The Journal of Pathology

PurposeTriple-negative breast cancer (TNBC) exhibits substantial clinical heterogeneity, with some patients experiencing early recurrence and poor survival despite similar clinicopathologic features. We sought to determine whether quantitative measures of intratumoral collagen architecture and composition derived from standard histopathologic specimens can identify patients at risk of recurrence and adverse survival outcomes. Experimental DesignWe analyzed a retrospective cohort of 79 TNBC tumors assembled into a tissue microarray using a multimodal computational pathology framework integrating Massons Trichrome staining with COL1 and COL3 immunohistochemistry. Collagen architecture was quantified using fiber-based image analysis and unsupervised clustering, while collagen composition was assessed using a normalized COL3:COL1 ratio. Associations with recurrence-free interval (RFI) and overall survival (OS) were evaluated using Kaplan-Meier analysis, restricted mean survival time (RMST), and Cox proportional hazards modeling. ResultsUnsupervised analysis identified four distinct collagen architectural states, which were consolidated into low-risk and high-risk groups based on recurrence patterns. High-risk collagen architecture was associated with significantly worse long-term RFI (log-rank p=0.025; RMST difference 10.1 months). Independently, a higher COL3:COL1 ratio was associated with improved OS (log-rank p=0.042; RMST difference 9.4 months). Integration of architectural and compositional biomarkers further refined risk stratification, identifying a subgroup with high-risk architecture and low COL3:COL1 ratio that exhibited the poorest survival outcomes. Notably, collagen-based stratification identified patients with divergent outcomes not readily predicted from tumor stage alone. ConclusionsQuantitative assessment of intratumoral collagen architecture and composition provides clinically meaningful prognostic information in TNBC and enables stratification of recurrence and survival risk. These findings support extracellular matrix phenotyping as a practical and scalable computational pathology approach for refining risk assessment in TNBC. Translational RelevanceTriple-negative breast cancer (TNBC) remains clinically challenging due to heterogeneous outcomes that are not fully captured by standard clinicopathologic variables. In this study, we demonstrate that quantitative features of intratumoral collagen architecture and composition, derived from routine pathology specimens, provide clinically meaningful prognostic information. Collagen-based biomarkers, including distinct collagen architectural phenotypes and the COL3:COL1 ratio, identify patient subgroups with distinct recurrence and survival outcomes, particularly among individuals whose risk is not adequately predicted by conventional staging. Importantly, these features can be extracted from widely available histological stains and immunohistochemistry, supporting the potential integration into existing pathology workflows. These findings support the tumor microenvironment as an underutilized source of biomarkers and suggest that extracellular matrix-based phenotyping may improve risk stratification and inform clinical decision-making in TNBC.

Introduction: With recent approvals of multiple targeted therapies for triple-negative breast cancer (TNBC), including antibody-drug conjugates and immunotherapy in biomarker-selected populations, it is critical to define the temporal evolution of cell-surface target expression from early-stage to metastatic disease, the co-expression patterns across these markers, and optimal quantification methodologies. Here we report biomarker expression profiles measured by multi-omics and pathology-based platforms in patients with TNBC using a large cohort of matched longitudinal tumor samples. Methods: Patients who underwent neoadjuvant chemotherapy (NAC) for stage I-III TNBC or were diagnosed with any stage TNBC and developed metastatic recurrence were retrospectively identified from an institutional database and prospective research metastatic biopsy protocol. Tumor samples from diagnosis (DX), residual disease (RD) post-NAC (if applicable), and metastasis/recurrence (MR) were collected. Quantification of HER2, TROP2, and PD-L1 expression was performed by immunohistochemistry (IHC), whole-exome sequencing, transcriptome sequencing, and targeted mass spectrometry (MS). For HER2, TROP2, and stromal tumor-infiltrating lymphocytes (sTILs), both manual pathologist assessment and computational pathology quantification were obtained. HER2 status was categorized as HER2-0 or HER2-low by local (L-IHC) and central (C-IHC) review, TROP2 status was defined as low (H-score <100), medium (H-score 100-200) or high (H-score >200), and PD-L1 as low (tumor area positivity, TAP <5%) or high (TAP [&ge;]5%). Pathologist-assessed sTILs were classified as low (<10%), medium ([&ge;]10% and <40%) or high ([&ge;]40%). Biomarkers were compared between primary (DX/RD) and MR, and between pre- vs post-NAC (DX-RD) samples. Correlations between markers, quantification methods, inferred PAM50 subtype, and clinical variables of interest were evaluated. Results: A total of 359 samples from 110 patients with TNBC with data available from at least one platform were included in the analysis. HER2-low prevalence at DX, RD, and MR was: 51% (50/98), 40% (21/53), and 27% (16/60); TROP2 high/medium was 90% (47/52), 91% (42/46), and 88% (28/32); PD-L1-high was 51%, 50%, and 38% (9/24); and sTILs-high/medium was 88% (59/67), 80% (40/50), and 49% (17/35), respectively. While TROP2-high/medium vs low remained stable over time, HER2 IHC and sTILs significantly decreased from DX/RD to MR samples, both at the cohort-level (HER2, p=0.0081; sTILs, p=4.6x10e-5) and longitudinal patient-level (HER2, p=0.030; sTILs, p=0.0077), with a similar decreasing trend for PD-L1 that did not reach statistical significance. HER2 concordance (0 vs low) between L-IHC and C-IHC was 78% (91/116). ERBB2, TACSTD2 and CD274 mRNA expression were significantly correlated with IHC protein levels, though only TACSTD2 had limited overlap in distribution of gene expression between high/medium vs low groups. Strong correlation between protein membrane staining intensity from computational pathology, protein expression measured by MS, and pathologist-assed IHC was observed across all biomarkers tested by each method. In comparisons between biomarkers, pathologist-assessed PD-L1 IHC and sTILs were significantly correlated (p=0.0001); 94% (51/54) of PD-L1-high tumors were classified as sTILs high/medium. PAM50 subtype was not significantly correlated with time point or biomarker status, although there was a trend toward more HER2-enriched tumors in HER2-low (20%, 5/25) vs HER2-0 (6%, 3/52) (p=0.086). Across biomarkers and clinical variables, an association between age and sTILs was observed (p=0.038, FDR=0.42) due to a decrease in sTILs high/medium tumors with age, primarily driven by post-treatment (RD/MR) but not DX samples. Conclusions: Multi-platform and multi-omics profiling in this large unique cohort of longitudinal TNBC samples revealed distinct patterns of expression and dynamic changes of key biomarkers of interest for targeted therapies. Given variability with manual IHC scoring, improved methods for quantification of expression may help optimize treatment selection in an individualized manner.

