McCabe, Chantal E.

Abstract Background SWI/SNF chromatin remodeling complexes are frequently mutated across human cancers, including biliary tract cancers (BTC). Within the SWI/SNF complexes, loss-of-function (LOF) mutations in ARID1A and PBRM1 are the most common and frequently co-occur alongside PI3K/AKT pathway activation. Yet, how those mutations affect the intracellular signaling landscape and transcriptomic programs is underexplored and may yield novel therapeutic opportunities. Methods Clinicodemographic parameters and mutation profiles of 250 patients with BTC were retrospectively collected through electronic medical records. Advanced overall survival (OS) was assessed in a multivariable analysis. Transcriptomic data were obtained and differentially expressed genes (DEGs) and pathways associated with SWI/SNF mutation status were analyzed. Changes in the transcriptomic landscape were compared to a murine syngeneic model of intrahepatic cholangiocarcinoma (CCA) initiated by loss of ARID1A and/or PBRM1 for cross-species validation. Results After adjusting for age, sex, and anatomical subtype, patients with SWI/SNF LOF mutations were found to have a 30% reduction in mortality risk (HR = 0.70, 95% CI: 0.50-0.98, p = 0.037). The transcriptomic cohort of 233 BTC patients included 71 (30%) with SWI/SNF LOF mutations, 21 (9%) with variants of uncertain significance, and 141 (61%) with SWI/SNF wild-type tumors. Differential gene expression and pathway analysis revealed changes in adaptive immune response, extracellular matrix, and cancer-associated proteoglycans. RNA-sequencing of murine tumors revealed the dominant effect of ARID1A loss in single and double knock-out tumors and conserved pathway alterations between mouse and human tumors. Conclusion Both murine and human primary tumors with either ARID1A alone or ARID1A/PBRM1 co-mutations exhibited altered expression of critical genes and pathways associated with proteoglycan synthesis and extracellular matrix. Ongoing research is investigating how CCA cells depend on those pathways and their canonical regulators for tumor formation and progression.

Objective To evaluate the effects of mepolizumab therapy on the blood transcriptome in patients with severe eosinophilic asthma (SEA) and to determine whether changes in gene expression predict responsiveness to mepolizumab treatment. Methods Fourteen consecutive patients diagnosed with SEA were prospectively enrolled. Each patient had sequential blood samples obtained pre-initiation and at 4, 8, and 12 weeks post-initiation of mepolizumab. Peripheral blood mononuclear cells (PBMCs) were isolated from blood samples for bulk RNA sequencing. Paired differential expression (DE) gene analysis was performed comparing baseline gene expression versus all timepoints. Changes in gene expression were also compared between responders versus nonresponders to mepolizumab treatment. Finally, gene set enrichment analysis was evaluated across timepoints and its interaction with the response to mepolizumab treatment. Results Principal component analysis of all genes demonstrated a homogeneous distribution, which did not separate into distinct groups based on either timepoint or therapeutic response. At week 12, 149 genes had significant DE (FDR < 0.05) compared to baseline. When performing all-way timepoint comparisons, 74 genes (63 protein-coding) were found to be downregulated at weeks 4, 8 and 12 compared to baseline, but no differences were observed between post baseline timepoints. Twenty-eight genes (16 protein-coding) did change with progression of time and were associated with response to therapy, and 56 protein-coding genes distinguished responders and nonresponders. At week 12, nonresponders had a high enrichment of genes involved with signaling pathways, including cytokines, growth factors, cell differentiation markers, and protein kinases. Conclusion In this exploratory study, mepolizumab use was associated with limited global transcriptomic separation with some preliminary differential-expression and enrichment findings. No definitive mechanistic or predictive response signatures were identified due to the study limitations. Future studies, including larger cohorts followed for longer durations with interrogation of specific immune subsets, may offer additional insight into the pathophysiology of severe eosinophilic asthma and into predicting response to mepolizumab treatment.

