Intercellular Mechanisms of Therapeutic Resistance at the Tumor-Stromal Interface Using Ultra High-Plex Single-Cell Spatial Transcriptomics and Genetically-Engineered Tumoroids

PURPOSE/OBJECTIVE(S)

There is a major gap in knowledge regarding how intercellular interactions in the tumor microenvironment (TME) mediate therapeutic resistance. Achievement of this goal has been limited by a lack of (1) spatial context in dissociated single-cell methods; (2) single-cell resolution in spatial profiling approaches; (3) high quality data and yield with FFPE patient specimens; and (4) computational methods for ligand-receptor analyses that consider both gene expression and spatial coordinates.

MATERIALS/METHODS

We developed an innovative spatial biology paradigm that combines cutting-edge experimental and computational methods to enable high-resolution, spatially-guided discovery of critical mediators of therapeutic resistance. We applied this approach to dissect the single-cell spatial transcriptomic landscape of untreated vs. chemoradiotherapy-treated primary human pancreatic ductal adenocarcinoma (PDAC; n = 21) using ultra-high plex spatial molecular imaging (SMI) optimized for high-sensitivity, subcellular detection of up to 6000 gene transcripts in FFPE sections-an order of magnitude greater than contemporary methods.

RESULTS

We recovered over 1,000,000 high-quality single cells in situ representing more than 20 distinct cell types, including epithelial, immune, endothelial, endocrine, and diverse stromal cells. We developed an optimal transport-based computational method to infer cell-cell communication at the cancer-stromal interface. Treatment with chemoradiotherapy was associated with the largest increase in fibroblast-malignant interactions. Comparing the SMI data with orthogonal single-nucleus RNA-sequencing and digital spatial profiling data, we identified CLCF1-CNTFR as the fibroblast-malignant interaction most associated with resistance to chemoradiotherapy in PDAC. CLCF1 is a gp130-family cytokine that activates Jak-STAT signaling and acts as a potent neurotrophic factor. Notably, the CLCF1-CNTRF (fibroblast-malignant) interaction has prominent pro-oncogenic effects in lung adenocarcinoma and an engineered CNTFR decoy receptor with therapeutic potential has been developed. To functionally validate the role of the CLCF1-CNTFR (fibroblast-malignant) interaction in mediating resistance to cytotoxic therapy, we created CRISPR-engineered cancer-fibroblast tumoroids and modulated expression of this ligand-receptor pair. Pancreatic cancer cell viability in the presence of 5-fluorouracil was better maintained with increased CLCF1-CNTFR signaling.

CONCLUSION

In this study, we integrated ultra high-plex single-cell spatial transcriptomics, optimal transport ligand-receptor predictions, and genetically-engineered stromal tumoroids to identify and validate CLCF1-CNTFR as an important intercellular mechanism of resistance to chemoradiotherapy in PDAC-pioneering a paradigm for translating single-cell spatial biology to clinical oncology.

Abstract 615: Spatially resolved expression of T cell receptors elucidates spatial relationships between T cells, immune infiltration, and cancer-associated pathways

Spatial distribution of T cells is key in understanding the escape of tumors from immune surveillance via the adaptive immune response, including interactions between immune cells and the surrounding tumor microenvironment. T cells are critical to the adaptive immune response to pathogens and cancers, mediating an antigen-specific response through both specificity and diversity of T cell receptor (TCR) clonotypes. Many methods exist to determine specific clonotypes and overall TCR diversity present from bulk tissues or sorted cell populations; however, nearly all fail to capture spatial orientation and arrangement of T cells engaging with their microenvironment, and most require large amounts of starting material from precious samples. Here, we present a TCR expression profiling panel for the GeoMx® Digital Spatial Profiler that can be combined with the GeoMx Cancer Transcriptome Atlas (CTA) or Human Whole Transcriptome Atlas (WTA) on archival formalin-fixed paraffin embedded (FFPE) tissue specimens. This represents the first commercial spatial expression profiling assay for the simultaneous quantification of TCR constant, variable, and joining segments in situ.

We show reliable sensitivity and specificity (>90%) with respect to orthogonal sequencing and robust detection of TCR chains with evidence of clonal expansion and CD8 infiltration across tumor regions in colorectal cancer tissue. These events also corresponded to increased signatures of exhaustion from the T cells and suggest that the T cells resident in or near the tumor are tumor-specific and poised for activation via checkpoint blockade. Signaling pathways and tumor-specific signatures were also evaluated to look for mechanisms through which tumor cells respond to T cell infiltration. We further validated the performance of the TCR probe pool in cell pellet arrays with orthogonal TCR sequencing, tonsil and colorectal cancer tissues.

Together, the combination of our TCR add-on panel with the CTA or WTA illuminates T cell phenotypes, signaling pathways, population dynamics, and transcriptomic changes, yielding an unparalleled view of the T cell response in any context.

FOR RESEARCH USE ONLY. Not for use in diagnostic procedures.

Citation Format: Katrina van Raay, Michelle Kriner, Jason Reeves, Erin Piazza, Hargita Kaplan, John Vivian, Francis Fernandez, Margaret Hoang, Joseph Beechem. Spatially resolved expression of T cell receptors elucidates spatial relationships between T cells, immune infiltration, and cancer-associated pathways [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 615.

Abstract 4617: A complete pipeline for high-plex spatial proteomic profiling and analysis on the cosmxtm spatial molecular imager and atomtm spatial informatics platform

Detecting and analyzing large numbers of proteins using whole-slide imaging is critical for a comprehensive picture of immune response to cancer. Many existing approaches for high-plex proteomics face issues around simplicity, speed, scalability, and big data analysis. Here, we present an integrated workflow from sample preparation through downstream analysis that addresses many key concerns around high plex proteomics. The CosMx Spatial Molecular Imager (SMI) and AtoMx Spatial Informatics Platform (SIP) comprise of a turnkey, end-to-end workflow that efficiently handles highly multiplex protein analysis at plex sizes exceeding 110 targets. We demonstrate an extension of our commercially available 64-plex human immuno-oncology panel to higher numbers of targets and show how the cloud computing-enabled AtoMx SIP allows flexible construction of analytic pipelines for cell typing and spatial analyses.

The CosMx protein assay uses antibodies conjugated with oligonucleotides, which are detected using universal, multi-analyte CosMx readout reagents. The CosMx Human Immuno-oncology panel was optimized to comprehensively profile lymphoid and stromal lineages within the tumor microenvironment as well as markers of cancer signaling and progression. Each CosMx SMI antibody was validated on multi-organ FFPE tissue microarrays covering prevalent solid tumor types with matched controls, and 52 human FFPE cell lines, including overexpression lines for key targets such as GITR, CD278, PD-L1, and PD-1. CosMx SMI uses a deep learning algorithm to segment whole cells and a semi-supervised algorithm to classify cell types. The AtoMx SIP provides full analysis support, including a whole-slide image viewer, and methods for performing built-in or fully customizable analyses for cell typing, ligand-receptor analysis, neighborhood analysis and spatial differential expression.

Within the cancer sample profiled, we performed in-depth single-cell proteomic profiling across different cell populations. We detected TLS, characterized TLS maturation, and identified immune interactions with the tumor microenvironment. The CosMx SMI assay profiled the composition and spatial organization of infiltrating immune cells within and around the tumor microenvironment. We found that markers of T cell activation and exhaustion varied across the tumor landscape.

CosMx SMI is a high-plex spatial multi-omics platform that enables detection of more than 110 proteins at subcellular resolution in real-world FFPE tissues. The extensibility of the CosMx protein assay to large numbers of protein targets and our flexible, scalable bioinformatic platform provides a straightforward and robust solution for comprehensive immune phenotyping with full spatial context.

FOR RESEARCH USE ONLY. Not for use in diagnostic procedures.

Citation Format: Tien Phan-Everson, Zachary Lewis, Giang Ong, Yan Liang, Emily Brown, Liuliu Pan, Aster Wardhani, Mithra Korukonda, Carl Brown, Dwayne Dunaway, Edward Zhao, Dan McGuire, Sangsoon Woo, Alyssa Rosenbloom, Brian Filanoski, Rhonda Meredith, Kan Chantranuvatana, Brian Birditt, Hye Son Yi, Erin Piazza, Jason Reeves, John Lyssand, Vik Devgan, Michael Rhodes, Gary Geiss, Joseph Beechem. A complete pipeline for high-plex spatial proteomic profiling and analysis on the cosmxtm spatial molecular imager and atomtm spatial informatics platform. [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 4617.

Abstract 5637: Path to the holy grail of spatial biology: Spatial single-cell whole transcriptomes using 6000-plex spatial molecular imaging on FFPE tissue

Cancer research across drug development, molecular biomarkers, and patient response depends on understanding biology that is dependent on complex interactions between malignant, immune, and stromal cells. To survive clearance mechanisms, a tumor can rely on a myriad of escape strategies, and the microenvironment is architected around the current path of escape. To enable a more comprehensive picture of tumor biology, we have developed the CosMx™ Spatial Molecular Imager (SMI) technology to capture a snapshot of thousands of RNA species resolved subcellularly from a single, standard histopathology slide. Building upon the previously released panels, this study tests a new 6,000-plex panel, the highest RNA plex measured in situ within human tissue, allowing the imputation of a spatial whole transcriptome in the tissue. We performed an ultra-high-plex RNA assay to detect 6,000 targets simultaneously in situ on an FFPE human liver cancer tissue (~1 cm2 area) using the CosMx SMI. This RNA panel covers broad biological areas with special emphasis on oncology, immunology, and signal transduction, such that all cancer researchers can benefit from the direct detection of targets of interest (sans imputation) in intact tissue. Analysis algorithms were developed to allow robust assessments of cell types, cell states, cell-cell interactions, and pathway activation. Imputation based on reference profiles from HCA, TCGA, and other public repositories allows estimation of non-measured transcripts at a ratio of approximately 1:3, compared to the approximate 1:20-1:70 imputations performed previously for spatial data.Thousands of transcripts were simultaneously detected with high sensitivity and specificity on the FFPE liver cancer tissue section at single-cell subcellular resolution. We were able to accurately map known reference profiles from scRNA-seq into this sample while identifying cancer-specific malignant, immune, and stromal cells in this tissue sample using this ultra-high plex RNA panel. In addition, we constructed sample-specific spatial neighborhoods, defined by cell types, cell states, and nearly unlimited sets of biological pathways through the imputed whole transcriptome. Finally, we measured >1,000 ligand-receptor interactions between key cell types of adjacent cells in the tissue, identifying mechanisms for tumor-mediated escape as well as reactive re-architecting of the native stroma which defines the trajectory of cancer’s evolution. Single-cell spatial measurements of gene expression at 6,000 plex from a single FFPE slide has the potential to transform our understanding of tumor biology and facilitate the next advances in cancer research by extracting the highest data density possible from rare specimens collected during patient treatment.

Citation Format: Shanshan He, Michael Patrick, Jason W. Reeves, Patrick Danaher, Julian Preciado, Joseph Phan, Erin Piazza, Zachary Reitz, Lidan Wu, Rustem Khafizov, Haiyan Zhai, Michael Rhodes, David Ruff, Joseph Beechem. Path to the holy grail of spatial biology: Spatial single-cell whole transcriptomes using 6000-plex spatial molecular imaging on FFPE tissue. [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 5637.