Background & AimsHepatocellular carcinoma (HCC) frequently exhibits resistance to immune checkpoint inhibitors (ICIs), particularly in {beta} -catenin-driven tumors characterized by immune exclusion. While the Unfolded Protein Response (UPR) and the Integrated Stress Responses (ISR) enable tumor adaptation to metabolic stress their role in shaping tumor immunogenicity remains incompletely understood. We investigated whether ATF4, a central effector of the integrated stress response, couples metabolic reprogramming to suppression of anti-tumor immunity in HCC. MethodsWe combined transcriptomic analyses across three independent human HCC cohorts with mechanistic studies using an immunotherapy-resistant MYC/{beta}-catenin-driven murine HCC model. We integrated CRISPR/Cas9-mediated deletion of Atf4 with RNA-sequencing and targeted metabolomics. The impact of tumor-derived metabolites on macrophage differentiation and polarization was evaluated using primary bone marrow-derived cells. Therapeutic responses were evaluated in orthotopic and subcutaneous models treated with anti-PD-1 and anti-VEGFA. ResultsATF4 and XBP1 transcriptional signatures are selectively enriched in human HCC and associate with poor prognosis, vascular invasion, and an immunosuppressive myeloid-enriched tumor microenvironment. Genetic ablation of Atf4 markedly suppressed tumor growth in immunocompetent but not immunodeficient hosts, establishing a requirement for immune-mediated tumor control. Mechanistically, Atf4 loss downregulated Aldh18a1 and disrupted proline biosynthesis, resulting in extracellular proline depletion. This proline-deficient environment abrogated monocyte-to-macrophage differentiation and decreased M2 polarization, thereby reshaping the tumor microenvironment toward enhanced T cell infiltration and activation. Functionally, Atf4-deficient tumors exhibited restored sensitivity to anti-PD-1 monotherapy and showed pronounced responses to combined anti-PD-1/anti-VEGFA treatment in aggressive orthotopic models. ConclusionATF4 programs a proline-dependent metabolic axis that sustains macrophage-mediated immunosuppression and immune evasion in {beta}-catenin-driven HCC. Disruption of this pathway converts immune-excluded tumors into T cell-inflamed states and restores responsiveness to immunotherapy. By governing proline homeostasis and macrophage-mediated immunosuppression, ATF4 is a key metabolic checkpoint for immune evasion, linking stress adaptation to immune escape and a candidate therapeutic target in HCC. Impact and implicationsWe identify ATF4 as a crucial metabolic-immune orchestrator that sustains myeloid-driven immune evasion in {beta}-catenin-dependent HCC through proline-dependent circuitry. Disrupting the ATF4-proline axis converts immune-desert tumors into T cell-inflamed lesions by blocking macrophage differentiation, thereby sensitizing tumors to immune checkpoint therapy. This work positions ATF4 as a tractable therapeutic target to overcome immunotherapy resistance in HCC. Graphical abstract Highlights- ATF4 orchestrates an immunosuppressive tumor microenvironment in HCC by coupling metabolic stress adaptation to immune evasion. - Ablation of ATF4 disrupts proline biosynthesis, leading to a marked depletion of extracellular proline. - Cancer cell-derived proline availability contributes to macrophage differentiation and M2 polarization; its loss restores T cell-mediated anti-tumor surveillance and sensitizes beta-catenin-driven HCC to immune checkpoint blockade.

