bluuebunny/crossref_metadata_2025 huggingface dataset:
Abstract 844: RNA binding domains of nucleolin exhibit specificity in driving nucleolin-miRNA interactions: An in silico modeling and RNA-protein docking study
Authors: San Avdar , Saxena Anjana , Singh Shaneen
Published: September 2020

Nucleolin (NCL) is a stress responsive multifunctional RNA binding protein (RBP) that plays important roles in gene transcription and RNA metabolism. NCL levels and similarly many of NCL RNA targets are dysregulated in multiple human cancers. NCL- RNA interactions are driven by its four RNA binding domains (RBDs). Despite the myriad NCL functions that involve its RNA-binding properties, the mechanisms driving these interactions are poorly understood. Partial three-dimensional structural information available on NCL RBDs in the RCSB PDB database, is not sufficient to provide a comprehensive understanding of NCL- RNA interactions. To get a better insight into RNA binding specificity for its diverse targets, we have built upon the existing NCL-RBDs structures to generate multiple combinations of RBDs in tandem, using in silico modeling approaches. In this study, we analyze NCL-miRNA interactions in depth with a focus on a subset of miRNAs that are implicated in breast cancer. Using both template-based and ab initio approaches, we have generated complete and robust structural models of all 4 NCL RBDs in tandem and in combinations of two different RBDs in sequence. All models were then tested using a variety of structural quality evaluation programs. Models with top validation scores were used in RNA-protein docking algorithms and assessed for interaction with specific miRNA. Our docking analyses have generated a comprehensive map of the miRNA-NCL protein interface sites for each individual miRNA and consistently predict specific RBDs in NCL-miRNA binding. We have also identified critical residues on the NCL-RBDs that may drive the miRNA binding in an RBD-type specific manner. Our results corroborate previous studies on RBDs from other RBPs. Structural information derived from this study provides a valuable perspective for future experiments. Identification of consensus on RNA binding motifs on NCL RBDs is critical in elucidating RNA target specificity by NCL. Computational analyses provide time and cost-effective benefits over experimental techniques; the in silico predictions are important in designing rational experiments for the future investigations confirming the NCL-miRNA interactions. Our study provides the foundational steps for establishing consensus motifs on NCL-RBDs that potentially direct RNA target specificity. Targeting these specific binding sites will provide new approaches to regulate NCL functions in gene expression during tumorigenesis.

Citation Format: Avdar San, Anjana Saxena, Shaneen Singh. RNA binding domains of nucleolin exhibit specificity in driving nucleolin-miRNA interactions: An in silico modeling and RNA-protein docking study [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 844.
Abstract 846: Microsatellite instability determined by clinical targeted next generation sequencing
Authors: Yeh Ya-Chi , Chen Chien-Hung , Chen Kuan-Ying , Chen Ying-Ja , Chen Shu-Jen
Published: September 2020

Microsatellite instability (MSI)/mismatch repair (MMR) status is a positive predictor for immune checkpoint inhibitors. Conventional detection method for MSI status relies on polymerase chain reaction (PCR) of 5 microsatellite loci. With the advancement of next-generation sequencing (NGS) applied to clinical samples, we developed a MSI prediction algorithm to determine MSI status from large-panel clinical targeted NGS data accounting for more than 500 microsatellite loci. A set of colorectal cancer clinical samples with known MSI status by PCR were used to train a MSI prediction model, which predicts a sample as microsatellite instability high (MSI-H) or microsatellite stable (MSS). The model was constructed based on the change of number of repeats of different lengths from a pooled MSS baseline across microsatellites in a comprehensive cancer genomic panel targeting 440 genes. Using a quantitative measure based on more than 500 microsatellites loci, the model achieves high robustness and efficiency for MSI status detection from NGS data without matched normal. An independent dataset of clinical samples across various cancer types were used to validate the model showing an accuracy of 96.8%. In summary, MSI status can be determined by the MSI prediction model from clinical targeted NGS panel without normal paired sample.

