Citations

Our study examined healthy human MASH and MASH-associated hepatocellular carcinoma (MASH-HCC) livers using bulk and scRNA sequencing, spatial transcriptomics, and immunohistochemistry. We found that ACSLs displayed differential and spatially heterogeneous expression. ACSL4 was abundant in tumor tissues, whereas ACSL5 was elevated in noncancerous MASH tissues. ACSL4 was mainly found in immune cells like natural killer cells and natural killer T cells in murine MASH-HCC, suggesting its role in tumor immune microenvironment modulation.

Abstract Purpose: Germline pathogenic variants (PV) in ATM increase the risk of pancreatic ductal adenocarcinoma (PDAC), but the underlying tumor biology of PDAC associated with germline PV in ATM has not been adequately explored. Experimental Design: Whole-genome, whole-exome, and RNA sequencing were performed on PDAC tumors from 25 germline ATM PV carriers diagnosed at Mayo Clinic between 2007 and 2017. Somatic and copy-number alterations, mutational signatures, transcriptomic subtypes, and the immune landscape were evaluated. Results: High-quality whole-exome and whole-genome sequencing were obtained from 21 and 15 tumors, respectively. Biallelic inactivation of ATM was observed in 87%, KRAS PV in 90%, CDKN2A homozygous loss in 60%, and TP53 alterations in <10% of these tumors. A predominant clock-like mutational signature was present in all samples. Whole-transcriptome analysis identified that the aberrantly differentiated endocrine exocrine subtype accounted for 18% of PDAC and was consistently associated with >5-year overall survival. In addition, a 28-gene expression–based signature associated with overall survival was identified and further validated in The Cancer Genome Atlas cohort. Immune landscape analysis through CODEX identified enriched CD4 T-helper cell/tumor interactions and reduced B7H3-high cell/tumor interactions in ATM PV carriers compared with noncarriers. Conclusions: The observed absence of TP53 PV and enrichment for CDKN2A alterations in ATM tumors, along with differences in the mutational signatures, transcriptomic subtypes and immune landscape, improve our understanding of the mechanistic pathways involved in PDAC development in germline ATM PV carriers and help identify potential targeted therapeutic strategies.

PURPOSE The development of colorectal liver metastases (CRLMs) is associated with poor prognosis, and recent data suggest that metastasis to the liver is associated with resistance to immunotherapy. We characterized the microenvironment of primary colorectal carcinomas (CRCs) relative to their synchronous CRLMs using a validated segmentation algorithm (QuantCRC) that quantifies 15 distinct morphologic tumor features. MATERIALS AND METHODS Adult patients with CRC with synchronous CRLM (N = 57) at Mayo Clinic were identified from the electronic health record. Routine tumor hematoxylin and eosin sections were digitized and reviewed for quality control. QuantCRC (Aiforia, Inc) was applied to digitized images to extract 15 GI pathologist predefined morphological features. Tumor features were compared between paired primary tumors and their synchronous CRLMs using the Wilcoxon signed-rank test overall and within subgroups. Linear regression models were used to find predictors of the paired differences in the distinct tumor morphological features. RESULTS The study included 57 patients (median age 59 years [IQR, 50-73], 51% female) with CRC primary and synchronous CRLM, and among primaries, 37 (65%) were left-sided. QuantCRC identified six of 15 morphological features that differed significantly between primaries and their CRLMs. Compared with the primary, CRLM showed reduced stroma, more high-grade tumor and necrosis, higher tumor–stromal ratio (TSR; all P < .05), and a trend toward increased tumor-infiltrating lymphocyte (TIL) density ( P = .052). Synchronous CRLM from patients with left-sided primary tumors had significantly higher TSR, percent high-grade, percent necrosis, and TIL density compared with the primary (all P values ≤0.04). Among right-sided primaries, CRLM had a significantly reduced percent mature stroma ( P = .0296) and a higher percent necrosis ( P = .0027). CONCLUSION Compared with the primary, synchronous CRLMs showed a higher TSR and increased high-grade tumor and necrosis, which are features of tumor aggressiveness and a metastatic phenotype.

