Tumoral and stromal hMENA isoforms impact tertiary lymphoid structure localization in lung cancer and predict immune checkpoint blockade response in patients with cancer

BACKGROUND

Tertiary Lymphoid Structures (TLS) correlate with positive outcomes in patients with NSCLC and the efficacy of immune checkpoint blockade (ICB) in cancer. The actin regulatory protein hMENA undergoes tissue-specific splicing, producing the epithelial hMENA11a linked to favorable prognosis in early NSCLC, and the mesenchymal hMENAΔv6 found in invasive cancer cells and pro-tumoral cancer-associated fibroblasts (CAFs). This study investigates how hMENA isoforms in tumor cells and CAFs relate to TLS presence, localization and impact on patient outcomes and ICB response.

METHODS

Methods involved RNA-SEQ on NSCLC cells with depleted hMENA isoforms. A retrospective observational study assessed tissues from surgically treated N0 patients with NSCLC, using immunohistochemistry for tumoral and stromal hMENA isoforms, fibronectin, and TLS presence. ICB-treated patient tumors were analyzed using Nanostring nCounter and GeoMx spatial transcriptomics. Multiparametric flow cytometry characterized B cells and tissue-resident memory T cells (TRM). Survival and ICB response were estimated in the cohort and validated using bioinformatics pipelines in different datasets.

FINDINGS

Findings indicate that hMENA11a in NSCLC cells upregulates the TLS regulator LTβR, decreases fibronectin, and favors CXCL13 production by TRM. Conversely, hMENAΔv6 in CAFs inhibits LTβR-related NF-kB pathway, reduces CXCL13 secretion, and promotes fibronectin production. These patterns are validated in N0 NSCLC tumors, where hMENA11ahigh expression, CAF hMENAΔv6low, and stromal fibronectinlow are associated with intratumoral TLS, linked to memory B cells and predictive of longer survival. The hMENA isoform pattern, fibronectin, and LTβR expression broadly predict ICB response in tumors where TLS indicates an anti-tumor immune response.

INTERPRETATION

This study uncovers hMENA alternative splicing as an unexplored contributor to TLS-related Tumor Immune Microenvironment (TIME) and a promising biomarker for clinical outcomes and likely ICB responsiveness in N0 patients with NSCLC.

FUNDING

This work is supported by AIRC (IG 19822), ACC (RCR-2019-23669120), CAL.HUB.RIA Ministero Salute PNRR-POS T4, "Ricerca Corrente" granted by the Italian Ministry of Health.

Building smart CAR T cell therapies: The path to overcome current challenges

Successful implementation of adoptive cell therapy (ACT) of cancer requires comprehensively addressing biological and practical challenges. This approach has been largely overlooked, resulting in a gap between the potential of ACT and its actual effectiveness. We summarize the most promising technical strategies in creating an "ideal" ACT product, focusing on chimeric antigen receptor (CAR)-engineered cells. Since many requirements for effective ACT are common to most cancers, what we outline here might have a broader impact.

CD39 and LDHA affects the prognostic role of NLR in metastatic melanoma patients treated with immunotherapy

BACKGROUND

Identifying response markers is highly needed to guide the treatment strategy in patients with metastatic melanoma.

METHODS

A retrospective study was carried out in patients with unresectable/metastatic melanoma (stage IIIb-IV), treated with anti-PD-1 in the first line setting, to better explore the role and the timing of neutrophil/lymphocyte ratio (NLR) as potential biomarker of response. The relationship of NLR with inflammation-immune mediators and the underlying negative effect of raising NLR during immunotherapy, have been investigated with transcriptomic gene analysis.

RESULTS

The results confirmed previous findings that a high baseline NLR is associated with a poorer prognosis and with higher serum level of lactate dehydrogenase (LDH), regardless of the presence of brain metastases. The transcriptomic analysis showed that high baseline NLR is associated with a characteristic gene signature CCNA1, LDHA and IL18R1, which correlates with inflammation and tumorigenesis. Conversely, low baseline NLR is associated with the signature CD3, SH2D1A, ZAP70 and CD45RA, linked to the immune-activation. The genes positively associated with NLR (CD39 (ENTPD1), PTEN, MYD88, MMP9 and LDH) are involved in processes of immunosuppression, inflammation and tumor-promoting activity. Increased expression of CD39 correlated with TGFβ2, a marker of the N2 neutrophils with immunosuppressive activity.

CONCLUSIONS

These results suggest that increasing NLR is associated with an increased neutrophil population, with polarization to the N2 phenotype, and this process may be the basis for the negatively prognostic role of NLR.

hMENA isoforms regulate cancer intrinsic type I IFN signaling and extrinsic mechanisms of resistance to immune checkpoint blockade in NSCLC

BACKGROUND

Understanding how cancer signaling pathways promote an immunosuppressive program which sustains acquired or primary resistance to immune checkpoint blockade (ICB) is a crucial step in improving immunotherapy efficacy. Among the pathways that can affect ICB response is the interferon (IFN) pathway that may be both detrimental and beneficial. The immune sensor retinoic acid-inducible gene I (RIG-I) induces IFN activation and secretion and is activated by actin cytoskeleton disturbance. The actin cytoskeleton regulatory protein hMENA, along with its isoforms, is a key signaling hub in different solid tumors, and recently its role as a regulator of transcription of genes encoding immunomodulatory secretory proteins has been proposed. When hMENA is expressed in tumor cells with low levels of the epithelial specific hMENA11a isoform, identifies non-small cell lung cancer (NSCLC) patients with poor prognosis. Aim was to identify cancer intrinsic and extrinsic pathways regulated by hMENA11a downregulation as determinants of ICB response in NSCLC. Here, we present a potential novel mechanism of ICB resistance driven by hMENA11a downregulation.

METHODS

Effects of hMENA11a downregulation were tested by RNA-Seq, ATAC-Seq, flow cytometry and biochemical assays. ICB-treated patient tumor tissues were profiled by Nanostring IO 360 Panel enriched with hMENA custom probes. OAK and POPLAR datasets were used to validate our discovery cohort.

RESULTS

Transcriptomic and biochemical analyses demonstrated that the depletion of hMENA11a induces IFN pathway activation, the production of different inflammatory mediators including IFNβ via RIG-I, sustains the increase of tumor PD-L1 levels and activates a paracrine loop between tumor cells and a unique macrophage subset favoring an epithelial-mesenchymal transition (EMT). Notably, when we translated our results in a clinical setting of NSCLC ICB-treated patients, transcriptomic analysis revealed that low expression of hMENA11a, high expression of IFN target genes and high macrophage score identify patients resistant to ICB therapy.

CONCLUSIONS

Collectively, these data establish a new function for the actin cytoskeleton regulator hMENA11a in modulating cancer cell intrinsic type I IFN signaling and extrinsic mechanisms that promote protumoral macrophages and favor EMT. These data highlight the role of actin cytoskeleton disturbance in activating immune suppressive pathways that may be involved in resistance to ICB in NSCLC.

Highly Multiplexed Spatially Resolved Proteomic and Transcriptional Profiling of the Glioblastoma Microenvironment Using Archived Formalin-Fixed Paraffin-Embedded Specimens

Glioblastoma is a heterogeneous tumor for which effective treatment options are limited and often insufficient. Few studies have examined the intratumoral transcriptional and proteomic heterogeneity of the glioblastoma microenvironment to characterize the spatial distribution of potential molecular and cellular therapeutic immunooncology targets. We applied an integrated multimodal approach comprised of NanoString GeoMx Digital Spatial Profiling, single-cell RNA-seq (scRNA-seq), and expert neuropathologic assessment to characterize archival formalin-fixed paraffin-embedded glioblastoma specimens. Clustering analysis and spatial cluster maps highlighted the intratumoral heterogeneity of each specimen. Mixed cell deconvolution analysis revealed that neoplastic and vascular cells were the prominent cell types throughout each specimen, with macrophages, oligodendrocyte precursors, neurons, astrocytes, and oligodendrocytes present in lower abundance and illustrated the regional distribution of the respective cellular enrichment scores. The spatial resolution of the actionable immunotherapeutic landscape showed that robust B7H3 gene and protein expression was broadly distributed throughout each specimen and identified STING and VISTA as potential targets. Lastly, we uncovered remarkable variability in VEGFA expression and discovered unanticipated associations between VEGFA, endothelial cell markers, hypoxia, and the expression of immunoregulatory genes, indicative of regionally distinct immunosuppressive microdomains. This work provides an early demonstration of the ability of an integrated panel-based spatial biology approach to characterize and quantify the intrinsic molecular heterogeneity of the glioblastoma microenvironment.

Baseline gene expression profiling determines long-term benefit to programmed cell death protein 1 axis blockade

Treatment with immune checkpoint inhibitors has altered the course of malignant melanoma, with approximately half of the patients with advanced disease surviving for more than 5 years after diagnosis. Currently, there are no biomarker methods for predicting outcome from immunotherapy. Here, we obtained transcriptomic information from a total of 105 baseline tumor samples comprising two cohorts of patients with advanced melanoma treated with programmed cell death protein 1 (PD-1)-based immunotherapies. Gene expression profiles were correlated with progression-free survival (PFS) within consecutive clinical benefit intervals (i.e., 6, 12, 18, and 24 months). Elastic net binomial regression models with cross validation were utilized to compare the predictive value of distinct genes across time. Lasso regression was used to generate a signature predicting long-term benefit (LTB), defined as patients who remain alive and free of disease progression at 24 months post treatment initiation. We show that baseline gene expression profiles were consistently able to predict long-term immunotherapy outcomes with high accuracy. The predictive value of different genes fluctuated across consecutive clinical benefit intervals, with a distinct set of genes defining benefit at 24 months compared to earlier outcomes. A 12-gene signature was able to predict LTB following anti-PD-1 therapy with an area under the curve (AUC) equal to 0.92 and 0.74 in the training and validation set, respectively. Evaluation of LTB, via a unique signature may complement objective response classification and characterize the logistics of sustained antitumor immune responses.

