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The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is known to present with pulmonary and extra-pulmonary organ complications. In comparison with the 2009 pandemic (pH1N1), SARS-CoV-2 infection is likely to lead to more severe disease, with multi-organ effects, including cardiovascular disease. SARS-CoV-2 has been associated with acute and long-term cardiovascular disease, but the molecular changes govern this remain unknown.In this study, we investigated the landscape of cardiac tissues collected at rapid autopsy from SARS-CoV-2, pH1N1, and control patients using targeted spatial transcriptomics approaches. Although SARS-CoV-2 was not detected in cardiac tissue, host transcriptomics showed upregulation of genes associated with DNA damage and repair, heat shock, and M1-like macrophage infiltration in the cardiac tissues of COVID-19 patients. The DNA damage present in the SARS-CoV-2 patient samples, were further confirmed by γ−H2Ax immunohistochemistry. In comparison, pH1N1 showed upregulation of Interferon-stimulated genes (ISGs), in particular interferon and complement pathways, when compared with COVID-19 patients.These data demonstrate the emergence of distinct transcriptomic profiles in cardiac tissues of SARS-CoV-2 and pH1N1 influenza infection supporting the need for a greater understanding of the effects on extra-pulmonary organs, including the cardiovascular system of COVID-19 patients, to delineate the immunopathobiology of SARS-CoV-2 infection, and long term impact on health.

In recent years, pregnant people infected with the SARS-CoV-2 virus have shown a higher incidence of “preeclampsia-like syndrome”. Preeclampsia is a systematic syndrome that affects 5-8 % of pregnant people worldwide and is the leading cause of maternal mortality and morbidity. It is unclear what causes preeclampsia, and is characterised by placental dysfunction, leading to poor placental perfusion, maternal hypertension, proteinuria, thrombocytopenia, or neurological disturbances.In this study, we used whole-transcriptome, digital spatial profiling of placental tissues to analyse the expression of genes at the cellular level between placentae from pregnant participants who contracted SARS-CoV-2 in the third trimester of their pregnancy and those prior to the start of the pandemic. Our focused analysis of the trophoblast and villous core stromal cell populations revealed tissue-specific pathways enriched in the SARS-CoV-2 placentae that align with a pre-eclampsia signature. Most notably, we found enrichment of pathways involved in vascular tension, blood pressure, inflammation, and oxidative stress.This study illustrates how spatially resolved transcriptomic analysis of placental tissue can aid in understanding the underlying pathogenic mechanisms of SARS-CoV-2 in pregnancy that are thought to induce “preeclampsia-like syndrome”. Moreover, our study highlights the benefits of using digital spatial profiling to map the crosstalk between trophoblast and villous core stromal cells linked to pathways involved in “preeclampsia-like syndrome” presenting in pregnant people with SARS-CoV-2.

Objectives: Attaining tumour material from lung cancer patients can be challenging with limited sample availability. Therefore, non-invasive means of assessing tumour material is becoming increasingly more important. Circulating tumour DNA (ctDNA), extracted from a blood sample is appealing for the patient, and can be performed serially over the course of treatment. Materials and Methods: Here, we describe an approach for profiling the blood samples of 103 NSCLC patients for 73 variants in ctDNA across a panel of actionable lung cancer mutations using the UltraSEEK lung Panel (Agena Biosciences). Results: Our cross-sectional study showed tumour and blood concordance in the detection of KRAS mutations (G12C, G12D, G12A/V, G12R, G12RC, Q61H) in 17/27 (63%), EGFR mutations (e746_a750del, e747_A750, T790M, L861Q) in 16/20 (80%) with additional PIK3CA_p545K mutations across both cohorts. In patients without reported tumour mutations, 11/56 (19.6%) presented with plasma mutations across EGFR, KRAS and PIK3CA. Where ctDNA mutations were measured longitudinally (n = 4 patients), the individual mutations mirrored the response to therapy/progression of disease. Conclusion: Whilst preliminary, this study demonstrates the utility of detecting clinically actionable mutations in the blood samples of NSCLC patients at the time of presentation, and over the course of therapy.

