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Characteristics of the patients

Results of PLA, CD8 and PDL1 (MELscore) in all the samples

Purpose:Less than 50% of patients with melanoma respond to anti–programmed cell death protein 1 (anti–PD-1), and this treatment can induce severe toxicity. Predictive markers are thus needed to improve the benefit/risk ratio of immune checkpoint inhibitors (ICI). Baseline tumor parameters such as programmed death ligand 1 (PD-L1) expression, CD8+ T-cell infiltration, mutational burden, and various transcriptomic signatures are associated with response to ICI, but their predictive values are not sufficient. Interaction between PD-1 and its main ligand, PD-L1, appears as a valuable target of anti–PD-1 therapy. Thus, instead of looking at PD-L1 expression only, we evaluated the predictive value of the proximity between PD-1 and its neighboring PD-L1 molecules in terms of response to anti–PD-1 therapy.Experimental Design:PD-1/PD-L1 proximity was assessed by proximity ligation assay (PLA) on 137 samples from two cohorts (exploratory n = 66 and validation n = 71) of samples from patients with melanoma treated with anti–PD-1±anti–CTLA-4. Additional predictive biomarkers, such as PD-L1 expression (MELscore), CD8+ cells density, and NanoString RNA signature, were also evaluated.Results:A PD-1/PD-L1 PLA model was developed to predict tumor response in an exploratory cohort and further evaluated in an independent validation cohort. This score showed higher predictive ability (AUC = 0.85 and 0.79 in the two cohorts, respectively) for PD-1/PD-L1 PLA as compared with other parameters (AUC = 0.71–0.77). Progression-free and overall survival were significantly longer in patients with high PLA values (P = 0.00019 and P < 0.0001, respectively).Conclusions:The proximity between PD-1 and PD-L1, easily assessed by this PLA on one formalin-fixed paraffin-embedded section, appears as a new biomarker of anti–PD-1 efficacy.

Supplementary Figure Legends

Kaplan Meier representation of the progression-free survival (PFS) and overall survival (OS) for PDL1, CD8, TIS and Melscore variables in all samples (exploratory and validation cohorts) with a recapitulive table of survival medians (NA : Not Available because the 50% survival is not reached)

CD8+ cells immunohistochemistry. Infiltration of tumor areas (A) and peritumor areas (B) as assessed semi-quantitatively using a 0 to 3 scale.

PD-L1 immunohistochemistry. Positive PD-L1 staining in immune cells (chromogen: diaminobenzidine). PT: peritumoral area, CT: center of the tumor, arrows: areas with dense PD-L1+ immune infiltrate.

Association between PLA score, disease characteristics and prior treatments

Purpose:Less than 50% of patients with melanoma respond to anti–programmed cell death protein 1 (anti–PD-1), and this treatment can induce severe toxicity. Predictive markers are thus needed to improve the benefit/risk ratio of immune checkpoint inhibitors (ICI). Baseline tumor parameters such as programmed death ligand 1 (PD-L1) expression, CD8+ T-cell infiltration, mutational burden, and various transcriptomic signatures are associated with response to ICI, but their predictive values are not sufficient. Interaction between PD-1 and its main ligand, PD-L1, appears as a valuable target of anti–PD-1 therapy. Thus, instead of looking at PD-L1 expression only, we evaluated the predictive value of the proximity between PD-1 and its neighboring PD-L1 molecules in terms of response to anti–PD-1 therapy.Experimental Design:PD-1/PD-L1 proximity was assessed by proximity ligation assay (PLA) on 137 samples from two cohorts (exploratory n = 66 and validation n = 71) of samples from patients with melanoma treated with anti–PD-1±anti–CTLA-4. Additional predictive biomarkers, such as PD-L1 expression (MELscore), CD8+ cells density, and NanoString RNA signature, were also evaluated.Results:A PD-1/PD-L1 PLA model was developed to predict tumor response in an exploratory cohort and further evaluated in an independent validation cohort. This score showed higher predictive ability (AUC = 0.85 and 0.79 in the two cohorts, respectively) for PD-1/PD-L1 PLA as compared with other parameters (AUC = 0.71–0.77). Progression-free and overall survival were significantly longer in patients with high PLA values (P = 0.00019 and P < 0.0001, respectively).Conclusions:The proximity between PD-1 and PD-L1, easily assessed by this PLA on one formalin-fixed paraffin-embedded section, appears as a new biomarker of anti–PD-1 efficacy.