74 Ge( n , γ ) cross section below 70 keV measured at n_TOF CERN

Neutron capture reaction cross sections on 74 Ge are of importance to determine 74 Ge production during the astrophysical slow neutron capture process. We present new resonance data on 74 Ge( n , γ ) reactions below 70 keV neutron energy. We calculate Maxwellian averaged cross sections, combining our data below 70 keV with evaluated cross sections at higher neutron energies. Our stellar cross sections are in agreement with a previous activation measurement performed at Forschungszentrum Karlsruhe by Marganiec et al., once their data has been re-normalised to account for an update in the reference cross section used in that experiment.

Nivolumab serum concentration in metastatic melanoma patients could be related to outcome and enhanced immune activity: a gene profiling retrospective analysis

BACKGROUND

Nivolumab is an anti-PD-1 antibody approved for treating metastatic melanoma (MM), for which still limited evidence is available on the correlation between drug exposure and patient outcomes.

METHODS

In this observational retrospective study, we assessed whether nivolumab concentration is associated with treatment response in 88 patients with MM and if the patient's genetic profile plays a role in this association.

RESULTS

We observed a statistically significant correlation between nivolumab serum concentration and clinical outcomes, measured as overall and progression-free survival. Moreover, patients who achieved a clinical or partial response tended to have higher levels of nivolumab than those who reached stable disease or had disease progression. However, the difference was not statistically significant. In particular, patients who reached a clinical response had a significantly higher concentration of nivolumab and presented a distinct genetic signature, with more marked activation of ICOS and other genes involved in effector T-cells mediated proinflammatory pathways.

CONCLUSIONS

In conclusion, these preliminary results show that in patients with MM, nivolumab concentration correlates with clinical outcomes and is associated with an increased expression of ICOS and other genes involved in the activation of T effectors cells.

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.

Concomitant medication of cetirizine in advanced melanoma could enhance anti-PD-1 efficacy by promoting M1 macrophages polarization

BACKGROUND

The clinical observation showed a potential additive effect of anti-PD-1 agents and cetirizine in patients with advanced melanoma.

METHODS

Clinical outcomes of concomitant cetirizine/anti-PD-1 treatment of patients with stage IIIb-IV melanoma were retrospectively collected, and a transcriptomic analysis was performed on blood samples obtained at baseline and after 3 months of treatment.

RESULTS

Patients treated with cetirizine concomitantly with an anti-PD-1 agent had significantly longer progression-free survival (PFS; mean PFS: 28 vs 15 months, HR 0.46, 95% CI: 0.28-0.76; p = 0.0023) and OS (mean OS was 36 vs 23 months, HR 0.48, 95% CI: 0.29-0.78; p = 0.0032) in comparison with those not receiving cetirizine. The concomitant treatment was significantly associated with ORR and DCR (p < 0.05). The expression of FCGR1A/CD64, a specific marker of macrophages, was increased after the treatment in comparison with baseline in blood samples from patients receiving cetirizine, but not in those receiving only the anti-PD1, and positively correlated with the expression of genes linked to the interferon pathway such as CCL8 (rho = 0.32; p = 0.0111), IFIT1 (rho = 0.29; p = 0.0229), IFIT3 (rho = 0.57; p < 0.0001), IFI27 (rho = 0.42; p = 0.008), MX1 (rho = 0.26; p = 0.0383) and RSAD2 (rho = 0.43; p = 0.0005).

CONCLUSIONS

This retrospective study suggests that M1 macrophage polarization may be induced by cetirizine through the interferon-gamma pathway. This effect may synergize with the immunotherapy of advanced melanoma with anti-PD-1 agents.

Safety and immunogenicity of the inactivated whole-virus adjuvanted COVID-19 vaccine VLA2001: A randomized, dose escalation, double-blind phase 1/2 clinical trial in healthy adults

OBJECTIVES

We aimed to evaluate the safety and optimal dose of a novel inactivated whole-virus adjuvanted vaccine against SARS-CoV-2: VLA2001.

METHODS

We conducted an open-label, dose-escalation study followed by a double-blind randomized trial using low, medium and high doses of VLA2001 (1:1:1). The primary safety outcome was the frequency and severity of solicited local and systemic reactions within 7 days after vaccination. The primary immunogenicity outcome was the geometric mean titre (GMT) of neutralizing antibodies against SARS-CoV-2 two weeks after the second vaccination. The study is registered as NCT04671017.

RESULTS

Between December 16, 2020, and June 3, 2021, 153 healthy adults aged 18-55 years were recruited in the UK. Overall, 81.7% of the participants reported a solicited AE, with injection site tenderness (58.2%) and headache (46.4%) being the most frequent. Only 2 participants reported a severe solicited event. Up to day 106, 131 (85.6%) participants had reported any AE. All observed incidents were transient and non-life threatening in nature. Immunogenicity measured at 2 weeks after completion of the two-dose priming schedule, showed significantly higher GMTs of SARS-CoV-2 neutralizing antibody titres in the highest dose group (GMT 545.6; 95% CI: 428.1, 695.4) which were similar to a panel of convalescent sera (GMT 526.9; 95% CI: 336.5, 825.1). Seroconversion rates of neutralizing antibodies were also significantly higher in the high-dose group (>90%) compared to the other dose groups. In the high dose group, antigen-specific IFN-γ expressing T-cells reactive against the S, M and N proteins were observed in 76, 36 and 49%, respectively.

CONCLUSIONS

VLA2001 was well tolerated in all tested dose groups, and no safety signal of concern was identified. The highest dose group showed statistically significantly stronger immunogenicity with similar tolerability and safety, and was selected for phase 3 clinical development.

Safety, immunogenicity, and reactogenicity of BNT162b2 and mRNA-1273 COVID-19 vaccines given as fourth-dose boosters following two doses of ChAdOx1 nCoV-19 or BNT162b2 and a third dose of BNT162b2 (COV-BOOST): a multicentre, blinded, phase 2, randomised trial

BACKGROUND

Some high-income countries have deployed fourth doses of COVID-19 vaccines, but the clinical need, effectiveness, timing, and dose of a fourth dose remain uncertain. We aimed to investigate the safety, reactogenicity, and immunogenicity of fourth-dose boosters against COVID-19.

METHODS

The COV-BOOST trial is a multicentre, blinded, phase 2, randomised controlled trial of seven COVID-19 vaccines given as third-dose boosters at 18 sites in the UK. This sub-study enrolled participants who had received BNT162b2 (Pfizer-BioNTech) as their third dose in COV-BOOST and randomly assigned them (1:1) to receive a fourth dose of either BNT162b2 (30 μg in 0·30 mL; full dose) or mRNA-1273 (Moderna; 50 μg in 0·25 mL; half dose) via intramuscular injection into the upper arm. The computer-generated randomisation list was created by the study statisticians with random block sizes of two or four. Participants and all study staff not delivering the vaccines were masked to treatment allocation. The coprimary outcomes were safety and reactogenicity, and immunogenicity (anti-spike protein IgG titres by ELISA and cellular immune response by ELISpot). We compared immunogenicity at 28 days after the third dose versus 14 days after the fourth dose and at day 0 versus day 14 relative to the fourth dose. Safety and reactogenicity were assessed in the per-protocol population, which comprised all participants who received a fourth-dose booster regardless of their SARS-CoV-2 serostatus. Immunogenicity was primarily analysed in a modified intention-to-treat population comprising seronegative participants who had received a fourth-dose booster and had available endpoint data. This trial is registered with ISRCTN, 73765130, and is ongoing.

FINDINGS

Between Jan 11 and Jan 25, 2022, 166 participants were screened, randomly assigned, and received either full-dose BNT162b2 (n=83) or half-dose mRNA-1273 (n=83) as a fourth dose. The median age of these participants was 70·1 years (IQR 51·6-77·5) and 86 (52%) of 166 participants were female and 80 (48%) were male. The median interval between the third and fourth doses was 208·5 days (IQR 203·3-214·8). Pain was the most common local solicited adverse event and fatigue was the most common systemic solicited adverse event after BNT162b2 or mRNA-1273 booster doses. None of three serious adverse events reported after a fourth dose with BNT162b2 were related to the study vaccine. In the BNT162b2 group, geometric mean anti-spike protein IgG concentration at day 28 after the third dose was 23 325 ELISA laboratory units (ELU)/mL (95% CI 20 030-27 162), which increased to 37 460 ELU/mL (31 996-43 857) at day 14 after the fourth dose, representing a significant fold change (geometric mean 1·59, 95% CI 1·41-1·78). There was a significant increase in geometric mean anti-spike protein IgG concentration from 28 days after the third dose (25 317 ELU/mL, 95% CI 20 996-30 528) to 14 days after a fourth dose of mRNA-1273 (54 936 ELU/mL, 46 826-64 452), with a geometric mean fold change of 2·19 (1·90-2·52). The fold changes in anti-spike protein IgG titres from before (day 0) to after (day 14) the fourth dose were 12·19 (95% CI 10·37-14·32) and 15·90 (12·92-19·58) in the BNT162b2 and mRNA-1273 groups, respectively. T-cell responses were also boosted after the fourth dose (eg, the fold changes for the wild-type variant from before to after the fourth dose were 7·32 [95% CI 3·24-16·54] in the BNT162b2 group and 6·22 [3·90-9·92] in the mRNA-1273 group).

INTERPRETATION

Fourth-dose COVID-19 mRNA booster vaccines are well tolerated and boost cellular and humoral immunity. Peak responses after the fourth dose were similar to, and possibly better than, peak responses after the third dose.

FUNDING

UK Vaccine Task Force and National Institute for Health Research.

