tbuckley/cabot-search huggingface dataset:
Abstract 189: The role of DEPTOR in promoting breast cancer initiation and progression
Authors: Alice Jisoo Nam, Bin Xiao, Virginie Sanguin-Gendreau, Dongmei Zuo, William J. Muller
Journal: Cancer Research (2025)

Abstract Breast cancer is one of the most common malignancies in the world, with 2.3 million women diagnosed in 2022. It is largely driven by dysregulation of cellular signaling pathways such as mTOR, which, as a key regulator of cellular growth, is frequently hyperactivated in many cancers. Despite evidence implicating mTOR as a promising target for anti-cancer therapies, many inhibitors in clinical trials yield unfavorable outputs, largely due to its complex regulatory mechanisms that are yet fully understood. DEPTOR, a recently identified direct inhibitor of mTOR, has thus become an intriguing focus of study. Interestingly, while many tumors exhibit high mTOR activity and, as expected, also show low DEPTOR expression, paradoxically, high DEPTOR levels in several cancers corresponds with the worst prognoses for patients. These observations point to dual roles for this protein, and unknown pro-tumor functions that are potentially independent of mTOR. Our work aims to expand our understanding of the functions and interacting partners of DEPTOR, and characterize its role in breast cancer, about which knowledge is currently lacking. In a mouse model of luminal B breast cancer, we observe a severe defect in early mammary cell expansion, delay in tumor onset, and reduction in tumor penetrance upon genetic ablation of DEPTOR, indicating DEPTOR acts in an oncogenic capacity in this system. However, these results are not accompanied by a significant change in activity of major mTOR effectors, and gene expression profiles indicate changes in factors related to transcription and chromatin accessibility but not translation, despite the latter being largely modulated by mTOR to drive cell growth. Additionally, while the innate proliferative ability of early DEPTOR-deficient mammary cancer cells appears unchanged, their immune microenvironment (TIME) is altered to favour an anti-tumor immune response. Thus, we will investigate how DEPTOR-dependent transcriptional regulation may reprogram the TIME to influence tumor initiation and progression. Considering mTOR’s ubiquity in cancer, elucidating the activities of a core regulatory component such as DEPTOR will provide important insights for its therapeutic targeting. Further, by investigating DEPTOR’s mTOR-independent roles, this work will highlight the scope of a poorly understood but widely acting player in cancer and its potential as a novel therapeutic target. Citation Format: Alice Jisoo Nam, Bin Xiao, Virginie Sanguin-Gendreau, Dongmei Zuo, William J. Muller. The role of DEPTOR in promoting breast cancer initiation and progression [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 189.
Abstract 1078: Enhancing reusability and adoption of cancer research tools: Development of the Cancer Complexity Toolkit
Authors: Aditi Gopalan, Brad Macdonald, James Eddy, Thomas Yu, Susheel Varma, Jineta Banerjee, Jineta Banerjee
Journal: Cancer Research (2025)

Abstract The Cancer Complexity Knowledge Portal (CCKP) is an open-access data repository that stores and shares resources from multiple cancer research programs. Maintained by Sage Bionetworks, in collaboration with The Multi-Consortia Coordinating (MC2) Center, which supports six NCI Division of Cancer Biology (DCB) funded programs made up of interdisciplinary communities of scientists, the CCKP centralizes access to cancer research tools and data, improving their discoverability and reuse.Reusing tools has proven to be challenging for various reasons. Therefore, we aim to enhance the reusability of the tools available on CCKP. To achieve this, we are designing and implementing a Cancer Complexity Toolkit to validate tool reusability and increase their adoption. Building on existing efforts to curate tools generated by the cancer research community, the 'Cancer Complexity Toolkit' aims to achieve three key objectives: (1) enhancing the discovery and reuse of cancer research tools through rich metadata and standardized evaluation frameworks, (2) creating a catalog of cancer research-focused tools to improve accessibility and confidence in their use, and (3) enabling standardized reporting and validation of tool functionality. Ultimately, we aim to provide a robust platform for discovering, validating, and integrating computational tools in cancer research.To achieve these goals, we are (1) refining a standardized schema to capture metadata on tool parameters and usage, (2) building infrastructure for automated checks to assess documentation, test coverage, and community metrics, and (3) developing tool cards to display relevant metrics and metadata, helping researchers select the right tools and allowing developers to highlight their tools' impact.In Phase 1, we refined the tool metadata schema and developed a Python-based testing infrastructure to check for documentation, testing files, and deployment on non-native Linux environments. We selected ten tools from the CCKP for initial testing, generating logs that assess their reusability. Citation Format: Aditi Gopalan, Brad Macdonald, James Eddy, Thomas Yu, Susheel Varma, Jineta Banerjee, Jineta Banerjee. Enhancing reusability and adoption of cancer research tools: Development of the Cancer Complexity Toolkit [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 1078.
