tbuckley/cabot-search huggingface dataset:
Abstract 4011: Locoregional GPC3 chimeric antigen receptor (CAR)-T cell therapy is associated with improved tumor control in hepatocellular carcinoma by enhancing CAR-T cell trafficking and functionality
Authors: Jue Wang, Kinching Tsang, Jiale Qiu, Bo Feng
Journal: Cancer Research (2024)

Abstract Despite the rapid development of anti-cancer immunotherapy, the prognosis of hepatocellular carcinoma (HCC) patients is far from satisfactory. Glypican-3 (GPC3) CAR-T cell therapy has shown varied patient response. One of the potential reasons of low response rates may be due to the limited CAR-T cell infiltration. Therefore, locoregional GPC3 CAR-T therapy has been a promising option, with a hope of enhancing CAR-T cell tumor penetration. In this study, the therapeutic efficacy and underlying mechanisms of locoregional GPC3 CAR-T cell delivery were explored using HCC mouse xenografts. Orthotopic NOD-scid IL2Rgnull (NSG) HCC models were established by tumor fragment implantation into the liver. CAR-T cell injections were performed via the tail vein and portal vein to simulate systemic and locoregional administrations, respectively. Compared to the systemic treatment, locoregional therapy could better control the tumor growth, and was associated with improved liver function. In addition, the locoregional therapy group demonstrated a higher percentage of tumor-infiltrating CAR-T cells which showed an increased expression level of the cytotoxicity marker GZMB and a reduced level of the exhaustion marker LAG3. Moreover, significantly higher IFN-gamma level was found in the blood of the locoregional therapy group, indicating a better CAR-T cell functionality. In conclusion, we have demonstrated that locoregional administration of CAR-T cells is associated with increased CAR-T cell infiltration and better therapeutic efficacy. Additionally, CAR-T cells being injected locoregionally are correlated with enhanced functionality and reduced exhaustion phenotype. These findings highlight the potential of locoregional GPC3 CAR-T therapy as a promising treatment strategy for HCC patients. Citation Format: Jue Wang, Kinching Tsang, Jiale Qiu, Bo Feng. Locoregional GPC3 chimeric antigen receptor (CAR)-T cell therapy is associated with improved tumor control in hepatocellular carcinoma by enhancing CAR-T cell trafficking and functionality [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 4011.
Abstract 3536: Paracell: A high throughput, deep learning-based pipeline for single-cell phenotypic profiling
Authors: David L. Nguyen, Jesse T. Chao
Journal: Cancer Research (2024)

Abstract Variants of uncertain significance constitute the vast majority of missense variants, hampering the utility of genetic testing, despite its remarkable impacts on clinical diagnosis and decision-making. Although the sequencing and interpretation of genetic variants have been drastically improved in recent years, only about 2% of novel missense variants are currently clinically actionable. Therefore, a robust and scalable pipeline is desperately needed to provide functional evidence critical for variant interpretation. In this work, we demonstrate Paracell, a deep learning-based phenotypic profiling pipeline that leverages subcellular segmentation, high-dimensional single-cell phenotyping, and machine learning to classify the functional impact of variants. Paracell captures heterogeneity in cellular phenotypes and protein colocalization between variants and their signaling partners, as well as subcellular markers, and enables analysis at a single-cell resolution. Using a classification model trained on single-cell features extracted by Paracell, we were able to accurately classify cells from loss-of-function (LoF) variants based on their impact. After aggregating cellular profiles on a variant level, our pipeline was able to distinguish LoF variants from functional ones with high sensitivity and specificity. Our work demonstrates that Paracell is a robust and scalable method that can sensitively detect differences in single-cell phenotypic profiles. The systematic application of this pipeline will provide valuable functional evidence for variant interpretation, enhancing their clinical utility and accelerating personalized cancer care. Citation Format: David L. Nguyen, Jesse T. Chao. Paracell: A high throughput, deep learning-based pipeline for single-cell phenotypic profiling [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 3536.
Abstract 3515: SynAI: An AI-driven cancer drug synergism prediction platform
Authors: Kuan Yan, Runjun Jia, Sheng Guo
Journal: Cancer Research (2024)