Abstract 3817: A single-cell, spatial multiomics atlas and cellular interactome of all major skin cancer types

Skin cancer is by far the most common cancer, encompassing squamous cell carcinoma (SCC), basal cell carcinoma (BCC), and melanoma. The diversity of cell types and tissue organisation in skin cancer remains poorly understood yet is required to improve diagnosis and treatment. In this work, we integrated six imaging and sequencing technologies to build the first spatial single cell reference for all three major skin cancer types and create a comprehensive skin cancer interactome. Using single-cell RNA-Seq (RNA) of &gt;100,000 cells from 11 paired patient biopsies, we identified 28 SCC cell types, including 10 immune cell types, and found core suites of 39 cancer genes and 222 healthy genes shared across ≥80% patient samples. Using independent Nanostring Digital Spatial Profiling (RNA, protein), we validated most immune cell types and gene markers at protein and RNA levels. The enrichment of an immune signalling signature in SCC was further revealed by spatial Nanostring Single Molecular Imaging - SMI (RNA). Strikingly, we found the high consistency in mapping cell types in scRNAseq data and the independent SMI data, for example, the distribution of the three keratinocyte layers (basal, cycling and differentiated). This observation suggested the power of combining scRNAseq data with spatial SMI data. Furthermore, we implemented three approaches to validate the spatial distribution and cell type co-localisation by both Visium Spatial Transcriptomics (RNA), SMI (RNA) and Opal Multiplex Polaris (protein). Finally, cell-cell interactions were inferred at the global level using scRNAseq data (no spatial information) and Visium data (with spatial dimension), which were then validated at high throughput (517 ligands/receptors) and single-cell resolution using SMI. These in situ interaction maps were built across all three cancer types to create a comprehensive spatial interaction atlas of skin cancer. We also used targeted approaches with Polaris (protein) and RNAScope (RNA) to confirm and visualise clinically-important ligand-receptor pairs, including checkpoint inhibitor drug targets PD-1 and PD-L1. By integrating six distinct yet complementary spatial and single cell technologies, this study highlights the power of a spatial multi-omics approach for understanding cell types and their activities in cancer tissues.

Citation Format: Laura Grice, Guiyan Ni, Xinnan Jin, Minh Tran, Emily Killingbeck, Mark Gregory, Onkar Mulay, Siok-Min Teoh, Arutha Kulasinghe, Michael Leon, Sarah Murphy, Sarah Warren, Youngmi Kim, Quan Nguyen. A single-cell, spatial multiomics atlas and cellular interactome of all major skin cancer types [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 3817.

Abstract 3484: Development of a custom high-plex GeoMx digital spatial profiler breast cancer protein biomarker assay

The goal of this study was to develop a high-plex assay to simultaneously quantitate 27 established and novel breast cancer (BC)-related, immune protein and phosphoprotein biomarkers using the GeoMx® Digital Spatial Profiler (DSP). The custom assay performance was compared to standard clinical BC biomarker assays (e.g.ER, PR, HER2, Ki67) across the spectrum of BC subtypes and in multiple laboratories. Commercially available antibodies to 27 BC-related protein biomarkers, including ER, PR, HER2, Ki-67, AR, immune-related (e.g. PD-L1) and several cell cycle/proliferation markers were oligonucleotide-tagged, and verified by immunohistochemistry for performance against untagged antibodies. The tagged antibodies were combined with 3 isotype controls and 2 housekeeping proteins into a custom BC high-plex assay for DSP. Confirmation of target specificity was done on a custom tissue microarray (TMA) (Run control) composed of (un)treated cancer cell lines and normal tissues. For clinical BC samples, each biopsy had 4x600 µm regions of interest segmented into pan-Cytokeratin+ tumoral epithelium and pan-Cytokeratin- adjacent stroma segments. With targeted UV light, oligonucleotides were collected from each segment sequentially and quantitated with nCounter. Raw counts were geomean normalized for analysis. Intra-site and inter-site assay reproducibility was assessed with the TMA and serial FFPE sections from BC biopsies. Quantitation of proteins showed high reproducibility within sites (e.g. Run 1 v. Run 2, p&gt;0.05 for all protein targets) and the high-plex custom assay showed good concordance between 3 participating laboratories. GeoMx DSP-derived protein data correlated well with orthogonal methodologies performed on a sample subset including immunohistochemistry, reverse phase protein array, DNA and RNA-sequencing. For example, DSP protein counts for p53 protein were higher in tumors with TP53 point mutation than those with truncating TP53 alterations. Expanded sample testing is underway with 120 well-characterized breast cancer biopsies of various histologies, immune subtypes (e.g. TIL scores) and clinical biomarker phenotypes (e.g. ER+/HER2-/Ki-67 high BC; ER+/HER2-/Ki-67 low BC; HER2+ BC; ER-/PR-/HER2- BC).Our preliminary data demonstrate that this custom high-plex BC assay can quantitate protein biomarkers across a wide dynamic range with high intra-lab and inter-lab reproducibility. The assay requirement of a single 5-µm tissue section facilitates complex biomarker profiling in biopsies with limited material. The custom assay alone or in combination with other targeted DSP protein modules can simultaneously interrogate the biomarker profile, immune-based and other drug target profile, and immune microenvironment of BC specimens, providing a novel approach for actionable tumor subtyping. For research use only. Not for use in diagnostic procedures.

Citation Format: Christopher Corless, Amber Bridgeman, Jinho Lee, Gary Geiss, Sarah Warren, Sarah Church, Joseph M. Beechem, E Aubrey Thompson, Jodi Carter. Development of a custom high-plex GeoMx digital spatial profiler breast cancer protein biomarker assay [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 3484.

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 66: A multi-institution examination of concordance in spatial transcriptomics using the GeoMx Cancer Transcriptome Atlas

Multiplexed spatial profiling can enable biological insights by characterizing gene expression within discrete physical locations of a tissue. However, these advanced techniques can be confounded by variability of sample collection, storage, or profiling protocols, making it difficult to accurately compare data generated by different laboratories. Further, as more spatial profiling datasets become publicly available, having methods to enable meta-analysis of samples collected on different studies will maximize the learnings to support the advancement of treatments or identifying patient segments.

To quantify the variability of spatial profiling data at different laboratories and to advance data normalization methodologies, 4 independent laboratories used the NanoString® GeoMx® Digital Spatial Profiling (DSP) to profile serial 5 µm sections of tissue and cell pellet arrays (CPAs). GeoMx DSP enables high throughput, spatially resolved analysis of gene or protein expression from fresh or archival human tissues. In this study, the GeoMx Cancer Transcriptome Atlas was used to profile &gt;1800 genes simultaneously. We examined the concordance of GeoMx data generated in the different laboratories when controlling for methodical variation (e.g., reagents, tissue source) and experimentally varying region of interest (ROI) size, collection site, and sample preservation methods.

Sections of tonsil, colon, and 2 CPAs were profiled separately at the 4 laboratories. Each analyzed fresh cut (FC) tissues and two sites examined sample stability by analyzing the impact of storing slides at -80°C for 1 month prior to spatial profiling. Concordance analysis was performed using the Horn-Morisita Index on raw data comparing paired and unpaired ROIs across each set of slides.

In CPA samples where each pellet was a different tumor type (e.g., NSCLC, melanoma), we observed strong clustering by cell line. While data initially showed varying degrees of clustering by slide, factoring out this variable removed the association of slide, allowing integration of the data across profiling locations without affecting concordance within slides. In tonsil, ROIs with increasing area were profiled. Comparing expression between pairs of samples for a given area, concordance increased with ROI size (R = -0.40, p&lt;6e-06). Finally, we observed little impact of preservation method (FC vs -80°C) in these data.

In this study, we quantify slide-specific variation observed in high-plex RNA profiling by the DSP platform and detail methods for accounting for this variation. We note that many downstream analyses (e.g., differential expression) already model slide effects during the analysis, but modeling it explicitly allows for direct comparison of concordance with other approaches (e.g., clustering, PCA). These methods support the use of multi-institution studies leveraging the GeoMx platform.

Citation Format: Tyler Hether, Tim Howes, David Scoville, Charlie Glaser, Yanyun Li, Rami Vanguri, Neeman Mohibullah, Wan-Jung Chang, Todd Yoder, Minnal Gupta, Kathy Ton, Yan Liang, Ying Huang, Zach Herbert, Jason Reeves, Elizabeth Mittendorf, Simon Lacey, Travis Hollmann, Sarah Warren, Theresa LaVallee. A multi-institution examination of concordance in spatial transcriptomics using the GeoMx Cancer Transcriptome Atlas [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 66.

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.

Abstract SY12-04: Multicellular spatial community featuring a novel neuronal-like malignant phenotype is enriched in pancreatic cancer after neoadjuvant chemotherapy and radiotherapy

Pancreatic ductal adenocarcinoma (PDAC) is projected to be the second leading cause of cancer mortality in the United States by 2030. Given that resistance to cytotoxic therapy is pervasive, there is a critical need to elucidate salient gene expression programs and spatial relationships among malignant and stromal cells in the tumor microenvironment (TME), particularly in residual disease. We developed and applied a single-nucleus RNA-seq (snRNA-seq) technique to 43 banked frozen primary PDAC specimens that either received neoadjuvant therapy (n=25) or were treatment-naïve (n=18). We discovered expression programs across malignant cell and fibroblast profiles that formed the basis for a refined molecular taxonomy, including a novel neural-like progenitor (NRP) malignant program enriched with neoadjuvant treatment in tumors and organoids, and associated with the worst prognosis in bulk profiles from independent cohorts.

To elucidate how neoadjuvant treatment and cancer cell- and fibroblast-intrinsic programs modulate the composition of multicellular neighborhoods, we performed spatial profiling with the GeoMx[1] platform (NanoString) on 21 formalin-fixed paraffin-embedded sections using the human whole transcriptome atlas (WTA). Each tumor showed intra-tumoral heterogeneity in tissue architecture and regions of interest (ROIs) with diverse patterns of neoplastic cells, cancer-associated fibroblasts (CAFs), and immune cells were selected for profiling. We deconvolved the WTA data with our snRNA-seq cell type signatures and mapped expression programs onto the tumor architecture to reveal three distinct multicellular neighborhoods, which we annotated as classical, squamoid-basaloid, and treatment-enriched. The observed enrichment in post-treatment residual disease of multiple spatially-defined receptor-ligand interactions and a neighborhood featuring the NRP program, neurotropic CAF program, and CD8+ T cells may open new therapeutic opportunities.

Next, we mapped malignant/CAF programs and immune cell subsets at single-cell spatial resolution by performing spatial molecular imaging (SMI[2]; NanoString CosMx) using a panel of 960 RNA targets on a subset of seven tumors (2 untreated, 5 treated) and captured over 200,000 cells with an average of more than 450 transcripts detected per cell. Correlating ROIs from whole-transcriptome DSP to matched fields of view in kiloplex SMI enabled further dissection of PDAC architecture and treatment-associated remodeling of cell type distributions and receptor-ligand interactions.

