A Hitchhiker's guide to high-dimensional tissue imaging with multiplexed ion beam imaging.

Advancements in multiplexed tissue imaging technologies are vital in shaping our understanding of tissue microenvironmental influences in disease contexts. These technologies now allow us to relate the phenotype of individual cells to their higher-order roles in tissue organization and function. Multiplexed Ion Beam Imaging (MIBI) is one of such technologies, which uses metal isotope-labeled antibodies and secondary ion mass spectrometry (SIMS) to image more than 40 protein markers simultaneously within a single tissue section. Here, we describe an optimized MIBI workflow for high-plex analysis of Formalin-Fixed Paraffin-Embedded (FFPE) tissues following antigen retrieval, metal isotope-conjugated antibody staining, imaging using the MIBI instrument, and subsequent data processing and analysis. While this workflow is focused on imaging human FFPE samples using the MIBI, this workflow can be easily extended to model systems, biological questions, and multiplexed imaging modalities.

Cross-domain information fusion for enhanced cell population delineation in single-cell spatial-omics data.

Cell population delineation and identification is an essential step in single-cell and spatial-omics studies. Spatial-omics technologies can simultaneously measure information from three complementary domains related to this task: expression levels of a panel of molecular biomarkers at single-cell resolution, relative positions of cells, and images of tissue sections, but existing computational methods for performing this task on single-cell spatial-omics datasets often relinquish information from one or more domains. The additional reliance on the availability of "atlas" training or reference datasets limits cell type discovery to well-defined but limited cell population labels, thus posing major challenges for using these methods in practice. Successful integration of all three domains presents an opportunity for uncovering cell populations that are functionally stratified by their spatial contexts at cellular and tissue levels: the key motivation for employing spatial-omics technologies in the first place. In this work, we introduce Cell Spatio- and Neighborhood-informed Annotation and Patterning (CellSNAP), a self-supervised computational method that learns a representation vector for each cell in tissue samples measured by spatial-omics technologies at the single-cell or finer resolution. The learned representation vector fuses information about the corresponding cell across all three aforementioned domains. By applying CellSNAP to datasets spanning both spatial proteomic and spatial transcriptomic modalities, and across different tissue types and disease settings, we show that CellSNAP markedly enhances de novo discovery of biologically relevant cell populations at fine granularity, beyond current approaches, by fully integrating cells' molecular profiles with cellular neighborhood and tissue image information.

Epstein-Barr Virus Orchestrates Spatial Reorganization and Immunomodulation within the Classic Hodgkin Lymphoma Tumor Microenvironment.

Classic Hodgkin Lymphoma (cHL) is a tumor composed of rare malignant Hodgkin and Reed-Sternberg (HRS) cells nested within a T-cell rich inflammatory immune infiltrate. cHL is associated with Epstein-Barr Virus (EBV) in 25% of cases. The specific contributions of EBV to the pathogenesis of cHL remain largely unknown, in part due to technical barriers in dissecting the tumor microenvironment (TME) in high detail. Herein, we applied multiplexed ion beam imaging (MIBI) spatial pro-teomics on 6 EBV-positive and 14 EBV-negative cHL samples. We identify key TME features that distinguish between EBV-positive and EBV-negative cHL, including the relative predominance of memory CD8 T cells and increased T-cell dysfunction as a function of spatial proximity to HRS cells. Building upon a larger multi-institutional cohort of 22 EBV-positive and 24 EBV-negative cHL samples, we orthogonally validated our findings through a spatial multi-omics approach, coupling whole transcriptome capture with antibody-defined cell types for tu-mor and T-cell populations within the cHL TME. We delineate contrasting transcriptomic immunological signatures between EBV-positive and EBV-negative cases that differently impact HRS cell proliferation, tumor-immune interactions, and mecha-nisms of T-cell dysregulation and dysfunction. Our multi-modal framework enabled a comprehensive dissection of EBV-linked reorganization and immune evasion within the cHL TME, and highlighted the need to elucidate the cellular and molecular fac-tors of virus-associated tumors, with potential for targeted therapeutic strategies.

