Abstract Introduction: Tertiary lymphoid structures (TLSs) are ectopic lymphoid formations. In cancer, they promote antitumor immunity by supporting B-cell maturation, antibody production, and sustained T-cell activation. TLSs can convert immunologically non-inflamed tumors into inflamed ones. However, the vascular and molecular cues that govern TLS induction in human tumors remain poorly defined. Methods: Formalin-fixed paraffin-embedded tissue sections from twelve primary lung adenocarcinomas were analyzed. Tumor-associated vasculature was histologically annotated and stratified into three categories based on TLS status: (1) noTLS (absence of TLS), (2) iTLS (presence of immature TLS), and (3) mTLS (presence of mature TLS). GeoMx spatial transcriptomics was performed on endothelial regions. Protein-level validation was conducted using sequential immunofluorescence on the COMET platform. Results: Endothelial cells in noTLS regions showed high expression of COL5A1, COL3A1, FN1, ERRFI1, COL1A1, IFI6, SPP1, MDK, and BGN, whereas CXCL13 and CCL19 were enriched in mTLS. Gene-set analyses revealed that noTLS endothelium exhibited a myofibroblast-like, extracellular matrix-producing, EndoMT-associated program consistent with a fibrotic, immunosuppressive microenvironment. In contrast, mTLS endothelium displayed immune-activated signatures aligned with lymphoid organogenesis and fibroblastic reticular cell-like function. Receptor-ligand analysis showed preferential Wnt signaling in noTLS, while chemokine signaling dominated in mTLS. COMET immunofluorescence confirmed that FN1 was highly expressed in noTLS regions, whereas CXCL13 was highly expressed in mTLS. Conclusion: Tumor endothelial cells display striking context-dependent plasticity. noTLS vasculature undergoes EndoMT and adopts a matrix-producing, immunosuppressive phenotype that may actively suppress TLS formation. Conversely, mTLS endothelium acquires immune-organizing properties that favor TLS maturation and lymphoid compartmentalization. These findings identify endothelial reprogramming as a potential therapeutic strategy to induce TLSs and enhance response to immune checkpoint blockade. Citation Format: Shoko Kure, Giorgia Brambilla Pisoni, Saba Tabasum, Xiaoyu Li, Jingjing Li, Yao Yu Yeo, Sizun Jiang, Harrison Olszewski, Nicholas C. Weaver, Kathleen L. Pfaff, Jason L. Weirather, Ian D. Dryg, Scott J. Rodig, Frank S. Hodi. Immune-active and mesenchymal endothelial programs define TLS presence in the tumor microenvironment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 2217.

Additional evaluation of macrophage significance, cellular motif optimization, and macrophage-tumor cell interactions stratified by LMP1 expression in DLBCL.

Supplementary Figure S5: Survival by ERBB2 status.

PURPOSE:Cabozantinib, a multi-kinase inhibitor, improves progression-free survival (PFS) in patients with advanced extrapancreatic neuroendocrine tumors (epNET). Cabozantinib alters the tumor microenvironment to be more permissive to immune cells by reducing the presence of regulatory T cells and CD14+ monocytes. This trial investigated the efficacy and safety of cabozantinib in combination with nivolumab in patients with advanced epNET. PATIENTS AND METHODS:This was an open-label, single-arm, phase II trial, which enrolled patients with advanced epNET. Patients received nivolumab 240 mg i.v. on days 1 and 15 and cabozantinib 40 mg orally once daily on a 28-day cycle. The primary endpoint was objective response rate (ORR) by RECIST v1.1. Using a Simon two-stage design, 19 patients were enrolled in the first stage. Secondary objectives included ORR by immune-related RECIST, PFS, and safety. Exploratory objectives included correlation between immune and angiogenic proteomic profile and clinical outcomes. RESULTS:Eighteen of the 19 enrolled patients were evaluable for response. Best response was partial response in one (5%), stable disease in 16 (90%), and progressive disease in one patient (5%). The ORR did not meet goal for the first stage, so enrollment was terminated. The median PFS was 5.6 months (95% confidence interval, 3.5-9.9). Grade 3 toxicities attributed to the combination included tumor lysis (n = 1, 5%), elevated transaminases (n = 1, 5%), and fatigue (n = 2, 10%). Immune and angiogenic proteomic profiles demonstrated trends associated with longer time on therapy. CONCLUSIONS:Cabozantinib and nivolumab were associated with limited response in patients with epNET. Alternative strategies to enhance the immune response in epNET are needed.