Ongoing functional studies have begun to elucidate the key regulatory elements underlying the distinct treatment-associated NRP malignant program and its interactions with the TME. Overall, the complementary combination of snRNA-seq, whole-transcriptome DSP, and kiloplex SMI provides a high-resolution molecular framework that can be harnessed to augment precision oncology efforts in pancreatic cancer.

[1] GeoMx DSP is for Research Use Only and not for use in diagnostic procedures. [2] CosMx SMI is for Research Use Only and not for use in diagnostic procedures.

Citation Format: William L. Hwang, Karthik A. Jagadeesh, Jimmy A. Guo, Hannah I. Hoffman, Carina Shiau, Jennifer Su, Payman Yadollahpour, Jason W. Reeves, Youngmi Kim, Sean Kim, Mark Gregory, Prajan Divakar, Eric Miller, Michael Rhodes, Sarah Warren, Erroll Rueckert, Kit Fuhrman, Daniel R. Zollinger, Robin Fropf, Joseph M. Beechem, Arnav Mehta, Toni Delorey, Cristin McCabe, Jaimie L. Barth, Piotr Zelga, Cristina R. Ferrone, Motaz Qadan, Keith D. Lillemoe, Rakesh K. Jain, Jennifer Y. Wo, Theodore S. Hong, Ramnik Xavier, Orit Rozenblatt-Rosen, Andrew J. Aguirre, Carlos Fernandez-Del Castillo, Andrew S. Liss, Mari Mino-Kenudson, David T. Ting, Tyler Jacks, Aviv Regev. Multicellular spatial community featuring a novel neuronal-like malignant phenotype is enriched in pancreatic cancer after neoadjuvant chemotherapy and radiotherapy [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 SY12-04.

Adaptive immune signature in HER2-positive breast cancer in NCCTG (Alliance) N9831 and NeoALTTO trials

Trastuzumab acts in part through the adaptive immune system. Previous studies showed that enrichment of immune-related gene expression was associated with improved outcomes in HER2-positive (HER2+) breast cancer. However, the role of the immune system in response to lapatinib is not fully understood. Gene expression analysis was performed in 1,268 samples from the North Central Cancer Treatment Group (NCCTG) N9831 and 244 samples from the NeoALTTO trial. In N9831, enrichment of CD45 and immune-subset signatures were significantly associated with improved outcomes. We identified a novel 17-gene adaptive immune signature (AIS), which was found to be significantly associated with improved RFS among patients who received adjuvant trastuzumab (HR 0.66, 95% CI 0.49-0.90, Cox regression model p = 0.01) but not in patients who received chemotherapy alone (HR 0.96, 95% CI 0.67-1.40, Cox regression model p = 0.97). This result was validated in NeoALTTO. Overall, AIS-low patients had a significantly lower pathologic complete response (pCR) rate compared with AIS-high patients (χ2 p < 0.0001). Among patients who received trastuzumab alone, pCR was observed in 41.7% of AIS-high patients compared with 9.8% in AIS-low patients (OR of 6.61, 95% CI 2.09-25.59, logistic regression model p = 0.003). More importantly, AIS-low patients had a higher pCR rate with an addition of lapatinib (51.1% vs. 9.8%, OR 9.65, 95% CI 3.24-36.09, logistic regression model p < 0.001). AIS-low patients had poor outcomes, despite receiving adjuvant trastuzumab. However, these patients appear to benefit from an addition of lapatinib. Further studies are needed to validate the significance of this signature to identify patients who are more likely to benefit from dual anti-HER2 therapy. ClinicalTrials.gov Identifiers: NCT00005970 (NCCTG N9831) and NCT00553358 (NeoALTTO).

Metabolic adaptation of ovarian tumors in patients treated with an IDO1 inhibitor constrains antitumor immune responses

To uncover underlying mechanisms associated with failure of indoleamine 2,3-dioxygenase 1 (IDO1) blockade in clinical trials, we conducted a pilot, window-of-opportunity clinical study in 17 patients with newly diagnosed advanced high-grade serous ovarian cancer before their standard tumor debulking surgery. Patients were treated with the IDO1 inhibitor epacadostat, and immunologic, transcriptomic, and metabolomic characterization of the tumor microenvironment was undertaken in baseline and posttreatment tumor biopsies. IDO1 inhibition resulted in efficient blockade of the kynurenine pathway of tryptophan degradation and was accompanied by a metabolic adaptation that shunted tryptophan catabolism toward the serotonin pathway. This resulted in elevated nicotinamide adenine dinucleotide (NAD⁺), which reduced T cell proliferation and function. Because NAD⁺ metabolites could be ligands for purinergic receptors, we investigated the impact of blocking purinergic receptors in the presence or absence of NAD⁺ on T cell proliferation and function in our mouse model. We demonstrated that A2a and A2b purinergic receptor antagonists, SCH58261 or PSB1115, respectively, rescued NAD⁺-mediated suppression of T cell proliferation and function. Combining IDO1 inhibition and A2a/A2b receptor blockade improved survival and boosted the antitumor immune signature in mice with IDO1 overexpressing ovarian cancer. These findings elucidate the downstream adaptive metabolic consequences of IDO1 blockade in ovarian cancers that may undermine antitumor T cell responses in the tumor microenvironment.

System-wide transcriptome damage and tissue identity loss in COVID-19 patients

The molecular mechanisms underlying the clinical manifestations of coronavirus disease 2019 (COVID-19), and what distinguishes them from common seasonal influenza virus and other lung injury states such as acute respiratory distress syndrome, remain poorly understood. To address these challenges, we combine transcriptional profiling of 646 clinical nasopharyngeal swabs and 39 patient autopsy tissues to define body-wide transcriptome changes in response to COVID-19. We then match these data with spatial protein and expression profiling across 357 tissue sections from 16 representative patient lung samples and identify tissue-compartment-specific damage wrought by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, evident as a function of varying viral loads during the clinical course of infection and tissue-type-specific expression states. Overall, our findings reveal a systemic disruption of canonical cellular and transcriptional pathways across all tissues, which can inform subsequent studies to combat the mortality of COVID-19 and to better understand the molecular dynamics of lethal SARS-CoV-2 and other respiratory infections.

Digital multiplexed analysis of circular RNAs in FFPE and fresh non‐small cell lung cancer specimens

Although many studies highlight the implication of circular RNAs (circRNAs) in carcinogenesis and tumor progression, their potential as cancer biomarkers has not yet been fully explored in the clinic due to the limitations of current quantification methods. Here, we report the use of the nCounter platform as a valid technology for the analysis of circRNA expression patterns in non‐small cell lung cancer (NSCLC) specimens. Under this context, our custom‐made circRNA panel was able to detect circRNA expression both in NSCLC cells and formalin‐fixed paraffin‐embedded (FFPE) tissues. CircFUT8 was overexpressed in NSCLC, contrasting with circEPB41L2, circBNC2, and circSOX13 downregulation even at the early stages of the disease. Machine learning (ML) approaches from different paradigms allowed discrimination of NSCLC from nontumor controls (NTCs) with an 8‐circRNA signature. An additional 4‐circRNA signature was able to classify early‐stage NSCLC samples from NTC, reaching a maximum area under the ROC curve (AUC) of 0.981. Our results not only present two circRNA signatures with diagnosis potential but also introduce nCounter processing following ML as a feasible protocol for the study and development of circRNA signatures for NSCLC.

A PD-1 /PD-L1 proximity assay as a theranostic marker for PD-1 blockade in patients with metastatic melanoma

PURPOSE

Less than 50% of patients with melanoma respond to anti-PD1, 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 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 PD1 and its main ligand, PDL1 appears a valuable target of anti-PD1 therapy. Thus, instead of looking at PD-L1 expression only, we evaluated the predictive value of the proximity between PD1 and its neighboring PD-L1 molecules in terms of response to anti-PD1 therapy.

EXPERIMENTAL DESIGN

PD1/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 melanoma patients treated with anti-PD1+/-anti CTLA4. Additional predictive biomarkers such as PD-L1 expression (MELscore), CD8+ cells density and nanostring RNA signature were also evaluated.

RESULTS

A PD1/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 PD1/PD-L1 PLA as compared to other parameters (AUC from 0.71 to 0.77). Progression free and overall survival were significantly longer in patients with high PLA values (p=0.00019 and p<0.0001 respectively).

CONCLUSION

The proximity between PD-1 and PD-L1, easily assessed by this PLA on one FFPE section, appears as a new biomarker of anti-PD1 efficacy.

Alpha-smooth Muscle Actin Expression in the Stroma Predicts Resistance to Trastuzumab in Patients with Early-stage HER2-positive Breast Cancer

PURPOSE

The companion diagnostic test for trastuzumab has not changed much in the last 25 years. We used high-plex digital spatial profiling to identify biomarkers besides HER2 that can help predict response to trastuzumab in HER2-positive breast cancer.

EXPERIMENTAL DESIGN

Fifty-eight protein targets were measured in three different molecularly defined compartments by the NanoString GeoMx Digital Spatial Profiler (DSP) in a tissue microarray containing 151 patients with breast cancer that received adjuvant trastuzumab as part of the Hellenic Cooperative Oncology Group 10/05 clinical trial. Promising candidate biomarkers were orthogonally validated with quantitative immunofluorescence (QIF). RNA-sequencing data from the Neoadjuvant Lapatinib and/or Trastuzumab Treatment Optimisation Study (NeoALTTO) were accessed to provide independent cohort validation. Disease-free survival (DFS) was the main outcome assessed. Statistical analyses were performed using a two-sided test (α = 0.05) and multiple testing correction (Benjamini-Hochberg method, FDR < 0.1).

RESULTS

By DSP, high expression of alpha-smooth muscle actin (α-SMA), both in the leukocyte and stromal compartments, was associated with shorter DFS in univariate analysis (P = 0.002 and P = 0.023, respectively). High α-SMA expression in the stroma was validated by QIF after controlling for estrogen receptor and progesterone receptor status [HR, 3.12; 95% confidence interval (CI), 1.12-8.68; P = 0.029] showing recurrence on trastuzumab in the same cohort. In the NeoALTTO cohort, elevated levels of ACTA2 were predictive for shorter DFS in the multivariate analysis (HR, 3.21; 95% CI, 1.14-9.05; P = 0.027).

