Co-localization Of Biomarkers Research Articles

Rapid Assessment of Biomarkers on Single Extracellular Vesicles Using "Catch and Display" on Ultrathin Nanoporous Silicon Nitride Membranes.

Extracellular vesicles (EVs) are particles released from cells that facilitate intercellular communication and have tremendous diagnostic and therapeutic potential. Bulk assays lack the sensitivity to detect rare EV subsets relevant to disease, and while single EV analysis techniques remedy this, they are often undermined by complicated detection schemes and prohibitive instrumentation. To address these issues, a microfluidic technique for EV characterization called "catch and display for liquid biopsy (CAD-LB)" is proposed. In this method, minimally processed samples are pipette-injected and fluorescently labeled EVs are captured in the nanopores of an ultrathin membrane. This enables the rapid assessment of EV number and biomarker colocalization by light microscopy. Here, nanoparticles are used to define the accuracy and dynamic range for counting and colocalization. The same assessments are then made for purified EVs and for unpurified EVs in plasma. Biomarker detection is validated using CD9 and Western blot analysis to confirm that CAD-LB accurately reports relative protein expression levels. Using unprocessed conditioned media,CAD-LB captures the known increase in EV-associated ICAM-1 following endothelial cell cytokine stimulation. Finally, to demonstrate CAD-LB's clinical potential, EV biomarkers indicative of immunotherapy responsiveness are successfully detected in the plasma of bladder cancer patients treated with immune checkpoint blockade.

Abstract 1066: Colocalization of ovarian cancer-associated biomarkers in tumors, cancer cells and extracellular vesicles

Abstract Introduction: We have previously shown that ovarian cancer can be detected with high specificity and sensitivity by interrogating colocalized membrane-associated cell-surface biomarkers on single tumor-associated extracellular vesicles (EVs). Our blood based Ovarian Cancer Test (OC Test) is composed of 5 cancer-associated biomarkers (BST-2, FOLR1, MUC-1, MUC-16, and sialylated Thomsen-nouveau antigen (sTn)) known to be overexpressed in ovarian cancer relative to healthy tissues. The test employs these 5 biomarkers in 3 combinations to capture and detect EVs from human plasma to distinguish high-grade serous ovarian carcinoma (HGSC) from both benign ovarian tumors and normal samples. Using super-resolution microscopy on ovarian cancer cell lines and EVs and multiplex immunohistochemistry of ovarian benign and tumor tissue, our study aimed to show that the 5 ovarian cancer biomarkers show 1) colocalization on ovarian cancer cells, 2) colocalization on the surface of EVs, and 3) colocalization on cancer cells within ovarian tumor biopsies. Methods: Super-resolution microscopy was employed to visualize stained biomarkers on the cell surface of a collection of ovarian cancer cell lines as well as on the surface of extracellular vesicles released by these cell lines. 58 HGSC (17 Stage I, 30 Stage II, and 10 Stage III) and 17 benign ovarian tumor K2EDTA plasma samples and paired FFPE tissue were sourced from the Ovarian Cancer Research Program (OVCARE, Vancouver BC, Canada). A tumor microarray from identical tissue samples was stained with an Opal multiplex-IHC (mIHC) assay comprised of antibodies to BST2, MUC1, sTn, and pan-cytokeratin and a DAPI counterstain. Machine learning based image analysis was utilized to determine colocalization of the biomarkers at the cellular level within benign and tumor tissue. RNA sequencing was carried out to assess expression levels of the biomarkers in each FFPE tissue sample. OC Tests were run on each plasma sample. Results: Super-resolution microscopy showed colocalization of OC Test combination biomarkers on ovarian cancer cells and EVs derived therefrom. Machine learning-based image analysis of tumor and benign tissue microarrays stained for BST2/MUC1/sTn using mIHC, showed strong evidence for colocalization of these biomarkers on single cells within ovarian tumor tissue, particularly in early-stage tumors, but not on benign tissue. RNA sequencing analysis showed good correlation of biomarker RNA expression levels and with the OC Test results. Conclusions: The results presented here demonstrate that the OC Test biomarkers are colocalized on tumor tissue, ovarian cancer cells, and EVs from ovarian cancer cell lines. RNA and protein expression levels show good correlation with OC Test results. These results provide further evidence that colocalized biomarkers on EVs can be utilized for early detection of cancer. Citation Format: Anthony D. Couvillon, Emily S. Winn-Deen, Shelby Thornton, Shuhong Liu, Michael DeRan, Maciej Pacula, Sanchari Banerjee, Daniel Gusenleitner, Laura T. Bortolin, Jonian Grosha, Timothy Santos-Heiman, Gabrielle Sangiuliano, Kelly M. Biette, Christopher R. Sedlak, Bilal Hamzeh, Delaney M. Byrne, Peter A. Duff, Julie Ho, Dongxia Gao, Amy Jamieson, Lauren T. Cuoco, MacKenzie S. King, Dawn R. Mattoon, Toumy Guettouche, Jessica N. McAlpine, David Huntsman. Colocalization of ovarian cancer-associated biomarkers in tumors, cancer cells and extracellular vesicles [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1066.