Association of Baseline Tumor-Specific Neoantigens and CD8+ T-Cell Infiltration With Immune-Related Adverse Events Secondary to Immune Checkpoint Inhibitors.

PURPOSE: Recent evidence has shown that higher tumor mutational burden strongly correlates with an increased risk of immune-related adverse events (irAEs). By using an integrated multiomics approach, we further studied the association between relevant tumor immune microenvironment (TIME) features and irAEs. METHODS: Leveraging the US Food and Drug Administration Adverse Event Reporting System, we extracted cases of suspected irAEs to calculate the reporting odds ratios (RORs) of irAEs for cancers treated with immune checkpoint inhibitors (ICIs). TIME features for 32 cancer types were calculated on the basis of the cancer genomic atlas cohorts and indirectly correlated with each cancer's ROR for irAEs. A separate ICI-treated cohort of non-small-cell lung cancer (NSCLC) was used to evaluate the correlation between tissue-based immune markers (CD8+, PD-1/L1+, FOXP3+, tumor-infiltrating lymphocytes [TILs]) and irAE occurrence. RESULTS: The analysis of 32 cancers and 33 TIME features demonstrated a significant association between irAE RORs and the median number of base insertions and deletions (INDEL), neoantigens (r = 0.72), single-nucleotide variant neoantigens (r = 0.67), and CD8+ T-cell fraction (r = 0.51). A bivariate model using the median number of INDEL neoantigens and CD8 T-cell fraction had the highest accuracy in predicting RORs (adjusted r2 = 0.52, P = .002). Immunoprofile assessment of 156 patients with NSCLC revealed a strong trend for higher baseline median CD8+ T cells within patients' tumors who experienced any grade irAEs. Using machine learning, an expanded ICI-treated NSCLC cohort (n = 378) further showed a treatment duration-independent association of an increased proportion of high TIL (>median) in patients with irAEs (59.7% v 44%, P = .005). This was confirmed by using the Fine-Gray competing risk approach, demonstrating higher baseline TIL density (>median) associated with a higher cumulative incidence of irAEs (P = .028). CONCLUSION: Our findings highlight a potential role for TIME features, specifically INDEL neoantigens and baseline-immune infiltration, in enabling optimal irAE risk stratification of patients.

Graph Fourier transform for spatial omics representation and analyses of complex organs.

Spatial omics technologies are capable of deciphering detailed components of complex organs or tissue in cellular and subcellular resolution. A robust, interpretable, and unbiased representation method for spatial omics is necessary to illuminate novel investigations into biological functions, whereas a mathematical theory deficiency still exists. We present SpaGFT (Spatial Graph Fourier Transform), which provides a unique analytical feature representation of spatial omics data and elucidates molecular signatures linked to critical biological processes within tissues and cells. It outperformed existing tools in spatially variable gene prediction and gene expression imputation across human/mouse Visium data. Integrating SpaGFT representation into existing machine learning frameworks can enhance up to 40% accuracy of spatial domain identification, cell type annotation, cell-to-spot alignment, and subcellular hallmark inference. SpaGFT identified immunological regions for B cell maturation in human lymph node Visium data, characterized secondary follicle variations from in-house human tonsil CODEX data, and detected extremely rare subcellular organelles such as Cajal body and Set1/COMPASS. This new method lays the groundwork for a new theoretical model in explainable AI, advancing our understanding of tissue organization and function.

Genomic and Immunophenotypic Landscape of Acquired Resistance to PD-(L)1 Blockade in Non-Small-Cell Lung Cancer.

