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Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal and debilitating disease with limited therapeutic options. The aim of this clinical study was to evaluate the safety, efficacy and pharmacokinetics of a novel regimen comprised of metronomic oxaliplatin (O), chronomodulated capecitabine (X) and UGT1A1 genotype-guided dosing of irinotecan (IRI) [OXIRI] as well as its immunomodulatory effects. Thirty-six patients were enrolled into either dose-escalation or expansion cohorts. In the dose escalation phase, capecitabine doses (2000, 2650, 3500 and 4500 mg/day) were administered at midnight on days 1 to 14 while oxaliplatin and irinotecan were intravenously infused at fixed doses of 50 and 75 mg/m

Angiosarcomas are rare malignant tumors of the endothelium, arising commonly from the head and neck region (AS-HN) and recently associated with ultraviolet (UV) exposure and human herpesvirus-7 infection. We examined 81 cases of angiosarcomas, including 47 cases of AS-HN, integrating information from whole genome sequencing, gene expression profiling and spatial transcriptomics (10X Visium). In the AS-HN cohort, we observed recurrent somatic mutations in CSMD3 (18%), LRP1B (18%), MUC16 (18%), POT1 (16%) and TP53 (16%). UV-positive AS-HN harbored significantly higher tumor mutation burden than UV-negative cases (p = 0.0294). NanoString profiling identified three clusters with distinct tumor inflammation signature scores (p

Given the high prevalence and relapse rates of hepatocellular carcinoma (HCC), an increased capacity for early identification of patients most at risk for post-resection recurrence would help improve patient outcomes and prioritize health care resources. Here, we combined spatial multi-transcriptomics and proteomics approaches to characterize the tumor and immunological landscape of 61 samples. We observed a spatial and HCC-recurrence-associated distribution of natural killer (NK) cells in the invasive front and tumor center. Using artificial-intelligence alongside an extreme gradient-boosting algorithm, we developed the Tumor Immune MicroEnvironment Spatial (“TIMES”) score based on the expression of five NK-associated markers (SPON2, ZFP36L2, ZFP36, VIM, and HLA-DRB1) to predict HCC recurrence. We also demonstrated that TIMES score (HR = 29.6, P < 0.001) outperforms the current standard tools for patient risk stratification including the TNM (HR = 1.93, P = 0.113) and BCLC (HR = 1.55, P = 0.253) systems. In the clinic, we validated the model in 103 patients from three multi-centered cohorts achieve a real-world sensitivity of 90.00% and specificity of 90.24%. In the lab, following up on the individual marker with the highest prediction accuracy, in vivo models revealed that SPON2 increases IFN-γ secretion and enhances infiltration potential of NK cells at the invasive front. Additionally, we established the TIMES score on a publicly accessible website that can be easily achieved by different levels of pathology labs to facilitate global prediction of HCC recurrence risk and stratification of high-risk patients. With its ability to efficiently stratify high-risk patients, it exemplifying the utility of artificial intelligence to improve our understanding on TIME features that underlie tumor progression.

Summary Background Therapeutic synergism between radiotherapy and immune checkpoint blockade has been observed in preclinical models of hepatocellular carcinoma. We aimed to study the safety and efficacy of sequential radioembolisation with yttrium-90-resin microspheres (Y90-radioembolisation) followed by nivolumab in patients with advanced hepatocellular carcinoma. Methods Patients with Child-Pugh A cirrhosis and advanced hepatocellular carcinoma not suitable for curative surgery were treated with Y90-radioembolisation followed by intravenous nivolumab 240 mg 21 days after Y90-radioembolisation and every 2 weeks thereafter. The primary endpoint, assessed in the per-protocol population, was the objective response rate, determined by RECIST version 1.1, defined as the proportion of patients with a confirmed complete or partial response observed for lesions both within and outside the Y90-radioembolisation field. This study is registered with ClinicalTrials.gov , NCT03033446 and has been completed. Findings 40 patients were enrolled, of whom 36 received Y90-radioembolisation followed by nivolumab. One (3%) patient had a complete response and ten (28%) had a partial response; the objective response rate was 30·6% (95% CI 16·4–48·1). The most common treatment-related adverse events of any grade were pruritus (18 [50%] of 36 patients) and maculopapular rash (13 [36%]). Two (6%) patients experienced grade 3–4 treatment-related adverse events: one patient had a grade 3 increase in alanine aminotransferase levels, grade 3 bilirubin increase, and grade 4 increase in aspartate aminotransferase levels, while the other had a grade 3 maculopapular rash. Five (14%) patients had a treatment-related serious adverse event (Steven-Johnson syndrome, hepatitis E infection, fever, liver abscesses, and ascites). Interpretation Y90-radioembolisation followed by nivolumab resulted in an encouraging objective response rate in patients with advanced hepatocellular carcinoma, although the activity observed was not as high as the study was powered for. This strategy should be further evaluated in patients with Barcelona Clinic Liver Clinic (BCLC) stage B hepatocellular carcinoma that is ineligible or refractory to transarterial chemoembolisation and patients with BCLC C disease without extrahepatic spread. Funding National Medical Research Council Singapore, Bristol-Myers Squibb, Sirtex.

Spatially resolved transcriptomics involves a set of emerging technologies that enable the transcriptomic profiling of tissues with the physical location of expressions. Although a variety of methods have been developed for data integration, most of them are for single-cell RNA-seq datasets without consideration of spatial information. Thus, methods that can integrate spatial transcriptomics data from multiple tissue slides, possibly from multiple individuals, are needed. Here, we present PRECAST, a data integration method for multiple spatial transcriptomics datasets with complex batch effects and/or biological effects between slides. PRECAST unifies spatial factor analysis simultaneously with spatial clustering and embedding alignment, while requiring only partially shared cell/domain clusters across datasets. Using both simulated and four real datasets, we show improved cell/domain detection with outstanding visualization, and the estimated aligned embeddings and cell/domain labels facilitate many downstream analyses. We demonstrate that PRECAST is computationally scalable and applicable to spatial transcriptomics datasets from different platforms.

The authors present a 45-year-old lady with a rare undifferentiated round cell tumour of the lung with a ESWR1-CREM fusion gene that progressed despite multiple lines of therapy. The tumour was Somatostatin Receptors Type 2 (SSTR2) positive and avid on 68Gallium-DOTATATE imaging. This allowed for novel treatment with Peptide Receptor Radionuclide Therapy (PRRT) using 177Lutetium-DOTATATE after all other standard of care options were exhausted.

ObjectivesEpigenomic alterations in cancer interact with the immune microenvironment to dictate tumour evolution and therapeutic response. We aimed to study the regulation of the tumour immune microenvironment through epigenetic alternate promoter use in gastric cancer and to expand our findings to other gastrointestinal tumours.DesignAlternate promoter burden (APB) was quantified using a novel bioinformatic algorithm (proActiv) to infer promoter activity from short-read RNA sequencing and samples categorised into APBhigh, APBint and APBlow. Single-cell RNA sequencing was performed to analyse the intratumour immune microenvironment. A humanised mouse cancer in vivo model was used to explore dynamic temporal interactions between tumour kinetics, alternate promoter usage and the human immune system. Multiple cohorts of gastrointestinal tumours treated with immunotherapy were assessed for correlation between APB and treatment outcomes.ResultsAPBhigh gastric cancer tumours expressed decreased levels of T-cell cytolytic activity and exhibited signatures of immune depletion. Single-cell RNAsequencing analysis confirmed distinct immunological populations and lower T-cell proportions in APBhigh tumours. Functional in vivo studies using ‘humanised mice’ harbouring an active human immune system revealed distinct temporal relationships between APB and tumour growth, with APBhigh tumours having almost no human T-cell infiltration. Analysis of immunotherapy-treated patients with GI cancer confirmed resistance of APBhigh tumours to immune checkpoint inhibition. APBhigh gastric cancer exhibited significantly poorer progression-free survival compared with APBlow (median 55 days vs 121 days, HR 0.40, 95% CI 0.18 to 0.93, p=0.032).ConclusionThese findings demonstrate an association between alternate promoter use and the tumour microenvironment, leading to immune evasion and immunotherapy resistance.

