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Background: It has been well established that the tumor microenvironment (TME), which comprises cancer cells, stromal cells, and surrounding extracellular matrix, plays a critical role in cancer development, progression, and control. The immunological components within tumors, known as the tumor immune microenvironment (TiME), have also been implicated in tumor development, recurrence, and metastasis. Effective strategies for cancer immunotherapies will require a deep understanding of the factors that shape both the TME and TiME. Here, we describe a spatial multiomics approach that utilizes RNAscope™ ISH technology paired with high-plex whole-slide spatial phenotyping with the PhenoCycler™-Fusion platform. This two-step approach is compatible with human FFPE tissues and enables researchers to characterize the spatial biology of the TiME more accurately by detecting RNA and protein markers on serial sections. The resulting multiomic data more accurately reveal the interplay between TME and TiME by giving insight into cell lineages, surrounding structures, as well as secreted chemokines and cytokines that exist within the TME ecosystem. Methods: We performed ultrahigh-plex spatial phenotyping on the PhenoCycler-Fusion on FFPE tumor tissue sections, using an antibody panel that is designed for immune cell phenotyping, evaluation of immune contexture and proliferation across the TME. Using serial sections from the same tissue blocks, we then ran the RNAscope HiPlex v2 assay automated on the PhenoCycler-Fusion system. This assay consisted of a 12-plex immuno-oncology panel of RNA target probes, which were selected to detect macrophages, chemokines, and cytokines within tumors. We used Phenoplex software to analyze the protein and RNA datasets and to compute cell phenotypes and spatial associations. Results and Conclusions: In this proof-of-concept study, we demonstrate the utility of multiomic spatial profiling on the PhenoCycler-Fusion platform. Analysis of the resulting multiplex imaging data not only revealed the structural organization of cells within the TME, but also activation states of immune cells. Together, this information provides a more complete functional map of immune cells within the TME and TiME and thereby enriches our understanding of tumor biology that may be deterministic of immunotherapy responsiveness. This work paves the way for future research that will rely on deep spatial phenotyping with protein biomarkers coupled with accurate quantification of the expression of regulatory cytokines, chemokines, growth factors, or non-coding RNAs that only RNA probes can detect. Citation Format: Niyati Jhaveri, HaYeun Ji, Anushka Dikshit, Jessica Yuan, Emerald Doolittle, Steve Zhou, Maithreyan Srinivasan, Bassem B. Cheikh, Fabian Schneider, James Mansfield, Julia Kennedy-Darling, Oliver Braubach. Multiomic spatial profiling of the tumor immune microenvironment at single cell resolution. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5626.

Interrogating complex tumor microenvironment requires a multi-omics approach that can provide high level of sensitivity and specificity. Identifying immune cell subsets within the tumor can be vital for predicting response and determining therapeutic efficacy. Detecting target immune cell markers using immunohistochemistry/Immunofluorescence (IHC/IF) and visualizing cytokine expression with in situ hybridization (ISH) can provide comprehensive information about the activation states of immune cells. Here, we demonstrate a newly developed integrated ISH and IHC/IF workflow compatible with manual and automated platforms that can substantially improve RNA-protein co-detection. We demonstrate the use of our RNA-Protein Co-detection assay in combination with the automated RNAscope Multiplex Fluorescent v2 assay, automated RNAscope Chromogenic Duplex assay and manual RNAscope Multiplex Fluorescent v2 assay to detect T cell markers, macrophage markers and checkpoint markers in the tumor microenvironment by using a microarray with different tumor samples. We identified CD4+ helper T cells and CD8+ cytotoxic T lymphocytes. Additionally, we determine the activation states of CD8+ T cells by visualizing IFNG, GZMB and IL-2 expression. We were also able to identify macrophages detected by CD68 protein expression and the M1 and M2 subsets were differentiated by using the M2-specific marker, CD163. We could also delineate tumor-stroma border in the samples by using the Pan-CK probe which distinctly marks the tumor cells and visualize the expression of immunoregulatory receptors PD-L1 and CTLA4 in the tumor cells. This assay is enabled for multiplexing by combining with our fluorescent assay platforms. Similarly, for researchers interested in detecting target expression while retaining morphological context, the codetection assay should be combined with our chromogenic assays. Overall, the new RNAscope-ISH-IHC co-detection workflow and reagents enable optimized simultaneous visualization of RNA and protein targets by enhancing the compatibility of antibodies with minimal optimization. Citation Format: Anushka Dikshit, Sayantani Basak, Emerald Doolittle, Ilya Kovalenko, Michaeline Bunting. Spatial analysis of tumor-infiltrated immune cells with highly specific RNAscope™ RNA-protein Co-detection assays [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 1723.