PURPOSE: Although immune checkpoint inhibitors (ICI) have extended survival in patients with non-small-cell lung cancer (NSCLC), acquired resistance (AR) to ICI frequently develops after an initial benefit. However, the mechanisms of AR to ICI in NSCLC are largely unknown. METHODS: Comprehensive tumor genomic profiling, machine learning-based assessment of tumor-infiltrating lymphocytes, multiplexed immunofluorescence, and/or HLA-I immunohistochemistry (IHC) were performed on matched pre- and post-ICI tumor biopsies from patients with NSCLC treated with ICI at the Dana-Farber Cancer Institute who developed AR to ICI. Two additional cohorts of patients with intervening chemotherapy or targeted therapies between biopsies were included as controls. RESULTS: We performed comprehensive genomic profiling and immunophenotypic characterization on samples from 82 patients with NSCLC and matched pre- and post-ICI biopsies and compared findings with a control cohort of patients with non-ICI intervening therapies between biopsies (chemotherapy, N = 32; targeted therapies, N = 89; both, N = 17). Putative resistance mutations were identified in 27.8% of immunotherapy-treated cases and included acquired loss-of-function mutations in STK11, B2M, APC, MTOR, KEAP1, and JAK1/2; these acquired alterations were not observed in the control groups. Immunophenotyping of matched pre- and post-ICI samples demonstrated significant decreases in intratumoral lymphocytes, CD3e+ and CD8a+ T cells, and PD-L1-PD1 engagement, as well as increased distance between tumor cells and CD8+PD-1+ T cells. There was a significant decrease in HLA class I expression in the immunotherapy cohort at the time of AR compared with the chemotherapy (P = .005) and the targeted therapy (P = .01) cohorts. CONCLUSION: These findings highlight the genomic and immunophenotypic heterogeneity of ICI resistance in NSCLC, which will need to be considered when developing novel therapeutic strategies aimed at overcoming resistance.

MAPS: pathologist-level cell type annotation from tissue images through machine learning.

Highly multiplexed protein imaging is emerging as a potent technique for analyzing protein distribution within cells and tissues in their native context. However, existing cell annotation methods utilizing high-plex spatial proteomics data are resource intensive and necessitate iterative expert input, thereby constraining their scalability and practicality for extensive datasets. We introduce MAPS (Machine learning for Analysis of Proteomics in Spatial biology), a machine learning approach facilitating rapid and precise cell type identification with human-level accuracy from spatial proteomics data. Validated on multiple in-house and publicly available MIBI and CODEX datasets, MAPS outperforms current annotation techniques in terms of speed and accuracy, achieving pathologist-level precision even for typically challenging cell types, including tumor cells of immune origin. By democratizing rapidly deployable and scalable machine learning annotation, MAPS holds significant potential to expedite advances in tissue biology and disease comprehension.

A spatial cell atlas of neuroblastoma reveals developmental, epigenetic and spatial axis of tumor heterogeneity.

Neuroblastoma is a pediatric cancer arising from the developing sympathoadrenal lineage with complex inter- and intra-tumoral heterogeneity. To chart this complexity, we generated a comprehensive cell atlas of 55 neuroblastoma patient tumors, collected from two pediatric cancer institutions, spanning a range of clinical, genetic, and histologic features. Our atlas combines single-cell/nucleus RNA-seq (sc/scRNA-seq), bulk RNA-seq, whole exome sequencing, DNA methylation profiling, spatial transcriptomics, and two spatial proteomic methods. Sc/snRNA-seq revealed three malignant cell states with features of sympathoadrenal lineage development. All of the neuroblastomas had malignant cells that resembled sympathoblasts and the more differentiated adrenergic cells. A subset of tumors had malignant cells in a mesenchymal cell state with molecular features of Schwann cell precursors. DNA methylation profiles defined four groupings of patients, which differ in the degree of malignant cell heterogeneity and clinical outcomes. Using spatial proteomics, we found that neuroblastomas are spatially compartmentalized, with malignant tumor cells sequestered away from immune cells. Finally, we identify spatially restricted signaling patterns in immune cells from spatial transcriptomics. To facilitate the visualization and analysis of our atlas as a resource for further research in neuroblastoma, single cell, and spatial-omics, all data are shared through the Human Tumor Atlas Network Data Commons at www.humantumoratlas.org.

A multi-cohort phase 1b trial of rituximab in combination with immunotherapy doublets in relapsed/refractory follicular lymphoma.