Abstract Background: CLL incidence differs by ancestry, with higher rates in individuals of European ancestry (EA) than African ancestry (AA). The contribution of epigenetic variation to these disparities remains unclear. We investigated chromatin accessibility, histone modifications, and gene expression in CLL patients of EA and AA to identify ancestry-associated epigenetic signatures. Methods: ATAC-seq was performed on blood clonal B cells from 15 AA and 51 EA patients; CUT&Tag profiling of six histone marks (H3K4me1, H3K4me3, H3K27ac, H3K9me3, H3K27me3, H3K36me3) was done in 8 AA and 12 EA cases; RNA-seq was generated for all samples. Ancestry was genetically confirmed. Differential regions were linked to genes using ENCODE and Hi-C datasets. Results: ATAC-seq revealed 4,955 regions with increased and 3,000 with decreased accessibility in AA vs EA (fold change >2, FDR ≤0.05). Regions with increased accessibility mapped to 2,313 genes; 599 were upregulated and enriched in TNF-α/NF-κB (p=1.40E-53) and apoptosis pathways (p=6.90E-11). Regions with decreased accessibility linked to 1,953 genes; 317 were downregulated, enriched in interferon-γ response (p=1.04E-03) and IL-6/JAK/STAT3 signaling (p=6.41E-03). Histone profiling showed ancestry-specific changes across all marks. For H3K27ac (active enhancer), 68 genes with a decreased signal in AA were downregulated and enriched in interferon-γ (p=1.55E-06) and IL-6/JAK/STAT3 (p=9.62E-05) pathways. Increased H3K27me3 (repressive histone modification) in AA affected 399 genes enriched in IL-6/JAK/STAT3 (p=8.13E-09) and interferon-γ (p=2.48E-05) pathways. These findings suggest coordinated regulation by active and repressive chromatin states. Conclusions: Despite limited sample size, this study suggests differences between AA and EA ancestries may exist in epigenetic signatures in CLL, implicating chromatin accessibility and histone modifications in pathways relevant to tumor biology. These signatures may also contribute to the differences in CLL incidence by ancestry. Future studies with more patients and functional validation experiments are needed to clarify the role of these epigenetic differences in CLL pathogenesis. Citation Format: Zhiquan Wang, Huihuang Yan, Mingma Sherpa, Daniel Bihnam, Cristine Allmer, Chantal McCabe, Daniel O’Brien, Dennis P. Robinson, James R. Cerhan, Neil E. Kay, Sameer A. Parikh, Esteban Braggio, Susan Slager. Ancestry-associated epigenetic differences in chronic lymphocytic leukemia [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 5064.

The underlying immunopathogenesis of inflammatory arthritis (IA) immune-related adverse event (irAE) remains obscure. Unlike rheumatoid arthritis (RA), where autoantibodies and B cell dysfunction are central features, the contribution of humoral immunity to IA-irAE is unclear. Here, we performed immunophenotyping of peripheral blood from patients with IA-irAE and compared them with patients with seronegative RA, immune checkpoint inhibition–treated patients without irAE, and healthy controls. IA-irAE was marked with increased cytotoxic gene expression and metabolic activation in T cells and reduced CXCR3 and CCR6 expression in CD4 + T cells. Contrary to seronegative RA, patients with IA-irAE displayed no substantial elevation in autoantibody levels or atypical CD11c + CD21 − B cells. IA-irAE was further characterized by elevated levels of interleukin-6 (IL-6), IL-12, and type I interferon, which correlated with the T cell activation phenotypes. Together, our findings define IA-irAE as a disease with certain immunological features distinctive from RA, representing a potentially T cell–driven, autoantibody-independent autoimmunity. These results offer insights into immune tolerance breakdown and therapeutic targeting in irAEs.