A single-nucleus and spatial transcriptomic atlas of the COVID-19 liver reveals topological, functional, and regenerative organ disruption in patients

The molecular underpinnings of organ dysfunction in acute COVID-19 and its potential long-term sequelae are under intense investigation. To shed light on these in the context of liver function, we performed single-nucleus RNA-seq and spatial transcriptomic profiling of livers from 17 COVID-19 decedents. We identified hepatocytes positive for SARS-CoV-2 RNA with an expression phenotype resembling infected lung epithelial cells. Integrated analysis and comparisons with healthy controls revealed extensive changes in the cellular composition and expression states in COVID-19 liver, reflecting hepatocellular injury, ductular reaction, pathologic vascular expansion, and fibrogenesis. We also observed Kupffer cell proliferation and erythrocyte progenitors for the first time in a human liver single-cell atlas, resembling similar responses in liver injury in mice and in sepsis, respectively. Despite the absence of a clinical acute liver injury phenotype, endothelial cell composition was dramatically impacted in COVID-19, concomitantly with extensive alterations and profibrogenic activation of reactive cholangiocytes and mesenchymal cells. Our atlas provides novel insights into liver physiology and pathology in COVID-19 and forms a foundational resource for its investigation and understanding.

A single-nucleus and spatial transcriptomic atlas of the COVID-19 liver reveals topological, functional, and regenerative organ disruption in patients

The molecular underpinnings of organ dysfunction in acute COVID-19 and its potential long-term sequelae are under intense investigation. To shed light on these in the context of liver function, we performed single-nucleus RNA-seq and spatial transcriptomic profiling of livers from 17 COVID-19 decedents. We identified hepatocytes positive for SARS-CoV-2 RNA with an expression phenotype resembling infected lung epithelial cells. Integrated analysis and comparisons with healthy controls revealed extensive changes in the cellular composition and expression states in COVID-19 liver, reflecting hepatocellular injury, ductular reaction, pathologic vascular expansion, and fibrogenesis. We also observed Kupffer cell proliferation and erythrocyte progenitors for the first time in a human liver single-cell atlas, resembling similar responses in liver injury in mice and in sepsis, respectively. Despite the absence of a clinical acute liver injury phenotype, endothelial cell composition was dramatically impacted in COVID-19, concomitantly with extensive alterations and profibrogenic activation of reactive cholangiocytes and mesenchymal cells. Our atlas provides novel insights into liver physiology and pathology in COVID-19 and forms a foundational resource for its investigation and understanding.

Abstract 1364: Spatially resolved T-cell receptor profiling elucidates relationships between TCR diversity, immune infiltration, and cancer-associated pathways

As T-cells mature, genes encoding T-cell receptor (TCR) segments are somatically recombined to generate a diverse repertoire of receptors specific to unique antigens. The resultant TCR diversity, and subsequent clonal expansion events, are critical in understanding the adaptive immune response to pathogens and cancers. While many methods have been developed to determine specific clonotypes and overall TCR diversity present in various tissues, these methods to date have failed to capture spatial orientation and arrangement of T-cells engaging with their microenvironment. Tracking T-cell migration and infiltration into the tumor has thus been limited to post-hoc low-plex profiling methods. To better understand T-cell localization during tumor development, we have developed a TCR profiling panel for the GeoMx® Digital Spatial Profiler that can be combined with the GeoMx Cancer Transcriptome Atlas (CTA) or Human Whole Transcriptome Atlas (WTA). This novel spatial assay enables simultaneous quantification of all functional TCR constant, variable and joining segments in situ along with transcriptome-wide gene expression profiling in spatially defined regions of a tissue. We validated the performance of the TCR probe pool in inflamed tonsil and cell pellet arrays, demonstrating comparable sensitivity and specificity relative to orthogonal methods. We next used the GeoMx TCR spike-in panel to characterize intra- and inter-patient TCR heterogeneity in a cohort of 68 T-cell lymphomas to track clonal interactions between the malignant and non-malignant immune microenvironment. We demonstrate the ability to link the spatial context of TCR segment expression to activation of malignant signaling cascades as well as non-cancerous T-cell response to the presence of other immune cells and cancer-associated signaling. Together, the combination of our TCR spike-in panel with the CTA or WTA illuminates spatial distribution of T-cell clones paving the way for studies to comprehensively link TCR clonality changes to the tumor microenvironment.

FOR RESEARCH USE ONLY. Not for use in diagnostic procedures.

Citation Format: Michelle A. Kriner, Katrina van Raay, Jason W. Reeves, Kit A. Fuhrman, Andrew Klock, Alecksandr Kutchma, Erin Piazza, Joseph Beechem. Spatially resolved T-cell receptor profiling elucidates relationships between TCR diversity, immune infiltration, and cancer-associated pathways [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 1364.

Abstract 2029: Multiomic analysis of whole transcriptome and high plex protein assays on a single FFPE slide

The GeoMx࣪ Digital Spatial Profiler (DSP) enables high-plex, high-throughput spatial profiling and quantification from a single slide for either protein or RNA. To fully understand the interplay between RNA and protein in tissue, we have developed a novel multi analyte assay that allows for the profiling of both analytes from the area of interest (AOI) on a single slide. Here we describe the development and performance of the multi analyte assay on cell pellet array (CPA) and various tissues including tonsil and colorectal cancer (CRC) using a high plex GeoMx Protein Panel and the GeoMx Human Whole Transcriptome Atlas (WTA). We successfully identified conditions to detect RNA and protein simultaneously, with comparable sensitivity and specificity to the single analyte conditions. The data accurately matched cell lines in an unbiased correlation analysis between GeoMx WTA and the entire CCLE RNAseq database. Furthermore, the assay performance was maintained in tissue samples. Tonsil and colorectal cancer biopsies were profiled for RNA (whole transcriptome) and protein from the same AOI, allowing simultaneous measurements of transcriptional and translational regulation of key biological pathways. This multi-analyte profiling enables deeper characterization of precious biological samples that are available in limited quantities.

Citation Format: Shilah Bonnett, Nicholas Confuorto, Kit Fuhrman, Giang Ong, Alyssa Rosenbloom, John Lyssand, Gary Geiss, Joseph Beechem. Multiomic analysis of whole transcriptome and high plex protein assays on a single FFPE slide [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 2029.

Abstract 1424: Prospective validation of a mRNA signature in plasma for the diagnosis of early stage lung cancer

Background: Non-small cell lung cancer (NSCLC) is usually diagnosed at stages IIIB-IV, with a median overall survival that does not exceed two years. In contrast, patients diagnosed at early and locally advanced stages (I-IIIA) can undergo surgery and have a significantly better prognosis. Imaging technologies often detect lung nodules of unknown significance that pose a diagnostic challenge. In a proof-of-concept study, based on a 76-patient cohort, we developed a preliminary mRNA expression signature in plasma that discriminated healthy individuals from early-stage NSCLC patients with AUC=0.98. Here, we aimed to expand the training cohort, to refine the diagnostic signature and to prospectively validate the final signature in the clinical setting.

Methods: Two hundred and thirty individuals with pulmonary nodules suspicious of lung cancer have been enrolled in the training cohort. All of them underwent bronchoscopy, fine needle aspiration, percutaneous or surgical biopsy to confirm the diagnosis. Circulating-free RNA (cfRNA) has been isolated from plasma using an automatic extraction method (Qiasymphony, Qiagen). Purified cfRNA has been quantified using Qubit®, retrotranscribed and pre-amplified with 14 cycles using the Low RNA Input Amplification kit (NanoString Technologies). Gene expression analysis has been performed on the nCounter platform using the PanCancer IO360࣪ panel (NanoString Technologies), which can detect 770 transcripts related to tumor biology, micro-environment and the immune system.

Results: One hundred twenty-six patients have been analyzed so far; plasma samples have been successfully analyzed by nCounter in all cases. Ongoing analysis reveal differential patterns of gene expression in early-stage NSCLC patients versus non-cancer individuals. Using a bioinformatics recursive feature elimination algorithm, we have selected a diagnostic signature with an area under the ROC curve of 0.89. The signature scores derived from the algorithm are significantly different between the non-cancer and NSCLC cases. Final results of the training and validation cohort will be presented at the meeting

Conclusions: Plasma RNA expression signatures can be a useful tool to guide clinical decision in patients with pulmonary nodules suspicious of malignancy, orienting towards surgery or observation.

Citation Format: Ana María Giménez Capitán, Pablo Rubisntein, Andrés Aguilar-Hernández, María González-cao, Irene Moya, Santiago Viteri, Carlos Cabrera, Santiago Ramón y Cajal, Karina Loor, Mario Culebras, Irene Sansano, Federico Rubisntein, Joselyn Valarezo, Clara Mayo-de las-Casas, Carlos Pedraz, Joseph Beechem, Sarah Warren, Rafael Rosell, Miguel Ángel Molina-Vila. Prospective validation of a mRNA signature in plasma for the diagnosis of early stage lung cancer [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 1424.

Abstract 3878: Subcellular characterization of over 100 proteins in FFPE tumor biopsies with CosMx Spatial Molecular Imager

The spatial interactions between the immune system and tumor cells greatly influence antitumoral immunity. Characterization of immune cell composition and infiltration within the tumor niche informs prognosis, drug delivery efficiency, and therapeutic efficacy. However, few methods exist to query large numbers of immune biomarkers at subcellular spatial resolution. The CosMx™ Spatial Molecular Imager is the first platform to demonstrate simultaneous single-cell and subcellular detection of over 100 proteins on standard, biobanked, FFPE tissue samples. This high-plex protein panel detects key drivers of cancer progression and immune cell activation states. Here, we apply the CosMx 100-plex immuno-oncology assay on a set of breast cancer biopsies and demonstrate its quantitative and spatial capabilities. Key to CosMx protein technology is an antibody-oligonucleotide-conjugate 64-bit encoding method, not a cyclic exchange method. The encoding scheme is enabled by a 20nm hybridization-based optical barcode. The CosMx system uses a fully automated, cyclic microfluidics imaging system, high-resolution optics and 3D capability. The raw cyclic encoded 4-color tissue images are decoded using a robust automated decoding algorithm that detects protein sub-cellular localization and quantifies expression level. CosMx SMI produces protein localization maps for each target, which characterizes tissue microenvironment heterogeneity while providing spatial information. Additionally, accurate segmentation of individual cells enables spatial single-cell protein expression analysis, facilitating further mining and analyses of cellular subpopulations. The CosMx protein assay reagents were validated on multi-organ FFPE tissue microarrays and 35 human FFPE cell lines, including overexpression lines for key targets and cellular activation states, such as GITR, CD278, PD-L1, and PD-1. Benchmarking to multiple orthogonal datasets (e.g., the Human Protein Atlas, Cancer Cell Line Encyclopedia, and low-plex IHC) demonstrates that the assay is highly sensitive and specific. CosMx SMI protein assay can be coupled with SMI’s 1000-plex RNA-detection assay; together, such a multi-omics platform can generate an unprecedented information-rich view of spatial biology that could usher in novel discoveries about health and disease. FOR RESEARCH USE ONLY. Not for use in diagnostic procedures.

