeneity Research Interactive Visualization Environment) software described in Spagnolo et al., Platform for Quantitative Evaluation of Spatial Intratumoral Heterogeneity in Multiplexed Fluorescence Images, Cancer Res. 2017 Nov 1; 77(21): e71-e74. The THRIVE software is an open source tool for assisting cancer researchers in conducting interactive hypothesis testing. THRIVE provides integrated workflows for multiplexed to ultra-multiplexed analysis of whole slide immunofluorescence images and tissue microarrays, including standard cellular and subcellular segmentation and biomarker quantification. THRIVE quantifies spatial intra-tumor heterogeneity and the interactions between different cellular phenotypes and non-cellular components. THRIVE is able to decipher the various molecular and cellular signaling networks that support the mutual co-evolution of malignant cells and their specific TME (e.g., cancer-associated fibroblasts, immune cells, extracellular matrix) to confer malignant phenotypes, leading to, for example, dormancy, drug resistance, immune escape, and metastatic potential.

[0044] As yet another alternative, the ultrasonography images 26 and image data 32 may be generated from the TMA slides 16a, 16b, and 16c as just described by sending the TMA slides 16a, 16b, and 16c to an ultrasonography Clinical Laboratory Improvement Amendments (CLIA) laboratory, such as the NeoGenomics MxIF: Multi-Molecular Multiplex Methods Laboratory (https: / / neogenomics.com / pharma-services / lab-services / inultiomyx).

[0045] After step 30, the method proceeds to step 35, where, for each imaging data portion 12 in the TMA slides 16a, 16b and 16c, the acquired image data 32 is used to identify multiple regions of interest ("ROIs", also called "micro-domains") in the genomic data portion 14 (contained in one TMA slide 18a, 18b and 18c) that are co-registered with the imaging data portion 12. The acquired image data 32 may be used to identify ROIs according to any of a number of known or later developed methods, such as, but not limited to, methods described in detail in U.S. Provisional Application Serial No. 62 / 675,832, filed May 24, 2018, entitled “Predicting the Recurrence Risk of Cancer Patients From Primary Tumors with Multiplexed Immunofluorescence Biomarkers and Their Spatial Correlation Statistics,” which is incorporated herein by reference; PCT Application No. PCT / US19 / 033662, filed May 23, 2019, entitled “Predicting the Recurrence Risk of Cancer Patients From Primary Tumors with Multiplexed Immunofluorescence Biomarkers and Their Spatial Correlation Statistics,” which is incorporated herein by reference; and in Spagnolo et al., Platform for Quantitative Evaluation of Spatial Intratumoral Heterogeneity in Multiplexed Fluorescence Biomarkers. Images, Cancer Res. 2017 Nov 1; 77(21): e71-e74. In this method, spatially resolved correlations between biomarkers are used as covariates in a multivariate survival model of outcome data (e.g., recurrence) to construct spatially organized maps of cancer recurrence in superpathway tissue samples. These maps depict microdomains associated with recurrence and metastatic progression. In addition, it is expected that performing region-specific genomics on phenotypically distinct microdomains of SCORGI data elements as described herein will reveal enriched malignant cell subclonal populations that are themselves enriched for metastases.The integration of genomic and imaging information in SCORGI as described herein enables modeling of phenotypic and genotypic progression and the development of predictive biomarkers mechanistically related to metastatic progression.

[0046] Reference again Figure 4 , showing an exemplary genomic data portion 14 and two exemplary ROIs 34 ("Region 1" and "Region 2"). At step 40, for each genomic data portion 14 in the TMA slides 18a, 18b, and 18c, a genomic analysis identified by reference numeral 36 is performed on each identified ROI 34 in the genomic data portion 14. As a result of the genomic analysis 36 and based on the genomic analysis 36, genomic data 38 for each identified ROI 34 will be generated for each genomic data portion 14. For example, but not limited to, the genomic analysis performed in step 40 can be whole exome sequencing obtained via next-generation sequencing methods, in situ transcriptomics, epigenomics, etc., and the generated genomic data 38 can include, but are not limited to, data indicating mutations and / or data indicating in situ transcriptomics (FISSEQ, DSP).