We read with interest the study by Manuel et al showing that chronic immunosuppression could protect against severe COVID-19 in liver transplant patients.1 Despite increased comorbidities, COVID-19 in liver transplant patients was not more severe than in non-transplant cohorts.1 2 We present findings from a COVID-19/HIV coinfected decedent who exhibited a significantly longer survival time (46 days) than that of three COVID-19 decedents (average 30 days) (figure 1A). Given the immunosuppressive effects of HIV,3 the prolonged survival of our COVID-19/HIV patient may reflect protection from severe COVID-19. Figure 1 Increased myeloid and reduced T-cell abundance characterises the liver and kidney but not the lungs of a COVID-19/HIV decedent. (A) Kaplan-Meier survival curve of COVID-19/HIV case (nCOVID-19/HIV = 1) and COVID-19 cases (nCOVID-19=3). P-value: Log-rank (Mantel-Cox) test. (B) Representative regions of interest (ROI) of the liver, kidney, and lung from the COVID-19/HIV decedent and one COVID-19 decedent. (C) Principal component analyses of transcriptional profiles of COVID-19/HIV and COVID-19 decedents from ROIs of the lung (nCOVID-19/HIV = 11, nCOVID-19=29), liver (nCOVID-19/HIV = 10, nCOVID-19=32), and kidney (nCOVID-19/HIV = 11, nCOVID-19=8). (D) Relative estimated levels of immune cells determined by deconvolution of digital spatial profiling ROIs using CIBERSORTx (https://cibersort.stanford.edu/). Grey bars indicate the means. P-values were calculated by a two-tailed t -test: *(

Introduction Programmed cell death protein-1 (PD-1) and programmed death-ligand 1 (PD-L1) blockade is currently widely used in the treatment of metastatic NSCLC. Despite available biomarker stratification, clinical responses vary. Thus, the search for novel biomarkers with improved response prediction is ongoing. Previously, using mass cytometry or cytometry by time-of-flight (CyTOF), our group demonstrated that CD39+CD8+ immune cells represent tumor antigen-specific, cytotoxic T cells in treatment-naive NSCLC. We hypothesized that accurate quantitation of this T cell subset would predict immunotherapy outcome. Methods To translate this to a clinical setting, the present study compared CyTOF data with a range of clinically relevant methods, including conventional immunohistochemistry (IHC), multiplex IHC or immunofluorescence (mIHC), and gene expression assay by NanoString. Results Quantification using mIHC but not conventional IHC or NanoString correlated with the CyTOF results. The specificity and sensitivity of mIHC were then evaluated in a separate retrospective NSCLC cohort. CD39+CD8+ T cell proportion, as determined by mIHC, successfully stratified responders and nonresponders to PD-1 or PD-L1 inhibitors (objective response rate of 63.6%, compared with 0% for the negative group). This predictive capability was independent from other confounding factors, such as total CD8+ T cell proportion, CD39+ lymphocyte proportion, PD-L1 positivity, EGFR mutation status, and other clinicopathologic parameters. Conclusions Our results suggest that the mIHC platform is a clinically relevant method to evaluate CD39+CD8+ T cell proportion and that this marker can serve as a potential biomarker that predicts response to PD-1 or PD-L1 blockade in patients with NSCLC. Further validation in additional NSCLC cohorts is warranted.

Mutations in the PI3K pathway, particularly of PIK3CA, were reported to be intimately associated with triple negative breast cancer (TNBC) progression and development of treatment resistance. We profiled PIK3CA and other genes on 166 early-stage TNBC tumors from Singapore, for comparison to publicly available TNBC cohorts. These tumors were profiled transcriptionally using a Nanostring panel of immune genes and multiplex immunohistochemistry, then manually scored for PD-L1-positivity using two clinically relevant clones, SP142 and 22C3. We discovered a higher rate of PIK3CA mutations in our TNBC cohort as compared to non-Asian cohorts, along with TP53, BRCA1, PTPN11, and MAP3K1 alterations. PIK3CA mutations did not affect overall or recurrence-free survival, and when compared to PIK3CAWT tumors, there were no differences in immune infiltration. Using two clinically approved antibodies, PIK3CAmut tumors were associated with PD-L1 negativity. Analysis of co-mutation frequencies further revealed that PIK3CA mutations tended to be accompanied by MAP kinase pathway mutation. The mechanism and impact of PIK3CA alterations on the TNBC tumor immune microenvironment and PD-L1 positivity warrant further study.

We read with great interest the article published by Zuo et al , which highlighted the presence of SARS-CoV-2 RNA in stool samples during active and convalescence phases of COVID-19 infection.1 However, no study has reported the presence of viral antigens within GI and hepatic organs during the convalescent phase. Using conventional immunohistochemistry, we detected SARS-CoV-2 nucleocapsid protein (NP) in the colon, appendix, ileum, haemorrhoid, liver, gallbladder and lymph nodes (figure 1A–K) from five patients who recovered from COVID-19, ranging from 9 to 180 days after testing negative for SARS-CoV-2 (online supplemental table 1). Notably, when multiple tissues were obtained from one patient (patients 1 and 4), all the tissues showed the presence of the viral antigen, suggesting widespread multiorgan involvement of the viral infection. Interestingly, for the colon, the viral antigen was only present in normal colonic crypts and polyps but not in the neoplastic tissues (figure 1Q). Similar negative staining in the hepatocellular carcinoma tumour region was also observed (figure 1R) albeit the positive staining in some of the scattered immune cells (figure 1D). Validating our findings, we detected SARS-CoV-2 spike protein (figure 1L–P) and RNA (figure 2B–F) in the above-mentioned tissues using conventional immunohistochemistry and RNAscope, respectively. However, we were unable to detect viral RNA in some patients’ tissues (online supplemental table 1), possibly because of higher RNA degradation rate as compared with protein and other patient-dependent factors such as disease severity, time since recovery and basal metabolic rate.### Supplementary data [gutjnl-2021-324280supp001.pdf] Figure 1 Immunohistochemical staining of the SARS-CoV-2 nucleocapsid and spike proteins in intestinal and hepatic tissues. (A and B) Positive SARS-CoV-2 nucleocapsid protein (NP) staining in colonic crypts (A) and appendix (B), both with a granular supranuclear cytoplasmic pattern. (C) positive SARS-CoV-2 NP staining in scattered immune cells …

Background & Aims Little is known about Epstein-Barr virus (EBV)-associated intrahepatic cholangiocarcinoma (EBVaICC) because of its rarity. We aimed to comprehensively investigate the clinicopathology, tumor immune microenvironment (TIME) and genomic landscape of this entity in southern China. Methods We evaluated 303 intrahepatic cholangiocarcinomas (ICCs) using in situ hybridization for EBV. We compared clinicopathological parameters between EBVaICC and nonEBVaICC, and we analyzed EBV infection status, tumor-infiltrating lymphocytes (TILs) and genomic features of EBVaICC by immunohistochemistry, double staining, nested PCR, multiplex immunofluorescence staining, fluorescence in situ hybridization and whole-exome sequencing. Results EBVaICC accounted for 6.6% of ICCs and was associated with EBV latency type I infection and clonal EBV isolates. Patients with EBVaICC were more often female and younger, with solitary tumors, higher HBV infection rates and less frequent cirrhosis; the lymphoepithelioma-like (LEL) subtype was more common in EBVaICC. EBVaICC was associated with a significantly larger TIME component than nonEBVaICC. The LEL subtype of EBVaICC – associated with a significantly increased density and proportion of CD20+ B cells and CD8+ T cells – was associated with significantly higher 2-year survival rates than conventional EBVaICC and nonEBVaICC. Both PD-1 and PD-L1 in TILs, and PD-L1 in tumor cells, were overexpressed in EBVaICC. High PD-L1 expression in tumor cells and high CD8+ TIL densities were significantly more common in EBVaICC than in nonEBVaICC. Seven genes (MUC4, DNAH1, GLI2, LIPE, MYH7, RP11-766F14.2 and WDR36) were mutated in at least 3 patients. EBVaICC had a different mutational pattern to liver fluke-associated cholangiocarcinoma and HBV-associated ICC. Conclusions EBVaICC, as a subset of ICC, has unique etiological, clinicopathological and genetic characteristics, with a significantly larger TIME component. Paradoxically, patients with EBVaICC could be candidates for immune checkpoint therapy. Lay summary Epstein-Barr virus (EBV) is associated with a subtype of intrahepatic cholangiocarcinoma, with unique clinicopathological and genetic characteristics. The tumor immune microenvironment is also different in this tumor subtype and patients with EBV-associated intrahepatic cholangiocarcinoma may respond well to immune checkpoint inhibitors.