CONCLUSIONS

This work identifies α-SMA as a novel, easy-to-implement biomarker of resistance to trastuzumab that may be valuable in settings where trastuzumab is combined with other therapies.

24 Nivolumab serum concentration in metastatic melanoma patients could be related to anti-tumor activity gene and outcome

Background

Nivolumab (nivo) is a monoclonal antibody that targets programmed death-1 (PD-1) molecule and has been approved for the treatment of several solid tumors; in the treatment of adjuvant and metastatic melanoma had better efficacy compared with chemotherapy or ipilimumab (anti-CTLA4).1–4 The classical dosage of nivo tested in the phase III trials was 3 mg/kg every 2 weeks (Q2W). However, in order to make easier the administration, it was introduced the flat dosage at 240mg every 2 weeks (Q2W) or 480mg every 4 weeks (Q4W).5 6 The purpose of this study was to investigate retrospectively the relationships between the different nivo dosages and their serum concentration; in addition, we also investigated possible relationship with the expression of pro/antitumor activity genes.

Methods

From July 2016 to December 2018 at INT IRCCS Pascale, Naples, we collected serum and RNA samples from 88 patients with metastatic melanoma at week 12 from the first administration of nivo. All patients have appropriately signed informed consent. The ORR among the 88 patients was 25% (patients baseline characteristics are listed in table 1). Commercial ELISA assay were performed in 96 well plates following the protocol procedures. Gene expression profiling was performed using NanoString® IO360 panels on 37 patients (CR: 4, PR: 10, SD: 11, PD: 12). Statistical analysis was performed through the Student’s t-test and via Spearman’s rho correlation coefficient. Gene profiling analysis was performed via Bonferroni correction.

Results

We observed that patients with complete response (CR) have a higher nivo concentration (p=0.003) compared to other groups. No correlation was observed with the most important markers of renal and hepatic function: eGFR, creatinine, AUC, albumin, ALT, AST and gamma GT. Data from gene expression profile shown that patients with CR had a higher expression of anti-tumor and immune activation genes such as: TAPBP, CD47, HDC, IL12RB2 and HLA-DQA1 (P <0.05). Furthermore, genes with pro-tumor or immunosuppressive activity such as MMP9, GOR160, HK2 and LILRA5 (P <0.05) were found to be inversely related with drug concentration while CD1C, a T-cell surface glycoprotein involved in antigen-presenting, it is directly related (p=0.005).

Abstract 24 Table 1

Patients clinical parameters

Conclusions

In this retrospective study we found that higher serum concentration of nivo was correlated with a better outcome and higher frequency of CR. Moreover, in patients with a CR there was an enhancing of the immune activation with an increase of HLA-DQA, TAPBP and IL12RB2. Further investigations are needed to get additional information.

Acknowledgements

The study was supported by the Institutional Project ‘Ricerca Corrente’ of Istituto Nazionale Tumori IRCCS Fondazione ‘G. Pascale’ of Napoli, Italy.

References

James Larkin, Vanna Chiarion-Sileni, Rene Gonzalezet al. Combined nivolumab and ipilimumab or monotherapy in untreated melanoma. N Engl J Med 2015 Jul 2;373(1):23–34.

Robert C, Long GV, Brady B et al. Nivolumab in previously untreated melanoma without BRAF mutation. N Engl J Med 2015 Jan 22;372(4):320–30.

Weber JS, D’Angelo SP, Minor D et al. Nivolumab versus chemotherapy in patients with advanced melanoma who progressed after anti-CTLA-4 treatment (CheckMate 037): a randomised, controlled, open-label, phase 3 trial. Lancet Oncol 2015 Apr;16(4):375–8.

Weber J, Mandala M, Del Vecchio M, Gogas HJ, Arance AM, Cowey CL, Dalle S,4. Schenker M, Chiarion-Sileni V, Marquez-Rodas I et al. CheckMate 238 Collaborators. Adjuvant nivolumab versus ipilimumab in resected stage III or IV melanoma. N Engl J Med 2017 Nov 9;377(19):1824–1835.

Zhao X, Suryawanshi S, Hruska M et al. Assessment of nivolumab benefit-risk profile of a 240-mg flat dose relative to a 3-mg/kg dosing regimen in patients with advanced tumors. Ann Oncol 2017 Aug 1;28(8):2002–2008.

Long GV, Tykodi SS, Schneider JG et al. Assessment of nivolumab exposure and clinical safety of 480?mg every 4 weeks flat-dosing schedule in patients with cancer. Ann Oncol 2018 Nov 1;29(11):2208–2213.

Ethics Approval

The study was approved by the internal ethics board of the Istituto Nazionale Tumori IRCCS Fondazione ‘G. Pascale’ of Napoli Italy, approval number of registry 33/17 OSS.

Consent

Written informed consent was obtained from the patient for publication of this abstract and any accompanying images. A copy of the written consent is available for review by the Editor of this journal.

946 Standardized transcriptional profiling for optimizing cellular therapies: a multi-center PICI-NanoString collaboration

Background

The field of cellular therapy remains one of the most promising areas for the development of new cancer treatments. To further these improvements, it is imperative to broadly understand cell therapy products at the molecular level and to identify factors that contribute to their efficacy. NanoString and the Parker Institute for Cancer Immunotherapy (PICI) have established a ground-breaking collaboration to characterize up to 1,000 apheresis and cellular therapy infusion products with the primary goal to dissect and study molecular pathways that correlate with optimal cellular therapies.

Methods

Using a large and diverse sample cohort collected from eight PICI network Cell Therapy Centers the team will aim to study gene expression profiles (GEP) that correlate with optimal apheresis and downstream cellular products, identifying biomarkers and signatures for clinical response or toxicity and further explore unique cancer-specific and shared characteristics that make an optimal and effective chimeric antigen receptor (CAR) T cell. As shown here, this first of its kind study will include samples that target dozens of different antigens covering both primary and metastatic hematological and solid tumors. Samples will be characterized using the standardized set of genes included in the nCounter CAR-T Characterization Panel and will measure essential components of CAR-T including: metabolic fitness, phenotype, TCR diversity, toxicity, activation, persistence, exhaustion and cell typing along with individual transgene expression.

Results

Presented here are initial questions that will be asked as part of this study. Meta-analysis will be performed as an aggregated set of data and individual site-specific analysis. Data will further be analyzed across individual cancer types, target types, outcome and manufacturing conditions as examples. We anticipate this information will prove useful across many aspects of the development, manufacturing and clinical applications for cellular therapies and further hypothesize that these findings will promote the understanding of pathways affecting safety and efficacy that may help optimize the therapy.

Conclusions

The project is anticipated to begin Fall of 2021 with work continuing in phases through 2022 with periodic data reports to be shared through scientific conferences. All data and findings will be made publicly available to the scientific community through PICI’s Cancer Data and Evidence Library analysis platform (CANDEL).

308 Transcriptomic analysis of melanoma patients in adjuvant setting treated with anti PD1 therapy: real life study

Background

Adjuvant treatment of melanoma patients with immune-checkpoint inhibition (ICI) significantly improved relapse-free survival (RFS).1 In the phase 3 keynote-054 trial showed that pembrolizumab (anti-PD1) administration in adjuvant setting provided a longer RFS (59,8%) than the placebo group (41,4%) at a 3.5-year median follow-up.2 Moreover, 4 years RFS results from the phase 3 checkmate 238 trial, showed a superior efficacy of nivolumab versus ipilimumab in patients with resected AJCC-7 stage III or IV melanoma. RFS rate was of 58% in the nivolumab arm and 45% in the ipilimumab arm.3 Although treatment with ICIs has improved the RFS of melanoma patients in adjuvant setting, there is still a large proportion of patients who do not respond to the treatment and then relapse. The aim of this study was to investigate the molecular mechanisms underlying resistance to anti-PD1 treatment in the adjuvant setting.

Methods

From December 2018 to July 2020, n. 121 melanoma patients in stage III or IV NED were treated with anti-PD1s as adjuvant (minimum follow up of 12 months, range 12–30 months). These patients received nivolumab (n=95) or pembrolizumab (n=26). Distant and local metastases was observed in 33 (27%) and 7 (6%) patients, respectively (patients baseline characteristics are listed in table1). Gene expression profiles, using NanoString IO 360 panel, were performed from peripheral blood mononuclear cell (PBMCs), collected retrospectively, from n.73 patients (of which n.26 had relapse). All patients have appropriately signed informed consent. Statistical analysis was performed via Bonferroni correction, P< 0.05 was considered statistically significant for median stratification.

Results

At a minimum follow-up of 12 months, the 12-month rate of Relapse-free survival was 72%, confirming the data reported by checkmate 238 trial. In the transcriptomic analysis we observed that in patients with local-regional metastases there was a higher expression of ITGA2 (p<0.05), a gene that promotes malignant tumor aggression by up-regulating PD-L1 expression through STAT3 pathway and the downregulation of DUSP1 (p<0.05) that is linked in promotion of angiogenesis, invasion and metastasis. Moreover, in male group we found a higher expression of HLA-DQB1 and HLA-DQA1 which belonged to HLA class II beta chains.

Abstract 308 Table 1

Conclusions

In this preliminary report we found that RFS 1-yr rate is similar to checkmate 238 study, and that patients with local metastasis have a higher expression of genes related to promote PDL1 levels. Further investigations are needed to get additional information.

Acknowledgements

The study was supported by the Institutional Project ”Ricerca Corrente” of Istituto Nazionale Tumori IRCCS Fondazione ”G. Pascale” of Napoli, Italy.

References

Weber J, Mandala M, Del Vecchio M, et al, CheckMate 238 Collaborators. Adjuvant nivolumab versus ipilimumab in resected stage III or IV melanoma. N Engl J Med 2017 November 9;377(19):1824–1835.

