Citations

Abstract Background Multiplexed immunofluorescence (MxIF) enables high-dimensional immune cell phenotyping and detailed characterization of the tumor immune microenvironment (TIME), but complex cyclic staining can introduce signal degradation and uncertainty in cell-level measurements. In routine practice, pathologists rely on hematoxylin and eosin (H&E) staining as the primary reference for tissue morphology and frequently cross-reference H&E to interpret MxIF findings. Methods We present a framework for aligning H&E and MxIF images at the tissue microarray (TMA) core level to support cross-modal analysis. Cell nucleus detections from each modality are used as anchor points, formulating the task as a point-set alignment problem. Coherent Point Drift (CPD) is applied for global alignment, followed by graph-matching–based refinement to improve local consistency. Evaluation on ovarian TMAs demonstrates consistent alignment performance for both restained and serial sections. We further explore the use of restained H&E as a reference for MxIF interpretation and investigate virtual H&E generation from MxIF data as a complementary approach when restained H&E is unavailable. Results The aligned images enable quantitative assessment of cross-modal feature concordance between MxIF-derived measurements and H&E morphology. The generated virtual H&E demonstrated similar cell population compared to the real H&E. Conclusions Cell-centric alignment can facilitate integrative multimodal histopathology analysis for TMA cores in spatial co-localization, cell feature validation, and virtual H&E generation.

Abstract Histopathological assessment has served as the gold standard for diagnosing Alzheimer’s disease (AD). Emerging technological advancements, including the development of amyloid positron emission tomography (PET), have enabled early detection of amyloid pathology, one of the neuropathological hallmarks of AD. Genome-wide association study (GWAS) across cohorts of aging and AD, leveraging different measurements of amyloid burden, may facilitate the identification of novel genetic variants that drive the earliest neuropathological changes in AD. This study presents the largest GWAS of brain amyloidosis to date, leveraging amyloid β (Aβ) measured by in vivo amyloid PET and postmortem histopathology from 13,555 individuals of European ancestry. Amyloid positivity was defined as moderate or frequent neuritic plaques according to the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) staging scores for each postmortem cohort. A Gaussian mixture model (GMM) was applied to each amyloid PET cohort to identify the cohort and tracer-specific cut-offs that differentiate amyloid positive and negative populations. In silico and ex vivo analyses further characterized implicated loci, including interrogating the association between bulk and single-nucleus gene expression profiles and AD-related traits. Genetic covariance analysis assessed the extent amyloid PET and postmortem measures reflect the shared genetic architecture of brain amyloidosis. Our combined amyloidosis GWAS identified three established AD risk loci: BIN1 (rs6733839, OR = 1.20, 95% CI 1.14-1.26, P = 1.32 × 10−11), CR1 (rs4844610, OR = 1.24, 95% CI = 1.16-1.32, P = 4.21 × 10−10), APOE (rs429358, OR = 4.01, 95% CI = 3.66-4.38, P = 4.54 × 10−201), and a newly identified brain amyloidosis-associated variant on chromosome 17 (rs35635959, OR = 1.18, 95% CI = 1.12-1.25, P = 1.47 × 10−8). SuSiE fine-mapping identified a single credible set of 15 putative causal variants with rs35635959 as the lead variant. Subsequent eQTL and SuSiE-based colocalization analyses prioritized rs35635959 as a strong eQTL for TUBG2, encoding tubulin gamma 2, which is involved in microtubule organization and synaptic plasticity. Further cell-type-specific characterization of this gene in neurons from dorsolateral prefrontal cortex tissue indicated that decreased TUBG2 expression was associated with increased Aβ burden and AD case status (PFDR < 0.045). Furthermore, our study is the first to report a modest genetic covariance (covariance=0.17, P < 6.54 × 10−8) between the genetic architecture of amyloid burden captured by different modalities. While APOE showed a strong association with both amyloid endophenotypes, the observed genetic covariance was not substantially attenuated after excluding variants within the APOE region (covariance=0.16, P < 1.32 × 10−7). Our results highlight the benefits of leveraging compatible, harmonized AD endophenotypes to increase power to uncover new molecular insights into the etiology of AD neuropathology. Wang et al. present the largest GWAS of brain amyloidosis to date, analysing 13,555 individuals using amyloid PET and postmortem Aβ measures. They identify a novel amyloidosis-associated variant on chromosome 17, demonstrate genetic covariance between modalities, and highlight complex traits sharing genetic architecture with Aβ burden.