Regulatory T cells (Tregs) are often enriched in tumors, where their immunosuppressive function has a key role in tumor persistence and progression. In colorectal cancer (CRC), however, Tregs are frequently associated with an improved clinical outcome. Tumor-infiltrating Tregs have been shown to exhibit a distinct signature comprising the co-stimulatory molecules (OX40, 4-1BB), cytokine receptors (IL1R2, IL21R, CCR8, CD30), and co-inhibitory molecules (PD-L1, TIGIT). Here, we showed by flow cytometry that circulating CD45RO+ Tregs from patients with CRC (n = 25) have elevated CD30 and OX40 expression compared to healthy subjects (n = 14). We identified co-expression of CD30 and OX40 on circulating CD45RO+ Tregs using single-cell images captured by the DEPArray™ system. The frequency of CD30+OX40+CD45RO+ Tregs was significantly higher in CRC patients than in healthy subjects (P +OX40+ Treg subset could strongly discriminate between CRC patients and healthy subjects with the highest accuracy of 92.3%, an AUC of 0.92, a sensitivity of 88%, a specificity of 100%, a positive predictive value of 100%, a negative predictive value of 82.35%, and a trade-off value of 3.44%, compared to other Treg subsets. Consistently, multiplex-IHC/IF of tumor-infiltrating Tregs revealed a significant association between high densities of CD30+OX40+ Tregs and improved overall survival; no such association was found for other subsets. These data suggest a potential role for CD30+OX40+ Tregs as a diagnostic or prognostic biomarker in CRC.

MotivationSpatially resolved transcriptomics (SRT) technologies have been developed to simultaneously profile gene expression while retaining physical information. To explore differentially expressed genes using SRT in the context of various conditions, statistical methods are needed to perform spatial differential expression analysis.ResultsWe propose that a new probabilistic framework, spatialDEG, can perform differential expression analysis by leveraging spatial information on gene expression with spatial information. SpatialDEG utilizes the average information algorithm and can be scalable to tens of thousands of genes. Comprehensive simulations demonstrated that spatialDEG can identify genes differentially expressed in tissues across different conditions with a controlled type-I error rate. We further applied spatialDEG to analyze datasets for human dorsolateral prefrontal cortex and mouse whole liver.AvailabilityThe R package spatialDEG can be downloaded from https://github.com/Shufeyangyi2015310117/spatialDEG.

BACKGROUND Invasive lobular carcinomas (ILC) form 5%-10% of breast cancer and rarely show overexpression of human epidermal growth factor receptor 2 (HER2). AIM To describe the prevalence and prognostic factors of HER2 positive (HER2+) ILC in an Asian population. METHODS A retrospective review of patients with ILC seen between January 1985 and March 2018 at various SingHealth medical institutions was conducted. Demographic and clinical data were collected from medical records. We examined clinicopathological characteristics and survival in relation to HER2 status. RESULTS A total of 864 patients were included. Prevalence of HER2 positivity was 10.1% (87 patients). Compared with HER2 negative (HER2-) ILC, HER2+ ILC was associated with a higher proportion of estrogen receptor negative (24.4% vs 5.9%, P < 0.001), progesterone receptor negative (PR-) (40.2% vs 24%, P = 0.002) and grade 3 tumours (Grade 3, 29.0% vs 10.2%, P < 0.001). Overall survival rate was poorer in patients with HER2+ compared to HER2- ILC (56.7% vs 72.9% alive at 10 years; hazard ratio 1.87, 95% confidence interval: 1.21-2.90, P = 0.004). Based on multivariate analysis, negative prognostic factors for overall survival included HER2 positivity, PR negativity, older age, Indian ethnicity and higher tumour stage. CONCLUSION Prevalence of HER2+ ILC was 10.1%. HER2+ ILC was more likely to have poorer prognostic features such as estrogen receptor negative, PR- and higher tumour grade, and have a poorer survival.

Dimension reduction and (spatial) clustering is usually performed sequentially; however, the low-dimensional embeddings estimated in the dimension-reduction step may not be relevant to the class labels inferred in the clustering step. We therefore developed a computation method, Dimension-Reduction Spatial-Clustering (DR-SC), that can simultaneously perform dimension reduction and (spatial) clustering within a unified framework. Joint analysis by DR-SC produces accurate (spatial) clustering results and ensures the effective extraction of biologically informative low-dimensional features. DR-SC is applicable to spatial clustering in spatial transcriptomics that characterizes the spatial organization of the tissue by segregating it into multiple tissue structures. Here, DR-SC relies on a latent hidden Markov random field model to encourage the spatial smoothness of the detected spatial cluster boundaries. Underlying DR-SC is an efficient expectation-maximization algorithm based on an iterative conditional mode. As such, DR-SC is scalable to large sample sizes and can optimize the spatial smoothness parameter in a data-driven manner. With comprehensive simulations and real data applications, we show that DR-SC outperforms existing clustering and spatial clustering methods: it extracts more biologically relevant features than conventional dimension reduction methods, improves clustering performance, and offers improved trajectory inference and visualization for downstream trajectory inference analyses.

The World Health Organization has defined long COVID-19 (LC) as a condition where patients exhibit persistent symptoms over time after its acute phase, which cannot be explained by alternative diagnosis. Since we have previously reported residual viral antigens in tissues of convalescent patients, we now aim to assess the presence of such antigens in post-convalescent tissues. Here, we established the presence of residual virus within the appendix and breast tissue of 2 patients who exhibited LC symptoms, 175 to 462 days upon positive diagnosis, using immunohistological techniques. We observed positive staining for viral nucleocapsid protein (NP) in the appendix, and tumour-adjacent region of the breast, but not within the tumour via multiplex immunohistochemistry. Notably, with RNAscope, both positive-sense and negative-sense (replicative intermediate) viral RNA were detected. As a single-stranded virus, SARS-CoV-2, have to produce a replicative intermediate as a template to synthesize new genomic RNAs. Thus, the detection of negative-sense viral RNA suggests ongoing viral replication. While viral RNA and antigen from gastrointestinal and stool samples of convalescent patients has been extensively reported, we believe this is the first study to detect viable virus. Furthermore, our positive finding in the breast tissue also corroborated with recent reports that immunocompromised patients had also experienced LC symptoms and persistent viral replication. Overall, our findings, along with emerging LC studies, question the possibility of the gastrointestinal tract functioning as a reservoir.

Hepatocellular carcinoma (HCC) is one of the deadliest cancer types with diverse etiological factors across the world. Although large scale genomic studies have been conducted in different countries, integrative analysis of HCC genomes and ethnic comparison across cohorts are lacking.