Eggermont AMM, Blank CU, Mandalà M, et al. EORTC melanoma group. Adjuvant pembrolizumab versus placebo in resected stage III melanoma (EORTC 1325-MG/KEYNOTE-054): distant metastasis-free survival results from a double-blind, randomised, controlled, phase 3 trial. Lancet Oncol 2021 May;22(5):643–654.

Ascierto PA, Del Vecchio M, Mandalá M, et al. Adjuvant nivolumab versus ipilimumab in resected stage IIIB-C and stage IV melanoma (CheckMate 238): 4-year results from a multicentre, double-blind, randomised, controlled, phase 3 trial. Lancet Oncol 2020 November;21(11):1465–1477.

Ethics Approval

The study was approved by internal ethics board of the Istituto Nazionale Tumori IRCCS Fondazione ”G. Pascale” of Napoli Italy, approval number of registry 33/17 OSS.

Consent

Written informed consent was obtained from the patient for publication of this abstract and any accompanying images. A copy of the written consent is available for review by the Editor of this journal.

934 Biological mechanisms in the different etiologies of Merkel cell carcinoma patients: polyomavirus or UV exposure

Background

Merkel cell carcinoma (MCC) is a rare and aggressive skin cancer with neuroendocrine features, and it is associated with elevated mortality. The pathogenesis is associated with presence of clonally integrated Merkel cell polyomavirus (MCPyV) or ultraviolet light (UV) exposure.1 The MCPyV causes up to 80% of MCC tumors in North America and Europe.2–4 Recently immunotherapy is having good results,5 the phase 2 trial JAVELIN Merkel 200 indicated that treatment with Avelumab (PDL1 inhibitor) in patients with metastatic MCC pre-treated have a meaningful long-term survival outcomes respect chemotherapy. Moreover, ORRs were highest in patients with high TMB that were also MCPyV−, PD-L1+ or had a greater CD8+ T cell density at the invasive margin.6 In this study, we investigated the biological signatures in patients with MCPyV or not.

Methods

From April 2011 to June 2018, we collected retrospectively 50 FFPE (Formalin-Fixed Paraffin-Embed) from 37 patients with metastatic MCC and 13 tissues from a secondary metastatic site. All patients have appropriately signed informed consent. We performed an immunohistochemistry assays (IHC) for MCPyV and PDL1. In addition, through the NanoString GeoMx DSP (Digital Spatial Profiling), we analysed 11 patients (6 MCPyV+; 5 MCPyV-) with cutaneous metastasis using a 44-plex antibody cocktail. For each slide we selected three different areas: Intratumoral, extratumoral and tumour border, in each area we selected CD4+ and CD8+ cells in 4 different ROIs (Region of Interest). Statistical analysis was performed via Bonferroni correction, P< 0.05 was considered statistically significant for median stratification.

Results

The DSP analysis showed that the tumour border cells have an overexpression of IDO respect intratumoral area (adj. p<0.01). Instead, extratumoral area of MCPyV- patients have a higher expression of B7-H3 respect MCPyV+ as well as FOXP3 is higher in the tumour border of MCPyV+ patients and EpCAM in the intratumoral area (p<0.05). PDL1 is overexpressed in MCPyV+ CD4+ cells respect CD8+ (p<0.05). The IHC assay shown that viral status does not change in multiple metastases and PDL1 is elevated in the tumour border (p<0.05).

Conclusions

In this retrospective study, our preliminary data shown that tumour edge have an important role in the modulations of immune infiltrate and patients with Merkel cell polyomavirus could have a different pathway of immunosuppression compared to patients with non-virus related etiology. Further investigations are needed to get additional information.

Acknowledgements

The study was supported by the Institutional Project ”Ricerca Corrente” of Istituto Nazionale Tumori IRCCS Fondazione ”G. Pascale” of Napoli, Italy.

References

Kaae J, Hansen AV, Biggar RJ, et al. Merkel cell carcinoma: incidence, mortality, and risk of other cancers. J Natl Cancer Inst 2010 June 2;102(11):793–801.

Feng H, Shuda M, Chang Y, et al. Clonal integration of a polyomavirus in human Merkel cell carcinoma. Science 2008 February 22;319(5866):1096–100.

Garneski KM, Warcola AH, Feng Q, et al. Merkel cell polyomavirus is more frequently present in North American than Australian Merkel cell carcinoma tumors. J Invest Dermatol 2009 January;129(1):246–8.

Goh G, Walradt T, Markarov V, et al. Mutational landscape of MCPyV-positive and MCPyV-negative Merkel cell carcinomas with implications for immunotherapy. Oncotarget 2016 January 19;7(3):3403–15.

Bichakjian CK, Olencki T, Aasi SZ, et al. Merkel cell carcinoma, version 1.2018, NCCN Clinical Practice Guidelines in Oncology. J Natl Compr Canc Netw 2018 June;16(6):742–774.

D’Angelo SP, Bhatia S, Brohl AS, et al. Avelumab in patients with previously treated metastatic Merkel cell carcinoma: long-term data and biomarker analyses from the single-arm phase 2 JAVELIN Merkel 200 trial. J Immunother Cancer 2020 May;8(1):e000674.

Ethics Approval

The study was approved by internal ethics board of the Istituto Nazionale Tumori IRCCS Fondazione ”G. Pascale” of Napoli Italy, approval number of registry 33/17 OSS.

Consent

Written informed consent was obtained from the patient for publication of this abstract and any accompanying images. A copy of the written consent is available for review by the Editor of this journal.

Abstract 466: Differential expression of circRNAs allows discrimination of NSCLC from cancer-free lung specimens using the nCounter platform

Introduction: Lung cancer mortality ranks as the highest of the cancer-related deaths. Studies on tumor profiling at the genomic, transcriptomic and proteomic level has soared in the last decade improving overall survival of these patients by shaping the current targeted therapies; however, further investigation of novel biomarkers for an early diagnosis still remains imperative.circRNAs are a class of tissue-specific stable structures that control mammalian transcription. Their aberrant expression plays an important role in carcinogenesis and tumor progression which profiles them as valuable biomarkers; Conversely, its potential has not been fully explored in lung cancer due to several limitations of current circRNA quantification methods that prevent their clinical implementation.The nCounter technology allows for quantitative and qualitative assessment of up to 800 targets providing an accurate and factual perspective of expression levels. To our knowledge, thru this study we stand as the first on assessing circRNA differential expression with this platform for lung cancer detection both in FFPE specimens and cell lines providing preliminary evidence of their differential expression in lung cancer.

Methods: Cells were cultured under standard conditions until harvested. RNA was isolated by using Allprep DNA/RNA/miRNA universal kit (Qiagen). FFPE lung tissue samples (n=28; 18 NSCLC,10 non-cancer) were retrospectively collected and micro-dissected. RNA was isolated with High Pure FFPET RNA isolation kit (Roche) and quantified by Qubit (Thermo Fisher).Overnight hybridization and posterior nCounter FLEX processing were performed following NanoString protocol for nCounter Elements. Expression analysis was carried out based on a tailored panel of 85 circRNAs related to the biology of the disease.

Results: FFPE lung tissues revealed a cluster of differentially expressed circRNAs that allow distinction of lung cancer versus control. circFOXP1, circEPB41L2 and circBNC2 ranked as the most downregulated circRNAs, whereas circCHD9, circAASDH, circRUNX1 and circCHST15 led the catalog of most upregulated in cancer specimens. circRNA expression of A549, H2228, H3122, PC9, H1666, and HOP-62 cells was compared to the CCL-171 fibroblast cell line. circEPB41L2 and circFOXP1 were also confirmed distinctly downregulated in cancer cell lines.

Conclusion: This study presents for the first time the use of the differential expression of circRNAs in FFPE tissues for lung cancer discrimination using the nCounter platform. While more samples are currently being collected to increase the statistical power of the study, these results pave the way for the developing of future circRNA-based nCounter tests for lung cancer diagnosis. Further experiments using epithelial cells as control will be carried out and results will be pertinently updated at the time of the meeting.

Citation Format: Carlos Pedraz-Valdunciel, Miguel Ángel Molina-Vila, Stavros Giannoukakos, Nicolas Potie, Ruth Roman-Llado, Jill Bracht, Martyna Filipska, Masaoki Ito, Ana Gimenez-Capitán, Cristina Aguado-Esteban, Sarah Warren, Chung-Ying Huang, Trever Bivona, Rafael Rosell. Differential expression of circRNAs allows discrimination of NSCLC from cancer-free lung specimens using the nCounter platform [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 466.

Abstract 339: Resistance to trastuzumab is associated with alpha-smooth muscle actin expression in the stroma of patients with HER2+ breast cancer

Background: Approximately 15-20% of women diagnosed with breast cancer have HER2+ disease. Trastuzumab is currently FDA approved for the treatment of HER+ breast cancer, based on assessment of HER2 status by the combination of IHC and FISH assays. We hypothesized that there are biomarkers besides HER2 that can help predict response, or resistance, to trastuzumab in HER2+ breast cancer.

Methods: We used the NanoString® GeoMx® Digital Spatial Profiler (DSP) to measure 58 protein targets in three different enriched compartments (tumor [PanCK+], leukocyte [CD45+/CD68-] and macrophage [CD68+]) in a cohort of 151 breast cancer patients that received trastuzumab in the adjuvant setting, represented in a tissue microarray. To assess stromal protein expression, leukocyte and macrophage compartments were analyzed in aggregate. Spatially-resolved proteins were correlated with disease-free survival (DFS). Then, we used multiplexed quantitative immunofluorescence (QIF), performed on the AQUA platform, to validate our findings. Statistical analyses were performed using a two-sided test (α=0.05) and multiple testing correction (Benjamini-Hochberg method, FDR&lt;0.10).

Results: We assessed 58 individual protein targets in four compartments resulting in 282 candidate biomarkers per patient. After adjusting for multiple testing, high expression of alpha-smooth muscle actin (a-SMA) and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), both measured in the leukocyte compartment, were associated with shorter DFS in univariate analysis (p=0.045 and p=0.084, respectively); high expression of a-SMA in the stroma was also associated with worse outcome (HR, 4.94; 95% CI, 1.07-22.86; unadjusted p=0.023). Digital counts of a-SMA were inversely correlated with immune cell infiltration in the stroma. Using QIF, and after adjusting for four clinical prognostic factors (stage, grade, ER status and PR status), we validated that high a-SMA expression in the stroma was predictive for shorter DFS (HR, 3.34; 95% CI, 1.18-9.48, p=0.023) in the same cohort.