Background Spatially resolved gene expression has emerged as a crucial technique to understand complex multicellular interactions within the tumor and its microenvironment. Interrogation of complex cellular interactions within the tumor microenvironment (TME) requires a multi-omics approach where multiple RNA and protein targets can be visualized within the same tumor sample and be feasible in FFPE sample types. Simultaneous detection of RNA and protein can reveal cellular sources of secreted proteins, identify specific cell types, and visualize the spatial organization of cells within the tissue. Examination of RNA by in situ hybridization (ISH) and protein by immunohistochemistry (IHC) or immunofluorescence (IF) are widely used and accepted techniques for the detection of biomarkers in tumor samples. Given the similarities in workflow, co-detection of RNA and protein by combining ISH and IHC/IF in a single assay can be a powerful multi-omics solution for interrogating the complex tumor and its microenvironment. Methods In this report we combined the single cell, single molecule RNA ISH technology known as RNAscope with IHC/IF to simultaneously detect RNA and protein in the same FFPE tumor section using both chromogenic and fluorescence detection methods. Results We demonstrate co-localization of target mRNA and the corresponding protein in human cancer samples, visualize infiltration of immune cells into the TME, characterize the activation state of immune cells in the TME, identify single cell gene expression within cellular boundaries demarcated by IHC/IF, examine cell type-specific expression of multiple immune checkpoint markers, and distinguish endogenous T cells from activated CAR+ T cells. Overall, we show that co-detection of RNA by the RNAscope ISH assay and protein by the IHC/IF assay in the same FFPE section is a feasible methodology. The combined RNAscope ISH-IHC/IF workflow is a powerful technique that can be used to study gene expression signatures at the RNA and protein level with spatial and single cell resolution. Conclusions By leveraging the strength of the similar workflows of RNAscope ISH and IHC/IF assays, this methodology combines transcriptomics and proteomics in the same tissue section, providing a multi-omics approach for characterizing complex tissues and revealing cell type specific gene expression with spatial and single cell resolution.

Interrogating complex tumor microenvironment requires a multi-omics approach. Detecting target immune cell markers using immunohistochemistry/Immunofluorescence (IHC/IF) and visualizing cytokine expression with in situ hybridization (ISH) can provide comprehensive information about the activation states of immune cells. Here, we demonstrate a newly developed integrated ISH and IHC/IF workflow compatible with manual and automated platforms with improved RNA-protein co-detection. We demonstrate the use of our RNA-Protein Co-detection assay in combination with the automated and manual RNAscope Multiplex Fluorescent assay as well as the automated RNAscope Chromogenic Duplex assay to detect T cell markers, macrophage markers and checkpoint markers in the tumor microenvironment by using a microarray with different tumor samples. We identified CD4+ helper T cells, CD8+ cytotoxic T cells and determined their activation states by visualizing IFNG, GZMB and IL-2 expression. We were also able to identify macrophages detected by CD68 protein expression and differentiate the M1 and M2 subtypes by using M2-specific marker, CD163. We could also delineate tumor-stroma border in the samples by using the Pan-CK probe which distinctly marks the tumor cells and visualize expression of immunoregulatory receptors PD-L1 and CTLA4 in the tumor. This assay is enables for multiplexing by combining with our fluorescent assays or enables target detection while retaining morphological context when combined with our chromogenic assays. Overall, the new RNAscope-ISH-IHC/IF co-detection workflow and reagents enable simultaneous visualization of RNA and protein targets by enhancing the compatibility of antibodies with minimal optimization.