CTNNB1- mutated hepatocellular carcinomas are characterized by a distinctive morphology and activation of the Wnt pathway. AXIN1 also plays a key role in the Wnt pathway, but the morphology of AXIN1-mutated tumors has not been examined. In addition, there are ongoing questions on the ability of AXIN1 mutations to activate the Wnt pathway in hepatocellular carcinoma. AXIN1 mutated tumors (N=18) were studied, along with control groups: CTNNB1 (N=17), APC (6), or “Other” genes in the Wnt pathway (5). Wnt pathway activation was studied by immunostains for beta-catenin and glutamine synthetase. Findings were supplemented by gene expression analysis using TCGA data. On histologic examination, the classic morphology associated with beta-catenin mutations was found in all 4 groups: 8/18 AXIN1 (44%), 10/17 CTNNB1 (59%), 4/6 APC (67%), and 1/5 Other (20%). By immunohistochemistry, Wnt pathway activation was found in 11/18 AXIN1 (61%), 15/17 CTTNB1 (88%), 6/6 APC (100%), and 5/5 (100%) of Other. In AXIN1- mutated tumors, the Wnt pathway was weakly activated. Glutamine synthetase stains also highlighted a new “progressed pattern” associated with distinct subnodules of staining. Tertiary lymphoid structures were uncommon except for cases with CTTNNB1 mutations plus additional mutations in the Wnt pathway. In summary, the classic morphology associated with CTNNB1 mutations is found in hepatocellular carcinomas with mutations in AXIN1 , APC , and other Wnt genes. AXIN1 mutated tumors have Wnt activation that is detectable but at lower levels than CTNNB1 mutated tumors. As tumors progress, their level of Wnt activation can change.

Background and Aims: Cholangiocarcinoma (CCA) is one of the most lethal cancers, characterized by molecular heterogeneity and treatment resistance. To uncover new biological signals and therapeutic opportunities, we employed multiomic characterization combined with machine learning. Approach and Results: We profiled all anatomical CCA subtypes using whole exome sequencing, mRNA sequencing, and proteome/phosphoproteome analysis. Integrative dimensional reduction revealed RNA, protein, and phosphoprotein features driving tumor heterogeneity, enabling clustering. Machine learning algorithms identified molecular features for each cluster and mapped external datasets and patient-derived xenograft (PDX) models onto these clusters. Kinase enrichment analysis highlighted targetable kinases active in each cluster. In vivo validation was performed in cluster-specific PDX models using the selective TNK1 inhibitor, TP-5801. We identified 3 molecular clusters with distinct pathway characterization: immunomodulatory (cluster 1), metabolic (cluster 2), and gene regulation/cellular fate (cluster 3). Cluster assignment was independent of anatomic subtype but correlated with overall survival following curative-intent resection. We also identified multiomic features and pathways linked to overall survival and lymph node metastases, crucial for patient treatment selection. Kinase enrichment analysis pinpointed TNK1 as a highly active kinase in the metabolic cluster. Treatment with TP-5801 significantly reduced tumor growth in a metabolic PDX model, but not in models representing the other clusters. Combining internal data with publicly available datasets, we identified the immunomodulatory cluster as most responsive to gemcitabine/cisplatin therapy, confirmed in vivo using cluster-specific PDX models. Conclusions: Integrated multiomic characterization provides translational insights by defining unique molecular subtypes associated both with therapeutic response and overall clinical outcomes. This approach identified TNK1 as a previously unrecognized therapeutic target in a defined subset of CCA tumors.

