tbuckley/cabot-search huggingface dataset:
Abstract 3666: Proteomic-based drug sensitivity prediction algorithms: generation, optimization, and assessment
Authors: Robert F. Gruener
Journal: Cancer Research (2025)

Abstract Personalized medicine uses genomic information to inform therapeutic decisions. In the past decade, much effort has been made to develop machine learning models to link drug response with large “-omics” expression patterns in pursuit of personalizing medicine. However, until recently, large-scale proteomic datasets have not been widely available and therefore have not often been incorporated into these machine learning methods. Proteomics has the advantage of directly assaying the functional molecular machinery of cells, leading to better understanding of pathway dynamics and quantifying the targets of small molecule inhibitors. Thus, we hypothesize that proteomic data in drug response modeling could offer distinct advantages and better performing drug response models. In this study, we sought to determine if drug response models built on proteomics data can outperform other transcriptomic or multi-omic based models. To this end, we developed and tested a novel framework to predict drug response using only proteomic data. We leveraged several recent large-scale cell line proteomics datasets from DepMap (CTRP) and Sanger (GDSC) to build machine learning models trained on baseline protein expression and drug sensitivity data. We used robust testing to determine optimal parameters, drug sensitivity processing, while comparing performance across multiple machine-learning methods. Our optimized framework demonstrated strong predictive power across multiple drug classes and cancer types. Moreover, our approach successfully predicted clinical outcomes in independent, publicly available datasets, illustrating its translational potential. It was worth noting that across most therapies, our models performed similarly to gene expression-based approaches in identifying responders to both cytotoxic and targeted therapies. The work to improve and optimize these models are on-going with the intent that these tools will be made available to all proteomic researchers looking to directly develop drug response hypotheses from their proteomic data. Citation Format: Robert F. Gruener. Proteomic-based drug sensitivity prediction algorithms: generation, optimization, and assessment [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 3666.
Abstract 6831: Systems biology analysis of vitamin D3 reveals new anticancer properties
Authors: Ashiana M. Sunderji, Shivangi Roy, Adin Aggarwal, Kenneth W. Yip
Journal: Cancer Research (2025)

Abstract Introduction: Vitamin D3 (also known as cholecalciferol) is an essential nutrient and hormone that is obtained through both sunlight-mediated cutaneous synthesis and direct dietary intake. Vitamin D3 functions to inhibit tumor cell growth by arresting the cell cycle at G0/G1 phases, increasing apoptosis, and reducing nuclear β-catenin levels to prevent the formation of cancer-promoting T-cell factor complexes. This study identified the cancer cell lines most responsive to in vitro treatment with vitamin D3, as well as the compounds and genetic perturbations that are most similar to treatment with vitamin D3. Methods: For cell line response analyses, the NCI60 dataset from the US National Cancer Institute was used. Human cancer cell lines were incubated for 24 hours and treated with cholecalciferol for 48 hours at 5 different ten-fold serial dilution concentrations. Sulforhodamine B was used to measure cell survival. To identify genetic and compound perturbations similar to vitamin D3, data was obtained from the L1000 gene expression assay and CLUE. In this assay, mRNA transcript abundance was measured in 978 human landmark genes and inferred for over 11, 000 others to compare gene expression levels to those induced by vitamin D3. Results: The least sensitive cell line to vitamin D3 was the multiple myeloma cell line RPMI-8226 (IC50=56.3 µM), and the most sensitive was the colorectal cancer cell line HCT-116 (IC50 = 18.2 µM). Overall, vitamin D3 was most potent against lymphoid, renal, and melanoma cancer cell lines, and least potent against myeloma cell lines. As indicated by high median tau scores, administration of vitamin D3 induced gene expression changes similar to OTX2 and ZNF114 knockdowns; OTX2 is a transcription factor associated with neurological organ development while ZNF114 is a zinc-finger protein important for transcription regulation, and both have a biological network connection to vitamin D3. Vitamin D3 treatment has similar genetic effects to known therapeutic compounds like VX-702, nelfinavir, and calcipotriol. Conclusions: This study provides a comprehensive in vitro examination of the cancer cell lines most impacted by treatment with vitamin D3. Further research will help better inform the use of vitamin D3 in nutrition plans and guide its use in cancer prevention and treatment. Citation Format: Ashiana M. Sunderji, Shivangi Roy, Adin Aggarwal, Kenneth W. Yip. Systems biology analysis of vitamin D3 reveals new anticancer properties [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 6831.
Abstract 3121: DWP217, a novel Arginase inhibitor enhancing tumor immunity through tumor microenvironment reprogramming
Authors: Seung Jae Jeong, Wolyoung Kim, Ji-Hae Kim, Sujin Ha, Youngwoo Choi, Jiyoon Seok, Ye Gi Han, Jong Cheol Shon, Hyoungrok Bak, Eunmi Hong, Jonghyeon Son, Kyung Seok Oh, Ji-Duck Kim, Joon Seok Park
Journal: Cancer Research (2025)