Immune checkpoint inhibitors (ICIs) Pembrolizumab and Nivolumab have shown promising results in patients with recurrent or metastatic (R/M) head and neck squamous cell carcinoma (HNSCC). Nonetheless, only up to 20% of patients may benefit from them. Next generation predictive biomarkers of response to ICI therapies are currently needed. This retrospective study profiled pre-treatment tissue samples collected from R/M HNSCC patients (n=30) treated with Pembrolizumab or Nivolumab. Targeted spatial proteomics profiling was performed using NanoString’s GeoMx® Digital Spatial Profiler (GeoMx). To develop an informed region-of-interest (ROI) selection strategy for the GeoMx, we analyzed H&E images from serial sections and performed Oncotopix® Discovery software, which considered pathology inputs and machine learning to analyze H&E imagery and 4-channel GeoMx visualization inputs. We profiled 80 proteins simultaneously using the GeoMx across modules in cell death, immune activation, immune cell typing, immuno-oncology drug target, immune profiling, PI3K/AKT signaling, and pan-tumor markers.. Next, we performed differential expression (DE) analysis of the proteins localized in the tumor and stromal compartments against response to therapy parameters of complete, partial, stable and progressive disease (according to RECIST criteria). Four-channel GeoMx immunofluorescence images provided per-ROI cell counts (total and phenotyped based on 3 markers), and these data were used to aid in area and cell count normalization within the tumor and stromal compartments. We found that patients responsive to immunotherapy had higher expression levels of PD-L1, Bcl-2, BCLX, and BIM in the tumor, whereas VISTA, FOXP3, and CD66b were downregulated. In the stromal compartment, it was found that responders had higher expression levels of B7-H3, CD40, and SMA, but lower expression of PARP, S100B, and NY-ESO-1 in comparison to non-responders. In terms of best response analysis, patients with PR (n=5) had higher levels of PD-L1, ER-alpha, and CD68 expression, but lower levels of VISTA, CD27, and CD95/Fas in tumor regions than patients with PD (n=8). In the stroma, PD-L1, CD68, and HLA-DR were upregulated, while VISTA, BIM, and BAD were downregulated in patients with PR versus those with PD. We found that informed ROI selection strategy aided in defining key features in the tumor microenvironment for comparative analysis across samples, and for data normalization methods. Moreover, we found that immune checkpoints and proteins involved in cell death signaling play important roles in the immune responsive tumor microenvironment of HNSCC based on response to immunotherapy. Citation Format: Habib Sadeghirad, Ning Liu, James Monkman, Chin Wee Tan, Caroline Cooper, Jeni Caldera, Sarah Church, Fabian Schneider, James Robert Mansfield, Ken O'Byrne, Melissa Davis, Brett Hughes, Arutha Kulasinghe. Spatial profiling of the tumor microenvironment in head and neck cancer identifies immune checkpoints and proteins involved in cell death signaling biomarkers of immunotherapy response. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4626.

Background Lung cancers are the leading cause of cancer-related deaths with a 5-year-survival of only ~20%. Whilst immunotherapies have led to durable and prolonged survival, only a subset of patients remain responsive. Additional biomarkers are thus needed to better predict if patients will respond or develop resistance against immune checkpoint inhibitor (ICI) therapies. Spatial phenotyping of the tumor microenvironment (TME) is now recognized as a proxy for ICI therapy outcomes. Our study employs an end-to-end spatial biology strategy to survey non-small-cell lung cancer (NSCLC) tissues for new biomarkers that could guide immunotherapy treatments. Methods We phenotyped pre-treatment biopsies from non-small-cell lung cancer (NSCLC) patients treated with single-agent Nivolumab. We first performed 57-plex whole-slide Single Cell Spatial Phenotyping on the PhenoCycler®-Fusion platform. Next, we developed the spatial analysis of a larger NSCLC cohort using customizable PhenoCode Signature Panels (PSP) for high-throughput immune profile (CD3/CD8/CD20/CD68/PanCK + CD4 add-in) and immuno-contexture (CD8/CD68/PD-L1/FoxP3/PanCK + PD-1 add-in) imaging. The PSP panel content combines the barcode-based antibody chemistry from the PhenoCycler platform with the signal amplification of Opal chemistry from the PhenoImager platform. PSP panels were profiled across n=27 NSCLC biopsies and provided a wider breadth of tissue profiling. Results Our whole-slide single-cell spatial phenotyping analyses revealed high phenotypic diversity in the TME of patients responsive and resistant to ICI therapy. However, higher-throughput analyses of the same tissues using targeted PSP panels revealed no significant differences in quantities of immune cell lineages, including T-cells and macrophages. On the contrary, we discovered multiple quantifiable and statistically significant spatial signatures that appear to be predictive of treatment benefit, which confirms the potential biomarker value of spatial associations in patient tissues. Conclusions This study amounts to a uniquely comprehensive Single Cell Spatial Phenotyping analysis of pre-treatment NSCLC biopsies from a single-agent Nivolumab study. Our data catalogue the diversity in the immune microenvironment of NSCLC but highlighted that immune cell quantification is insufficient to stratify patient cohorts. Single-cell spatial phenotyping, on the other hand, promises to reveal new biomarkers that may aid in better stratification of patients in pre-treatment evaluations. Citation Format: Ning Ma, Aditya Pratapa, James Monkman, Ken O’Byrne, Oliver Braubach, Arutha Kulasinghe. The potential predictive role of spatial phenotyping in non-small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6768.

Background: Immune checkpoint inhibitors (ICI) have proven to be game-changing treatments for mucosal head and neck squamous cell cancer (HNSCC). Emerging successes with anti-PD-1/PD-L1 therapy have led to durable responses and prolonged survival in both human papillomavirus-positive (HPV+) and negative (HPV-) patients. There is now a need for predictive biomarkers to guide patient selection for highly targeted ICI therapies as currently available diagnostic biomarkers have a limited value. The tumor microenvironment (TME) composition, contexture, and cellular architecture are now recognized as key to understanding immune responsive and resistant phenotypes. Here, we are using a spatial biology approach to explore the TME in metastatic/recurrent HNSCC tumors treated with Pembrolizumab/Nivolumab. Methods: In this study, we used single cell, multiomic spatial phenotyping utilizing the PhenoCycler-Fusion spatial biology platform to characterize the TME of HNSCC tumors from a cohort of n=40 patients. The discovery cohort consisted of patients who had complete vs. partial vs. stable vs. progressive responses to ICI therapy. We first analyzed tissues using an ultrahigh-plex antibody panel of >60 antibodies that label immune cell lineages, checkpoints, activation markers as well as tissue structure and the stroma. We then conducted whole-slide, single cell resolution RNA detection with complementary markers on serial sections from the same tissue blocks; the combination of these data allowed us to obtain multiomic spatial signatures that offered uniquely comprehensive insight into the TME of our tissue cohorts. Results: Our study identified highly resolved tissue immune contexture analysis and metabolic tissue signatures associated with resistance and sensitivity to immunotherapy. Most notably, multiomic profiling of HNSCC tumours provided deeper insights into ICI therapy resistance than the single omics based approaches alone. Conclusions: Our study demonstrates the power of unbiased, multiomic spatial phenotyping with whole-slide imaging to identify biomarkers associated with response to ICI therapy in HNSCC. Citation Format: HaYeun Ji, Niyati Jhaveri, Ning Ma, Bassem B. Cheikh, Aditya Pratapa, James Monkman, Ken O’Byrne, Brett Hughes, Arutha Kulasinghe, Oliver Braubach. Single cell, multiomic spatial phenotyping of immunotherapy responses in head and neck cancer. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5647.

