Joe Yeong

Figure S1: Quality-control parameters and sensitivity analyses of CLDN18.2 microenvironmental and pathway changes Figure S2: Additional sensitivity survival analyses of the YCC cohort and CheckMate 649 trial Figure S3: Features of cellular neighbourhoods and correlation with progression-free survival Figure S4: Supplementary analyses to digital spatial profiling Figure S5: B/plasma cell enrichment scores across the tumor-stroma interface

Supplementary Tables 1-4 from Spatial Organization of Tumor-Infiltrating B Cells Informs Immune Checkpoint Inhibitor Response in Claudin 18.2–Expressing Gastric Cancer

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Durable remissions after anti-CD19 chimeric antigen receptor T cell (CAR-T) therapy in relapsed/refractory B-lineage acute lymphoblastic leukaemia are limited by antigen escape and T-cell dysfunction. The tandem CAR22-19/LTG2737 construct links human-derived anti-CD22 and anti-CD19 scFvs to CD8 hinge/transmembrane, 4-1BB, and CD3ζ domains. In a multicentre phase I/II trial, all patients (n=11; 7 children, 4 adults) achieved complete remission by Day 28 (91% minimal residual disease-negative). At a 34-month median follow-up, median overall survival (OS) and leukaemia-free survival (LFS) were not reached. The 12-month OS was 82% (95%CI: 45%-95%) and LFS was 64% (95%CI: 30%-85%) without consolidative transplantation. Immune-effector cell-associated toxicities included cytokine release syndrome, haematotoxicity, and haemophagocytic lymphohistiocytosis-like syndrome. De novo CD19 escape caused one relapse. Exploratory multi-omic profiling linked durable response to higher CD22 antigen density on blasts; pre-infusion CD4 CAR-T cells expressing IL7Rα, LEF1, BACH2, and TCF7 but lower FOXP3; post-infusion NK-like effector CAR-T expansion; and central-memory CAR-T pool maintenance.

Background: Triple-negative breast cancer (TNBC) exhibits aggressive biology and heterogeneous immune infiltration. Lysine-specific demethylase 1 (LSD1/KDM1A) is an epigenetic regulator implicated in oncogenic transcriptional programs, but its role in immune exclusion remains incompletely defined. Methods: LSD1 expression was evaluated by immunohistochemistry in TNBC specimens and correlated with survival. Functional effects of LSD1 depletion or pharmacological inhibition were assessed in TNBC cell lines and patient-derived xenograft organoids (PDXOs). Transcriptomic, ChIP-seq, multiplex immunofluorescence, and GeoMX digital spatial profiling analyses were integrated to characterize LSD1-associated transcriptional, chromatin, and immune programs. PBMC-PDXO co-cultures evaluated the effects of LSD1 inhibition on tumor growth and immune cell infiltration. Results: High LSD1 expression was associated with inferior overall survival, hypoxia-associated programs and suppressed immune pathways. LSD1-high tumors exhibited reduced infiltration of T cells, B cells, NKT-like cells, and macrophages. Spatial profiling revealed suppressed innate immune responses and type I interferon signaling within B-cell and T-cell compartments, respectively. ChIP-seq demonstrated preferential LSD1 occupancy at AP-1 motif-enriched regions, while co-immunoprecipitation supported association with AP-1 complexes. Integration of LSD1 chromatin occupancy sites with transcriptomics data identified SPPL2A and NCOA3 as candidate LSD1-regulated genes associated with interferon-γ response pathways. LSD1 depletion increased SPPL2A, NCOA3, MHC-I and PD-L1 expression. LSD1 inhibition reduced PDXO growth and increased immune cell infiltration. Conclusions: LSD1 is associated with a poor clinical outcome and immune exclusion in TNBC. These findings support a role for LSD1 in AP-1-associated chromatin regulation and interferon-γ-related transcriptional response; they warrant further investigation into LSD1 inhibition as a therapeutic strategy for immune-cold TNBCs.