4026 Background: Immune checkpoint inhibitors (ICI) are now standard-of-care treatment for patients with metastatic gastric cancer (GC). To guide patient selection for ICI therapy, programmed death ligand-1 (PD-L1) biomarker expression is routinely assessed via immunohistochemistry (IHC). Regulatory approval for ICIs is granted based on PD-L1 expression status, scored using metrics such as the combined positive score (CPS). However, with an increasing number of approved ICIs, each paired with a different PD-L1 antibody IHC assay used in their respective landmark trials, there is an unmet clinical and logistical need for harmonization. We thus investigated the interchangeability between the Dako 22C3, Dako 28-8 and Ventana SP-142 assays in GC PD-L1 IHC. Methods: In this cross-sectional study, samples were obtained via biopsy or resection of gastric cancer at the National University Hospital, Singapore. We scored 362 GC samples for PD-L1 CPS, tumor proportion score (TPS) and immune cells (IC) using a multiplex immunohistochemistry/immunofluorescence technique. 344 samples were developed into a tissue microarray (TMA), while 18 samples were used as whole slides for orthogonal validation. The samples selected for whole slide analysis were obtained from GC patients treated with ICI therapy. Results: The percentage of PD-L1 positive samples at clinically relevant CPS ≥1, ≥5 and ≥10 cut-offs (Table) for the 28-8 assay were approximately two-fold higher than that of the 22C3 (CPS≥1: 70.3% vs 49.4%, p

Dimension reduction and (spatial) clustering is usually performed sequentially; however, the low-dimensional embeddings estimated in the dimension-reduction step may not be relevant to the class labels inferred in the clustering step. We therefore developed a computation method, Dimension-Reduction Spatial-Clustering (DR-SC), that can simultaneously perform dimension reduction and (spatial) clustering within a unified framework. Joint analysis by DR-SC produces accurate (spatial) clustering results and ensures the effective extraction of biologically informative low-dimensional features. DR-SC is applicable to spatial clustering in spatial transcriptomics that characterizes the spatial organization of the tissue by segregating it into multiple tissue structures. Here, DR-SC relies on a latent hidden Markov random field model to encourage the spatial smoothness of the detected spatial cluster boundaries. Underlying DR-SC is an efficient expectation-maximization algorithm based on an iterative conditional mode. As such, DR-SC is scalable to large sample sizes and can optimize the spatial smoothness parameter in a data-driven manner. With comprehensive simulations and real data applications, we show that DR-SC outperforms existing clustering and spatial clustering methods: it extracts more biologically relevant features than conventional dimension reduction methods, improves clustering performance, and offers improved trajectory inference and visualization for downstream trajectory inference analyses.

Recent advancements in deep learning based artificial intelligence have enabled us to analyse complex data in order to provide patients with improved cancer prognosis, which is an important goal in precision health medicine. In this chapter, we would be discussing how deep learning could be applied to clinical data and immunopathological images to accurately determine survival rate prediction for patients. Multiplex immunohistochemistry/immunofluorescence (mIHC/IF) is a relatively new technology for simultaneous detection of multiple specific proteins from a single tissue section. To adopt deep learning, we collected and pre-processed the clinical and mIHC/IF data from a group of patients into three branches of data. These data were subsequently used to train and validate a neural network. The specific process and our recommendations will be further discussed in this chapter. We believe that our work will help the community to better handle their data for AI implementation while improving its performance and accuracy.

Growing evidence supports the importance of quantifying tumor-immune cell interactions in the tumor microenvironment to enable precision cancer therapy. However, most existing methods rely solely upon immune cell density or nearest neighbor-type analyses and fail to fully characterize spatial heterogeneity. Herein, we describe a computational algorithm, termed Tumor-Immune Partitioning and Clustering (TIPC), that jointly measures immune cell partitioning between tumor epithelial and stromal areas and immune cell clustering versus dispersion. As proof of principle, we apply TIPC to two large colorectal cancer cohorts. TIPC identifies tumor subtypes with unique interaction signatures between tumor cells and T cells that harbor prognostic significance and are associated with distinct tumor molecular features. We extend our findings by applying TIPC to additional immune cell types identified using morphology and supervised machine learning. Spatial heterogeneity quantification and novel tumor subtype identification by TIPC may inform precision cancer immunotherapy and deepen our understanding of tumor immunobiology.

Background:Neoadjuvant chemotherapy (NAC) plays an important role in the management of locally advanced breast cancer. It allows for downstaging of tumours, potentially allowing for breast conservation. NAC also allows for in-vivo testing of the tumours’ response to chemotherapy and provides important prognostic information. There are currently no clearly defined clinical models that incorporate imaging with clinical data to predict response to NAC. Thus, the aim of this work is to develop a predictive AI model based on routine CT imaging and clinical parameters to predict response to NAC. Methods:The CT scans of 324 patients with NAC from multiple centers in Singapore were used in this study. Four different radiomics models were built for predicting pathological complete response (pCR): first two were based on textural features extracted from peri-tumoral and tumoral regions, the third model based on novel space-resolved radiomics which extract feature maps using voxel-based radiomics and the fourth model based on Deep Learning (DL). Clinical parameters were included to build a final prognostic model. Results:The best performing models were based on space-resolved and deep learning approaches. Space-resolved radiomics improves the clinical AUCs of pCR prediction from 0.743 (0.650 to 0.831) to 0.775 (0.685 to 0.860) and our DL model improved it from 0.743 (0.650 to 0.831) to 0.772 (0.685 to 0.853). The tumoral radiomics model performs the worst with no improvement of the AUC from the clinical model. The peri-tumoral combined model gives moderate performance with an AUC of 0.765 (0.671 to 0.855). Conclusions:Radiomics features extracted from diagnostic CT augments the predictive ability of pathological complete response when combined with clinical features. The novel space-resolved radiomics and deep learning radiomics approaches outperformed conventional radiomics techniques.

Background/aimsThe programmed cell death receptor 1 (PD-1) checkpoint inhibitor, nivolumab, has been approved for the treatment of metastatic renal cell carcinoma (RCC). However, the understanding of the expression and distribution of PD ligand 1 (PD-L1) in the tumour immune microenvironment and its prognostic role in an Asian cohort is limited. Our group investigated PD-L1 protein expression in a cohort of Asian patients with RCC of mixed ethnicity, using two commercially available antibody clones.MethodsE1L3N and SP263 anti-PD-L1 clones were used to categorise RCCs of various histological subtypes, diagnosed at our institution between 1995 and 2008, into PD-L1-positive or PD-L1-negative groups, based on a 1% Tumour Proportion Score (TPS) cut-off.ResultsIn total, 267 (83%) clear cell (cc)RCC and 55 (17%) non-ccRCC cases were studied. Overall PD-L1 protein expression rates for the entire cohort were 13% and 8% for the E1L3N and SP263 clones, respectively. Patients bearing PD-L1-positive tumours experienced significantly decreased disease-free survival (DFS; E1L3N: p=0.01; SP263: p=0.03) but not overall survival, compared with those with PD-L1-negative tumours. Multivariate survival analysis further confirmed the results of the E1L3N clone (HR 1.85, 95% CI 1.10 to 3.13, p=0.02), but not SP263, after adjusting for pathological stage, histological subtype and grade. The addition of PD-L1 (E1L3N) TPS to clinicopathological features significantly increased the prognostic value for DFS (∆LRχ2=5.25; p=0.022), compared with clinicopathological features alone.ConclusionsPD-L1 protein expression was associated with an unfavourable prognosis in our study cohort. PD-L1 (E1L3N) expression was an independent prognostic indicator of clinical outcome in all RCCs when using a 1% cut-off.

BackgroundProgrammed death-ligand 1 (PD-L1) monoclonal antibody therapy has recently gained approval for treating metastatic triple-negative breast cancer (TNBC) -, in particular in the PD-L1+patient subgroup of the recent IMpassion130 trial. The SP142 PD-L1 antibody clone was used as a predictive assay in this trial, but this clone was found to be an outlier in previous harmonisation studies in lung cancer.AimsTo address the comparability of PD-L1 clones in TNBC, we evaluated the concordance between conventional immunohistochemistry (IHC) and multiplex immunohistochemistry/immunofluorescence (mIHC/IF) that allowed simultaneous quantification of three different PD-L1 antibodies (22C3, SP142 and SP263).MethodsOur cohort comprised 25 TNBC cases, 12 non-small-cell lung carcinomas and 8 other cancers. EpCAM labelling was used to distinguish tumour cells from immune cells.ResultsModerate-to-strong correlations in PD-L1 positivity were found between results obtained through mIHC/IF and IHC. Individual concordance rates in the study ranged from 67% to 100%, with Spearman’s rank correlation coefficient values up to 0.88.ConclusionsmIHC/IF represents a promising tool in the era of cancer immunotherapy, as it can simultaneously detect and quantify PD-L1 labelling with multiple antibody clones, and allow accurate evaluation of tumour and immune cells. Clinicians and pathologists require this information to predict patient response to anti-PD-1/PD-L1 therapy. The adoption of this assay may represent a significant advance in the management of therapeutically challenging cancers. Further analysis and assay harmonisation are essential for translation to a routine diagnostic setting.