[0047] Step 40 just described can be performed by any suitable method and / or device. For example, DNA can be extracted from ROI 34 using a microfluidic dissection method and a unit compatible with a standard optical microscope to quickly extract nucleic acids from a small (1-5 mm) ROI of a standard FFPE tissue section developed by Neuroindx (http: / / www.neuroindx.com / ). In this method, the position of the ROI is transferred to a microfluidic dissection unit, and the microfluidic gasket is tightly positioned above the corresponding ROI. The tissue digestion buffer is then automatically pumped onto the tissue and circulated within the ROI gasket. Once digested, the liquefied tissue sample (i.e., the extracted ROI) is pumped back into the storage tank and then transferred to a test tube. Thereafter, DNA can be extracted from the tissue digestion solution and quantified using standard Qiagen and Invitrogen reagents and protocols. For genomic analysis, next generation sSequencing, such as whole exome sequencing (WES), can be performed by an external sequencing service provider (such as, Roswell Park Cancer Institute, Buffalo, NY's RPCI genome shared resource). For example, WES can be performed using SureSelectHuman All Exon V6 plus COSMIC r2 (design ID S07604715, ˜64 Mbp) as the Agilent target. Raw reads received from such sequencing can be further analyzed using pipelines assembled from publicly available software packages and / or custom software scripts.

[0048] In an exemplary embodiment, after step 40, the multiplexed-to-superimage 26, image data 32, and genomic data 38 for each co-registered imaging data portion 12 and genomic data portion 14 (i.e., each SCORGI tissue portion) are stored in association with one another (in a suitable computer-readable storage medium, such as the storage medium described herein) as a SCORGI data element. In the non-limiting exemplary embodiment described herein, one hundred and twenty-six SCORGI data elements are created and stored.

[0049] As noted elsewhere herein, in one particular embodiment, the disclosed concepts may be implemented as part of a digital pathology system in a manner in which image data 32 is generated from multiplexed to super-channel images 26, and ROIs in the genomic data portion 14 are identified using the acquired image data 32 using a software tool, such as but not limited to the THRIVE software described herein, which is local or otherwise accessible to a local computing device forming part of the digital pathology system. Additionally, as also noted elsewhere herein, in such an embodiment, certain genomic data 38 may also be generated from raw sequencing data using software tools local to or otherwise accessible by the same computing device. Figure 5 is a schematic diagram of such an exemplary system 42 according to one specific non-limiting exemplary embodiment. Figure 5 As shown in FIG. 4 , system 42 includes a computing device, which may be, for example, but not limited to, a PC, a laptop computer, a tablet computer, or any other suitable device configured to perform the functions described herein. System 42 may be located, for example, but not limited to, a computer that performs the following operations: Figure 1 and Figure 2 4 and in the same laboratory where sampling is described herein. System 42 includes an input device 44 (such as a keyboard and / or touch pad), a display 46 (such as an LCD), and a processing device 48. A user can use input device 44 to provide input to processing device 48, and processing device 48 provides output signals to display 46 to enable display 46 to display information (e.g., information related to SCORGI) to the user, as described in detail herein.

[0050] The processing device 48 of the system 42 includes a processor and a memory. The processor can be, for example, but not limited to, a microprocessor (μP), a microcontroller, an application-specific integrated circuit (ASIC), or some other suitable processing device that interfaces with a memory. The memory can be any one or more of various types of internal and / or external storage media, such as but not limited to RAM, ROM, (one or more) EPROM, (one or more) EEPROM, FLASH, etc., which provide storage registers, that is, non-volatile computer-readable media, for data storage such as in the form of an internal storage area of ​​a computer, and can be a volatile memory or a non-volatile memory. The memory has stored therein a plurality of routines that can be executed by the processor, including routines for implementing various aspects of the disclosed concepts as described herein. In particular, in Figure 5 In the illustrated embodiment shown in , the processing device 48 is constructed to receive and store the multiplexed to super-path image 26 as described elsewhere herein. The processing device 48 also includes an image data generation component 50, which is constructed and configured to generate image data 32 (i.e., quantification) as described elsewhere herein from the received and stored multiplexed to super-path image 26. The generated image data 32 is then stored by the processing device 48. As described above, the image data generation component 50 may include the THRIVE software described elsewhere herein. In addition, the processing device also includes a ROI identification component 52, which is constructed and configured to use the image data 32 obtained as described elsewhere herein to identify the ROI in the genomic data portion 14. The identified ROI can then be used to generate the genomic data 38 as described herein, which is then stored by the processing device 48. As also described above, the ROI identification component 52 can similarly include the THRIVE software described elsewhere herein.

[0051] In addition, if Figure 5 As shown in FIG. 4 , the processing device 48 of the present embodiment further includes a SCORGI generation component 54. The SCORGI generation component 54 is constructed and configured to generate and store SCORGI data elements as described herein based on the stored multi-way to super-way images 26, image data 32, and genome data 38.