Citation Format: Zachary R. Lewis, Tien Phan-Everson, Gary Geiss, Mithra Korukonda, Ruchir Bhatt, Carl Brown, Dwayne Dunaway, Joseph Phan, Alyssa Rosenbloom, Brian Filanoski, Rhonda Meredith, Kan Chantranuvatana, Yan Liang, Emily Brown, Brian Birditt, Giang Ong, Hye Son Yi, Erin Piazza, Vikram Devgan, Nicole Ortogero, Patrick Danaher, Sarah Warren, Michael Rhodes, Joseph Beechem. Subcellular characterization of over 100 proteins in FFPE tumor biopsies with CosMx Spatial Molecular Imager [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 3878.

High-Plex Spatial RNA Profiling Reveals Cell Type‒Specific Biomarker Expression during Melanoma Development

Early diagnosis of melanoma is critical for improved survival. However, the biomarkers of early melanoma evolution and their origin within the tumor and its microenvironment, including the keratinocytes, are poorly defined. To address this, we used spatial transcript profiling that maintains the morphological tumor context to measure the expression of >1,000 RNAs in situ in patient-derived formalin-fixed, paraffin-embedded tissue sections in primary melanoma and melanocytic nevi. We profiled 134 regions of interest (each 200 μm in diameter) enriched in melanocytes, neighboring keratinocytes, or immune cells. This approach captured distinct expression patterns across cell types and tumor types during melanoma development. Unexpectedly, we discovered that S100A8 is expressed by keratinocytes within the tumor microenvironment during melanoma growth. Immunohistochemistry of 252 tumors showed prominent keratinocyte-derived S100A8 expression in melanoma but not in benign tumors and confirmed the same pattern for S100A8's binding partner S100A9, suggesting that injury to the epidermis may be an early and readily detectable indicator of melanoma development. Together, our results establish a framework for high-plex, spatial, and cell type‒specific resolution of gene expression in archival tissue applicable to the development of biomarkers and characterization of tumor microenvironment interactions in tumor evolution.

50 In-situ visualization and measurement of tumor-infiltrating lymphocytes (TILs) on intact FFPE renal cell carcinoma (RCC) tissue using the spatial molecular imager (SMI)

Background

Although cancer immunotherapies can effectively restore T cell-mediated immunity leading to sustained clinical responses, these responses are unpredictable partly due to highly heterogeneous phenotypes of tumor-infiltrating lymphocytes (TILs) between patients. Thus, understanding such TILs and their roles in the context of tumor microenvironments (TME) may lead to developing better immunotherapy solutions. The spatial molecular imager (SMI) is a novel spatial transcriptomics platform that allows spatially resolved high-dimensional cellular phenotyping for comprehensive TIL profiling. SMI uses fluorescent molecular barcodes to enable in-situ measurement of biological targets on an intact tissue sample. Here, we characterize comprehensive TIL phenotypes and visualize landscape of TILs directly on intact formalin-fixed paraffin-embedded (FFPE) tissues using a 1000+-plex RNA panel.

Methods

To build multi-omics TIL profiling data sets for renal cell carcinoma (RCC) tissues, we employed scRNA-seq, mass cytometry (CyTOF) and SMI. Peripheral blood mononuclear cells and dissociated cells from matched RCC tumor and adjacent normal tissues were analyzed by CyTOF and single-cell sequencing. Then, SMI profiling of matching FFPE tissues was used to visualize TILs in the context of the TME and to understand relationships between high-dimensional cellular heterogeneity and the spatial organization of cells within a tumor tissue.

Results

CyTOF and scRNA-seq analysis of dissociated cells was used to determine the gene expression profiles of numerous cellular subsets. TCR sequencing was also used to assess the extent of clonal expansion and clonotypic relationships between blood and tumor. Consistent with our previous reports, T cell populations could be segregated based on markers associated with chronic T cell receptor signaling and many T cells with an exhausted phenotype were clonally expanded in the tumor but not the blood. In contrast, T cell clonotypes with bystander phenotypes in the tumor were readily detected as expanded clones in the blood, supporting notion that not all tumor-infiltrating T cells are specific for tumor antigens. SMI analysis of matched tumor tissue was used to accurately quantify the densities and to determine the spatial organization of all T cell subsets. In addition, computational methods were used to describe distinct cellular niches within tumors with accurately defined cellular compositions.

Conclusions

High dimensional cellular profiling highlights the abundance of bystander T cell infiltration of RCC tumors. Comprehensive spatial profiling by SMI provides spatial context to the highly diverse immune cell composition of tumor infiltrates.

Ethics Approval

Fully anonymous human material was obtained from Northwest Biotrust and given IRB designation of non-human subjects research.

Abstract 94: Multi-compartment reprogramming and spatially-resolved interactions in frozen pancreatic cancer with and without neoadjuvant chemotherapy and radiotherapy at single-cell resolution

A molecular classification of pancreatic ductal adenocarcinoma (PDAC) that informs clinical management remains elusive. Previously identified bulk expression subtypes in the untreated setting were influenced by contaminating stroma whereas single cell RNA-seq (scRNA-seq) of fresh tumors under-represented key cell types. Two consensus subtypes have arisen from these prior efforts: (1) classical-like, and (2) basal-like. Basal-like tumors were associated with worse survival in the metastatic setting but attempts to refine this binary classification have failed to further stratify patient survival. Here, we developed a robust single-nucleus RNA-seq (snRNA-seq) technique for banked frozen PDAC specimens and studied a cohort of untreated resected primary tumors (n ~ 20). Gene expression programs learned across malignant cell and cancer-associated fibroblast (CAF) profiles uncovered a clinically-relevant molecular taxonomy with improved prognostic stratification compared to prior classifications. Digital spatial profiling revealed an association between malignant cells expressing basal-like programs and greater immune infiltration with relatively fewer macrophages, whereas those exhibiting classical-like programs were linked to inflammatory CAFs and macrophage-predominant microniches. Recent clinical trials have supported the increasing adoption of neoadjuvant therapy to aggressively address the risk of micro-metastatic spread and to circumvent concerns of treatment tolerance in the postoperative setting. There is an urgent need to understand how preoperative treatment impacts residual tumor cells and their interactions with other cell types in the tumor microenvironment to identify additional therapeutic vulnerabilities that can be exploited. Towards this end, we performed snRNA-seq on an unmatched cohort of neoadjuvant-treated resected primary tumors (n ~ 25) with most cases involving FOLFIRINOX chemotherapy followed by chemoradiation. Remarkably, the quality of single-nucleus mRNA profiles was comparable between heavily pre-treated and untreated specimens. We identified differentially expressed genes between treated and untreated samples to infer cell-type specific reprogramming in the residual tumor. This analysis revealed that in the neoadjuvant treatment context, there was lower expression of classical-like phenotypes in malignant cells in favor of basal-like phenotypes associated with TNF-NFkB and interferon signaling as well as the presence of novel acinar and neuroendocrine classical-like states. Our refined molecular taxonomy and spatial resolution may help advance precision oncology in PDAC through informative stratification in clinical trials and insights into compartment-specific therapies.

Citation Format: William L. Hwang, Karthik A. Jagadeesh, Jimmy A. Guo, Hannah I. Hoffman, Payman Yadollahpour, Jason Reeves, Eugene Drokhlyansky, Nicholas Van Wittenberghe, Samouil Farhi, Denis Schapiro, George Eng, Jason M. Schenkel, William A. Freed-Pastor, Orr Ashenberg, Clifton Rodrigues, Domenic Abbondanza, Toni Delorey, Devan Phillips, Jorge Roldan, Debora Ciprani, Marina Kern, Jaimie L. Barth, Daniel R. Zollinger, Kit Fuhrman, Robin Fropf, Joseph Beechem, Colin Weekes, Cristina R. Ferrone, Jennifer Y. Wo, Theodore S. Hong, Orit Rozenblatt-Rosen, Andrew J. Aguirre, Mari Mino-Kenudson, Carlos Fernandez-del- Castillo, Andrew S. Liss, David T. Ting, Tyler Jacks, Aviv Regev. Multi-compartment reprogramming and spatially-resolved interactions in frozen pancreatic cancer with and without neoadjuvant chemotherapy and radiotherapy at single-cell resolution [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 94.

COVID-19 tissue atlases reveal SARS-CoV-2 pathology and cellular targets

COVID-19, which is caused by SARS-CoV-2, can result in acute respiratory distress syndrome and multiple organ failure^1-4, but little is known about its pathophysiology. Here we generated single-cell atlases of 24 lung, 16 kidney, 16 liver and 19 heart autopsy tissue samples and spatial atlases of 14 lung samples from donors who died of COVID-19. Integrated computational analysis uncovered substantial remodelling in the lung epithelial, immune and stromal compartments, with evidence of multiple paths of failed tissue regeneration, including defective alveolar type 2 differentiation and expansion of fibroblasts and putative TP63⁺ intrapulmonary basal-like progenitor cells. Viral RNAs were enriched in mononuclear phagocytic and endothelial lung cells, which induced specific host programs. Spatial analysis in lung distinguished inflammatory host responses in lung regions with and without viral RNA. Analysis of the other tissue atlases showed transcriptional alterations in multiple cell types in heart tissue from donors with COVID-19, and mapped cell types and genes implicated with disease severity based on COVID-19 genome-wide association studies. Our foundational dataset elucidates the biological effect of severe SARS-CoV-2 infection across the body, a key step towards new treatments.

Spatial proteomic characterization of HER2-positive breast tumors through neoadjuvant therapy predicts response

The addition of HER2-targeted agents to neoadjuvant chemotherapy has dramatically improved pathological complete response (pCR) rates in early-stage, HER2-positive breast cancer. Nonetheless, up to 50% of patients have residual disease after treatment, while others are likely overtreated. Here, we performed multiplex spatial proteomic characterization of 122 samples from 57 HER2-positive breast tumors from the neoadjuvant TRIO-US B07 clinical trial sampled pre-treatment, after 14-21 d of HER2-targeted therapy and at surgery. We demonstrated that proteomic changes after a single cycle of HER2-targeted therapy aids the identification of tumors that ultimately undergo pCR, outperforming pre-treatment measures or transcriptomic changes. We further developed and validated a classifier that robustly predicted pCR using a single marker, CD45, measured on treatment, and showed that CD45-positive cell counts measured via conventional immunohistochemistry perform comparably. These results demonstrate robust biomarkers that can be used to enable the stratification of sensitive tumors early during neoadjuvant HER2-targeted therapy, with implications for tailoring subsequent therapy.

Inter- and intra-tumor heterogeneity of metastatic prostate cancer determined by digital spatial gene expression profiling

Metastatic prostate cancer (mPC) comprises a spectrum of diverse phenotypes. However, the extent of inter- and intra-tumor heterogeneity is not established. Here we use digital spatial profiling (DSP) technology to quantitate transcript and protein abundance in spatially-distinct regions of mPCs. By assessing multiple discrete areas across multiple metastases, we find a high level of intra-patient homogeneity with respect to tumor phenotype. However, there are notable exceptions including tumors comprised of regions with high and low androgen receptor (AR) and neuroendocrine activity. While the vast majority of metastases examined are devoid of significant inflammatory infiltrates and lack PD1, PD-L1 and CTLA4, the B7-H3/CD276 immune checkpoint protein is highly expressed, particularly in mPCs with high AR activity. Our results demonstrate the utility of DSP for accurately classifying tumor phenotype, assessing tumor heterogeneity, and identifying aspects of tumor biology involving the immunological composition of metastases.