Abstract Most disease-associated single-nucleotide polymorphisms (SNPs) identified by genome-wide association studies (GWASs) reside in noncoding regions. There is increasing evidence that they play regulatory roles through epigenetic mechanisms by altering local chromatin state, 3D chromatin structure, and looping interactions. We and others have identified 42 CLL risk loci from GWASs. At 12 risk loci located outside of gene promoters, we previously demonstrated that functional SNPs are highly enriched in enhancers and super-enhancers that mostly target BCL2 family genes and transcriptional regulators. However, the study was limited by using only public epigenomic data generated in lymphoblastoid cell lines (LCL) and normal immune related cell types. To gain a better understanding of how the functional SNPs alter local chromatin state and modulate target gene expression in CLL, we generated RNA-seq data (n=588) and transposase-accessible chromatin with sequencing (ATAC-seq) data (n=69) in CLL tumor B cells. We performed molecular quantitative trait loci (QTL) analysis with index and correlated SNPs (R2 0.5) at 41 risk loci (excluding the HLA locus). The analyses identified cis expression QTLs (eQTLs), within 1Mb of genes’ transcription start site, at 25 risk loci and chromatin accessibility QTLs (caQTLs, within peak) at 11 risk loci, with both eQTLs and caQTLs at 8 risk loci. We identified a total of 54 eGenes, for which the expression is affected by nearby SNPs within 1Mb, including 40 novel eGenes at 16 CLL risk loci not previously reported. Notably, based on publicly available chromosome interaction data from CLL, LCL, and normal B cells, for over 70% of the novel eGenes, their promoters showed looping interactions with the regions carrying the eQTLs. Further, 13 SNPs were identified as both caQTL and eQTL, with the associated novel eGenes including CD81 at 11p15.5, IPCEF1 at 6q25.2, as well as CXXC1 and MBD1 at 18q21.1. The result suggests that these SNPs play a role in altering chromatin accessibility contributed to gene expression variation. At 11p15.5 risk locus, SNP rs2651823 (A/G) represents a novel caQTL and eQTL. The alternative G allele is associated with increased chromatin accessibility and CD81 expression. Hi-C data from GM12878 and CD20+ B cells supported interaction between the open chromatin region carrying rs2651823 and CD81 promoter. CD81 facilitates the trafficking of CD19 to the surface of activated B cells, and CD81-null mice showed impaired immune response. In a mouse model, CD81 contributes to tumor progression and metastasis in Lewis lung carcinoma. In summary, our molecular QTL analysis revealed that functional SNPs, located in CLL risk loci, modulate chromatin accessibility and expression of downstream target genes that could impact CLL risk. Citation Format: Huihuang Yan, Zhiquan Wang, Mingma Hoel, Cristine Allmer, Chantal McCabe, Daniel O’Brien, Dennis Robinson, James Cerhan, Sameer Parikh, Esteban Braggio, Susan Slager. Molecular QTL analyses identify functional variants at inherited risk loci in chronic lymphocytic leukemia [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 2763.