Abstract Human genomic studies link reduced CUB domain-containing protein 1 (CDCP1) expression with myocardial recovery in heart failure. While CDCP1 regulates cardiac fibroblast proliferation in vitro, it’s in vivo role in cardiac fibrosis remains unclear. Using a Cdcp1 -knockout (KO) angiotensin II/phenylephrine mouse model, we show that Cdcp1 deletion reduces echocardiographic left ventricular mass, histologic cardiac fibrosis, and pro-fibrotic gene expression, along with decreased fibroblast activation and inflammatory markers. Spatial transcriptomics identified a pressure overload–expanded fibroblast subpopulation enriched for growth factor and TGF-β signaling (FB5), which was markedly attenuated in Cdcp1 -KO hearts, alongside reduction of a pro-inflammatory cardiomyocyte subtype (CM4). Complementary studies in human ventricular fibroblasts demonstrate that CDCP1 knockdown reduced extracellular matrix gene expression and collagen I deposition. These findings establish CDCP1 as a regulator of cardiac fibrotic remodeling in vivo and open avenues for its further investigation as a potential therapeutic target.

Abstract The genetic contributions of the X chromosome to Alzheimer’s disease (AD) remain poorly understood yet are expected to importantly shape sex differences in AD. We therefore performed large-scale X-chromosome-wide association studies (N=1,240,451), evaluating differential risk due to sex, APOE *4, and escape from X-chromosome inactivation, finding most X-linked loci appear relevant to female-biased AD etiology. In evaluating genetic pleiotropy with hormonal, lipid, and brain imaging traits, we discovered X-linked AD loci converged on white matter traits, particularly in the anterior corona radiata and splenium of the corpus callosum. Through brain-centric functional genomics analyses, we then nominated candidate causal genes, including 5 that appeared highly robust. Notably, we found the escape gene RBBP7 decreases AD risk in APOE *4 carriers likely through higher expression in excitatory neurons to counter tau-related neurodegeneration. Altogether, we provide an atlas of sex and APOE *4-informed candidate X-linked AD risk loci, genes, and mechanisms that will guide future studies.

Abstract Background: Most colorectal cancer (CRC) arises from polyps and is mainly prevented by polypectomy. The most important polyps to manage with colonoscopy are those with highest CRC risk- namely, advanced polyps (> 1cm, villous histology or high-grade dysplasia (HGD). Yet, 48% of advanced polyps recur within 1 to 3 years of removal, and up to 5% of advanced polyps under surveillance still progress to CRC. We performed this pilot study to investigate molecular and microenvironment heterogeneities of polyps and how they might impact their clinical behavior. Methods: GeoMx spatial transcriptomics was performed on FFPE tissues from three different polyp outcome phenotypes (POPs) including the polyp that does not recur (POP-NR), that recurs following polypectomy but cured by colonoscopy (POP-R) or the polyp despite polypectomy develops CRC at the polypectomy(ies) site (POP-CRC). Normal colon and polyp with low or HGD from the index polyp were assessed from 6 patients with POP-NR, 9 with POP-R and 12 with POP-CRC with a minimum of 2 follow up colonoscopies at 3-year intervals. Epithelium was identified as PanCK positive, and stroma identified as PanCK negative and positive nuclear staining. Cell type deconvolution was implemented using single-cell adult human intestinal tract catalogue (Elmentaite et al., https://www.gutcellatlas.org/). Differential gene expression (DEG), cell type abundance and functional enrichment analyses was performed using linear mixed effects model, and observations with p-value < 0.05 and log2FC >= |1| are reported. Results: The greatest number of DEGs were identified in stroma of the index POP-CRC compared to POP-NR polyps (n = 17 down and 11 upregulated genes), followed by epithelium of the index POP-CRC vs POP-NR polyps (n = 10 down and one upregulated gene(s)). Between the index POP-CRC and POP-R, epithelium showed downregulation of 7 genes, and upregulation of no genes. In stroma two genes were down and none upregulated. Four genes were downregulated in stroma of the index POP-R vs POP-NR polyp and 3 in epithelium, and one gene was upregulated in stroma and another in epithelium. MZT2B was upregulated in stroma of both the index POP-R (log2FC = 1.09, p-value = 0.0014) and POP-CRC (log2FC = 1.29, p-value = 0.0001) and has been implicated as a prognostic marker associated with worse prognosis in certain cancers. IgM and IgA plasma cells, proximal progenitors, MMP9+ inflammatory macrophages and myofibroblasts were found to be downregulated in epithelium of index POP-CRC and POP-R compared to POP-NR polyps; while microfold cells were downregulated in stroma of index POP-CRC and POP-R compared to POP-NR polyps. Conclusions: The stromal microenvironment and less so, epithelial features present in the index polyp differ based on a polyp’s future clinical behavior. The polyp-immune interaction warrants further study as a potential prevention target against polyp progression. Citation Format: Mrunal Dehankar, Lisa A. Boardman, Daniel O'Brien, E. Aubrey Thompson, Jennifer M. Kachergus, Ji Shi, Alexej Abyzov, Milovan Suvakov, Rondell P. Graham, Chen Wang. Stromal immune composition significantly contributes to adenomatous polyp recurrence or progression to cancer [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 4018.