The inter- and intra-tumor heterogeneity of metastatic prostate cancer (mPC) is underexplored. Here the authors use Digital Spatial Profiling to study gene and protein expression heterogeneity in 27 mPC patients, finding variation in associated pathways and potential immunotherapy targets.

A single-cell and spatial atlas of autopsy tissues reveals pathology and cellular targets of SARS-CoV-2

The SARS-CoV-2 pandemic has caused over 1 million deaths globally, mostly due to acute lung injury and acute respiratory distress syndrome, or direct complications resulting in multiple-organ failures. Little is known about the host tissue immune and cellular responses associated with COVID-19 infection, symptoms, and lethality. To address this, we collected tissues from 11 organs during the clinical autopsy of 17 individuals who succumbed to COVID-19, resulting in a tissue bank of approximately 420 specimens. We generated comprehensive cellular maps capturing COVID-19 biology related to patients' demise through single-cell and single-nucleus RNA-Seq of lung, kidney, liver and heart tissues, and further contextualized our findings through spatial RNA profiling of distinct lung regions. We developed a computational framework that incorporates removal of ambient RNA and automated cell type annotation to facilitate comparison with other healthy and diseased tissue atlases. In the lung, we uncovered significantly altered transcriptional programs within the epithelial, immune, and stromal compartments and cell intrinsic changes in multiple cell types relative to lung tissue from healthy controls. We observed evidence of: alveolar type 2 (AT2) differentiation replacing depleted alveolar type 1 (AT1) lung epithelial cells, as previously seen in fibrosis; a concomitant increase in myofibroblasts reflective of defective tissue repair; and, putative TP63+ intrapulmonary basal-like progenitor (IPBLP) cells, similar to cells identified in H1N1 influenza, that may serve as an emergency cellular reserve for severely damaged alveoli. Together, these findings suggest the activation and failure of multiple avenues for regeneration of the epithelium in these terminal lungs. SARS-CoV-2 RNA reads were enriched in lung mononuclear phagocytic cells and endothelial cells, and these cells expressed distinct host response transcriptional programs. We corroborated the compositional and transcriptional changes in lung tissue through spatial analysis of RNA profiles in situ and distinguished unique tissue host responses between regions with and without viral RNA, and in COVID-19 donor tissues relative to healthy lung. Finally, we analyzed genetic regions implicated in COVID-19 GWAS with transcriptomic data to implicate specific cell types and genes associated with disease severity. Overall, our COVID-19 cell atlas is a foundational dataset to better understand the biological impact of SARS-CoV-2 infection across the human body and empowers the identification of new therapeutic interventions and prevention strategies.

Abstract 1364: Spatially-resolved in situ expression profiling using the GeoMx™ Cancer Transcriptome Atlas panel in FFPE tissue

The emerging field of spatial genomics represents a significant advance for biology. To drive new discoveries in spatial genomics and immuno-oncology, we introduce the GeoMx Cancer Transcriptome Atlas (CTA) Panel for comprehensive spatial analysis of cancer pathways using the Nanostring GeoMx Digital Spatial Profiler (DSP). We demonstrate profiling of 1600+ immuno-oncology targets in the tumor, microenvironment, and immune compartments of archival FFPE tissue sections, coupled to downstream Next Generation Sequencing (NGS) readout to enable high-throughput workflows. High-plex spatial RNA molecular profiling with GeoMx CTA was performed as follows:

1. Photocleavable DNA oligonucleotides tags were coupled to 8000+ in situ hybridization probes targeting 1600+ genes. These reagents were allowed to bind targets directly on slide-mounted FFPE tissue sections.

2. ROIs were identified and selected using GeoMx DSP, and ROI-specific oligonucleotide tags were released using ultraviolet exposure.

3. Released oligonucleotide tags from each ROI were collected and deposited into designated wells on a microtiter plate, allowing well indexing of each ROI during NGS library preparation.

4. After indexing, the entire plate was pooled into a single tube for purification and then sequenced on an Illumina instrument.

5. NGS reads were processed into digital counts and mapped back to each ROI, generating a map of transcript activity within the tissue architecture.

We compared data from experiments in which bulk RNA-seq and GeoMx DSP using the CTA Panel were performed on the same samples. Overall, we found good correlation between pseudo-bulk GeoMx CTA (sum of ROIs) and RNA-seq from the same tissue specimen. Individually, however, each ROI showed a distinct expression pattern from bulk, and ROI expression patterns clustered based on similar tissue morphology. Importantly, GeoMx CTA was able to detect a higher number of genes with low expression within the microenvironment and immune spatial compartment compared to bulk RNA-seq, providing a detailed look at the anti-tumor immune response. Lastly, we profiled similar tissues using a novel 18000+ gene whole transcriptome panel and found further enrichment of low-expressers relative to RNA-seq, revealing novel spatial biology previously masked by bulk assays. Together, these data demonstrate that GeoMx offers high sensitivity for genome-scale expression profiling while preserving critical information about tissue architecture. GeoMx DSP technology is for Research Use Only and not for use in diagnostic procedures.

Citation Format: Margaret L. Hoang, Michelle Kriner, Zoey Zhou, Zach Norgaard, Kristina Sorg, Chris Merritt, Erin Piazza, Marty Ross, Robin Fropf, Nileshi Saraf, Patrick Danaher, Michael Rhodes, Joseph Beechem. Spatially-resolved in situ expression profiling using the GeoMx™ Cancer Transcriptome Atlas panel in FFPE tissue [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 1364.

Abstract 840: Pathway enrichment analysis of gene expression data from formalin-fixed paraffin embedded (FFPE) samples using the GeoMx™ DSP Platform

The GeoMx Digital Spatial Profiling (DSP) Platform enables robust detection of high-plex protein and RNA expression from user-defined sections within FFPE samples. As the number of targets detected within such tissues increases, it becomes important to apply systems biology strategies in order to better interpret the complex biology of the tumor microenvironment.

In this study, we investigated the expression profiles of more than 1600 genes by utilizing more than 10,000 DSP-specific in situ hybridized (ISH) probes on FFPE samples. The bioinformatics tools we have development are enabling us to move beyond single-gene profiling to a better understanding of pathway-based expression. Our study includes colorectal cancer patient samples from which we have matching bulk RNA sequencing and NanoString analysis to compare. The panel of genes profiled have a strong focus around capturing biological signaling along canonical signaling pathways and cell-intrinsic signaling from immune cells and other cell types. We demonstrate the ability to leverage foundational pathway interrogation tools, including Reactome, with the data to capture spatially-resolved pathway interactions and signaling within FFPE tissues.

As we look towards the future of the GeoMx platform and high-plex RNA profiling of tissue samples, these experiments highlight not only the need but the capacity for this platform to derive deep understanding of the biology within and across a single slide of tissue. These experiments are being used to drive development of the software features within the GeoMx ecosystem, which will provide further support for pathway-level exploration of expression when working with highly multiplexed reagents in future platform offerings.

GeoMx™ DSP technology is for Research Use Only and not for use in diagnostic procedures.

Citation Format: Tressa R. Hood, Jason Reeves, Zach Norgaard, Margaret Hoang, Sarah Warren, Erin Piazza, Rich Boykin, Joseph Beechem. Pathway enrichment analysis of gene expression data from formalin-fixed paraffin embedded (FFPE) samples using the GeoMx™ DSP Platform [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 840.

Abstract 2825: High-plex, spatial RNA profiling of tumor infiltrating leukocytes and the tumor microenvironment of microsatellite instable colorectal cancer using GeoMx™ Digital Spatial Profiler

Immunotherapeutic intervention has revolutionized cancer treatment but improved understanding of immunomodulation in tumors is still necessary to expand the reach of these therapies and identify rational combination approaches. An important aspect of this process will be characterizing the molecular differences between tumor-infiltrating leukocytes (TILs) and stromal leukocytes (non-TILs) surrounding the same tissues. Most studies to date have focused on dissociated tissues, which means identifying the origin of the profiled leukocytes is only possible with post-hoc inference. High-plex profiling that retains spatial orientation has proven difficult in fixed tissues, preventing direct understanding of TIL localization beyond a handful of pre-selected targets. To explore the transcriptional profile of TILs in situ, we leveraged a high-plex (1,400+ gene) mRNA panel for the GeoMxTM Digital Spatial Profiler (DSP) to profile microsatellite instable (MSI) colorectal cancer (CRC) samples noted to have a high abundance of CD3+ TILs by 4-color immunofluorescence (IF).

In this study, more than 5,000 unique probes (3 to 10 probes per target mRNA) with coupled photocleavable oligonucleotide tags were hybridized to formalin-fixed paraffin-embedded (FFPE) tissue sections from these CRC samples. Regions of interest were selected inside (n = 6, per tumor) and outside (n = 6, per tumor) the tumor invasive margin focusing on tumor or stromal regions with high numbers of CD3+ cells. Within each region of interest, we created a custom segmentation strategy to specifically illuminate CD3+ cells, and then sequentially illuminate regions neighboring those cells. These additional custom masks (n = 47) were defined by extending multiple contours around the initially selected TILs and non-TILs to determine differences in the local environment of each population.

Collected photocleaved oligonucleotide tags were sequenced using the GeoMxTM NGS workflow. Targets included in the 1,400+ gene panel represent immune cell markers, checkpoint molecules, cytokines and chemokines, canonical cancer pathways, and biological signatures. We found that regions neighboring TILs express higher levels of known oncogenic pathways and stromal regions neighboring non-TILs were noted to have higher expression of ECM genes, confirming the specificity of the profiling approach. Furthermore, we found that TILs specifically up-regulate expression of cytolytic pathway genes, as well as several coinhibitory and costimulatory checkpoint genes. We also observe dysregulation of members of the adenosine metabolism pathway within the tumor regions profiled and TILs, but not in regions adjacent to the tumor itself. Together, our results demonstrate the feasibility of profiling specific cell populations with a high plex mRNA panel in situ in FFPE tissue, thus enabling pathway level differential expression analyses and exploration of key interactions between neighboring cell types while retaining their spatial context. For research use only. Not for use in diagnostic procedures.

Citation Format: Zachary Norgaard, Dan Zollinger, Jason Reeves, Zoey Zhou, Michelle Kriner, Jill McKay-Fleisch, Arya Bahrami, Sarah Warren, Sarah Church, Chris Merritt, Margaret Hoang, Joseph Beechem. High-plex, spatial RNA profiling of tumor infiltrating leukocytes and the tumor microenvironment of microsatellite instable colorectal cancer using GeoMx™ Digital Spatial Profiler [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 2825.

Abstract P4-10-12: Characterizing the tumor and immune microenvironment through treatment to predict response to neoadjuvant HER2-targeted therapy using the Digital Spatial Profiler

Background: While introduction of HER2-targeted therapies has dramatically improved outcomes for patients with HER2-positive disease, even with the addition of HER2-targeted agents, 40-50% of patients do not achieve a pCR (pathologic complete response) following neoadjuvant therapy implying that clinical or molecular differences may be present in responders versus non-responders. While recent bulk expression studies have identified several biomarkers associated with response to HER2-targeted therapies in the neoadjuvant setting, these studies are limited in their ability to assign observed changes to specific geographic or phenotypic cell populations, such as the malignant tumor core or the surrounding microenvironment.