Barretts esophagus (BE) is the precursor lesion of esophageal adenocarcinoma (EAC). It affects approximately 5% of adults in the United States and significantly increases the risk of developing EAC. However, current surveillance strategies cannot reliably distinguish patients who will progress from those who will remain stable. Direct studies of progressor BE are extremely limited due to availability of tissue with known progression outcomes, and have largely been restricted to genomic profiling approaches. The premalignant cellular landscape of progressor BE remains poorly understood. Here, we used complementary spatial transcriptomic and proteomic imaging to profile 34 non-dysplastic BE patients under endoscopic surveillance, including those who subsequently progressed to dysplasia or EAC, termed "Progressors" and those who remained stable, termed "Non-progressors". Transcriptomics based Xenium analysis captured 974,604 cells across 70 whole-biopsy regions, while protein based imaging mass cytometry profiled 372,242 cells across 119 selected regions. FUME-TCRseq further quantified T cell clonotypes from matched tissues scrolls. Cellular composition was generally similar between Progressors and Non-progressors. However, Progressors showed increased intestinal Barretts columnar cells, B cells and gastric progenitor-like cells, together with enhanced immune-epithelial interactions, whereas Non-progressors retained coordinated stromal organization. Spatial interaction features strongly outperformed cell composition and density for progression prediction. Combined spatial interaction model achieved an area under the curve (AUC) of 0.97, compared with 0.62 and 0.68 for comparison and density alone. Complementary imaging mass cytometry further resolved the underlying immune programs, identifying cytotoxic and antigen presenting myeloid features enriched in progressors, and CD56 associated memory T cell interactions enriched in non progressors. Together, these findings support a model that BE progression is driven by progressive remodeling of epithelial-immune-stromal architecture rather than emergence of distinct dysplasia-like cell subsets. Increased T cell clonal diversity and recruitment of cytotoxic and antigen-presenting immune niches may also reflect an evolving response to genomic alteration prior to dysplasia. These results establish spatial tissue architecture, rather than specific cell types, captures progression associated microenvironmental states in BE and provides a framework for spatially informed patient stratification and early cancer risk assessment.

Background: CD8+ tumor-infiltrating lymphocytes (TILs) are established prognostic markers in colorectal cancer, yet the clinical significance of CD103+CD8+ tissue-resident memory-like (TRM-like) T cells in locally advanced rectal cancer (LARC) after neoadjuvant chemoradiotherapy (NACRT) remains unknown. Methods: We quantified CD8+ and CD103+CD8+ T-cell densities in stromal and intratumoral compartments of post-NACRT resection specimens from 40 LARC patients using Cu-Cyto, a deep learning-based imaging cytometry platform. Associations with survival, pathological response, and adjuvant chemotherapy (AC) were examined. Treatment-induced T-cell dynamics were assessed in paired pretreatment biopsies and post-NACRT resections (n = 9). Results: High stromal CD103+CD8+ density independently predicted better 5-year RFS (67.4% vs. 12.1%, p < 0.001) and OS (80.0% vs. 26.6%, p = 0.016); intratumoral density showed no prognostic significance. Pathological response correlated with stromal CD8+ but not CD103+CD8+ density. Paired analysis revealed a selective non-expansion of the CD103+ subset: stromal CD8+ T cells increased significantly after NACRT while CD103+CD8+ density remained unchanged. AC may preferentially benefit patients with low stromal CD103+CD8+ density. Conclusions: Stromal CD103+CD8+ T-cell density is a robust independent prognostic biomarker in rectal cancer after NACRT that appears to reflect pre-existing rather than treatment-induced immunity. Given its stability across NACRT, pretreatment biopsy assessment may provide equivalent prognostic information, with potential implications for patient stratification before treatment initiation.

BackgroundBreast cancer exhibits extensive molecular heterogeneity across intrinsic subtypes, yet convergent metabolic reprogramming may represent an obligate feature of tumour initiation. We hypothesised that suppression of nuclear-encoded mitochondrial fatty acid oxidation (FAO) constitutes such a convergence point, defining a shared metabolic phenotype independent of subtype. MethodsRNA-seq data from 1,106 primary breast tumours and 113 normal-adjacent tissues (TCGA-BRCA) were intersected with 1,079 nuclear-encoded mitochondrial genes from MitoCarta 3.0. Differential expression was assessed using Welch t-test with Benjamini-Hochberg correction at all tumour stages, at Stage I specifically, and stratified across PAM50 subtypes. A 55-gene core FAO signature was derived by three-way intersection. Ten candidate genes were selected by pre-specified objective scoring, locked before any clinical testing. Gene set enrichment analysis (GSEA) was performed using MitoCarta 3.0 pathway annotations. Diagnostic performance, clinical associations, survival, and mutation independence were characterised. External validation used two independent GEO cohorts (GSE42568, n = 121; GSE109169, n = 50); prognostic validation used METABRIC (Molecular Taxonomy of Breast Cancer International Consortium; n = 1,980). DESeq2 was applied as methodological cross-validation. ResultsAmong 126 differentially expressed mitochondrial genes, fatty acid oxidation was the most significantly depleted pathway (normalised enrichment score -2.130; false discovery rate 0.001). The 55-gene core signature replicated in both external cohorts with 100% directional concordance (hypergeometric p < 10-{superscript 1}). All 10 candidate genes discriminated tumour from normal tissue (area under the curve 0.915-0.979) and demonstrated broad clinical associations. The composite FAO suppression score predicted overall survival in METABRIC (log-rank p = 7.82 x 10-) and MAOA achieved independent prognostic significance in multivariable Cox regression (hazard ratio 0.890; adjusted p = 0.009). DESeq2 cross-validation confirmed Spearman {rho} = 0.980 concordance. ConclusionsNuclear-encoded FAO suppression is a robust, pan-subtype feature of breast cancer detectable at Stage I and validated across independent platforms and cohorts. These 10 candidate genes constitute a consistent initiation-phase mitochondrial signature, implicating FAO suppression as a potential convergence point in breast cancer oncogenesis and motivating targeted functional investigation.