Abstract Ovarian endometrioid carcinoma (OEC) is the second most common histotype associated with the most favorable prognosis among ovarian carcinomas. Similar to endometrial carcinoma, OEC exhibit significant molecular diversity. We aimed to develop a practical immunohistochemical (IHC) prognosticator by integrating IHC biomarkers with clinical substage, and surgical outcomes. This multi-institutional study included participants with primary invasive OEC from the Alberta Cancer Registry (AOVT), Mayo Clinic, and Disease of the Ovary and their Evaluation Study (DOVE). Pathology review excluded misclassified high-grade serous and mesonephric carcinomas leaving 422 OEC cases (AOVT N=158; DOVE N=143; Mayo N=121) with available tumor biospecimens who did not receive neoadjuvant treatment. Clinical characteristics included age, stage, grade, residual disease and 5-year survival. Clinical risk group was defined by combining stage and residual disease: Low (FIGO stage IA/IB & no macroscopic disease), Intermediate (stage IC-II& no macroscopic disease), High (stage III/IV or macroscopic disease). Tissue microarrays were stained for TP53, PMS2, MSH6, PGR, and CTNNB1 using IHC and were scored by a single pathologist. Tumors were hierarchically categorized as TP53-abnormal (TP53abn)/PGR-loss, mismatch-repair deficient (MMRd, via PMS2 and MSH6), nuclear-CTNNB1 (nCTNNB1), or no-specific-immunohistochemical-profile (NSIP). Overall survival (OS) at 5 years was compared across clinical risk and biomarker groups using Cox regression, adjusted for age and site to generate hazard ratios (HR), and 5-year survival rates (5-YSR). High clinical risk group was associated with worse 5-year OS compared to low & intermediate risk (p<0.0001). Hierarchical IHC biomarker groups were also associated with 5-year OS, adjusted for age and study site (p<0.0001), with consistently worse survival for combined TP53abn/PGR-loss (n=17, HR=6.07, 95% CI 2.78-13.26), PGR-loss only (n=55, HR=4.17, 95% CI 2.19-7.94), TP53abn only (n=29, HR=2.04, 95% CI 0.85-4.90), and better survival for nuclear-CTNNB1 (n=146, HR=0.22, 95% CI 0.07-0.65) compared to NSIP (n=132). Within the low-risk group, MMRd, nCTNNB1, or NSIP had greater than 97% 5-YSR, while OEC with TP53abn/PGR-loss or PR-loss only had less than 75% 5-YSR. Within the intermediate group, only nCTNNB1 exceeded a 5-YSR of greater than 97%. Within the high-risk group, 5YSR for nCTNNB1 OEC was 90.9%, compared to only 16.7% for TP53abn/PGR-loss. This IHC-based algorithm refines prognosis beyond clinical substage. It identifies low-risk patients with unfavorable prognosis (TP53abn/PGRloss, PGR loss only) who may benefit from adjuvant therapy, and also patients with favorable prognosis within the intermediate group for whom adjuvant therapy could be de-escalated. Further patient selection for chemo vs. hormone therapy in the high-risk group may be improved by biomarkers. Citation Format: Gamaliel Taengwa, Hunter J. Atkinson, Bryan M. McCauley, Sebastian M. Armasu, Chen Wang, Jennifer A. Doherty, Holly R. Harris, Ellen L. Goode, Martin Koebel, Stacey J. Winham. IHC-based prognostic sub-stratification of ovarian endometrioid carcinoma [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 1184.