Imaging of Ancient Microbial Biomarkers within Miocene Dolomite (Kuwait) Using Time-of-Flight Secondary Ion Mass Spectrometry

Time-of-Flight–Secondary Ion Mass Spectrometry (ToF-SIMS) using a bismuth liquid metal ion source was utilized to characterize and image microbial biomarkers within dolomite from early-middle Miocene coastal mud volcano outcrops in Kuwait. ToF-SIMS analysis revealed biomarkers of ancient microbial consortia of sulfate reducers and methane oxidizers participating in the anaerobic oxidation of methane. The identified lipid biomarkers comprised 17α(H),21β(H)-Norhopane, Hop-17(21)-ene or Hop-22(29)-ene (diploptene), non-isoprenoidal dialkyl glycerol diethers (DAGEs), and Diacylglycerol esters (DGs). The ion µ-scale images of carbonate rocks showed two characteristic styles: (1) high signal intensity of dolomite, halite, and biomarkers, where the biomarkers demonstrate a distinctive co-localization pattern with both dolomite and halite; and (2) a lack of dolomite, halite low signal intensity, and an absence of biomarker co-localization patterns. Our results highlight three remarkable observations. Firstly, the concomitance of dolomite and halite suggests a common source of magnesium and sodium supply, likely from the hypersaline Al-Subiya sabkha. This emphasizes the importance of hypersaline seawater for dolomite formation. Secondly, microbial biomarkers correspond to methane- and sulfate-rich conditions under which dolomite was formed. Lastly, the high intensity of biomarker signals and their association with dolomite and halite indicate that the consortia involved in dolomite formation have preferences for high-salinity conditions. The three observations align with previous studies that have highlighted the importance of methane-sulfate redox, high salinity, and halophilic microbes for dolomite formation. This work is the first to acknowledge ancient microbial biomarkers within Miocene dolomite in Kuwait, which aims to broaden the understanding of the biogeochemical processes triggering dolomite formation in similar environments and ancient geologic settings.

MP14-05 EXTRACELLULAR VESICLE BIOMARKER SIGNATURE DETECTION PLATFORM FOR GUIDING CANCER DETECTION AND THERAPY

You have accessJournal of UrologyCME1 Apr 2023MP14-05 EXTRACELLULAR VESICLE BIOMARKER SIGNATURE DETECTION PLATFORM FOR GUIDING CANCER DETECTION AND THERAPY Thomas Osinski, Samuel Walker, Karen Doersch, Jonathan Flax, and James McGrath Thomas OsinskiThomas Osinski More articles by this author , Samuel WalkerSamuel Walker More articles by this author , Karen DoerschKaren Doersch More articles by this author , Jonathan FlaxJonathan Flax More articles by this author , and James McGrathJames McGrath More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003234.05AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Extracellular Vesicles (EVs) have tremendous potential in cancer diagnostics and personalized cancer therapeutics. They are abundant in all biofluids, carry molecular markers of their cell-of-origin and can be readily obtained via noninvasive techniques. Current EV biomarker assessments have several limitiations. Pooled EVs from samples have low detection sensitivity for less abundant biomarkers and preclude colocalization of biomarkers on individual EVs. Currently, expensive specialized devices requiring large biofluid inputs are needed for more detailed EV analysis. Here, we develop an easy to use and inexpensive device that permits optical detection of multiple markers on individual EVs using only 10 µl of serum. This work investigates whether the microfluidic strategy we call ‘catch and display for liquid biopsy [CAD-LB]’ can detect biomarkers on single EVs. We also sought to determine the dynamic range of accurate quantitation using purified EVs and serum and validate detection of immune checkpoint proteins (PD-L1 and/or PD-1), which may help to distinguish immune checkpoint immunotherapy (ICI) responders from non-responders in bladder cancer. METHODS: For this study EVs were derived from: 1. ultracentrifuge purified urinary EVs; 2. EVs from media of 5637 bladder cancer and primary bladder epithelium cell lines and; 3. Serum from patients with advanced urothelial carcinoma or healthy controls. EVs were labeled with the pan-EV marker carboxyfluorescein succinimidyl ester and fluorescently labeled primary antibodies. Small volumes (10 µL) of solutions were captured on our membrane with nanopores in a transparent membrane and imaged using fluorescence microscopy. Detection range was assessed by serial dilutions of EVs. EV surface antigen labeling was assessed by CAD-LB. RESULTS: 1. Counting curves demonstrate a wide dynamic range of CAD-LB (102 – 106 EVs) for purified EVs while serum plateaus at lower inputs (∼104 EVs). 2. CAD-LB detects PD-1 and PD-L1 biomarkers in urothelial carcinoma patients’ serum. 3. CAD-LB detects T cell biomarker CD3 on approximately 1-2% of EVs in healthy control serum. CONCLUSIONS: CAD-LB can detect rare and clinically significant EV associated biomarkers in conditioned medium and patient serum samples. Furthermore, CAD-LB provides single EV characterization with small sample volumes. These qualities make CAD-LB a potentially useful tool to help discover novel markers that could aid in diagnosis and treatment decisions for cancer patients. Source of Funding: None © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e183 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Thomas Osinski More articles by this author Samuel Walker More articles by this author Karen Doersch More articles by this author Jonathan Flax More articles by this author James McGrath More articles by this author Expand All Advertisement PDF downloadLoading ...

