tbuckley/cabot-search huggingface dataset:
Abstract 1259: Studying the role of chromatin accessibility in lineage plasticity of Rb1-deficient EGFR-mutant lung adenocarcinoma
Authors: Bradley Balk, David W. Goodrich
Journal: Cancer Research (2025)

Abstract Lung cancer is the leading cause of cancer mortality worldwide. Mutations in the epidermal growth factor receptor (EGFR) account for approximately 27% of all lung adenocarcinoma (LUAD) cases. Osimertinib is a third generation EGFR tyrosine kinase inhibitor (TKI) that is, initially, remarkably effective at treating patients with EGFR mutant LUAD. Acquired resistance to Osimertinib develops in most patients leaving few therapeutic options. This highlights an unmet clinical need to prevent/combat Osimertinib resistance. Lineage plasticity, an epigenetic process characterized by transcriptional heterogeneity and molecular adaptation, has been identified as a mechanism of Osimertinib resistance in the clinic. As more potent targeted therapeutics are deployed for treating cancer patients, plasticity-based resistance will likely increase. The molecular basis of lineage plasticity is not well understood, and greater characterization of lineage plasticity is imperative for developing new therapies aimed at preventing/reversing plasticity-associated resistance. Loss of the major tumor suppressor gene Rb1 has previously been implicated in lineage plasticity of several different cancers including LUAD. How loss of Rb1 contributes towards lineage plasticity remains poorly understood. Rb1 is a known regulator of chromatin accessibility, playing a key role in recruiting epigenetic writers to silence gene expression through repressive methylation of histones and DNA. Whether altered chromatin regulation in the absence of Rb1 contributes to LUAD lineage plasticity has not been examined. To begin examining the chromatin accessibility/plasticity axis in vitro, we are developing a PROTAC-based, rapidly inducible Rb1 protein degradation system utilizing the dTAG degron system to characterize the dynamics of molecular changes subsequent to Rb1 loss of function. Changes in chromatin accessibility will be assessed by micrococcal nuclease digestion and a novel nuclear propidium iodide staining technique. Plasticity will be assessed indirectly by in vitro colony formation and time to resistance assays. The timing of changes in transcriptional plasticity and chromatin accessibility will be compared. The goal of this project is to gain a greater understanding of how Rb1 loss impacts chromatin structure and subsequently, whether increased chromatin accessibility promotes plasticity-associated Osimertinib resistance. Citation Format: Bradley Balk, David W. Goodrich. Studying the role of chromatin accessibility in lineage plasticity of Rb1-deficient EGFR-mutant lung adenocarcinoma [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 1259.
Principles and Operation of Virtual Brain Twins
Authors: Meysam Hashemi, Damien Depannemaecker, Marisa Saggio, Paul Triebkorn, Giovanni Rabuffo, Jan Fousek, Abolfazl Ziaeemehr, Viktor Sip, Anastasios Athanasiadis, Martin Breyton, Marmaduke Woodman, Huifang Wang, Spase Petkoski, Pierpaolo Sorrentino, Viktor Jirsa
Journal: IEEE Reviews in Biomedical Engineering (2025)

Current clinical methods often overlook individual variability by relying on population-wide trials, while mechanismbased trials remain underutilized in neuroscience due to the brain's complexity. This situation may change through the use of a Virtual Brain Twin (VBT), which is a personalized digital replica of an individual's brain, integrating structural and functional brain data into advanced computational models and inference algorithms. By bridging the gap between molecular mechanisms, whole-brain dynamics, and imaging data, VBTs enhance the understanding of (patho)physiological mechanisms, advancing insights into both healthy and disordered brain function. Central to VBT is the network modeling that couples mesoscopic representation of neuronal activity through white matter connectivity, enabling the simulation of brain dynamics at a network level. This transformative approach provides interpretable predictive capabilities, supporting clinicians in personalizing treatments and optimizing interventions. This Review outlines the key components of VBT development, covering the conceptual, mathematical, technical, and clinical aspects. We describe the stages of VBT construction-from anatomical coupling and modeling to simulation and Bayesian inference-and demonstrate their applications in resting-state, healthy aging, multiple sclerosis, and epilepsy. Finally, we discuss potential extensions to other neurological disorders, such as Parkinson's disease, and explore future applications in consciousness research and brain-computer interfaces, paving the way for advancements in personalized medicine and brainmachine integration.
Abstract 5510: Targeting BET, Hippo-YAP and RAS-MAPK signaling interplay in lung cancer and therapy resistance
Authors: Nilanjana Chatterjee, Victor Olivas, Wei Wu, Tracy Tang, Ben Powell, Trever Bivona
Journal: Cancer Research (2025)