Invasive lobular carcinoma (ILC) is the most frequently diagnosed special histological subtype of invasive breast cancer and accounts for 10 - 15% of all cases. The pathognomonic hallmark of ILC is the genetic loss of E-cadherin (CDH1) causing the disruption of adherens junctions and resulting in discohesive, linear growth. To better understand the role of E-cadherin in ILC metastasis, we generated three ILC cell lines, MDA-MB-134-VI, SUM44PE, and BCK4, with inducible E-cadherin expression, resulting in successful restoration of functional adherens junctions. E-cadherin expression reduced growth in 2D culture, and that effect was even greater in 3D ultra-low attachment (ULA) conditions where increased cell death was consistent with the previously described role of E-cadherin in anoikis. E-cadherin expression did not rescue the lack of migration and invasion of ILC cell line models; however, it decreased haptotaxis and increased adherence to Collagen I in SUM44 cells. There was no significant effect of E-cadherin expression on primary orthotopic tumor growth, but spontaneous metastasis to the reproductive tract, brain, and GI tract was reduced. Inhibition of metastasis to the reproductive tract and brain was also seen after tail vein injection of MDA-MB-134 E-cadherin-expressing cells. In summary, overexpression of functional E-cadherin in ILC models has some, but limited, effects on 2D growth in vitro and primary tumor growth in vivo, but there are pronounced effects on 3D ULA growth and metastases in vivo, with stronger effects on metastatic sites enriched in patients with ILC, especially the reproductive and GI tracts.

Background Background breast features are frequently noted in pathology reports alongside invasive breast cancer but rarely factor into prognosis or treatment decisions. Their relationship to tumor characteristics and patient outcomes remains incompletely characterised. Methods We conducted a retrospective cohort study of 7,603 patients with Stage I-III invasive breast cancer (diagnosed 1991-2022, age <80 years) from the Joint Breast Cancer Registry in Singapore. Natural language processing (NLP) was applied to 9,754 free-text pathology reports to extract co-existing background breast features, with accuracy validated by dual-reviewer assessment of 200 reports. Unsupervised hierarchical clustering grouped extracted features into three categories. Associations with tumor characteristics were assessed by multinomial logistic regression, and ten-year overall survival by Cox proportional hazards models (median follow-up 9.6 years; 620 deaths). Results Here we show that NLP-based extraction of background breast features from routine pathology reports achieves an accuracy of over 90% across features. Lobular neoplasia and benign proliferative changes are associated with less aggressive tumor characteristics, whereas early neoplastic and papillary lesions are more prevalent in HER2-enriched and luminal B tumor subtypes. Benign proliferative changes are associated with better survival in age- and year-adjusted models (hazard ratio 0.91, 95% CI 0.86-0.97), but this association is attenuated after adjustment for stage and subtype. Conclusions NLP-enabled extraction of background breast features from pathology text is feasible at scale. These features reflect tumor biology but do not independently add prognostic information beyond established clinical variables.

Purpose: The prognostic role of tumor-infiltrating lymphocytes in luminal breast cancer remains uncertain, partly because density-based metrics do not capture spatial interactions between immune cell subsets. We developed a density-independent spatial metric quantifying macrophage-T cell proximity and assessed its prognostic value. Experimental Design: Using multiplex immunohistochemistry across three breast cancer cohorts (exploratory, n = 17; discovery, n = 687; validation, n = 305), we measured nearest-neighbor distances from T cells to M1-like and M2-like macrophages, benchmarked against a randomly subsampled total macrophage pool. We defined the Macrophage Spatial Polarity Index (MSPI) as the difference between M2-to-T cell and M1-to-T cell affinity scores, where higher values reflect an M2-dominated spatial phenotype. Cox regression was used to assess associations with distant disease-free survival (discovery) and overall survival (validation). Results: M2-like macrophages preferentially localized near T cells, independent of cell density. Higher MSPI was associated with shorter survival in luminal cancers (discovery: HR = 1.45, p < 0.001), with the strongest effect in young women with early-stage disease (HR = 2.16, p < 0.0001). MSPI remained independently prognostic after adjustment for stage, systemic treatment, and diagnosis period (HR = 2.31, 95% CI 1.73-3.09, p < 0.0001) and was non-significant in HER2-positive and triple-negative subtypes. Validation in an independent ER-positive cohort confirmed the finding (HR = 1.30, p = 0.004). Pooled analysis yielded HR = 2.13 (95% CI 1.68-2.70, p = 3.45 x 10-10). Conclusions: MSPI is a robust prognostic biomarker in luminal breast cancer, particularly in young women with early-stage disease, warranting further validation for risk stratification and therapeutic guidance.

IntroductionCellular differentiation and lineage commitment are known to be associated with differences in DNA methylation. Leiomyosarcoma (LMS) is a tumor thought to originate from smooth muscle cells in the walls of vessels in the soft tissue (STLMS) or from the uterine myometrium (ULMS). Here, we identify the methylation signatures of normal smooth muscle cells from blood vessels and the uterine wall and compare these with those found in STLMS and ULMS. We hypothesized that these methylation signatures could be used to assign a smooth muscle subtype of origin to individual leiomyosarcomas, and that tumors of different origin would show biological differences with potential therapeutic relevance. MethodsTo define methylation profiles for smooth muscle from vessel walls versus those found in myometrium, EPIC methylation profiling was performed on DNA from 49 formalin-fixed paraffin-embedded (FFPE) normal smooth muscle samples. A supervised machine learning algorithm (Random Forest) was used to distinguish the methylation patterns of normal smooth muscle cells in vessel walls from those in the myometrium. The resulting classifier was applied to methylation data on 67 cases of LMS with corresponding bulk RNAseq data to identify which tumors showed a methylation signature most consistent with either blood vessel wall (LMSvessel) or myometrial smooth muscle (LMSwall). A custom signature matrix derived from scRNAseq data from 6 samples of LMS was used in CIBERSORTx analysis to compare the cellular composition of LMS cases with a vessel or uterine wall methylation signature. ResultsA high degree of correlation was found between the known site of origin for LMS (STLMS vs ULMS) and the methylation signature derived from different types of normal smooth muscle. LMSwall tumors compared to LMSvessel tumors had significantly higher activation of the PD-1 checkpoint pathway in RNAseq analysis. Digital flow cytometry by CIBERSORTx analysis showed an increased expression of transcriptomic signatures of several immune cell subtypes in LMSvessel tumors. ConclusionUsing a supervised machine learning approach we classified LMS samples as either showing a high similarity in methylation patterns to normal smooth muscle cells of either the vessel wall or the myometrium. We found a correlation between LMS showing either a "vessel" or "muscle wall" methylation signature and their site of origin, but notably we also identified some exceptions. When classified based on their methylation signature LMSwall and LMSvessel differed in their PD-1 pathway activation and in their predicted immune cell populations, suggesting potential implications for immunotherapeutic approaches.