Methods: Here we used the Digital Spatial Profiler (DSP, NanoString Technologies, Inc.) to profile regions-of-interest containing pancytokeratin (panCK)+ tumor cells and infiltrated immune cells that are co-localized with the tumor cells. Using this technology, we assayed archival tissue from 28 patients with HER2-positive breast cancer from the TRIO-B07 (NCT00769470) clinical trial, who were treated with trastuzumab, lapatinib, or both, followed by standard chemotherapy plus HER2-targeted therapy. Tissue specimens were collected from the pre-treatment diagnostic biopsy (Baseline) and after one cycle of targeted therapy (Runin). To study regional heterogeneity, we selected an average of four panCK-enriched tissue regions from each sample. Using DSP, we performed multiplexed quantification of 38 tumor and immune protein markers and 96 RNA markers on the selected tissue regions and compared our findings to bulk mRNA expression data from the same cohort.

Results: Within the panCK-enriched regions, DSP revealed significant treatment-associated decreases in HER2 protein levels and the downstream PI3K-Akt signaling pathway in Runin compared to Baseline samples. In tandem, we observed a significant increase in infiltrating leukocytes, with CD45, a pan-leukocyte marker, and CD8, a marker for T cells that mediate tumor cell killing, showing the most dramatic changes. These changes in Runin compared to Baseline were more significant in the subset of cases that achieved a pCR versus those that do not, independent of ER status. Comparison of Runin samples to matched Baseline samples from the same patient enabled improved prediction of patient outcome (pCR) compared with analysis of a single timepoint alone. We also found that the DSP panCK enrichment strategy captures additional signal not observed in bulk expression data. For instance, using bulk expression, a decrease in HER2 RNA levels between Baseline and Runin was evident but there was no difference in the degree of decrease in HER2 mRNA between pCR and no pCR cases. Using DSP, we observed that the significant decrease in HER2 levels at Runin is more pronounced in cases that achieved a pCR. Across both tumor and immune markers, regional heterogeneity increased at Runin compared to Baseline.

Conclusions: In this study, we used DSP and a panCK enrichment strategy to retrospectively delineate the changes that occurred in tumor cells and co-localized immune cells during HER2-targeted therapy. In comparison to traditional or multiplexed IHC, DSP allows for simultaneous profiling of a large number of markers, enabling the characterization of multiple cancer signaling pathways and immune markers on a single tissue specimen. This study demonstrates the utility of pancytokeratin-enriched spatial proteomic profiling to characterize treatment-associated changes and identify predictive biomarkers.

NanoString’s Digital Spatial Profiler is for Research Use Only. Not to be used for diagnostic procedures.

Citation Format: Katherine Lee McNamara, Jennifer L. Caswell-Jin, Zhicheng Ma, Jason J. Zoeller, Michelle Kriner, Zoey Zhou, Jason Reeves, Margaret Hoang, Joseph Beechem, Dennis J. Slamon, Michael F. Press, Joan Brugge, Sara A. Hurvitz, Christina Curtis. Characterizing the tumor and immune microenvironment through treatment to predict response to neoadjuvant HER2-targeted therapy using the Digital Spatial Profiler [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P4-10-12.

Simultaneous detection of genotype and phenotype enables rapid and accurate antibiotic susceptibility determination

Multidrug resistant organisms (MDROs) are a serious threat to human health^1,2. Fast, accurate antibiotic susceptibility testing (AST) is a critical need in addressing escalating antibiotic resistance, since delays in identifying MDROs increase mortality^3,4 and use of broad-spectrum antibiotics, further selecting for resistant organisms. Yet current growth-based AST assays, such as broth microdilution⁵, require several days before informing key clinical decisions. Rapid AST would transform the care of infected patients while ensuring that our antibiotic arsenal is deployed as efficiently as possible. Growth-based assays are fundamentally constrained in speed by doubling time of the pathogen, and genotypic assays are limited by the ever-growing diversity and complexity of bacterial antibiotic resistance mechanisms. Here, we describe a rapid assay for combined Genotypic and Phenotypic AST through RNA detection, GoPhAST-R, that classifies strains with 94–99% accuracy by coupling machine learning analysis of early antibiotic-induced transcriptional changes with simultaneous detection of key genetic resistance determinants to increase accuracy of resistance detection, facilitate molecular epidemiology, and enable early detection of emerging resistance mechanisms. This two-pronged approach provides phenotypic AST 24–36 hours faster than standard workflows, with <4 hour assay time on a pilot instrument for hybridization-based multiplexed RNA detection implemented directly from positive blood cultures.

Abstract 753: In situ RNA expression profiling of 1600+ immuno-oncology targets in FFPE tissue using NanoString GeoMx™Digital Spatial Profiler

Clinical specimens including formalin-fixed, paraffin embedded (FFPE) tumor sections preserve spatial and molecular information of tumor cells and their surrounding microenvironment. This valuable spatial information is loss with bulk RNA-seq, the most prevalent method for gene expression profiling of archival FFPE samples. In contrast, the NanoString GeoMx™ Digital Spatial Profiler (DSP) is a high multiplexing assay that can profile thousands of RNAs from user selectable regions of interest (ROIs) in FFPE sections. Here we introduce a 1600+ gene panel of tumor, stroma, and immune cell-specific content derived from NanoString nCounter® PanCancer series. We compare RNA profiling using our 1600+ immune-oncology panel to the RNA-seq methodology in FFPE samples. DSP RNA in situ probes are photocleavable oligonucleotides tags coupled to hybridization sequences that bind to mRNA transcripts in the FFPE tissue section. We gridded 96 ROIs upon the FFPE section, photocleaved oligonucleotide tags from each ROI were collected and prepared into sequencing libraries with our NGS readout workflow. After sequencing, reads were charted back to each ROI in the tissue section, generating a map of transcript activity within the tissue. We found high concordance between “bulk” DSP RNA (counts from all 96 gridded ROIs) and RNA-seq from the same FFPE block. Individually, however, each ROI showed different expression patterns than bulk and ROI expression patterns clustered based on similar tissue morphology. We further profiled the tumor and microenvironment compartments from multiple FFPE cancer tissues, comparing our 1600+ RNA expression profile to RNA-seq. DSP was able to detect a higher number of genes with low expression within each spatial compartment compared to bulk RNA-seq. These data demonstrate that DSP offers unparalleled sensitivity for large-scale gene expression while preserving critical information about tissue architecture. GeoMx™ DSP technology is for Research Use Only and not for use in diagnostic procedures.

Citation Format: Margaret Hoang, Zoey Zhou, Michelle Kriner, Kristina Sorg, Zach Norgaard, Erin Piazza, Chris Merritt, Dae Kim, Joseph Beechem. In situ RNA expression profiling of 1600+ immuno-oncology targets in FFPE tissue using NanoString GeoMx™Digital Spatial Profiler [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 753.

Abstract 2798: High density of CD68+HLA-DR- macrophages in the stroma of primary melanoma correlates with an unfavorable immune microenvironment as assessed by Digital Spatial Profiling

Introduction: The role of macrophages (Mϕ) in melanoma progression is controversial, as they have been shown to both favor and inhibit anti-tumor immunity. Density of Mϕ at the leading tumor edge has been shown to be a marker of poor prognosis. In previous work, we used quantitative multiplexed immunofluorescence (qmIF) to discover the ratio of CD8+ T lymphocytes (CTLs) to CD68+ Mϕ in the peritumoral stroma predicts a favorable prognosis. Further, we found that increased proximity of HLA-DR- Mϕ to CTLs in the stroma predicts poor prognosis. These findings highlight the importance of the location of Mϕ within the tumor microenvironment (TME). Here, we further analyze and compare the TME of patients with high and low stromal densities of HLA-DR- Mϕ.

Methods: From a cohort of 104 patients with primary stage II-III melanoma and known survival information, we selected 8 patients for Digital Spatial Profiling (DSP) analyses. Of this subcohort, 4 patients had a high density of HLA-DR- Mϕ and close proximity of HLA-DR- Mϕ to CTLs in the stroma while the other 4 had a high CTL to Mϕ ratio with low HLA-DR- Mϕ density, as determined by qmIF (methods published). FFPE slides were stained with antibodies conjugated to UV-photocleavable DNA barcodes and specific to 34 proteins, including CD45, CD4, CD8, CD68, PD-1, and PD-L1. Twelve regions of interest (ROIs) per patient were selected based on high Mϕ density as determined by qmIF. ROIs were then analyzed using UV excitation, which releases DNA barcodes for downstream quantitation on the nanoString nCounter® platform. Protein expression was compared between patients and statistical analysis performed using Mann-Whitney test.

Results: We found that ROIs from patients with higher density of HLA-DR- Mϕ had a lower immune infiltration overall as assessed by quantitation of CD45 per ROI (p&lt;0.0001). As expected, the ratio of CD68 to CD45 was higher in these patients than in patients with lower density of HLA-DR- Mϕ (p&lt;0.0001). Interestingly, patients with higher density of HLA-DR- Mϕ also had a significantly higher ratio of CD4 to CD45 (p&lt;0.0001), but a similar CD8A to CD45 ratio. Patients with a higher HLA-DR- Mϕ density had a higher CD4 to CD8A ratio (p&lt;0.0001). Further, PD-L1 and PD1 levels per CD45 were significantly higher in patients with higher HLA-DR- Mϕ density (p&lt;0.0001 and p=0.0002, respectively).

Conclusion: Patients with higher densities of HLA-DR- Mϕ in the stroma and increased proximity of HLA-DR- Mϕ to CTLs in the tumor stroma have lower levels of CD45, a higher ratio of CD4 to CD8, and a higher ratio of PDL1 and PD1 to CD45 by assessment of Mϕ-rich areas using DSP. These findings highlight the close relation between Mϕ and the local immune microenvironment in primary stage II-III melanoma.

Citation Format: Emanuelle M. Rizk, Andrew Chen, Andrew M. Silverman, Douglas K. Marks, Raul Rabadan, Kit Fuhrman, Alison VanSchoiack, Yan Liang, Joseph Beechem, Yvonne M. Saenger, Robyn D. Gartrell. High density of CD68+HLA-DR- macrophages in the stroma of primary melanoma correlates with an unfavorable immune microenvironment as assessed by Digital Spatial Profiling [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 2798.

Abstract 146: Multiple modalities of NanoString GeoMx™ Digital Spatial Profiler allow for spatially-resolved, multiplexed quantification of protein and mRNA distribution and abundance

Characterization of the spatial distribution and abundance of proteins and mRNAs with morphological context within tissues enables a better understanding of biological systems in many research areas, including immunology and oncology. However, it has proven difficult to perform such studies in a highly multiplexed manner. To address this unmet need, we have developed a novel optical-barcode based microscope and tissue-sampling platform designed to simultaneously analyze hundreds of proteins or mRNAs on a single FFPE section from distinct tissue spatial regions (GeoMxTM Digital Spatial Profiler, DSP).

