tbuckley/cabot-search huggingface dataset:
Abstract 4235: A combination of CAR-NK and CAR-T cells results in rapid and persistent anti-tumor efficacy while reducing CAR-T cell mediated cytokine release and T-cell proliferation
Authors: Guangnan Li, Xiumin Wu, Ivan H. Chan, James B. Trager
Journal: Cancer Research (2020)

Abstract CAR-NK cells show rapid and potent anti-tumor cytotoxic activity even at very low effector-to-target ratios, however, they do not typically expand upon encounter with antigen and lack long term persistence commonly associated with CAR-T cells. Conversely, CAR-T cells generally exhibit persistent killing activity, even though they are activated somewhat more slowly. In addition, the explosive expansion of CAR-T cells is frequently associated with a variety of toxicities (e.g. CRS, CRES, etc.). To address these shortcomings, Nkarta has developed a novel platform to combine both CAR-NK and CAR-T cells as a novel cancer therapeutic. To evaluate the overall outcomes of combining CAR-NK and CAR-T cells as an anti-tumor therapy, we have developed two novel in vitro assays: (a) IncuCyte-based matrixed cytotoxicity assay, which allows direct assessment of tumor killing kinetically with different E:T and NK:T ratios; (b) IncuCyte-based tumor re-challenge assay, which provides a convenient and quick assessment of anti-tumor persistence. For proof-of-concept studies, a CD19 directed CAR (CAR19) was retrovirally engineered into NK and T cells. Our newly developed assays revealed that the combination of CAR-NK and CAR-T cells clearly outperformed CAR19-NK or CAR19-T cells alone in anti-tumor efficacy and persistence. Additionally, the combination also showed an improved cytokine profile. To further investigate the cellular mechanism(s) underlying the beneficial effects of combining CAR-NK and CAR-T cells, we performed FACS-based phenotyping and a Violet Cell Trace based proliferation assay. When challenged with tumor cells, the presence of CAR19-NK cells reduced the proliferation of CAR19-T cells. Surprisingly, the presence of CAR19-T cells could trigger the proliferation of CAR19-NK cells. Finally, we evaluated the NK plus T platform in vivo with a Nalm6 xenograft model. Treatment with CAR19-NK cells combined with a low dose of CAR19-T cells (5e5 cells/animal) delayed tumor progression. Combined treatment with a medium dose of CAR19-T cells (2.5e6 cells/animal) largely prevented tumor relapse, and consequently enhanced the overall survival of the animals. In summary, our in vitro and in vivo studies strongly demonstrate that the NK plus T platform can harness the advantages of both CAR-NK and CAR-T cells, allowing for both rapid and persistent killing while potentially minimizing the toxicities associated with CAR-T cells. Citation Format: Guangnan Li, Xiumin Wu, Ivan H. Chan, James B. Trager. A combination of CAR-NK and CAR-T cells results in rapid and persistent anti-tumor efficacy while reducing CAR-T cell mediated cytokine release and T-cell proliferation [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4235.
Abstract 6275: Targeting RRM2 by triapine sensitizes glioblastoma to radiotherapy
Authors: Sergio Corrales-Guerrero, Erica H. Bell, Arnab Chakravarti, Changxian Shen, Terence M. Williams
Journal: Cancer Research (2020)