AimsMucinous cystic neoplasms (MCN) are defined by the presence of an ovarian‐type stroma (OTS). Once ovarian stroma has become a requirement for the diagnosis of MCNs, studies using this criterion have disclosed that MCNs are seen almost exclusively (97%) in women. The occurrence of MCNs (with ovarian stroma) in men is exceedingly rare and raises questions about the origin of OTS and the role of hormones in tumourigenesis. This study aims to investigate the clinical and histopathological features of pancreatic or hepatic MCNs in men.Methods and resultsWe examined the MCN cases in men and compared them with age‐matched women. We further investigated MCN in premenopausal and postmenopausal women to explore the impact of hormonal status.The stromal cellularity tended to be lower in men as compared to women; however, limited numbers prevented statistical significance. Clinical presentation, tumour location, body mass index and cyst complexity were similar between men and age‐matched women, similarly in pre‐ and postmenopausal woman groups. All MCN cases, regardless of gender or hormonal status, showed OTS with positivity for oestrogen receptor (ER), androgen receptor (AR) and SF‐1 immunostains. Additionally, the presence of AR and ER‐beta in lining epithelial cells, in addition to the stromal cells, raised the probability for a potential role for local hormonal signalling in the pathogenesis of these tumours.ConclusionsMCNs in men had overlapping histopathologic and immunohistochemical profiles with those in women, regardless of menopausal status.

For over a century, scientists reported the disruption of normal nuclear shape and size in cancer. These changes have long been used as tools for diagnosis and staging of malignancies. However, to date, the mechanisms underlying these aberrant nuclear phenotypes and their biological significance remain poorly understood. Using a model of pancreatic ductal adenocarcinoma (PDAC), the major histological subtypes of pancreatic cancer, we found that oncogenic mutant KRAS reduces nuclear size. Transcriptomic and protein expression analysis of mutant KRAS–expressing PDAC cells revealed differential levels of several nuclear envelope–associated genes. Further analysis demonstrated the nuclear lamina protein, Emerin (EMD), acted downstream of KRAS to mediate nuclear size reduction in PDAC. Analysis of human PDAC samples showed that increased EMD expression associates with reduced nuclear size. Finally, in vivo genetic depletion of EMD in a mutant KRAS–driven PDAC model resulted in increased nuclear size and a reduced incidence of poorly differentiated PDAC. Thus, our data provide evidence of a potentially novel mechanism underlying nuclear size regulation and its effect in PDAC carcinogenesis.

Radiologists are integral members of the interdisciplinary team for patients with mucinous appendiceal neoplasms and can directly affect care by suggesting the diagnosis of pseudomyxoma peritonei, optimizing imaging protocols for evaluating peritoneal implants, and reporting the primary tumor and spilled tumor cells thoroughly.

e14551 Background: Extracellular vesicles (EVs) are microscopic particles released by all cell types with a distinct fingerprint reflecting the cell of origin. In patients with prostate cancer, PSMA+EVs have been associated with clinical outcomes. In this study, we investigated tumor-derived EVs (tdEVs) using the tumor-specific CD326 marker as a novel biomarker for pancreas ductal adenocarcinoma (PDAC). Methods: The study included patients with localized PDAC treated on a prospective phase 2 clinical trial evaluating a 15-fraction chemoradiation (CRT) regimen. Blood samples were obtained after induction chemotherapy (C) (prior to CRT) and in follow-up. 20 healthy controls were included. High-resolution flow cytometry enumerated levels of fluorescent antibody labelled tumor-specific CD326 (EpCAM)-positive EVs. All samples were de-identified and randomly coded. The technologist responsible for EV analysis was blinded to patient information and clinical data. Each sample was run in triplicate. Flow cytometry data was analyzed with custom-built software to automatically determine and apply gates and generate reports with scatter plots and EV concentrations for each combination of markers and data summaries. Results: tdEV data were analyzed from 70 patients with pre-CRT samples. Patients had mean age 66 years (9.0 standard deviation), with 60% ECOG 0, 43% borderline resectable and 48% locally advanced. Patients had a median 8 cycles of C prior to CRT, and 70% proceeded to surgery after CRT. 2-year overall survival (OS) was 54%. Patient samples showed elevated total CD326 EVs compared to the healthy controls (p = 0.0005). Furthermore, patient CD326 EVs revealed two distinct subpopulations: small (120-1,000nm) and large (1,000-3,000nm) size CD326 EVs. No large CD326 subpopulation was found in healthy donor samples. Higher pre-CRT levels of total CD326 and large CD326 EVs were associated with decreased progression-free survival (PFS) (hazard ratio (HR) = 2.38, p = 0.013 and HR = 2.017, p = 0.021) on multivariable models with surgical resection. Resection was associated with increased PFS (p < 0.0001), and the interaction terms did not meet significance (p = 0.083 and p = 0.21). No differences in pre-CRT total or large CD326 EVs were identified between patients with or without surgical resection (p = 0.72 and p = 0.83). CA19-9 levels were not predictive of clinical outcomes in this trial and showed no association with EV levels. Conclusions: We present an association between clinical outcomes and tdEVs in PDAC, highlighting their potential as a novel, independent biomarker. If validated, tdEVs may offer an opportunity to personalize care and improve risk stratification.