INTRODUCIONTumor cell infiltration in regional lymph nodes is a strong prognostic marker, guiding treatment decisions in breast cancer. While the immune cell composition in primary tumors has been more widely explored in later years, the immune cell composition of the sentinel node (SN) and axillary lymph nodes (ALN) remains understudied. A better understanding of how primary tumor and metastatic tumor cells alter the nodal immune microenvironment can shed light on metastasis and cancer progression to unveil new treatment strategies. MATERIALS AND METHODSFrom a prospective clinical cohort of 458 treatment-naive patients with primary operable breast cancer, we performed comprehensive immunophenotypic analysis using mass cytometry analysis of non-metastatic (SN-) and metastatic (SN+) and ALN (ALN+) lymph nodes. RESULTSAs expected, patients with ALN+ cases had a shorter time to distant metastases than SN+ and SN- cases. We identified an exhausted T-cell phenotype and an increase in Germinal Center B (GC B) cells and plasma cells in ALN+ samples compared to SN- samples, both in the whole cohort as well as when investigating estrogen-receptor positive (ER+) patients only. There were no differences in immune cell composition across breast cancer (BC) subtypes within SN-samples. SN+ samples from triple negative BC (TNBC) showed a trend towards increased abundance of GC B and plasma cells, similar to more advanced ALN+, suggesting that smaller TN metastases may trigger an immune activation at an early stage of dissemination. Further analysis of SN- samples from ER+ patients revealed a subset of patients where the immune response had a more exhausted T-cell phenotype. This group was enriched for lymph nodes that were deemed negative by ordinary pathology examination (microscopy) but had detectable tumor cells by CyTOF analysis. CONCLUSIONThe immune profiles of SN and ALN samples from breast cancer patients are highly diverse, showing limited associations to BC subtype, clinical parameters or patient outcome. Metastatic tumor cells play a significant role in driving T-cell exhaustion and immunosuppression. Notably, in approximately 50% of the ER+ samples, T-cell exhaustion was detectable. This coincides with the presence of tumor cells identified by CyTOF, which were likely missed by conventional pathological examination. These findings suggest that small tumor deposits alter the immune composition, and the immune profile reveals the presence of tumor cells.

BackgroundAntibody-mediated blockade of innate receptor-MHC-I interactions represents a promising strategy to enhance anti-tumor immunity, particularly against metastatic cancers resistant to conventional checkpoint inhibitors. In this study, we investigated the effects of the pan anti-MHC-I monoclonal antibody M1/42, which targets MHC-I interactions with Ly49, selectively expressed on murine NK cell subsets. MethodsWe administered M1/42 to mice and assayed the proliferation and activation immune cells. Anti-tumor activity of growth and metastasis of checkpoint inhibitor-resistant pancreatic ductal adenocarcoma (PDAC) and B16F10 melanoma were assessed, complemented by extensive cellular phenotypic and RNA expression analysis. Binding and cryo-electron microscopic (cryo-EM) and X-ray crystallographic structural studies of M1/42 complexed with the mouse MHC-I molecule, H2-Dd, examined the Ab interaction site in comparison with those of Ly49 inhibitory receptors. ResultsM1/42 administration in mice robustly unleashed the proliferation and activation of natural killer (NK) cells, memory CD4+ and CD8+ T cells, dendritic cells, and macrophages in both lymphoid and non-lymphoid tissues, independent of Fc{gamma} receptors. M1/42 significantly restricted the growth and metastasis of checkpoint inhibitor-resistant pancreatic ductal adenocarcinoma (PDAC) and B16F10 melanoma in the liver and lungs, accompanied by increased tumor infiltration of effector CD8+ T cells, reduction of T regulatory cells, and a pro-inflammatory cytokine milieu. The anti-tumor effects of M1/42 depend on NK cells and are associated with upregulation of genes involved in antigen processing, interferon gamma responsiveness, and Th1 cytokine production, while downregulating inhibitory PD1/11 signaling. Structural analysis indicated that the effect of M1/42 on Ly49/MHC-I interactions was not due to direct steric competition. ConclusionsCollectively, these findings demonstrate that M1/42 unleashes coordinated innate and adaptive immune responses, overcoming tumor-induced immunosuppression and resistance to checkpoint blockade. This approach represents a paradigm shift in cancer immunotherapy, offering potential for more effective treatment of metastatic cancers that evade immune surveillance through MHC-I modulation. KEY MESSAGESO_ST_ABSWhat is already known on this topicC_ST_ABSA pan anti-mouse MHC-I mAb (M1/42) blocks interaction with several NK inhibitory receptors (Ly49A or Ly49C) resulting in NK cell activation and anti-viral and anti-tumor responses in vitro and in vivo. Other pan anti-human MHC-I mAbs (DX17 and W6/32) function similarly, blocking LILRB inhibitory receptor interaction of myeloid cells and NK cells. These stimulate human immune cells in humanized mouse models. What this study addsThis study analyzes the effects of the pan anti-mouse MHC-I mAb on NK and myeloid cell activation in detail, in the absence of T or B cells, and independent of FcR interaction. Additionally we analyze several mouse models of metastatic tumor progression, indicative of the progressive activation not only of the innate immune response, but also adaptive responses. The molecular mechanism of the mAb blocking of inhibitory receptors is revealed by cryo-EM and X-ray structures of M1/42 Fab/MHC-I (H2-Dd) complexes. How this study might affect research, practice, or policyElucidation of the details of the inhibitory effects of the mouse pan anti-mouse MHC-I mAb provides not only a more advanced understanding of the murine model system, but suggests additional functional avenues to be explored using the parallel an anti-human MHC-I mAbs.