Background: Cutaneous squamous cell carcinoma (cSCC) is the second most common skin cancer and represents a major global health burden. Approximately 50% of cSCC patients develop primary resistance and 20% will develop secondary resistance to immune checkpoint inhibitors (ICI). There are limited biomarkers that reflect the tumor dynamics predictive of response to ICI therapy, and therefore we need to explore new biomarkers that can better understand the cSCC tumor microenvironment (TME). Methods: Our retrospective study profiled pre-treatment cutaneous skin cancer tissues from patients with immunotherapy sensitive and resistant diseases. In this exploratory study, we designed a high-dimensional > 50-plex antibody panel identifying cell lineages, activation states, and immune checkpoints. In addition, we deployed a combination of antibodies for a novel multiplexed metabolic readout, to enhance our in situ profiling beyond well-known TME targets. Whole-slide spatial phenotyping was conducted on the PhenoCycler-Fusion spatial biology platform. Highplex image analysis was performed using Phenoplex (Visiopharm), including tissue segmentation and cellular phenotyping. Here, we used a deep learning approach to discriminate tumor regions and margins based on their morphology. Spatial analyses including phenotypic composition, cell-to-cell localization, and cellular neighborhoods were performed and compared to clinicopathological findings and responses to ICI therapy. Results: We have profiled the TME of cSCC via ultrahigh-plex, single-cell spatial analyses of whole tissues. Our data have revealed unique cell phenotype compositions and metabolic states within the TME of different patient cohorts. Areas of metabolic activity were visualized and compartmentalized to determine spatial distributions of inherent sensitivity and resistance to ICI therapy. Additionally, a comparison of the phenotypic expression patterns between immunotherapy sensitive and resistant cohorts in the tumor, stromal and margin regions showed relevant differences in the immune content. Taken together, this high-dimensional imaging approach of the cSCC TME has revealed new tissue insights. Conclusion: There is a need to understand the contexture of the cSCC immune microenvironment. Here we identify distinct cellular phenotypic compositions and metabolic states in tissues from immune-competent and immunocompromised cSCC. We thereby confirm biological differences in tissue composition and cellular interactions between these tissues and provide putative new biomarkers for cSCC patient stratification. Citation Format: Niyati Jhaveri, Dmytro Klymyshyn, Bassem B. Cheikh, James Monkman, Dan Winkowski, James Mansfield, Subham Basu, Michael Prater, Nadine Nelson, Gabrielle Belz, Oliver Braubach, Arutha Kulasinghe. The development of a spatial metabolic map of immunotherapy sensitive and resistant cutaneous skin carcinoma. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6774.

Advances in immunotherapy have led to durable and long‐term benefits in a subset of patients across a number of solid tumor types. Understanding of the subsets of patients that respond to immune checkpoint inhibitors at the cellular level, and in the context of their tumor microenvironment (TME) is becoming increasingly important. The TME is composed of a heterogeneous milieu of tumor and immune cells. The immune landscape of the TME can inhibit or promote tumor initiation and progression; thus, a deeper understanding of tumor immunity is necessary to develop immunotherapeutic strategies. Recent developments have focused on characterizing the TME immune contexture (type, density, and function) to discover mechanisms and biomarkers that may predict treatment outcomes. This has, in part, been powered by advancements in spatial characterization technologies. In this review article, we address the role of specific immune cells within the TME at various stages of tumor progression and how the immune contexture determinants affecting tumor growth are used therapeutically.

Introduction: Metastasis results in more than 90% of cancer-related deaths globally. The process is thought to be facilitated by metastatic precursor cells, commonly termed circulating tumor cells (CTCs). CTCs can exist as single cells or cell clusters and travel through the lymphovasculature to distant organs where they can form overt metastasis. Areas covered: Studies have highlighted that CTC clusters, which may be homotypic or heterotypic in composition, have a higher metastatic potential compared to single CTCs. The characterization of CTC clusters is becoming important as heterotypic clusters can provide a mechanism for immune evasion. This review summarizes the latest advances in CTC cluster-mediated metastasis and clinical significance. Expert opinion: Comprehensive characterization of CTC clusters is needed to understand the cell types and interactions within clusters, in order to identify ways in which to reduce CTC cluster-mediated metastasis. The role of CTC clusters in prognosticating disease progression needs to be determined by documenting CTC clusters from the time of diagnosis over the course of therapy.