Abstract Glioblastoma multiforme (GBM) remains characterized by poor clinical outcomes and limited treatment options. Currently, the standard of care for patients with this disease is surgery with radiation therapy and concurrent and adjuvant temozolomide. However, most patients succumb to the disease within the first 15 months after diagnosis. Therefore, effective treatment regimens are desperately needed. Exacerbated cell proliferation as well as repair of DNA damage induced by chemoradiation requires a constant supply of dNTPs. Ribonucleotide reductase (RNR) is the key enzyme for the synthesis of dNTPs and is a complex formed by two subunits: RRM1 and RRM2 3-aminopyridine-2-carboxaldehyde thiosemicarbazone (3AP - commercially Triapine) is a molecule that potently inhibits RRM2 by affecting its active site, and has been shown to cross the brain-blood barrier (Jiang et al. 2006. PMID: 16834759). We herein report that triapine induces DNA replication stress and sensitizes GBM cells to radiation. Analyses of available datasets including TCGA show that RRM2 is overexpressed in GBM and lower grade glioma (LGG), and a higher expression of RRM2 associates with worse overall survival and disease-free survival of GBM and LGG patients. Nevertheless, RRM2 levels do not change between initial and recurrent tumors (Wang et al. 2017. PMID: 28697342). Using human GBM cell lines LN229, LN18 and U251, we have performed cytotoxicity assays and clonogenic radiation assays. The IC50 of triapine in these cell lines are between 1-2 μM. We find that triapine significantly radiosensitizes LN229, LN18 and U251 cells. Consistent with the role of RRM2 in dNTPs biosynthesis, triapine treatment of GBM cells induces robust phosphorylation of CHK1 at S345, which is accompanied by elevated gamma H2AX. Importantly, we reveal that triapine promotes ionizing radiation induced phosphorylation of CHK2 at T68. Acknowledging the increasing concerns about using established cell lines for GBM studies, we are currently moving to validate our results in primary GBM cell lines. Our results demonstrate that RRM2 is overexpressed in glioblastoma and targeting RRM2 with triapine enhances radiation-induced DNA damage leading to radiosensitization of glioblastoma cells. Our findings suggest that triapine is a promising agent for the sensitization of glioblastoma to radiotherapy. Citation Format: Sergio Corrales-Guerrero, Erica H. Bell, Arnab Chakravarti, Changxian Shen, Terence M. Williams. Targeting RRM2 by triapine sensitizes glioblastoma to radiotherapy [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 6275.
Abstract 2814: Establishment and optimization of a drug-resistant PDX-based platform using <i>in vivo</i> and <i>in vitro</i> approaches
Authors: Xiaoying Zhuang, Nan Xie, Lei Jin, Wengang Zeng, Yuhui Zheng, Chunling Zhang, Liping Cai, Hanmei Sun, Jie Xu, Wenjie Gao, Qunsheng Ji
Journal: Cancer Research (2020)

Abstract Induced resistance after anticancer agent treatment is the main reason for cancer relapse and short median survival of patients. Here we employed in vivo and in vitro approaches to establish and optimize a drug-resistant platform based on patient-derived xenografts (PDXs). PDXs derived from lung cancer patients who acquired drug resistance reproduced the insensitivity to standard target therapies in mice. Alternatively, resistance was induced in established PDX by continuously exposing with dosage increasing, which demonstrated the induced response declining after the treatment of one second-line therapy drug (Irinotecan). These drug resistant models were additionally confirmed by the in vitro 3D cell based assay, which mimicked the precise histologic structure and cellular composition of the corresponding patient samples. These results from in vivo and in vitro studies displayed good correlation, suggesting that this platform of PDXs and 3D cell based assay can be applied to preclinical development, mechanism research and new drug screen to overcome treatment resistance and have the potential for application to personalized medicine programs. Citation Format: Xiaoying Zhuang, Nan Xie, Lei Jin, Wengang Zeng, Yuhui Zheng, Chunling Zhang, Liping Cai, Hanmei Sun, Jie Xu, Wenjie Gao, Qunsheng Ji. Establishment and optimization of a drug-resistant PDX-based platform using in vivo and in vitro approaches [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2814.
Abstract 869: Leveraging a novel analysis pipeline for outcomes predictions from routine MRIs
Authors: Vachan Vadmal, Kristin Waite, Jill S. Barnholtz-Sloan
Journal: Cancer Research (2020)