Abstract 431: Novel WRN drug resistant CDX models
Authors: Haiting Dai, Tiejun Bing, Huayi Qu, Huawei Pan, Wen-Jen Yu
Journal: Cancer Research (2025)

Abstract Microsatellite Instability (MSI) is a condition characterized by the presence of mutations in microsatellite regions of DNA. This can lead to the accumulation of mutations in microsatellite regions, resulting in genomic instability and happened in various cancer types. Werner helicase (WRN) plays an important role in highly MSI (MSI-H) cancer cells and cause synthetic lethality when WRN was inhibited or knockout. Few WRN inhibitor like HRO761 and VVD-214 were revealed effectively killing the MSI-H cancer cells such as human colorectal cell lines HCT116 and SW48. In this study, to face the new unmet need that WRN inhibitors anti-cancer drugs may occurred, a WRN inhibitor resistant cell line against HRO761 and VVD-214 were established through the combination drug tolerance in vivo and in vitro was established. The drug resistant tumor tissues were collected after the in vivo drug resistance appeared as regrowth of tumors under 20 mg/kg HRO761 and 5 mg/kg VVD-214 treatment and dissected for primary cell culture to get the drug resistant cell line by escalating drug concentrations in vitro. The WRN inhibitors resistant cell lines were genotype and phenotype checked by STR and IC50 of cell growth when reached the drug resistant index more than 5 times of that of parental cells and indicated that different WRN inhibitors resistant HCT116 cell lines were successfully established and helpful for the discovery of anti-cancer drugs targeted on resistant to WRN inhibitors. Citation Format: Haiting Dai, Tiejun Bing, Huayi Qu, Huawei Pan, Wen-Jen Yu. Novel WRN drug resistant CDX 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 431.
Abstract 43: Establishment and characterization of prostate adenocarcinoma XPDX models from naïve and pretreated patients
Authors: Johnnie Flores, Alyssa Simonson, Anna Stackpole, Jennifer Garcia, Shaquille Johnson, Pedro Cesenes, Mia Lopez, Peter Forofontov, Lisa Gonzales, Garrett Mercer, Amarissa Rojas, Nehal Lakhani, Emiliano Calvo, Andrew Cunningham, Michael J. Wick
Journal: Cancer Research (2025)

Abstract Background: Preclinical models of prostate adenocarcinoma (PAC) are challenging to develop and maintain. We previously reported (AACR2022/ENA2023) the successful establishment and characterization of four parental and three conditioned prostate adenocarcinoma models in intact immunodeficient male mice. Using this experience, we have expanded our platform with six additional PAC models designated ST6084, ST6838, ST7482, ST7695, STF1159 and STM344. These models were characterized for receptor expression, genomic alterations, and in vivo drug sensitivity to relevant therapies. Methods: XPDX models representing prostate cancer were established from primary (ST6084, ST6838, ST7695, STF1159) or metastatic (ST7482, STM344) samples implanted into intact CB-17 SCID mice. Resulting models were passaged serially and further developed in both intact and castrated mice until growth stabilization. Resulting models were characterized using genomic analysis, including WES and RNAseq, receptor expression, and in vivo drug sensitivity studies. For in vivo studies, docetaxel, abiraterone and enzalutamide were evaluated at standard treatment regimens. Study endpoints included tumor volume and time from treatment initiation with %T/C values and tumor regression reported at study completion; a %T/C of ≤ 20% versus control was considered sensitive. Tumor regression (%T/C&amp;lt;0%) versus Day 0 