Abstract Identifying alternate survival pathways or compensatory mechanisms that limit the response to targeted therapy is critical to discover effective combinatorial strategies for lung cancer treatment and prevention of drug resistance.Using a combinatorial drug screen in a panel of non-small cell lung cancer (NSCLC) cell lines, we identified a functional interplay between RAS-MAPK pathway oncoproteins and BET chromatin regulators in non-small cell lung cancer (NSCLC). We found that combination of BET and RAS-MAPK inhibitors caused pronounced cell death and potent tumor regression/ stasis in several KRAS or BRAF mutant models of NSCLC with potent apoptosis induction, pro-apoptotic BIM upregulation, and pro-survival MYC and BIRC5 (Survivin) downregulation. However, NSCLC cells and tumors with co-occurring alterations in the tumor suppressor STK11 were found to be partially sensitive/ resistant to the BET and RAS-MAPK inhibitors combination. By modeling STK11 deficiency in NSCLC cells and tumors, we further found that STK11 loss creates an unprecedented dependence on YAP/TEAD TFs in lung cancer. STK11 silencing in NSCLC cells resulted in the nuclear translocation of the Hippo pathway effector, YAP and activation of YAP targets, conferred resistance to RAS-MAPK inhibitors and their combination with BET inhibitors and restored cell viability. Furthermore, phenocopying STK11 loss, constitutively active 5SAYAP mitigated the deleterious effects of BET and RAS-MAPK co-inhibition in STK11-proficient NSCLC cells with concomitant upregulation of YAP targets, such as, MYC and BIRC5. Conversely, YAP/TEAD suppression re-sensitized STK11-deficient NSCLC cells and tumors to BET and RAS-MAPK inhibitors combination and induced apoptosis, pronounced loss in cell viability, and tumor regression.This study uncovered a functional interplay between BET chromatin regulators, YAP/TEAD TFs and RAS-MAPK oncoproteins that drives therapy resistance in lung cancer, specifically upon loss of key tumor suppressors, such as, STK11 and suggests rational combinatorial strategies with BET, TEAD and RAS-MAPK inhibitors. Citation Format: Nilanjana Chatterjee, Victor Olivas, Wei Wu, Tracy Tang, Ben Powell, Trever Bivona. Targeting BET, Hippo-YAP and RAS-MAPK signaling interplay in lung cancer and therapy resistance [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 5510.
Abstract 1576: RenBiologics- a fully human antibody library generated by RenMice facilitates the development of antibody drugs
Authors: Ting Yi, Jun Du, Yue Zhang, Yuting Hu, Shujin Zhang, Xin Ji, Yi Yang
Journal: Cancer Research (2025)

Therapeutic antibodies have become important drugs in the field of targeted therapy because of their high specificity to target antigens. Currently, over 100 antibody drugs have been approved for the treatment of various human diseases, yet the targets covered are indeed limited, with approximately half of these drugs targeting only 10 common targets. Approved drugs encompass not only monoclonal antibodies but also antibody-drug conjugates, bispecific antibodies, and antibody fragments. The scarcity of antibody drug targets and subsequent conjugation or engineering modifications pose challenges for the development of novel antibody drugs. In response to the growing demand for fully human antibody drugs, Biocytogen’s antibody discovery team has generated a library of antibodies targeting hundreds of antigens using fully human antibody transgenic mice (RenMice). Our RenMice undergo additional gene-editing procedures to knock out designated target genes. Subsequently, antibodies obtained by conventional immunization have a wide range of epitope-binding properties to homologous protein targets, but also exhibit cross-species reactivity. We have completed over 900 fully human antibody target projects and established a library containing over four hundred thousand off-the-shelf fully human antibody sequences. The antibodies generated from RenMice can be used in a variety of applications, and many of the TAA (tumor-associated antigen)-targeting antibodies have been screened for internalization activity to ensure suitability for ADC development. In addition to fully human monoclonal antibody derived from RenMab platform (fully human immunoglobulin variable domains replacing the mouse loci), RenLite-derived common light chain antibodies are easy to assemble into bispecific antibodies (BsAb) with low mismatch rate and ideal physiochemical properties, which are suitable for BsADC, biparatopic antibody (BpAb) and other modalities. Small and flexible fully human nanobodies based on RenNano platform (fully human heavy chain only) also provide solutions for specific antigen epitopes or multi-targets, multi-epitope antigens. Thus, the fully human antibody library can accelerate the development of antibody drugs. Citation Format: Ting Yi, Jun Du, Yue Zhang, Yuting Hu, Shujin Zhang, Xin Ji, Yi Yang. RenBiologics- a fully human antibody library generated by RenMice facilitates the development of antibody drugs [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 1576.
Abstract 1695: Paricalcitol plus hydroxychloroquine enhances gemcitabine activity and induces mesenchymal to epithelial transition in pancreatic ductal adenocarcinoma
Authors: Ganji Purnachandra Nagaraju, Madhu Sudhana Saddala, Sujith Sarvesh, Dhanasekhar Reddy Bandi, Ateeq Muhammed Khaliq, Ashiq Masood, Mehmet Akce, Bassel F. El-Rayes
Journal: Cancer Research (2025)