Here, we present a series of modalities and associated applications for the GeoMxTM DSP platform and its integrated software. First, geometric profiling can be utilized by drawing automated circles, squares or even manual hand-drawn polygons as regions of interest (ROI) to characterize tissue heterogeneity. Second, gridded profiling offers high resolution unbiased tumor profiling by placing a grid on tissues and separately analyzing each segment in the grid. Third, contour profiling employs concentric rings, or any custom shape at a growing distance from a site of interest. Finally, segment and rare cell profiling exploits fluorophore-conjugated antibodies to profile specific cell types. These techniques can be used to discover drug mechanism of action or immune activation status, as well as to facilitate prediction of treatment response and disease progression or investigation of specific rare cell populations’ molecular profiles.

Using these multiple modalities, we spatially resolve protein and mRNA expression over 30 immune targets on FFPE tissue sections from various organs, including colon and tonsil. We demonstrate multiplexed detection from discrete regions within a tumor (tumor center and immune invasive margin), enabling systematic interrogation of immune activity in FFPE samples. Finally, we present the utility of each modality under different scenarios.

Citation Format: Gokhan Demirkan, Elena Viboch, Chris Merritt, Giang Ong, Kristi Zevin, Kristina Sorg, Lindy Irving, Dwayne Dunaway, Gary K. Geiss, Joseph Beechem. Multiple modalities of NanoString GeoMx™ Digital Spatial Profiler allow for spatially-resolved, multiplexed quantification of protein and mRNA distribution and abundance [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 146.

Analytical Validation of Digital Spatial Profiling - a novel approach for multiplexed characterization of protein distribution and abundance in FFPE tissue sections

Nanostring Technologies’ Digital Spatial Profiling (DSP) technology allows for the simultaneous analysis of 10’s to 100’s of proteins from discrete regions of interest (ROI), providing a morphological context to multiplexed protein analysis. The purpose of this study is to validate an antibody panel designed to characterize key immunology and tumor markers on the DSP platform.

IHC was performed on human FFPE tissues and human cell line pellets to evaluate binding specificity in both unconjugated and oligo-conjugated antibodies. The dynamic range of antibodies was tested using positive and negative FFPE cell pellets at different ratios. Interaction screens were performed to evaluate potential effects of multiplexing antibodies. A tissue microarray (TMA) containing normal and cancer tissues was employed to assess assay robustness.

IHC analysis of antibodies displayed indistinguishable staining patterns for both unconjugated and oligoconjugated antibodies. Mixed-proportion cell pellet assays revealed strong correlations between positive counts and positive cell numbers in an ROI. For example, CD3 displayed a LOD of 4% when assayed using cell pellet mixtures containing CD3+ CCRF-CEM cells and CD3− HEK293T cells. Interaction studies showed similar values for antibodies alone or in combination (R2 &gt; 0.8). TMA hierarchical clustering analysis demonstrated expected patterns for immune and tumor cells across different tissues.

These results demonstrate that indexing oligo conjugation does not interfere with antibody specificity and that these conjugated antibodies are robust reagents for quantification of protein abundance. Continued work on the DSP platform will expand the library of antibodies accessible for profiling.

Abstract 2422: Simultaneous detection of activating somatic DNA mutations and expressed fusion transcripts from lung tumor FFPE samples

Worldwide, lung cancer is the most commonly diagnosed form of cancer with a survival rate among the lowest. Combined, somatic mutations (in the form of SNVs and InDels) and gene fusions, account for the majority of interpretable and actionable genomic alterations. Importantly, this typically requires the analysis of DNA and RNA from limited amounts of FFPE-preserved specimens. Currently, these analyses typically require complex sample pre-processing for assay on separate platforms or separate complex library preparation methods for assessment by high throughput sequencing. To provide a unified and simpler alternative, NanoString’s molecular barcoding technology has been modularized to permit simultaneous digital measurement of cancer-relevant targets that span these two analyte classes. Novel ‘SNV’ probes enable sensitive and specific identification of DNA mutant allele sequences down to a level of detection of ≤ 5% from 5 ng of FFPE-extracted genomic DNA. Fusion transcripts are detected with 5’/3’ imbalance probes and toehold-mediated junction probes. This dual analyte workflow requires just a single 5-10 micron section of FFPE tissue and provides to sample-to-answer results with approximately 5 minutes of hands-on time per sample after nucleic acid extraction.

To demonstrate utility, 37 lung cancer samples were assayed simultaneously with an SNV panel that targets &gt;100 solid tumor somatic mutations and a lung cancer fusion gene panel that provides general evidence of ALK, RET, and ROS1 gene fusion events along with specific detection of 35 unique fusion transcripts that correspond to known break-points. In this particular cohort, 16 samples were positive for activating KRAS SNVs (one of which was also positive for an activating STK11 variant), 3 were positive for activating EGFR mutations including two SNVs and an 18-base InDel and one was positive for an activating KIF5B16:RET12 fusion transcript. Positive mutation calls obtained with the SNV panel could only be confirmed by whole-exome sequencing (average depth of 100X) for 13 of 20 variants detected; however, ultra-deep (average depth of 4400X) targeted sequencing revealed that the 7 additional panel-detected mutations were, in fact, present. Measured against the sequencing datasets, the SNV panel provided 100% sensitivity, specificity, accuracy and precision for all variants present at 5% or greater allele frequency. The KIF5B16:RET12 fusion event was also confirmed by sequencing. Combined, these results show that these two important classes of activating mutations can be readily and efficiently assayed together on a NanoString nCounter® system (for research use only).

Citation Format: A. McGarry Houghton, Gavin Meredith, Julia Kargl, Jill McKay-Fleisch, P. Martin Ross, Anisha Kharkia, Afshin Mashadi-Hossein, Dae Kim, Joseph Beechem. Simultaneous detection of activating somatic DNA mutations and expressed fusion transcripts from lung tumor FFPE samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2422. doi:10.1158/1538-7445.AM2017-2422

Abstract 3377: Simultaneous analysis of the mutational landscape and RNA and protein expression profile of HER2-positive breast cancer using 3D BiologyTM

Background: Understanding heterogeneity within individual breast tumors is key to the ability to predict therapeutic outcome. Molecular heterogeneity is commonly evaluated based on genomic features, including mRNA abundance, gene copy number events, and somatic mutations. The expression profile and activation state of key proteins is widely recognized as another key element in defining tumor heterogeneity. We have taken advantage of NanoString 3D Biology™ technology (for research use only) and curated nCounter Vantage 3DTM Solid Tumor Assay to interrogate a survey panel of HER2-positive breast tumors with the ultimate goal of determining key relationships between multiple genomic and proteomic profiles in individual tumors.

Methods: We analyzed samples from 24 HER2+ breast cancer patients using NanoString technology to quantify the expression profile for over 25 total and phospho signaling proteins, including PI3K/MAPK/EGFR/HER2, 770 mRNA corresponding to 13 canonical cancer pathways, and 104 somatic mutations and small INDELS that are commonly associated with cancer, including 8 known PIK3CA mutations. These analyses were carried out in a matched fresh frozen and FFPE samples on the nCounter paltform. Data were analyzed by nSolver to identify genotype specific expression profiles across the 24 samples.

Results: In our proof-of-concept data set, we successfully demonstrate that NanoString’s 3D biology Technology shows concordance across both FFPE and fresh frozen sample types for DNA, RNA, and protein. NanoString analysis also showed high concordance to gold-standard techniques used to assess genotype and RNA expression profiles. The combination of digital DNA, RNA, and protein data from our HER2+ breast cancer samples yielded potentially actionable data based on mapping of mutational status as the driver of key differences in protein expression and mRNA abundance of the signaling targets profiled. This work sheds new light on HER2+ breast cancer biology and the interplay between genomic and proteomic profiles while setting the stage for future studies that further probe the differences observed in this sample set.

Conclusions: Simultaneous analysis of mutational status (SNV) and expression at the level of both mRNA and protein promises to enable a more detailed view of the relationship between genotype and the biological and clinical behavior of key tumor types. The NanoString Vantage 3DTM Solid Tumor platform provides a rapid, reliable, and economic means of assessing these analytes simultaneously. The application of these analytes to models that make clinically actionable predictions will require additional analyses of large sample cohorts, but such analysis is quite feasible using a variety of sample types.

Acknowledgements: Supported in part by grants from the Breast Cancer Research Foundation and the 26.2 with Donna Foundation.

Citation Format: Sarayna Chumsri, Daniel J. Serie, Brian M. Necela, Jennifer M. Kachergus, Bianca C. Axenfeld, Gokhan Demirkan, Gavin Meredith, P. Martin Ross, Anisha Kharkia, Erin Piazza, Afshin Mashadi-Hossein, Sarah Warren, Sarah A. McLaughlin, Joseph Beechem, Gary Geiss, E. Aubrey Thompson. Simultaneous analysis of the mutational landscape and RNA and protein expression profile of HER2-positive breast cancer using 3D BiologyTM [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3377. doi:10.1158/1538-7445.AM2017-3377

Abstract 5563: 3D Biology™ view of cancer: Simultaneous detection of somatic DNA mutations and expression profiling of genes and signaling proteins from melanoma tumor FFPE samples

Prognosis is favorable in patients with primary localized melanoma but poor in patients with metastatic disease. With more than 76,000 cases expected to be diagnosed in 2016, more precise prognostic technologies and new therapies are needed. Although targeted treatment regimens have been approved in recent years, resistance has emerged in large part due to adaptive response mechanisms and intratumoral heterogeneity. Analysis of tumor samples across multiple molecular platforms will help elucidate the complexities within and across tumors which may underlie response to therapy as well as assist in identifying predictive biomarkers; however, these approaches require significant amounts of sample, time, and resources.

In order to integrate the strengths of analyzing different molecular analytes, we have modularized Nanostring Technologies' molecular barcoding technology to permit simultaneous digital measurement of cancer-associated DNA mutation variants, mRNA expression, and protein expression in one assay from the same sample (3D Biology). Novel nucleotide variant probes enable sensitive and specific identification of DNA mutant allele sequences down to a level of detection of ≤ 5% from 5 ng of FFPE-extracted genomic DNA. Gene expression is measured via unique digital barcoding technology to measure mRNA transcripts, and protein expression and activity (via phosphorylation) is measured by DNA-labeled antibodies. The multi-omic workflow requires only two 5-10 micron sections of FFPE tissue, whereby DNA and RNA are extracted from one section and multiplex digital protein profiling is conducted on the second.

As proof of concept demonstrating the utility of this 3D Biology platform, we have simultaneously analyzed DNA variants, RNA expression, and protein expression using NanoString’s nCounter Vantage 3D™ Solid Tumor Panel on 12 FFPE melanoma tumor samples and one normal tissue from six patients. This sample set included two metastatic tumors from each patient, and in one instance multiple regions from each metastatic site (7 and 2 regions) in order to assess intratumoral heterogeneity. Importantly, this sample set has associated mRNA expression measured using the nCounter® PanCancer Pathways for Human panel as well as whole exome sequencing (WES) data. Somatic variants seen in this latter dataset were compared with the results from the DNA SNV Solid Tumor Panel. Samples with variants that were detected in the nCounter assay but not WES were subjected to deep sequencing for validation. Overall, we show that this multiplex and multi-omic platform has the potential for rapid and sensitive assessment of patient samples that will impact clinical care.