tumor volume was also reported. Results: Most models lacked AR or PSMA staining but ST6838 and STM344 were positive for AR-V7. Genomic characterization identified KDM6A loss in ST7482, a model from a patient post-apalutamide. An ATM aberration was present in both ST7482 and STM344, the latter derived from a patient post-chemo and targeted therapies including a five-month response on an ATR inhibitor. No tested models were sensitive to abiraterone or enzalutamide (%T/C&amp;gt;20%) and only ST7482 was sensitive to docetaxel. Conclusion: We have established and characterized an expanded panel of PAC XPDX models. These models can be utilized as a valuable tool in better understanding prostate cancer and in developing novel therapies for drug-resistant patients. Citation Format: Johnnie Flores, Alyssa Simonson, Anna Stackpole, Jennifer Garcia, Shaquille Johnson, Pedro Cesenes, Mia Lopez, Peter Forofontov, Lisa Gonzales, Garrett Mercer, Amarissa Rojas, Nehal Lakhani, Emiliano Calvo, Andrew Cunningham, Michael J. Wick. Establishment and characterization of prostate adenocarcinoma XPDX models from naïve and pretreated patients. [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 43.
Abstract 428: Low cellular pH promotes survival in CDK4/6 inhibitor resistant ER+ breast cancer
Authors: Erin R. Scheidemann, Ayesha N. Shajahan-Haq
Journal: Cancer Research (2025)

Abstract Cyclin dependent kinase 4 and 6 inhibitors (CDK4/6i) are part of standard of care therapy in combination with antiestrogens for the treatment of metastatic estrogen receptor positive (ER+) breast cancer. However, resistance to CDK4/6i is prevalent and advanced metastatic ER+ breast cancer remains incurable. Beside inhibiting the cell cycle, CDK4/6i are known to induce accumulation of lysosomes in sensitive cells but the role of lysosomes in CDK4/6i resistance remains elusive. Recently, we have shown that CDK4/6i resistant breast cancer cells gain metastatic potential relative to sensitive cells and this is potentially due to deregulated lysosomes. We have shown that all three CDK4/6i induce rapid cellular acidification in sensitive cells, which suggests a role of cellular pH in CDK4/6i-mediated cell death. Particularly, in abemaciclib resistant cells, intracellular pH is lower (pH=6.9) than that of sensitive cells (pH=7.4). Therefore, we hypothesize that a lower pH in CDK4/6i resistant cells promotes survival and this pathway can be leveraged to target resistance. Interestingly, protein levels of carbonic anhydrase IX (CA9), an important regulator of cellular pH, are significantly elevated in resistant cells. Increased CA9 levels correlate with impaired overall survival in breast and other cancers. Small molecule inhibitor of CA9, S4 or the clinical-grade drug SLC-0111, inhibits growth and invasive potential in resistant cells when combined with CDK4/6i plus an antiestrogen. CDK4/6-induced cellular acidity correlated with increased levels of hypoxia-inducible factor 2-alpha (HIF2α) protein in sensitive cells. Moreover, basal HIF2α was increased in resistant cells compared with sensitive cells. Furthermore, knockdown of HIF2α reduces CA9 protein expression and inhibits proliferation in resistant cells. Thus, our study highlights the role of the modulation of pH homeostasis as a mechanism for CDK4/6i resistant breast cancer and identifies CA9 and HIF2α as novel targets in treating advanced ER+ breast cancer. Citation Format: Erin R. Scheidemann, Ayesha N. Shajahan-Haq. Low cellular pH promotes survival in CDK4/6 inhibitor resistant ER+ breast 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 428.