Abstract There is a desperate need for approaches that allow us to use routinely gathered clinical and imaging data to make outcomes predictions for patients. The acquisition of MRI images forms a standard part of clinical care for cancer patients, especially for malignant brain tumor patients. As these digital MRI scans are performed regularly, the associated digital MRI data also grows and can form the basis for longitudinal assessment of disease and prediction of clinical outcomes. However, standard modalities are coupled with non-standard modalities in most cases (some of which is institution specific), making it difficult to organize and standardize these images for analysis. In addition, for a rare cancer such as malignant brain tumors, multi-institutional collaborations are necessary in order to have appropriate power for analyses, thereby complicating the issues around organization and standardization of images for analysis. In addition, there are likely to be discrepancies among data formats intra-institutionally. To address these shortcomings and to expedite the research process, we developed a general digital MRI analysis pipeline that is able to organize messy data, automatically preprocess, segment, extract features, and produce results that are ready for statistical analysis and discovery. Such a pipeline with modular segments for major stages in the process is beneficial to investigators who are analyzing MRI data and hope to save time from the tedium of organization and data management. With a focus on efficiency, extensibility, and reproducibility, the tools that form this pipeline also aim to increase the accessibility of complex imaging analysis to a wider audience by leveraging artificial intelligence. While pipelines exist in the literature, most are not focused on clinical MRI images of brain tumors and quickly become deprecated as software dependencies change, resulting in outdated and potentially buggy software. Our pipeline implements the latest Python version using object-oriented principles, employing PEP 8 style, and is optimized to run on modern hardware thus ensuring extensibility. The pipeline itself runs intuitively via the command line interface (CLI) that requires minimal input parameters to perform its subtasks but will have the option of accepting other parameters. We showcase features of this new MRI analysis pipeline, using malignant brain tumors as an exemplar, given their disproportionate contribution to cancer morbidity and mortality. Citation Format: Vachan Vadmal, Kristin Waite, Jill S. Barnholtz-Sloan. Leveraging a novel analysis pipeline for outcomes predictions from routine MRIs [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 869.
Abstract 5475: Evaluation of feature selection methods used for cluster analysis in identification of novel cancer subtypes
Authors: Linda Vidman, David Källberg, Patrik Rydén
Journal: Cancer Research (2020)

Abstract Background: RNA-seq data from tumor samples can be used to identify novel cancer subtypes using cluster analysis. The number of features is often large compared to the number of samples and different clusters can appear in different subsets of the feature space. Feature selection techniques are therefore commonly used to reduce the dimension and remove redundant and irrelevant features before performing cluster analysis. An abundance of feature selection methods have been proposed in the literature, but it is unclear how the ability to identify novel subtypes of cancer using cluster analysis is affected by choice of feature selection method. Method: We evaluated 13 feature selection methods on four publicly available cancer data sets from The Cancer Genome Atlas. RNA-seq data and associated clinical data were retrieved from Broad institute GDAC Firehose. Overlap and characterization of the highest ranked features (i.e. genes) were studied for top 100, 1000 and 3000 genes. Performance was measured by comparing known cancer subtypes to partitions obtained using hierarchical clustering with Euclidean distance and Ward´s linkage, based on the selected features. The result was compared to both a random selection (negative control) and a supervised approach (positive control) using adjusted Rand index. Results: The relative performance of the feature selection methods varied heavily depending on number of included genes and the data set used. Based on all data, gene selection using the Dip-test statistic and the Bimodality index generated the overall highest clustering performance. The overlap of selected genes between the Bimodality index, the Dip-test and the supervised approach was relatively low. The Dip-test and Bimodality index tended to favor genes with relatively low expression values. Conclusions: The choice of feature selection method can have a huge impact on the ability to identify cancer subtypes using cluster analysis, and the relative performance is highly dependent on the data. Low overlap of selected genes between the highest ranked methods suggests that the methods identify genes that contain complementary information, and that it might be beneficial to combine two or more feature selection methods. Citation Format: Linda Vidman, David Källberg, Patrik Rydén. Evaluation of feature selection methods used for cluster analysis in identification of novel cancer subtypes [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5475.
Abstract 141: G9a regulates tumorigenicity and stemness through genome-wide DNA methylation reprogramming in non-small cell lung cancer
Authors: Rajendra P. Pangeni, Lu Yang, Keqiang Zhang, Jinhui Wang, Wendong Li, Chao Guo, Xinwei Yun, Ting Sun, Jami Wang, Dan J. Raz
Journal: Cancer Research (2020)