Abstract Epithelial mesenchymal transition (EMT) describes a process by which the epithelial cells acquire mesenchymal properties associated with increased migration, invasion, and resistance to therapy. Targeting the intercellular communications and molecular changes that enable EMT is a rational therapeutic approach in PDAC. Our group has previously reported on KPC-Luc PDAC orthotopic mouse models treated with 1. Sham, 2. paricalcitol plus hydroxychloroquine (PH), 3. gemcitabine (G), and 4. GPH. Single cell RNA sequence (scRNASeq) was performed and analyzed using hdWGCNA (high dimensional Weighted Gene Co-expression Network Analysis) and GSEA (Gene Set Enrichment Analysis) to plot and determine intracellular interactions as well as gene expression changes in various treatment conditions. GPH treatment reduces EMT, which is associated with the downregulation of the essential gene fibronectin (Fn1). Collagen and Fn1 pathways co-expression decreases in GPH-treated KPC-Luc tumors. Cancer-associated fibroblasts (CAFs) appear dominant in Collagen signaling, whereas macrophages mediate Fn1 signaling. GPH treatment reduces the expression interaction strength between ligands and receptors (Collagen-Integrin and Fn1-Cd44 or Fn1-Sdc4) compared to sham, PH, and G. This comprehensive study of cell-cell communication and molecular changes during therapy offers a deep understanding of the molecular underpinnings of PDAC-EMT and metastasis and identifies possible targets for GPH. Citation Format: Ganji Purnachandra Nagaraju, Madhu Sudhana Saddala, Sujith Sarvesh, Dhanasekhar Reddy Bandi, Ateeq Muhammed Khaliq, Ashiq Masood, Mehmet Akce, Bassel F. El-Rayes. Paricalcitol plus hydroxychloroquine enhances gemcitabine activity and induces mesenchymal to epithelial transition in pancreatic ductal adenocarcinoma [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 1695.
Abstract 4680: Simultaneous DDR1/FGFR inhibition elicits adaptive EGFR/MAPK pathway activation to counteract susceptibility to radiochemotherapy in preclinical glioblastoma models
Authors: Anne Vehlow, Irina Korovina, Olegs Borodins, Nils Cordes
Journal: Cancer Research (2025)

