Flotetuzumab (FLZ), an Investigational CD123 x CD3 Bispecific Dart® Protein-Induced Clustering of CD3+ T Cells and CD123+ AML Cells in Bone Marrow Biopsies Is Associated with Response to Treatment in Primary Refractory AML Patients

Background: Acute myeloid leukemia (AML) is a molecularly and clinically heterogeneous hematological malignancy. Despite recent advancements in the treatment of AML, approximately 50% of patients with acute myeloid leukemia (AML) do not respond to induction therapy (primary induction failure, PIF) or relapse after < 6-month remission (early relapse, ER). Immunotherapy is an attractive modality to exploit in patients (pts) with AML, however, the ability to predict the groups of pts that will respond to immune targeting remains limited. Immune infiltration into tumors has been associated with therapeutic effects in preclinical models and patients with cancer. We have recently shown an association between an immune-enriched tumor microenvironment (TME) and resistance to cytarabine-based chemotherapy. Flotetuzumab (MGD006) is a bispecific DART® antibody-based molecule to CD3ε and CD123 being tested in adults with relapsed/refractory AML. Herein, we report the results of a multicenter, open-label, phase 1/2 study of flotetuzumab and the correlative data used to determine the target AML population of PIF/ER AML.

Methods: The recommended Phase 2 dose (RP2D) of flotetuzumab has been identified as 500 ng/kg/day administered as a 7 -day/week continuous infusion following multi-step step-up dosing during week 1 of cycle 1. Disease status was assessed by modified IWG criteria. Bone marrow (BM) aspirates were collected to investigate biomarkers, including CD123 receptor density (RD), and gene expression profiling using the NanoString PanCancer IO 360™ panel. FFPE BM biopsies were evaluated using multi-plex IHC staining panels. Slides were stained using a Leica BondRx autostainer and fluorescence imaged using a Polaris Vectra 3 and analyzed using inForm software. Lastly, BM biopsies were also profiled using the GeoMx DSP platform.

Results: Total of 88 AML patients were enrolled, 42 in dose-finding and 46 at the RP2D. Consistent with flotetuzumab’s mode of action, the most frequent adverse events were infusion-related reactions (IRR)/cytokine release syndrome (CRS). Stepwise dosing, pre-treatment dexamethasone, prompt use of tocilizumab and temporary dose reductions/interruptions successfully managed IRR/CRS. Flotetuzumab showed acceptable tolerability. Based on previous finding of immune-enriched TME and association with chemotherapy resistance in AML, we hypothesized that higher expression of IFNγ inducible genes might identify AML pts who derive benefit from immunotherapy with flotetuzumab. BM samples from pts with evidence of FLZ anti-leukemic activity had an immune infiltrated TME relative to non-responders. Interestingly, the IFNγ-signaling score (from IO360) was significantly higher in pts with chemotherapy-refractory AML compared with relapsed AML at time of flotetuzumab treatment, and in individuals with evidence of anti-leukemic activity compared to non-responders. Additionally, interferon-related gene modules strongly predicted flotetuzumab’s activity. In line with these findings, clinical benefit accrued exclusively to PIF/ER AML patients, who had a predominantly immune-infiltrated TME at baseline. Flotetuzumab modified the TME; on-treatment BM samples displayed increased expression of antigen presentation and immune activation genes relative to baseline. BM biopsies from six pts with PIF/ER AML were analyzed by IHC. In baseline BM samples, CD3 and CD8 cell infiltrates were higher in responder vs non-responders. Interestingly, T-cell clusters surrounding CD123+ cells were identified in on-treatment BM biopsies in responders. GeoMx DSP analysis identified increased T-cell activation markers within the T-cell clusters.

Conclusions: In conclusion, we show that FLZ elicited clinical activity in heavily pre-treated patients with poor response rates to primary therapy. We also show that increased IFNγ signaling gene expression scores in baseline BM appeared to associate with response to FLZ therapy. Flotetuzumab represents an innovative experimental approach associated with acceptable safety and encouraging evidence of activity in AML patients with PIF/ER. Trial registration number: NCT02152956.