Abstract Checkpoint inhibitors have transformed cancer immunotherapy, yet their efficacy is often undermined by the immunosuppressive tumor microenvironment (TME). Arginase, a key enzyme secreted by myeloid-derived suppressor cells and tumor-associated macrophages, contributes to this suppression by depleting arginine, a critical nutrient for T-cell and NK cell activation. Elevated Arginase activity is associated with immune resistance and diminished response to immunotherapy, highlighting it as a promising target to reprogram the TME and restore antitumor immunity. Preclinical evaluation of DWP217 revealed its potent ability to inhibit Arginase activity, enabling T-cell proliferation and reversing immune cell dysfunction. Structural analyses uncovered a unique binding mechanism, supporting the rational design of an optimized compound series with enhanced potency. In combination with anti-PD-1 antibodies, DWP217 achieved significantly better tumor control and survival outcomes in syngeneic cancer models compared to anti-PD-1 monotherapy. Notably, DWP217 outperformed competing Arginase inhibitors that had advanced to clinical trials, underscoring its superior efficacy and potential as an immune-oncology therapeutic candidate. Immune profiling revealed that DWP217 enhances tumor-infiltrating lymphocyte activation and reprograms the TME toward a pro-inflammatory state. These findings indicate that DWP217 not only counteracts Arginase-mediated immune suppression but also reshapes the TME to support durable antitumor immunity. With its strong preclinical efficacy and favorable immune modulation profile, DWP217 is a promising therapeutic candidate for overcoming immuno-oncology resistance. Its further development holds the potential to significantly improve therapeutic outcomes in refractory solid tumors. Citation Format: Seung Jae Jeong, Wolyoung Kim, Ji-Hae Kim, Sujin Ha, Youngwoo Choi, Jiyoon Seok, Ye Gi Han, Jong Cheol Shon, Hyoungrok Bak, Eunmi Hong, Jonghyeon Son, Kyung Seok Oh, Ji-Duck Kim, Joon Seok Park. DWP217, a novel Arginase inhibitor enhancing tumor immunity through tumor microenvironment reprogramming [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 3121.
Abstract 5521: Integrative analysis of acquired drug resistance to KRAS(G12D) inhibitors
Authors: Ines Pulido Endrino, Laura Gunder, Malek Massad, Julian Carretero, Takeshi Shimamura
Journal: Cancer Research (2025)

Abstract KRAS is the most frequently mutated oncogene in cancer and, until recently, targeted therapies against mutant KRAS haven’t been successful. However, new breakthroughs in pharmacological design have led to the FDA-approval of two KRAS G12C inhibitors and one inhibitor specific to target the KRAS glycine to aspartic acid in codon 12 (G12D) mutation has shown strong responses in vitro and has entered phase I in clinical trials, MRTX1133. KRAS(G12D) is the most common KRAS mutation, being found in 37% of pancreatic ductal adenocarcinomas (PDACs), as well as in 12.5% of colorectal cancer and 4.9% of lung adenocarcinoma (LUAD) patients. MRTX1133, a selective non-covalent inhibitor of the KRAS(G12D) mutation, has demonstrated promising preclinical efficacy and has entered phase 1 clinical trials; however, the acquired drug resistance is expected to emerge. We have generated an acquired resistant model to KRASG12D inhibitors by drug escalation of MRTX1133. Our results show that although the IC50 for parental AsPC-1 cells is 0.2nM, drug resistant AsPC-1M-R cells can grow normally at 10 µM. Expression of KRAS, NRAS but more significantly HRAS are increased in the drug-resistant phenotype, likely to bypass inhibition of KRAS(G12D). Oncogenic KRAS(G12D) signaling isn’t essential in AsPC-1M-R cells as determined by a persistent RAS-GTP activity after MRTX1133 treatment due to the emergence of a secondary mutation in KRAS. In fact, tumor proliferation and survival in the resistant phenotype is sustained by increased receptor tyrosine kinase (RTK) phosphorylation. Evaluation of RTK activity demonstrated that resistant tumor cells activated several RTK such as the ErbB and Eph families and MET, predominantly. Dual inhibition with SHP2, SOS or ErbB in combination with MRTX113 didn’t exhibit a synergistic effect. Novel therapeutic approaches such as RAS(ON) inhibitors like RMC-6236 or specific KRAS(G12D) PROTAC degraders can significantly inhibit cell proliferation in vitro not only in MRTX1133 acquired resistance but also in adagrasib resistance models. To determine the underlying mechanisms of acquired drug resistance to MRTX1133, RNAseq analysis was performed. Complex transcriptomic reorganization shows the upregulation of CD24 -a potential cancer stem cell related gene- and the epithelial to mesenchymal signature highlight the difficulty to target drug resistant cells. These findings emphasize the necessity to design combinatorial treatments to prevent and delay the acquisition of drug resistance in KRAS-driven cancers. Citation Format: Ines Pulido Endrino, Laura Gunder, Malek Massad, Julian Carretero, Takeshi Shimamura. Integrative analysis of acquired drug resistance to KRAS(G12D) inhibitors [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 5521.
Abstract 6823: Dynamics of KMT2D modulation of the PI3K-Akt pathway and the impact on metastasis in prostate cancer
Authors: Abbas Jawadwala, Surrendra Gulla, Remi Adelaiye-Ogala
Journal: Cancer Research (2025)

