tbuckley/cabot-search huggingface dataset:
Abstract 3236: Discovery of hydrazide-based HDAC8 selective PROTACs
Authors: Yufeng Xiao, Yi Liu, Nikee Awasthee, Chengcheng Meng, Michael He, Seth Hale, Rashmi Karki, Zongtao Lin, Robert Kridel, Daiqing Liao, Guangrong Zheng
Journal: Cancer Research (2024)

Abstract HDAC8 plays crucial roles in biological processes and is a highly desirable target for therapeutic interventions. However, due to the conserved catalytic domain among HDACs, developing specific inhibitors for these isozymes has proven challenging. HDAC8 also has deacetylase-independent activity which cannot be blocked by an inhibitor. Previously we reported the discoveries of a potent HDAC3 degrader XZ9002 and an HDAC3/8 dual degrader YX968. In this study, we carried out further optimizations based on the warhead of YX968 through rational design, which led to the discovery of YX862 and YL246, novel hydrazide-based HDAC8 selective PROTAC degraders with single-digit nanomolar DC50 and excellent selectivity. We demonstrated that the degradation of HDAC8 affects its non-histone substrates; however, it does not trigger profound histone hyper-acetylation and gene expression alteration, highlighting the unique role of HDAC8. The PROTACs developed in this study are well-characterized HDAC8 degraders without triggering pan-HDAC inhibition which represent valuable tool compounds for exploring the biological and therapeutic potential of HDAC8 in cancers and beyond. Citation Format: Yufeng Xiao, Yi Liu, Nikee Awasthee, Chengcheng Meng, Michael He, Seth Hale, Rashmi Karki, Zongtao Lin, Robert Kridel, Daiqing Liao, Guangrong Zheng. Discovery of hydrazide-based HDAC8 selective PROTACs [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3236.
Abstract 6004: HOXC8 epigenetically controls caspse-1 expression and pyroptosis in lung cancer cells
Authors: Lei Sun, Ravi Padia, Ozlem Calbay, Cheng Chi, Mahmuda Akter, Lingtao Jin, Shuang Huang
Journal: Cancer Research (2024)

Abstract Homeobox C8 (HOXC8) is a transcription factor preferentially overexpressed in a large percentage of lung adenocarcinoma (LUAD). To investigate the function of HOXC8 in LUAD, we showed that knockdown of HOXC8 led to massive LUAD cell death in a mechanism of pyroptosis because both YVAD, a caspase-1 (CASP1) inhibitor, and disulfiram, which prevents gasdemin D (GSDMD) pore formation, blocked cell death caused by HOXC8 depletion. Intriguingly, ASC and NLRP3, components of canonic inflammasome, were not involved in pyroptosis occurring in HOXC8-depleted cells. Instead, we found that silencing HOXC8 led to a marked increase in CASP1 abundance. As forced expression of CASP1 is sufficient to induce CASP1 activation and pyroptosis, we reason that HOXC8 deters pyroptosis by suppressing the level of CASP1. Moreover, we revealed that knockdown of HOXC8 augmented CASP1 transcription involving in HDAC1/2. In fact, HOXC8 and HDAC1 were in the same immunocomplex and the presence of HOXC8 is required for the recruitment of HDAC1 to CASP1 promoter. Since HOXC8 also binds CASP1 promoter, we conclude that HOXC8 negatively regulates CASP1 expression by drafting HDAC1/2 to CASP1. This study suggests that HOXC8 participates LUAD development by controlling CASP1 expression and pyroptosis. Citation Format: Lei Sun, Ravi Padia, Ozlem Calbay, Cheng Chi, Mahmuda Akter, Lingtao Jin, Shuang Huang. HOXC8 epigenetically controls caspse-1 expression and pyroptosis in lung cancer cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6004.
Abstract 1845: 11,000-plex aptamer based proteomics of colorectal cancer stools for the discovery of novel disease biomarkers
Authors: Chandra Mohan, Kamala Vanarsa, Jessica Castillo, Robert Bresalier, Nicholas Chia
Journal: Cancer Research (2024)