e14626 Background: Despite advancements in neoadjuvant therapy and surgical techniques, patients with pancreatic ductal adenocarcinoma (PDAC) often experience high recurrence rates after total neoadjuvant therapy (TNT) and resection. Existing tumor response scoring systems, such as the College of American Pathologists (CAP) guidelines, fail to stratify recurrence risk effectively, emphasizing the need for novel, objective approaches. Methods: This study evaluated spatial characteristics of residual cancer and stroma in a multi-site cohort of 203 patients with resected PDAC following TNT, not having achieved a major pathologic response (CAP 2 or 3). Whole slide images (WSI) of hematoxylin and eosin-stained sections were digitized and analyzed using artificial intelligence to perform tissue segmentation. Metrics quantifying spatial morphology and configuration, inspired by principles of landscape ecology, were computed to explore spatial features of the tumor microenvironment (TME). Statistical models (recursive partitioning and regression tree [RPRT] model and Cox model with backwards eliminations) incorporating these features were developed to stratify recurrence risk. Results: Five metrics were used for risk classification model build. Three models successfully classified patients into high- and low-risk groups based on spatial metrics. Models demonstrated moderate discriminatory power (C-statistics: 0.560–0.566) and showed that increased tumor fragmentation, like stromal patch density and cancer patch shape index, were strongly associated with improved outcomes. Conclusions: Integrating spatial metrics of cancer-stroma configuration enhances risk stratification beyond conventional scoring systems. Given increased tumor fragmentation is associated with improved outcomes, these data indirectly suggest ecological mechanisms of treatment resistance. This approach offers a pathway toward personalized post-operative management strategies to improve outcomes in PDAC. Risk classification models. Model Description Event/n Median DFS (95% CI) HR(95% CI) p-value C-statistics 1(RPRT) High risk: log standard deviation of the stroma shape index > 0.651 87 / 101 8.22(5.72 – 10.1) 1.64(1.20 – 2.25) 0.002 0.562 Low risk: log standard deviation of the stroma shape index ≤ 0.651 71 / 102 11.90(9.24 – 25.1) Ref 2(RPRT) High risk: log standard deviation of the stroma shape index > 0.651 & mean cancer shape index ≤ 1.775 58 / 63 7.23(5.19 – 9.63) 1.82(1.31 – 2.52) 0.0003 0.560 Low risk: (log standard deviation of the stroma shape index > 0.651 & mean cancer shape index > 1.775) or log standard deviation of the stroma shape index ≤ 0.651 100 / 140 11.57(9.24 – 17.92) Ref 3(Backwards elimination) High risk: PI * > median 86 / 101 8.02(6.08 – 9.86) 1.73(1.26 – 2.37) 0.0007 0.566 Low risk:PI * ≤ median 72 / 102 15.72(9.97 – 25.05) Ref *PI: (0.2701 * log mean stroma area) + (0.3905 * log edge density).