RNA in situ hybridization (ISH) is a widely used technique for the localization of mRNA in tissues. Limitations to traditional ISH include the number of targets that can be analyzed concurrently and the ability for many of these assays to be used in formalin-fixed, paraffin-embedded tissues (FFPE). Here, we describe the GeoMx™ RNA assay that is capable of the highly multiplexed detection of mRNA targets in FFPE tissues. This assay utilizes ISH probes linked to indexing oligo barcodes via a photocleavable linker and the GeoMx Digital Spatial Profiler (DSP) Instrument to enable profiling of RNA targets in a region-of-interest-based method. In brief, 5 μm FFPE sections are dewaxed, target retrieved, digested with proteinase K, post-fixed, and then incubated overnight with GeoMx RNA detection probes. Stringent washes are performed followed by the addition of fluorescently labeled antibodies for use as morphology markers. User-defined regions of interest are then profiled on the GeoMx DSP through region-specific cleaving and collecting the photocleaved indexing oligos. Cleaved indices are then quantified using NanoString nCounter

5015 Background: B7-H3/CD276, a member of the B7 superfamily, is highly expressed in prostate cancer (PCa) and is associated with rapid biochemical recurrence and early metastases. B7-H3 is the only checkpoint candidate to have a presumptive androgen receptor binding site, suggesting interaction with the androgen axis. Enoblituzumab (MacroGenics) is an investigational humanized Fc-optimized B7-H3–targeting antibody that induces antibody dependent cellular cytotoxicity (ADCC). Methods: In this phase 2 single-arm biomarker-rich neoadjuvant trial, men with operable intermediate- and high-risk localized prostate cancer (Grade Groups 3-5) were enrolled to evaluate the safety, anti-tumor efficacy, and immunogenicity of enoblituzumab when given prior to prostatectomy. Patients received enoblituzumab (15 mg/kg IV weekly x 6) prior to surgery. Prostate glands were harvested 2 weeks after the last dose, and were examined for pathologic and immunologic endpoints. The co-primary outcomes were safety and PSA0 at 1 year post-op. Pre-planned secondary outcomes were PSA and Gleason grade group change from biopsy to prostatectomy. Results: 32 men were enrolled. Grade 3/4 adverse events occurred in 12% of patients. One patient developed a grade-3 infusion reaction, and one had immune myocarditis that improved with steroids. Pre-prostatectomy PSA declines of >10% were observed in 31% of patients (95% CI: 16-50%). PSA0 at 1 year post-op was seen in 66% of men (95% CI: 47-81%). Median time to PSA recurrence was not reached, with a median follow-up of 30 months. Gleason group upgrade, no change, and downgrade was observed in 13%, 37%, and 50% of patients. Gleason grade group changes were significantly associated with enoblituzumab treatment compared to 1:1 matched historical controls (p=0.023). Tumor microenvironment profiling by NanoString GeoMx spatial proteomics and PanCancer IO 360 mRNA expression analysis revealed post-treatment upregulation of CD8+ T cells, PD-1/PD-L1 expression, and immune activation (granzyme B, IFN signaling, myeloid inflammation). There was a significant association between CD8+ T-cell increases and Gleason grade group declines. First-in-human antigen spread profiling revealed no safety concerns. TCR sequencing showed focused peripheral expansion of tumor associated T-cell clones that correlated with PSA0 at 1 year. Whole exome and RNAseq data, and clinical correlations, will be presented. Conclusions: In this neoadjuvant trial, inhibition of B7-H3 with enoblituzumab demonstrated favorable safety and encouraging activity in localized PCa patients. Data suggest robust intratumoral induction (adaptive upregulation) of immune checkpoints, T-cell activation, and myeloid inflammation. Enoblituzumab-induced peripheral expansion of tumor associated T-cell clones may be associated with tumor control. Clinical trial information: NCT02923180.

RNA in situ hybridization (ISH) is a widely used technique for the localization of mRNA in tissues. Limitations to traditional ISH include the number of targets that can be analyzed concurrently and the ability for many of these assays to be used in formalin-fixed, paraffin-embedded tissues (FFPE). Here, we describe the GeoMx™ RNA assay that is capable of the highly multiplexed detection of mRNA targets in FFPE tissues. This assay utilizes ISH probes linked to indexing oligo barcodes via a photocleavable linker and the GeoMx Digital Spatial Profiler (DSP) Instrument to enable profiling of RNA targets in a region-of-interest-based method. In brief, 5 μm FFPE sections are dewaxed, target retrieved, digested with proteinase K, post-fixed, and then incubated overnight with GeoMx RNA detection probes. Stringent washes are performed followed by the addition of fluorescently labeled antibodies for use as morphology markers. User-defined regions of interest are then profiled on the GeoMx DSP through region-specific cleaving and collecting the photocleaved indexing oligos. Cleaved indices are then quantified using NanoString nCounter® Technology generating digital quantification of RNA expression with spatial context.