Citation Format: Ya-Chi Yeh, Chien-Hung Chen, Kuan-Ying Chen, Ying-Ja Chen, Shu-Jen Chen. Microsatellite instability determined by clinical targeted next generation sequencing [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 846.
Abstract 858: PrismML: A machine learning platform to query genotype-phenotype patterns in large genomics studies
Authors: Reddy Anupama , Flemming Daisy , Selitsky Sara , Pavel Ana Brandusa , Alexe Gabriela , Bhanot Gyan
Published: September 2020

Background: Large-scale genomics studies (e.g. AACR Project GENIE, TCGA, TopMed) have sequenced thousands of patients in an attempt to understand disease associated genomic variables and their clinical correlates. Existing online platforms (e.g. cBioPortal) enable simple gene-based queries, but do not allow more complex modeling to understand disease pathogenesis, risk and outcome. There is an urgent need to build an interactive, modular and scalable platform that enables users to perform multivariate machine learning on existing genomic data.

Results: We have built a platform, PrismML, that enables a user to interactively query a dataset, and to run a multitude of machine learning tools, from simple statistical tests for differential analysis to multivariate modeling to predict clinical response, or mortality-risk. Since machine learning models are computationally intensive, we have used the power of cloud computing to make the analyses faster and scalable.

Key feature of our platform are: (1) availability of extensive statistical and machine learning methods; (2) implementation of best practices for machine learning, e.g. cross-validation; (3) graphical querying of results to understand the interplay among features. Users can choose to analyze existing data/studies, or upload their own data. Examples of possible queries: “identify genomic features that distinguish metastasis from primary tumors, either in a single cancer or pan-cancer”, or, “build a machine learning model to predict survival within ER- breast cancer patients”.

In addition, there is also an acute need to integrate the knowledge extracted from the multitude of data types. To this end, we have integrated multiple data types into gene-scores, and have incorporated known biological/functional information by integrating gene-scores into pathway-scores.

Summary: PrismML is an interactive and flexible platform to bring the power of machine learning and statistical modeling to the genomics community. This is an active area of development with multiple ongoing features, such as integrating multiple datasets to increase statistical power in rare diseases, and to enable subsetting large diseases to identify prognostic features.

Citation Format: Anupama Reddy, Daisy Flemming, Sara Selitsky, Ana Brandusa Pavel, Gabriela Alexe, Gyan Bhanot. PrismML: A machine learning platform to query genotype-phenotype patterns in large genomics studies [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 858.
Abstract 861: Improvements in variant calling sensitivity and specificity in single-cell DNA sequencing using deep learning
Authors: Manivannan Manimozhi , Sahu Sombeet , Dong Kim , Wang Shu , Gulati Saurabh , Parikh Saurabh , Beard Nigel , Parikh Anup
Published: September 2020

Background: It is now possible to interrogate thousands of cells in a single experiment for studying genetic variability with the advancements in single-cell sequencing technologies. Single-cell DNA platforms like Tapestri is still susceptible to errors from polymerase incorporations, structure induced template switching, PCR mediated recombination in Tapestri workflow or DNA-damage. Errors from sequencing could propagate from cluster amplification, cycle sequencing or image analysis. All together these errors can be divided into substitutions, insertions and deletion errors and can range from 0.5% to 2% depending on the sequencer. This makes rare variant and minimal residual disease detection challenging. To address these challenges, we developed deep learning models for correcting the errors, reduce false-positive rates and predict true variants.

Method: First we build a consensus sequence from several reads to predict the correct sequence. The initial layers learn the motifs and local sequence contexts in classifying the patterns. The output of this network is a probability distribution over possible bases and the prediction is the base with highest probability. The bases in the reads are subsequently corrected to the predicted base from the first step model. After error correcting the reads, we used the variants called by Genome Analysis Toolkit to feed into a multi-class classifier network. Our features consists of percent of cells mutated, and the different genotype features including depth, AF and quality of each variant in these cells. The truth labels are generated using tapestri instrument from multiple experiments with known bulk truth. We trained the network on over 200k cells from 13 samples and tested on a larger set of samples. Class imbalance was handled using upsampling the truth data. Our training samples include diverse samples from cell mixtures at various dilution uptill 0.1% and clinical samples processed through tapestri instrument and sequenced on a diverse set of sequencers including miseq and novaseq.