Abstract Despite advances in the treatment of prostate cancers, such as androgen receptor (AR) inhibitors and androgen depreivation therapies (ADT), relapse often occurs, which leads to drug resistant forms of prostate cancer. Understanding the mechanism behind resistance thus becomes important for developing effective treatments. Epigenetic regulators such as KMT2D, a histone 3 lysine 4 methlytransferase, have been implicated in modulating signature pathways associated with cell progression and survival. The PI3K-AKT-mTOR pathway has been studied by many in the field on its role in cancer progression and treatment resistance. However, not as much is known about it being epigenetically regulated. Our preliminary studies demonstrate an association of KMT2D expression/activity and the PI3K-AKT signaling pathway. Interestingly, enrichment analysis in KMT2D knockout treatment-resistant prostate cancer models and their respective controls, demonstrated enriched signatures associated with tumor metastasis and cell adhesion downregulated. While these studies are still preliminary, our results provides an insight to the role of KMT2D in a context dependent mannar, where in an already acquired treatment-resistant state, KMT2D may be promoting a tumor-suppressor-like program and help improve the existing treatment regimen. Ongoing studies will validate our preliminary findings and provide a better understanding of the correlation between KMT2D and these genes along with the PI3K-Akt-mTOR signaling pathway.. Citation Format: Abbas Jawadwala, Surrendra Gulla, Remi Adelaiye-Ogala. Dynamics of KMT2D modulation of the PI3K-Akt pathway and the impact on metastasis in 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 6823.
Abstract 5499: A comparison of spheroid formation using AcroCyte‘s 3-dimensional R3CE spheroid culture platform <i>versus</i> traditional 3D culture methods
Authors: Zichun Wang, Di Zhan, Qikuan Chen, Chao-Jie Yang, Jia-Yang Chen, Ying C Chang, Yinfei Yin
Journal: Cancer Research (2025)

Abstract Three-dimensional (3D) spheroid culture systems have gained attention due to their evident advantages in mimicking the in vivo tumor microenvironment, making them highly valuable for drug testing and cancer research, as the behavior of 3D-cultured cells is more reflective of in vivo cellular responses. However, traditional spheroid methods, including ultra-low attachment plates, Matrigel, and soft agar, have limitations, especially for certain cell lines that fail to form stable spheroids. Here, we introduce a novel 3D spheroid culture method using the AcroCyte R3CE plate, and compare it to the generation of spheroids using traditional 3D culture methods. R3CE is a revolutionary scaffold-free single-cell proliferation 3D cell culture platform that can quickly and reliably culture spheroids from a variety of samples including cell lines, circulating tumor cells and biopsies. This technology is highly efficient and can help researchers gain insight into cancer research, clinical treatments, and drug discovery. 20 cell lines with historically poor spheroid formation in standard methods were subjected to the novel AcroCyte R3CE plate culture system which enabled robust and consistent spheroid formation. RNA sequencing (RNA-seq) was performed to compare gene expression profiles between 3D spheroids cultured using the R3CE plate and traditional 2D monolayer cultures. Our analysis identified distinct biomarker expression profiles associated with spheroid cultures, including cancer stem cell-related proteins and key signaling pathways relevant to cell differentiation and tumor biology. The unique biomarker expression profiles of the cancer spheroid cells were validated at the protein level by way of immunofluorescence or western blot. This innovative approach utilizing the R3CE 3D cell culture platform, not only improves spheroid formation across difficult-to-culture cell lines, but also preserves critical biomarker expression profiles and pathways linked to tumorigenesis. These findings highlight the potential of the R3CE 3D culture system to establish a reliable and versatile spheroid panel for high-throughput drug screening, providing a more physiologically relevant model to evaluate drug efficacy and mechanistic insights. Citation Format: Zichun Wang, Di Zhan, Qikuan Chen, Chao-Jie Yang, Jia-Yang Chen, Ying C Chang, Yinfei Yin. A comparison of spheroid formation using AcroCyte‘s 3-dimensional R3CE spheroid culture platform versus traditional 3D culture methods [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 5499.
Abstract 7007: Identifying novel non-allosteric PIM1 degraders to overcome treatment resistance in triple negative breast cancer
Authors: Sanjay V. Malhotra, Benedikt W. Grau, Dhanir Tailor, Abel Bermudez, Fernando Jose Garcia Marques, Juliana Geppert, Sharon Pitteri
Journal: Cancer Research (2025)