Abstract Given the morbidity and mortality associated with colorectal cancer, novel biomarkers are clearly warranted, especially for early detection, particularly for advanced adenomas. An earlier 1317-plex aptamer-based proteomic screen of stool proteins revealed 92 proteins to be significantly elevated in CRC stool, with the most discriminatory proteins being MMP9, haptoglobin, myeloperoxidase, fibrinogen, and adiponectin (PMID: 34117903). Results from a recent 2000-plex proteomic screen of CRC stools are detailed below, while a 11,000-plex aptamer based proteomic screen is in progress. Comprehensive proteomic screening revealed 116 proteins to be differentially expressed in CRC stool compared to control stool, with 45 being elevated 2-fold or higher. 37 of these proteins were ELISA validated in 3 independent cohorts. Stool MMP-8, MMP-9, Hemoglobin, PGRP-S, Haptoglobin, Myeloperoxidase and Fibrinogen emerged as being most discriminatory for distinguishing CRC from healthy controls (AUC: 0.91-0.95), while Stool Fibrinogen, MMP-9, Hemoglobin, MMP-8, and PGRP-S best distinguished advanced adenoma from healthy control (HC) stool, with stool Fibrinogen topping the list with an ROC AUC value of 0.86, as detailed in Table 1. Functional pathway analysis revealed a significant over-representation of pathways related to anti-oxidant activity, integrin/receptor binding, cytokines, blood coagulation, and lipoprotein biosynthesis in patients with CRC compared to HC. Nuclear Factor IC (NFIC) and IKZF2 were identified as key regulators of the molecular cascades over-represented in CRC. Stool Fibrinogen, MMP-8, MMP-9, PGRP-S, Haptoglobin, and Myeloperoxidase emerge as promising biomarkers for distinguishing CRC/advanced adenomas/healthy stools, outperforming Hemoglobin. Thus, comprehensive proteomics and independent ELISA validation have uncovered novel stool biomarkers for identifying CRC and advanced adenomas, that warrant further head to head comparison against current diagnostic tests. Citation Format: Chandra Mohan, Kamala Vanarsa, Jessica Castillo, Robert Bresalier, Nicholas Chia. 11,000-plex aptamer based proteomics of colorectal cancer stools for the discovery of novel disease biomarkers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1845.
Abstract 1101: A patient-derived xenograft in vitro platform identifies panobinostat as the most efficient drug to treat high-risk hepatoblastoma patients
Authors: Salih Demir, Emilie Indersie, Sophie Branchereau, Eiso Hiyama, Stefano Cairo, Roland Kappler
Journal: Cancer Research (2024)

Abstract Hepatoblastoma is the most common pediatric liver tumor, and the treatment of patients with preoperative chemotherapy and surgical resection of the tumor has led to survival rates of up to 83%. However, resistance of the primary tumor towards chemotherapy and the persistence of metastases still represents major challenges to achieve complete remission in high-risk patients, which is associated with poor prognosis. In order to identify new treatment options, we have used a newly developed in vitro drug-testing platform comprised of conventional cell lines and cultures from dissociated patient-derived xenografts of pediatric liver cancers to test standard-of-care medications used in the current PHITT trial as well as compounds targeting a wide range of different cellular pathways. We identified histone deacetylase (HDAC) inhibitors as a promising drug family to reduce tumor cell growth in a dose-dependent manner, with panobinostat being the most effective drug tested. Subsequent in vitro assays showed that panobinostat reduced short- and long-term proliferation, retarded three-dimensional spheroid growth and ultimately induced apoptosis of hepatoblastoma cells. RNA sequencing indicated that panobinostat results in downregulation of MYC target genes and upregulation of the dual specificity phosphatase 1. Of clinical relevance, the combination of panobinostat with doxorubicin revealed a strong synergistic effect, even stronger than the one of cisplatin and doxorubicin, which is currently given to high-risk hepatoblastoma patients. Moreover, increased expression of HDAC4 and HDAC11 in primary tumor tissues was significantly associated with metastatic disease. Our results strongly suggest panobinostat to be used in future therapeutic trials for high-risk hepatoblastoma patients, especially when combined with doxorubicin. Citation Format: Salih Demir, Emilie Indersie, Sophie Branchereau, Eiso Hiyama, Stefano Cairo, Roland Kappler. A patient-derived xenograft in vitro platform identifies panobinostat as the most efficient drug to treat high-risk hepatoblastoma patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1101.
Abstract 7621: Serum albumin and derived neutrophil-to-lymphocyte ratio are potential predictive biomarkers for immune checkpoint inhibitors in small cell lung cancer
Authors: Zhanpeng Kuang, Jessica Miao, Xiaoli Zhang
Journal: Cancer Research (2024)