Additional antibody staining specificity validation and cell phenotyping maps across DLBCL tissue sections.

Representativeness of Study Participants

Across cancer, one of the most frequent examples of histologic transformation is the evolution of follicular lymphoma (FL) to an aggressive large cell lymphoma. Despite recent progress, understanding of the molecular and cellular underpinnings of transformation remains incomplete. Here, we dissect the interplay of tumor and microenvironment cell populations across transformation through a multimodal investigation of 95 FL and transformed FL (tFL) samples, including single-cell and bulk RNA-sequencing alongside spatial transcriptomics and proteomics, and validate findings across independent FL-tFL pairs. Upon transformation, fibroblasts and GPNMB+ macrophages increase while lymph-node organizing follicular dendritic and CCL21+ fibroblastic reticular cells were lost, resulting in an altered spatial distribution of cytokines that impacts T cell infiltration and macrophage differentiation and function. Secreted stromal and macrophage signals were further evident by non-invasive plasma proteomics. Taken together, our data reveal expansion of macrophages and fibroblasts as key features of transformation with potential diagnostic and therapeutic implications.

INTRODUCTION:Thyroid transcription factor-1 (TTF-1) expression, routinely assessed through immunohistochemistry in the diagnostic evaluation of lung adenocarcinomas (LUADs), is negative (TTF-1Neg) in approximately 15% to 20% of cases. Although worse outcomes have been reported for these tumors compared with TTF-1-positive (TTF-1Pos) LUAD, a comprehensive characterization of TTF-1 negativity is currently lacking. METHODS:Patients with LUAD and available TTF-1 immunohistochemistry from five institutions, The Cancer Genome Atlas, the Stand Up To Cancer-Mark Foundation, and the POPLAR/OAK data sets, were included. Features and outcomes were analyzed according to TTF-1 expression. RESULTS:Among 3297 patients, TTF-1Neg (15%, n = 496), compared with TTF-1Pos (85%, n = 2801), was associated with a more frequent tobacco use history and lower PD-L1 expression. TTF-1Neg LUAD was enriched for STK11, KEAP1, SMARCA4, NKX2-1, CDKN2A, and KRAS mutations (q < 0.05). Patients with metastatic TTF-1Neg LUAD treated with immune checkpoint inhibitors (n = 233), compared with TTF-1Pos cases (n = 1179), had worse objective response rates (ORR, 17% versus 28%, p = 0.001), median progression-free survival (mPFS, 2.5 versus 4.4 mo, p < 0.0001), and median overall survival (mOS, 9.6 versus 20.2 mo, p < 0.0001). Similarly, TTF-1Neg cases had worse outcomes to chemoimmunotherapy (ORR, 26% versus 41%, p < 0.0001; mPFS, 4.6 versus 8.2 mo, p < 0.0001; mOS, 11.2 versus 23.4 mo, p < 0.0001), durvalumab after chemoradiation for unresectable stage III disease (mPFS, 8.0 versus 24.8 mo, p = 0.016; mOS, 20.0 mo versus not reached, p = 0.004), and KRASG12C inhibitors in KRASG12C-mutant LUAD (ORR, 13% versus 36%, p = 0.03; mPFS, 2.7 versus 5.9 mo, p < 0.0001; mOS, 4.4 versus 12.1 mo, p < 0.0001). CONCLUSIONS:TTF-1 negativity identifies a subset of LUAD with worse outcomes to immunotherapy, chemoimmunotherapy, and KRASG12C inhibitors.

Classic Hodgkin lymphoma (cHL) is composed of rare malignant Hodgkin and Reed-Sternberg (HRS) cells within a T-cell-rich tumor microenvironment (TME). Epstein-Barr virus (EBV) is present in ∼25% of cases, but its contribution to pathogenesis and immunomodulation remains unclear due to technical barriers. Using complementary spatial proteomics and transcriptomics across multi-institutional cohorts, we systematically map key EBV-linked TME reorganization. EBV-positive cHL exhibits distinct immunological features, including memory CD8 T cell enrichment, heightened T cell dysfunction spatially correlated with HRS proximity, and terminally exhausted T cell signatures contrasting with progenitor-exhausted patterns in EBV-negative disease. We identify EBV-encoded LMP1 as a factor in T cell dysfunction through enhanced HRS:CD8 interactions, and its expression level correlates with T cell terminal exhaustion in a distance-dependent manner. This spatial framework dissects viral-mediated immune evasion in the cHL TME, highlighting potential therapeutic opportunities to target virus-associated T cell dysfunction for precision immunotherapy in virus-associated malignancies.