Abstract 3390: Preliminary results for a novel single extracellular vesicle assay for early stage ovarian cancer: The power of co-localized detection of surface biomarkers

Abstract Introduction: Ovarian cancer (OC) is one of the deadliest cancers, with 314,000 new cases and 207,000 deaths globally in 2020. Serum CA125 has been explored as an OC biomarker for the past 40 years, but lacks sensitivity for early stage OC and is not recommended for screening average-risk, asymptomatic women. We hypothesize that co-localization of biomarkers on the surface of individual extracellular vesicles (EVs), which are shed into the circulation by cancer cells, may lead to development of a blood test for early stage OC. We evaluated the potential of our approach in detecting early stage OC in clinical samples. Methods: We isolated EVs using size-exclusion chromatography and immunoaffinity capture, and detected biomarkers co-localized on the surface of individual EVs with proximity ligation qPCR. Using this approach, we evaluated 49 antibody combinations recognizing 2 or more biomarkers. Each combination consisted of 1 capture antibody and 2 oligonucleotide-tagged detection antibodies. We tested plasma samples from women with early stage I/II high-grade serous ovarian carcinoma (HGSOC)(n=18; 48-80 yr, med 57) and late stage HGSOC (n=24; 37-80 yr, med 54). HGSOC samples were sourced from 2 commercial vendors. Controls comprised samples from women with benign ovarian masses (n=26; 23-76 yr, med 39.5) sourced from a single vendor, and samples prospectively collected by Mercy from healthy women with no cancer history (n=24; 22-72 yr, med 52.5). PCR cycle threshold (Ct) values were measured for each of 49 combinations and data was evaluated using univariate analysis. Performance was compared to plasma CA125 measured at Mercy by commercial ELISA. Results: 8 of 49 combinations distinguished all stages of HGSOC relative to benign and healthy controls with AUCs ranging from 0.86 (95% CI 0.78-0.94) to 0.95 (95% CI 0.90-1.00), comparable to CA125 with an AUC of 0.87 (95% CI 0.79-0.95). One of the most effective combinations (STn, BST2, MUC1) had a sensitivity of 0.78 (95% CI 0.52-0.94) at a specificity of 0.96 (95% CI 0.87-0.99) in detecting early stage HGSOC. This combination also detected HGSOC in 6 of 11 women (3 early stage, 3 late stage) with normal CA125 (< 25 U/mL) and correctly classified 7 of 8 women with benign masses and high CA125 (> 25 U/mL). Conclusions: These preliminary data suggest that co-localization of surface biomarkers in single EVs may provide an effective means to identify women with early stage HGSOC, including those with normal CA125, while avoiding false positives in women with benign masses and high CA125. Despite the inherent challenges associated with commercial samples, our finding that several combinations detected early stage HGSOC is promising. Statistically powered studies with curated repository specimens are underway to refine combinations and independently validate our assay for early stage OC detection. Citation Format: Laura T. Bortolin, Daniel P. Salem, Sanchari Banerjee, Kelly M. Biette, Delaney M. Byrne, Anthony D. Couvillon, Peter A. Duff, Jonian Grosha, MacKenzie Sadie King, Christopher R. Sedlak, Ibukunoluwapo O. Zabroski, Claire Alexander, Karen Copeland, Daniel Gusenleitner, Emily S. Winn-Deen, Eric K. Huang, Bo R. Rueda, Joseph Charles Sedlak. Preliminary results for a novel single extracellular vesicle assay for early stage ovarian cancer: The power of co-localized detection of surface biomarkers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3390.