With over 200 validated antibodies and the option to add custom antibodies, the GeoMx DSP protein portfolio offers options to fit a wide range of spatial profiling application needs. NanoString’s robust validation pipeline for GeoMx antibodies, ensures that researchers can use GeoMx assays off the shelf without having to spend months to years validating panels of antibodies. Here, we present our validation process with data from our three newest Human Immuno-oncology protein panels: MAPK Signaling, PI3K/AKT Signaling, and Cell Death.

Background: Despite the immunogenicity and safety profile of dendritic cell (DC) vaccines, the importance of vaccine-induced antigen-specific T cell responses is unclear across clinical trials, and therapeutic efficacy remains low with limited clinical responses. Our comprehensive characterization of T cell responses, cell-intrinsic and soluble immune checkpoint molecules and immune-related gene expression profiles reveal novel insights into CD8+ T cells specific for melanoma-associated antigens (MAA) from patients who received autologous DC engineered to express three full length melanoma antigens: tyrosinase, MART-1 and MAGE-A6 [1].

Methods: MAA-specific T cell responses were examined by standardized IFNγ ELISPOT assays at baseline, day 43 (post DC vaccines) and d89 (post observation or IFNα).  Luminex was used to detect serum checkpoint and costimulatory molecules, and whole blood flow cytometry was used to quantify PBMC subsets. Targeted mRNA and protein expression analyses in circulating lymphocytes and melanoma tumor samples were performed using NanoString nCounter platform (RUO).

Results: The majority of the 35 patients were successfully vaccinated, and the total vaccine-induced T cell responses were higher among those exhibiting a favorable clinical outcome. Patients who received checkpoint blockade prior to DC vaccination had higher baseline MA-specific CD8 T cell responses but no evidence for improved functional responses to the vaccine. Patients who showed the best clinical responses had low PD-1 expression on MA-specific T cells before and after DC vaccination, however blockade of PD-1 during antigen presentation by DC had minimal functional impact on PD-1high MA-specific T cells. Molecular profiling in circulating lymphocytes and tumor biopsies identified critical immunoregulatory pathways, including CTLA-4 and PD-1.  High immune checkpoint, type I interferon response and T-cell exhaustion gene expression networks correlated with inferior clinical outcomes. Interestingly, B cell receptor pathways negatively correlated with PD-1 expression, while gene signatures downstream of T cell receptor activation and IL-2 signaling were negatively correlated with CTLA-4 expression. Serum levels of PD-1 and PD-L2 were inversely correlated and post-vaccine serum levels PD-L2 correlated with decreased circulating T­reg and favorable outcome in patients, suggesting that it may serve as a biomarker of clinical response.

Conclusions: Collectively, our study shows that specific checkpoint molecular pathways are critical for vaccine outcomes and for the activation of anti-tumor responses in melanoma patients. DC-vaccine immunization followed by immune checkpoint blockade may be an optimal sequential therapy to improve antitumor immunity in melanoma.

Tumor phenotypes are dictated not only by the neoplastic cell component, but also by the tumor microenvironment (TME), which is inherently immuno-suppressive, is equipped to hamper effector T-cell function and includes immune and inflammatory cells, soluble mediators such as interferon (IFN)-g and extracellular matrix components. Acute myeloid leukemia (AML) is characterized by clonal expansion of poorly differentiated myeloid precursors, resulting in impaired hematopoiesis and often bone marrow (BM) failure. TP53 mutations occur in 8-10% of de novo AML and are associated with poor prognostic features. The development and delivery of new therapeutic strategies for high-risk AML, including immunotherapy, therefore remains a priority.

Our multi-institutional study was undertaken to characterize the immune ecosystem of non-promyelocytic AML with TP53 mutations using he nCounter™ system (NanoString Technologies Inc., Seattle, WA), with the ultimate goal to implement new immunotherapy agents for patients with specific immunologic subtypes of AML.