The assessment of B-cell clonality is a critical component of the evaluation of suspected lymphoproliferative disorders, but analysis from formalin fixed paraffin embedded tissues can be challenging if fresh tissue is not available for flow cytometry. Immunohistochemical and conventional bright field in situ hybridization stains for kappa and lambda are effective for evaluation of plasma cells, but are often insufficiently sensitive to detect the much lower abundance of light chains present in B cells. We describe an ultrasensitive RNA in situ hybridization assay which has been adapted for use on an automated immunohistochemistry platform and compare results with flow cytometry in 203 consecutive tissues and 104 consecutive bone marrows. Overall, in 203 tissue biopsies, RNA in situ hybridization identified light chain restricted B-cells in 85 (42%) vs. 58 (29%) by flow cytometry. Within 83 B-cell non-Hodgkin lymphomas, RNA in situ hybridization identified a restricted B-cells in 74 (89%) vs. 56 (67%) by flow cytometry. B-cell clonality could be evaluated in only 23/104 (22%) bone marrow cases due to poor RNA preservation, but evaluable cases showed 91% concordance with flow cytometry. RNA in situ hybridization allowed for recognition of biclonal/composite lymphomas not identified by flow cytometry, and highlighted unexpected findings, such as coexpression of kappa and lambda RNA in 2 cases and the presence of lambda light chain RNA in a T lymphoblastic lymphoma. Automated RNA in situ hybridization showed excellent interobserver reproducibility for manual evaluation (average K=0.92), and an automated image analysis system showed high concordance (97%) with manual evaluation. Automated RNA in situ hybridization staining, which can be adopted on commonly utilized immunohistochemistry instruments, allows for the interpretation of clonality in the context of the morphologic features in formalin fixed, paraffin embedded tissues with a clinical sensitivity similar or superior to flow cytometry.

Complex tissues such as tumors are comprised of multiple cells types and extracellular matrix. These cells include heterogenous populations of immune cells that infiltrate the tumors. Understanding the composition of these immune infiltrates in the tumor microenvironment (TME) can provide key insights to guide therapeutic intervention and predict treatment response. Thorough understanding of complex tissue dynamics and immune cell characterization requires a multi-omics approach. Simultaneous detection of RNA and protein using in situ hybridization (ISH) and immunohistochemistry/immunofluorescence (IHC/IF) can reveal cellular sources of secreted proteins, identify specific cell types, and visualize the spatial organization of cells within the tissue. However, a sequential workflow of ISH followed by IHC/IF frequently yields suboptimal protein detection because the protease digestion step in the ISH protocol resulting in poor antibody signal. Here we demonstrate a newly developed integrated ISH/IHC workflow that can substantially improve RNA-protein co-detection, enabling the visualization and characterization of tumor immune infiltrates at single-cell resolution with spatial and morphological context. To characterize tumor-infiltrating immune cells in a tumor TMA (tumor microarray), we utilized the RNAscope Multiplex Fluorescence assay in combination with the RNA-Protein Co-detection Kit to detect multiple immune cell populations. Immune cells such as macrophages, T cells and NK cells were detected using specific antibodies against CD68, CD8, CD4 and CD56, respectively. Precise characterization of these immune cells was achieved by using probes against targets such as CCL5, IFNG, GNZB, IL-12, NCR1 etc. that not only help in identifying specific immune cells but also assist in determining their activation states. We identified subsets of T cells such as CD4+ regulatory T cells and CD8+ cytotoxic T lymphocytes. Additionally, we were able to determine the activation states of CD8+ T cells by visualizing the expression of IFNG and GZMB. Furthermore, infiltrating macrophages were identified by detecting the CD68 protein expression while the M1 and M2 subsets were differentiated by detecting the M2-specific target RNA for CD163. Similarly, NK cells were identified by detecting CD56 protein in combination with CCL5 and NCR1 RNA expression. Interestingly, the degree of infiltration of the different immune cell populations varied based on the tumor type. In conclusion, the new RNAscope-ISH-IHC co-detection workflow and reagents enable optimized simultaneous visualization of RNA and protein targets by enhancing the compatibility of antibodies - including many previously incompatible antibodies - with RNAscope. This new workflow provides a powerful new approach to identifying and characterizing tumor infiltrating populations of immune cells. Citation Format: Anushka Dikshit, Jyoti Phatak, Lydia Hernandez, Emerald Doolittle, Vasudha Murlidhar, Bingqing Zhang, Xiao-Jun Ma. Characterizing tumor-infiltrated immune cells with spatial context using an integrated RNAscope-immunohistochemistry co-detection workflow in FFPE tissues [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr LB235.