Abstract Eukaryotic Histone Methyltransferase 2 (EHMT2 or G9A) has been regarded as a potential target for Non-Small Cell Lung Cancer (NSCLC) therapy. To investigate the regulatory roles of G9A in tumorigenesis, and stemness, we isolated and enriched tumor-initiating cells (TIC) from surgically resected NSCLC tissues by FACS and sphere formation assays. We then knocked down G9A using shRNA and carried out genome-wide 850K methylation array and RNA sequence analyses. We identified 67 genes hypomethylated and 143 genes upregulated following G9A knockdown of which 43 genes were both hypomethylated and upregulated. We selected 6 genes (CDYL2, DPP4, SP5, FOXP1, STAMBPL1 and ROBO1) for validation. These genes are involved in epigenetic regulation in human cancers, signaling pathways, other biological processes and have roles in patients' prognosis. In addition, G9A expression was higher in TICs and targeting G9a by shRNA knockdown or by selective inhibitor UNC0638 significantly inhibited the expression of cancer stem cell markers and sphere forming capacity, in vitro proliferation and in vivo growth. Further, transient overexpression of FOXP1 in TICs resulted in downregulation of stem cell markers and sphere forming capacity and cell proliferation in vitro indicating that the genes we identified are directly regulated by G9A through aberrant DNA methylation and subsequent expression. These data suggest that G9A contributes to epigenetic regulation by maintaining DNA methylation of multiple genes genome-wide and their expression. Citation Format: Rajendra P. Pangeni, Lu Yang, Keqiang Zhang, Jinhui Wang, Wendong Li, Chao Guo, Xinwei Yun, Ting Sun, Jami Wang, Dan J. Raz. G9a regulates tumorigenicity and stemness through genome-wide DNA methylation reprogramming in non-small cell lung cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 141.
Abstract 2988: PLAC8 confers the chemoresistance of placental site trophoblastic tumor and choriocarcinoma to etoposide in an autophagy-dependent manner
Authors: Xuan Feng, Huandi Yu, Xiang Tao, Yan Du, Jing Wu, Yinhua Yu, Congjian Xu, Hongbo Zhao
Journal: Cancer Research (2020)

Abstract Chemotherapy is commonly used to treat gestational trophoblastic neoplasia (GTN), but placental site trophoblastic tumor (PSTT) and a small proportion of choriocarcinoma demonstrate chemotherapy resistance, which becomes the major obstacle for the treatment. However, the underlying mechanism remains elusive. In the present study, we found that PLAC8 expression in PSTT tissues was higher than that in placental site intermediate trophoblast cells. In addition, PLAC8 was also highly expressed in human choriocarcinoma tissues compared with normal placental villi. Over-expression of PLAC8 inhibited p53 protein stability and induced the autophagic flux in HTR-8 and JAR cells. PLAC8-induced autophagic activity could be partially recovered by p53 re-expression. Further, PLAC8 over-expression conferred chemoresistance of trophoblast cells to etoposide, which can be effectively abrogated by autophagic inhibitors 3-methyladenine (3-MA) or chloroquine (CQ). In conclusion, over-expression of PLAC8 in PSTT and choriocarcinoma tissues may endow the trophoblast cells with enhanced chemoresistance via inducing autophagy activity. Therefore, PLAC8 may serve as a potential therapeutic target for the treatment of PSTT and choriocarcinoma. Citation Format: Xuan Feng, Huandi Yu, Xiang Tao, Yan Du, Jing Wu, Yinhua Yu, Congjian Xu, Hongbo Zhao. PLAC8 confers the chemoresistance of placental site trophoblastic tumor and choriocarcinoma to etoposide in an autophagy-dependent manner [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2988.
Abstract 4121: ORIC-101 overcomes resistance to diverse chemotherapeutics across cancer types
Authors: Haiying Zhou, Shravani Barkund, Aleksandr Pankov, Ganapati Hegde, Wayne Kong, Padmini Narayanan, Jessica D. Sun, Omar Kabbarah, Lori S. Friedman, Anneleen Daemen
Journal: Cancer Research (2020)

