tbuckley/cabot-search huggingface dataset:
Abstract 4466: Machine-learning-driven optimization of kinase inhibitors to overcome CNS efflux and target breast cancer brain metastases
Authors: Eneye D. Ajayi, Mostafa M. Aref, Rokaia Abdullah, Md Emran Hossain, Hamed I. Ali
Journal: Cancer Research (2025)

Breast cancer (BC) is the most prevalent form of malignancy and the leading cause of cancer mortality in women. The fatality of BC is highly attributed to BC brain metastases (BCBM) which represent 30%, with a 1-year survival rate of 20%. About 15-20% of BC demonstrates significant overexpression of HER2, hence the development of anti-HER2 targeted therapies such as tucatinib which have prolonged survival rates and improved patient quality of life. Despite the improvements in HER2 targeted therapy to rapidly target BCBM, tucatinib and other quinazoline HER2 inhibitors (dacomitinib and gefitinib) possess poor CNS penetration due to P-gp and BCRP efflux. In vitro, BBB permeability assays such as the BBB-PAMPA are cost-intensive prompting the need for computational methods that can rapidly predict the BBB permeability potential of small molecules in the early phase of drug discovery. Herein, we used quantitative and qualitative machine learning (ML) algorithms trained with experimental data to direct structural optimization of in-house KIs to improve BBB penetration. We employed qualitative and quantitative ML models to identify the most promising compounds from our in-house library of 120 KIs previously designed for dual HER2/VEGFR targeting. The core of our approach lies in the structural simplification of starting compounds to drastically reduce molecular weight and topological surface area and the appropriate substitution of solubilizing residues to modulate pKa. Furthermore, we developed a benchmark of optimal physiochemical properties of molecules intended as CNS therapeutics using an approved CNS drug dataset. Optimized analogs possessing physicochemical properties within the benchmark range and a favorable ML prediction of BBB permeability were synthesized and tested on a kinase panel. BBB-PAMPA was also used to evaluate BBB penetration of both starting KIs and optimized analogs. Optimized analogs demonstrated HER2 kinase inhibitory activity alongside a significant increase in BBB permeability compared to the starting compounds. Our results suggest that structural optimization to modulate the physicochemical properties of small molecules is key to identifying potential drug candidates for targeting BCBM. In vivo studies using animal models will be conducted to validate these findings. Citation Format: Eneye D. Ajayi, Mostafa M. Aref, Rokaia Abdullah, Md Emran Hossain, Hamed I. Ali. Machine-learning-driven optimization of kinase inhibitors to overcome CNS efflux and target breast cancer brain metastases [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 4466.
Abstract 2343: CancerSpot: a multi-cancer early detection test using targeted methylation sequencing
Authors: Urvashi Bahadur, Divya Vishwanath, Prakash Hiremath, Nihesh Rathod, Swaraj Basu, Sampuran Chakraborty, Aastha Tripathi, Preetha R T, Aditi Chatterjee, Arunima Ghosh, Sameer Phalke, Subuhi Yete, Ankita Khan, Sweta Sanguri, Mohammed Rahman, Sewanti Limaye, Charles Cantor, Vamsi Veeramachaneni, Ramesh Hariharan
Journal: Cancer Research (2025)

Abstract Background: Liquid biopsy-based cancer detection is a noninvasive method to identify cell-free DNA (cfDNA) fragment based signatures in the bloodstream characterized by distinct methylation patterns. Tumor-derived fragments (ctDNA) form a tiny fraction of all cfDNA fragments in the bloodstream. ctDNA originating from some specific genomic regions can have altered methylation patterns. Reliable and cost-effective detection of altered methylation pattern in these regions requires a broad targeted sequencing approach. Methods: We developed CancerSpot, a multi-cancer early detection (MCED) test based on cfDNA methylation signatures in a cohort of 688 cancer patients and 326 healthy controls representing 10 cancer types. A custom genomics workflow prioritizes high-quality reads by rejecting poorly aligned or imperfectly