Digital Spatial Profiling (DSP) is a method for highly multiplex spatial profiling of proteins or RNAs suitable for use on formalin-fixed, paraffin-embedded (FFPE) samples. The approach relies on (1) multiplexed readout of proteins or RNAs using oligonucleotide tags; (2) oligonucleotide tags attached to affinity reagents (antibodies or RNA probes) through a photocleavable (PC) linker; and (3) photocleaving light projected onto the tissue sample to release PC oligonucleotides in any spatial pattern across a region of interest (ROI) covering 1 to ~5,000 cells. DSP is capable of single-cell sensitivity within an ROI using the antibody readout, with RNA detection feasible down to ~600 individual mRNA transcripts. We show spatial profiling of up to 44 proteins and 96 genes (928 RNA probes) in lymphoid, colorectal tumor and autoimmune tissues by using the nCounter system and 1,412 genes (4,998 RNA probes) by using next-generation sequencing (NGS). DSP may be used to profile not only proteins and RNAs in biobanked samples but also immune markers in patient samples, with potential prognostic and predictive potential for clinical decision-making. A turnkey system allows for spatial profiling of proteins and RNA in fixed tissues, providing a window on cellular heterogeneity.

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. The GeoMxTM Digital Spatial Profiler (DSP) enables the highly-multiplexed detection of mRNA or protein targets within distinct regions of tissues, including FFPE. This assay utilizes in situ hybridization (ISH) probes or antibodies linked to indexing oligo barcodes via a photo-cleavable linker. The GeoMx DSP enables profiling of RNA or protein targets by releasing and collecting these barcodes from user-defined regions-of-interest. Manual preparation of FFPE tissue uses conventional immuno-fluorescence (IF) and ISH reagents, however it requires greater than two hours of hands-on-time over 2 days. Protocols have been developed to enable the automation of these tissue preparation protocols using the Leica Biosystems BOND RX and BOND RXm Fully Automated Research Stainers. Here we describe protocols for the semi-automated preparation of GeoMx RNA and protein assays as well as the fully-automated preparation of GeoMx RNA assays. These protocols reduce the hands-on time of performing the assay to 72 minutes and 35 minutes for the semi- and fully-automated protocols, respectively. Signal-to-noise ratios (SNR) are highly concordant between serial sections processed manually and processed on the Leica BOND RXm using the GeoMx Immune Cell Profiling Panel for protein (58-plex) and GeoMx Immune Pathways Panel for RNA (84-plex). Furthermore, automated assays show high concordance between the BOND RX and BOND RXm instruments. Lastly, we demonstrate the use of the fully automated slide preparation protocol with the GeoMx Cancer Transcriptome Atlas, a panel that targets >1,600 key cancer mRNAs that are read out by next-generation sequencing. GeoMx Assays are for RESEARCH USE ONLY. Not for use in diagnostic procedures. Citation Format: Daniel R. Zollinger, Sarah Ketting, Kristina Sorg, Oliver Appelbe, Danielle Aaker, Damian Cockfield, Chris Merritt, Joseph M. Beechem. High-throughput slide preparation for spatially-resolved, multiplexed quantification of protein or mRNA in tumor tissues with automation of GeoMx™ DSP Assays on Leica Biosystems BOND RX [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 5237.

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.

We have developed Digital Spatial Profiling (DSP), a non-destructive method for high-plex spatial profiling of proteins and RNA, using oligonucleotide detection technologies with unlimited multiplexing capability. The key breakthroughs underlying DSP are threefold: (1) multiplexed readout of proteins/RNA using oligo-tags; (2) oligo-tags attached to affinity reagents (antibodies/RNA probes) through a photocleavable (PC) linker; (3) photocleaving light projected onto the tissue sample to release PC-oligos in any spatial pattern. Here we show precise analyte reproducibility, validation, and cellular resolution using DSP. We also demonstrate biological proof-of-concept using lymphoid, colorectal tumor, and autoimmune tissue as models to profile immune cell populations, stroma, and cancer cells to identify factors specific for the diseased microenvironment. DSP utilizes the unlimited multiplexing capability of modern genomic approaches, while simultaneously providing spatial context of protein and RNA to examine biological questions based on analyte location and distribution.