IntroductionCraniopharyngioma (CP) comprises two distinct histological subtypes, adamantinomatous craniopharyngioma (ACP) and papillary craniopharyngioma (PCP), which are often challenging to distinguish preoperatively. Approximately 95% of PCP harbor the BRAF V600E mutation, whereas ACP lacks this alteration, making PCP uniquely sensitive to BRAF and MEK inhibition. However, in the absence of a reliable preoperative classification strategy, targeted therapy has been limited to recurrent disease or to cases with histological confirmation. This study aims to describe and prospectively evaluate a pragmatic preoperative classification strategy and short-course neoadjuvant BRAF and MEK inhibition followed by surgery in newly diagnosed, preoperatively classified PCP. Methods and analysisThis is a prospective, single-arm, open-label study. Patients with newly diagnosed craniopharyngioma will be screened using an integrated preoperative strategy combining imaging-based prediction and selective cerebrospinal fluid (CSF) cell-free DNA testing for BRAF V600E in indeterminate cases. Twelve participants preoperatively predicted as PCP and BRAF V600E positive will receive dabrafenib 150 mg twice daily plus trametinib 2 mg once daily for up to three 28-day cycles, followed by transnasal endoscopic surgery. Assessments are scheduled at days 7, 14, 28, 56, and 84 until surgery. The primary endpoint is objective response rate, assessed by contrast-enhanced MRI using RANO 2.0 criteria. Secondary outcomes include progression-free survival, local disease control, endocrine outcomes of the hypothalamic-pituitary-adrenal and hypothalamic-pituitary-thyroid axes, visual and cognitive outcomes, postoperative diabetes insipidus, surgical complexity, and concordance between the preoperative classification strategy and postoperative pathology and BRAF V600E status. Exploratory analyses will evaluate treatment-related changes in tumor vascularity, tissue characteristics, and post-treatment molecular alterations in tumor tissue. Ethics and disseminationThis protocol has been approved by the Ethics Committee of Huashan Hospital, Fudan University (KY2024-028). Written informed consent will be obtained from all participants. Results will be disseminated through peer-reviewed publications and scientific conferences. Trial registration numberChiCTR2400081636 STRENGTHS AND LIMITATIONS OF THIS STUDYO_ST_ABSStrengthC_ST_ABS[tpltrtarr] This study proposes an integrated, clinically applicable preoperative strategy that combines imaging-based prediction with selective cerebrospinal fluid cell-free DNA analysis to identify papillary craniopharyngioma (PCP) prior to surgery. [tpltrtarr]It prospectively evaluates short-course neoadjuvant BRAF and MEK inhibition in newly diagnosed PCP, addressing a clinically relevant gap in current management. [tpltrtarr]Standardized, multidimensional assessments are performed across the neoadjuvant, perioperative, and early postoperative periods, capturing radiographic, surgical, endocrine, visual, and cognitive outcomes. Limitation[tpltrtarr] The single-arm, open-label design without a surgical control group limits direct comparison with upfront surgery. [tpltrtarr]Despite the integrated prediction strategy, preoperative misclassification cannot be excluded entirely.

Cutaneous squamous cell carcinoma (cSCC) is a common skin cancer associated with substantial morbidity and mortality in advanced stages. Despite its well-described stepwise progression from actinic keratosis to invasive disease, robust molecular markers for stage discrimination and clinical decision-making remain limited. We sought to define the transcriptional continuum underlying cSCC progression, identify stage-associated biomarkers, and assess the broader relevance of these programs across human malignancies. Bulk RNA sequencing (HTG EdgeSeq) and spatial transcriptomics (GeoMx) were performed on biopsies from eight patients, each presenting multiple disease stages (healthy skin, premalignant lesion, tumor core, and invasive front) within the same lesion field, enabling within-patient analysis of progression. Spatial transcriptomic analyses identified more than 2,000 differentially expressed genes whose expression varied across disease stages. These genes were organized into 18 coordinated expression programs reflecting progressive biological rewiring during tumor evolution. Proliferation, extracellular matrix remodeling, inflammation, and stress-response pathways were progressively upregulated, whereas epithelial differentiation and metabolic processes, including lipid and amino acid metabolism, were downregulated. Macrophages exhibited distinct metabolic reprogramming, with increased purine metabolism, glycolysis, and pyruvate metabolism across progression. To evaluate the broader clinical relevance of these progression-associated programs, we developed a reproducible Snakemake pipeline to systematically screen 32 solid and hematologic malignancies from The Cancer Genome Atlas (TCGA). A combined cSCC-progression signature was significantly associated with poor overall survival (P < 0.05) in 10 additional cancer types. Finally, we identified 12 stage-informative biomarkers, whose spatially restricted expression patterns were validated using Visium HD. This study provides a spatially resolved and stage-aware transcriptomic map of cSCC progression, identifies coordinated gene programs underlying disease evolution, and defines progression-associated signatures with prognostic relevance across multiple cancers, highlighting their potential translational value.