Citation Format: Jinho Lee, Christopher P. Vellano, Gavin Meredith, Jill Mckay-Fleisch, P. Martin Ross, Michael Tetzlaff, Alexandre Reuben, Courtney Hudgens, Jennifer Wargo, Jessica Garber, Andrew White, Joseph Pan, Mike Krouse, Mekala Pansalawatta, Lucas Dennis, Anisha Kharkia, Erin Piazza, Afshin Mashadi-Hossein, Rich Boykin, Nathan Elliott, Brian Filanoski, Gokhan Demirkan, Sarah Warren, Gary Geiss, Dae Kim, Joseph Beechem, Gordon B. Mills. 3D Biology™ view of cancer: Simultaneous detection of somatic DNA mutations and expression profiling of genes and signaling proteins from melanoma tumor FFPE samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 5563. doi:10.1158/1538-7445.AM2017-5563

Abstract 2441: NanoString 3D Biology™ technology: simultaneous digital counting of DNA, RNA and protein

Introduction: Development of improved cancer diagnostics and therapeutics requires detailed understanding of the genomic, transcriptomic, and proteomic profiles in the tumor microenvironment. Current technologies can excel at measuring a single analyte, but it remains challenging to simultaneously collect high-throughput DNA, RNA, and protein data from small samples. We have developed an approach that uses optical barcodes to simultaneously profile DNA, RNA, and protein from as little as 5ng DNA, 25ng RNA, and 250ng protein or just 2 5µm FFPE slides, and simplifies data analysis by generating digital counts for each analyte.

Methods: The approach uses paired capture and reporter oligonucleotide probes and optical barcodes to enumerate up to 800 targets. The platform was initially developed to measure RNA, and we have adapted it to measure DNA single nucleotide variants (SNVs), proteins, and phospho-proteins. SNVs are detected by direct hybridization of sequence discriminating probes to the wild-type and mutant sequence of interest. Proteins are detected via binding of oligonucleotide-conjugated antibodies.

Results: Combinations of DNA, RNA, and protein in biological and experimental contexts. SNV probes are able to detect variant alleles down to 5% abundance within a wild type population and can discriminate variants within mutation hotspots. It was &gt;96% accurate at identifying variants from samples displaying a range of allele frequencies and DNA integrity when benchmarked against next-generation sequencing. Protein detection has been developed for cell surface, cytosolic, and nuclear proteins, as well as phospho-proteins. It was validated against flow cytometry, western blot, and mass spectrometry using cell lines with ectopic target expression and primary cells. To demonstrate concurrent measurement of DNA, RNA, and protein from a single system, BRAFWT or BRAFV600E cell lines were treated with the BRAFV600E inhibitor vemurafenib and the MEK inhibitor trametinib. We measured the allele usage at the BRAFV600 locus, as well as BRAFV600E dependent changes in mRNA expression, protein expression and protein phosphorylation in a single experiment.

Conclusions: 3D Biology has several advantages over other analytical approaches. Direct, single-molecule digital counting allows detection over a broad dynamic range with high reproducibility, often over 98% concordance between technical replicates. The simultaneous interrogation of DNA, RNA, and protein maximizes the amount of data obtained from precious samples and minimizes instrumentation demands by leveraging a single detection platform. The 3D Biology approach allows holistic, digital analysis of biological samples with high specificity and precision. This technology is currently available for research use, but may also have clinical application in the future.

Citation Format: Chris Lausted, Yong Zhou, Jinho Lee, Christopher Vellano, Karina A. Eterovic, Ping Song, Lin-ya Tang, Gloria Fawcett, Tae-Beom Kim, Ken Chen, Gary Geiss, Gavin Meredith, Qian Mei, Gokhan Demirkan, Dwayne Dunaway, Dae Kim, P. Martin Ross, Elizabeth Manrao, Nathan Elliott, Sarah Warren, Christina Bailey, Chung-Ying Huang, Joseph Beechem, Gordon Mills, Leroy Hood. NanoString 3D Biology™ technology: simultaneous digital counting of DNA, RNA and protein [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2441. doi:10.1158/1538-7445.AM2017-2441

Abstract B095: Multiplexed detection of RNA and proteins on the nCounter® platform with low sample input protocol

As our understanding of the immune responses to cancer continues to grow, the need to extract greater amounts of information from ever smaller sample sizes increases. One of the biggest challenges facing the field is to develop a comprehensive understanding of how the immune system responds to a tumor, and multi-omic profiling (DNA, RNA, and protein) is crucial to building a holistic model of tumor immunity. The NanoString nCounter platform has become an important tool in quantifying transcriptional responses from a wide variety of sample types by enabling direct digital counting of up to 800 targets from a single sample using nucleic acid probes that directly hybridize to the RNA sequence of interest and then are quantified with optical barcoding technology. The platform has now been extended to permit quantification of proteins at the same time using primary antibodies conjugated to DNA oligos that hybridize with the barcodes. We have developed new technology that enables characterization of up to 30 proteins and 770 RNA transcripts in key immuno-oncology pathways from a very low amount of starting material - as few as 50,000 cells. NanoString has previously developed the nCounter Vantage RNA:Protein Immune Profiling Panel which allows digital counting of extracellular proteins which facilitates quantitation of multiple immune cell populations and provides information about their activation status. We have now applied this technology to detect intracellular and secreted proteins as well in the new nCounter Vantage RNA:Protein Immune Signaling panel. This panel is able to detect key transcription factors, signaling molecules, and secreted proteins from peripheral blood mononuclear cells (PBMC), dissociated cells, or cell culture. Additionally, we have recently developed a universal cell capture technology that utilizes anti-β2M antibody coupled to magnetic beads to pull down nucleated cells from a large starting volume. As proof of concept, PBMC from a healthy donor were treated with phorbol 12-myristate 13-acetate (PMA) and ionomycin, TNFα, or IFNγ and RNA and protein were characterized with both the Immune Profiling and Immune Signaling panels. nCounter protein detection compared favorably when validated with flow cytometry, and the additional information imparted by simultaneous profiling of the RNA transcriptome enabled mapping of signaling pathways activated by treatment. Furthermore, RNA and protein counts from the low input protocol were representative of counts obtained from higher cell inputs, indicating that no loss or skewing of data resulted from reducing the starting material. This advance in multi-analyte, multiplexed digital molecular profiling will accelerate immuno-oncology research by reducing sample size requirements and may enable the discovery and development of novel immunotherapies and their associated companion diagnostics.

Citation Format: Sarah Warren, Gary Geiss, Brian Burditt, Qian Mei, Alan Huang, Maribeth Eagen, Eduardo Ignacio, Dwayne Dunaway, Lucas Dennis, Joseph Beechem. Multiplexed detection of RNA and proteins on the nCounter® platform with low sample input protocol [abstract]. In: Proceedings of the Second CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; 2016 Sept 25-28; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2016;4(11 Suppl):Abstract nr B095.

Biomarker Development for Cancer Immuno-oncology/Immunotherapy: Simultaneous Digital Counting of Nucleic Acids and Proteins at 800-plex

The ability to measure changes to the DNA, RNA, and protein is crucial to understanding both tumor and immune responses to therapy. NanoString® has pioneered 3D Biology™ – the ability to measure any combination of DNA, RNA, and protein simultaneously using a single detector from a small clinical sample – in order to characterize these complex interactions. Analytes of interest are labeled with fluorescent nucleic acid barcode (via direct hybridization for nucleic acids or antibody conjugated barcodes for protein) and detected via digital counting. This enables quantification of up to 800 analytes from a small sample (50,000 cells for DNA/RNA/protein, or 1–2 5μm FFPE slides for RNA alone). The cancer immunology profiling panel measures 770 mRNAs (unique signatures for 24 infiltrating immune cell types plus extensive immune-signaling pathways) plus 30 key IO proteins.

We present two examples of 3D Biology in action. First, a targeted BRAFV600E inhibitor induces expression changes of immune genes which can be detected at both the RNA and protein levels. Second, in work from ongoing collaborations with the Cancer Immunotherapy Trials Network, clinical samples from patients treated with either mono- or combination immunotherapy can be stratified by gene expression. We also show that gene signatures predict presence of immune cell populations with a high degree of concordance to flow cytometry and immunohistochemistry measurements.

Multiplexed RNA biomarkers have achieved success in predicting patient response to therapy, e.g. NanoString signatures predict response to pembrolizumab (anti-PD-1). Measuring DNA, RNA, and proteins in unison greatly expands the power of biomarker signatures to characterize responses to immunotherapy.

Abstract A49: Building a comprehensive view of tumor biology in breast cancer by combining NanoString's Prosigna assay with the Pancancer Pathways, Immune Profiling, and Progression Panels

Recent advances in molecular profiling of breast cancer have given clinicians the tools required to make better treatment decisions for patients. Building an accurate representation of the biology of a particular tumor is key for: patient selection, therapeutic monitoring, and rational combination therapy design.

The NanoString PanCancer Pathways, PanCancer Immune Profiling and PanCancer Progression Panels enable researchers to quickly analyze the expression of up to 770 genes (per panel) and construct a comprehensive view of the biology of a particular tumor. The PanCancer Pathways Panel groups genes into 13 canonical driver pathways and provides both an expression value for each gene based on digital counts of transcripts and a Pathway Score that describes the relative dysregulation of each pathway. The Immune Profiling Panel measures the expression level of target genes that are specific to immune cell types and immune cell functions. Differential expression of each gene, relative abundance of immune cell types and abundance of tumor-specific antigens can be analyzed with the Immune Profiling panel. The Progression Panel analyzes the expression level of genes within four major biological processes that are associated with tumor growth and invasiveness. Together, these panels allow holistic characterization of the biologically meaningful attributes of a tumor.

In this proof-of-concept study, we analyzed 59 FFPE primary breast tumor samples along with 10 normal breast tissues using the PanCancer panels as well as the Prosigna Gene Signature Assay. We grouped the tumor samples by intrinsic subtype and explored pathway dysregulation using the PanCancer Pathways Panel, the immune landscape using the Immune Profiling Panel and the metastatic potential of the tumor using the Progression panel. For data analysis purposes, we used NanoString's PanCancer Advanced Analysis software. In each panel's data we compared the Prosigna subtypes at the single gene and the pathway level. We measured differential expression of various genes across subtypes as well as overall changes in pathway activation and suppression. Using the Immune Profiling Panel, we further compared relative abundance of the various immune cells across subtype.

The distribution of intrinsic subtype, as determined by the Prosigna Assay, in the 59 breast tumors was as follows: 16 (27.1%) Luminal A; 20 (33.9%) Luminal B; 13 (22.0%) Her2 Enriched; and 10 (17.0%) BasalLike. PanCancer Pathways analysis of these tumor samples along with 10 normal breast tissues revealed that dysregulation of certain canonical pathways characterizes each intrinsic subtype. In BasalLike tumors, we found that genes involved in the TGF-b pathway are significantly downregulated relative to Luminal A tumors and normal breast tissues. Further analysis with the Immune Profiling Panel revealed that the relative abundance of Mast cells is reduced while that of type 2 Th (Th2) cells is increased in Basal Like tumors relative to Luminal A and normal breast tissue. These results suggest that pathways associated with angiogenesis are downregulated in Basal Like breast cancer and favor the recruitment of immune cells associated with hypoxic conditions. These results confirm findings from multiple previous studies.

In this study, we show that the NanoString PanCancer Pathways, Immune Profiling and Progression panels reveal associations between intrinsic breast cancer subtype and specific pathway dysregulation as well as related changes in the immune landscape of the tumor. We demonstrate that a comprehensive view of the biology of a tumor can be readily obtained with the NanoString platform and the PanCancer Panels.