Chronic liver injury leads to fibrosis and cirrhosis. Cirrhosis, the end stage of chronic liver disease, is a leading cause of death worldwide and increases the risk of developing hepatocellular carcinoma. Currently, there is a lack of effective antifibrotic therapies to treat fibrosis and cirrhosis. Development of antifibrotic therapies requires an in-depth understanding of the cellular and molecular mechanisms involved in inflammation and fibrosis after hepatic injury. Two growth factor signaling pathways that regulate liver fibrosis are transforming growth factor-β (TGFβ) and platelet-derived growth factor (PDGF). However, their specific contributions to fibrogenesis are not well understood. Using a genetic model of liver fibrosis, we investigated whether the canonical TGFβ signaling pathway was necessary for fibrogenesis. PDGF-C transgenic ( PDGF-C Tg) mice were intercrossed with mice that lack Smad3, and molecular and histological fibrosis was analyzed. PDGF-C Tg mice that also lacked Smad3 had less fibrosis and improved liver lobule architecture. Loss of Smad3 also reduced expression of collagen genes, which were induced by PDGF-C, but not the expression of genes frequently associated with hepatic stellate cell (HSC) activation. In vitro HSCs isolated from Smad3-null mice proliferated more slowly than cells from wild-type mice. Taken together, these findings indicate that PDGF-C activates TGFβ/Smad3 signaling pathways to regulate HSC proliferation, collagen production and ultimately fibrosis. In summary, these results suggest that inhibition of both PDGF and TGFβ signaling pathways may be required to effectively attenuate fibrogenesis in patients with chronic liver disease.

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.

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.

e14218 Background: 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. Methods: Using colorectal cancer FFPE sections we spatially resolve protein and mRNA expression of immune-oncology targets and present a series of modalities and associated applications for the GeoMx Digital Spatial Profiler platform. Results: Microsatellite stable (MSS) or instable (MSI) colorectal tumors will be characterized to evaluate active and suppressive immune mechanisms in both immune dense regions and tumor versus stroma by utilizing segment profiling. Regions from the invasive margins and tumor centers will be investigated with contour profiling to define different immunosuppressive and activated immune phenotypes. Evaluation of tumor versus stroma will also identify pathways related to each compartment that are different between MSI and MSS tumors. 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. Conclusions: This study will demonstrate multiplexed pathway-level protein and gene expression analysis from discrete regions within a colorectal tumor (tumor center and immune invasive margin), enabling systematic interrogation of immune activity in FFPE samples. Further studies could eventually lead to the identification of unique localized immune characteristics to guide combination therapeutic approaches.

Characterization of spatial mRNA expression across multiple targets in a single tissue section has proven difficult to accomplish. To address this unmet need, we have developed a novel imaging platform, Digital Spatial Profiling (DSP), designed to simultaneously analyze 10s to 100s of RNAs (or proteins) from discrete regions by detecting oligo-conjugated probes. We show that this system can resolve mRNA expression panels in a highly multiplexed and automated manner on human FFPE and fresh frozen tissues. DSP RNA probes consist of antisense target-recognition sequences and UV-cleavable tags that can be released in a precise manner by the DSP instrument and digitally counted using nCounter® reagents. For this, probes are first hybridized overnight in situ to human FFPE or fresh frozen tissue sections. After hybridization, tags are released by nondestructive exposure of UV light, automatically collected by the DSP Instrument, and quantified using nCounter® technology. The nCounter PlexSet™ reagents are used to enable the analysis of 96 regions of interest with a single nCounter run. To demonstrate the regional specificity of RNA detection on DSP, we profiled distinct regions in human tonsillitis tissues using a 48-plex of RNA target probes. Our results show that genes are detected in the expected region-specific manner. Using an orthogonal in situ hybridization (ISH) approach, we validate the RNA DSP results in tonsil across multiple targets. To determine the regionally specific RNA expression in tumor area and nontumor area in non-small cell lung cancer (NCSLC), we used a high-plex probe mix of relevant Immuno-oncology RNA targets. These results show that the DSP platform can be used to obtain high-plex, spatial RNA expression data on tissue sections. The protein profiling assay on DSP, presented elsewhere, depends upon FFPE-compatible antibodies, which can be difficult to generate for some targets. Utilizing spatial mRNA profiling provides an alternative for cases where the necessary antibodies do not exist. In all, simultaneous, high-plex RNA and protein detection with DSP on serial sections could provide a novel method that can bridge the gap between translational research discovery and clinical applications. Citation Format: Daniel Zollinger, Kristina Sorg, Jill McKay-Fleisch, Kristi Barker, Karen Nguyen, Chris Merritt, Joseph Beechem. Digital spatial profiling platform allows for spatially resolved, high-plex quantification of mRNA distribution and abundance on FFPE and fresh frozen tissue sections [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3434.