converted data while rescuing reliable reads to calculate methylation scores across genomic regions at the read level accounting for detection of a weak signal from tumor derived DNA. Machine learning (ML) models were developed using methylation signatures from ∼7000 genomic markers. A gradient-boosted trees approach with repeated cross-validation incorporated data perturbations to account for variability in lab protocols and sequencing platforms ensuring robust prediction accuracy and error tolerance. Results: CancerSpot achieved 79% sensitivity and 97% specificity for detecting Stage I-III tumors across 10 cancer types. It also demonstrated a 77% accuracy in identifying the tumor tissue of origin within the top two predictions. The robust workflow enhances detection of tumor-derived cfDNA signals even in samples with low conversion efficiency while mitigating background noise from normal cfDNA. The regions used by the test show strong differential methylation in tumor-normal data from a diverse population in TCGA indicating its wide applicability. Conclusions: CancerSpot provides a cost-effective and accurate MCED solution tailored to diverse cohorts. Citation Format: Urvashi Bahadur, Divya Vishwanath, Prakash Hiremath, Nihesh Rathod, Swaraj Basu, Sampuran Chakraborty, Aastha Tripathi, Preetha R T, Aditi Chatterjee, Arunima Ghosh, Sameer Phalke, Subuhi Yete, Ankita Khan, Sweta Sanguri, Mohammed Rahman, Sewanti Limaye, Charles Cantor, Vamsi Veeramachaneni, Ramesh Hariharan. CancerSpot: a multi-cancer early detection test using targeted methylation sequencing [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 2343.
Abstract 7018: Antibody-degrader conjugates unlock the therapeutic potential of heterobifunctional degraders through antibody-like pharmacokinetics and excellent in vivo efficacy
Authors: Jan G. Felber, Anil P. Jagtap, Philipp Ochtrop, Saskia Schmitt, Isabelle Mai, Sarah Herterich, Paul Machui, Dietmar König, simon vogt, Dominik Schumacher, Jonas Helma-Smets, Annette Vogl, Marc-André Kasper
Journal: Cancer Research (2025)

Abstract Heterobifunctional small molecules recruiting the proteasomal machinery enable the targeted protein degradation (TPD) of selected proteins and considerably broaden the druggable space for therapeutic use. Many such molecules have seen fantastic success in preclinical and clinical developments, e.g., for targeted degradation of specific oncoproteins that were previously inaccessible for cancer therapy. Even though early hits are quickly generated by adapting the modular concept of bifunctional degraders, most of such molecules are against the central rules of a “drug-like” molecule: they are usually larger in size (800-1500 Da) and often lack sufficient solubility. These early bifunctional degraders hits require exhaustive structure optimization in each case to optimize pharmacokinetics (PK) profiles and bioavailability. Here, we report Tubulis’ antibody-degrader conjugates that exploit bifunctional degraders as high-potency bioactive payloads to be released specifically inside cells that are targeted by the antibody. Our linker technology ensures high degrader-to-antibody ratios (DARs) and excellent linker stability in blood plasma. Moreover, we liberate the degrader after receptor-mediated uptake of the ADC and show high efficiencies in target protein degradation. Most importantly, our conjugates exhibit antibody-like PK properties that ensure long-lasting plasma circulation of high DAR constructs over weeks, even when bifunctional degraders are employed that have not been optimized for PK properties. Taken together, these factors allow impressive in vivo efficacy of the conjugates after single dose application in preclinical animal models. Citation Format: Jan G. Felber, Anil P. Jagtap, Philipp Ochtrop, Saskia Schmitt, Isabelle Mai, Sarah Herterich, Paul Machui, Dietmar König, Dominik simon vogt, Schumacher, Jonas Helma-Smets, Annette Vogl, Marc-André Kasper. Antibody-degrader conjugates unlock the therapeutic potential of heterobifunctional degraders through antibody-like pharmacokinetics and excellent in vivo efficacy [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 7018.
