We previously demonstrated that the anti-CD33 antibody drug conjugate gemtuzumab ozogamicin (GO) binds CD33-expressing monocytic myeloid-derived suppressor cells (M-MDSCs), is internalized, and decreases those cells' viability. Treatment of MDSCs with GO restores T-cell proliferation in co-culture, overcomes M-MDSC suppression of CAR-T cell proliferation, and enhances target-cell killing. Gemtuzumab Ozogamicin Therapy in Hemophagocytic Lymphohistiocytosis or Macrophage Activation Syndrome (GOTHAM) is a phase 2 single-arm clinical trial for which patients were eligible if they had a diagnosis of solid cancer with radiological or clinical evidence of disease progression, or primary or secondary hemophagocytic lymphohistiocytosis, or macrophage activation syndrome disease relapsing or refractory to treatment at enrollment. An initial regimen of 3 mg/m2 GO on days 1, 8, and 15 was tested, adjusted to 21-d intervals: days 1, 22, and 43. The primary outcome was the impact of GO therapy on peripheral CD33+ myeloid cells. Using 2 schedules of GO, we could not convincingly demonstrate safe feasibility in patients with solid cancer, because of neutropenia. However, GO reproducibly and significantly reduced circulating MDSCs. Importantly, there is consistent preliminary evidence that, upon rebound, the monocyte population of CD33+ cells is replaced with nonsuppressive monocytes. These data support the phase 1b dose-escalation testing of GO up to 2 mg/m2 in combination with immune checkpoint blockade and other immunotherapies in patients with solid cancer to find a dose that depletes and repolarizes MDSCs without causing undue neutropenia, paving the way to use GO as an immune potentiator in this patient population. Trial registration: ISRCTN 89158144.

Neoadjuvant chemoimmunotherapy (chemo-IO) has fundamentally reshaped the treatment paradigm for resectable non-small cell lung cancer (NSCLC), challenging long-held surgical boundaries and redefining what constitutes “resectable” disease. Trials such as CheckMate-816, KEYNOTE-671, and AEGEAN have demonstrated that integrating immune checkpoint blockade with chemotherapy yields unprecedented rates of pathological response and event-free survival, positioning chemo-IO as the new global standard for stage IB–IIIA NSCLC. Yet these advances bring new complexities; how do we define resectability in an era of immunotherapeutic downstaging, and how should multidisciplinary teams adapt to evolving biology? Traditional radiological and anatomic criteria now sit alongside immune-mediated regression and circulating tumor DNA (ctDNA) kinetics as measures of treatment success. ctDNA clearance and pathological response serve as powerful surrogates for long-term survival, with ongoing studies such as MERMAID-1/2 exploring their potential to guide adjuvant therapy and spare overtreatment. The modern challenge lies in integrating these biomarkers into surgical decision-making and developing standardized, biology-informed resectability frameworks. Future progress will depend on close collaboration between surgeons, oncologists, and translational scientists to expand surgical candidacy safely and define the next generation of curative strategies in lung cancer.

In this report, we present a rare case of toxic epidermal necrolysis secondary to combination ICI therapy for pleural mesothelioma, which was successfully managed with ruxolitinib, highlighting a promising therapeutic avenue for severe ICI-induced dermatologic irAEs.

There are no current stratified medicine options for STK11-deficient NSCLC. STK11 loss mediates mTORC activation, GLUT1 up-regulation and increased glycolysis. This metabolic reprogramming might represent a therapeutic vulnerability targetable with mTORC1/2 inhibition. In arm B2 of the National Lung Matrix Trial 54 patients with NSCLC received vistusertib, of which 49 were STK11-deficient (30 with KRAS mutation (B2D), 19 without (B2S)). Objective response (OR) and durable clinical benefit (DCB) rates with 95% credible intervals (CrI) were estimated from posterior probability distributions generated using Bayesian beta-binomial conjugate analysis. In B2D, 2 per-protocol patients obtained OR (estimated true OR rate (95%CrI) 9.8% (2.4–24.3). Estimates of true DCB rate (95%CrI): B2D 24.4% (11.1–42.3), B2S 14.6% (3.6–34.7). Overall, vistusertib cannot be recommended in this context. Longitudinal ctDNA analysis demonstrates enrichment of SMARCA4 mutations post-treatment. In vitro studies show adaptive resistance to mTORC1/2 inhibition via AKT reactivation. (NCT02664935, ISRCTN38344105, EudraCT 2014-000814-73, 10 June 2015)