Abstract Introduction: The SynAI solution is an adaptive AI-driven in silico drug synergism screening solution aiming to discover the potential therapeutic value of compounds at an early development stage. Given one of both compound inputs in SMILE sequences, SynAI can predict the potential Bliss score of compounds in any given cell line without the need for compound synthesis or structural analysis.The evaluation version of SynAI is accessible at https://synai.crownbio.com Methods: The AI core of SynAI was constructed using the MLP (multi-layer perceptron) network under the PyTorch machine learning framework. The AI core of SynAI was trained against NCI-Almanac and DrugCombDB datasets. In total, these datasets consist of over 12 million in vitro synergism tests across 150 cancer cell lines of different origins. On average, each cell line is tested against over 6000 two-compound combinations of FDA-approved cancer drugs. One MLP network was trained for each cell line. Essentially, these networks predict the Bliss score for any combination of SMILE-based feature sets known as molecular fingerprints. The networks were trained against the NCI Almanac set and verified against NCI and DrugCombDB using n-fold cross-validation to avoid model overfitting. During the training, a hyperparameter tuning (HT) study was performed for SynAI and other popular algorithms; allowing an objective comparison of SynAI performances. Results: Compared to existing synergism prediction platforms, SynAI yields similar performance in all categories (cf. Table 1) but provides more flexibility for data input using SMILE sequences directly. In addition, the AI core of SynAI can be constantly updated with new inputs from different cell lines and drug combinations. Table 1. Pearson cross correlation (PCC) between measured and predicted Bliss scores of NCI test set Conclusions: Its adaptive and dynamic nature allows SynAI to learn from new data feeds from future studies and has significant potential in reducing the time and cost of synergism screening. PCC Score Cell Lines Algorithm MCF7 OVCAR-8 SK-MEL-5 SynAI 0.68 ± 0.02 0.56 ± 0.07 0.86 ± 0.02 RF 0.64 ± 0.02 0.55 ± 0.03 0.89 ± 0.02 GBX 0.66 ± 0.02 0.48 ± 0.05 0.88 ± 0.02 RNN 0.54 ± 0.12 0.43 ± 0.06 0.83 ± 0.08 Citation Format: Kuan Yan, Runjun Jia, Sheng Guo. SynAI: An AI-driven cancer drug synergism prediction platform [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 3515.
Abstract 4004: Fine-tuning affinity/avidity of anti-CAIX CAR T cells to mitigate on-target off-tumor toxicity in clear cell renal cell carcinoma
Authors: Stephen Hsien-Chi Yuan, Yufei Wang, Rabia Abbas, Peterson Mathenge, Charles Chien, Christian D. Coherd, Branson Bajoua, Matthew R. Chang, Nithyassree Murugan, Gabriella M. Kastrunes, Guilin Wang, Song-My Hoang, Wayne A. Marasco
Journal: Cancer Research (2024)

Abstract On-target off-tumor toxicity (OTOT) is one of the major hurdles preventing tumor-associated antigen (TAA) targeted therapy from effectively treating patients with solid tumors due to the shared presence of the same TAA on normal tissues. We have previously demonstrated high expression of carbonic anhydrase IX (CAIX) in ccRCC patient samples and low-density expression on healthy bile duct epithelium. In 2006, a clinical trial was stopped due to OTOT bile duct toxicity observed in patients infused with anti-CAIX CAR T cell therapy. To address the issue of OTOT in the bile duct, we performed affinity/avidity fine-tuning of the anti-CAIX CAR G36 to specifically target ccRCC tumor cells with high CAIX expression while sparing cholangiocytes with low CAIX expression. We generated a complementarity-determining region (CDR) single variant mutagenesis library of G36 and displayed the library on yeast for screening. Using flow cytometry, we were able to identify six populations based on antigen-binding affinity: high, med-high, med, med-low, low, and loss of binding. These libraries were sequenced via PacBio, a next generation sequencing (NGS) platform that excels in long-read sequencing, providing a powerful tool to detect single mutations in the scFv. The results were analyzed to identify enriched mutations compared to the wild-type G36, and inspected using in silico modeling and docking. Furthermore, enriched mutants from med-low and low populations were tested in CAR-T format for their cytotoxic capacity on tumor cells and bile duct cholangiocytes, as well as their avidity. We demonstrate that mutations in CDR2 and CDR3 of the heavy chain successfully mitigate OTOT toxicity on cholangiocytes with physiological levels of CAIX expression while maintaining tumor-killing capacity, shedding light on CDR mutagenesis as a useful tool to mitigate OTOT toxicity. Citation Format: Stephen Hsien-Chi Yuan, Yufei Wang, Rabia Abbas, Peterson Mathenge, Charles Chien, Christian D. Coherd, Branson Bajoua, Matthew R. Chang, Nithyassree Murugan, Gabriella M. Kastrunes, Guilin Wang, Song-My Hoang, Wayne A. Marasco. Fine-tuning affinity/avidity of anti-CAIX CAR T cells to mitigate on-target off-tumor toxicity in clear cell renal cell carcinoma [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 4004.
Abstract 3521: Robust inference of PTEN deletion in prostate cancer from routine histopathology whole slide images using attention-based deep learning
Authors: Federico Scarfò, Mohamed Omar, Luigi Marchionni
Journal: Cancer Research (2024)

