1512 Single-cell resolution spatial transcriptomics detection of pathogens followed by studying the immune milieu: using virus-associated cancers from different organs as paradigm

Background Tumor Immuno-MicroEnvironment (TIME) is characterized by a heterogeneous interplay of cellular and molecular components. For the TIME of cancers caused by virus infection, the comparison of immune cells close to and far from viral infection, crucial for understanding localized immune response and developing targeted therapies, has not been not possible to investigate until the advent of spatial transcriptomic techniques. Here, we proposed a methodology to localize viral infection sites using SpaTial Enhanced REsolution Omics-sequencing (Stereo-seq, figure 1)1 data of virus-associated cancers. We used Epstein-Barr virus (EBV)-associated Nasophayngeal Carcinoma (NPC)2 3 and human Hepatitis B Virus (HBV)-associated hepatocellular carcinoma (HCC)4 5 as two paradigmatic examples to show the robustness of this methodology. Methods We ran Stereo-seq experimental protocol separately for fresh-frozen NPC and LELC samples. In each run, we added one virus-free cancer fresh-frozen sample as control Given the low read depth per Nanoball, a grid of 100 x 100 Nanoballs (BIN100) were used as the unit of analysis to ensure that there is sufficient read depth (figure 1A). For each BIN100, we used Stereo-Seq Analysis Workflow (SAW) pipeline v5.5.2 to align its reads to human genome GRCh38.p13 for Seurat cell clustering and cell type annotation using Bioconductor packages EasyCellType and SingleR. We used STAR v2.7.10b to map reads unaligned from human genome to EBV-1 or HBV genome from NCBI RefSeq. Finally, we superimposed BIN100 with high viral reads onto SAW-registered ssDNA fluorescent-staining image. In addition, we performed Hematoxylin and Eosin (H&E) staining, and QuPath tissue annotation. Results The overlaid images of virus-positive BIN100s and ssDNA tissue-staining illustrated a clear contrast between virus-positive and virus-negative cancer samples (figures 2A, 3A). Most EBV1-positive BIN100s are in the invasive margin indicated by QuPath annotation of H&E staining (figure 2A-B), which is as expected. Most cells surrounding viral infection sites are B cell/plasma cell clusters 5,9,14 for NPC, and monocyte clusters 13,14,15 for HCC (figures 2,3). The clear separation of these clusters from other immune cell clusters illustrates that the distance to viral infection site significantly alters the gene expression profile of immune cells. Conclusions Our study proposes a powerful virus localization method to uncover the fine structure of TIME contributed by virus infection. In future, we will test this method with more NPC and HCC samples, and more virus-free cancer samples to validate its robustness. We will continue differential gene expression analysis for immune cell clusters with different distance to viral infection sites. References Chen A, Liao S, Cheng M, Ma K, Wu L, Lai Y, et al. Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays. Cell. 2022;185:1777–1792. Young L, Yap L, Murray P. Epstein-Barr virus: more than 50 years old and still providing surprises. Nat Rev Cancer. 2016;16:789–802. Png YT, Yang AZY, Lee MY, Chua MJM, Lim CM. The Role of NK Cells in EBV Infection and EBV-Associated NPC. Viruses. 2021 Feb 15;13(2):300. Chen CJ, Yang HI, Su J, Jen CL, You SL, Lu SN, Huang GT, Iloeje UH; REVEAL-HBV Study Group. Risk of hepatocellular carcinoma across a biological gradient of serum hepatitis B virus DNA level. JAMA. 2006 Jan 4;295(1):65–73. Liu Z, Jiang Y, Yuan H, Fang Q, Cai N, Suo C, Jin L, Zhang T, Chen X. The trends in incidence of primary liver cancer caused by specific etiologies: Results from the Global Burden of Disease Study 2016 and implications for liver cancer prevention. J Hepatol. 2019 Apr;70(4):674–683. Ethics Approval This study was approved by the Agency of Science, Technology and Research (A*STAR) Human Biomedical Research Office (A*STAR IRB: 2021-161, 2021-188, 2021-112). Consent De-identified patient data was used in our work. Samples were collected with consent from patients.