tbuckley/cabot-search huggingface dataset:
Abstract 7435: CRCFound: A colorectal cancer CT image foundation model based on self-supervised learning
Authors: Jing Yang, Du Cai, Junwei Liu, Zhenfeng Zhuang, Fengao Wang, Chenghang Li, Chuling Hu, Baowen Gai, Yiping Chen, Yixue Li, Liansheng Wang, Feng Gao, Xiaojian Wu
Journal: Cancer Research (2025)

Abstract Background: Colorectal cancer (CRC) is a significant global health threat. Accurate risk stratification is essential for determining the optimal treatment plan, yet existing deep learning models perform poorly in the preoperative diagnosis of CRC and lack generalizability due to insufficient annotated data. To address these issues, we propose CRCFound, a self-supervised learning-based CT image foundational model for CRC. Methods: A total of 6, 332 CRC patients with preoperative CT images were collected from 2008 to 2019 at the Sixth Affiliated Hospital of Sun Yat-sen University. Among them, 5, 137 unlabeled CT images were used for pretraining, and 1, 195 images were reserved for fine-tuning and validation. Comprehensive benchmark tests were conducted on six diagnostic and two prognosis tasks in comparison with other models. Model interpretation was also explored to gain a more profound understanding of the model's behavior and decision-making process. Results: CRCFound demonstrated excellent performance and generalization ability. For preoperative diagnosis of TNM stage, the average AUC of CRCFound for T, N, M, and overall TNM stage reached 0.889, 0.847, 0.830, and 0.774. In the MSI and CMS diagnosis tasks, it also showed good predictive performance (AUC 0.952 and 0.810, respectively). For prognosis prediction, CRCFound_CT was an independent risk factor for disease-free survival (hazard ratio (HR)= 4.62, 95%CI = 2.7-7.88, P &amp;lt; 0.001) and overall survival (HR = 7.78, 95%CI = 4.12-14.7, P &amp;lt; 0.001). Feature visualization using the t-SNE algorithm demonstrated that CRCFound could effectively differentiate samples in multiple tasks. Visualization of the attention map indicates that CRCFound can focus more effectively on the critical areas of the tumor than traditional supervised learning models, thus providing more accurate predictions. Conclusion: CRCFound addresses the challenge of insufficient annotated data and performs well in a wide range of downstream tasks, offering a promising solution for accurate diagnosis and personalized treatment of CRC patients. Citation Format: Jing Yang, Du Cai, Junwei Liu, Zhenfeng Zhuang, Fengao Wang, Chenghang Li, Chuling Hu, Baowen Gai, Yiping Chen, Yixue Li, Liansheng Wang, Feng Gao, Xiaojian Wu. CRCFound: A colorectal cancer CT image foundation model based on self-supervised learning [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 7435.
Abstract 3859: Ephrin inhibition disrupts stromal-cancer crosstalk and reduces metastasis in pancreatic cancer
Authors: Cerian L. Bolton, Rhianna O'Sullivan, Shinelle Menezes, Angus J. Cameron, Guillem Marin, John F. Marshall, Ed P. Carter, Mark Henkemeyer, Richard P. Grose
Journal: Cancer Research (2025)