Abstract 2232: Preliminary results for a novel single extracellular vesicle assay for early lung cancer: The power of co-localized detection of surface biomarkers

Abstract Introduction: Screening for lung cancer (LC), the leading cause of cancer deaths, with helical computerized tomography lowers mortality but uptake is poor. Investigations into new approaches such as using circulating tumor cells and circulating tumor DNA for LC detection have soared in the last decade. However, the low abundance of these targets has limited the performance of these approaches as screening tools. We hypothesize that co-localization of biomarkers on the surface of individual extracellular vesicles (EVs), which are shed into the circulation by cancer cells, may lead to development of a blood test for early stage LC. We evaluated the potential of our approach in detecting early stage LC in clinical samples. Methods: EVs were purified from plasma using size-exclusion chromatography and immunoaffinity capture, and biomarkers co-localized on the EV surface were detected with proximity ligation qPCR. We used antibody combinations comprising 1 capture antibody and 2 oligonucleotide-tagged detection antibodies, recognizing 1, 2 or 3 unique biomarkers. We evaluated this approach by testing plasma samples from early stage I/II lung adenocarcinoma (LUAD) patients (15 smokers, 19 non-smokers), late stage III/IV LUAD patients (16 smokers, 18 non-smokers), and healthy donors (34 smokers, 33 non-smokers). Samples were from one vendor, processed using a standardized protocol. LUAD samples were sourced from a cancer research center and healthy samples from a primary care facility. PCR cycle threshold (Ct) values were generated for each combination and data was evaluated using univariate analysis. Results: Combinations recognizing 3 biomarkers were better in detecting all stages of LUAD (AUC=0.83, 95% CI 0.77-0.90), as compared to combinations recognizing 2 biomarkers (AUC=0.71, 95% CI 0.63-0.80) or 1 biomarker (AUC=0.50, 95% CI 0.35-0.55), demonstrating greater accuracy with an increasing number of co-localized biomarkers. In detecting LUAD (all stages) at a specificity of 0.80 (95% CI 0.69-0.88), sensitivity improved as the number of co-localized biomarkers increased from 1 (0.08, 95% CI 0.03-0.18) to 2 (0.60, 95% CI 0.48-0.72) to 3 (0.76, 95% CI 0.65-0.86). In detecting early stage I/II LUAD, the most effective combination used 3 biomarkers (STn, MUC1, CEACAM6) and had a sensitivity of 0.56 (95% CI 0.38-0.73). Conclusions: These preliminary data highlight the potential of detecting biomarkers co-localized on the surface of single EVs as an effective tool for early stage LC detection, and the benefit of using 3 biomarkers simultaneously. Despite inherent challenges associated with commercial samples, our finding that detection of co-localized EV surface biomarkers distinguished LUAD is promising. Additional studies with LC cohorts beyond LUAD are underway to refine combinations and independently validate our assay for early stage LC detection. Citation Format: Daniel P. Salem, Laura T. Bortolin, Sanchari Banerjee, Kelly M. Biette, Delaney M. Byrne, Anthony D. Couvillon, Peter A. Duff, Jonian Grosha, Daniel Gusenleitner, MacKenzie Sadie King, Christopher R. Sedlak, Ibukunoluwapo O. Zabroski, Karen Copeland, Emily S. Winn-Deen, Eric K. Huang, Christine D. Berg, Joseph C. Sedlak. Preliminary results for a novel single extracellular vesicle assay for early lung cancer: The power of co-localized detection of surface biomarkers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2232.

Single-Particle Interferometric Reflectance Imaging Characterization of Individual Extracellular Vesicles and Population Dynamics.