Characterizing heterogenous populations of tumor-infiltrating immune cells requires a multi-omics approach. Here we demonstrate a newly developed integrated in situ hybridization (ISH) and immunohistochemistry (IHC/IF) workflow that can substantially improve RNA-protein co-detection, enabling the visualization and characterization of tumor immune infiltrates at single-cell and spatial resolution. To characterize tumor-infiltrating immune cells in a tumor TMA (tumor microarray), we utilized the RNAscope Multiplex Fluorescence assay in combination with the RNA-Protein Co-detection Kit to detect multiple immune cell populations. Immune cells such as macrophages, T cells and NK cells were detected using antibodies against CD68, CD8, CD4 and CD56 in combination with probes targeting CCL5, IFNG, GNZB, IL-12, NCR1 etc. We identified CD4+ regulatory T cells and CD8+ cytotoxic T lymphocytes. Additionally, we determine the activation states of CD8+ T cells by visualizing IFNG and GZMB expression. Furthermore, infiltrating macrophages were detected by CD68 protein expression while the M1 and M2 subsets were differentiated by using the M2-specific marker, CD163. NK cells were identified by detecting CD56 protein in combination with CCL5 and NCR1 RNA expression. The degree of immune cell infiltration varied based on the tumor type. In conclusion, the new RNAscope-ISH-IHC co-detection workflow and reagents enable optimized simultaneous visualization of RNA and protein targets by enhancing the compatibility of antibodies, including many previously incompatible antibodies with RNAscope . This new workflow provides a powerful approach to identifying and characterizing tumor infiltrating immune cells.

About 25% of non-small cell lung cancer (NSCLC) patients bear one or more KRAS mutations in their tumors, which is correlated with poor prognosis. The precise identification of somatic mutations in tumors is becoming increasingly important for studying tumor progression and developing targeted therapies. While sequencing technologies allow for mutation-profiling, they do not permit direct visualization and association of genetic alterations with cellular morphology. In addition, DNA mutational status does not predict expression of the mutant allele which may provide information connecting genotype to phenotype. Therefore, a technology for mutation detection at the transcript level directly in the tumor context is desirable. To address this need we developed a specialized RNA in situ hybridization (ISH) method known as BaseScope. The BaseScope assay has a unique signal amplification system that allows for highly sensitive and specific detection of single nucleotide point mutations in tissues. BaseScope probes specific for KRAS G12C, G12A, G12V, G12S and wild type KRAS were designed and expression of each point mutation was assessed in a NSCLC tumor microarray with 48 tumor cores with known KRAS mutation status as determined by DNA sequencing. RNA quality and background signal threshold for each tumor core were determined using PPIB (positive) and dapB (negative) control probes. Using the sequencing data as the gold standard, the BaseScope assay demonstrated 83-100% sensitivity and 97-100% specificity for various KRAS mutations [Table 1]. For KRAS G12C, the assay correctly identified all 6 sequencing-positive cores and identified the rest as negatives. For KRAS G12V, the assay detected 5 of 6 mutated cores with 100% specificity. Interestingly, for KRAS G12S and KRAS G12A mutations, the BaseScope assay demonstrated 100% sensitivity and 97% specificity. Furthermore, it was observed that 100% of the KRAS-mutated tumors showed expression for both wild type and mutant KRAS alleles within these NSCLC tumors. In summary, we demonstrate the development of an RNA ISH assay for point mutations detection with morphological context in FFPE tissues. Unlike current sequencing methods that lack spatial information this assay has the unique ability to identify very small subclones whose frequency within the tumor might fall below the detection limit of sequencing. Performance characteristics of BaseScope KRAS assaysKRAS POINT MUTATIONSNo. of cores with specified mutationsNo. of cores without specified mutationsBaseScope sensitivityBaseScope specificityG12C633100% (6/6)100% (33/33)G12A336100% (3/3)97.2% (35/36)G12V63383% (5/6)100% (33/33)G12S138100% (1/1)97.3% (37/38) Citation Format: Anushka Dikshit, Helen Jarnagin, Emerald Doolittle, Courtney Anderson, Bingqing Zhang, Xiao-Jun Ma. Visualization of KRAS point mutations in non-small cell lung cancer tumors with morphological context using the BaseScope in situ hybridization assay [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2705.