Abstract GBM cell survival critically depends on cell adhesion molecules like discoidin domain receptor 1 (DDR1) and receptor tyrosine kinases like fibroblast growth factor receptors (FGFR), both of which represent potential therapeutic vulnerabilities. Based on the radiochemosensitizing potential of DDR1 mono-inhibition, we investigated the adaptive response induced by DDR1 deactivation using broad-spectrum kinome analyses. Since FGFR were identified most hyperactive, we examined the efficacy of simultaneous pharmacological DDR1/FGFR inhibition and found enhanced cytotoxicity and radiochemosensitization in a human gliomasphere panel. Subsequent evaluation of DDR1 and FGFR single and dual inhibition in orthotopic, radiochemotherapy-treated GBM mouse models revealed a profound reduction in efficacy for dual as opposed to single inhibition. This was mechanistically underpinned through RNA-seq analyses uncovering strong activation of EGFR/MAPK signaling under DDR1/FGFR deactivation relative to monotherapies. In conclusion, our data evidently show that particularly DDR1 monotherapy effectively augments radiochemotherapy in GBM, while simultaneous DDR1/FGFR inhibition requires more in-depth investigation. Citation Format: Anne Vehlow, Irina Korovina, Olegs Borodins, Nils Cordes. Simultaneous DDR1/FGFR inhibition elicits adaptive EGFR/MAPK pathway activation to counteract susceptibility to radiochemotherapy in preclinical glioblastoma models [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 4680.
Abstract 4676: MRI-based radiomics ensemble model for predicting radiation necrosis in brain metastasis patients treated with stereotactic radiosurgery and immunotherapy
Authors: Yijun Chen, Corbin A. Helis, Christina K. Cramer, Michael T. Munley, Fei Xing, Qing Lyu, Christopher T. Whitlow, Jeffrey Willey, Michael D. Chan, Yuming Jiang
Journal: Cancer Research (2025)

Abstract This study aims to apply an ensemble model integrating MRI-based radiomics and clinical information as a reliable tool for precisely predicting radiation necrosis, a severe consequence of radiation therapy for brain metastases that requires accurate early prediction to improve patient management. We retrospectively collected and analyzed MRI images and clinical information from 209 stereotactic radiosurgery sessions involving 130 patients with brain metastasis. Radiomic features were extracted from MRI using PyRadiomics and selected via L2 regularization and coefficient analysis. An ensemble model integrating gradient boosting, random forest, decision tree, and support vector machine as base regressors was developed using a soft voting approach to generate the final prediction of the likelihood of necrosis. Performance was assessed and compared with other machine-learning algorithms using metrics including the area under the curve (AUC), sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV). SHapley Additive exPlanations (SHAP) and local interpretable model-agnostic explanations (LIME) analyses were applied to explain the model's prediction. The soft-voting ensemble model demonstrated strong performance in the validation cohort, achieving the highest AUC of 0.873 (95%CI: 0.672 - 1.000). It consistently outperformed individual models and the stacking ensemble model, exhibiting superior accuracy, generalizability, and reliability in predicting radiation necrosis. Both univariate and multivariate logistic regression analyses were performed and confirmed the model as the strongest predictor. SHAP and LIME analyses were employed to interpret the predictive model for radiation necrosis, identifying metastasis volume and the radiomic feature, log-sigma-1-mm_glcd_ldmn, as key predictors. Both analyses highlighted similar significant factors, enhancing the understanding of prediction dynamics. This MRI-based radiomics ensemble model exhibited high accuracy and robustness in predicting radiation necrosis. It has the potential to serve as a novel and valuable tool to facilitate radiotherapy for patients with brain metastasis. Citation Format: Yijun Chen, Corbin A. Helis, Christina K. Cramer, Michael T. Munley, Fei Xing, Qing Lyu, Christopher T. Whitlow, Jeffrey Willey, Michael D. Chan, Yuming Jiang. MRI-based radiomics ensemble model for predicting radiation necrosis in brain metastasis patients treated with stereotactic radiosurgery and immunotherapy [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 4676.
Abstract 1679: APG-2449, a novel focal adhesion kinase (FAK) inhibitor, enhances the antitumor activity of chemotherapy in preclinical models of small-cell lung cancer (SCLC) with activated FAK
Authors: Zhou Yu, Zhiyan Liang, Xinyi Yao, Daojie Liu, Dajun Yang, Yifan Zhai
Journal: Cancer Research (2025)