Antibodies targeting PD-1 or 4-1BB achieve objective responses in follicular lymphoma (FL), but only in a minority of patients. We hypothesized that targeting multiple immune receptors could overcome immune resistance and increase response rates in patients with relapsed/refractory FL. We therefore conducted a phase 1b trial testing time-limited therapy with different immunotherapy doublets targeting 4-1BB (utomilumab), OX-40 (ivuxolimab), and PD-L1 (avelumab) in combination with rituximab among patients with relapsed/refractory grade 1-3A FL. Patients were enrolled onto 2 of 3 planned cohorts (cohort 1 - rituximab/utomilumab/avelumab; cohort 2 - rituximab/ivuxolimab/utomilumab). 3+3 dose escalation was followed by dose expansion at the recommended phase 2 dose (RP2D). Twenty-four patients were enrolled (16 in cohort 1 and 9 in cohort 2, with one treated in both cohorts). No patients discontinued treatment due to adverse events and the RP2D was the highest dose level tested in both cohorts. In cohort 1, the objective and complete response rates were 44% and 19%, respectively (50% and 30%, respectively, at RP2D). In cohort 2, no responses were observed. The median progression-free survivals in cohorts 1 and 2 were 6.9 and 3.2 months, respectively. In cohort 1, higher density of PD-1+ tumor-infiltrating T-cells on baseline biopsies and lower density of 4-1BB+ and TIGIT+ T-cells in on-treatment biopsies were associated with response. Abundance of Akkermansia in stool samples was also associated with response. Our results support a possible role for 4-1BB agonist therapy in FL and suggest that features of the tumor microenvironment and stool microbiome may be associated with clinical outcomes (NCT03636503).

Cutaneous Manifestations of Myeloid Neoplasms Exhibit Broad and Divergent Morphologic and Immunophenotypic Features but Share Ancestral Clonal Mutations With Bone Marrow.

In this study, we performed a comprehensive molecular analysis of paired skin and peripheral blood/bone marrow (BM) samples from 17 patients with cutaneous myeloid or cutaneous histiocytic-dendritic neoplasms. The cutaneous manifestations included 10 patients with cutaneous acute myeloid leukemia (c-AML), 2 patients with full or partial Langerhans cell differentiation, 2 patients with blastic plasmacytoid dendritic cell neoplasms (BPDCN), 1 patient with both Langerhans cell differentiation and BPDCN, and 2 patients with full or partial indeterminate dendritic cell differentiation. Seven of the 10 c-AML patients (70%) exhibited concurrent or subsequent marrow involvement by acute myeloid leukemia, with all 7 cases (100%) demonstrating shared clonal mutations in both the skin and BM. However, clonal relatedness was documented in one additional case that never had any BM involvement. Nevertheless, NPM1 mutations were identified in 7 of the 10 (70%) of these c-AML cases while one had KMT2A rearrangement and one showed inv(16). All 3 patients (100%) with Langerhans cell neoplasms, 2 patients with BPDCN (100%), and one of the 2 patients (50%) with other cutaneous dendritic cell neoplasms also demonstrated shared mutations between the skin and concurrent or subsequent myeloid neoplasms. Both BM and c-AML shared identical founding drivers, with a predominance of NPM1, DNMT3A, and translocations associated with monocytic differentiation, with common cutaneous-only mutations involving genes in the signal transduction and epigenetic pathways. Cutaneous histiocytic-dendritic neoplasms shared founding drivers in ASXL1, TET2, and/or SRSF2. However, in the Langerhans cell histiocytosis or histiocytic sarcoma cases, there exist recurrent secondary RAS pathway hits, whereas cutaneous BPDCN cases exhibit copy number or structural variants. These results enrich and broaden our understanding of clonally related cutaneous manifestations of myeloid neoplasms and further illuminate the highly diverse spectrum of morphologic and immunophenotypic features they exhibit.

Systematic benchmarking of imaging spatial transcriptomics platforms in FFPE tissues.

Emerging imaging spatial transcriptomics (iST) platforms and coupled analytical methods can recover cell-to-cell interactions, groups of spatially covarying genes, and gene signatures associated with pathological features, and are thus particularly well-suited for applications in formalin fixed paraffin embedded (FFPE) tissues. Here, we benchmarked the performance of three commercial iST platforms on serial sections from tissue microarrays (TMAs) containing 23 tumor and normal tissue types for both relative technical and biological performance. On matched genes, we found that 10x Xenium shows higher transcript counts per gene without sacrificing specificity, but that all three platforms concord to orthogonal RNA-seq datasets and can perform spatially resolved cell typing, albeit with different false discovery rates, cell segmentation error frequencies, and with varying degrees of sub-clustering for downstream biological analyses. Taken together, our analyses provide a comprehensive benchmark to guide the choice of iST method as researchers design studies with precious samples in this rapidly evolving field.