Abstract 316: Translational studies of HDM2012, a novel topoisomerase inhibitor ADC targeting MUC17, in patient derived GC, CRC, PDAC tumor models
Authors: Qinyu Shu, Zhaofeng Qin, Shengxing Zhao, Yang Chen, Kuan Lu, Qian Zhang, Liubin Guo, Qingli Wei, Hao Pan, Yan Xia, Hongwen Li, Dongzhou Jeffery Liu
Journal: Cancer Research (2025)

Introduction: Mucin-17 (MUC17) is a transmembrane glycoprotein, expressed on the apical membrane of normal gastrointestinal mucosal epithelial cells, play important roles in preventing infection at mucosal surfaces1-2. MUC17 is a promising target for ADC development due to its highly expressed in gastric, colon and pancreatic cancers, but limit normal organs expression. Methods: HDM2012 is a MUC17 targeting ADC, consisting of a topoisomerase inhibitor via a cleavable liker with average drug antibody ratio (DAR) 8. The efficacy and safety of HDM2012 was tested in patient derived xenograft (PDX) models and monkeys, respectively. Results: HDM2012 showed target dependent anti-tumor activity and by-stander effect in vitro. HDM2012 exhibits good efficacy in PDX and CDX models. In gastric PDX models, HDM2012 demonstrated dose dependent efficacy, with TGI (tumor growth inhibition) value of 82-93%, regardless of prior Ironitecan and Top-I ADC treatment. In heavily pre-treated colon cancer PDX models, HDM2012 induced prolonged tumor regression, with TGI value of 94.6%. Furthermore, in MUC17 low expression pancreatic PDX models, HDM2012 could induce sustained tumor regression, with TGI value of 91.5%. In exploratory toxicology study, HDM2012 is well tolerated by cynomolgus monkeys at 45 mpk. Conclusion: Here, we reporting a novel ADC product HDM2012 targeting MUC17, is a potential therapeutic approach for MUC17 positive GC, CRC, PDAC cancer treatment. All the experiment data indicated HDM2012 may be a promising candidate for GI cancer treatment. Reference: 1. Gum JR, et al. Biochem Biophys Res Commun.2002;291:466-475. 2. Van Putten JPM, et al. J Innate Immun. 2017;9:281-299. Citation Format: Qinyu Shu, Zhaofeng Qin, Shengxing Zhao, Yang Chen, Kuan Lu, Qian Zhang, Liubin Guo, Qingli Wei, Hao Pan, Yan Xia, Hongwen Li, Dongzhou Jeffery Liu. Translational studies of HDM2012, a novel topoisomerase inhibitor ADC targeting MUC17, in patient derived GC, CRC, PDAC tumor 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 316.
Abstract 1016: Reduction of social disparities in clinical cancer feature prediction via somatic evolutionary embedding of mutational data
Authors: Nic Fisk, Jeffrey P. Townsend
Journal: Cancer Research (2025)

Whole exome and whole genome sequencing (WES/WGS) of tumors provide rich repositories of information towards understanding the etiology of various cancer and how best to prevent and intervene in its progression. Studies utilizing these technologies, however, notably skew towards the inclusion of patients from white and well-resourced backgrounds. Considerable and ongoing effort has gone into reducing the disparate representation of WES/WGS data from diverse and global populations in the collective digital tumor corpus; however, the rapid development and deployment of machine learning models for cancer has not paused in wait of data reflective of the populace. This dissonance has resulted in imbalanced and, in an absolute sense, small WES/WGS data being used by increasingly complex machine learning models. Targeted sequencing panels, such as those hosted by AACR Project GENIE, are still skewed in a relative sense, but contain many more samples from all populations due to their routine clinical deployment and comparatively inexpensive. However, panel sequencing data is fundamentally limited in the amount of information captured. It is incumbent, then, to maximize the information that can be derived from WES/WGS data as it applies to somatic mutations assayed in these abundant targeted sequencing panels. As cancer is ultimately a disease of somatic evolution, with even social and germline contributors to cancer often actualized via somatic mutation, impact scores—derived from observed evolutionary conservation over extended organismal timescales—are frequently used to contextualize somatic mutations for input into predictive machine learning models. We show that cancer effect size, a disease-specific, empirical measure of evolutionary benefit conferred to the tumor by a mutation, matches or outperforms impact measures to this end across a wide range of clinical features of cancer. Further, we apply a transfer learning approach to leverage the feature importance discovered by the cancer effect size annotated WES/WGS models to train models using targeted panel data. We find this embedding to not only improve the performance on predictive tasks overall, but also that it disproportionately improves performance for underrepresented groups. Lastly, we show that, while improvements to models and clever embedding of data undoubtedly can reduce disparities in model performance, the simple inclusion of samples from more diverse, representative individuals reduces that disparity more effectively. Citation Format: Nic Fisk, Jeffrey P. Townsend. Reduction of social disparities in clinical cancer feature prediction via somatic evolutionary embedding of mutational data [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 1016.