We detected high T-cell infiltration and high expression of immune checkpoints and IFN-g signaling molecules in patients with TP53 mutated AML compared with AML subgroups with other risk-defining molecular lesions. We also computed an experimentally derived, TP53-related immune gene signature which stratified survival in a broad cohort of TCGA AML cases. Finally, our correlative analysis in patients with relapsed/refractory AML treated with flotetuzumab, an investigational immunotherapy, showed efficacy in individuals with altered TP53 status and identified immune gene signature that support the prediction of therapeutic responses.

In conclusion, our study has identified unique immunological profiles in patients with TP53 mutated AML. From a clinical standpoint, ‘immune enriched’ AMLs might be amenable to immunotherapy approaches with T-cell engagers.

Personalized medicine has beomce a paradigm in lung cancer management; ~ 25–30% of advanced lung cancer patients could benefit from a targeted therapy. Several guidelines currently endorse routine genomic testing of several druggable oncogenic biomarkers—EGFR, ALK, ROS1, and BRAF—in new metastatic non-squamous NSCLC patients, while a number of other emerging molecular targets, such as RET and NTRK gene rearrangements, MET exon 14 skipping mutations (METex14), and activating HER2 or KRAS mutations are likely approaching clinical practice. Consequently, more extensive analysis such as multiplexed DNA/RNA profiling platforms are increasingly required for comprehensive biomarker testing of lung cancer. We validated the sensitivity of the NanoString® nCounter® technology to identify driver mutations (METex14) and gene fusions (ALK, ROS1, RET1, NTRK) in lung cancer patients. Our work demonstrates that embedding two DNA and RNA (using the nCounter) multiplexing technologies early into the routine workup of patients with advanced NSCLC is feasible and useful to identify distinct subsets of patients amenable to targeted therapies, resulting in significantly improved outcomes.

Research Use Only. Not for use in Diagnostic Procedures.

Background: CDK4/6 inhibitors increase tumor immunogenicity in preclinical models of breast cancer and several trials combining CDK4/6 inhibitors and anti-PD1/PDL1 therapies are underway. However, immune response data in tumor samples from patients (pts) treated with CDK4/6 inhibitors are scarce. Here, we present exploratory results of the CORALLEEN trial, which evaluated the efficacy of ribociclib and endocrine therapy in patients with high-risk Luminal B disease (Gavilá et al. submitted to SABCS 2019).

Methods: CORALLEEN is a randomized exploratory study in postmenopausal women with operable stage I-III breast cancer, hormone receptor positive (HR+)/HER2-negative and Luminal B by Prosigna®. Pts were randomized 1:1 to receive either 6 cycles of ribociclib (600mg; 3-weeks-on/1-week-off) plus daily letrozole (R+L) or chemotherapy (CHT): 4 cycles of AC followed by 12 doses of weekly paclitaxel. The primary endpoint is the rate of PAM50 Risk of Relapse (ROR)-low disease at surgery in each arm. Baseline and surgical specimens were also collected for stromal tumor infiltrating lymphocyte (TIL) determination and gene expression analysis. Expression of 770 genes and 31 biological signatures were determined using the Breast360TM panel (nCounter). In order to identify genes whose expression correlated with TIL, a significance of microarrays (SAM) quantitative analysis was used with a false discovery rate (FDR) <5%. Finally, interaction tests between each variable and tumor ROR response (i.e. relative decrease in ROR score) according to type of therapy were explored in logistic regression models.