Abstract 7011: Humanized CRBN knockin mice enable in vivo assessment the efficacy and toxicity of CRBN-targeted protein degraders
Authors: Yi Li, Xiaolei Qiu, Liping Feng, Dongxiao Feng, Ruilin Sun
Journal: Cancer Research (2025)

Abstract Protein degraders have emerged as a transformative therapeutic approach in the past decade, enabling targeted degradation of proteins, including traditionally undruggable targets, by facilitating the recruitment of E3 ubiquitin ligases. Among these, molecular glues such as thalidomide and its derivatives, and PROteolysis TArgeting Chimeras (PROTACs), have gained significant attention. Cereblon (CRBN), a key component of the Cullin 4 RING E3 ubiquitin ligase (CRL4), is the most extensively studied target in protein degrader research. CRBN interacts with DDB1, Cullin 4 (CUL4A/B), and RBX1 to form the CRL4^CRBN complex, which mediates substrate recognition and degradation. Thalidomide derivatives bind to CRBN, modulating substrate specificity and promoting substrate degradation. However, differences at the V388 and E377 residues between human and mouse CRBN proteins (94% homology) impede the antitumor efficacy and teratogenicity of thalidomide in mice, limiting suitable preclinical models. To address this, we developed a humanized CRBN knockin mouse model by inserting the human CRBN coding region (exon 2-11) and a WPRE/polyA cassette into the mouse Crbn locus using ES cell-based gene targeting. This model expresses full-length human CRBN in targeted cells. We validated human CRBN (hCRBN) expression across multiple tissues, including spleen, liver, brain, and intestines, via RT-PCR and western blot. Lenalidomide and CC-885 treatments of hCRBN splenocytes demonstrated the degradation of substrate proteins CK1α and GSPT1. Pharmacokinetic analysis revealed no significant differences between hCRBN knockin and wild-type C57BL/6 mice. In vivo CC-885 treatment induced on-target toxicity, as evidenced by rapid lethality, GSPT1 degradation, and increased pathological scores in hCRBN knockin mice. Our humanized CRBN mouse model serves as a robust preclinical platform for evaluating the efficacy and toxicity of CRBN-targeted protein degraders, offering valuable insights for drug development. Citation Format: Yi Li, Xiaolei Qiu, Liping Feng, Dongxiao Feng, Ruilin Sun. Humanized CRBN knockin mice enable in vivo assessment the efficacy and toxicity of CRBN-targeted protein degraders [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 7011.
Abstract 1927: High-sensitivity screening of a large number of samples for KRAS and PIK#CA mutations using digital PCR
Authors: James Qin
Journal: Cancer Research (2025)

Abstract Colorectal cancer (CRC) is one of the top commonly occurring cancers with 1.9 million new cases and 935,000 deaths worldwide in 2020 according to CDC. KRAS plays an important role in colorectal metastasis and progression, affects the tumor microenvironment and has been implicated in angiogenesis. KRAS mutations are the most common, presenting in approximately 25% of all tumors and is one of the most common gene mutations linked to cancers. It drives 40% of colorectal cancers, 32% of lung cancers, and 85% of pancreatic cancer cases. Phosphatidylinositol 3-kinases (PI3Ks) participate in signaling pathways essential for cell proliferation, adhesion, survival and motility; and are the initiators of carcinogenic process. PI3K mutations produce an altered p110a subunit, which allows PI3K to signal without regulation and initiates broad spectrum carcinogenic process. (Cell Cycle. 2009 May 1; 8(9): 1352-1358). Studies have shown a strong association of simultaneous mutations in PIK3CA exon 9 and KRAS exon 2 were the most common (67.2% of CRC cases) (Oncol.Rep.25(6) (2011) 1691-1697). When that happens, tumors with the bi-mutations were found to be significantly associated with aggressive pathological features compared with WT tumors, for example, increased proportions of proximal colon cancer that were prone to metastasize to distal organs at initial surgery. (Q. Luo et. al. Elsevier Translational Oncology 13 (2020) 100874). There is an increasing need for simple and robust tools to frequently screen and monitor such activating mutations with a sensitivity of 0.05-0.5%, which is suitable for testing of FFPE DNA samples. (I. Oscorbin et. al. Cellpress Heliyon 8 (2022) e11804). Here we introduce a novel digital PCR instrumentation and nanoplate technology that allows the screening of a large number of samples within 2 hours. We selected KRAS/G12S and PIK3CA/H1047R LNA mutational assays from the QIAGEN Geneglobe assay database and tested them against mutants from 2 germline cell models (Horizon Discovery) under various amount of WT gDNA backgrounds. Data shows good detection sensitivity at the 0.05-0.1% level. Citation Format: James Qin. High-sensitivity screening of a large number of samples for KRAS and PIK#CA mutations using digital PCR [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 1927.