Abstract Preclinical studies have shown that GR activation leads to decreased response to antimetabolites, taxanes, and platinum agents, while GR inhibition enhances therapeutic efficacy. The novel, selective GR antagonist ORIC-101 is under clinical evaluation in combination with anticancer therapies. In this study we set out to assess which cancer types and chemotherapeutics are responsive to combination with ORIC-101. Specifically, we employed caspase assays, in vitro and in vivo tumor growth inhibition studies, and transcriptional profiling in a panel of preclinical models spanning triple-negative breast, ovarian, non-small cell lung cancers, pancreatic ductal adenocarcinoma, hepatocellular carcinoma, sarcoma, and renal cell carcinoma. We found that ORIC-101 reverses GR-mediated antiapoptosis effects towards diverse chemotherapeutics, including paclitaxel, gemcitabine, and cisplatin, across the seven cancer types. Furthermore, ORIC-101 completely overcomes GR-driven chemoprotection and tumor growth in colony formation assays in vitro and in xenograft studies in vivo. At the molecular level, transcriptional profiling and pathway enrichment analysis showed that ORIC-101 fully reverses GR-activated pathways that are directly involved in drug resistance, such as epithelial-to-mesenchymal transition and antiapoptosis, supporting a pan-cancer role of GR as a mediator of therapy resistance. Altogether, ORIC-101, a selective and potent GR antagonist, overcomes resistance to common chemotherapeutics across multiple cancer models. Clinical evaluation of ORIC-101 in combination with nab-paclitaxel is currently ongoing in advanced solid tumors. Citation Format: Haiying Zhou, Shravani Barkund, Aleksandr Pankov, Ganapati Hegde, Wayne Kong, Padmini Narayanan, Jessica D. Sun, Omar Kabbarah, Lori S. Friedman, Anneleen Daemen. ORIC-101 overcomes resistance to diverse chemotherapeutics across cancer types [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4121.
Psychosocial Moderators of the Impact of Diabetes Stigma: Results From the Second Diabetes MILES – Australia (MILES-2) Study
Authors: Elizabeth Holmes-Truscott, Adriana D. Ventura, Sharmala Thuraisingam, Frans Pouwer, Jane Speight
Journal: Diabetes Care (2020)

To examine the association of diabetes stigma with psychological, behavioral, and HbA1c outcomes and to investigate moderation effects of self-esteem, self-efficacy, and/or social support.The national Second Diabetes MILES - Australia (MILES-2) survey included adults with type 1 diabetes (n = 959, 41% of whom were male, with mean ± SD age 44 ± 15 years), insulin-treated type 2 diabetes (n = 487, 60% male, age 61 ± 9 years), and non-insulin-treated type 2 diabetes (n = 642, 55% male, age 61 ± 10 years). (Un)adjusted linear regression analyses tested the association between diabetes stigma (Diabetes Stigma Assessment Scale [DSAS]) and psychological outcomes (depressive symptoms [eight-item version of the Patient Health Questionnaire (PHQ-8)], anxiety symptoms [Generalized Anxiety Disorder 7-item (GAD-7) questionnaire], and diabetes-specific distress [20-item Problem Areas In Diabetes (PAID) scale]), behavioral outcomes (healthy diet and physical activity [Summary of Diabetes Self-Care Activities (SDSCA)]), and self-reported HbA1c. Interaction effects tested whether associations varied by self-esteem (Rosenberg Self-Esteem Scale [RSES]), self-efficacy (Confidence in Diabetes Self-Care [CIDS] scale), or diabetes-specific social support (Diabetes Support Scale [DSS]).Significant positive associations were observed between DSAS and PHQ-8, GAD-7, and PAID across diabetes type/treatment groups (all P < 0.001), whereby each SD increase in DSAS scores was associated with approximately one-half SD deterioration in emotional well-being. Associations between DSAS and SDSCA and HbA1c were nonmeaningful. Self-esteem moderated psychological outcomes among participants with type 1 and non-insulin-treated type 2 diabetes and diabetes distress among those with insulin-treated type 2 diabetes. Interaction effects were partially observed for social support but not for self-efficacy.This study provides evidence of the association between diabetes stigma and depressive/anxiety symptoms and diabetes distress and for the moderating effects of self-esteem and social support among adults with type 1 and type 2 diabetes. Further research is needed to examine associations with objectively measured behavioral and clinical outcomes.