Results: From July-2017 to Nov-2018, 198 pts were screened and 106 (54%) pts with Luminal B disease were recruited. baseline characteristics were: mean age 64, mean tumor size 3.8 cm, N+ (39%), mean Ki67 33.2%; 86.8% of pts were ROR-high. A total of 95 pts (90%) were included in this analysis (46 pts in the CHT arm and 49 in the R+L arm). At baseline, 21.7% and 32.7% of pts in the CHT and R+L arms had ≥10% of TILs, respectively. Compared to baseline, no significant change patterns in TILs expression were observed. In the CHT arm, 32.6%, 28.3 % and 39.1% of tumors increased, decreased or did not show any change in TILs. In the R+L arm, 30.6%, 44.9% and 24.5% of tumors increased, decreased or did not show any change in TILs. At surgery, 15.2% of pts in the CHT arm and 26.5% of pts in the R+L arm had ≥10% of TILs. Moreover, 5 of the 13 pts (38.5%) with ≥10% of TILs at surgery following R+L had TILs < 10% at baseline. In both arms, high expression of immune-related genes and signatures tracking CD8 T-cells (i.e. CD8A, PD1, LAG3 and CD8T-cell signature) were found associated with high TILs (FDR<5%). when immune response was evaluated based on tumor ROR response (as a continuous variable), high TILs at surgery were associated with better response to CHT but not to R+L (interaction P=0.03). In the CHT arm, mean % of TILs at surgery in low and high ROR responders (defined as <50% or ≥50% relative decrease in ROR score) were 4.2% and 11.2%, respectively. In the R+L arm, mean % of TILs at surgery in low and high ROR responders were 16.2% and 6.1%, respectively. Similar results were found with genes/signatures such as CD8A mRNA (interaction P=0.03), CD8 T-cell signature (interaction P=0.04), Tumor Inflammation Signature (interaction P=0.04) and GZMA mRNA (Granzyme A, interaction P=0.02).

Conclusions: An increase in TILs following 24-weeks of R+L occurs in ~30% of pts with high-risk Luminal B tumors, regardless of tumor ROR response. These findings suggest that immune checkpoint blockade might be an interesting strategy to explore in patients with a low ROR response after R+L.

Metastatic prostate cancer (mPC) is a phenotypically diverse disease with poor responses to immune based therapeutics. Development of immunotherapeutic strategies for mPC is hampered by the heterogeneity and lack of understanding of the immune composition and tumor microenvironment (TME) within and between molecular subtypes.

To characterize the immune TME of mPC, we obtained multiple metastases from patients with mPC belonging to multiple genomic subtypes and three phenotypes. Previous work defined the molecular subtype of each metastatic tumor by RNA-seq and whole exome sequencing, and patients were stratified to compare and contrast androgen receptor (AR) active tumors (AR+/NE-), neuroendocrine (NE) tumors (AR-/NE+), and double-negative tumors (AR-/NE-). An immuno-oncology RNA panel for the NanoString GeoMx™ Digital Spatial Profiler was used to determine the immune cell phenotypes within the tumor, in proximity to the tumor, and distant from the tumor margin.

Here we present a map of the metastatic landscape in mPC patients, focusing on the organization of the immune cells within the tissue. We use these maps to determine the immune cell compositions, spatial organization of metastatic niches, and spatial expression signatures that associate with the molecular subtypes of mPC. We further characterized the expression patterns between metastatic sites within the same patient, as well as the variation between patients.

Our study demonstrates a spatial genomics approach to defining the microenvironment landscape of molecular subtypes of mPC, potentially revealing patterns in the metastatic microenvironments that may predict the utility of immune-based therapies.

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

The spread of severe acute respiratory syndrome coronavirus 2 (SARS CoV2), changed the daily life of medical oncologists. To keep safe both patients and healthy workers is the most important rule. In our daily practice we adopted a specific policy about the conduct of our clinical managements of melanoma patients, in order to minimise the risk of any potential exposure. In addition, immuno-oncologists may have an important role during such pandemic. Indeed, they have an important experience in the management of immuno-related adverse events due to the hyperactivation of immune system as consequence of immunotherapy. Since the acute respiratory distress syndrome by COVID-19 seems to occur from an excess of cytokine production, some drugs used in the management of immune-related side effects could be useful for treating ARDS by COVID-19. In particular, they know the key role played by IL-6 in the pathogenesis of these kind of hyperinflammation syndromes. In Italy we started on 19th of March a phase II study (NCT04317092), which enrolled 330 patients in 24 hours, looking to the ability of tocilizumab to reduce the one-month mortality rate as main study endpoint. Results should be reported very soon. Other drugs active in reducing the cytokine release syndrome are at moment in clinical trial or expanded access program like JAK inhibitors, complement inhibitors, toll like receptor inhibitors and others.