Abstract Background: Immune checkpoint inhibitors (ICIs) have reshaped the treatment landscape of small cell lung cancer (SCLC), but only a minority of patients benefit from this therapy. Therefore, it is critical to identify potential risk factors that could predict the efficacy of ICI treatment in SCLC patients and identify patient subgroups who may benefit the most from ICI therapy. Methods: Our study included a total of 183 SCLC patients who had received at least one dose of ICI treatment. We utilized both logistic regression and Cox proportional hazard regression to evaluate whether various patient clinical factors and serum biomarkers, could serve as predictors of patient response to treatment and overall survival (OS) during ICI therapy. Results: Logistic regression showed that patients with a history of surgery (p=0.003, OR 9.06, 95% CI: (2.17, 37.9)) and no metastasis (p=0.008, OR 7.82, 95% CI: (1.73, 35.4)) exhibited a higher odds of response to ICI treatment. Cox regression analyses demonstrated that pretreatment blood albumin (p=0.003, HR 1.72, 95% CI: (1.21, 2.45)) and derived neutrophil to lymphocyte ratio (dNLR) (p=0.003, HR 1.71, 95% CI: (1.20-2.44)) were independent predictors for OS in SCLC patients. By establishing a pre-treatment prognostic scoring system based on baseline albumin and dNLR, we found that patients with high albumin and low dNLR exhibited a significantly better prognosis than those with low albumin and high dNLR in both the full (P&amp;lt;.0001, HR 0.33, 95% CI: 0.20-0.55) and the metastatic cohort (P&amp;lt;.0001, HR 0.28, 95% CI: 0.15-0.51). The better prognostic group also had younger age, higher BMI and lower systemic inflammatory biomarker values than the unfavorable group (P&amp;lt;.0001). Conclusion: Our data reveals the significant role of metastasis status and treatment history in predicting the initial response of SCLC patients to ICI treatment. However, baseline serum albumin and dNLR provide a more precise prognostic prediction for patient OS. The scoring system based on albumin and dNLR enhances the ability to stratify patient prognosis and holds the potential to guide clinical decision-making for SCLC patients undergoing ICI therapy. Citation Format: Zhanpeng Kuang, Jessica Miao, Xiaoli Zhang. Serum albumin and derived neutrophil-to-lymphocyte ratio are potential predictive biomarkers for immune checkpoint inhibitors in small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7621.
Abstract 6904: Model-derived progression-free survival (mPFS): A better metric for patient-derived xenograft studies
Authors: Andrew Chen, Madison Stoddard, Lin Yuan, Debra Van Egeren, Arijit Chakravarty, Dean Bottino
Journal: Cancer Research (2024)

Abstract Patient-derived xenografts (PDX) are a powerful assay system for translational prediction of therapeutic potential for experimental therapeutics. The primary readout from PDX models is tumor shrinkage, measured by the ratio of treated/control tumor volume. This readout corresponds loosely to the Objective Response Rate (ORR) metric used in clinical trials, in that it is a readout of drug effect on the sensitive subclones within a tumor. In prior work, we have shown that there is a paradoxical relationship between short-term tumor response and progression-free survival (PFS). While ORR is the primary measure utilized in the Phase II to III transition in clinical development, approval hinges on survival metrics, and the disconnect between ORR and PFS creates a potential risk of late-stage failures for experimental anticancer therapeutics. Thus, it is of interest to understand whether there are alternative approaches to analyzing PDX data that can enable the assessment of therapeutic potential in terms of a projected PFS. In this simulation study, we will examine the accuracy of progression-free survival (PFS) estimates obtained directly from observation during a PDX study and compare their accuracy with the accuracy of PFS estimates derived using a mathematical model-based approach that relies on a kinetic model of tumor subclone growth (model-based PFS, or mPFS) fitted directly to PDX tumor growth and rebound kinetics under treatment. We generated our test dataset using a mathematical model of tumor kinetic growth to simulate xenograft data using fitted parameters derived from literature, adding in experimental error consistent with prior experimental measurement-derived variability. We used the simulated raw data to calculate an observed PFS as well as mPFS derived from fitting the tumor clonal kinetic model to the raw data in a blinded fashion. Our results show that the empirical PFS from PDX models is subject to overestimation, as a function of the observation time interval. On the other hand, mPFS is significantly less biased and more accurate, but is subject to some logistical constraints on sampling. Our work demonstrates the practical translational utility of a novel analysis method (mPFS) in deriving estimates of progression-free survival from PDX model data. Citation Format: Andrew Chen, Madison Stoddard, Lin Yuan, Debra Van Egeren, Arijit Chakravarty, Dean Bottino. Model-derived progression-free survival (mPFS): A better metric for patient-derived xenograft studies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6904.
Abstract 3248: Metabolic rewiring shifts engineered TCR T cell bioenergetics to enhance cytotoxicity
Authors: Rashmi Pillai, Xiaoyu Zhang, Yama Abassi
Journal: Cancer Research (2024)