Extracellular vesicles (EVs) are nanometer-sized vesicles with a lipid bilayer that are secreted by most cells. EVs carry a multitude of different biological molecules, including protein, lipid, DNA, and RNA, and are postulated to facilitate cell-to-cell communication in diverse tissues and organs. Recently, EVs have attracted significant attention as biomarkers for diagnostics and therapeutic agents for various diseases. Many methods have been developed for EV characterization. However, current methods for EV analysis all have different limitations. Thus, developing efficient and effective methods for EV isolation and characterization remains one of the crucial steps for this cutting-edge research field as it matures. Here, we provide a detailed protocol outlining a single-particle interferometric reflectance imaging sensor (SP-IRIS), as a method that is capable of detecting and characterizing EVs from unpurified biological sources and purified EVs by other methodologies. This advanced technique can be used for multi-level and comprehensive measurements for the analysis of EV size, EV count, EV phenotype, and biomarker colocalization.

A hierarchical and multi-view registration of serial histopathological images

Serial histopathological images sliced from the same biopsy section exhibit quite similar topological structures. They are usually stained with different dyes and inspected individually for different clinical purposes in the routine workflow of pathology. Recently there is increasing demand for browsing them jointly, e.g., viewing the colocalization of biomarkers. Image registration is recognized as a feasible means to bridge this requirement. However, it is challenging to register the images due to their natural content difference, variation and distortion introduced from slice preparation, the extremely large image size, etc. This letter proposes a novel Hierarchical and Multi-View Registration (HMVReg) method to alleviate the difficulties. It is a three-stage coarse-to-fine registration consisting of global rigid registration, multi-view affine transformation and multi-view elastic registration, respectively for eliminating the translational and rotational differences, globally isotropic deformation and locally anisotropic distortion. The stages are complementary and jointly contribute to a stable registration. Experimental results on both private and public data, which cover histopathological images from multiple organ tissues, demonstrate the effectiveness of the proposed HMVReg. It not only well balance the registration accuracy, robustness and speed, where serial but differently stained images are accurately aligned in a reasonable time cost. Moreover, it also shows satisfactory user experience in applying the alignment to biomarker colocalization browsing.

Abstract 1179: Deep spatial immuno-profiling through high biomarker colocalization in FFPE tumor tissue sections

Abstract Background: The recent emergence of highly multiplexed immunohistochemistry (IHC) has the potential to revolutionize immuno-oncology and pathology research as it enables the identification of complex cell subtypes and their potential interactions in the tumor environment. Comprehensive classification of the different cell types in immuno-oncology presents a unique challenge as many of the relevant biomarkers are common to large subsets of cell types within a particular cell class. Therefore, a key feature for accurate phenotypic classification is the ability to detect a high number of colocalized biomarkers. Current IHC technologies offer a low subtyping level due to steric constraints, spectral overlap between dyes, or depletion of deposition sites. Alternative strategies using mass- or cleavable oligonucleotide- tags can potentially achieve high colocalization but are hindered by their low-throughput, high-cost, and elaborate post-acquisition image reconstruction. In this study, we demonstrate how the Ultivue® InSituPlex® technology enables researchers to reliably label and detect at least 4 markers in the same compartment (cytoplasmic or nuclear) on single cells in tumor tissue samples. Methods: Different FFPE tumor sections were labeled, imaged, and profiled for 15 targets using InSituPlex technology. Staining was carried out in a single workday on a Leica BOND RX autostainer using a cocktail of the 15 primary antibodies relevant to immuno-oncology. Commercially available multi-color fluorescence slide scanners were used to obtain whole slide images. The resulting images were then segmented and analyzed for different phenotypes and their spatial relationships using Indica Labs HALO® software. Additional dimensionality reduction algorithms were used to visualize the high-dimensional phenotypic data of cells with many overlapping biomarkers. Results: In this poster, we demonstrate the detection of at least 4 co-localized biomarkers on the same cell in FFPE tissue sections. Analysis of the high dimensional, spatially resolved data obtained from a 15-plex assay provided phenotypic information of different lymphocytes, macrophages, dendritic cells, antigen presenting cells, and tumor cell populations with multiple colocalized biomarkers. Conclusions: InSituPlex technology empowers pathology research through colocalization analysis of many markers on single cells over entire sections of tissue for accurate differentiation and subtyping of cell populations in the tumor microenvironment. As exploratory research in immuno-oncology expands, advancements in multiplex spatial profiling technologies promise to offer greater insights by providing a systems-level view of the biology. Citation Format: Abdul Mohammed, Douglas Wood, Mael Manesse. Deep spatial immuno-profiling through high biomarker colocalization in FFPE tumor tissue sections [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1179.