Citation Format: Lucas Dennis, Patrick Danaher, Maribeth Eagan, Andrew White, Nathan Elliot, Namratha Ram, Gayathri Balasundaram, Arthur Jeiranian, Seely Kaufmann, Rich Boykin, Lindy Irving, Wesley Buckingham, Sean Ferree, Christina Bailey, Joseph Beechem. Building a comprehensive view of tumor biology in breast cancer by combining NanoString's Prosigna assay with the Pancancer Pathways, Immune Profiling, and Progression Panels. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Breast Cancer Research; Oct 17-20, 2015; Bellevue, WA. Philadelphia (PA): AACR; Mol Cancer Res 2016;14(2_Suppl):Abstract nr A49.

Abstract A013: Biomarker development for cancer immuno-oncology/immunotherapy: Simultaneous digital counting of nucleic acids and proteins at 800-plex

The ability of mutated cells to give rise to pathological cancer relies upon the capability of these cells to interact with the immune system and ultimately evade immune recognition, suppress immune activity, and persist in a chronically inflamed environment. There is a clear need for new technologies capable of monitoring these crucial tumor immune-system interactions. The importance of measuring non-DNA markers (e.g., mRNA and proteins) becomes crucial in immuno-oncology (IO), since transcriptional reprogramming, cell-signaling, tumor microenvironment, and protein-protein interactions dominate the immune response. Combining multiple data types together into a single correlated analysis, however, is very difficult, due to the drastically different methodologies utilized for measurement. New developments in multiple biomarker-class optical barcode counting significantly reduce this problem. Recent work from the Weissleder-lab [1] has shown how optical barcode technology can be utilized for multiplexed digital counting of proteins, and be combined with simultaneous digital counting of nucleic-acids on a single platform. NanoString has expanded upon this original work and developed a cancer immune-profiling technology that simultaneously measures 770 mRNA's (unique signatures for 24 infiltrating immune cell types plus extensive immune-signaling pathways) plus 30 key IO proteins (including PD-1, PD-L1, PD-L2, CTLA4, OX40) using small amounts of clinically relevant samples (~ 50,000 PBMCs for mRNA+protein, 1 or 2, 5um slices for mRNA alone). This technology (RNA:Protein) is forming the basis for multi-year collaborations between NanoString and both MD Anderson (Houston TX) and the Cancer Immunotherapy Trials Network (CITN) to discover unique multi-analyte-type (mRNA + protein) biomarker signatures to guide cancer immunotherapy. NanoString gene expression profiling has also been highlighted by Merck (poster # 6017, ASCO 2015) as a method to select patients that will benefit from anti-PD1 based therapy (Keytruda). This technology is also being expanded to work on multi-analyte detection completely from FFPE slices. Several examples of the utilization of RNA:Protein immune-profiling technology to develop biomarker signatures will be presented.

Reference:

[1] Ullal et al. Science Translational Medicine 6:219 (Jan 15 2014)

Citation Format: Joseph Beechem, Liz Manrao, Marty Ross, Gokhan Demirkan, Brian Filanoski, Brian Birditt, Celine Ngouenet, Christina Bailey, Lucas Dennis, Irena Pekker, Gavin Meredith, Dae Kim, Gary Giess. Biomarker development for cancer immuno-oncology/immunotherapy: Simultaneous digital counting of nucleic acids and proteins at 800-plex. [abstract]. In: Proceedings of the CRI-CIMT-EATI-AACR Inaugural International Cancer Immunotherapy Conference: Translating Science into Survival; September 16-19, 2015; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2016;4(1 Suppl):Abstract nr A013.

Modeling bi-modality improves characterization of cell cycle on gene expression in single cells

Advances in high-throughput, single cell gene expression are allowing interrogation of cell heterogeneity. However, there is concern that the cell cycle phase of a cell might bias characterizations of gene expression at the single-cell level. We assess the effect of cell cycle phase on gene expression in single cells by measuring 333 genes in 930 cells across three phases and three cell lines. We determine each cell's phase non-invasively without chemical arrest and use it as a covariate in tests of differential expression. We observe bi-modal gene expression, a previously-described phenomenon, wherein the expression of otherwise abundant genes is either strongly positive, or undetectable within individual cells. This bi-modality is likely both biologically and technically driven. Irrespective of its source, we show that it should be modeled to draw accurate inferences from single cell expression experiments. To this end, we propose a semi-continuous modeling framework based on the generalized linear model, and use it to characterize genes with consistent cell cycle effects across three cell lines. Our new computational framework improves the detection of previously characterized cell-cycle genes compared to approaches that do not account for the bi-modality of single-cell data. We use our semi-continuous modelling framework to estimate single cell gene co-expression networks. These networks suggest that in addition to having phase-dependent shifts in expression (when averaged over many cells), some, but not all, canonical cell cycle genes tend to be co-expressed in groups in single cells. We estimate the amount of single cell expression variability attributable to the cell cycle. We find that the cell cycle explains only 5%–17% of expression variability, suggesting that the cell cycle will not tend to be a large nuisance factor in analysis of the single cell transcriptome.

Recent technological advances have enabled the measurement of gene expression in individual cells, revealing that there is substantial variability in expression, even within a homogeneous cell population. In this paper, we develop new analytical methods that account for the intrinsic, stochastic nature of single cell expression in order to characterize the effect of cell cycle on gene expression at the single-cell level. Applying these methods to populations of asynchronously cycling cells, we are able to identify large numbers of genes with cell cycle-associated expression patterns. By measuring and adjusting for cellular-level factors, we are able to derive estimates of co-expressing gene networks that more closely reflect cellular-level processes as opposed to sample-level processes. We find that cell cycle phase only accounts for a modest amount of the overall variability of gene expression within an individual cell. The analytical methods demonstrated in this paper are universally applicable to single cell expression data and represent a promising tool to the scientific community.

Spectral imaging in preclinical research and clinical pathology

Spectral imaging methods are attracting increased interest from researchers and practitioners in basic science, pre-clinical and clinical arenas. A combination of better labeling reagents and better optics creates opportunities to detect and measure multiple parameters at the molecular and cellular level. These tools can provide valuable insights into the basic mechanisms of life, and yield diagnostic and prognostic information for clinical applications. There are many multispectral technologies available, each with its own advantages and limitations. This chapter will present an overview of the rationale for spectral imaging, and discuss the hardware, software and sample labeling strategies that can optimize its usefulness in clinical settings.

Spectral imaging in preclinical research and clinical pathology

Spectral imaging methods are attracting increased interest from researchers and practitioners in basic science, preclinical and clinical arenas. A combination of better labeling reagents and better optics creates opportunities to detect and measure multiple parameters at the molecular and cellular level. These tools can provide valuable insights into the basic mechanisms of life, and yield diagnostic and prognostic information for clinical applications. There are many multispectral technologies available, each with its own advantages and limitations. This chapter will present an overview of the rationale for spectral imaging, and discuss the hardware, software and sample labeling strategies that can optimize its usefulness in clinical settings.

A fluorescent high-throughput assay for double-stranded DNA: the RediPlate PicoGreen assay

The fluorescent PicoGreen reagent for detection and quantitation of double-stranded DNA has been adapted for high-throughput screening: the RediPlate PicoGreen double-stranded DNA assay format. In the RediPlate PicoGreen assay format, the PicoGreen reagent is predistributed and co-dried into either 96- or 384-well microplates with the excipient trehalose. The user resuspends the dried reagents upon adding DNA, and measures the resulting fluorescence after a five minute incubation. Replicate fluorescence measurements on nominally identical wells have less than a 5% coefficient of variation. The assay is linear from 5 to 500 ng/ml DNA in a 200 micro l volume. The RediPlate PicoGreen assay format retains the advantages of the original PicoGreen reagent - sensitivity, speed, and specificity - but in a high-throughput format.

Multiple elements in the upstream glucokinase promoter contribute to transcription in insulinoma cells

beta-cell type-specific expression of the upstream glucokinase promoter was studied by transfection of fusion genes and analysis of DNA-protein interactions. A construct containing 1,000 bp of 5'-flanking DNA was efficiently expressed in HIT M2.2.2 cells, a beta-cell-derived line that makes both insulin and glucokinase, but not in NIH 3T3 cells, a heterologous cell line. In a series of 5' deletion mutations between bases -1000 and -100 (relative to a base previously designated +1), efficient expression in HIT cells was maintained until -280 bp, after which transcription decreased in a stepwise manner. The sequences between -180 and -1 bp contributing to transcriptional activity in HIT cells were identified by studying 28 block transversion mutants that spanned this region in 10-bp steps. Two mutations reduced transcription 10-fold or more, while six reduced transcription between 3- and 10-fold. Three mutationally sensitive regions of this promoter were found to bind to a factor that was expressed preferentially in pancreatic islet beta cells. The binding sites, designated upstream promoter elements (UPEs), shared a consensus sequence of CAT(T/C)A(C/G). Methylation of adenine and guanine residues within this sequence prevented binding of the beta-cell factor, as did mutations at positions 2, 3, and 5. Analysis of nuclear extracts from different cell lines identified UPE-binding activity in HIT M2.2.2 and beta-TC-3 cells but not in AtT-20, NIH 3T3, or HeLa cells; the possibility of a greatly reduced amount in alpha-TC-6 cells could not be excluded. UV laser cross-linking experiments supported the beta-cell type expression of this factor and showed it to be approximately 50 kDa in size. Gel mobility shift competition experiments showed that this beta-cell factor is the same that binds to similar elements, termed CT boxes, in the insulin promoter. Thus, a role for these elements (UPEs or CT boxes), and the beta-cell factor that binds to them, in determining the expression of genes in the beta cells of pancreatic islets is suggested.

Mechanism of serpin action: evidence that C1 inhibitor functions as a suicide substrate

Serpins form a family of structurally related proteins, many of which function in plasma as inhibitors of serine proteases involved in inflammation, blood coagulation, fibrinolysis, and complement activation. To further characterize the mechanism by which serpins inhibit their target enzymes, we have studied the effect of temperature on the reaction of C1 inhibitor and the serine protease plasma kallikrein. At both 38 and 4 degrees C, C1 inhibitor (Mr 105,000) is cleaved by alpha-kallikrein (Mr 85,000 and 88,000) at position P1 (Arg444) of the reactive center, a reaction that leads to the formation of a covalent bimolecular enzyme-serpin complex (Mr 195,000) and cleaved but uncomplexed serpin (Mr 95,000). Between 38 and 4 degrees C, the product distribution is temperature-dependent, with more cleaved C1 inhibitor (Mr 95,000) formed at lower temperatures and correspondingly less Mr 195,000 complex. Studies employing intrinsic tryptophan fluorescence and 1H NMR spectroscopy show that this behavior is not caused by temperature-dependent conformational changes of kallikrein or C1 inhibitor. C1 inhibitor also behaves in this manner with the light chain of kallikrein and, to a lesser extent, with plasmin and C1s. These data are best explained by a branched reaction pathway, identical with the scheme describing the mechanism of action of suicide substrates. This scheme involves the formation of an enzyme-inhibitor intermediate, which can be stabilized into a covalent complex and/or dissociate into free enzyme and cleaved inhibitor, depending on the reaction conditions.