Abstract Background: Adoptive T cell-based transfer has shown tremendous success in hematological cancers. However, an important obstacle to using cell and gene therapy for solid tumors is the aggressive tumor microenvironment (TME). To significantly improve prognosis of subjects undergoing immunotherapy, it is essential to incorporate unique methods to drive T cell energy production and metabolism towards empowering T cells to dismantle the suppressive TME. This can promote anti-tumor effects and persistence of the transfused engineered T cells. In the present study we present a simple metabolic preconditioning process that improves T cell performance and bioenergetics. Methods: Using the Agilent xCELLigence RTCA eSight, and Seahorse XF Analyzer we assessed the killing efficiency, and bioenergetics of engineered T-cells after pretreating with Arginine. Briefly, engineered TCR T-cells against MART-1 were generated by transducing CD3+ T-cells (Hemacare, Seattle, WA) with retrovirus SAMEN-DMF5 with a CD34 marker gene, against MART-1. The TCR T cells were pre-conditioned in 6mM Arginine for 7 days, followed by a killing assay using MART-1 expressing melanoma cell line as target cells (624.38) at the E:T ratio of 5:1. Target melanoma cells, 624.38 cells, were engineered to express a red-fluorescent nuclear protein. The comparison was made with transduced T-cells grown in RPMI (no added amino acid supplementation, and non-transduced T cells. The cytotoxicity assay was assessed using real-time impedance and live cell imaging data collected on xCELLigence RTCA eSight. Concurrently, the metabolic profiling of the engineered T-cells was examined by the XF96 Analyzer. Results: Supplementing the growth medium with 6 mM Arginine significantly increased the potency of MART-1 engineered T cells (up to 6-fold) and bioenergetic studies revealed increased spare respiratory capacity, basal respiration, and ATP production via mitochondrial respiration. Conclusions: Arginine pre-conditioning improved TCR T cell potency through metabolic rewiring favoring mitochondrial respiration. For Research Use Only. Not for use in diagnostic procedures RA45236.3483333333 Citation Format: Rashmi Pillai, Xiaoyu Zhang, Yama Abassi. Metabolic rewiring shifts engineered TCR T cell bioenergetics to enhance cytotoxicity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3248.
Abstract 323: Optimization of a liquid biopsy assay to accommodate low cfDNA samples and increase throughput
Authors: Michael Salmans, Dasom Kim, Andrew Carson, Mengchi Wang, Byung In Lee, Bryan Leatham
Journal: Cancer Research (2024)