Conclusions: This work supports the role of cancer-associated fibroblasts in the tumor microenvironment in orchestrating the immune response and mediating resistance to trastuzumab for patients with HER2+ breast cancer. In light of the many new HER2 targeted therapies, this observation identifies a-SMA as a potential biomarker to augment the predictive value of the current standard of care HER2 assay and justifies further validation.

Citation Format: Ioannis A. Vathiotis, Myrto K. Moutafi, Prajan Divakar, Thazin Nwe Aung, Aileen Fernandez, Vesal Yaghoobi, Saba Shafi, Konstantinos N. Syrigos, George Fountzilas, Lajos Pusztai, Sarah Warren, David L. Rimm. Resistance to trastuzumab is associated with alpha-smooth muscle actin expression in the stroma of patients with HER2+ breast cancer [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 339.

Abstract 1623: Response and skin toxicity related protein signature in late stage melanoma patients after anti-PD-1 treatment

Skin toxicity after anti-PD1 treatment in melanoma patients is the most common type of immune related adverse effect (irAE) and has been associated with improved overall response rate and survival. Nonetheless, not many mechanistic biomarkers have been identified so far, that could be associated with low-grade skin toxicity and good response rates. In this study we have addressed this question by analyzing tumor tissue samples from late-stage melanoma patients with first-line anti-PD1 treatment. Samples obtained prior to treatment were submitted for an unbiased deep proteomic analysis using mass spectrometry (LC-MS) and a targeted transcriptomic analysis. Using the unbiased analysis as a discovery platform we were able to define a potential biomarker panel associated not only with improved response but also low-grade skin toxicity. Unbiased quantification of proteins in tumor tissues was done using data-independent acquisition (DIA) LC-MS technology. Proteins from tissue samples were denatured, digested, and analyzed on a mass spectrometer. A deep spectral library was generated, and proteins were quantified using Spectronaut software (Biognosys). In addition, from the same tumor tissue RNA was extracted and subjected to transcriptomic analysis with NanoString nCounter using the PanCancer IO 360 panel. Subsequent data analysis was done using a sPLS-DA using combined factor of skin toxicity and response. Unbiased analysis of 22 baseline tumor tissue samples from late-stage melanoma patients treated in first line with anti-PD1 resulted in identification and quantification of more than 8000 proteins. Progression free survival analysis showed difference between patients with reported low-grade skin toxicity against all others. Therefore, for sPLS-DA both factors, presence/absence of skin toxicity and response status, were used (non-responders with low-grade skin toxicity were not present in this cohort). Complete separation of subjects was achieved with a panel of 21 proteins. This panel was used for hierarchical clustering and was able to fully restore all three groups of patients. Among all proteins identified in the proteomic panel, melanoma-associated antigen C1 (MAGEC1) has been also assessed in the targeted transcriptomic analysis and represents strikingly similar results. MAGEC1 is also found as a strong predictor in the Human Protein Atlas project. Interestingly, MAGE protein family are tumor-specific antigens that can be recognized by autologous cytolytic T lymphocytes and could serve as a novel ICI target or predictive biomarker. In this study we confirm prior observations of a survival benefit related to irAEs after treatment with PD-1 blockade in late-stage melanoma patients. We also demonstrate the power of deep proteomic profiling and transcriptomic analysis in molecular biomarker selection associated to response and irAEs which further benefit patient survival.

Citation Format: Jakob Vowinckel, Domenico Mallardo, Kamil Sklodowski, Martin Soste, Mariaelena Capone, Gabriele Madonna, Vito Vanella, Sarah Warren, Kristina Beeler, Paolo A. Ascierto. Response and skin toxicity related protein signature in late stage melanoma patients after anti-PD-1 treatment [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 1623.

Abstract 2606: A nCounter-Based mRNA signature in plasma associates with localized non-small cell lung cancer

Background: 80% of non-small cell lung cancer (NSCLC) cases are diagnosed at stages IIIB-IV and have a dismal prognosis with a median life expectancy that does not exceed 2 years. In contrast, patients diagnosed at early and locally advanced stages (I-IIIA) can undergo surgery and have the potential to be totally cured. Imaging technologies often detect lung nodules of unknown significance that pose a diagnostic challenge; some patients with benign nodules are submitted to unnecessary surgical interventions while others with small tumors are just kept in observation, risking a significant delay for treatment. A diagnostic test that could differentiate between benign and malignant masses would be of great help in this setting.

Methods: Circulating-free RNA (cfRNA) was isolated from the plasma of healthy individuals (N=21), early(I-II) stage (N=22) and stage IIIA (N=12) NSCLC patients, using an automatic extraction method(Qiasymphony, Qiagen). Purified cfRNA was quantified using Qubit, retrotranscribed and pre-amplified (14cycles) using the Low RNA Input Amplification kit (NanoString Technologies). Gene expression analysis was performed on the nCounter platform using the PanCancer IO360TM (NanoString Technologies), which can detect 770 transcripts related to tumor biology, micro-environment and the immune system.

Results: Gene expression analysis revealed differential patterns for some cf-mRNAs from localized stage NSCLC patients versus healthy controls. A bioinformatics recursive feature elimination algorithm selected a 16-gene mRNA signature that was able to distinguish between localized NSCLC and control samples with an area under the ROC curve of 0.91 to 0.95. Furthermore, the signature scores derived from the algorithm were significantly different between the two cohorts.

Conclusions: We have found an 16-gene signature that can differentiate between cfRNA of localized stages NSCLC patients and control individuals. Our results warrant validation studies in larger cohorts.

Citation Format: Ana Giménez Capitán, Jillian Bracht, Nicolas Potie, María González-Cao, Santiago Viteri, Alejandro Martínez-Bueno, Carlos Cabrera-Gálvez, Pablo Rubinstein, Clara Mayo-de-las-Casas, Joselyn Valarezo, Chung-Ying Huang, Carlos Pedraz, Richard Boykind, Sarah Warren, Rafael Rosell, Miguel Ángel Molina-Vilaa, Andrés Aguilar-Hernández. A nCounter-Based mRNA signature in plasma associates with localized non-small cell lung cancer [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 2606.

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.

Abstract 409: A pre-treatment plasma extracellular vesicle-mRNA signature associates with checkpoint inhibitor pneumonitis in lung cancer patients

Introduction: Immune checkpoint inhibitors (ICIs) have demonstrated clinical efficacy in non-small cell lung cancer (NSCLC) patients (p). However, ICIs can also trigger a self-reactive response in the adjacent healthy lung tissue that can eventually lead to life-threatening immune-related adverse events (irAEs), like checkpoint inhibitor pneumonitis (CIP). We hypothesized that a pre-treatment state of chronic inflammation or immune system imbalance could predict which p are at higher risk of developing CIP.

Methodology: We retrospectively collected pre-ICI-treatment FFPE tumor tissue and matching plasma samples from 17 CIP- and 24 non-CIP lung cancer p. An additional 40 plasma samples, including 3 CIP and 37 non-CIP p were used as a validation cohort. The miRCURY exosome isolation kit (Qiagen) was used for extracellular vesicle (EV) enrichment from 500 μL of plasma and RNA was extracted using TRI-reagent. EV-mRNA was then pre-amplified (10 cycles) using the Low RNA Input Amplification kit (NanoString Technologies). FFPE mRNA was extracted using the High Pure FFPET RNA Isolation Kit (Roche). Gene expression analysis was performed on tissue and EV-derived mRNA using the NanoString nCounter platform with the Human PanCancer IO360 panel, which targets 770 genes related to tumor biology, immune response and microenvironment. Differential expression (DE) analysis was carried out based on the development of CIP. Finally, a classifier was created using a bioinformatic recursive feature elimination and a leave-one-out cross validation algorithm to predict which combination of genes is most effective to predict CIP development.

Results: DE analysis revealed 54 differentially expressed genes (DEGs) in pre-treatment tissue of CIP vs. non-CIP p. An 8-gene CIP mRNA signature was able to distinguish between the two cohorts with areas under the ROC curve (AUC) of 0.81-0.95. When analyzing plasma EV samples, we found 57 DEGs. The tissue CIP signature was not translatable to EVs, yielding AUCs of only 0.53-0.54. Therefore, we developed a new 4-gene EV-based mRNA signature that could differentiate CIP vs. non-CIP developing p with AUCs of 0.82-0.90 and an overall accuracy of 89.9%. The negative- and positive predictive values (NPV and PPV) were 92.7% and 78.6%, respectively with a Youden´s index of 0.67. The 4 genes included in the EV signature were upregulated in CIP p and were found to be involved in T-cell activation and immune cell localization to the tumor.

Conclusions: We have created a 4-gene EV-mRNA signature that associates with CIP development upon ICI treatment. Our results also indicate that plasma EV-mRNA was non-inferior to invasive tissue biopsy analysis in predicting CIP development. Validation studies in larger patient cohorts are ongoing.

Citation Format: Jillian Wilhelmina Bracht, Santiago Viteri-Ramirez, Andrés Aguilar, Silvia Calabuig-Fariñas, Juan José García-Mosquera, Chung-Ying Huang, Elena Duréndez-Sáez, Nicolas Potie, Erika Aldeguer, Ana Gimenez-Capitán, Sonia Rodriguez, Ruth Roman, Cristina Aguado, Sarah Warren, Carlos Camps, Rafael Rosell, Eloisa Jantus-Lewintre, Miguel-Angel Molina-Vila, Maria González-Cao. A pre-treatment plasma extracellular vesicle-mRNA signature associates with checkpoint inhibitor pneumonitis in lung cancer patients [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 409.