A multidimensional analysis reveals distinct immune phenotypes and tertiary lymphoid structure-like aggregates in the bone marrow of pediatric acute myeloid leukemia.

Because of the low mutational burden, children with acute myeloid leukemia (AML) are thought to have a 'cold' tumor microenvironment and consequently, a low likelihood of response to T cell-directed immunotherapies. Here, we provide a multidimensional overview of the tumor immune microenvironment in newly diagnosed pediatric AML. On a cohort level, we demonstrate wide variation in T cell infiltration with nearly one-third of cases harboring an immune-infiltrated bone marrow. These immune-infiltrated cases are characterized by a decreased abundance of M2-like macrophages, which we find to be associated with response to T cell-directed immunotherapy in adult AML. On an organizational level, we reveal the composition of spatially organized immune aggregates in pediatric AML, and show that in the adult setting such aggregates in post-treatment bone marrow and extramedullary sites associate with response to ipilimumab-based therapy. Altogether, our study provides immune correlates of response to T cell-directed immunotherapies and indicates starting points for further investigations into immunomodulatory mechanisms in AML.

Clinical trial links oncolytic immunoactivation to survival in glioblastoma.

Immunotherapy failures can result from the highly suppressive tumour microenvironment that characterizes aggressive forms of cancer such as recurrent glioblastoma (rGBM)1,2. Here we report the results of a first-in-human phase I trial in 41 patients with rGBM who were injected with CAN-3110-an oncolytic herpes virus (oHSV)3. In contrast to other clinical oHSVs, CAN-3110 retains the viral neurovirulence ICP34.5 gene transcribed by a nestin promoter; nestin is overexpressed in GBM and other invasive tumours, but not in the adult brain or healthy differentiated tissue4. These modifications confer CAN-3110 with preferential tumour replication. No dose-limiting toxicities were encountered. Positive HSV1 serology was significantly associated with both improved survival and clearance of CAN-3110 from injected tumours. Survival after treatment, particularly in individuals seropositive for HSV1, was significantly associated with (1) changes in tumour/PBMC T cell counts and clonal diversity, (2) peripheral expansion/contraction of specific T cell clonotypes; and (3) tumour transcriptomic signatures of immune activation. These results provide human validation that intralesional oHSV treatment enhances anticancer immune responses even in immunosuppressive tumour microenvironments, particularly in individuals with cognate serology to the injected virus. This provides a biological rationale for use of this oncolytic modality in cancers that are otherwise unresponsive to immunotherapy (ClinicalTrials.gov: NCT03152318 ).

Preexisting tumor-resident T cells with cytotoxic potential associate with response to neoadjuvant anti-PD-1 in head and neck cancer.

About 50% of patients with locally advanced head and neck squamous cell carcinoma (HNSCC) experience recurrences after definitive therapy. The presurgical administration of anti-programmed cell death protein 1 (PD-1) immunotherapy results in substantial pathologic tumor responses (pTR) within the tumor microenvironment (TME). However, the mechanisms underlying the dynamics of antitumor T cells upon neoadjuvant PD-1 blockade remain unresolved, and approaches to increase pathologic responses are lacking. In a phase 2 trial (NCT02296684), we observed that 45% of patients treated with two doses of neoadjuvant pembrolizumab experienced marked pTRs (≥50%). Single-cell analysis of 17,158 CD8+ T cells from 14 tumor biopsies, including 6 matched pre-post neoadjuvant treatment, revealed that responding tumors had clonally expanded putative tumor-specific exhausted CD8+ tumor-infiltrating lymphocytes (TILs) with a tissue-resident memory program, characterized by high cytotoxic potential (CTX+) and ZNF683 expression, within the baseline TME. Pathologic responses after 5 weeks of PD-1 blockade were consistent with activation of preexisting CTX+ZNF683+CD8+ TILs, paralleling loss of viable tumor and associated tumor antigens. Response was associated with high numbers of CD103+PD-1+CD8+ T cells infiltrating pretreatment lesions, whereas revival of nonexhausted persisting clones and clonal replacement were modest. By contrast, nonresponder baseline TME exhibited a relative absence of ZNF683+CTX+ TILs and subsequent accumulation of highly exhausted clones. In HNSCC, revival of preexisting ZNF683+CTX+ TILs is a major mechanism of response in the immediate postneoadjuvant setting.