While many technologies focus on either exploring the spatial context of a handful of targets, or expression patterns of hundreds or thousands of targets in bulk samples or dissociated single-cells, the GeoMx Cancer Transcriptome Atlas (CTA) for use with the GeoMx DSP blends high-plex and spatial analysis in a single experiment. GeoMx DSP enables spatially resolved, digital characterization of proteins or mRNA in a highly multiplexed (>1,000-plex) assay. The assay relies upon antibody or RNA probes coupled to photocleavable oligonucleotide tags called DSP barcodes. After hybridization of probes to slide-mounted tissue sections, the DSP barcodes are released from discrete regions of the tissue via UV exposure. Released tags are quantitated via sequencing, and counts are mapped back to tissue location, yielding a spatially-resolved digital profile of analyte abundance. CTA uses the RNA probes described above and has been designed with the spatial context of cancer biology in mind, to enable studying key facets of disease without compromising sensitivity or specificity in Formalin Fixed Paraffin Embedded (FFPE) and fresh frozen tissues.

Targeted therapies for cancer are increasingly being developed as an alternative for, and in addition to, immunotherapy. Altered tumor signaling can be exploited to single-out cancer cells for destruction while leaving normal cells intact. However, as we continue to learn, a therapeutic strategy that treats the biology of the tumor by itself in a vacuum without the context of the immune response and the surrounding microenvironment can lead to reduced efficacy. The new nCounter Tumor Signaling 360 gene expression panel homes in on signaling pathways involved in the sustained growth and maintenance of tumor cells while providing a holistic view of the immune response and microenvironment that can be complicit in the development and progression of cancer. Using the foundation of the PanCancer IO 360 and Breast Cancer 360 panels as a model, the Tumor Signaling 360 panel was designed to include 770 genes across 40+ pathways integral for tumor biology, immune evasion, and microenvironment remodeling. The panel offers the same direct, digital detection benefits of other NanoString gene expression panels and includes the 18-gene Tumor Inflammation Signature (TIS) as well as 14 immune cell type signatures for profiling the peripheral immune response.

Rational: Pancreatic Ductal Adenocarcinoma (PDAC) is a highly aggressive disease associated with poor outcome. Most PDAC patients die within the first two years, and only a small subgroup of patients exceeds this survival rate. So far, factors and pathways underlying long-term survivorship in PDAC are unknown. In a previous study we showed that high CD8/FoxP3 ratio is associated with a favorable outcome. Therefore, we aimed to reveal the immune-related key players that drive the long-term survivorship in PDAC patients.

Methods: The immune-related gene expression profiles of 10 PDAC patients survived and free of recurrence for ≥ 5 years, was compared to 10 PDAC patients in whom recurrence and death occurred within 6 months after surgery. Samples were profiled using the PanCancer Immune Profiling Panel of nanoString technology. Subsequently, a subgroup of samples was measured by the GeoMx Digital Spatial Profiler (DSP) to determine the spatial location of the immune cells.

Results: The immune microenvironment in long-term survivors was altered differentially than that of the short-term survivors. B cells were found to be highly expressed in long-term survivors by gene expression profile. The presence of B cells was confirmed by performing a high-plex proteomic analysis with spatial resolution (GeoMx DSP). B cells infiltrated to the tumor stroma together with T cells and antigen presenting cells in long-term survivors.

Conclusion: This is the first comprehensive study that compares the expression and the spatial infiltration of immune cells in PDAC patients with different survival rates. Our data demonstrate that long-term survivorship of PDAC patients is influenced by the presence of B cells in the tumor microenvironment. The role of B cells in PDAC disease is controversial. However, our findings illustrate that B cells interact with other compartments of the immune system and drive long-term survivorship in PDAC patients.