Abstract Pancreatic Ductal Adenocarcinoma (PDAC) is the 10th most common cancer in the UK but has devastating mortality rates world-wide. Reasons underpinning this include delays in diagnosis and treatment resistance, where the desmoplastic nature of the disease hampers treatment efficacy. One of the most influential cell types within the PDAC stroma is the cancer associated fibroblast (CAF). CAFs are known to have both pro- and anti-tumoral roles, making them an attractive cell type to target for re-programming. To investigate CAF-cancer cell crosstalk we developed a 3D in vitro model of CAF-led invasion using heterocellular spheroids of cancer cells and CAFs. RNA sequencing of chimeric mouse/human versions of these spheres identified complementary expression of ephrin family receptors (Eph-B2) and ligands (EFNB2) between cancer and CAFs respectively, implicating their involvement in invasion. Part of the receptor tyrosine kinase superfamily, the ephrin family are unique in that both the ligand and receptor can signal, with implications of this having been well described in vasculogenesis and axon guidance. Utilising CAFs expressing either EFNB2 knockout or a gain-of-function mutation in EFNB2, we have found that both forward and reverse signalling is required for invasion, suggesting that disruption of both elements could be beneficial therapeutically. Using first-in-class inhibitors of this pathway, we observed a significant decrease in PDAC invasion in our 3D spheroid invasion model. Extending this in vivo, we have utilised a KPC-derived PDAC orthotopic mouse model that recapitulates human biology through the formation of both primary and metastatic disease. We found that tumour growth and size were not affected by ephrin blockade. However, eph-ephrin signalling inhibition did cause a significant decrease in metastatic tumour presence across multiple organ sites. This highlights a potential for this treatment to halt disease progression and reverse disease severity. We hope to extend these results further to test the potential clinical applications of this compound as a treatment option for both early and late-stage PDAC patients. Citation Format: Cerian L. Bolton, Rhianna O'Sullivan, Shinelle Menezes, Angus J. Cameron, Guillem Marin, John F. Marshall, Ed P. Carter, Mark Henkemeyer, Richard P. Grose. Ephrin inhibition disrupts stromal-cancer crosstalk and reduces metastasis in pancreatic cancer [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 3859.
Abstract 5579: Identification of MTA1 as a new molecular marker in urothelial carcinoma
Authors: Gisella Campanelli, Noah Waxner, Nema Parkhomovsky, Raphael Vanderstichel, Ching Yang, Anait S. Levenson
Journal: Cancer Research (2025)

Abstract Metastasis-associated protein 1 (MTA1), a master transcriptional co-regulator and chromatin modifier, is strongly associated with many types of clinically aggressive cancers. Loss of MTA1 reduces aggressiveness and metastatic potential in cancer cells. A publicly available human dataset predicts that MTA1 might work as a prognostic marker, however, the exact role of MTA1 in the pathobiology of bladder cancer is unknown. We sought to evaluate the expression of MTA1 and associated epithelial-to-mesenchymal (EMT) events using canine urothelial carcinoma (UC) clinical samples as well as cell lines. We found that MTA1 and cyclooxygenase 2 (COX2) are overexpressed in canine UC samples compared to normal bladder samples, whereas E-cadherin (E-cad) levels are higher in normal bladder. The results of samples demonstrated that MTA1 expression correlated with aggressive clinicopathological features such as high tumor-grade, muscular/vascular invasion, and metastasis. The MTA1 expression differed in tumors depending on their localization, with the highest being in the urethra adjoining the prostate. Unexpectedly, higher E-cad levels were detected in metastatic tumor cells compared to primary tumor cells. Further, we analyzed MTA1 and EMT-associated markers in four invasive canine UC cell lines. Using two cell lines, AxA and SH, and their corresponding MTA1 knockdown (shMTA1) clones, we validated the direct link between MTA1 and these markers on mRNA and protein levels. Overall, these findings suggest that MTA1 may represent a key upstream effector tightly associated with COX2 and EMT-mediated events in canine UC. Accordingly, MTA1 may be considered a feasible interceptive and therapeutic target for canine UC treatment. Citation Format: Gisella Campanelli, Noah Waxner, Nema Parkhomovsky, Raphael Vanderstichel, Ching Yang, Anait S. Levenson. Identification of MTA1 as a new molecular marker in urothelial carcinoma [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 5579.
Abstract 7439: Label-free 3D virtual papanicolaou staining of urine cytology using deep learning and holotomography
Authors: Tal Lifshitz, Geon Kim, Su-Jin Shin, Kwang Suk Lee, YongKeun Park
Journal: Cancer Research (2025)