Ductal carcinoma in situ (DCIS) of the breast is often regarded as a non-obligate precursor to invasive breast carcinoma but current diagnostic tools are unable to accurately predict the invasive potential of DCIS. Infiltration of immune cells into the tumour and its microenvironment is often an early event at the site of tumourigenesis. These immune infiltrates may be potential predictive and/or prognostic biomarkers for DCIS. This review aims to discuss recent findings pertaining to the potential prognostic significance of immune infiltrates as well as their evaluation in DCIS. A literature search on PubMed was conducted up to 28th January 2019. Search terms used were “DCIS”, “ductal carcinoma in situ”, “immune”, “immunology”, “TIL”, “TIL assessment”, and “tumour-infiltrating lymphocyte”. Search filters for “Most Recent” and “English” were applied. Information from published papers related to the research topic were synthesised and summarised for this review. Studies have revealed that immune infiltrates play a role in the biology and microenvironment of DCIS, as well as treatment response. There is currently no consensus on the evaluation of TILs in DCIS for clinical application. This review highlights the recent findings on the potential influence and prognostic value of immunological processes on DCIS progression, as well as the evaluation of TILs in DCIS. Further characterisation of the immune milieu of DCIS is recommended to better understand the immune response in DCIS progression and recurrence.

Human umbilical cord lining epithelial cells [CLECs) are naïve in nature and can be ethically recovered from cords that are routinely discarded. The success of using oral mucosal epithelial cells for cornea defects hints at the feasibility of treating cutaneous wounds using non-native CLECs. Herein, we characterized CLECs using flow cytometry (FC) and skin organotypic cultures in direct comparison with skin keratinocytes (KCs). This was followed by wound healing study to compare the effects of CLEC application and the traditional use of human skin allografts (HSGs) in a porcine wound model. While CLECs were found to express all the epidermal cell markers probed, the major difference between CLECs and KCs lies in the level of expression (in FC analysis) as well as in the location of expression (of the epithelium in organotypic cultures) of some of the basal cell markers probed. On the pig wounds, CLEC application promoted accelerated healing with no adverse reaction compared to HSG use. Though CLECs, like HSGs, elicited high levels of local and systemic immune responses in the animals during the first week, these effects were tapered off more quickly in the CLEC-treated group. Overall, the in vivo porcine data point to the potential of CLECs as a non-native and safe source of cells to treat cutaneous wounds.

Spatial transcriptomics has been emerging as a powerful technique for resolving gene expression profiles while retaining tissue spatial information. These spatially resolved transcriptomics make it feasible to examine the complex multicellular systems of different microenvironments. To answer scientific questions with spatial transcriptomics and expand our understanding of how cell types and states are regulated by microenvironment, the first step is to identify cell clusters by integrating the available spatial information. Here, we introduce SC-MEB, an empirical Bayes approach for spatial clustering analysis using a hidden Markov random field. We have also derived an efficient expectation-maximization algorithm based on an iterative conditional mode for SC-MEB. In contrast to BayesSpace, a recently developed method, SC-MEB is not only computationally efficient and scalable to large sample sizes but is also capable of choosing the smoothness parameter and the number of clusters. We performed comprehensive simulation studies to demonstrate the superiority of SC-MEB over some existing methods. We applied SC-MEB to analyze the spatial transcriptome of human dorsolateral prefrontal cortex tissues and mouse hypothalamic preoptic region. Our analysis results showed that SC-MEB can achieve a similar or better clustering performance to BayesSpace, which uses the true number of clusters and a fixed smoothness parameter. Moreover, SC-MEB is scalable to large ‘sample sizes’. We then employed SC-MEB to analyze a colon dataset from a patient with colorectal cancer (CRC) and COVID-19, and further performed differential expression analysis to identify signature genes related to the clustering results. The heatmap of identified signature genes showed that the clusters identified using SC-MEB were more separable than those obtained with BayesSpace. Using pathway analysis, we identified three immune-related clusters, and in a further comparison, found the mean expression of COVID-19 signature genes was greater in immune than non-immune regions of colon tissue. SC-MEB provides a valuable computational tool for investigating the structural organizations of tissues from spatial transcriptomic data.

BackgroundExamining Hematoxylin & Eosin (H&E) images using brightfield microscopes is the gold standard of pathological diagnosis as it is an inexpensive method and provides basic information of tumors and other nuclei. Complementary to H&E-stained images, Immunohistochemical (IHC) images are crucial in identifying tumor subtypes and efficacy of treatment response. Other newer technologies such as Multiplex Immunofluorescence (mIF) in particular, identifies cells such as tumor infiltrating lymphocytes (TILs) which can be augmented via immunotherapy, an evolving form of cancer treatment. Immunotherapy helps in the manipulation of the host immune response and overcome limitations like the PD-1 (Programmed Cell Death-1) receptor induced restrictions on TIL production. If the same biopsy specimen is used for inspection, the higher order features in H&E images can be used to obtain information usually found in mIF images using Convolutional Neural Networks (CNNs), widely used in object detection and image segmentation tasks.MethodsAs shown in (figure 1), firstly, a novel optical flow-based image registration paradigm is prepared to co-register H&E and mIF image pairs, aided by adaptive color thresholding and automated color clustering. Secondly, generative adversarial networks (GANs) are adapted to predict TIL (CD3, CD45) regions. For this purpose, a unique dataset is ideated and used in which a given single channel mIF image, e.g., a CD3 channel mIF image is superimposed on the corresponding H&E image. Primarily, the Pix2Pix GAN model is used to predict CD3 and/or CD45 regions.ResultsThe intensity-based image registration workflow is fast and fully compatible with the given dataset, with an increase in evaluation metric scores after alignment (table 1). Furthermore, this study would be the first implementation of optical flow as the registration algorithm for pathological images. Next, the use of the special dataset not only reduces penalization during the training of the Pix2Pix model, but also helped in gaining repeatable results with high scores in metrics like structural similarity index measure and peak-signal to noise ratio, with minimal effects on location accuracy (table 2 and table 3).ConclusionsThis multi-modal pathological image transformation study could potentially reduce dependence on mIF and IHC images for TILs scoring, reducing the amount of tissue and cost needed for examination, as its information is derived directly from inexpensive H&E images automatically – ultimately develop into a pathologist-assisted tool for TILs scoring. This would be highly beneficial in facilities where resources are relatively limited.Ethics ApprovalThe Agency of Science, Technology and Research, Singapore, provided approval for the use of control tissue materials in this study IRB: 2020 112Abstract 818 Figure 1Proposed workflowAbstract 818 Table 1Image registration metricsAbstract 818 Table 2CD3 negative regions examplesAbstract 818 Table 3CD3 positive regions examples