As we strive to prolong patient survival, the advent of targeted therapy for the treatment of ovarian cancer has significantly added to our armamentarium. Unfortunately, both chemotherapy and molecularly targeted PARPi approaches share the overarching limitation of the emergence of drug resistance. One key aspect towards realizing the potential of targeted therapies is a better understanding of the intrinsic and acquired resistance mechanisms that limit their efficacy. Through comprehensive genomic analysis of post-treatment patient samples, we recently identified the most common mechanism of acquired drug resistance in high-grade serous ovarian cancer (HGSC) to date, a transcriptional fusion involving ABCB1. ABCB1 encodes P-gp also known as multidrug resistance protein 1 (MDR1), a multi-transmembrane domain protein that is a member of the superfamily of ATP binding cassette (ABC) transporters involved in the cellular efflux of chemotherapeutic drugs. The SLC25A40-ABCB1 fusion was associated with upregulation of ABCB1 expression, whilst leaving the predicted ABCB1 protein unaltered. Interestingly, fusion events were only detected in patients who had been exposed to chemotherapies that are known substrates of P-gp, with the probability of fusion events closely correlated to the number of lines of P-gp substrate chemotherapy. Surprisingly, WGS analysis of patient samples revealed that not all tumor cells in fusion-positive patients carry the fusion. An intriguing possibility is that resistance within tumor sites is spatially ordered rather than random. Identifying such patterning could explain why tumor eradication has not been effective for the majority of HGSC patients to date. To address the subclonal localization and spatial patterning of ABCB1 fusions in HGSC, CASCADE (rapid autopsy program), biopsy specimens, and PDX tissue are being prescreened (qRT-PCR) to identify those with the highest levels of ABCB1 expression and thus most likely to harbor fusions. In situ DNA and RNA detection assays are being employed to identify ABCB1 fusions. To examine whether fusion negative cells also overexpress P-gp, IHC analysis will then be conducted to co-register fusion positivity and protein expression. We have successfully identified fusion events using ACD BaseScope technology and examined the localization of key HGSC genes including CCNE1 and ABCB1 through PCR FISH assays. In summary, this study will decipher the diversity of resistance mechanisms within individual HGSC patients, thereby providing critical information required for next-generation chemotherapy and PARPi clinical trials aimed at reversing or bypassing acquired resistance. Citation Format: Kathleen I. Pishas, Elizabeth L. Christie, Jessica A. Beach, Kathryn Alsop, Alison Freimund, Nidhi Vashistha, Niyati Jhaveri, Emerald Doolittle, Wei Wei, Bingqing Zhang, Xiao-Jun Ma, David D.L. Bowtell. Spatial characterization of drug resistance in ovarian cancer [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research; 2019 Sep 13-16, 2019; Atlanta, GA. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(13_Suppl):Abstract nr A65.

Because precision medicine is highly dependent on the accurate detection of biomarkers, there is an increasing need for standardized and robust technologies that measure RNA biomarkers in situ in clinical specimens. While grind-and-bind assays like RNAseq and quantitative RT-PCR enable highly sensitive gene expression measurements, they also require RNA extraction and thus prevent valuable expression analysis within the morphological tissue context. The in situ hybridization (ISH) assay described here can detect RNA target sequences as short as 50 nucleotides at single-nucleotide resolution and at the single-cell level. This assay is complementary to the previously developed commercial assay and enables sensitive and specific in situ detection of splice variants, short targets, and point mutations within the tissue. In this protocol, probes were designed to target unique exon junctions for two clinically important splice variants, EGFRvIII and METΔ14. The detection of short target sequences was demonstrated by the specific detection of CDR3 sequences of T-cell receptors α and β in the Jurkat T-cell line. Also shown is the utility of this ISH assay for the distinction of RNA target sequences at single-nucleotide resolution (point mutations) through the visualization of EGFR L858R and KRAS G12A single-nucleotide variations in cell lines using automated staining platforms. In summary, the protocol shows a specialized RNA ISH assay that enables the detection of splice variants, short sequences, and mutations in situ for manual performance and on automated stainers.

Because precision medicine is highly dependent on the accurate detection of biomarkers, there is an increasing need for standardized and robust technologies that measure RNA biomarkers in situ in clinical specimens. While grind-and-bind assays like RNAseq and quantitative RT-PCR enable highly sensitive gene expression measurements, they also require RNA extraction and thus prevent valuable expression analysis within the morphological tissue context. The in situ hybridization (ISH) assay described here can detect RNA target sequences as short as 50 nucleotides at single-nucleotide resolution and at the single-cell level. This assay is complementary to the previously developed commercial assay and enables sensitive and specific in situ detection of splice variants, short targets, and point mutations within the tissue. In this protocol, probes were designed to target unique exon junctions for two clinically important splice variants, EGFRvIII and METΔ14. The detection of short target sequences was demonstrated by the specific detection of CDR3 sequences of T-cell receptors α and β in the Jurkat T-cell line. Also shown is the utility of this ISH assay for the distinction of RNA target sequences at single-nucleotide resolution (point mutations) through the visualization of EGFR L858R and KRAS G12A single-nucleotide variations in cell lines using automated staining platforms. In summary, the protocol shows a specialized RNA ISH assay that enables the detection of splice variants, short sequences, and mutations in situ for manual performance and on automated stainers.