[0052] In addition, Figure 5 As shown in FIG. 4 , according to another aspect of the present embodiment, the processing device 48 further includes a tumor atlas component 56. According to one non-limiting aspect of the disclosed concept, the tumor atlas component 56 is constructed and configured to generate and display on the display 46 as shown in FIG. Figure 6The tumor atlas 57 shown in FIG. The tumor atlas 57 is a three-dimensional (3D) diagram that can display spatial ITH through a plurality of SCORGI icons 58. Specifically, each SCORGI icon 58 represents and corresponds to a SCORGI data element generated by the SCORGI generation component 54 from one or more specific tissue samples as described herein. Figure 6 As shown in FIG. 4 , each SCORGI icon 58 is positioned at a specific location in the x, y, z coordinate system of the tumor atlas 57. The specific location corresponds to and is based on the location of a specific tissue portion within the original tissue sample that was used to generate the SCORGI data element corresponding to the SCORGI icon 58. In addition, the tumor atlas component 56 is constructed and configured to generate the tumor atlas 57 so that certain images and / or information can be selectively displayed on the display 46 when a user selects a specific one of the SCORGI icons 58 using the input device 44. For example, but not limited to, Figure 6 As shown in , the displayed information may include one or more of: (i) an image of the imaging data portion 12, (ii) an image of the genomic data portion 14, and (iii) a selected multi-path to superpath image 26, (iv) a selected portion of the image data 32, and (v) a selected portion of the region-specific genomic data 38.

[0053] The tumor atlas 57 just described is only one application of the disclosed concepts for SCORGI-based sampling. Other applications can include using scRNAseq as a region-specific genomics process in SCORGI generation to establish phylogenetic relationships between microdomains and generate pseudo-time tumor evolution trajectories within a given biological sample and in longitudinally collected samples (e.g., regional lymph nodes and distant metastases) from the same patient.

[0054] In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The words "comprise" or "comprising" do not exclude the presence of elements or steps other than those listed in the claim. In a device claim enumerating several components, several of these components may be implemented by one and the same hardware. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. In any device claim enumerating several components, several of these components may be implemented by one and the same hardware. The fact that certain elements are recited in mutually different dependent claims does not indicate that these elements cannot be used in combination.

[0055] Although the present invention has been described in detail for illustrative purposes based on what are currently considered to be the most practical and preferred embodiments, it should be understood that such details are only for this purpose and that the present invention is not limited to the disclosed embodiments, but on the contrary, the present invention is intended to cover modifications and equivalent arrangements within the spirit and scope of the appended claims. For example, it should be understood that the present invention contemplates that, where possible, one or more features of any embodiment can be combined with one or more features of any other embodiment.

Claims

1. A method to create multiple tissue sections for imaging and genomic analysis, include: Obtain cores from tissue samples; obtaining a plurality of imaging data portions and a plurality of genomic data portions from the core in an alternating manner along the length of the core such that each imaging data portion is associated with a respective one of the genomic data portions to form a plurality of serial pairs of adjacent tissue portions, wherein for each serial pair of tissue portions, the imaging data portions and the genomic data portions are obtained from immediately adjacent portions of the core along the length of the core; Each imaging data portion from the core is fixed to a first tissue microarray TMA slide, and each genomic data portion from the core is fixed to a second tissue microarray TMA slide, wherein for each series pair of tissue portions, the imaging data portion of the series pair is fixed to a specific position on the first TMA slide, and the genomic data portion of the series pair is fixed to a specific position on the second TMA slide that corresponds to and matches the specific position on the first TMA slide where the imaging data portion of the series pair is fixed.

2. The method of claim 1, wherein each imaging data portion has a first thickness and each genomic data portion has a second thickness greater than the first thickness. 3 . The method according to claim 2 , wherein the first thickness is 5 μm and the second thickness is 10-20 μm.