Expression of PD-1 and TIGIT ligands in the PDAC TME. A, Average expression profiles of TIGIT and PD-1 family receptors/ligands on all annotated cell subsets from scRNA-seq data first presented in Fig. 1. B, Representative confocal images of immunofluorescent staining for PD-1 and TIGIT ligands on tumor epithelium (EpCAM+), macrophages (CD68+), and stroma/fibroblasts (α-SMA+) using PDAC FFPE tissue (n = 10 patients). White arrows indicate examples of dual staining. Scale bars: 50 μm. C, Multiplex IHC staining of PD-1 and TIGIT ligands within ectopic lymphoid structures (scale bar: 100 μm; i). Digital representation of cell segmentation and localization of PD-L1+CD155+ cells and PD-1+TIGIT+ CD8+ T cells (ii). Direct engagement of a PD-1+TIGIT+ CD8+ T cell with a PD-L2+CD155+ cell within the T-cell area (scale bar: 10 μm; iii). Dashed line represents the border between the T- and B-cell areas. D, A 35-parameter CyTOF panel was used to determine the expression of PD-1 and/or TIGIT ligands on different myeloid-cell subsets in matched PBMC and TIL samples from patients with PDAC (n = 10). t-SNE plot shows PhenoGraph clusters of myeloid-enriched cell populations from combined PBMC and TIL (i), and cells stratified by sample type (ii). E, Heat map shows median expression level of key markers in each PhenoGraph cluster. F, t-SNE plots show the expression level of PD-1 and TIGIT ligands.

Characterization of CD8+ T-cell populations within the PDAC tumor microenvironment. A, Dot plot of the top markers expressed in each CD8+ T-cell cluster identified via Louvain clustering of scRNA-seq data (first presented in Fig. 1) from CD8+ T cells (i). UMAP embedding of CD8+ T cells from the 3 PDAC patient samples overlaid with Louvain cluster label (ii). B, CyTOF analysis of CD45+ cells from PDAC patient PBMC and TIL (n = 10), using data first used in Fig. 2B. t-SNE plots show PhenoGraph-clustered CD8+ T-cell populations in PBMC and TIL. C, Representative contour plot showing CD8+ TRM cells in PDAC TIL based on positive expression of CD69 and CD103, generated using the data in Fig. 2B (i). Box and whisker plot showing the proportion of CD8+ TRM cells in PBMC and TIL, generated using the data in Fig. 2B (ii). D, UMAP embedding, performed using scRNA-seq first presented in Fig. 1, overlaid with module score quintiles and module score distributions by CD8 T-cell cluster from scoring a core module of genes overexpressed in TRM T-cells (i). Differential expression analysis distinguishing TRM-like cells (clusters CD8_1 and CD8_6) from non-TRM cells (ii). Selected genes are labelled, and colored points indicate genes that are differentially expressed [BH adjusted P < 0.01 and absolute (average logFC) > 0.5]. E, Comparison of memory T-cell markers in CD8+ TRM and non-TRM in PDAC TIL, performed using the data in Fig. 2B. Bar graph comparing the proportion of Naïve, EM, CM, and TEMRA subsets in CD8+ TRM and non-TRM cells (i). Bar graph comparing the CD27 and CD28 expression pattern in CD8+ EM T-cells within TRM and non-TRM cells (ii). F, Line graphs comparing T-cell activation and differentiation marker expression on CD8+ TRM versus non-TRM cells in PDAC TIL, generated using the data in Fig. 2B. G, Representative contour plots (i) and quantification (ii) of CD39+ CD8+ TRM cells in PBMC and TIL, generated using the data in Fig. 2B. H, DFS analysis of patients with PDAC from the TCGA-PAAD dataset based on the expression level of ITGAE (CD103) in tumor tissue. Horizontal lines represent median, boxes represent quartiles and whiskers represent min and max values. Data analyzed using Wilcoxon matched-pairs signed rank test. *, P < 0.05; **, P < 0.01.