Abstract The diagnostic workup of prostate cancer (PCa) requires a thorough manual histopathological inspection of prostate tissue specimens stained with hematoxylin and eosin (H&amp;E). While immunohistochemistry and advanced molecular tests like FISH could uncover key genetic alterations, they are not cost-effective and often require special training, necessitating the development of more effective tools that can accurately infer the status of such alterations directly from the tissue morphology depicted in routine H&amp;E-stained glass slides. PTEN deletion, which is present in 15-20% of PCa, is significantly associated with tumor aggressiveness and negative prognostic impact. Deep learning (DL) models can be trained to predict the presence of PTEN deletion on routine whole slide images (WSIs) and select patients that could benefit from further treatment. In this study, we trained and tested the performance of a weakly supervised, multiple-instance learning network on a cohort of 449 WSIs radical prostatectomy specimens stained with hematoxylin &amp; eosin. Our model demonstrated robust performance in predicting PTEN loss based on tumor morphology alone. Through the model, we also generated attention heatmaps of the most informative tiles of each slide, allowing us to quantify the different cellular components, thus inferring the morphological features associated with PTEN loss. This study shows that DL is a potential tool that can assist the pathologist in accurately inferring the molecular status of key genetic alterations using the tissue morphology depicted in histopathology slides. Moreover, the morphological information that can be obtained by attention-based models can be leveraged to close the gap between the pathologist’s morphological analysis and the interpretability of artificial intelligence models. Citation Format: Federico Scarfò, Mohamed Omar, Luigi Marchionni. Robust inference of PTEN deletion in prostate cancer from routine histopathology whole slide images using attention-based deep learning [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 3521.
Abstract 4006: IL12-secreting CAR-T cells eliminate the requirement for lymphodepletion and promote epitope spreading via local antigen presenting cells
Authors: Aditya Mohan, Steven Shen, Kelly Hotchkiss, Sarah Quackenbush, John Sampson, Peter Fecci, Anoop Patel
Journal: Cancer Research (2024)