MAPS: Pathologist-level cell type annotation from tissue images through machine learning.

Highly multiplexed protein imaging is emerging as a potent technique for analyzing protein distribution within cells and tissues in their native context. However, existing cell annotation methods utilizing high-plex spatial proteomics data are resource intensive and necessitate iterative expert input, thereby constraining their scalability and practicality for extensive datasets. We introduce MAPS (Machine learning for Analysis of Proteomics in Spatial biology), a machine learning approach facilitating rapid and precise cell type identification with human-level accuracy from spatial proteomics data. Validated on multiple in-house and publicly available MIBI and CODEX datasets, MAPS outperforms current annotation techniques in terms of speed and accuracy, achieving pathologist-level precision even for challenging cell types, including tumor cells of immune origin. By democratizing rapidly deployable and scalable machine learning annotation, MAPS holds significant potential to expedite advances in tissue biology and disease comprehension.

MYD88L265P augments proximal B-cell receptor signaling in large B-cell lymphomas via an interaction with DOCK8.

Diffuse large B-cell lymphoma (DLBCL) is a clinically and genetically heterogeneous disease with at least 5 recognized molecular subtypes. Cluster 5 (C5)/MCD tumors frequently exhibit concurrent alterations in the toll-like receptor (TLR) and B-cell receptor (BCR) pathway members, MYD88L265P and CD79B, and have a less favorable prognosis. In healthy B cells, the synergy between TLR and BCR signaling pathways integrates innate and adaptive immune responses and augments downstream NF-κB activation. In addition, physiologic TLR9 pathway engagement via MYD88, protein tyrosine kinase 2 (PYK2), and dedicator of cytokinesis 8 (DOCK8) increases proximal BCR signaling in healthy murine B cells. Although C5/MCD DLBCLs are selectively sensitive to Bruton tyrosine kinase (BTK) inhibition in in vitro studies and certain clinical trials, the role of mutated MYD88 in proximal BCR signaling remains undefined. Using engineered DLBCL cell line models, we found that concurrent MYD88L265P and CD79B alterations significantly increased the magnitude and duration of proximal BCR signaling, at the level of spleen tyrosine kinase and BTK, and augmented PYK2-dependent DOCK8 phosphorylation. MYD88L265P DLBCLs have significantly increased colocalization of DOCK8 with both MYD88 and the proximal BCR-associated Src kinase, LYN, in comparison with MYD88WT DLBCLs, implicating DOCK8 in MYD88L265P/proximal BCR cross talk. Additionally, DOCK8 depletion selectively decreased proximal BCR signaling, cellular proliferation, and viability of DLBCLs with endogenous MYD88L265P/CD79BY196F alterations and increased the efficacy of BTK blockade in these lymphomas. Therefore, MYD88L265P/DOCK8-enhanced proximal BCR signaling is a likely mechanism for the increased sensitivity of C5/MCD DLBCLs to BTK blockade.

Expanded vacuum-stable gels for multiplexed high-resolution spatial histopathology.

Cellular organization and functions encompass multiple scales in vivo. Emerging high-plex imaging technologies are limited in resolving subcellular biomolecular features. Expansion Microscopy (ExM) and related techniques physically expand samples for enhanced spatial resolution, but are challenging to be combined with high-plex imaging technologies to enable integrative multiscaled tissue biology insights. Here, we introduce Expand and comPRESS hydrOgels (ExPRESSO), an ExM framework that allows high-plex protein staining, physical expansion, and removal of water, while retaining the lateral tissue expansion. We demonstrate ExPRESSO imaging of archival clinical tissue samples on Multiplexed Ion Beam Imaging and Imaging Mass Cytometry platforms, with detection capabilities of > 40 markers. Application of ExPRESSO on archival human lymphoid and brain tissues resolved tissue architecture at the subcellular level, particularly that of the blood-brain barrier. ExPRESSO hence provides a platform for extending the analysis compatibility of hydrogel-expanded biospecimens to mass spectrometry, with minimal modifications to protocols and instrumentation.