BackgroundImmune check-point blockade (ICB) is one of the emerging therapeutic options for advanced hepatocellular carcinoma (HCC). However, low response rates amongst patients necessitates the development of robust predictive biomarkers that identify patients who likely benefit from ICB. Previously our group found that immunohistochemical scoring of CD38 in the tumour microenvironment predicts responsiveness to anti-PD-1/anti-PD-L1 immunotherapy in HCC.1 Recently BMS 4-gene inflammatory signature, comprising the 4 genes CD8, PD-L1, LAG-3 and STAT1, has been shown to be associated with better overall response to immunotherapy in various cancer types.2–4 In the present study, we examined the relationship between tissue expression of BMS 4-gene inflammatory signature and the responsiveness of HCC to immunotherapy, and whether BMS 4-gene inflammatory signature increases the predictive power of CD38.MethodsHCC tissue samples from 124 Asian patients that underwent conventional treatment and from 49 Asian patients that underwent ICB were analysed for CD8, PD-L1, LAG-3, STAT1, CD38 and CD68 tissue expression using immunohistochemistry and multiplex immunohistochemistry, followed by survival and statistical analysis.ResultsSurvival analysis of the 124 samples showed that high LAG-3 tissue expression was associated with shorter progression-free survival (PFS). On the other hand, immunohistochemical analyses on the 49 patient samples treated with ICB revealed that high LAG-3 density and high total LAG-3+CD8+ T cell proportion were associated with improved response to ICB (figure 1). However, CD8, PD-L1 and STAT1 levels did not significantly correlate with improved survival. The addition of total LAG-3+ cell proportion to total CD38+ cell proportion significantly increased the predictive value for both PFS (DeltaLRChi2=9.97; P=0.0016; table 1) and overall survival (OS) (DeltaLRChi2=8.84; P=0.0021; table 1), compared with total CD38+ cell proportion alone. Similarly findings were obtained after adding total LAG-3+CD8+ cell proportion to total CD38+ cell proportion (PFS: DeltaLRChi2=7.21; P=0.0072; OS: DeltaLRChi2=8.06; P=0.0045; table 1), compared with total CD38+ cell proportion alone. Lastly, when the total LAG-3+CD8+ cell proportion was added to total CD38+ and CD38+CD68+ cell proportion, the predictive value of the biomarker was significantly increased (PFS: DeltaLRChi2=6.10; P=0.0136; OS: DeltaLRChi2=6.18; P=0.0129; table 1). Ongoing works include further validation of the findings in various cohorts, and correlating with clinical outcome of the patients.Abstract 89 Table 1Log-likelihood of models with added predictive termsAbstract 89 Figure 1HCC patients‘ response to ICB in relation to LAG-3 density. (A) Kaplan-Meier curve showing the association between a high LAG-3 density and improved overall survival after treatment with ICB. (B) Kaplan-Meier curve showing the association between a high total LAG-3+CD8+ T cell proportion and improved overall survival after treatment with ICB. (C) Kaplan-Meier curve showing the association between a high LAG-3 density and improved progression-free survival after treatment with ICB. (D) Kaplan-Meier curve showing the association between a high total LAG-3+CD8+ T cell proportion and improved progression-free survival after treatment with ICB.ConclusionsHigh LAG-3 expression on tissue-infiltrating immune cells predicted greater response to ICB. LAG-3+ and LAG3+CD8+ cell proportion added predictive value to CD38+ cells for predicting survival outcome in immunotherapy-treated HCC. LAG-3 may be used in conjunction with CD38 to predict responsiveness to ICB in HCC.ReferencesNg HHM, Lee RY, Goh S, et al. Immunohistochemical scoring of CD38 in the tumor microenvironment predicts responsiveness to anti-PD-1/PD-L1 immunotherapy in hepatocellular carcinoma. J Immunother Cancer 2020;8.Hodi FS, Wolchok JD, Schadendorf D, et al. Abstract CT037: Genomic analyses and immunotherapy in advanced melanoma. AACR 2019.Lei M, Siemers NO, Pandya D, et al. Analyses of PD-L1 and Inflammatory Gene Expression Association with Efficacy of Nivolumab ± Ipilimumab in Gastric Cancer/Gastroesophageal Junction Cancer. Clinical Cancer Research 2021;27:3926–35.Sangro B, Melero I, Wadhawan S, et al. Association of inflammatory biomarkers with clinical outcomes in nivolumab-treated patients with advanced hepatocellular carcinoma. J Hepatol 2020.Ethics ApprovalThis study was approved by the Centralised Institutional Review Board of SingHealth (CIRB ref: 2009/907/B).ConsentWritten 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.

Immune evasion is key to cancer initiation and later at metastasis, but its dynamics at intermediate stages, where potential therapeutic interventions could be applied, is undefined. Here we show, using multi-dimensional analyses of resected tumours, their adjacent non-tumour tissues and peripheral blood, that extensive immune remodelling takes place in patients with stage I to III hepatocellular carcinoma (HCC). We demonstrate the depletion of anti-tumoural immune subsets and accumulation of immunosuppressive or exhausted subsets along with reduced tumour infiltration of CD8 T cells peaking at stage II tumours. Corresponding transcriptomic modification occur in the genes related to antigen presentation, immune responses, and chemotaxis. The progressive immune evasion is validated in a murine model of HCC. Our results show evidence of ongoing tumour-immune co-evolution during HCC progression and offer insights into potential interventions to reverse, prevent or limit the progression of the disease.

Cancer is the leading cause of death worldwide. Unfortunately, efforts to understand this disease are confounded by the complex, heterogenous tumor microenvironment (TME). Better understanding of the TME could lead to novel diagnostic, prognostic, and therapeutic discoveries. One way to achieve this involves in vitro tumor models that recapitulate the in vivo TME composition and spatial arrangement. Here, we review the potential of harnessing in vitro tumor models and artificial intelligence to delineate the TME. This includes (i) identification of novel features, (ii) investigation of higher-order relationships, and (iii) analysis and interpretation of multiomics data in a (iv) holistic, objective, reproducible, and efficient manner, which surpasses previous methods of TME analysis. We also discuss limitations of this approach, namely inadequate datasets, indeterminate biological correlations, ethical concerns, and logistical constraints; finally, we speculate on future avenues of research that could overcome these limitations, ultimately translating to improved clinical outcomes.

Angiosarcomas are a rare subtype of soft-tissue sarcomas which exhibit aggressive clinical phenotypes with limited treatment options and poor outcomes. In this study, we investigated the clinical relevance of the peripheral blood neutrophil-to-lymphocyte ratio (NLR) as a marker of systemic immune response, as well as its correlation with intra-tumoral immune profiles in a subgroup of cases (n = 35) using the NanoString PanCancer IO360 panel and multiplex immunohistochemistry. In the overall cohort (n = 150), angiosarcomas of the head and neck (AS-HN) comprised most cases (58.7%) and median overall survival (OS) was 1.1 year. NLR, classified as high in 78 of 112 (70%) evaluable patients, was independently correlated with worse OS (HR 1.84, 95%CI 1.18–2.87, p = 0.0073). Peripheral blood NLR was positively correlated with intra-tumoral NLR (tNLR) (Spearman’s rho 0.450, p = 0.0067). Visualization of tumor-infiltrating immune cells confirmed that tNLR scores correlated directly with both neutrophil (CD15+ cells, rho 0.398, p = 0.0198) and macrophage (CD68+ cells, rho 0.515, p = 0.0018) cell counts. Interestingly, tNLR correlated positively with oncogenic pathway scores including angiogenesis, matrix remodeling and metastasis, and cytokine and chemokine signaling, as well as myeloid compartment scores (all p