Abstract Introduction: EGFRvIII is a commonly studied tumor-specific antigen in glioblastoma (GBM) and poses an enticing target for immunotherapy. Its varied expression, however, complicates its effectiveness as a Chimeric Antigen Receptor (CAR) T cell target. Given the increasing prominence of Interleukin-12 (IL12) in treating solid tumors, its synergy with EGFRvIII specific CARs in treating preclinical models of GBM is explored. Methods: To simulate tumor heterogeneity, mice were implanted with equal ratios of CT2A and CT2A EGFRvIII+ cells. We developed EGFRvIII-specific third-generation CAR T cells, both with and without IL12 using a MSGV retrovirus backbone and transduced them into murine T cells. Their antitumor effectiveness was gauged by evaluating survival rates, and their capability to enhance and modify the tumor environment was determined using single-cell sequencing. Results: Standalone EGFRvIII CARs were unsuccessful in curing mice with heterogeneous tumors. However, 60% of mice treated with EGFRvIII CARs combined with IL12 were long term survivors. IL12 secreting CARs exhibited prolonged persistence in vivo, and there was no need for prior lymphodepletion before ALT introduction. Our studies reveal that EGFRvIII CARs secreting IL12 can eliminate EGFRvIII negative tumor cells by drawing on the inherent CD8 T cell compartment. Moreover, IL12 prominently impacted microglia among all Antigen Presenting Cells in the tumor environment, amplifying antigen presentation processes and broadening epitope exposure. Conclusion: By leveraging IL12, EGFRvIII CARs can counteract antigen heterogeneity in tumors by recruiting endogenous CD8 T cells and polarizing microglia. These IL12-secreting CARs outlast their traditional counterparts without requiring lymphodepletion. Harnessing CAR-T cells that secrete IL12 represents a novel strategy for overcoming tumor heterogeneity and treating GBM in a clinical context. Citation Format: Aditya Mohan, Steven Shen, Kelly Hotchkiss, Sarah Quackenbush, John Sampson, Peter Fecci, Anoop Patel. IL12-secreting CAR-T cells eliminate the requirement for lymphodepletion and promote epitope spreading via local antigen presenting 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 4006.
Abstract 7583: Discovery of a potent small molecule MALT1 protease inhibitor for the treatment of cancer
Authors: Yuzhen Zhou, Bang Fu, Jie Chen, Weidong Cai, Xiao Sun, Yinlong Li, Wei Ren, Qichao Shen, Guolong Du, Xiaojun Zhou, Zhengyao Zou, Haibo Chen, Xiaoyun Liu, Cheng Yang, Xiangyong Liu, Jing Guo, Hao Wu, Lieming Ding, Jiabing Wang, Hong Lan
Journal: Cancer Research (2024)

Abstract The paracaspase mucosa-associated lymphoid tissue lymphoma translocation protein 1 (MALT1), as the core component of CBM complex (CARD9/10/11/14-BCL10-MALT1), plays an essential role in activating the NF-κB pathway and regulating the cell proliferation, differentiation and immunity. Inhibiting of MALT1 is considered a promising therapeutic approach for the treatment of several non-Hodgkin B-cell lymphomas, chronic lymphocytic leukemia (CLL), solid tumors and autoimmune diseases. Herein, we report the discovery of a novel potent MALT1 allosteric inhibitor, BPI-530616, which strongly inhibited MALT1 protease activity with subnanomolar IC50, and low off-target activity on other proteases. BPI-530616 can inhibit the proliferation of B-cell diffuse large B-cell lymphoma (ABC-DLBCL) cell line, OCI-ly3, bearing CD79b and CARD11 mutations. The cell line is intrinsically resistant to covalent and non-covalent Bruton's Tyrosine Kinase (BTK) inhibitors. Meanwhile, BPI-530616 suppressed the cellular cytokine secretion (e.g.IL-10, IL-2) or MALT1 direct substrate cleavage (e.g. CYLD). In vivo, BPI-530616 dose-dependently suppressed tumor growth and inhibited the cleavage of CYLD in OCI-ly3 xenograft mouse model. To address the role of MALT1 inhibitor in the contest of immune-oncology, a CT26 syngeneic mouse model was set up. Oral administration of BPI-530616 exhibited a good antitumor effect comparable to that of the anti-PD1 antibody, with no observable adverse effects. Additionally, BPI-530616 displayed desirable drug-like properties, including low clearance and good oral bioavailability across multiple pre-clinical species. Taken together, our research has led to the discovery of a novel, potent, selective, and orally bioavailable small molecule MALT1 inhibitor, BPI-530616. It demonstrated anti-tumor efficacy in the DLBCL animal model and showed promising effects in an immune-oncology animal model. Citation Format: Yuzhen Zhou, Bang Fu, Jie Chen, Weidong Cai, Xiao Sun, Yinlong Li, Wei Ren, Qichao Shen, Guolong Du, Xiaojun Zhou, Zhengyao Zou, Haibo Chen, Xiaoyun Liu, Cheng Yang, Xiangyong Liu, Jing Guo, Hao Wu, Lieming Ding, Jiabing Wang, Hong Lan. Discovery of a potent small molecule MALT1 protease inhibitor for the treatment of 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 7583.
Abstract 488: Modulation of ENPP1 activity and 2'3'-cGAMP degradation in ovarian cancer cell lines via loadable pre-formed lipid nanoparticles
Authors: David Taylor, Jiajia Ji, Phillip Rzeczycki, Margaret L. Collins, Lauren Clements, Aileen R. Ariosa
Journal: Cancer Research (2024)