Hosein Aziz1, Lawlaw Saida1, Jasper Dumas2,4, Andrew Stubbs2,3, Yunlei Li2,3, Casper van Eijck1,4 and Dana A. Mustafa2,4

1 Department of Surgery, 2 Department of Pathology, 3 Division of Clinical Bioinformatics, 4 The Tumor Immuno-Pathology (TIP) Laboratory, Erasmus University Medical Center, Rotterdam, the Netherlands.

The RNAscope in situ hybridization technology allows high sensitivity, specificity and spatial resolution providing pivotal single-cell gene expression information to gain better insights into the complex and heterogeneous tumor microenvironment. Using the RNAscope technology, it is possible to simultaneously visualize and assess the gene expression of cytokines, chemokines, immune cell markers, tumor cell markers and checkpoint markers within the tumor in order to:

- Understand complex spatial relationship among different cell types within the TME

-Profile immune checkpoint markers and other therapeutic targets

-Characterize immune cell types and activation states

Background: Pathologists have long recognized that the interaction between immune and tumour cells is critical in the development and progression of breast cancer. Studies have demonstrated the presence of tumour-infiltrating lymphocytes (TILs) correlates with improved clinical outcome in breast cancer especially in the triple negative and HER-2 positive subtypes. TILs predict for improved response to certain therapies including chemotherapy and trastuzumab. The predictive value of TILs in ER positive tumours is less clear. It has been demonstrated the higher presence of the immune microenvironment is associated with a better prognosis and as a result a higher likelihood of benefit from chemotherapy and possibly from immunotherapy, whereas cold immune microenvironment carries greater risk of relapse and lower benefit from chemotherapy and possibly immuno-therapies. In this study we examined the immune landscape in early breast cancer patients prior to anthracycline treatment.

Methods: NanoString’s DSP platform was used to analysis 256 patient samples from the BR9601 clinical trial. A panel of 56 antibodies incorporating the Immune Profile Core; 22 targets, IO Drug Target, Immune Activation Status, Immune Cell Typing, and Pan Tumour were examined and 2 fluorescent markers (pan-cytokeratin (pan-CK) and CD45) were used to select regions of interest (ROI).

Results: Proteomic analysis was successfully performed on 256 cores from the BR9601 cohort. Multivariate analysis demonstrated 27 proteins were associated with distant relapse free survival. A T-cell score was generated using the average expression of CD3, CD4 and CD8. The T-cell score was examined in both the tumour and TME. Using the T cell score it was apparent that the cohort had a range of immune “hot” and immune “cold” tumours. It was demonstrated that immune “hot” TME doesn’t not always correlate with immune “hot” tumour expression. Proteins that were most associated with T-cell exclusion (p<0.01) in the TME were Fibronectin, B7-H3, PTEN, ER-α, TGFB1, FAPα and CD34. This would indicate that these proteins are causal inhibitors of T-cell invasion.

Conclusion: In conclusion, this study highlights the significance of assessing the entire tumour since TILs, tumour and stromal cells collectively engage in a complex interplay that contributes to disease development and progression. NanoString’s GeoMx DSP is a promising technology for multiplexed analysis. TILs, whether measured using automated software, or estimation by protein profiling, are predictive of chemotherapy benefit.

Immune checkpoint inhibitors (ICI) have shown durable and long-term benefits in a subset of head and neck squamous cell carcinoma (HNSCC) patients. To identify patient-responders from non-responders, biomarkers are needed which are predictive of outcome to ICI therapy. Cues in the tumour microenvironment (TME) have been informative in understanding the tumour-immune contexture. In this study, the NanoString GemoMx™ Digital Spatial Profiling (DSP) technology was used to determine the immune marker and compartment specific measurements in a cohort of HNSCC tumours from patients receiving ICI therapy. Our data revealed that markers involved with immune cell infiltration (CD8 T-cells) were not predictive of outcome to ICI therapy. Rather, a number of immune cell types were found to correlate with progressive disease. This study, to our knowledge, represents the first spatial analysis of HNSCC tumours.