Major histocompatibility complex class II is expressed by mature professional antigen-presenting cells, forming a critical part of the innate immune response. However, other cell types, including tumour (tsMHCII), can be induced to express MHCII in response to inflammatory signalling by IFN-g, leading to increased tumour killing. TsMHCII-II expression has been associated with a higher number of tumour-infiltrating CD4 and CD8, with improved progression-free survival (PFS) and overall survival (OS). These observations suggested that increased tsMHCII expression is associated with increased tumour recognition by T cells and enhanced antitumor immunity. However, treatment with IFN-g is not a practical solution due to patient side effects and the finding that a high percentage of tumours have no upregulation of MHCII in response to IFNg stimulation. We have recently shown that EHMT1 is a potential target to upregulate MHCII in a genome wide CRISPR/Cas9 screen. In this study, we aim to 1) investigate a potential non-canonical relationship between EHMT1 and MHC-II expression in a microsatellite stable (MSS) colorectal organoid model 2) Evaluate the ability of organoids that constitutively express MHC-II to prime naïve T cells; and 3) explore pharmacological EHMT1 inhibitors as treatments to enhance MHC-II expression in tumour cells CRISPR/Cas9 was used to knock down the EHMT1 gene in colorectal organoids, confirmed with Sanger sequencing and Western blot analysis. To investigate the mechanistic differences between these clones and the WT, we carried out a differential gene expression analysis using RNAseq and ChIP-sequencing, focusing on the impact of EHMT1 knockout on whole genomic methylation signatures. Furthermore, we investigated the efficacy of targeting EHMT1 pharmacologically, utilising a selection of EHMT1 inhibitors. Finally, we co-cultured EHMT1-/- clones with allogenic T cells in a mixed lymphocyte reaction (MLR) assay. T cell stimulation was evaluated by assessing CD25, CD69, CD107a, and CD137 In contrast to the wild-type (WT) organoid that showed no response to IFNg stimulation, four EHMT1-/- knockout clones demonstrated upregulated levels of MHCII expression, independent of IFNg. The level of MHCII expression by the clones was correlated with the level of methylated H3K9. Additionally, EHMT inhibitors showed variable efficacy in enhancing MHCII expression in wild-type organoids. Analysis is ongoing to investigate the capability of these clones with constitutively expressed MHCII to process and present tumor antigens to stimulate naïve CD4+ T cells This study reveals a potentially novel role for EHMT1 in modulating the tumour immune response by controlling the expression of MHC-II in colorectal organoids. Future work will focus on assessing the efficacy of combining immune checkpoint inhibitors with EHMT1 inhibitors Nahla A. Elzefzafy, Louise Tee, Maria Pinna, Neeraj Lal, Gary M. M Middleton, Andrew Beggs. Re-expression of MHCII in colorectal organoids: Investigating the novel role of EHMT1 in regulating MHCII expression [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 4836.