Abstract The Papanicolaou stain is commonly used to assess cells for carcinoma in urine cytopathology. However, due to the nature of cytology, cells are often imaged overlapping one another, which makes them hard to distinguish and complicates the assessment process. The staining procedure not only introduces changes to the cells, but it is also lengthy and expensive. Here, we present a deep learning model that creates virtual Papanicolaou stained 3D images from label-free 3D holotomography images of urine cytology. We acquired 38 3D holotomography images of urine cytology samples using the Tomocube HT-X1, after which the samples were stained and 38 matching whole slide images were acquired. The image pairs were preprocessed to flatten the 3D holotomography images into 2D, and image registration to align the image pairs. This produced 10, 693 image pairs of size 256x256 px, 8670 of which were used to train a modified version of the CycleGAN model. After the model was fully trained, the z-stack 3D holotomography images were input into the model one by one, resulting in a 3D virtual stained image. Our results show that our model was able to virtually stain the test sample (SSIM = 0.691 ± 0.097, PSNR = 19.9 ± 5.8, MSE = 0.017 ± 0.011) to produce an accurate 2D image, and also virtually visualize the Papanicolaou stained test samples in 3D. The presented work has potential in aiding practitioners by shortening the standard staining process. Through visualizing virtually stained urine cytology samples in 3D, our work provides the information needed to accurately assess cases of overlapping cells and cell clusters. Citation Format: Tal Lifshitz, Geon Kim, Su-Jin Shin, Kwang Suk Lee, YongKeun Park. Label-free 3D virtual papanicolaou staining of urine cytology using deep learning and holotomography [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 7439.
Abstract 3868: Decreased metastatic burden in a spontaneous metastatic melanoma model by inhibiting myeloid-derived suppressor cell function
Authors: Kaitlyn M. Landreth, Angisha Basnet, Mary Garland-Kledzik, Brian A. Boone, Tracy W. Liu
Journal: Cancer Research (2025)

Abstract Metastatic melanoma is the leading cause of skin cancer-related deaths, with a five-year survival rate of only 30%. Myeloid derived suppressor cells (MDSCs) are considered a driver of metastatic progression, supporting pre-metastatic niche formation, facilitating tumor cell migration, invasion, and extravasation and promoting immune evasion. This study evaluates the contribution of myeloperoxidase (MPO) and extracellular trap formation in melanoma metastasis. Using a spontaneous melanoma metastasis model, we demonstrate metastases in the lungs, bone, and lymph node approximately 4 weeks post surgical resection of primary subcutaneous B16F10 tumors. Tumor growth and metastatic burden were quantified using a bioluminescent reporter stably expressed in B16F10 cells. Syngeneic myeloperoxidase-deficient and peptidyl arginine deiminase 4 (PAD4)-deficient mice, as well as C57BL/6J wild-type mice treated with an MPO-specific inhibitor or hydroxychloroquine (an extracellular trap inhibitor), exhibited significantly reduced lung and bone metastases compared to untreated wild-type controls. PAD4, a critical enzyme in extracellular trap formation, was essential for these effects. Targeting myeloperoxidase or extracellular traps significantly reduced MDSC populations while increasing B cells in the metastatic microenvironment, as assessed by flow cytometry. Ex vivo assays revealed diminished MDSC-mediated suppression of T and B cells when myeloperoxidase or extracellular trap formation was inhibited. Notably, depletion of B cells abrogated the anti-metastatic effects of targeting myeloperoxidase or extracellular traps, highlighting B cells as central mediators of metastasis suppression. These findings demonstrate that targeting myeloperoxidase or extracellular trap formation reduces metastatic burden and mitigates MDSC-mediated pro-metastatic and immunosuppressive functions. This work underscores the therapeutic potential of targeting myeloperoxidase and extracellular trap formation in combating melanoma metastasis. Citation Format: Kaitlyn M. Landreth, Angisha Basnet, Mary Garland-Kledzik, Brian A. Boone, Tracy W. Liu. Decreased metastatic burden in a spontaneous metastatic melanoma model by inhibiting myeloid-derived suppressor cell function [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 3868.
Abstract 5580: Determining the effects of serine-arginine protein kinases inhibition on splicing factors and long non-coding ribonucleic acids regulation in cervical cancer cells
Authors: Lydia Mphahlele, Zodwa Dlamini, Rahaba Makgotso Marima
Journal: Cancer Research (2025)