1 The School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology, Kelvin Grove, QLD, Australia.

2 Translational Research Institute, Brisbane, QLD, Australia.

The majority of patients with advanced NSCLC do not respond to monotherapy with PD-1 axis inhibition, and more robust predictive biomarkers are needed. In this study, we assessed tumor samples from 67 immunotherapy-treated NSCLC cases represented in a tissue microarray, 53 of whom had pre-treatment samples and received monotherapy. Using GeoMx Digital Spatial Profiling (DSP) system (NanoString), we quantified 39 immune parameters simultaneously in four tissue compartments defined by fluorescence co-localization (tumor [panCK+], leucocytes [CD45+], macrophages [CD68+], and non-immune stroma). In the univariate unadjusted analysis, we found 18 markers associated with outcome in spatial context, 5 of which remained significant after multiplicity adjustment and after controlling for clinical confounding factors. In the multivariate analysis, high expression of CD56 and CD4 in the CD45 compartment were significantly associated with all favorable clinical outcomes, whereas high levels of VISTA and CD127 in the tumor compartment were markers associated with immunotherapy resistance. We also validated the DSP finding that high CD56+ immune cell counts in the stroma were predictive for PFS and OS in the same set of patients using multiplex immunofluorescence, strengthening the relevance of NK/NKT cells

Pancreatic ductal adenocarcinoma (PDAC) remains a treatment-refractory disease and existing molecular subtypes do not inform clinical decisions. Previously-identified bulk transcriptomic subtypes of PDAC were derived exclusively in the treatment-naïve context and several are unintentionally driven by “contaminating” stroma. RNA extraction from pancreatic tissue is difficult and prior single-cell RNA-seq efforts have been limited by suboptimal dissociation/RNA quality and poor performance with the trend towards increased use of neoadjuvant chemoradiotherapy (CRT). To address these limitations, we developed a robust single-nucleus RNA-seq (sNuc-seq) technique compatible with frozen archival PDAC specimens (both naïve and treated) and computational techniques to identify the transcriptomic programs driving intratumoral heterogeneity and therapeutic resistance.

Single nuclei suspensions were extracted from flash frozen primary PDAC specimens and processed with the 10x Genomics Single Cell 3’ v3 pipeline and gene expression libraries were sequenced (Illumina HiSeq 2500). Combined treatment-naïve (n=13) and CRT-treated (n=12) specimens yielded approximately 150,000 high-quality nuclei. In each tumor, distinct clusters with gene expression profiles consistent with acinar, ductal, fibroblast, endothelial, endocrine, lymphocyte, and myeloid populations were identified. Malignant cells were confirmed by inferred copy number variation analysis (InferCNV v3.9) and segregated into several distinct programs by non-negative matrix factorization (NMF) for each individual patient highlighting intratumoral heterogeneity. Previously identified basal-like and classical-like programs were identified in a subset of treatment-naïve cells but not CRT-treated cells. In the treatment-naïve cohort, we identified additional NMF programs that were distinct from the basal-like and classical-like signatures (neuronal, epithelial-mesenchymal transition, anabolic, catabolic, cycling). In CRT-treated specimens, there was enrichment of catabolic and epithelial-mesenchymal transition programs and several unique programs were also uncovered (invasive stem-like, neuronal stem-like, and stress signaling). Deconvolution of clinically-annotated bulk RNA-seq cohorts using our sNuc-seq signatures and characterization of intercellular interactions with receptor-ligand analysis, spatial transcriptomics (Nanostring GeoMx™ Digital Spatial Profiler), and multiplexed immunofluorescence are ongoing.