Abstract Despite the advent of novel targeted therapies with high overall response rates, chronic lymphocytic leukemia (CLL) is still largely incurable due to the development of resistance. The bone marrow microenvironment (BMME) plays an important role in the survival and drug resistance in CLL. BM stromal cells (BMSCs) are considered a key component of BMME. Our long-term goal is to gain further insights of BMSCs-CLL crosstalk influencing both survival and drug resistance in CLL. To understand the global biologic changes that occur in leukemic CLL cells when in contact with BMSCs, we assessed RNA-seq in paired CLL cells isolated from untreated blood and BM and in untreated patients’ CLL cells cultured alone or with BMSCs. CLL cells from blood/BM and cultured alone/with BMSCs were also examined by Immunoprecipitation (IP), Western blot (WB), untargeted metabolomics (LCMS+GCMS), and preclinical drug sensitivity assays. We detected only 13 upregulated genes that overlap between CLL cells from BM and cocultured with BMSCs (p&lt0.05, fold change &gt1.5). When we analyzed the expression of these 13 genes in CLL cells from a cohort of 162 untreated patients by RNA-seq, we found associations between 4 genes (PNP, C16orf54, MOB3A, CDK2AP2) and clinical outcomes including overall survival (OS), progression free survival (PFS), and time to first treatment (TTFT) [multivariable Cox proportional hazards models, p&lt0.05]. Of the 4 genes, purine nucleoside phosphorylase (PNP), an enzyme in the purine pathway, had the most significant association with OS, PFS, and TTFT. Metabolomic profiling indicated an increased level of purine pathway metabolites adenosine, adenine, inosine, and hypoxanthine in cocultured CLL cells. WB analysis showed variable baseline PNP protein expression with 2 cohorts: low /no (L) and high (H) PNP using CLL blood cells. An induction in PNP protein levels were noticed in CLL cells expressing only LPNP when cocultured. Given the association of HPNP with adverse clinical outcomes, we tested for L vs. HPNP cohorts drug sensitivity to known BTK inhibitors(is) or Bcl2is. Treatment of CLL cells from untreated patients with Bcl2is venetoclax, S55746, and LP-118 (Bcl2-Bclxli, Newave) showed increased sensitivity to the Bcl2/Bclxlis in HPNP but not in LPNP cells. In addition, BTKis showed no difference in drug sensitivity associated with CLL PNP levels. To explain this discrepancy, WB and IP analyses were conducted in L vs. HPNP leukemic cells for apoptotic profiles, where we found increased phosphorylated-Bcl2(S70) and an increased association of Bcl2 with Bax in LPNP-expressing CLL cells compared to HPNP. These findings support increased resistance to apoptosis afforded by inhibiting Bcl2 for LPNP vs. HPNP-expressing CLL cells. Our future goals are to continue to understand the prognostic significance of the 4 genes with adverse clinical outcomes and to investigate how best to exploit the peculiar, enhanced sensitivity to Bcl2/Bclxlis found in the HPNP CLL cells. Citation Format: Sutapa Sinha, Weiguo Han, Zhiquan Wang, Brianna M. Finke, Heather C. Darby, Kari G. Rabe, Susan L. Slager, Chantal E. McCabe, Daniel R. O'Brien, Sameer A. Parikh, Esteban Braggio, Yi Chen, Fenlai Tan, Stephen P. Anthony, Yu Chen, Bing Dai, Yue Shen, Neil E. Kay. CLL drug resistance- A multifaceted mechanism [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 4423.

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 Extracellular vesicles (EVs) are key mediators of cell–cell communication and are involved in transferring specific biomolecular cargo to recipient cells to regulate their physiological functions. A major challenge in the understanding of EV function in vivo is the difficulty ascertaining the origin of the EV particles. The recent development of the “Snorkel-tag,” which includes EV-membrane-targeted CD81 fused to a series of extra-vesicular protein tags, can be used to mark EVs originating from a specific source for subsequent isolation and characterization. We developed an in vivo mouse model, termed “CAGS-Snorkel,” which expresses the Snorkel-tag under the control of the Cre-lox system, and crossed this mouse with either Prx1-Cre (mesenchymal progenitors) or Ocn-Cre (osteoblasts/osteocytes) and isolated Snorkel-tagged EVs from the mouse bone marrow plasma using a magnetic bead affinity column. miRNA-sequencing was performed on the isolated EVs, and although similar profiles were observed, a few key miRNAs involved in bone metabolism (miR-106b-5p, miRs-19b-3p, and miRs-219a-5p) were enriched in the Ocn-derived relative to the Prx1-derived EV subpopulations. To characterize the effects of these small EVs on a bone cell target, cultured mouse bone marrow stromal cells were treated with Prx1 or Ocn EVs, and mRNA-sequencing was performed. Pathways involved in ossification, bone development, and extracellular matrix interactions were regulated by both EV subpopulations, whereas a few pathways including advanced glycation end-products signaling were uniquely regulated in the Ocn EV subpopulation, underlying important biological effects of specific EV subpopulations within the bone marrow microenvironment. These data demonstrate that EV isolation in vivo using the CAGS-Snorkel mouse model is a useful tool in characterizing the cargo and understanding the biology of tissue-specific EVs. Moreover, while bone mesenchymal cell populations share a common EV secretory profile, we uncover key differences based on the stage of osteoblastic differentiation that may have important biological consequences.