Abstract Cervical cancer (CCa) remains a significant global health challenge, with high morbidity and mortality rates, particularly in developing countries. The pathogenesis of CCa is largely driven by persistent infection with high-risk strains of Human Papillomavirus (HPV). Serine-arginine protein kinases are a family of cell cycle-regulated kinases that phosphorylate the serine/arginine (SR) domain-containing proteins in the nuclear patches to intervene with pre-mRNA splicing, signals splicing controls in response to extracellular stimuli and contributes to tumorigenesis. It has been reported in recent studies that the dysregulation of splicing factors and lncRNAs affects the progression of CCa. The involvement of SRPKs with lncRNAs regulation remains unelucidated in CCa. This study aimed to investigate the association of lncRNAs and SRPKs inhibition by SRPIN340 in CCa cells SiHa and C33A. Alamar blue cell viability assay, 84 lncRNA gene panel, bioinformatics analysis and RT-qPCR were used to achieve the aim of the study. SRPIN340 showed no cytotoxicity to CCa. Differential lncRNA gene expression, favoring CCa progressing was observed and these results were verified by increased expressions of MALAT1 and TUG1. The association between splicing factors and lncRNAs is complex, as influence of these 2 parities may be bi-directional. Understating this relationship may unlock diagnostic, prognostic and therapeutic targets in CCa. Citation Format: Lydia Mphahlele, Zodwa Dlamini, Rahaba Makgotso Marima. Determining the effects of serine-arginine protein kinases inhibition on splicing factors and long non-coding ribonucleic acids regulation in cervical cancer cells [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 5580.
Abstract 7437: AI-guided discovery of small molecules targeting eIF4F complex to inhibit oncogenic mRNA translation in castration-resistant prostate cancer
Authors: Fengze Jin, Puja Singh, Hanyong Chen, Yibin Deng
Journal: Cancer Research (2025)

Abstract Effective treatment of castration-resistant prostate cancer (CRPC) remains a significant clinical challenge. Our structure-guided biochemical studies have revealed that the interaction between eukaryotic initiation factors eIF4A and eIF4G within the eIF4F complex plays an essential role for prostate cancer cell survival and CRPC tumor growth. Genetic disruption of the eIF4A-eIF4G interaction in cancer cells selectively inhibits oncogenic mRNA translation, significantly reduces prostate cancer cell survival, and suppresses the in vivo growth of xenografted CRPC tumors. Despite its promise as a therapeutic target, no chemical drug has been developed that effectively disrupts the eIF4A-eIF4G complex to block oncogenic mRNA translation for cancer therapy. To enhance the likelihood of discovering highly biologically active compounds targeting the eIF4A-eIF4G complex, we are developing and utilizing artificial intelligence (AI)-guided “Deep Docking (DD)” algorithms with Schrödinger Molecular Docking platform. This approach enables to develop 'end-to-end' algorithms for structure-based virtual screening (SBVS) of ultra-large chemical libraries containing billions of synthesizable molecules, including novel and unchartered areas of the chemical universe. Building on our resolved structure of the human eIF4A-eIF4G complex, we performed AI-guided SBVS of a chemical library containing 1.5 billion of molecules. By integrating our optimized computational filtering and validation approaches, we identified and selected top-ranked promising candidates for chemical synthesis. Experimental validation of the synthesized compounds demonstrated their abilities to disrupt the eIF4A-eIF4G interaction, block the translation of oncogenic mRNAs such as MYC, MDM2, BCL2, and MCL1, and significantly reduce the survival of CRPC cells. These results demonstrate the effectiveness of our AI-guided platform for structure-based ultra-high chemical library screening, highlighting its potential to accelerate the discovery of drug-like molecules targeting the eIF4F complex. Translationally, the experimentally validated compounds could be advanced into first-in-class therapies for castration-resistant prostate cancer (CRPC) characterized by aberrant activation of the eIF4F complex. Citation Format: Fengze Jin, Puja Singh, Hanyong Chen, Yibin Deng. AI-guided discovery of small molecules targeting eIF4F complex to inhibit oncogenic mRNA translation in castration-resistant prostate cancer [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 7437.
Abstract 7331: Antitumor activity of amivantamab in diffuse pleural mesothelioma
Authors: Shinichiro Suzuki, Lin Yang, Jennifer Ayers-Ringler, Ezequiel J. Tolosa, Kuan-Li Wu, Janet L. Schaefer-Klein, Farhad Kosari, Aaron S. Mansfield
Journal: Cancer Research (2025)