Background Neutralization of interferon (IFN)-γ abrogates the efficacy of anti-programmed death-ligand 1 (PD-(L)1) checkpoint inhibitors. Most epithelial cells do not constitutively express major histocompatibility complex (MHC) class II but can be induced to do so by IFN-γ. Inducible tumor-specific MHC class II (tsMHC-II) underlies responsiveness to anti-PD-(L)1. Retrospective studies show that tsMHC-II positivity associates with improved outcomes in patients treated with anti-PD-(L)1. The ANICCA-Class II single-arm Bayesian phase II trial prospectively explored whether positive tsMHC-II status could be a useful selection marker for anti-programmed cell death protein-1 (PD-1) in proficient mismatch repair colorectal cancer (pMMR CRC). In parallel, we retrospectively evaluated the potential predictive power of immunoscore-immune checkpoint (IS-IC) for outcome with single-agent immune checkpoint blockade.Methods Patients with histologically confirmed locally advanced/metastatic pMMR CRC with >1% MHC class II expression, Eastern Cooperative Oncology Group performance status 0–2, aged ≥18 years were eligible. Participants received 480 mg nivolumab every 28 days for up to 24 cycles. The primary outcome was durable clinical benefit (DCB) defined as participants remaining progression-free at their third trial-specific scan since treatment start (ie, at approximately 27 weeks). Secondary outcomes included progression-free survival time (PFS) and overall survival time (OS).Results 35 participants were treated: 65.7% of participants’ cancers were tsMHC-II ≥5%. 3/35 patients achieved DCB (8.6%), estimating the true DCB rate (R) of 11% (95% credible interval 3% to 22%) with 0.002 probability that the true DCBR was >30%, below the required 0.5 to warrant further research. The higher tsMHC-II cut-point ≥5% was not more useful in predicting duration of disease stabilization. All three participants who achieved DCB had no evidence of liver metastases (LM); DCBR 23.1% in those without versus 0% in those with LM. PFS and OS were significantly greater in those without LM. There was no evidence that IS-IC high predicted for prolonged time on treatment or improved tumor growth inhibition.Conclusions In pMMR CRC, tsMHC-II positivity fails to identify a subset of patients with metastatic pMMR CRC obtaining potentially meaningful benefit from single-agent anti-PD-1. Although numbers are limited, there is no clear evidence that IS-IC is predictive of outcome with single-agent anti-PD-1. The poor outcome in those with LM underscores the need for therapies that overcome the systemic immunosuppression driven by LM.

Characterization of CD4+ T-cell populations within the PDAC tumor microenvironment. A, Dot plot of the top markers expressed in each CD4+ T-cell cluster identified via Louvain clustering of scRNA-seq data from CD4+ T cells from 3 PDAC tumor tissue samples (i). Where identifiable in the data, clusters are annotated with known CD4+ T-cell phenotypes. UMAP embedding of CD4+ T cells overlaid with Louvain cluster labels (ii). B, A 35-parameter CyTOF analysis of CD45+ cells from PDAC patient PBMC and TIL (n = 10). t-SNE plots shows PhenoGraph-clustered CD4+ T-cell populations in PBMC and TIL. C, Stacked bar graph showing the proportion of Naïve, EM, CM, and TEMRA subsets in CD4+ T cells generated from the data in (B). D, Bar graph comparing the proportion of each annotated CD4+ EM subset (TEM1-5) in PBMC vs. TIL, generated using the data in (B). E, Differential expression analysis distinguishing CD4+ Th17 from other non-Treg CD4+ T-cells in scRNA-seq data, first presented in Fig. 1. Selected genes are labelled, and colored points indicate genes that are differentially expressed [BH adjusted P < 0.01 and absolute (average logFC) > 0.5]. F, Quantification of CD4+ Th17 based on dual expression of CCR6 and CD161, performed using the data in (B). Representative contour plots comparing Th17 in PBMC and TIL (i). Box and whisker plot comparing the proportion of Th17 among total memory (CD45RA–) non-Treg CD4+ T cells in PBMC and TIL (ii). G, Quantification of CD4+ Treg cells based on expression of CD25 and CD127, generated using the data in (B). Representative contour plot of Treg cells (CD25+CD127low) from PDAC TIL (i). Box and whisker plot comparing the proportion of Th17 cells in PBMC and TIL (ii). H, Histograms comparing expression levels of activation and differentiation markers on total Tregs from PBMC and TIL, generated using the data in (B). Horizontal lines represent median, boxes represent quartiles and whiskers represent minimum and maximum values. Data analyzed using Wilcoxon matched-pairs signed rank test. CyTOF comparisons analyzed using Wilcoxon matched-pairs signed rank test. *, P < 0.05; **, P < 0.01.