PurposeBladder cancer (BLCA) is a heterogeneous tumor type. Only one third of muscle-invasive (MIBC) patients respond to immune checkpoint inhibitors (ICIs). Reliable resistance markers are needed to guide clinical decisions. We investigated the nerve growth factor receptor (NGFR) in BLCA and analyzed its correlation with disease progression and response to immunotherapy. Experimental DesignWe analyzed NGFR expression in BLCA cell lines, organoids, mouse models and patient samples. The cohorts used were The Cancer Genome Atlas (TCGA), enriched in muscle-invasive bladder cancer (MIBC) (n=407); IMvigor210, representing MIBC patients treated with ICIs (n=348); and UROMOL2, as a non-muscle-invasive bladder cancer (NMIBC)-specific cohort (n=535). IMvigor010 was also included (n=728). Patients were stratified by NGFR expression quartiles. We analyzed survival and tumor subtypes and performed stromal deconvolution and functional profiling. We assessed stemness- and invasion-related features in SCaBER cells. ResultsNGFR marks a basal tumor cell subcluster and is independently associated with poor prognosis in TCGA and IMvigor210. NGFR-high tumors show stromal content enriched in cancer-associated fibroblasts, lower neoantigen burden, higher CD8+ T effector signature together with an immune-excluded phenotype, and a CAF-specific TGF{beta} signature. In the immunotherapy-treated cohort, high NGFR expression was also associated with poorer outcome. Functionally, NGFR appears to promote a stem-like/pro-invasive program in BLCA cells. ConclusionsNGFR identifies a basal-like BLCA subpopulation linked to poor survival, while its association with immunotherapy response requires further validation. In addition, our in vitro analyses support a role of NGFR in stem-like and invasive traits, highlighting its relevance as a biomarker in BLCA.

BackgroundPancreatic ductal adenocarcinoma (PDAC) is the paradigmatic immunotherapy-refractory cancer, with a 5-year survival of approximately 12% and minimal benefit from immune checkpoint blockade (ICB). The dominant mechanistic explanation classifies PDAC as a T cell-excluded "cold" tumor, implying that no functional anti-tumor T cells are available for checkpoint release. Whether this Block-strategy view is correct has not been re-examined under integrated evasion-framework analysis. MethodsWe applied a previously developed 16-module immune evasion framework to TCGA-PAAD (n=183), integrated with hub-cytokine analysis (IL-10/TGF-{beta}), Kv1.3-immune channelome data, and clinical trial mapping (12,007 trials). Single-cell validation used two independent PDAC cohorts retrieved through TISCH2: PAAD_CRA001160 (Peng 2019, 35 samples [24 PDAC + 11 adjacent normal], 57,443 cells) and PAAD_GSE154778 (Lin 2020, 16 samples, 14,953 cells), examined for CD8A, TOX, PRF1, KCNA3, and FAP expression by cell type. ResultsPDAC scored highest in CAF Wall (z=0.768) and Platelet Cloak (z=0.663) modules; strategy classification yielded Brake -- not Block -- driven by a positive KCNA3-survival relationship (HR=0.649, 95% CI 0.43-0.97, p=0.037). Single-cell qualitative analysis of TISCH2 violin plots showed that CD8 exhausted T cells (CD8Tex) carried (i) high CD8A, (ii) the highest TOX expression among annotated cell types, (iii) preserved PRF1, and (iv) high KCNA3 expression. FAP was strongly localized to fibroblasts (peak [~]3.0 vs. <0.5 elsewhere). The pattern was reproduced in the second cohort. The optimal three-module attack (MHC restoration + CAF disruption + VEGF blockade) suppressed 10 of 16 evasion modules in silico (62.5%); zero of 370 PDAC immunotherapy trials test this combination. ConclusionsPDAC may not be T cell-cold but T cell-trapped: CD8 T cells with intact Kv1.3 channels appear immobilized behind a FAP-positive cancer-associated fibroblast wall. ICB monotherapy is mechanistically insufficient because the brake is engaged on T cells that cannot reach the tumor. The framework predicts that triple-targeted intervention -- checkpoint release + CAF wall disruption + vascular normalization -- is the minimum effective strategy. This is a hypothesis-generating computational analysis; prospective experimental and clinical validation are required.