Abstract 1720: Analysis of multiplexed immunotherapy targets and secreted ligands using computational tumor microenvironment profiling

Abstract As the number and diversity of cellular and signaling pathway therapeutic targets in immuno-oncology increases, more therapy combinations are aimed at multiple cell types in the tumor microenvironment (TME). To develop rational combinations of therapies that will be effective in any individual patient, multivariate biomarker assays will be required to understand each patient's specific tumor and immune profile. Understanding the mechanistic effects of immunotherapy includes the tissue context of direct immunotherapy targets and downstream effector molecules such as secreted cytokines. Although the content of tumor-infiltrating immune cells and gene expression of the total tumor can be ascertained through several methods, spatial arrangements and proximity of cells and co-localization of biomarkers can only be achieved with tissue-based assays. Duplex chromogenic in situ hybridization assays using the RNAscope platform allows for the visualization of gene expression of mRNA targets directly in tissue for multiple cell types or biomarkers. Computational Tissue Analysis (cTA™) was used to quantify cellular spatial distributions including regional density maps, proximity measurements, and colocalization of biomarkers in both the tumor nests and the surrounding stroma that would be challenging by visual inspection of duplex RNAscope assays in non-small cell lung cancer (NSCLC) tissue microarrays (TMAs). Often, neither immune effector cells nor the therapeutic target is sufficient in isolation to understand blocked anti-tumor immune responses and therefore the potential efficacy of a single or combination therapeutic strategy. Multiplex RNAscope assays and cTA™ in combination allow the assessment of end points that measure spatial relationships between cell types expressing certain biomarkers. As these are performed in the context of the tissue microarchitecture within and across multiple tissue sections, they are a significant advancement over traditional tissue-based manual end points. Citation Format: Jenifer Caldara, Brooke Hirsch, Joseph Krueger, Chris Bunker, Jeff Kim, Annelies Laeremans, Mohammed Qutaish, Allison Harney. Analysis of multiplexed immunotherapy targets and secreted ligands using computational tumor microenvironment profiling [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1720.

Registration of whole immunohistochemical slide images: an efficient way to characterize biomarker colocalization.

Extracting accurate information from complex biological processes involved in diseases, such as cancers, requires the simultaneous targeting of multiple proteins and locating their respective expression in tissue samples. This information can be collected by imaging and registering adjacent sections from the same tissue sample and stained by immunohistochemistry (IHC). Registration accuracy should be on the scale of a few cells to enable protein colocalization to be assessed. We propose a simple and efficient method based on the open-source elastix framework to register virtual slides of adjacent sections from the same tissue sample. We characterize registration accuracies for different types of tissue and IHC staining. Our results indicate that this technique is suitable for the evaluation of the colocalization of biomarkers on the scale of a few cells. We also show that using this technique in conjunction with a sequential IHC labeling and erasing technique offers improved registration accuracies. Brightfield IHC enables to address the problem of large series of tissue samples, which are usually required in clinical research. However, this approach, which is simple at the tissue processing level, requires challenging image analysis processes, such as accurate registration, to view and extract the protein colocalization information. The method proposed in this work enables accurate registration (on the scale of a few cells) of virtual slides of adjacent tissue sections on which the expression of different proteins is evidenced by standard IHC. Furthermore, combining our method with a sequential labeling and erasing technique enables cell-scale colocalization.

A novel, automated technology for multiplex biomarker imaging and application to breast cancer

Multiplexed immunofluorescence is a powerful tool for validating multigene assays and understanding the complex interplay of proteins implicated in breast cancer within a morphological context. We describe a novel technology for imaging an extended panel of biomarkers on a single, formalin-fixed paraffin-embedded breast sample and evaluating biomarker interaction at a single-cell level, and demonstrate proof-of-concept on a small set of breast tumours, including those which co-express hormone receptors with Her2/neu and Ki-67. Using a microfluidic flow cell, reagent exchange was automated and consisted of serial rounds of staining with dye-conjugated antibodies, imaging and chemical deactivation. A two-step antigen retrieval process was developed to satisfy all epitopes simultaneously, and key parameters were optimized. The imaging sequence was applied to seven breast tumours, and compared with conventional immunohistochemistry. Single-cell correlation analysis was performed with automated image processing. We have described a novel platform for evaluating biomarker co-localization. Expression in multiplexed images is consistent with conventional immunohistochemistry. Automation reduces inconsistencies in staining and positional shifts, while the fluorescent dye cycling approach dramatically expands the number of biomarkers which can be visualized and quantified on a single tissue section.