The effect of T-cell proliferation and cytokine secretion following anti–PD-1 and anti-TIGIT blockade. A, Schematic representation of the CHO-aAPC:T-cell coculture assay. T cells from patients with PDAC were cocultured with aAPCs expressing PD-1 and/or TIGIT ligands for 4 days in the presence of anti-TIGIT and/or anti–PD-1, or with a mAb isotype control. B, Cell culture supernatants from 6 patients in triplicate wells were harvested after 4 days of coculture and IFNγ was quantified by ELISA. Box and whisker graphs compare the levels of IFNγ secreted under 3 conditions—without ligand expression, with ligand expression, and for both ligand expression and mAb blockade with either CD155, CD112, or PD-L1 (i) or dual CD155 and PD-L1 (ii) expression. C, Proliferation of T cells (n = 9 patients) following coculture was determined by CTV dilution and analyzed by flow cytometry on day 4. Box and whisker graphs compare fold change in T-cell proliferation following single or dual CD155/PD-L1 mAb blockade compared with without (isotype mAb) blockade with CHO-aAPCs expressing both CD155 and PD-L1. Horizontal lines represent median, boxes represent quartiles and whiskers represent minimum and maximum values. Data analyzed using Wilcoxon matched-pairs signed rank test. *, P < 0.05; **, P < 0.01.

Supplementary Figures S1 - S12

Checkpoint inhibitory receptor expression on PDAC T cells. A, Expression of checkpoint inhibitory receptors PD-1, TIGIT, Tim-3, LAG-3, and CTLA-4 on CD4+ and CD8+ T cells from matched PBMC and TIL was examined by flow cytometry (n = 14). Representative flow cytometric zebra plots show expression of each checkpoint inhibitory receptor alongside PD-1 expression for CD4+ and CD8+ T cells from PBMC and TIL. B, Scatter plots compare the proportion of each checkpoint receptor (i) and dual PD-1 and TIGIT expression (ii) on CD4+ and CD8+ T cells from PBMC and TIL. C, Venn diagrams show the overlapping expression of checkpoint inhibitory receptors on CD4+ and CD8+ T cells from PBMC and TIL. D, t-SNE plot of PDAC TIL CyTOF data first presented in Fig. 2B showing the expression level of TIGIT and PD-1. CD8+ TRM cells are highlighted. E, Box and whisker plot, generated using the CyTOF data first presented in Fig. 2B, compares dual TIGIT and PD-1 expression on TRM and non-TRM CD8+ T cells from PDAC TIL. F, Box and whisker plots, generated using the CyTOF data first presented in Fig. 2B, compare the MMI of PD-1 and TIGIT on TRM and non-TRM CD8+ T cells from PDAC TIL. G, Multiplex IHC staining shows T-cell staining around CD20+ B cells in lymphoid structures (scale bar: 100 μm; i); expression of PD-1 and TIGIT across the follicle with TIGIT focused within the T-cell zone (scale bar: 50 μm) and PD-1+TIGIT+ coexpression on CD8+ T cells (scale bar: 10 μm; ii). Horizontal lines represent median, boxes represent quartiles and whiskers represent minimum and maximum values. Data analyzed using Wilcoxon matched-pairs signed rank test. *, P < 0.05; **, P < 0.01; ***, P < 0.001.