Abstract Molecular testing that interrogates cell free DNA (cfDNA) from plasma has significant potential value across the cancer care continuum, including early cancer detection, driver mutation identification, and disease recurrence monitoring. To achieve this potential, liquid biopsy assays must be optimized to address multiple challenges. For one, cfDNA quantity in the blood is highly variable, with different amounts present depending on malignancy and stage of progression. This requires optimization to detect low concentrations of circulating tumor DNA (ctDNA) and to accommodate variable tumor fractions. In addition, minimizing assay costs will improve test accessibility and adoption. To address these issues, Genece Health is optimizing their lung cancer liquid biopsy assay to accommodate minimal cfDNA input into library preparation. Furthermore, Genece is testing algorithms that tolerate reduced read depths from low-pass whole genome sequencing (LP-WGS) while maintaining high performance. The Genece lung cancer liquid biopsy assay profiles fragment end-motif and size (FEMS) and fragment coverage signals using LP-WGS (Illumina) and proprietary machine learning algorithms. This study first tested the frequency of end motifs in pooled ctDNA after modifying library preparation (IDT) to reduce reagent volumes from 1X down to 0.5X, 0.25X, and 0.1X of manufacturer specification. A range of cfDNA input from 0.25 ng to 6 ng was tested with each library preparation volume. In addition, LP-WGS read coverage from 5X to 1X was evaluated to assess impact on end motif frequency and assay sensitivity. Performance characterization was further evaluated with a cohort of 50 clinical lung cancer and 100 healthy donor plasma samples tested at 1X and 0.25X library reagent volume. We observed an expected increase in library complexity at higher cfDNA input and library reagent volume. Assay performance was minimally impacted by variable cfDNA input and library reagent volume. However, reducing sequencing read depth is tolerated down to 1.25X depth before increasing the variability of end motif frequencies. These observations are corroborated in the 150 clinical sample cohort. This data shows that by altering standard library preparation conditions and reducing unique read depth, liquid biopsy assays can accommodate a wider range of cfDNA, while concurrently decreasing overall costs. Citation Format: Michael Salmans, Dasom Kim, Andrew Carson, Mengchi Wang, Byung In Lee, Bryan Leatham. Optimization of a liquid biopsy assay to accommodate low cfDNA samples and increase throughput [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 323.
Abstract 6911: Expanding reported molecular characteristics for the NCI Patient-Derived Models Repository
Authors: Cindy R. Timme, Yvonne A. Evrard, Biswajit Das, Ting-Chia Chang, Alice Chen, Li Chen, Michelle A. Crespo-Eugeni, Shahanawaz Jiwani, Chris A. Karlovich, Rini Pauly, Peter I-Fan Wu, Dianne L. Newton, P. Mickey Williams, Melinda G. Hollingshead, James H. Doroshow
Journal: Cancer Research (2024)

Abstract The National Cancer Institute’s Patient-Derived Models Repository (NCI PDMR; https://pdmr.cancer.gov) has developed a national repository of Patient-Derived Models (PDMs) comprised of patient-derived xenografts (PDXs), in vitro patient-derived tumor cell cultures (PDCs) and cancer associated fibroblasts (CAFs) as well as patient-derived organoids (PDOrg). These PDMs are clinically annotated with molecular information available in an easily accessible database for the extramural community. To ensure the data and models remains pertinent to current translational efforts, NCI actively reviews and adds new molecular features to the public database for researchers to use. While these data could be obtained through analysis of the available NextGen sequencing files in the PDMR database, many laboratories do not have the bioinformatics support to run these assessments for models that are of research interest. Therefore, new pipelines for an array of additional model and molecular characteristics present in PDX, PDOrg, and PDC models have been validated and are reported in the public database in a searchable format. Current model characteristics include addition of OncoTree Codes as a second histologic classifier, use of the PDXNet Consortium’s inferred ancestry caller to better represent Native/Latin American populations, human leukocyte antigen (HLA) typing, molecular classification of tumors (e.g. CMS subtyping of colorectal adenocarcinoma, PAM50 signature based subtyping of breast carcinoma), microsatellite instability (MSI) assessment, and identification of clinically relevant fusions. SOPs for the pipelines used are available on the public website to allow for independent validation and use by other laboratories. Funded by NCI Contract No. HHSN261200800001E Citation Format: Cindy R. Timme, Yvonne A. Evrard, Biswajit Das, Ting-Chia Chang, Alice Chen, Li Chen, Michelle A. Crespo-Eugeni, Shahanawaz Jiwani, Chris A. Karlovich, Rini Pauly, Peter I-Fan Wu, Dianne L. Newton, P. Mickey Williams, Melinda G. Hollingshead, James H. Doroshow. Expanding reported molecular characteristics for the NCI Patient-Derived Models Repository [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6911.