Abstract 4328: Preclinical development of SCR-A008: A CDH17-targeted ADC for gastrointestinal cancer
Authors: Guangcun Cheng, Hui Zheng, Zhiyong Yu, Chunlei Xia, Huipeng Guo, Xiyuan Wang, Yayuan Fu, Renhong Tang
Journal: Cancer Research (2025)

Abstract Background: Cadherin is a superfamily of cell adhesion molecules that depend on Ca2+ and play an important role in maintaining tissue architecture. Abnormal expression of Cadherins is often associated with malformation of tissues, tumor formation, and metastasis. Cadherin-17 (CDH17) also known as hepatocyte-enterocyte cadherin, is a non-classical member of the calcium-dependent cadherin superfamily. Unlike classical cadherins, the CDH17 sequence is formed by seven extracellular calcium-dependent cadherin domains and a very short cytoplasmic domain. CDH17 is a calcium-dependent transmembrane glycoprotein that mediates cell-cell adhesion in intestinal epithelial cells. Studies have found that CDH17 expression is limited to the intestinal and pancreatic duct epithelial cells in human normal tissues. However, in tumor tissues, CDH17 is highly expressed in various digestive tract tumors, such as gastric cancer (73%), colorectal cancer (100%) and pancreatic cancer (31%). Some studies have also reported positive staining for CDH17 in about 6% of lung cancer patients, 11% of ovarian cancer patients, and 2% of liver cancer patients. These results suggest that CDH17 may be a potential therapeutic target in related tumors, especially digestive tract tumors. Methods &amp; Results: We developed a novel CDH17-targeting antibody-drug conjugate (ADC) called SCR-A008, which is comprised of an anti-CDH17 humanized monoclonal antibody conjugated with novel topoisomerase 1 inhibitor (CPT116) via a hydrophilic cleavable linker at DAR 8. SCR-A008 specifically recognizes human and cyno CDH17 with high affinity. In vitro cytotoxicity experiment demonstrated that SCR-A008 induced tumor cell lysis in various tumor cell type. Compared to MMAE-based CDH17-ADC, SCR-A008 exhibits significantly stronger anti-tumor activity in colorectal cancer cells. Additionally, we utilized CDX and PDX model to evaluate the in vivo efficacy of SCR-A008. The results showed that SCR-A008 inhibited tumor growth of various tumors in a dose dependent manner. SCR-A008 also have good stability and favorable developability. Pharmacokinetics and tolerability were assessed in mouse and cynomolgus monkey. The pharmacokinetics experiment in mice showed better PK characteristic than the reference ADC. Conclusion: These findings suggest that SCR-A008 is a potential Best-in-Class therapeutic drug for CDH17-positive solid tumor. Citation Format: Guangcun Cheng, Hui Zheng, Zhiyong Yu, Chunlei Xia, Huipeng Guo, Xiyuan Wang, Yayuan Fu, Renhong Tang. Preclinical development of SCR-A008: A CDH17-targeted ADC for gastrointestinal 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 4328.