Abstract Background: The transcriptional cofactor Yes-associated protein (YAP) is activated in CCA pathophysiology. While canonical regulation by the Hippo pathway resulting in phosphorylation at serine 127 (S127) is inhibitory, SRC-family kinases (SFKs) phosphorylate YAP at tyrosine 357 (Y357), causing activation. Previously, cholangiocytes, hepatic progenitor cells (HPCs), and even mature hepatocytes were suggested as potential cells of origin of CCA, which highlights the plasticity in the liver. However, the role of YAP activation in selecting the cell of origin and lineage commitment during hepatobiliary oncogenesis is unknown. Aim: To determine if YAP Y357 phosphorylation is required for CCA tumorigenesis, we utilized an in vivo model. Unexpectedly, a shift in tumor phenotype to hepatocellular carcinoma (HCC) was identified. Subsequently, we further explored cell signaling and cell of origin contributions to this phenotypic switch. Method: C57BL/6 mice underwent biliary transfection with Sleeping Beauty transposase and transposons encoding myr-AKT and either YAP S127A (YAP-S) or YAP S127A/Y357F (YAP-SY), followed by IL-33 treatment. Tumor nodule count, histologic classification, and liver-to-body ratio were assessed at necropsy after 10 weeks. RNA sequencing and ingenuity pathway analysis (IPA) were performed on HCC and CCA nodules. To determine the cell of origin, tumors were generated in lineage tracing mice (Rosa26 mT/mG mice treated with AAV8-TBG-Cre). Finally, two tumor-derived cell lines with YAP-SY and constitutive AKT expression were isolated. Results: Both YAP-S and YAP-SY models developed similar tumor numbers and bulk. YAP-S mice generated frequent CCA (25.3%) in addition to combined HCC-CCA (cHCC-CCA) tumors (10.7%) and HCC (64%), whereas YAP-SY mice developed predominantly HCC (86.7%), with rare CCA (8.8%) and mixed tumors (4.5%). Transcriptome analysis identified 3,367 differentially expressed genes (DEGs) between HCC from YAP-SY mice and CCA from YAP-S mice. Notably, YAP-regulated genes had decreased expression in the HCC from YAP-SY mice. IPA revealed key upstream regulators, including cytokines and growth factors (e.g., TGFB1, TNF, INFG, CSF2, IL6, IL1B, IL4) and transcription factors (e.g., TP53, JUN, SP1, NFKBIA, STAT3). Lineage tracing demonstrated HCC originated from hepatocytes and CCA from cholangiocytes in both models. Finally, gene expression analysis of novel syngeneic cancer cell lines from YAP-SY mice showed mixed features of both HCC and CCA. Conclusion: In this murine model, we found that sub-maximal YAP activation is associated with increased formation of HCC from hepatocytes, while a higher level of YAP activation due to YAP Y357 phosphorylation is associated with efficient formation of CCA. We identified cytokines and growth factors that may orchestrate this phenotypic switch. Finally, we developed novel syngeneic cancer cell lines with cHCC-CCA characteristics. Citation Format: Muhammed D. Aksu,Jayla T. Millender,Ryan D. Watkins,Jennifer A. Yonkus,EeeLN H. Buckarma,Nathan W. Werneburg,Daniel R. O'Brien,Chantal E. McCabe,Rondell P. Graham,Gregory J. Gores,Rory L. Smoot,Caitlin B. Conboy. YAP tyrosine phosphorylation regulates lineage commitment in liver tumorigenesis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 1457.

Abstract Despite advances in surgery and chemotherapy, patients with resectable pancreatic ductal adenocarcinoma (PDAC) face high recurrence rates (40-60%). Total neoadjuvant therapy (TNT) seeks to enhance margin-negative resections (R0) and address micrometastatic disease, with potential survival benefits. Yet, TNT still results in high recurrence rates, with 1-, 2-, and 3-year disease-free survival (DFS) at 65%, 48%, and 32%, respectively. Residual cancer extent is a key prognostic factor in PDAC after TNT. Tumor response scores show favorable outcomes only for patients achieving near-complete or complete pathologic response. In a cohort of 511 PDAC patients treated with TNT and surgery (2015-2022), improved DFS was only found in those with a complete pathologic response (pCR, 7.8%). This highlights the limited use of current response scoring in stratifying post-TNT patient risk, underscoring the need to better understand disease persistence and relapse. Here we developed a quantitative method to assess residual cancer. Using a digital pathology H&E library from 2180 PDAC cases (2000-2022), an AI platform segmented tissue into cancer epithelium, stroma, and normal regions. For 202 TNT-treated cases without pCR, we calculated a ratio of cancer area to stromal area from representative slides. Modeled after the histologic tumor regression grade (HTRG) system, cases were classified into &lt;5%, 5-50%, or &gt;50% cancer-to-stroma ratios. However, this measure alone showed no difference in DFS, suggesting tumor burden cannot fully explain differences in clinical outcomes. We hypothesized that the spatial organization of the tumor microenvironment (TME) is a determinant of patient outcomes. Drawing from landscape ecology, which studies spatial properties of ecosystems, we applied similar principles to analyze tissue architecture. Using an AI-based two-class segmentation of whole-slide images, we assessed spatial features like patch area, perimeter, density, and Shannon diversity. Python’s ‘pylandstats’ package calculated 21 spatial metrics, reduced via stepwise Cox regression using the Akaike information criterion (AIC). The final model included mean Shannon diversity, mean and standard deviation of stromal patch areas, and stromal patch density. Kaplan-Meier analysis of 202 samples stratified model predictions into quartiles, correlating with high (mean DFS 10.85 months), medium (19.32 months), and low risk (25.92 months) groups. These findings aligned with model expectations, underscoring the potential of spatial TME analysis to predict outcomes. Citation Format: Andrea V. Maraone, Zafar Siddiqui, Luis H. Cisneros, Merih D. Toruner, Mark Truty, Cornelius Thiels, Robert R. McWilliams, Steven R. Alberts, Rondell P. Graham, Carlo Maley, Qian Shi, Martin E. Fernandez-Zapico, Ryan M. Carr. Tumor spatial configuration predicts pancreatic cancer recurrence risk after total neoadjuvant therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5070.