Abstract Background: SCLC is a genetically heterogeneous disease with no standardized targeted therapy options. Despite the recent advancement of immune checkpoint inhibitors, improvements in overall survival have been modest, and platinum-based chemotherapy combined with topoisomerase inhibitors remains the standard of care in SCLC. FAK, a non-receptor tyrosine kinase, has been reported to regulate cellular proliferation, migration, invasion, and DNA-damage repair. Previous studies have shown that FAK is amplified and overexpressed in SCLC tumors. Although non-small-cell lung cancer cells harboring FAK6, 7 (splicing isoforms of FAK that increase phosphorylation of FAK [pFAK]) are more sensitive to FAK inhibition than wild-type FAK (FAKWT), the expression and implications of FAK6, 7 expression in SCLC remain unclear. Given the role of FAK in cancer progression, we hypothesized that inhibition of FAK would augment the antitumor effects of chemotherapy in SCLC. The aim of this study was to evaluate the antitumor activity of investigational agent APG-2449 alone and combined with chemotherapy in SCLC. Methods: Cellular proliferation was measured by CellTiter-Glo® assays and apoptosis assessed via flow cytometry. Protein expression levels were examined via western blot. An H446 xenograft model was used to evaluate antitumor effects in vivo. Results: SCLC cell lines harboring FAK6, 7 (H446, H69, and H526) showed increased sensitivity to APG-2449 in a dose-dependent manner compared to a FAKWT cell line (DMS-114). When combined with chemotherapy (topotecan or etoposide plus carboplatin), APG-2449 synergistically decreased cell viability and increased apoptosis in H446 and H526 cell lines. Mechanistically, APG-2449 combined with topotecan and etoposide plus carboplatin enhanced DNA damage and apoptosis compared to either therapy alone in western blot assays. APG-2449 synergistically enhanced the antitumor effects of topotecan (synergy ratio: 22.08) and etoposide plus carboplatin (synergy ratio: 3.81) in the H446 xenograft model. Conclusions: Novel FAK inhibitor APG-2449 demonstrated a synergistic enhancement when combined with first- and second-line chemotherapies in SCLC, significantly increasing antitumor activity. These encouraging findings support further clinical development of APG-2449 for the treatment of patients with SCLC. Citation Format: Zhou Yu, Zhiyan Liang, Xinyi Yao, Daojie Liu, Dajun Yang, Yifan Zhai. APG-2449, a novel focal adhesion kinase (FAK) inhibitor, enhances the antitumor activity of chemotherapy in preclinical models of small-cell lung cancer (SCLC) with activated FAK [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 1679.
Abstract 2470: Transforming cancer diagnosis with digital chemical pathology
Authors: Kianoush Falahkheirkhah, Kevin Yeh, Ji-Hun Oh, Yen-Ting Liu, Ruo-Jing Ho, Ishaan Sharma, Matthew Confer, Andres Orr, Mykolas Tamonis, John Cheville, Rohit Bhargava
Journal: Cancer Research (2025)

Pathology remains a labor-intensive discipline, relying on workflows rooted in practices established over a century ago. Despite incremental technological advancements, the diagnostic process—from tissue preparation to interpretation—still heavily depends on thinly sliced tissue sections stained and examined under brightfield microscopy by skilled pathologists. Difficult cases often necessitate iterative staining or complex immunohistochemistry (IHC) analyses. However, the recent emergence of machine learning (ML) presents an opportunity to revolutionize traditional diagnostic workflows. One promising advancement is Digital Chemical Pathology (DCP), a paradigm that combines modern ML algorithms with infrared (IR) imaging to streamline pathology and enhance diagnostic accuracy. Infrared wavelengths inherently align with molecular vibrational frequencies, providing intrinsic contrast based on the chemical composition of samples. Mid-IR spectroscopic microscopes leverage this principle to spatially resolve molecular distributions at the pixel level, creating "chemical fingerprints" that ML algorithms can correlate with cellular identities and disease states. Recent advancements, particularly the development of broadly tunable quantum cascade lasers (QCLs), have enabled faster IR imaging, paving the way for clinical applications of IR spectroscopic microscopes. In this research, we demonstrate the potential of DCP using frozen tissue samples. Our approach focuses on two core tasks: (1) virtual staining, translating IR images into realistic, stained images interpretable by pathologists, and (2) tissue segmentation, enabling the automated detection of cancer and the distinction between normal and cancerous tissues. Furthermore, we incorporate statistical safety algorithms to generate uncertainty maps, ensuring the reliability of predictions. Our findings highlight that the integration of IR imaging and ML can facilitate automated diagnostics, providing pathologists with powerful tools for enhanced healthcare delivery. By leveraging DCP, we aim to modernize pathology workflows, reduce diagnostic turnaround times, and improve patient outcomes through precise and efficient analysis. Citation Format: Kianoush Falahkheirkhah, Kevin Yeh, Ji-Hun Oh, Yen-Ting Liu, Ruo-Jing Ho, Ishaan Sharma, Matthew Confer, Andres Orr, Mykolas Tamonis, John Cheville, Rohit Bhargava. Transforming cancer diagnosis with digital chemical pathology [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 2470.