Proteomics meets transcriptomics: Identification of tumor tissue signatures specific to anti-PD1 treatment in late-stage melanoma patients

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Background: Despite advances of anti-PD1 treatment in melanoma, still large subset of patients does not respond or relapses due to primary or acquired resistance. One potential way to overcome the mechanisms of resistance is to identify molecular signatures associated with response to treatment. Here, we are presenting the results of an integrated deep transcriptomic and proteomic analysis of melanoma tissue samples coming from patients prior the treatment with anti-PD1. The combination of targeted transcriptomic approach with unbiased proteomic approach allowed for identification of a molecular response signature specific to anti-PD1 therapy. Methods: Unbiased quantification of proteins in tumor tissues was done using data-independent acquisition (DIA) LC-MS technology. Proteins from tissue samples were denatured, digested, and analyzed on a mass spectrometer. A deep spectral library was generated, and proteins were quantified using Spectronaut software (Biognosys). From the same tumor tissue RNA was extracted and subjected to transcriptomic analysis with NanoString nCounter using the PanCancer IO 360 panel. Integration analysis using latent components, a generalized PLS and sparse sGCCA method implemented in R mixOmics package was used for signature discovery. Results: Studied cohort was balanced for gender, BRAF mutations and stage. Treatment included Nivolumab or Pembrolizumab. Only among responding subjects, low grade (≤ 2) skin toxicity was identified at a significant level (p-value < 0.05). In total, 22 samples were measured (nine non-responders and 13 responders). Overall, the analysis of proteome across all samples resulted in 8548 proteins being identified and quantified. The IO 360 panel contained 770 targets. In combined analysis, 10 mRNA targets together with 64 protein targets were highly associated with response to treatment. Two top candidates identified for mRNA and proteins were SIGLEC5 and ACP6 respectively. The panel of 74 features was sufficient to separate all subjects using unsupervised hierarchical clustering into to two main clusters enriched for responders and non-responders (p-value < 0.05). String-DB analysis revealed numerous interactions and associations within identified panel. Functional analysis using GO enrichment showed major involvement of the selected mRNA and proteins in T-cell regulation as well as in neutrophil degranulation and antigen receptor mediated signaling. Conclusions: Combination of both omics assays provides a very comprehensive image of tumor tissue responses to anti-PD1 treatment in late-stage melanoma patients. Identified candidates show striking changes in responder and non-responder groups and should undergo further validation for use in precision medicine.

The spatial landscape of lung pathology during COVID-19 progression

Recent studies have provided insights into the pathology of and immune response to COVID-191-8. However, a thorough investigation of the interplay between infected cells and the immune system at sites of infection has been lacking. Here we use high-parameter imaging mass cytometry9 that targets the expression of 36 proteins to investigate the cellular composition and spatial architecture of acute lung injury in humans (including injuries derived from SARS-CoV-2 infection) at single-cell resolution. These spatially resolved single-cell data unravel the disordered structure of the infected and injured lung, alongside the distribution of extensive immune infiltration. Neutrophil and macrophage infiltration are hallmarks of bacterial pneumonia and COVID-19, respectively. We provide evidence that SARS-CoV-2 infects predominantly alveolar epithelial cells and induces a localized hyperinflammatory cell state that is associated with lung damage. We leverage the temporal range of fatal outcomes of COVID-19 in relation to the onset of symptoms, which reveals increased macrophage extravasation and increased numbers of mesenchymal cells and fibroblasts concomitant with increased proximity between these cell types as the disease progresses-possibly as a result of attempts to repair the damaged lung tissue. Our data enable us to develop a biologically interpretable landscape of lung pathology from a structural, immunological and clinical standpoint. We use this landscape to characterize the pathophysiology of the human lung from its macroscopic presentation to the single-cell level, which provides an important basis for understanding COVID-19 and lung pathology in general.

Systemic Tissue and Cellular Disruption from SARS-CoV-2 Infection revealed in COVID-19 Autopsies and Spatial Omics Tissue Maps

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) virus has infected over 115 million people and caused over 2.5 million deaths worldwide. Yet, the molecular mechanisms underlying the clinical manifestations of COVID-19, as well as what distinguishes them from common seasonal influenza virus and other lung injury states such as Acute Respiratory Distress Syndrome (ARDS), remains poorly understood. To address these challenges, we combined transcriptional profiling of 646 clinical nasopharyngeal swabs and 39 patient autopsy tissues, matched with spatial protein and expression profiling (GeoMx) across 357 tissue sections. These results define both body-wide and tissue-specific (heart, liver, lung, kidney, and lymph nodes) damage wrought by the SARS-CoV-2 infection, evident as a function of varying viral load (high vs. low) during the course of infection and specific, transcriptional dysregulation in splicing isoforms, T cell receptor expression, and cellular expression states. In particular, cardiac and lung tissues revealed the largest degree of splicing isoform switching and cell expression state loss. Overall, these findings reveal a systemic disruption of cellular and transcriptional pathways from COVID-19 across all tissues, which can inform subsequent studies to combat the mortality of COVID-19, as well to better understand the molecular dynamics of lethal SARS-CoV-2 infection and other viruses.

Multiplex Detection of Clinically Relevant Mutations in Liquid Biopsies of Cancer Patients Using a Hybridization-Based Platform

BACKGROUND

With the advent of precision oncology, liquid biopsies are quickly gaining acceptance in the clinical setting. However, in some cases, the amount of DNA isolated is insufficient for Next-Generation Sequencing (NGS) analysis. The nCounter platform could be an alternative, but it has never been explored for detection of clinically relevant alterations in fluids.

METHODS

Circulating-free DNA (cfDNA) was purified from blood, cerebrospinal fluid, and ascites of patients with cancer and analyzed with the nCounter 3 D Single Nucleotide Variant (SNV) Solid Tumor Panel, which allows for detection of 97 driver mutations in 24 genes.

RESULTS

Validation experiments revealed that the nCounter SNV panel could detect mutations at allelic fractions of 0.02-2% in samples with ≥5 pg mutant DNA/µL. In a retrospective analysis of 70 cfDNAs from patients with cancer, the panel successfully detected EGFR, KRAS, BRAF, PIK3CA, and NRAS mutations when compared with previous genotyping in the same liquid biopsies and paired tumor tissues [Cohen kappa of 0.96 (CI = 0.92-1.00) and 0.90 (CI = 0.74-1.00), respectively]. In a prospective study including 91 liquid biopsies from patients with different malignancies, 90 yielded valid results with the SNV panel and mutations in EGFR, KRAS, BRAF, PIK3CA, TP53, NFE2L2, CTNNB1, ALK, FBXW7, and PTEN were found. Finally, serial liquid biopsies from a patient with NSCLC revealed that the semiquantitative results of the mutation analysis by the SNV panel correlated with the evolution of the disease.

CONCLUSIONS

The nCounter platform requires less DNA than NGS and can be employed for routine mutation testing in liquid biopsies of patients with cancer.

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.

The effect of confounding data features on a deep learning algorithm to predict complete coronary occlusion in a retrospective observational setting

Aims

Deep learning (DL) has emerged in recent years as an effective technique in automated ECG analysis.

Methods and results

A retrospective, observational study was designed to assess the feasibility of detecting induced coronary artery occlusion in human subjects earlier than experienced cardiologists using a DL algorithm. A deep convolutional neural network was trained using data from the STAFF III database. The task was to classify ECG samples as showing acute coronary artery occlusion, or no occlusion. Occluded samples were recorded after 60 s of balloon occlusion of a single coronary artery. For the first iteration of the experiment, non-occluded samples were taken from ECGs recorded in a restroom prior to entering theatres. For the second iteration of the experiment, non-occluded samples were taken in the theatre prior to balloon inflation. Results were obtained using a cross-validation approach. In the first iteration of the experiment, the DL model achieved an F1 score of 0.814, which was higher than any of three reviewing cardiologists or STEMI criteria. In the second iteration of the experiment, the DL model achieved an F1 score of 0.533, which is akin to the performance of a random chance classifier.

Conclusion

The dataset was too small for the second model to achieve meaningful performance, despite the use of transfer learning. However, 'data leakage' during the first iteration of the experiment led to falsely high results. This study highlights the risk of DL models leveraging data leaks to produce spurious results.

High-Throughput Simultaneous mRNA Profiling Using nCounter Technology Demonstrates That Extracellular Vesicles Contain Different mRNA Transcripts Than Their Parental Prostate Cancer Cells

Extracellular vesicles (EVs) are nano-sized lipid bilayer encapsulated particles with a molecular cargo that appears to play important roles within the human body, such as in cell-to-cell communication. Unraveling the composition of EV cargos remains one of the most fundamental steps toward understanding the role of EVs in intercellular communication and the discovery of new biomarkers. One of the unmet needs in this field is the lack of a robust, sensitive, and multiplexed method for EV mRNA profiling. We established a new protocol using the NanoString low RNA input nCounter assay by which the targeted mRNA transcripts in EVs can be efficiently and specifically amplified and then assayed for 770 mRNAs in one reaction. Prostate cancer cells with epithelial (PC3-Epi) or mesenchymal (PC3-EMT) phenotypes and their progeny EVs were analyzed by the same panel. Among these mRNAs, 157 were detected in PC3-Epi EVs and 564 were detected in PC3-EMT EVs. NOTCH1 was the most significantly abundant mRNA transcripts in PC3-EMT EVs compared to PC3-Epi EVs. Our results demonstrated that when cells undergo epithelial-to-mesenchymal transition (EMT), a more active loading of cancer progression-related mRNA transcripts may occur. The mRNA cargos of EVs derived from mesenchymal prostate cancer cells may contribute to the pro-EMT function. We found that mRNA transcripts are different in progeny EVs compared to parental cells. EV cargos are not completely reflective of their cell origin, and the underlying mechanism of cargo sorting is complicated and needs to be further elucidated.

Impact of checkpoint blockade on cancer vaccine-activated CD8+ T cell responses

Immune and molecular profiling of CD8 T cells of patients receiving DC vaccines expressing three full-length melanoma antigens (MAs) was performed. Antigen expression levels in DCs had no significant impact on T cell or clinical responses. Patients who received checkpoint blockade before 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. Gene and protein expression analyses in lymphocytes and tumor samples identified critical immunoregulatory pathways, including CTLA-4 and PD-1. High immune checkpoint gene expression networks correlated with inferior clinical outcomes. Soluble serum PD-L2 showed suggestive positive association with improved outcome. These findings show that checkpoint molecular pathways are critical for vaccine outcomes and suggest specific sequencing of vaccine combinations.