Proposed short titleY90-Resin Microspheres Radioembolization Followed by Nivolumab in Advanced Hepatocellular CarcinomaBackground : Nivolumab (N) and Y90-resin microspheres radioembolization (Y90-RE) aretherapeutic options in advanced hepatocellular carcinoma (aHCC). Emerging evidence suggests synergy between radiotherapy and immune checkpoint inhibitors. Methods : Eligible Child-Pugh A aHCC patients were treated with Y90-RE followed by N 240mg, 21 days after Y90-RE and every 2 weeks thereafter. Pre- and on-treatment tumor biopsies were obtained. Primary end-point was overall response rate (ORR) (RECIST v1·1), defined as the composite overall response observed for lesions both within and outside Y90-RE field. Secondary end points included progression free survival (PFS), overall survival (OS), and safety. This study is registered with ClinicalTrials.gov, NCT03033446 .Findings : Forty patients were enrolled, 36 received Y90-RE followed by N. At baseline: 61·1% had hepatitis B; 66·7% BCLC stage C; 50·0% had AFP > 400ng/mL; median number of liver lesions was 5 (range 1- >20); median size of largest liver lesion was 78·5 mm (range 14-177mm); 38·9% had prior TACE/RFA/MWA; and 12·5% had prior systemic therapy. ORR was 30·6% (16·4% to 48·1%). ORR was 43·5% in patients with no extra-hepatic spread (EHS) (n=23). 81% of target lesions within Y90-RE field regressed. Median PFS and OS were 5·6 months (95% CI 2·1 to 8·8 months) and 16.9 months (95% CI 8·1 to 27·6 months). Treatment was well tolerated with only 13·8% experiencing grade (G) 3/4 treatment related adverse events (TRAEs). Immune activation predicted response to Y90-RE followed by N. Interpretation : Y90-RE followed by N resulted in an encouraging ORR of 30·6% in aHCC and of 43·5% in subjects with no EHS. 81% of target lesions within Y90-RE field regressed suggesting synergy. Importantly, this combination is safe and tolerable with low G 3/4 TRAEs of 13·8%. Trial Registration: NCT number: NCT03033446 Funding: Funding for this study was acquired from National Medical Research Council Singapore (NMRC/CIRG/1454/2016), Bristol-Myers Squibb (BMS), and SIRTEX Declaration of Interest: David Tai All support for the present manuscript (e.g., funding, provision of study materials, medical writing, article processing charges, etc.): BMS, SIRTEX, NMRC Singapore (CIRG/1470/2017) Payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events: IPSEN, Eisai, BMS Consulting fees: Novartis, BMS, MSD Choo Su Pin Payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events: Roche, BMS, Ipsen, Lilly, AZ, Roche. Consulting fees: BMS, Roche, Ipsen, Servier, Eisai, AstraZeneca. Leadership or fiduciary role in other board, society, committee or advocacy group, paid or unpaid: MOH Medishield Life Cancer Drug committee Stock or stock options: BMS David Ng All support for the present manuscript (e.g., funding, provision of study materials, medical writing, article processing charges, etc.): SIRTEX Payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events: SIRTEX Joycelyn Lee Payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events: BMS, IPSEN, Bayer Research Funding: Bayer Pierce K.H. Chow Grants or contracts from any entity: Sirtex Medical, Ipsen, IQVIA, New B Innovation, Perspectum, AMiLi, MiRXES, Genentech, Engine Biosciences. Payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events: Sirtex Medical, Ipsen, Oncosil, Bayer, Roche, New B Innovation, MSD, BTG PLC, Eisai, Abbott, AZ, IQVIA, Genentech, Worrell Guerbet, LEK Consulting, COR2ED. Leadership or fiduciary role in other board, society, committee or advocacy group, paid or unpaid: AVATAMED Stock or stock options: AVATAMED Too Chow Wei Payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events: SIRTEX Consulting fees: SIRTEX Ethical Approval: All patients provided written informed consent and the institutional review board committee approved the protocol (Singhealth IRB Ref No. 2016/2613). The study was done in accordance with the Declaration of Helsinki and Good Clinical Practice.

In the context of hepatitis B virus (HBV)-associated hepatocellular carcinoma (HCC), despite a range of possibilities, the antigen specificities of tumor-infiltrating T cells and their relevance to control of is largely unknown. Using highly multiplexed peptide-MHC tetramer staining of unexpanded cells from blood, liver and tumor tissues from 46 HCC patients, we detected 91 different CD8 T cell populations specific for epitopes derived from HBV, tumor-associated and neoantigens (NeoAg), as well as disease-unrelated antigens. Parallel high-dimensional analysis delineated distinct tissue-resident memory T cells (TRM) populations among other highly diverse lymphocytes profiles observed in these compartments. Intratumoral and intrahepatic HBV-specific T cells were particularly enriched for three TRM phenotypes and the majority expressed relatively low levels of PD-1 receptor and TOX gene, inconsistent with reported terminal exhausted T cells (TEX) despite being clonally expanded within tumors. High frequencies of terminal TEX in these tumors was uncommon, whereas patients who had detectable and less exhausted tumor-infiltrating HBV- or NeoAg-specific CD8 TRM had superior long-term relapse-free survival. Thus, non-terminally-exhausted tumor-resident HBV-specific CD8 TRM show hallmarks of active involvement and effective antitumor response, implying that these cells could be harnessed for therapeutic purposes.

Summary Hepatocellular carcinoma (HCC) often develops following chronic hepatitis B virus (HBV) infection and responds poorly to immune checkpoint blockade. Here, we examined the antigen specificities of HCC-infiltrating T cells and their relevance to tumor control. Using highly multiplexed peptide-MHC tetramer staining of unexpanded cells from blood, liver, and tumor tissues from 46 HCC patients, we detected 91 different antigen-specific CD8+ T cell populations targeting HBV, neoantigen, tumor-associated, and disease-unrelated antigens. Parallel high-dimensional analysis delineated five distinct antigen-specific tissue-resident memory T (Trm) cell populations. Intratumoral and intrahepatic HBV-specific T cells were enriched for two Trm cell subsets that were PD-1loTOXlo, despite being clonally expanded. High frequencies of intratumoral terminally exhausted T cells were uncommon. Patients with tumor-infiltrating HBV-specific CD8+ Trm cells exhibited longer-term relapse-free survival. Thus, non-terminally exhausted HBV-specific CD8+ Trm cells show hallmarks of active involvement and effective antitumor response, implying that these cells could be harnessed for therapeutic purposes.

Residual SARS-CoV-2 RNA has been detected in stool samples and gastrointestinal tissues during the convalescence phase of COVID-19 infection. This raises concern for persistence of SARS-CoV-2 virus particles and faecal-oral transmissibility in recovered COVID-19 patients. Using multiplex immunohistochemistry, we unexpectedly detected SARS-CoV-2 viral antigens in intestinal and liver tissues, in surgical samples obtained from two patients who recovered from COVID-19. We further validated the presence of virus by RT-PCR and flow cytometry to detect SARS-CoV-2-specific immunity in the tissues. These findings might have important implications in terms of disease management and public health policy regarding transmission of COVID-19 via faecal-oral and iatrogenic routes during the convalescence phase.

Growing evidence supports the importance of understanding tumor-immune spatial relationship in the tumor microenvironment in order to achieve precision cancer therapy. However, existing methods, based on oversimplistic cell-to-cell proximity, are largely confounded by immune cell density and are ineffective in capturing tumor-immune spatial patterns. Here we developed a novel computational algorithm, termed Tumor-Immune Partitioning and Clustering (TIPC), to offer an effective solution for spatially informed tumor subtyping. Our method could measure the extent of immune cell partitioning between tumor epithelial and stromal areas as well as the degree of immune cell clustering. Using a U.S. nation-wide colorectal cancer database, we showed that TIPC could determine tumor subtypes with unique tumor-immune spatial patterns that were significantly associated with patient survival and key tumor molecular features. We also demonstrated that TIPC was robust to parameter settings and readily applicable to different immune cell types. The capability of TIPC in delineating clinically relevant patient subtypes that encapsulate tumor-immune spatial relationship, immune density, and tumor morphology is expected to shed light on underlying immune mechanisms. Hence, TIPC can be a useful bioinformatics tool for effective characterization of the spatial composition of the tumor-immune microenvironment to inform precision immunotherapy.

Background Stromal and collagen biology has a significant impact on tumorigenesis and metastasis. Collagen is a major structural extracellular matrix component in breast cancer, but its role in cancer progression is the subject of historical debate. Collagen may represent a protective layer that prevents cancer cell migration, while increased stromal collagen has been demonstrated to facilitate breast cancer metastasis. Methods Stromal remodeling is characterized by collagen fiber restructuring and realignment in stromal and tumoral areas. The patients in our study were diagnosed with triple-negative breast cancer in Singapore General Hospital from 2003 to 2015. We designed novel image processing and quantification pipelines to profile collagen structures using numerical imaging parameters. Our solution differentiated the collagen into two distinct modes: aggregated thick collagen (ATC) and dispersed thin collagen (DTC). Results Extracted parameters were significantly associated with bigger tumor size and DCIS association. Of numerical parameters, ATC collagen fiber density (CFD) and DTC collagen fiber length (CFL) were of significant prognostic value for disease-free survival and overall survival for the TNBC patient cohort. Using these two parameters, we built a predictive model to stratify the patients into four groups. Conclusions Our study provides a novel insight for the quantitation of collagen in the tumor microenvironment and will help predict clinical outcomes for TNBC patients. The identified collagen parameters, ATC CFD and DTC CFL, represent a new direction for clinical prognosis and precision medicine. We also compared our result with benign samples and DICS samples to get novel insight about the TNBC heterogeneity. The improved understanding of collagen compartment of TNBC may provide insights into novel targets for better patient stratification and treatment.