BackgroundRobust biomarkers that predict disease outcomes amongst COVID-19 patients are necessary for both patient triage and resource prioritisation. Numerous candidate biomarkers have been proposed for COVID-19. However, at present, there is no consensus on the best diagnostic approach to predict outcomes in infected patients. Moreover, it is not clear whether such tools would apply to other potentially pandemic pathogens and therefore of use as stockpile for future pandemic preparedness.MethodsWe conducted a multi-cohort observational study to investigate the biology and the prognostic role of interferon alpha-inducible protein 27 (IFI27) in COVID-19 patients.FindingsWe show that IFI27 is expressed in the respiratory tract of COVID-19 patients and elevated IFI27 expression is associated with the presence of a high viral load. We further demonstrate that systemic host response, as measured by blood IFI27 expression, is associated with COVID-19 severity. For clinical outcome prediction (e.g. respiratory failure), IFI27 expression displays a high positive (0.83) and negative (0.95) predictive value, outperforming all other known predictors of COVID-19 severity. Furthermore, IFI27 is upregulated in the blood of infected patients in response to other respiratory viruses. For example, in the pandemic H1N1/09 swine influenza virus infection, IFI27-like genes were highly upregulated in the blood samples of severely infected patients.InterpretationThese data suggest that prognostic biomarkers targeting the family of IFI27 genes could potentially supplement conventional diagnostic tools in future virus pandemics, independent of whether such pandemics are caused by a coronavirus, an influenza virus or another as yet-to-be discovered respiratory virus.Research in contextEvidence before this studyWe searched the scientific literature using PubMed to identify studies that used the IFI27 biomarker to predict outcomes in COVID-19 patients. We used the search terms “IFI27”, “COVID-19, “gene expression” and “outcome prediction”. We did not identify any study that investigated the role of IFI27 biomarker in outcome prediction. Although ten studies were identified using the general terms of “gene expression” and “COVID-19”, IFI27 was only mentioned in passing as one of the identified genes. All these studies addressed the broader question of the host response to COVID-19; none focused solely on using IFI27 to improve the risk stratification of infected patients in a pandemic.Added value of this studyHere, we present the findings of a multi-cohort study of the IFI27 biomarker in COVID-19 patients. Our findings show that the host response, as reflected by blood IFI27 gene expression, accurately predicts COVID-19 disease progression (positive and negative predictive values; 0.83 and 0.95, respectively), outperforming age, comorbidity, C-reactive protein and all other known risk factors. The strong association of IFI27 with disease severity occurs not only in SARS-CoV-2 infection, but also in other respiratory viruses with pandemic potential, such as the influenza virus. These findings suggest that host response biomarkers, such as IFI27, could help identify high-risk COVID-19 patients - those who are more likely to develop infection complications - and therefore may help improve patient triage in a pandemic.Implications of all the available evidenceThis is the first systemic study of the clinical role of IFI27 in the current COVID-19 pandemic and its possible future application in other respiratory virus pandemics. The findings not only could help improve the current management of COVID-19 patients but may also improve future pandemic preparedness.

IntroductionImmunotherapies, such as immune checkpoint inhibitors (ICI) have shown durable benefit in a subset of non-small cell lung cancer (NSCLC) patients. The mechanisms for this are not fully understood, however the composition and activation status of the cellular milieu contained within the tumour microenvironment (TME) is becomingly increasingly recognised as a driving factor in treatment-refractory disease.MethodsHere, we employed multiplex IHC (mIHC), and digital spatial profiling (DSP) to capture the targeted immune proteome and transcriptome of tumour and TME compartments of pre-treatment samples from a 2nd line NSCLC ICI-treated cohort (n=41 patients; n=25 responders, n=16 non-responders).ResultsWe demonstrate by mIHC that the interaction of CD68+ macrophages with PD1+, FoxP3+ cells is significantly enriched in ICI refractory tumours (p=0.012). Our study revealed that patients sensitive to ICI therapy expressed higher levels of IL2 receptor alpha (CD25, p=0.028) within the tumour compartments, which corresponded with the increased expression of IL2 mRNA (p=0.001) within their stroma, indicative of key conditions for ICI efficacy prior to treatment. IL2 mRNA levels within the stroma positively correlated with the expression of pro-apoptotic markers cleaved caspase 9 (p=2e-5) and BAD (p=5.5e-4) and negatively correlated with levels of memory T cells (CD45RO) (p=7e-4). Immuno-inhibitory markers CTLA-4 (p=0.021) and IDO-1 (p=0.023) were also supressed in ICI-responsive patients. Of note, tumour CD44 (p=0.02) was depleted in the response group and corresponded inversely with significantly higher stromal expression of its ligand SPP1 (osteopontin, p=0.008). Analysis of differentially expressed transcripts indicated the potential inhibition of stromal interferon-gamma (IFNγ) activity, as well as estrogen-receptor and Wnt-1 signalling activity within the tumour cells of ICI responsive patients. Cox survival analysis indicated tumour CD44 expression was associated with poorer prognosis (HR=1.61, p=0.01), consistent with its depletion in ICI sensitive patients. Similarly, stromal CTLA-4 (HR=1.78, p=0.003) and MDSC/M2 macrophage marker ARG1 (HR=2.37, p=0.01) were associated with poorer outcome while levels of apoptotic marker BAD (HR=0.5, p=0.01) appeared protective. Interestingly, stromal mRNA for E-selectin (HR=652, p=0.001), CCL17 (HR=70, p=0.006) and MTOR (HR=1065, p=0.008) were highly associated with poorer outcome, indicating pro-tumourigenic features in the tumour microenvironment that may facilitate ICI resistance.ConclusionsThrough multi-modal approaches, we have dissected the characteristics of NSCLC and provide evidence for the role of IL2 and stromal activation by osteopontin in the efficacy of current generations of ICI therapy. The enrichment of SPP1 in the stroma of ICI sensitive patients in our data is a novel finding, indicative of stromal activation that may aid immune cell survival and activity despite no clear association with increased levels of immune infiltrate.