Myeloid-derived suppressor cells (MDSCs) are a paradigmatic, immunosuppressive cell population found in the blood and tumors of people with cancer. Alternatively-activated tumor-associated macrophages (TAMs) are immunosuppressive cells present in high numbers in the tumour microenvironment (TME) derived from circulating monocytes which in people with cancer are monocytic (M)-MDSC which migrate into the TME and polarise towards a macrophage phenotype. MDSCs express the common myeloid marker CD33. We previously reported that the anti-CD33 antibody drug conjugate, gemtuzumab ozogamicin (GO) binds predominantly to M-MDSCs, is rapidly internalised and induces dose-dependent decrease in viability. Treatment of circulating or tumor-polarised MDSCs with GO restores T cell proliferation in co-culture. We report here clinical proof of principle that the anti-CD33 antibody drug conjugate, gemtuzumab ozogamicin (GO) significantly reduces and subsequently repolarizes circulating M-MDSCs in cancer patients. 7 patients with relapsed/refractory cancer were treated with GO at a dose of 3mg/m2, 6 of whom had pMMR colorectal cancer (CRC) with liver metastases (LM). 0/4 patients treated on a day 1,8,15 schedule received all 3 doses and this schedule was deemed unfeasible. However, GO delivered 3-weekly was feasible and tolerable. GO administration using both dosing schedules caused a highly reproducible, and profound short-lived fall in the absolute number of circulating CD33+ cells at one week following administration which rebounds to values > baseline 2-3 weeks following each infusion. Importantly, using the 3-weekly schedule, at the time of rebound of the CD33+ CD14+ cells, there is a marked increase in the number of cells expressing HLA-DR, which suggested potential re-programming towards a less immunosuppressive phenotype following GO therapy. In line with the phenotypic shift in CD33+ cells at rebound, there is a sustained loss of monocyte suppression of activated CD4+ T cell proliferation. Thus, GO significantly reduces immunosuppressive CD33+ monocytoid cell numbers in pMMR CRC patients with LM and on CD33+ cell rebound these cells are both phenotypically and functionally no longer immune-suppressive. This loss of immune-suppressivity is maintained throughout the entire duration of treatment. Alternatively-polarised macrophages also express CD33 and are sensitive to GO. These results support the combination of 3 cycles of three-weekly GO alongside the initial 3 cycles of immune checkpoint blockade (ICB), during which time the initial proliferative burst is crucial, so as to improve ICB outcomes in those with liver metastatic disease, a metastatic site resistant to ICB. Gary Middleton, Aimee Jackson, Saly Al-Taei, Vicki Kunene, Su Lee, Anna Jackson, Joe Rogers, Francis Mussai, Carmen de Santo. The anti-CD33 antibody drug conjugate gemtuzumab ozogamicin depletes and re-programmes CD33+ myeloid-derived suppressor cells in patients with metastatic cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_2):Abstract nr CT220.

Background & Aims: Effective control of chronic liver diseases (CLD) requires suppression of effector T cells by CD4+CD25+CD127low regulatory T cells (Tregs). This study investigated the role of TIGIT, a co-inhibitory receptor, in CLD by examining the phenotype, recruitment, localisation, and function of TIGIT+Tregs and how TIGIT augments Treg function. We also elucidated the function of TIGIT+effector T cells on hepatocytes. Methods: Liver infiltrating (CLD explants n = 7, donor liver n = 4) and peripheral (CLD blood n = 22, healthy control blood n = 10) TIGIT+Tregs and TIGIT+effector T cells were phenotyped by flow cytometry, and their localisation was examined by immunohistochemistry. Phenotypic and functional changes in TIGIT+Tregs in response to TIGIT agonism and IL-2 supplementation were also assessed. TIGIT+effector T cell-induced primary hepatocyte apoptosis was investigated using co-culture experiments and blocking assays. Results: TIGIT+Tregs were more suppressive towards CD4+T cells than TIGIT-Tregs (p = 0.04254), and their suppressive action was IL-10 dependent. TIGIT expression was highly enriched on intrahepatic Tregs compared to effector T cells (p <0.0001). TIGIT+Tregs and TIGIT+effector T cells expressed CXCR3 and VLA-4 and localised around hepatocytes which express TIGIT ligand, CD155. TIGIT+Tregs also exhibited significantly higher cytotoxic T lymphocyte-associated antigen-4 (CTLA-4; p = 0.0012), FoxP3 (p <0.0001), and CD39 (p <0.0001) expression than TIGIT-Tregs. TIGIT agonism upregulated FoxP3 and CTLA-4 on Tregs, reduced proliferation, and increased TNF-α expression. Supplementing TIGIT+Tregs with IL-2 further enhanced FoxP3 and CTLA-4 expression. In contrast, TIGIT+effector T cells displayed reduced cytotoxicity towards hepatocytes, which reversed upon TIGIT blockade. Conclusions: TIGIT+Tregs are highly suppressive and can be enhanced in response to TIGIT agonism and IL-2 stimulation, demonstrating their translational therapeutic potential. However, TIGIT blockade on CD8+T cells induces hepatitis, caution is required when using anti-TIGIT therapy. Impact and implications: We identified a highly suppressive subset of regulatory T cells in the liver, defined as TIGIT+CD39+CTLA-4+Tregs. TIGIT agonists and IL-2 enhanced the suppressive function of this cell subset. The TIGIT ligand, CD155, is expressed on inflamed hepatocytes, and TIGIT blockade in oncology could instigate checkpoint inhibitor induced liver injury (CHILI). These findings have implications for future therapy in liver disease.