Angiosarcomas are rare, clinically aggressive tumors with limited treatment options and a dismal prognosis. We analyzed angiosarcomas from 68 patients, integrating information from multiomic sequencing, NanoString immuno-oncology profiling, and multiplex immunohistochemistry and immunofluorescence for tumor-infiltrating immune cells. Through whole-genome sequencing (n = 18), 50% of the cutaneous head and neck angiosarcomas exhibited higher tumor mutation burden (TMB) and UV mutational signatures; others were mutationally quiet and non–UV driven. NanoString profiling revealed 3 distinct patient clusters represented by lack (clusters 1 and 2) or enrichment (cluster 3) of immune-related signaling and immune cells. Neutrophils (CD15(+)), macrophages (CD68(+)), cytotoxic T cells (CD8(+)), Tregs (FOXP3(+)), and PD-L1(+) cells were enriched in cluster 3 relative to clusters 2 and 1. Likewise, tumor inflammation signature (TIS) scores were highest in cluster 3 (7.54 vs. 6.71 vs. 5.75, respectively; P < 0.0001). Head and neck angiosarcomas were predominant in clusters 1 and 3, providing the rationale for checkpoint immunotherapy, especially in the latter subgroup with both high TMB and TIS scores. Cluster 2 was enriched for secondary angiosarcomas and exhibited higher expression of DNMT1, BRD3/4, MYC, HRAS, and PDGFRB, in keeping with the upregulation of epigenetic and oncogenic signaling pathways amenable to targeted therapies. Molecular and immunological dissection of angiosarcomas may provide insights into opportunities for precision medicine.

BackgroundRecent advances in multiplex immunohistochemistry/immunofluorescence (mIHC/IF) technologies have enabled simultaneous measurements of large numbers of markers on the same tissue sections, and more comprehensive views of the cellular compositions and immune responses of the tumor microenvironment. However, the reproducibility and interpretation of the complex staining patterns and analysis results obtained from these markers remain major barriers to more general adoptions of these technologies. Here, we report the availability of an online public portal, “ImmunoAtlas”, which would enable researchers/clinicians to present or share their published mIHC/IF images or results; international workgroups to create and share standard marker panels or assay guidelines; end users to validate antibodies or protocols; or computational scientists to benchmark different analysis methods on standard reference images (figure 1).MethodsImmunoAtlas is based on a HistoPathological image management and Analysis (HPA) software platform developed by us, and hosted in the data center of Bioinformatics Institute. The platform uses the cellXpress software,1 which is written in C++ and supports parallel processing, to efficiently process and manage large numbers of huge mIHC/IF or brightfield images. The web interface of ImmunoAtlas is also completely developed by us in PHP and JavaScript to address the specific needs and requirements in managing these images.ResultsImmunoAtlas is a user-friendly online portal for sharing, visualizing, and referencing original tissue images and analysis results (https://ImmunoAtlas.org). We have completed the first phase of development of the portal. Users can now perform image uploading, annotation, publishing, sharing, and viewing with standard web browsers on desktop computers or mobile devices/phones (figure 2). The portal supports image files from common microscopes and slide scanners, and can process mIHC/IF or brightfield images from selected areas, tissues microarrays, or whole slides. It can handle up to 1000 multiplexed markers, and whole-slide images that are >20GB/image. Several internal and external immuno-oncology studies have deposited and shared their images via ImmunoAtlas. They include a study of multiplexed PD-L1 markers in breast cancers2; the development of a panel of 56 highly-multiplexed markers for cutaneous T cell lymphoma3; and a study of CD38 scoring in hepatocellular carcinoma.4ConclusionsImmunoAtlas promotes open science and collaborations that can accelerate the adoptions of mIHC/IF technologies in immuno-oncology. The next phase of development will focus on adding image searching and comparison functions to the portal. The community is welcome to use and share their images and analysis results via the portal.ReferencesLaksameethanasan D, Tan RZ, Toh GW-L, et al. cellXpress: a fast and user-friendly software platform for profiling cellular phenotypes. BMC Bioinformatics 2013;14:S4. doi:10.1186/1471-2105-14-S16-S4.Yeong J, Tan T, Chow ZL, et al. Multiplex immunohistochemistry/immunofluorescence (mIHC/IF) for PD-L1 testing in triple-negative breast cancer: a translational assay compared with conventional IHC. J Clin Pathol 2020;73:557–62. doi:10.1136/jclinpath-2019-206252.Phillips D, Schürch CM, Khodadoust MS, et al. Highly multiplexed phenotyping of immunoregulatory proteins in the tumor microenvironment by CODEX tissue imaging. Front Immunol 2021;0. doi:10.3389/fimmu.2021.687673.Ng HHM, Lee RY, Goh S, et al. Immunohistochemical scoring of CD38 in the tumor microenvironment predicts responsiveness to anti-PD-1/PD-L1 immunotherapy in hepatocellular carcinoma. J Immunother Cancer 2020;8:e000987. doi:10.1136/jitc-2020-000987Abstract 627 Figure 1Key target users and applications of ImmunoAtlasAbstract 627 Figure 2ImmunoAtlas' web interface for sharing and visualizing mIHC

BackgroundTriple-negative breast cancers (TNBCs) are defined by their lack of oestrogen receptor, progesterone receptor and epidermal growth factor receptor 2. Although heterogeneous, the majority are aggressive and treatment options are limited. Caveolin acts as tumour suppressor or promoter depending on the cancer type.AimIn this study, we aimed to determine if the expression levels of the candidate biomarker caveolin-1 on stromal or tumour cells were associated with clinicopathological parameters and disease outcomes in TNBCs from an ethnically diverse cohort of Asian women.MethodsTumour specimens from 699 women with TNBC were subjected to immunohistochemical analysis of the frequency and intensity of caveolin-1 expression in tumour and stromal cells. A subset of 141 tumour samples also underwent Nanostring measurement ofCAV1mRNA. Results were correlated with clinicopathological parameters and disease outcomes.ResultsExpression of caveolin-1 in stromal cells was observed in 14.4% of TNBC cases. TNBCs of the basal-like phenotype (85% of samples) were significantly more likely to exhibit stromal cell caveolin-1 expression (p=0.028), as were those with a trabecular growth pattern (p=0.007). Lack of stromal caveolin-1 expression in both TNBCs and those with the basal-like phenotype was significantly associated with worse overall survival (p=0.009 and p=0.026, respectively): accordingly, increasing mRNA levels ofCAV1in TNBC samples predicted better overall survival. Caveolin-1 expression on TNBC tumour cells was not associated with clinical outcome.ConclusionStromal, but not tumoural, caveolin-1 expression is significantly associated with survival in Asian women with TNBC.

AimThe International Society of Urological Pathology made recommendations for the use of Grade Groups (GG) originally described by Epstein and colleagues over Gleason score (GS) alone in 2014, which was subsequently adopted by the WHO classification in 2016. The majority of studies validating this revision have been in Caucasian populations. We therefore asked whether the new GG system was retrospectively associated with biochemical disease-free survival in a mixed-ethnicity cohort of Asian men.MethodsA total of 680 radical prostatectomies (RPs) from 2005 to 2014 were included. GS from initial biopsy and RP were compared and used to allocate cases to GG, defined as: 1 (GS≤6); 2 (GS 3+4=7); 3 (GS 4+3=7); 4 (GS 4+4=8/5+3=8/3+5=8) and 5 (GS 9–10). Biochemical recurrence was defined as two consecutive post-RP prostate-specific antigen (PSA) levels of >0.2 ng/mL after post-RP PSA reaching the nadir of ResultsOur data showed that Kaplan–Meier analysis revealed significant differences in biochemical recurrence within Gleason GG based on either biopsy or prostatectomy scoring. Multivariate analysis further confirmed that a higher GG was significantly associated with risk of biochemical recurrence. This GG system had a higher prognostic discrimination for both initial biopsy and RP than GS.ConclusionsOur study validates the use of the revised and updated GG system in a mixed-ethnicity population of Asian men. Higher GG was significantly associated with increased risk of biochemical recurrence. We therefore recommend its use to inform clinical management for patients with prostate cancer.