ObjectivesThrombotic and microvascular complications are frequently seen in deceased COVID-19 patients. However, whether this is caused by direct viral infection of the endothelium or inflammation-induced endothelial activation remains highly contentious.MethodsHere, we use patient autopsy samples, primary human endothelial cells and an in vitro model of the pulmonary epithelial-endothelial cell barrier to show that primary human endothelial cells express very low levels the SARS-CoV-2 receptor ACE2 and the protease TMPRSS2.ResultsAccordingly, endothelial cells can only be infected when SARS-CoV-2 is present at very high concentrations. However, this is not a productive infection (i.e. no infectious virus is produced) and viral entry induces an inflammatory response. We also show that SARS-CoV-2 does not infect endothelial cells in 3D vessels under flow conditions. We further demonstrate that in a co-culture model endothelial cells are not infected with SARS-CoV-2. They do however sense and respond to infection in the adjacent epithelial cells, increasing ICAM-1 expression and releasing pro-inflammatory cytokines.ConclusionsTaken together, these data suggest that in vivo, endothelial cells are unlikely to be infected with SARS-CoV-2 and that infection is only likely to occur if the adjacent pulmonary epithelium is denuded (basolateral infection) or a high viral load is present in the blood (apical infection). In such a scenario, whilst SARS-CoV-2 infection of the endothelium can occur, it does not contribute to viral amplification. However, endothelial cells are still likely to play a key role in SARS-CoV-2 pathogenesis by sensing adjacent infection and mounting a pro-inflammatory response to SARS-CoV-2.

BackgroundThe severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which emerged in late 2019 has spread globally, causing a pandemic of respiratory illness designated coronavirus disease 2019 (COVID-19). A better definition of the pulmonary host response to SARS-CoV-2 infection is required to understand viral pathogenesis and to validate putative COVID-19 biomarkers that have been proposed in clinical studies.MethodsHere, we use targeted transcriptomics of formalin-fixed paraffin-embedded tissue using the NanoString GeoMX platform to generate an in-depth picture of the pulmonary transcriptional landscape of COVID-19, pandemic H1N1 influenza and uninfected control patients.ResultsHost transcriptomics showed a significant upregulation of genes associated with inflammation, type I interferon production, coagulation and angiogenesis in the lungs of COVID-19 patients compared to non-infected controls. SARS-CoV-2 was non-uniformly distributed in lungs (emphasising the advantages of spatial transcriptomics) with the areas of high viral load associated with an increased type I interferon response. Once the dominant cell type present in the sample, within patient correlations and patient–patient variation, had been controlled for, only a very limited number of genes were differentially expressed between the lungs of fatal influenza and COVID-19 patients. Strikingly, the interferon-associated gene IFI27, previously identified as a useful blood biomarker to differentiate bacterial and viral lung infections, was significantly upregulated in the lungs of COVID-19 patients compared to patients with influenza.ConclusionCollectively, these data demonstrate that spatial transcriptomics is a powerful tool to identify novel gene signatures within tissues, offering new insights into the pathogenesis of SARS-COV-2 to aid in patient triage and treatment.

Objectives Thrombotic and microvascular complications are frequently seen in deceased COVID‐19 patients. However, whether this is caused by direct viral infection of the endothelium or inflammation‐induced endothelial activation remains highly contentious. Methods Here, we use patient autopsy samples, primary human endothelial cells and an in vitro model of the pulmonary epithelial–endothelial cell barrier. Results We show that primary human endothelial cells express very low levels of the SARS‐CoV‐2 receptor ACE2 and the protease TMPRSS2, which blocks their capacity for productive viral infection, and limits their capacity to produce infectious virus. Accordingly, endothelial cells can only be infected when they overexpress ACE2, or are exposed to very high concentrations of SARS‐CoV‐2. We also show that SARS‐CoV‐2 does not infect endothelial cells in 3D vessels under flow conditions. We further demonstrate that in a co‐culture model endothelial cells are not infected with SARS‐CoV‐2. Endothelial cells do however sense and respond to infection in the adjacent epithelial cells, increasing ICAM‐1 expression and releasing pro‐inflammatory cytokines. Conclusions Taken together, these data suggest that in vivo, endothelial cells are unlikely to be infected with SARS‐CoV‐2 and that infection may only occur if the adjacent pulmonary epithelium is denuded (basolateral infection) or a high viral load is present in the blood (apical infection). In such a scenario, whilst SARS‐CoV‐2 infection of the endothelium can occur, it does not contribute to viral amplification. However, endothelial cells may still play a key role in SARS‐CoV‐2 pathogenesis by sensing adjacent infection and mounting a pro‐inflammatory response to SARS‐CoV‐2., We show that endothelial cells are not productively infected with SARS‐CoV‐2 but mount a pro‐inflammatory response to the virus.