Impact of TMB/PD-L1 expression and pneumonitis on chemoradiation and durvalumab response in stage III NSCLC.

Although concurrent chemoradiation (CRT) and durvalumab consolidation has become a standard treatment for stage III non-small cell lung cancer (NSCLC), clinicopathologic and genomic factors associated with its efficacy remain poorly characterized. Here, in a multi-institutional retrospective cohort study of 328 patients treated with CRT and durvalumab, we identify that very high PD-L1 tumor proportion score (TPS) expression ( ≥ 90%) and increased tumor mutational burden (TMB) are independently associated with prolonged disease control. Additionally, we identify the impact of pneumonitis and its timing on disease outcomes among patients who discontinue durvalumab: compared to patients who experienced early-onset pneumonitis ( < 3 months) leading to durvalumab discontinuation, patients with late-onset pneumonitis had a significantly longer PFS (12.7 months vs not reached; HR 0.24 [95% CI, 0.10 to 0.58]; P = 0.001) and overall survival (37.2 months vs not reached; HR 0.26 [95% CI, 0.09 to 0.79]; P = 0.017). These findings suggest that opportunities exist to improve outcomes in patients with lower PD-L1 and TMB levels, and those at highest risk for pneumonitis.

Targeting KDM2A Enhances T-cell Infiltration in NSD1-Deficient Head and Neck Squamous Cell Carcinoma.

In head and neck squamous cell carcinoma (HNSCC), a significant proportion of tumors have inactivating mutations in the histone methyltransferase NSD1. In these tumors, NSD1 inactivation is a driver of T-cell exclusion from the tumor microenvironment (TME). A better understanding of the NSD1-mediated mechanism regulating infiltration of T cells into the TME could help identify approaches to overcome immunosuppression. Here, we demonstrated that NSD1 inactivation results in lower levels of H3K36 dimethylation and higher levels of H3K27 trimethylation, the latter being a known repressive histone mark enriched on the promoters of key T-cell chemokines CXCL9 and CXCL10. HNSCC with NSD1 mutations had lower levels of these chemokines and lacked responses to PD-1 immune checkpoint blockade. Inhibition of KDM2A, the primary lysine demethylase that is selective for H3K36, reversed the altered histone marks induced by NSD1 loss and restored T-cell infiltration into the TME. Importantly, KDM2A suppression decreased growth of NSD1-deficient tumors in immunocompetent, but not in immunodeficient, mice. Together, these data indicate that KDM2A is an immunotherapeutic target for overcoming immune exclusion in HNSCC. SIGNIFICANCE: The altered epigenetic landscape of NSD1-deficient tumors confers sensitivity to inhibition of the histone-modifying enzyme KDM2A as an immunotherapeutic strategy to stimulate T-cell infiltration and suppress tumor growth.

High-plex immunofluorescence imaging and traditional histology of the same tissue section for discovering image-based biomarkers.

Precision medicine is critically dependent on better methods for diagnosing and staging disease and predicting drug response. Histopathology using hematoxylin and eosin (H&E)-stained tissue (not genomics) remains the primary diagnostic method in cancer. Recently developed highly multiplexed tissue imaging methods promise to enhance research studies and clinical practice with precise, spatially resolved single-cell data. Here, we describe the 'Orion' platform for collecting H&E and high-plex immunofluorescence images from the same cells in a whole-slide format suitable for diagnosis. Using a retrospective cohort of 74 colorectal cancer resections, we show that immunofluorescence and H&E images provide human experts and machine learning algorithms with complementary information that can be used to generate interpretable, multiplexed image-based models predictive of progression-free survival. Combining models of immune infiltration and tumor-intrinsic features achieves a 10- to 20-fold discrimination between rapid and slow (or no) progression, demonstrating the ability of multimodal tissue imaging to generate high-performance biomarkers.