Persistent inflammation and tissue injury may contribute to post-acute COVID-19 syndrome (PACS). However, direct tissue evidence from mildly-infected individuals sampled long after recovery remains exceptionally limited. Here, we performed post-mortem bulk RNA-seq and GeoMx digital spatial profiling of lung, heart, and brain tissues from four individuals who recovered from mild COVID-19 more than 250 days before death from unrelated causes. Samples were collected during the early phase of the national vaccination program, before widespread vaccine uptake and recurrent infection, providing a rare reference cohort for defining tissue responses to SARS-CoV-2 in the absence of major confounding from vaccination and/or reinfection; such a cohort can no longer be prospectively assembled. We observed residual SARS-CoV-2 nucleocapsid antigen within tissues and revealed organ-specific immune alterations. Lung and heart tissues exhibited a coordinated, self-sustaining inflammatory response, whereas brain tissue showed vascular dysfunction and altered neuroimmune homeostasis. These findings showcase the distinct tissue responses following mild infection and provide a spatially resolved view of sub-clinical long-term tissue sequelae. Collectively, our data establish a unique baseline for persistent viral antigen and tissue-specific immune dysregulation underlying PACS.

Genomic landscape of neoadjuvant gefitinib-treated EGFR-mutated NSCLC tumors. A, Oncoprint of EGFR alterations and reported EGFR TKI resistance genes within the neoadjuvant gefitinib patient cohort. B, Estimated cancer cell proportion distributions of different NSCLC cohorts. Tumors from the TKI-resistant group comprises patients from the study by Chua and colleagues (24). C, Cancer cell proportions for a subset of the treatment-naïve and neoadjuvant gefitinib cohort, selected at random for downstream purity-matched analyses. D, Distribution of the number of cancer subclones estimated in patient-level analysis between purity-matched treatment-naïve and neoadjuvant gefitinib tumors at 50× and 250× depth WES respectively. E, Inferred phylogenetic structures of treatment-naïve (A111) and neoadjuvant gefitinib (P001) patients with NSCLC with the highest number of cancer subclones within their respective cohorts. F, Inferred phylogenetic structures of treatment-naïve (A161) and neoadjuvant gefitinib (P009) patients with NSCLC with the lowest number of cancer subclones within their respective cohorts. Only known lung adenocarcinoma (LUAD) and TKI-resistant (n = 96) genes are annotated for each clone on the tree, and the mutation burden of a given clone is represented by the relative distances between nodes.

Clinical assessments of response and outcomes to neoadjuvant gefitinib-treated EGFR-mutated NSCLC. A, Consort diagram and study workflow. Study includes the baseline PET/CT scan and treatment with gefitinib 250 mg daily for a minimum of 4 weeks, followed by posttreatment PET/CT scan and surgical resection. Multiregion WES and RNA-seq were then performed on tumor sectors for multi-omics analysis. B, Waterfall plot. Dotted line indicates PR or partial metabolic response (PMR; <30% change in baseline). C, Pathologic assessment of response. Dotted line indicates the threshold for a MPR (<10% viable tumor). D and E, Correlations of clinical measures of response. D, CT response compared with pathologic response. E, PET response compared with pathologic response.

Transcriptomic analysis of neoadjuvant gefitinib-treated EGFR-mutated NSCLC tumors. A, Top 5 enriched mSigDB “hallmark” gene pathways found in neoadjuvant gefitinib or treatment-naïve tumors in GSEA. B, T-cell inflammation GEP scores between treatment-naïve and neoadjuvant gefitinib tumors. The horizontal line demarcates the GEP cutoff score (GEP = −0.318) as previously reported by Cristescu and colleagues (23). C, Heatmap summarizing the expression levels of key immune inflammatory genes within patient tumors, as well as their corresponding tumor classification into either immuneHot or immuneCold status. D, Heatmap of immune cell types estimated by CIBERSORTx ranked by the order and direction of significance (adjusted P value) between treatment-naïve vs. neoadjuvant gefitinib cohorts. E, Boxplots of selected CIBERSORTx cell-type proportions present within treatment-naïve vs. neoadjuvant gefitinib tumors.

Analysis of immune checkpoint and cytokine/chemokine responses in purity-matched neoadjuvant gefitinib EGFR-mutated NSCLC tumors. A and B, Boxplots of selected CIBERSORTx cell-type proportions present within purity-matched treatment-naïve vs. neoadjuvant gefitinib tumors. C, Gene expression comparison of immune checkpoint and cytokine/chemokine ligand–receptor pairs. D and E, Boxplot of gene expression levels comparing CD47–SIRPA and CD200–CD200R1 immune checkpoint pairs in treatment-naïve vs. neoadjuvant gefitinib tumors. F, Correlation of immune cell type and immune checkpoint gene expression with clinical response, including CT tumor shrinkage, SUVmax change, and pathologic response.