The era of precision medicine has been powered in part by advancements in the field of immuno-oncology, which postulates that harnessing the body’s own immune system is key to eliminating cancer. Immunotherapies have, to date, revolutionised the field of oncology. The immune contexture of the tumour microenvironment (TME) is an important factor in dictating how well a tumour may respond to immune checkpoint inhibitors (ICI), but biomarker information alone is insufficient to design appropriate treatment strategies. Instead, we now understand that spatial classification of the immune contexture within the TME is foundational towards addressing how immunological composition and status dictates responses to therapy. In this project, we used a combination of high throughput and high-fidelity spatial biomarker detection strategies to thoroughly characterize the TME of non-small cell lung carcinoma tissue samples against outcomes for immunotherapy arm of the trial (Nivolumab) and standard of care (chemotherapy). Experimental cohorts were categorized into four pools, consisting of tissues from complete responders, partial responders, stable disease and progressive disease patients. We first analyzed tissues via whole-slide multiplex-immunohistochemistry (mIHC) using the Vectra Polaris spatial imaging platform. For this purpose we used 3 x 6 plex antibody panels, aimed at T-cell profiling, immune exhaustion and immuno-modulatory targets. We then expanded upon this work using an ultra-high plex antibody imaging panel of 50 or more antibodies with the aim at identifying additional spatial signatures in the different experimental conditions. The latter experiments were conducted with CODEX system, which readily provides whole-slide, single cell resolution imaging data from FFPE samples. Both datasets were for distinct spatial profiles in each experimental condition and compared to their clinical outcome to therapy via discriminant analyses. Identifying the benefit of treating patients with immune checkpoint inhibitor therapy prior to treatment will ensure better outcomes given that immunotherapies can only fight tumours that the immune system ‘sees’ and recognises as foreign and harmful. However, in tumour tissue, these biomarkers are highly variable and change dynamically. Therefore, there is growing consensus for the development of additional and more predictive biomarkers of response to ICI therapy. Spatial phenotyping of the immune landscape will reveal cell types and spatial signatures associated with outcomes to immunotherapy. Citation Format: Arutha Kulasinghe, Ning Ma, James Monkman, Najiba Mammadova, Oliver Braubach, Ken O'Byrne. Profiling spatial signatures in the microenvironment of non-small cell lung carcinomas in immunotherapy responsive and resistant disease cohorts [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 1714.

Immunotherapies have led to long term benefits in a subset of non-small cell lung cancer (NSCLC) patients. Developing predictive biomarkers of response to therapy is currently an unmet clinical need. The composition of the cellular content of the tumour microenvironment (TME) is an important characteristic driving treatment resistance. In this study, we utilised spatial transcriptomics methods, including Nanostring digital spatial profiling (DSP) and multiplex IHC, to define the tumour/stroma (compartment) specific proteome and transcriptome from a cohort of 2nd line immunotherapy treated NSCLC patients. We identified by mIHC that CD68+ macrophages with PD1+, FoxP3+ cells is significantly enriched in immunotherapy resistant tumours (p=0.012). Moreover, IL2 mRNA (p=0.001) in the stromal compartment was significantly increased in patients that were sensitive to ICI therapy, whilst CTLA-4 and IDO-1 were suppressed in responsive patients. Tumour compartment localised CD44 was depleted in the responder group and corresponded inversely with higher stromal expression of one of its ligands, SPP1 (p=0.008). Orthogonal validation of CD44 by multiplex immunofluorescence confirmed both its association with response and localisation to tumour cells rather than immune cell infiltrate. Cox survival analysis showed that tumour compartment CD44 expression was associated with a poorer prognosis (HR=1.61, p=0.01) whilst stromal localisation of CTLA-4 (HR=1.78, p=0.003) and ARG1 (HR=2.37, p=0.01) were associated with poorer outcome. Through a multi-omics approach, we demonstrate the utility of spatial mapping of NSCLC tumours and provide evidence for the role of a number of compartment-specific biomarkers which may aid in identifying those likely to respond to immunotherapy. Citation Format: Arutha Kulasinghe, James Monkman, Honesty Kim, Aaron Mayer, Ahmed Mehdi, Nicholas Matigian, Marie Cumberbatch, Milan Bhagat, Rahul Ladwa, Scott Mueller, Mark Adams, Ken O'Byrne. Multi-omic dissection of immunotherapy response groups in non-small cell lung cancer (NSCLC) [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 2036.