Abstract Ovarian cancer is a complex heterogeneous disease with various subtypes and diverse molecular mechanisms of pathogenesis. Among different forms, epithelial ovarian cancer is the most common, representing up to 90% of total reported cases. Due to the lack of early diagnostic tools, the prognosis is mainly poor, as most cases are typically identified in advanced stages. Thus, a more thorough understanding of the inherent complexities of the disease, in terms of its biochemical etiology, will allow for identification of specific molecular and genetic profiles that could lead to more effective treatment plans. Recent studies have shown that ENPP1 may play a role in cancer cell proliferation, migration, and invasion in ovarian and other types of cancer. ENPP1 is a glycosylated type II transmembrane protein acting as a pyrophosphatase and phosphodiesterase with broad specificity. ENPP1 substrates include mononucleotides and cyclic dinucleotides such as the second messenger, 2'3'-cGAMP, which binds to and activates STING. 2'3'-cGAMP is exported extracellularly by cancerous cells into the tumor microenvironment where uptake into neighboring cells can activate their STING-dependent type 1 interferon pathway and promote antitumoral immune responses. ENPP1 can hydrolyze extracellular 2'3'-cGAMP however, allowing cancer cells to evade such an immune response. In this study, we assessed the activity of ENPP1 in CaOV-3, SK-OV-3, and PA-1 ovarian cancer cell lines using a fluorometric cell-based assay. The effects of ENPP1 inhibition via a chemical inhibitor on extracellular 2'3'-cGAMP levels were characterized and compared with siRNA-mediated knockdown of ENPP1 via loadable pre-formed lipid nanoparticles, which enable small-scale encapsulation and transfection of nucleic acid cargo. In addition, we explored whether uptake of exogenous 2'3'-cGAMP into THP-1 and RAW immune cell lines can be enhanced through delivery via preformed loadable lipid nanoparticles. Corresponding immune cell activation was also assessed using immunoblotting and RT-PCR. Our results demonstrate how modulation of ENPP1 activity and 2'3'-cGAMP levels in ovarian cancer cell lines using unconventional, pre-formed loadable lipid nanoparticle transfection reagent can aid in elucidating mechanisms of immune evasion in cancer cells. Citation Format: David Taylor, Jiajia Ji, Phillip Rzeczycki, Margaret L. Collins, Lauren Clements, Aileen R. Ariosa. Modulation of ENPP1 activity and 2'3'-cGAMP degradation in ovarian cancer cell lines via loadable pre-formed lipid nanoparticles [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 488.
Abstract 2789: NCAPG promotes triple-negative breast cancer stemness by a positive feedback loop with HIF-1α
Authors: Huimin Zhang, Peiling Xie, Rui An
Journal: Cancer Research (2024)

Abstract Objective: Triple-negative breast cancer (TNBC) is life-threatening because of limited therapies and lack of effective therapeutic targets. NCAPG, an oncogenic marker, might be served as a new target for TNBC treatment. Here, we aimed to elucidate the role of NCAPG played in TNBC and the underlying mechanism. Design: GEO data was used to investigate the potential targets for TNBC. Patient samples and TCGA data were used to demonstrate the clinical significance. Cell migration, self-renewal ability, chemoresistance and expression of pluripotency factors were tested to detect the stemness of TNBC cells. Immunoprecipitation, ubiquitination assay and chromatin immunoprecipitation assay were utilized to investigate the mutual regulation mechanism of NCAPG and HIF-1α. Results: NCAPG was significantly overexpressed in TNBC compared with other subtypes of breast cancer and was positively correlated with poor overall survival. Elevated NCAPG expression could enhance cancer stem-like cell properties of TNBC cells. Mechanically, NCAPG positively regulated HIF-1α protein stability by interacting with HIF-1α and competitively abrogating the E3 ligase FBXW7-mediated ubiquitination and degradation towards HIF-1α. NCAPG, as a direct target gene of HIF-1α, could be in turn transcriptionally upregulated by HIF-1α. Conclusion: NCAPG promotes TNBC stemness by a HIF-1α/NCAPG positive feedback loop. NCAPG is a promising target for TNBC treatment. Citation Format: Huimin Zhang, Peiling Xie, Rui An. NCAPG promotes triple-negative breast cancer stemness by a positive feedback loop with HIF-1α [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 2789.