Pain in pancreatic ductal adenocarcinoma (PDAC) is associated with poor survival, but whether altered pain processing carries prognostic significance is unknown. We analyzed a prospective cohort of 143 patients with PDAC who underwent pancreatic quantitative sensory testing (PQST) after diagnosis. Patients were classified as having normal pain processing (n=84), segmental hyperalgesia (n=30), or widespread hyperalgesia (n=29). Survival was measured from the date of P-QST assessment. During follow-up, 70 deaths occurred. Widespread hyperalgesia was associated with increased mortality in unadjusted Cox analysis (HR 1.96, 95% CI 1.14,3.35) and after adjustment for age, sex, tumor stage, comorbidity, opioid treatment, and body mass index (adjusted HR 2.33, 95% CI 1.30,4.15). Segmental hyperalgesia was not associated with mortality. Kaplan Meier analysis demonstrated lower survival probability in the widespread hyperalgesia group (log rank p=0.025). These findings suggest that widespread hyperalgesia, reflecting altered central pain processing, identifies a subgroup of PDAC patients at increased risk of mortality independent of conventional clinical factors.

Aims Active surveillance (AS) allows selected men with localized prostate cancer to defer curative therapy and reduce treatment morbidity. Conversion from AS to treatment is commonly triggered by Gleason grade group (GGG) upgrading on confirmatory biopsy. We developed and validated a digital pathology artificial intelligence (DPAI) biomarker to predict GGG upgrading in AS-eligible patients. Materials & Methods The DPAI model was trained using histopathology image features from diagnostic biopsies of 998 patients and validated in an independent cohort of 296 patients meeting criteria for AS. Logistic regression estimated the probability of confirmatory-biopsy GGG increase, and feature selection identified the most predictive variables. Results AI-GUR (Artificial Intelligence-Gleason Upgrade Risk) predicted GGG reclassification at confirmatory biopsy (OR 1.60; p=0.0003), and provided information beyond conventional stratification (risk group, CAPRA) and cribriform morphology (all p<0.01). Predicted risks were similar across time from diagnosis (~10-15% to ~85% at 1, 1.5, or 2 years; p for time=0.50), consistent with initial biopsy mischaracterization rather than time-dependent progression. Conclusions AI-GUR provides individualized estimates of confirmatory-biopsy GGG upgrading for AS candidates. Using DPAI may improve shared decision-making by complementing standard clinicopathologic tools and molecular testing using the same biopsy specimen, while informing the likelihood of grade upgrade at confirmation.

Patients with gastric intestinal metaplasia (GIM), a precancerous lesion, are at high risk for progressing to gastric cancer. Identifying these patients is critical to enable gastric cancer interception. Current approaches rely primarily on histologic evaluation of GIM severity and extent, which may be improved by incorporating molecular features that distinguish high-risk lesions. Our prior single-cell and spatial transcriptomics study identified differentially expressed genes associated with the highest-risk category of GIM. They included ANPEP expressed in enterocytes and CPS1 and OLFM4 expressed in intestinal stem-like or progenitor cells. We evaluated the protein expression and localization of these three markers to understand the cellular features associated with GIM risk and their spatial distribution within metaplastic tissues. Using multiplex immunofluorescence, whole slide image analysis and confocal microscopy, we examined protein expression from 100 tissue biopsies annotated for metaplasia severity using the Operative Link on Gastric Intestinal Metaplasia Assessment (OLGIM) system. Tissue samples included control gastric tissue, GIM, dysplasia and adenocarcinoma. Quantitative whole slide image analysis demonstrated that CPS1 expression had a modest association with disease severity. Although ANPEP was strongly associated with GIM severity, it was also frequently expressed in stromal regions outside epithelial glands. In contrast, OLFM4 expression was largely restricted to epithelial glands and showed a strong association with increased OLGIM severity. These OLFM4-positive epithelial cells were present in discrete glandular foci that expanded with increasing severity of metaplasia. Within individual metaplastic glands, OLFM4 expression was highest at the gland base with decreased expression toward the gland surface. Overall, these findings identified OLFM4 as a protein marker associated with high-risk GIM. The spatial organization of OLFM4-expressing cells at the base of metaplastic glands and their focal expansion within tissues suggest the presence of a stem cell-like epithelial compartment that may contribute to the progression of GIM towards gastric cancer.

ObjectiveTo determine whether pyroptosis-related transcription in systemic sclerosis skin forms a translayer spatial architecture rather than a single coextensive inflammatory program. MethodsWe reanalyzed public Visium formalin-fixed paraffin-embedded skin sections (4 healthy controls, 9 systemic sclerosis) from a discovery cohort and tested prespecified endpoints in 10 independent systemic sclerosis sections. The tissue section was the inferential unit. Epidermal versus dermal contrasts within each section were evaluated for inflammasome-related and gasdermin genes, followed by cell2location spatial deconvolution and partial correlation adjusted for endothelial context in the dermis. ResultsNLRP1, PYCARD, and CASP4 displayed epidermal bias in all 13 discovery sections, whereas GSDMD displayed dermal bias in all 13. This spatial separation was detectable in healthy skin and appeared stronger in systemic sclerosis. A tier 1 triad captured the epidermal signal better than broader composites (dilution 35.5%; P = 0.0002). In an independent systemic sclerosis cohort, the dermal gasdermin endpoint retained its direction in 8 of 10 sections and the epidermal inflammasome-related endpoint in 10 of 10. Spatial deconvolution indicated that dermal GSDMD associated most strongly with estimated endothelial abundance in both healthy and systemic sclerosis skin. The IFN{gamma}-GSDMD association remained positive after endothelial adjustment across sections, compatible with an additional IFN{gamma} component. ConclusionSystemic sclerosis skin harbors a reproducible translayer pyroptosis-related transcriptional architecture in which upstream epidermal inflammasome-related transcription and dermal GSDMD expression are spatially dissociated. This organization, detectable in healthy skin and often stronger in SSc, may warrant future mechanistic and therapeutic interrogation by compartment.