8544 Background: Immune checkpoint inhibitors (ICI) have shown durable benefit in a subset of non-small cell lung cancer (NSCLC) patients. The composition of the tumour microenvironment (TME) is becomingly increasingly recognised as an important factor to predict response to therapy. Methods: Here, we applied digital spatial profiling of the tumour and stromal compartments from a 2nd line NSCLC ICI-treated cohort (n = 41 patient) and standard of care (SOC), platinum treated NSCLC cohort (n = 47), to identify tissue-based signatures of response to therapy. Results: We demonstrate by mIHC that the interaction of CD68+ macrophages with PD1+, FoxP3+ cells is significantly enriched in ICI refractory tumours (p = 0.012). Patients sensitive to ICI therapy expressed higher levels of IL2 receptor alpha (CD25, p = 0.028) within the tumour compartments, which corresponded with the increased expression of IL2 mRNA (p = 0.001) within their stroma. Immuno-inhibitory markers CTLA-4 (p = 0.021) and IDO-1 (p = 0.023) were supressed in ICI-responsive patients. Tumour CD44 (p = 0.02) was depleted in the response group and corresponded inversely with significantly higher stromal expression of one of its ligands, SPP1 (osteopontin, p = 0.008). Analysis of dysregulated transcripts indicated the potential inhibition of stromal interferon-gamma (IFNγ) activity, estrogen-receptor and Wnt-1 signalling activity within the tumour cells of ICI responsive patients. Cox survival analysis indicated tumour CD44 expression was associated with poorer prognosis (HR = 1.61, p = 0.01), consistent with its depletion in ICI sensitive patients. Similarly, stromal CTLA-4 (HR = 1.78, p = 0.003) and MDSC/M2 macrophage marker ARG1 (HR = 2.37, p = 0.01) were associated with poorer outcome while BAD (HR = 0.5, p = 0.01) appeared protective. The SOC cohort paralleled similar roles for immune checkpoints and pro-apoptotic markers, with LAG3 (HR = 3.81, p = 0.04) indicating poorer outcome, and BIM (HR = 0.16, p = 0.014) with improved outcome. Interestingly, stromal mRNA for E-selectin (HR = 652, p = 0.001), CCL17 (HR = 70, p = 0.006) and MTOR (HR = 1065, p = 0.008) were highly associated with poorer outcome in ICI treated patients, indicating pro-tumourigenic features in the tumour microenvironment that may facilitate ICI resistance. Conclusions: Through multi-modal approaches, we have dissected the characteristics of NSCLC treatment groups and provide evidence for the role of several markers including IL2, CD25, CD44 and SPP1 in the efficacy of current generations of ICI therapy.

Profiling the tumour microenvironment (TME) has been informative in understanding the underlying tumour&ndash, immune interactions. Multiplex immunohistochemistry (mIHC) coupled with molecular barcoding technologies have revealed greater insights into the TME. In this study, we utilised the Nanostring GeoMX Digital Spatial Profiler (DSP) platform to profile a non-small-cell lung cancer (NSCLC) tissue microarray for protein markers across immune cell profiling, immuno-oncology (IO) drug targets, immune activation status, immune cell typing, and pan-tumour protein modules. Regions of interest (ROIs) were selected that described tumour, TME, and normal adjacent tissue (NAT) compartments. Our data revealed that paired analysis (n = 18) of matched patient compartments indicate that the TME was significantly enriched in CD27, CD3, CD4, CD44, CD45, CD45RO, CD68, CD163, and VISTA relative to the tumour. Unmatched analysis indicated that the NAT (n = 19) was significantly enriched in CD34, fibronectin, IDO1, LAG3, ARG1, and PTEN when compared to the TME (n = 32). Univariate Cox proportional hazards indicated that the presence of cells expressing CD3 (hazard ratio (HR): 0.5, p = 0.018), CD34 (HR: 0.53, p = 0.004), and ICOS (HR: 0.6, p = 0.047) in tumour compartments were significantly associated with improved overall survival (OS). We implemented both high-plex and high-throughput methodologies to the discovery of protein biomarkers and molecular phenotypes within biopsy samples, and demonstrate the power of such tools for a new generation of pathology research.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that emerged in late 2019 has spread globally, causing a pandemic of respiratory illness designated coronavirus disease 2019 (COVID-19). Robust blood biomarkers that reflect tissue damage are urgently needed to better stratify and triage infected patients. Here, we use spatial transcriptomics to generate an in-depth picture of the pulmonary transcriptional landscape of COVID-19 (10 patients), pandemic H1N1 (pH1N1) influenza (5) and uninfected control patients (4). Host transcriptomics showed a significant upregulation of genes associated with inflammation, type I interferon production, coagulation and angiogenesis in the lungs of COVID-19 patients compared to non-infected controls. SARS-CoV-2 was non-uniformly distributed in lungs with few areas of high viral load and these were largely only associated with an increased type I interferon response. A very limited number of genes were differentially expressed between the lungs of influenza and COVID-19 patients. Specific interferon-associated genes (includingIFI27) were identified as candidate novel biomarkers for COVID-19 differentiating this COVID-19 from influenza. Collectively, these data demonstrate that spatial transcriptomics is a powerful tool to identify novel gene signatures within tissues, offering new insights into the pathogenesis of SARS-COV-2 to aid in patient triage and treatment.

Background: Circulating tumour DNA (ctDNA) has emerged as a promising biomarker for monitoring non-small-cell lung cancer (NSCLC). This has enabled the monitoring of clinically actionable mutations over the course of therapy. Case presentation: We present the case of a 74-year-old female who was treated with EGFR inhibitors for NSCLC which later transformed to SCLC. The kinetics of ctDNA was monitored by measuring the EGFR Exon 19 mutant L747–A750 > P and PIK3CA E545K over the course of therapy. Stabilisation of the PIK3CA mutation was found in response to therapy, however there appeared to be increasing levels of the EGFR mutant, potentially reflective of untreated EGFR-driven disease. Conclusion: The key finding described here, revealed by mutational tracking of mutations from the blood, is that clinically actionable mutations are assessable and may demonstrate clinical utility in measuring disease burden, multiple clones and progression non-invasively for lung cancer.