Abstract Background: Diffuse pleural mesothelioma (DPM) is a rare and aggressive cancer arising from mesothelial cells of the pleura. Over 2, 500 new cases are diagnosed annually in the United States, mainly attributable to asbestos exposure. The prognosis is poor, and while nivolumab (PD-1 inhibitor) and ipilimumab (CTLA-4 inhibitor) have been approved for first-line treatment of unresectable DPM, the three-year survival rate is only 23%. DPM tumors express high levels of epidermal growth factor receptor (EGFR) and mesenchymal-epithelial transition (MET), but targeted therapies like erlotinib (EGFR tyrosine kinase inhibitors) have shown no clinical benefit. We hypothesized that amivantamab, a bispecific antibody that targets both EGFR and MET, may have activity against DPM through antibody-dependent cellular cytotoxicity (ADCC). Objective: The purpose of this study was to assess the potential of amivantamab to mediate ADCC in tissue culture experiments with DPM cell lines. Methods: We assessed DPM for the expression of EGFR and MET using available data from bulk RNA sequencing. We also examined protein expressions of EGFR and MET by Western blot analysis in five epithelial (EM-Meso, H2452, H2461, Mero-41 and Mero-95), three sarcomatoid (H2373, H2596 and ONE58), and one normal mesothelial (MeT-5A) cell lines. Co-culture experiments were performed with the DPM and normal cell lines and NK cells in the presence of amivantamab to evaluate ADCC. Results: We identified high levels of EGFR and MET expression in both epithelial and sarcomatoid cases of DPM from 183 patients. This finding was corroborated by Western blot analysis of all eight DPM cell lines. In vitro experiments demonstrated that amivantamab induced dose-dependent ADCC in DPM cell lines, with robust NK cell-mediated ADCC observed across all tested DPM lines. Notably, sarcomatoid-type DPM cells were more sensitive to amivantamab-induced ADCC than epithelial-type cells. These findings suggest that amivantamab may offer therapeutic benefits for DPM tumors with high EGFR and MET expression. Conclusion: This study provides preclinical evidence supporting the potential of amivantamab as a novel therapeutic option for DPM, especially in sarcomatoid tumors. Ongoing in vivo studies including in patient-derived xenograft (PDX) models will further evaluate the efficacy of amivantamab in DPM. Citation Format: Shinichiro Suzuki, Lin Yang, Jennifer Ayers-Ringler, Ezequiel J. Tolosa, Kuan-Li Wu, Janet L. Schaefer-Klein, Farhad Kosari, Aaron S. Mansfield. Antitumor activity of amivantamab in diffuse pleural mesothelioma [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 7331.
Abstract 5556: Development of osimertinib resistant mouse models for preclinical evaluation of third-generation EFGR-TKI therapies
Authors: Hongyan Sun, Yinuo Wang, Shiying Guo, Jianming Xu, Xiang Gao, Jun Wang
Journal: Cancer Research (2025)

Abstract Osimertinib was developed as a third-generation EGFR tyrosine kinase inhibitor. Numerous clinical trials have demonstrated that EGFR-TKI targeted drug therapy for non-small cell lung cancer can prolong the survival of patients. However, its efficacy is impacted by acquired EGFR C797 mutations (including EGFR triple mutations Del19/T790M/C797S and L858R/T790M/C797S). To better understand the drug resistance mechanism towards Osimertinib, we have developed both in vitro and in vivo models associated with Osimertinib resistance for the evaluation of novel therapeutics that overcome Osimertinib resistance. The human lung adenocarcinoma H1975 is a cell line with double mutations in the EGFR gene (L858R/T790M). To create a model which mimics patients in clinic who received Osimertinib treatment and developed drug resistance thereafter, the C797S mutation was introduced using advanced gene editing technology for site-directed mutagenesis, resulting in the EGFR triple-mutant cell line (H1975 with EGFR L858R/T790M/C797S). To explore other Osimertinib resistance mechanisms than the C797 mutation, we induced cell lines in vitro with multiple rounds of increasing concentrations of Osimertinib. Following the induction of Osimertinib, the IC50 of different cell lines treated by Osimertinib was assessed, confirming increased resistance to Osimertinib. In vivo tumorigenicity and efficacy studies with Osimertinib were performed to screen and validate our Osimertinib-resistant models. Currently, we have obtained the EGFR triple mutant H1975 and PC-14 cell lines that exhibit resistance to Osimertinib for in vitro and in vivo study, which serve as vital tools for studying drug resistance mechanisms and developing innovative treatment strategies. Citation Format: Hongyan Sun, Yinuo Wang, Shiying Guo, Jianming Xu, Xiang Gao, Jun Wang. Development of osimertinib resistant mouse models for preclinical evaluation of third-generation EFGR-TKI therapies [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 5556.