Abstract 435: JAK/STAT1-interferon-ISGylation networks in breast cancer resistance to inhibitors of FOXM1 and CDK4/6
Authors: Benita S. Katzenellenbogen, Yvonne Ziegler, Sandeep Kumar, Blake N. Plotner, Carlos M. Saeh, Grace O. Pento, Sung Hoon Kim, Rachel Schiff, John A. Katzenellenbogen
Journal: Cancer Research (2025)

Abstract Resistance to targeted therapies often develops in advanced estrogen receptor (ER)-positive breast cancer, but the mechanisms underlying this resistance are still not fully known. We show that ER-positive FOXM1 inhibitor resistant cells and CDK4/6 inhibitor (Palbociclib and Abemaciclib) resistant cells all exhibit an increased JAK/STAT1-interferon responsive gene and protein signaling network with elevated interferon stimulated gene15 (ISG15). ISG15 protein is present as high intracellular free ISG15 and also as increased ISGylated protein conjugates that can be markedly reduced by treatment of resistant cells with the JAK1/2 inhibitor ruxolitinib. Likewise, resistant cells contain increased levels of ubiquitin-like conjugating enzymes HERC5 and HERC6 and ubiquitin ligases (e.g., UBE2L6) known to facilitate the transfer of ISG15 onto cell proteins. Notably, elevated ISG15 and elevated HERC5 and HERC6 are all associated with poorer relapse-free and overall patient survival. Breast cancer cells resistant to the CDK4/6 inhibitors Palbo or Abema, which are often used in first line treatment of patients with HR-positive breast cancer, and cells resistant to FOXM1 inhibitor show some similarities in the ISGylated protein patterns. However, there are also some differences observed in these patterns between Palbo and Abema and FOXM1 inhibitor (NB73) resistant cells. Upregulation of this STAT1-interferon-ISGylation network in ER-positive breast cancers displaying resistance to three different drugs suggests it may be centrally involved in supporting the drug-resistant state. Importantly, Palbo and Abema resistant cells and organoids can still be effectively growth inhibited by FOXM1 inhibitor NB73, and likewise, FOXM1 inhibitor resistant cells and organoids are sensitive to suppression of viability by Palbo or Abema. This suggests that sequential treatment approaches might be effective in overcoming resistance and enabling the suppression of these drug-resistant cancers.(Supported by Breast Cancer Research Foundation grant BCRF-083 and NIH R01CA220284 to BSK and BCRF grant BCRF-145 to RS) Citation Format: Benita S. Katzenellenbogen, Yvonne Ziegler, Sandeep Kumar, Blake N. Plotner, Carlos M. Saeh, Grace O. Pento, Sung Hoon Kim, Rachel Schiff, John A. Katzenellenbogen. JAK/STAT1-interferon-ISGylation networks in breast cancer resistance to inhibitors of FOXM1 and CDK4/6 [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 435.