Abstract Background: Breast cancer (BC) is the most common cancer among women, with triple-negative breast cancers (TNBC) being the most aggressive type. Resistance to current mainline therapies is one of the major reasons for increased mortality. PIM1 oncoprotein has been implicated in causing treatment resistance, and therefore, associated with the development and progression of this disease. Several attempts have been made to develop inhibitors of PIM1. However, these inhibitors are not specific and can lead to toxicity by inhibiting the activity of other kinases. Therefore, there is an unmet need to develop a non-orthosteric inhibitor or non-allosteric degrader, which would be more specific and could help in effective treatment of TNBC. Methods: We synthesized a novel class of PIM1 degraders and confirmed their non-allostatic mode of action experimentally in vitro, in silico and in vivo. Results: Our lab has designed indole-based compounds and identified initial hits on their PIM1 inhibition properties in a luciferase reporter assay. Further optimization improved the PIM1 inhibition up to 80-90%. However, the in silico analysis suggested that the compounds do not interact with the orthosteric center of the protein. This was confirmed by a kinase assay, which revealed that the new compounds do not interfere with PIM1 kinase activity. On the other hand, Bio-layer interferometry (BLI) studies confirmed the physical interaction of our compounds with the PIM1 protein, concluding non-allosteric interaction. The top three compounds were tested further in vitro. Treatment with our top candidate(s) inhibits cell proliferation and arrests the cells in G1 phase. This was followed by apoptotic cell death. These findings suggest that our newly designed compounds can indeed interact with PIM1 and hinder its protein function while leaving its kinase activity unaffected. Furthermore, in vivo study in the EMT6 orthotopic mice model of the top three compounds suggest that treatment inhibits tumor progression and lung metastasis. Conclusion: Preliminary results merit the optimization of ‘Hit-to-Lead’ and development of a suitable candidate to treat TNBC, where PIM1 is the cause of treatment resistance. Successful completion of the proposed work will enable a new combination therapy to reverse chemoresistance. Citation Format: Sanjay V. Malhotra, Benedikt W. Grau, Dhanir Tailor, Abel Bermudez, Fernando Jose Garcia Marques, Juliana Geppert, Sharon Pitteri. Identifying novel non-allosteric PIM1 degraders to overcome treatment resistance in triple negative 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 7007.
Abstract 3656: Using a hierarchical transformer for mechanistic response prediction to chemotherapy
Authors: Zach Wallace, Ingoo Lee, Sungjoon Park, Akshat Singhal, Xiaoyu Zhao, Trey Ideker
Journal: Cancer Research (2025)

Abstract How a cancer patient responds to chemotherapy drugs can be notoriously difficult to predict, as the mechanisms triggering these responses are not completely understood. The superiority of attention-based models in machine learning, such as Transformers, offers the potential to improve drug response prediction while gaining deeper mechanistic understanding. Here, we develop and evaluate a hierarchically structured transformer model for chemotherapy response. The transformer architecture leverages prior knowledge of biological structure and function, enabling it to learn how genetic alterations perturb the states of genes and higher order multigenic systems in governing a drug response. This model accurately predicts response to 12 chemotherapies with high attention to systems known to function in replication stress, such as cell cycle regulation and genome maintenance via p53, as well as unexpected systems related to the actin cytoskeleton and regulation of cellular structure. This work demonstrates how transformer-based modeling can improve chemotherapy response prediction and reveal deeper understanding of molecular systems that underlie therapeutic outcomes. Citation Format: Zach Wallace, Ingoo Lee, Sungjoon Park, Akshat Singhal, Xiaoyu Zhao, Trey Ideker. Using a hierarchical transformer for mechanistic response prediction to chemotherapy [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 3656.