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

We applied CITE-Seq to measure >150 cell surface immune markers and checkpoint proteins simultaneous to RNA-Sequencing. We resolve the tumour-immune milieu with high precision and reveal subsets of CD8 T cells that are specific to luminal and triple-negative breast cancers, with unique checkpoint molecule expression. In addition, a number of stromal cell-states were identified across the cohort, including three subsets of cancer-associated fibroblasts (CAFs), two subsets of smooth-muscle cells and four subsets of endothelial cells. Distinct transcription factor networks regulate these polarised states. We derived novel markers for these populations using CITE-Seq and carried out prospective isolation and functional characterisation of stromal subsets. Ligand-receptor signalling predicted a role for CAF subsets in T cell immunosuppression, which was further supported by deconvoution analysis of large bulk RNA_Seq cohorts and by in vitro CAF-T-cell co-culture proliferation assays.

Background: Growing evidence supports the critical role of preexisting immune response in triple negative breast cancer (TNBC). However, there are limitations with current evaluation approaches: inability to functionally assess the type of immune infiltration with traditional pathologic evaluation and loss of spatial distribution in conventional high-plex gene or protein expression analyses from the whole tumor section. Here, we report the initial analysis of immune protein expression as a function of spatial distribution and clinical outcomes in TNBC samples.

Methods: NanoString GeoMx® Digital Spatial Profiling (DSP) was used to quantify 39 immunerelated proteins in stromal and tumor segments from 44 TNBC samples from the FinXX trial. Samples were matched for patient characteristics, treatment arm (capecitabine vs. 5- fluorouracil), and outcome based on recurrence-free survival (RFS) with 22 samples from patients who recurred and 22 samples from patients with durable RFS. Regions of interest (ROIs) were selected based on expression of cytokeratin (tumor), CD45 (leukocytes), or CD68 (macrophages). Each ROI was segmented into tumor (pancytokeratin-positive area) and stroma (pancytokeratin-negative/nuclear SYTO13-positive area). The general linear model was used for statistical analysis of differential expression with RFS as a categorical variable (recur yes or no).

Results: A total of 950 tumor and stroma segments were included in this initial analysis. In both tumor and stroma segments, over-expression of T cell activation markers (CD137, GITR) was associated with better outcome, whereas T cell markers (CD3, CD4, CD8) were not significantly associated with outcome. In tumor segments alone, improved outcome was significantly associated with increased protein expression [> 2-fold change (FC) at p2.0, p2.0, p
In CD45-enriched stroma, improved outcome was associated with elevated expression (FC>2.0, p2.0, p
whereas durable RFS was associated with elevated PD-L2 and IDO1 expression in CD68-enriched stroma. In contrast, macrophage/dendritic cell markers CD68 and CD11c were not associated with outcome. In tumor cells adjacent to CD45-enriched stroma, durable RFS was associated with increased abundance (FC>2.0, p
Among 39 immune function proteins, only elevated CTLA4 expression in CD68-enriched stroma was associated with recurrence (FC=0.55, p whereas tumor-segment CTLA4 was associated with RFS.

Conclusions: Using an in-depth analysis to precisely quantify the abundance of multiple immune function proteins in a spatially defined manner, we observed that PD-L2, IDO1, and T cell activation markers were robustly associated with durable RFS in both tumor and stromal segments. In contrast, MHC components (HLA-DR, beta-2-microglobulin), B cell markers (CD20), and NK cell markers (CD56) were strongly associated with favorable outcome in tumor but not in stromal segments. Our study highlights the conclusion that the immune landscape of TNBC is far too complex to be encompassed by any single molecular marker, and more detailed analyses of the DSP data reported here are ongoing with a view towards using quantitative multiplex analyses to refine our understanding of how therapeutic outcome is influenced by interactions among immune cells and between immune and tumor cells.

The GeoMx Digital Spatial Profiling technology enables high-plex RNA and protein profiling of any region within any tissue type. This workshop will highlight the latest developments toward enabling spatial transcriptome analysis as well as highlighting novel applications in CAR T biology. Dr. Carl June, MD (University of Pennsylvania), will describe this application in a patient undergoing CAR T cellular therapy. GeoMx DSP was used to spatially analyze thousands of RNA targets to understand differences in tumor-related pathways in the presence of CAR T cells and the exhaustion status of the CAR T cells themselves.

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