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.

Convergent framework for future POC cancer diagnostics aligning clinical needs (why), enabling technologies (how), and translational bridges. It integrates lab-on-chip biosensing and analytics for decentralized, early, longitudinal care.

Abstract Deep learning models enable the prediction of clinical endpoints from whole-slide images (WSIs), but many such models function as “black boxes”, lacking transparency about whether and which histomorphological patterns drive their predictions, hindering interpretability and clinical adoption. Here we propose a human-in-the-loop explanation framework, MorphoXAI, which provides both local and global interpretability for deep learning models by incorporating human-expert interpretations. At the global level, it reveals the histomorphological patterns on which the model consistently relies to distinguish between classes of WSIs, as well as the patterns associated with confusion between classes. At the local level, it indicates which of these patterns are used in the prediction of an individual WSI and which regions within the slide correspond to such patterns. We validated our method on a deep learning model trained for ovarian tumor histologic subtype prediction. The results show that our framework generates explanations that accurately reflect the histomorphology underlying the model’s predictions at both global and local levels. For interpretability and clinical utility in diagnostic contexts, human evaluation results showed that our explanations were easy to interpret, rich in diagnostic features, and directly helpful for diagnostic decision-making, thereby enhancing pathologist-AI collaboration. Our work highlights that unifying global and local explanations and grounding them in expert-interpreted morphology enhances the interpretability and verifiability of deep learning models, thereby facilitating the transparent deployment of such models in clinical practice.

Abstract Background Our group recently performed the largest‐to‐date X‐chromosome wide association study (XWAS) of Alzheimer's disease (AD). Here, we expand on this with additional samples, novel sex‐ and APOE *4‐stratified analyses, and evaluate escape from random X chromosome inactivation (eXCI) to better capture female‐biased risk genes. We then integrate these results with XWASs of various AD‐relevant traits to elucidate shared genetic signals and ultimately uncover novel AD risk genes and mechanisms. Method The AD XWAS design is shown in Figure 1A and includes random X chromosome inactivation (rXCI) and eXCI models. We further assessed suggestive AD signals ( p <1x10 ‐3 ) for pleiotropy using genetic colocalization with 2852 AD‐relevant traits (Figure 2A). Loci exhibiting X chromosome‐wide significance ( p <1x10 ‐5 ) or apparent trait colocalization underwent quantitative trait locus (QTL) colocalization analyses across 62 tissues and cell types to functionally prioritize AD risk genes. Result Full sample analyses reproduced Belloy et al. 2024 findings and identified 3 additional loci, including a male‐specific signal near GLUD2 that impacts glutamate/glutamine metabolism (Figure 1B). APOE *4‐stratified analyses revealed 9 additional loci, including 3 eXCI hits in APOE *4 carriers (Figure 1C‐D). Pleiotropy colocalization identified 38 loci, most being novel and many driven by eXCI and/or female‐specific AD XWAS, including MOSPD2, PNMA3 and GABRE loci that showed extensive colocalization with brain imaging traits (Figure 2B). The most significant XWAS locus, SLC9A7 , colocalized with total testosterone, HDL‐C, and various brain imaging traits. Only the NLGN4X locus colocalized with amyloid positivity, linking its proposed role in synaptic dysfunction to amyloid pathology. The locus at KDM6A , previously implicated as an AD resilience gene, colocalized with a functional MRI (fMRI) phenotype. QTL colocalization analyses confirmed gene prioritizations in Belloy et al. 2024, and additionally provided support for PNMA3 , an antigen highly expressed in the brain, and 3 APOE ‐stratified loci, including ACLS4 , which impacts lipid metabolism. Conclusion This study provides novel insights into biological mechanisms that contribute to X‐linked genetic risk for AD in an APOE *4 and sex‐specific manner, identifying various novel risk loci. Notably, 29 female‐biased risk loci were uncovered, which may shed light on sex disparities in AD. Overall, our findings will aid in elucidating AD pathways and drug targets relevant to personalized medicine.