4. The method of claim 1, wherein the diameter of each imaging data portion and each genomic data portion is 5 mm.

5. The method of claim 1, wherein the tissue sample is a tumor, a regional lymph node, or a distant metastasis sample.

6. A tissue microarray (TMA) slide comprising a plurality of tissue sections for imaging and genomic analysis, include: a first TMA slide having a plurality of imaging data portions taken from a core of a tissue sample fixed thereon; as well as a second TMA slide having immobilized thereon a plurality of genomic data portions from each of a plurality of cores of the tissue sample; wherein the plurality of imaging data portions and the plurality of genomic data portions are from alternating portions along the length of the core such that each imaging data portion is associated with a corresponding one of the genomic data portions of the core to form a plurality of series pairs of adjacent tissue portions, wherein for each series pair of tissue portions, imaging data portions and genomic data portions are obtained from immediately adjacent portions of the core along the length of the core, and wherein for each series pair of tissue portions, the imaging data portions of the series pair are fixed at specific locations on a first TMA slide, and the genomic data portions of the series pair are fixed at specific locations on a second TMA slide that correspond to and match specific locations on the first TMA slide where the imaging data portions of the series pair are fixed.

7. A plurality of tissue microarray (TMA) slides according to claim 6, wherein each imaging data portion has a first thickness and each genomic data portion has a second thickness greater than the first thickness.

8. The plurality of tissue microarray (TMA) slides according to claim 7, wherein the first thickness is 5 μm and the second thickness is 10-20 μm.

9. The plurality of tissue microarray (TMA) slides according to claim 6, wherein each imaging data portion and each genomic data portion has a diameter of 5 mm.

10. The plurality of tissue microarray (TMA) slides according to claim 6, wherein the tissue samples are tumor, regional lymph node or distant metastasis samples.

11. A method for generating a plurality of spatially co-registered data elements from a tissue sample, include: Obtain cores from tissue samples; obtaining a plurality of imaging data portions and a plurality of genomic data portions from the core in an alternating manner along the length of the core such that each imaging data portion is associated with a respective one of the genomic data portions to form a plurality of serial pairs of adjacent, co-registered tissue portions, wherein for each serial pair of co-registered tissue portions, the imaging data portions and the genomic data portions are obtained from immediately adjacent portions of the core along the length of the core; affixing each imaging data portion from the core to a first tissue microarray (TMA) slide, and affixing each genomic data portion from the core to a second tissue microarray (TMA) slide, wherein for each serial pair of co-registered tissue portions, the imaging data portion of the serial pair is affixed to a specific location on the first TMA slide, and the genomic data portion of the serial pair is affixed to a specific location on the second TMA slide that corresponds to and matches the specific location on the first TMA slide where the imaging data portion of the serial pair was affixed; For each imaging data portion: (i) obtaining a plurality of multiplexed-to-supergram images from the imaging data portion by repeated labeling with a plurality of fluorescent tags, (ii) analyzing the multiplexed-to-supergram images to obtain image data therefrom, and (iii) identifying a plurality of regions of interest in a genomic data portion associated with the imaging data portion based on the image data obtained for the imaging data portion; For each genomic data portion, performing genomic analysis on each region of interest in the genomic data portion to generate genomic data for the genomic data portion; as well as For each serial pair of co-registered tissue portions, associating the following with each other as co-registered imaging and genomic data elements: (i) a multiplexed to super-segment image of the imaging data portion of the serial pair of co-registered tissue portions, (ii) image data of the imaging data portion of the serial pair of co-registered tissue portions; and (iii) genomic data of the co-registered serial pairs of tissue portions.

12. The method of claim 11, further comprising storing the co-registered data imaging and genomic elements of each co-registered tissue portion in a non-transitory computer readable medium.

13. The method according to claim 11, further comprising: include: A map is generated and displayed on a display of a computer system including a plurality of co-registered data element icons, each co-registered data element icon being associated with and based on a corresponding one of the co-registered imaging and genomic data elements.

14. The method according to claim 13, further comprising: include: In response to selection of a particular one of the co-registered data element icons, one or more of a plurality of multiplexed to super-path images, at least a portion of the image data, and at least a portion of the genomic data of the co-registered imaging and genomic data elements associated with the particular one of the co-registered data element icons are displayed on a display.

15. The method of claim 11, wherein for each imaging data portion, the imaging data portion is divided into a plurality of fields, and obtaining the plurality of multiplexed to super-pass images by repeatedly labeling with the plurality of fluorescent tags comprises obtaining a plurality of images for each field.

16. A non-transitory computer readable medium storing a plurality of spatially co-registered data elements generated by the method of claim 11.