Background: Breast cancer (BC) is a heterogeneous disease for which the commonly used chemotherapeutic agents primarily include the anthracyclines (doxorubicin, epirubicin), microtubule inhibitors (paclitaxel, docetaxel, eribulin), and alkylating agents (cyclophosphamide). While these drugs can be highly effective, metastatic tumours are frequently refractory to treatment or become resistant upon tumour relapse. Methods: We undertook a cell polarity/epithelial mesenchymal plasticity (EMP)-enriched short hairpin RNA (shRNA) screen in MDA-MB-468 breast cancer cells to identify factors underpinning heterogeneous responses to three chemotherapeutic agents used clinically in breast cancer: Doxorubicin, docetaxel, and eribulin. shRNA-transduced cells were treated for 6 weeks with the EC10 of each drug, and shRNA representation assessed by deep sequencing. We first identified candidate genes with depleted shRNA, implying that their silencing could promote a response. Using the Broad Institute&rsquo, s Connectivity Map (CMap), we identified partner inhibitors targeting the identified gene families that may induce cell death in combination with doxorubicin, and tested them with all three drug treatments. Results: In total, 259 shRNAs were depleted with doxorubicin treatment (at p &lt, 0.01), 66 with docetaxel, and 25 with eribulin. Twenty-four depleted hairpins overlapped between doxorubicin and docetaxel, and shRNAs for TGFB2, RUNX1, CCDC80, and HYOU1 were depleted across all the three drug treatments. Inhibitors of MDM/TP53, TGFBR, and FGFR were identified by CMap as the top pharmaceutical perturbagens and we validated the combinatorial benefits of the TGFBR inhibitor (SB525334) and MDM inhibitor (RITA) with doxorubicin treatment, and also observed synergy between the inhibitor SB525334 and eribulin in MDA-MB-468 cells. Conclusions: Taken together, a cell polarity/EMP-enriched shRNA library screen identified relevant gene products that could be targeted alongside current chemotherapeutic agents for the treatment of invasive BC.

Immunotherapies have shown long‐lasting and unparalleled responses for cancer patients compared to conventional therapy. However, they seem to only be effective in a subset of patients. Therefore, it has become evident that a greater understanding of the tumor microenvironment (TME) is required to understand the nuances which may be at play for a favorable outcome to therapy. The immune contexture of the TME is an important factor in dictating how well a tumor may respond to immune checkpoint inhibitors. While traditional immunohistochemistry techniques allow for the profiling of cells in the tumor, this is often lost when tumors are analysed using bulk tissue genomic approaches. Moreover, the actual cellular proportions, cellular heterogeneity and deeper spatial distribution are lacking in characterisation. Advances in tissue interrogation technologies have given rise to spatially resolved characterisation of the TME. This review aims to provide an overview of the current methodologies that are used to profile the TME, which may provide insights into the immunopathology associated with a favorable outcome to immunotherapy., In this review, we discuss spatial analysis tools that can be used to characterise the tumor microenvironment. We present a number of technologies that are transforming the field and providing insights into the immunopathology associated with a favorable outcome to immunotherapy.

Dynamic interconversions between transitional epithelial and mesenchymal states underpin the epithelial mesenchymal plasticity (EMP) seen in some carcinoma cell systems. We have delineated epithelial and mesenchymal subpopulations existing within the PMC42-LA breast cancer cell line by their EpCAM expression. These purified but phenotypically plastic states, EpCAMHigh (epithelial) and EpCAMLow (mesenchymal), have the ability to regain the phenotypic equilibrium of the parental population (i.e., 80% epithelial and 20% mesenchymal) over time, although the rate of reversion in the mesenchymal direction (epithelial-mesenchymal transition; EMT) is higher than that in the epithelial direction (mesenchymal-epithelial transition; MET). Single-cell clonal propagation was implemented to delineate the molecular and cellular features of this intrinsic heterogeneity with respect to EMP flux. The dynamics of the phenotypic proportions of epithelial and mesenchymal states in single-cell generated clones revealed clonal diversity and intrinsic plasticity. Single cell-derived clonal progenies displayed differences in their functional attributes of proliferation, stemness marker (CD44/CD24), migration, invasion and chemo-sensitivity. Interrogation of genomic copy number variations (CNV) with whole exome sequencing (WES) in the context of chromosome count from metaphase spread indicated that chromosomal instability was not influential in driving intrinsic phenotypic plasticity. Overall, these findings reveal the stochastic nature of both the epithelial and mesenchymal subpopulations, and the single cell-derived clones for differential functional attributes.

Epithelial−mesenchymal plasticity (EMP), encompassing epithelial−mesenchymal transition (EMT) and mesenchymal−epithelial transition (MET), are considered critical events for cancer metastasis. We investigated chromosomal heterogeneity and chromosomal instability (CIN) profiles of two sister PMC42 breast cancer (BC) cell lines to assess the relationship between their karyotypes and EMP phenotypic plasticity. Karyotyping by GTG banding and exome sequencing were aligned with SWATH quantitative proteomics and existing RNA-sequencing data from the two PMC42 cell lines; the mesenchymal, parental PMC42-ET cell line and the spontaneously epithelially shifted PMC42-LA daughter cell line. These morphologically distinct PMC42 cell lines were also compared with five other BC cell lines (MDA-MB-231, SUM-159, T47D, MCF-7 and MDA-MB-468) for their expression of EMP and cell surface markers, and stemness and metabolic profiles. The findings suggest that the epithelially shifted cell line has a significantly altered ploidy of chromosomes 3 and 13, which is reflected in their transcriptomic and proteomic expression profiles. Loss of the TGFβR2 gene from chromosome 3 in the epithelial daughter cell line inhibits its EMT induction by TGF-β stimulus. Thus, integrative ‘omics’ characterization established that the PMC42 system is a relevant MET model and provides insights into the regulation of phenotypic plasticity in breast cancer.