Additional image quality, tissue integrity, and segmentation validation across extended CODEX cycles and multi-omics spatial workflow orders in IN-DEPTH.

Additional details on the CODEX-GeoMx spatial alignment, integration workflow, and batch effect correction for the DLBCL cohort.

Abstract Immune checkpoint inhibitors (ICI) synergize preclinically with antibody drug conjugates (ADC), harboring anti-tubulin maytansinoid payloads. We conducted an investigator-initiated, single-arm, phase 2 trial of mirvetuximab soravtansine (MIRV), a folate receptor alpha (FOLR1/FRα)-targeting ADC with the maytansinoid payload, DM4, combined with pembrolizumab in female patients with recurrent FOLR1-expressing serous endometrial cancer (EC, NCT03835819). Co-primary objectives include objective response rate (ORR) and rate of progression-free survival at 6 months (PFS6); secondary objectives include PFS, overall survival, duration of response and safety. Exploratory objectives include correlation of tumor genomics and immunoprofiling with clinical activity. Eighteen patients initiated protocol therapy [MIRV 6 mg/kg adjusted ideal body weight IV and pembrolizumab 200 mg IV every 3 weeks]. Confirmed ORR is 28% (1 complete and 4 partial responses, 95% CI:10-53%), Kaplan Meier estimate of PFS6 is 24.4% (95% CI:7.7-46.1%) with 4 patients progression free at 6 months; trial was closed early for feasibility (planned sample size of 35 patients not reached) and hence these results are considered preliminary. G3 treatment-related adverse effects were rare with no grade ≥4 toxicities. We report a population of high FOLR1-expressing tumor-associated macrophages (CD163 + FOLR1 + ), suggesting potential on-target, off-tumor immune editing by MIRV. A composite biomarker score derived in this cohort correlates with objective response to MIRV and pembrolizumab.

Upper and lower bound values used in data processing.

Spatial transcriptomics and proteomics have enabled profound insights into tissue organization, yet these technologies remain largely disparate, and emerging same-slide multiomics approaches are limited in plex, spatial resolution, signal retention, and integrative analytics. We introduce IN-situ DEtailed Phenotyping To High-resolution transcriptomics (IN-DEPTH), a streamlined, resource-efficient, commercially compatible workflow using single-cell spatial proteomics-derived imaging to guide transcriptomic capture on the same slide without RNA signal loss. To integrate modalities beyond niche-level mapping, we developed Spectral Graph Cross-Correlation (SGCC), a proteomic-transcriptomic framework resolving spatially coordinated functional state changes across interacting cell populations. Applied to diffuse large B-cell lymphoma (DLBCL), IN-DEPTH and SGCC enabled stepwise discovery from Epstein-Barr virus (EBV)-positive and EBV-negative tumor comparisons with single-cell resolution, revealing coordinated tumor-macrophage-CD4 T-cell remodeling, immunosuppressive C1Q macrophage enrichment, CD4 T-cell dysfunction, and a candidate IL27-STAT3 signaling axis. Collectively, IN-DEPTH enables scalable spatial multiomics to uncover clinically relevant microenvironmental mechanisms and toward robust spatial multimodal AI models. SIGNIFICANCE:IN-DEPTH enables same-slide spatial multiomics across commercial platforms via a protein-first strategy preserving protein epitopes, RNA quality, and tissue integrity. Coupled with SGCC, it resolves coordinated spatial immune remodeling, revealing EBV/LMP1-driven C1Q macrophage polarization and CD4 T-cell dysfunction in DLBCL, with broad applicability to other diseases.

Details of the antibody panel used in all IN-DEPTH experiments throughout the study including antibody clones, vendors, working concentrations, imaging channel, imaging cycle and exposure time.

Additional reproducibility assessment of IN-DEPTH in tonsil benchmark tissues across serial tissue sections, including antibody validation, spatial registration, and multi-modal consistency across protein expression, transcriptomics, and deconvolution methods.

Mean expression, statistical metrics, and Log2fold change of ligand-receptor interactions.

Enrichment pathways in LMP1-positive and LMP1-negative tumors and their neighboring macrophages.