Abstract 701: Understanding the genomic landscape of pediatric cancer predisposition
Authors: Martha O'Brien, Robert J. Autry, Olaf Witt, David Jones, Stefan Pfister
Journal: Cancer Research (2025)

Abstract Once thought to be rare, 10% of pediatric cancers can be attributed to mutations in known cancer predisposition genes (CPGs). However, given that many pediatric cancers occur sporadically without germline mutations in the ∼114 known CPGs, it is plausible that previously unidentified mutations in novel genes and non-coding regions contribute to pediatric cancer development. This research aims to uncover novel germline mutations, to use somatic “second hits” to prioritize candidates for detailed multi-faceted analysis of downstream effects contributing to pediatric cancer predisposition and pathogenesis. Here we present an analysis of the largest pediatric burden testing cohort to date (&amp;gt;7, 000 tumor/normal) of WGS, WES and RNAseq data to explore the genetic landscape of childhood cancers. First, we combined multiple rare-variant burden testing methods, such as TRAPD, SKAT-O, CoCoRV, RV-EXCALIBER, to identify novel germline variants associated with cancer at both within and across pediatric cancer entities. Putative CPGs were prioritized by detecting somatic second hits in tumors, leveraging multiple genomic data types (SNVs, indels, structural variants (SVs), and copy number variations (CNVs). The impact of germline mutations on the somatic landscape was explored by examining how these variants influence tumor mutational profiles, including co-occurring mutations and mutational signatures. Single-cell RNA sequencing data were interrogated when available for pediatric brain tumors and sarcomas to determine how the identified germline genes influence the cell-of-origin and its malignant transformation. We will assess whether these mutations can be observed early in development and their potential causative role in specific tumor types. The findings from our comprehensive approach will deepen our understanding of the interplay between germline and somatic mutations in cancer, enhancing risk prediction and guiding precision oncology efforts. Citation Format: Martha O'Brien, Robert J. Autry, Olaf Witt, David Jones, Stefan Pfister. Understanding the genomic landscape of pediatric cancer predisposition [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 701.
Abstract 3960: Genome-wide CRISPR screens for genes inhibiting T cell-tumor cell interactions identify complex N-glycans
Authors: Adriaan F. de Groot, Zowi R. Huinen, Juan Simon Nieto, Daniel S. Peeper
Journal: Cancer Research (2025)

The efficacy of immunotherapy fundamentally depends on effective T cell-tumor cell interactions, yet the molecular determinants orchestrating this engagement are not fully understood. Here, we systematically mapped and perturbed key regulators of the T cell-tumor cell interactome using innovative cell-cell interaction assays. We performed genome-wide CRISPR screens to identify genes critically required for physical and functional interactions between T cells and tumor cells. Using TurboID proximity labeling and T cell-tumor cell conjugates, we identified the complex N-glycan biosynthesis pathway as a crucial regulator of T cell-tumor cell interactions. Recognizing the role of N-glycans in protein trafficking and surface retention, we subsequently performed cell surface proteomics and TurboID-based interactome profiling on complex N-glycan-deficient T cells, revealing increased expression of cell adhesion and co-stimulatory molecules. T cells with perturbed N-glycans show a shift towards an effector memory phenotype with elevated granzyme and integrin expression. In vivo, both genetic and pharmacological interventions that decrease the number of complex N-glycans on the surface of T cells enhanced intra-tumoral infiltration. Our findings provide a comprehensive functional atlas of molecules modulating T cell-tumor cell interactions and position the complex N-glycan biosynthesis pathway as a potential therapeutic target to strengthen T cell-mediated cytotoxicity in cancer immunotherapy. Citation Format: Adriaan F. de Groot, Zowi R. Huinen, Juan Simon Nieto, Daniel S. Peeper. Genome-wide CRISPR screens for genes inhibiting T cell-tumor cell interactions identify complex N-glycans [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 3960.