17. A method for generating a plurality of spatially co-registered data elements from a tissue sample, the method comprising: include: Obtain cores from tissue samples; obtaining a plurality of imaging data portions and a plurality of genomic data portions from the core in an alternating manner along the length of the core such that each imaging data portion is associated with a respective one of the genomic data portions to form a plurality of serial pairs of adjacent, co-registered tissue portions, wherein for each serial pair of co-registered tissue portions, the imaging data portions and the genomic data portions are obtained from immediately adjacent portions of the core along the length of the core; affixing each imaging data portion from the core to a first tissue microarray (TMA) slide, and affixing each genomic data portion from the core to a second tissue microarray (TMA) slide, wherein for each serial pair of co-registered tissue portions, the imaging data portion of the serial pair is affixed to a specific location on the first TMA slide, and the genomic data portion of the serial pair is affixed to a specific location on the second TMA slide that corresponds to and matches the specific location on the first TMA slide where the imaging data portion of the serial pair was affixed; For each series pair of co-registered tissue portions: (i) obtaining a plurality of multiplex-to-super-path images from the imaging data portion obtained from the series pair of co-registered tissue portions and storing them as part of the data element, (ii) generating image data obtained from the plurality of multiplex-to-super-path images and storing them as part of the data element; and (iii) generating and storing as part of the data element genomic data obtained from the genomic data portions of the series pairs of co-registered tissue portions.

18. A method according to claim 17, wherein for each pair of co-registered tissue portions, genomic data is generated from a plurality of regions of interest in the genomic data portion of the associated pair of co-registered tissue portions, wherein the plurality of regions of interest are identified based on image data generated from the plurality of multiplexed to super-path images, wherein the plurality of multiplexed to super-path images are obtained from the imaging data portion of the associated pair of co-registered tissue portions.

19. The method of claim 17, wherein each imaging data portion and each genomic data portion has a diameter of 1 cm to 5 cm.

20. A non-transitory computer readable medium storing a plurality of spatially co-registered data elements generated by the method of claim 17.

21. A non-transitory computer-readable medium according to claim 20, wherein in each spatially co-registered data element, genomic data is generated from multiple regions of interest in the genomic data portion of an associated pair of co-registered tissue portions, and the multiple regions of interest are identified based on image data generated from multiple multi-channel to super-channel images, and the multiple multi-channel to super-channel images are obtained from the imaging data portion of the associated pair of co-registered tissue portions.

22. A system for generating and storing a plurality of spatially co-registered data elements from a plurality of imaging data portions and a plurality of genomic data portions, the plurality of imaging data portions and the plurality of genomic data portions being obtained from the core of a tissue sample in an alternating manner along the length of the core such that each imaging data portion is associated with a respective one of the genomic data portions to form a plurality of series pairs of adjacent, co-registered tissue portions, wherein for each series pair of co-registered tissue portions, the imaging data portions and the genomic data portions are obtained from immediately adjacent portions of the core along the length of the core, wherein each imaging data portion from the core is affixed to a first tissue microarray (TMA) slide, and each genomic data portion from the core is affixed to a second tissue microarray (TMA) slide, wherein for each series pair of co-registered tissue portions, the imaging data portions of the series pair are affixed to a specific location on the first TMA slide, and the genomic data portions of the series pair are affixed to a specific location on the second TMA slide that corresponds to and matches the specific location on the first TMA slide where the imaging data portions of the series pair are affixed, the system comprising a processing device, the processing device include: an image data generation component constructed and arranged to generate, for each series pair of co-registered tissue portions, image data from a plurality of multiplexed to super-channel images obtained from imaging data portions of the series pair of co-registered tissue portions; a region of interest identification component constructed and configured to, for each series pair of co-registered tissue portions, identify a plurality of regions of interest in a genomic data portion of the series pair of co-registered tissue portions based on the generated image data of the series pair of co-registered tissue portions, wherein, for each series pair of co-registered tissue portions, genomic data is generated from the genomic data portion of the series pair of co-registered tissue portions based on the identified plurality of regions of interest; as well as A data element generation component is constructed and configured to generate and store spatially co-registered data elements of the multiple spatially co-registered data elements for each series pair of co-registered tissue portions, the stored spatially co-registered data elements including the multiple multiplexed to super-channel images, the generated image data and the generated genomic data of the series pair of co-registered tissue portions.

23. According to the system of claim 22, the processing device also includes a map generation component, which is constructed and configured to generate a map including a plurality of co-registered data element icons, wherein each co-registered data element icon is associated with and based on one of the spatially co-registered data elements generated by the data element generation component.

24. A system according to claim 23, wherein the processing device is constructed and configured to: in response to selection of one of the co-registered data element icons, display one or more of a multiplexed to super-path image of the spatially co-registered data elements, at least a portion of the generated image data of the spatially co-registered data elements, and at least a portion of the generated genomic data of the spatially co-registered data elements.

Images