Conclusion: To validate this method, we used two different targeted panels on a Latin square model system with known truth mutations. With our 2-step workflow using error correction and variant prediction model, we significantly improved our median PPV 2-3 fold at 0.5% LOD while maintaining the sensitivity. We are further optimizing the model by adding more training samples and feature optimization.

Citation Format: Manimozhi Manivannan, Sombeet Sahu, Kim Dong, Shu Wang, Saurabh Gulati, Saurabh Parikh, Nigel Beard, Anup Parikh. Improvements in variant calling sensitivity and specificity in single-cell DNA sequencing using deep learning [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 861.
Abstract 862: A method to create aggregate histogram representations for machine learning from small sample size medical sensor time series
Authors: Moss Nick , Oakley-Girvan Ingrid , Longmire Michelle R.
Published: September 2020

Background: Machine learning has been used to successfully develop biomarkers from data collected from a wide range of commodity and specialized sensor devices. Typical machine learning algorithms, such as deep learning, require several thousand to on the order of millions of samples of data to work most effectively. However, in many studies with limited numbers of patients and data samples, such methods cannot be used.

Objective: To solve this problem, we have developed a specialized algorithm that can convert time series signals into a set of histogram signatures that can then be used with unsupervised methods such as clustering to create biomarkers.

Methods: Our methods decompose the time series data into time windows and analyze aggregate mean and variance and other statistical qualities over these windows.

Results: We will describe our approach and show how we have applied it along with genetic algorithms to perform auto-tuning for novel biomarkers and endpoints.

Conclusions: We will be able to develop a highly accurate biomarker to detect gate imbalance and impairment from limited accelerometer data.

Citation Format: Nick Moss, Ingrid Oakley-Girvan, Michelle R. Longmire. A method to create aggregate histogram representations for machine learning from small sample size medical sensor time series [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 862.
Abstract 867: Prostate cancer: AI-markers for detecting, grading, and prognosticating 5-year survival post-biopsy
Authors: Laifenfeld Daphna , Reouven Cobi , Gross Inbal , Heled Ronen , Shalev Varda , Sandbank Judith , Linhart Chaim
Published: September 2020

Adenocarcinoma of the prostate is a diverse disease with multiple treatment options and inconsistent outcomes, and is the second most common cancer diagnosed in men, with approximately one in nine men diagnosed in their lifetime. The recent development and regulatory approval of whole slide image (WSI) scanning systems, together with the advent of robust computational approaches such as artificial-intelligence (AI) and machine learning, enable the development of new AI-based algorithmic markers (“AI markers”) that can be used to support the pathologist in their diagnostic process, as well as to better predict outcome and thus disease management in prostate cancer patients. Through a collaboration with Maccabi Healthcare Services, we have developed AI-based diagnostic tools that can correctly identify multiple features within prostate core needle biopsies (PCNBs), including adenocarcinoma, Gleason grade, inflammation, high grade prostatic intraepithelial neoplasia, and others. Combining these features with clinical and molecular data, we have developed multi-feature AI markers that prognosticate 5-year survival post-biopsy using thousands of slides from over 500 patients. In addition, we identify explanatory features associated with pre-biopsy PSA levels that together may help guide treatment decisions. Using AI on a combination of multiple data types, including lab tests, clinical outcome, and tissue biopsy, we demonstrate a powerful approach for the development of novel prognostic algorithms. These algorithms constitute low-cost accessible AI markers that are tissue-sparing and can be easily applied in clinical settings for optimal patient stratification for prospective clinical trials, as well as for different treatment options in prostate cancer. Further, this approach can be extended to additional cancer tissues, with the potential to revolutionize the field of precision medicine in oncology.

Citation Format: Daphna Laifenfeld, Cobi Reouven, Inbal Gross, Ronen Heled, Varda Shalev, Judith Sandbank, Chaim Linhart. Prostate cancer: AI-markers for detecting, grading, and prognosticating 5-year survival post-biopsy [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 867.
Abstract 871: Development of a smartphone-based electrochemiluminescence biosensor for dopamine detection in advanced breast cancer
Authors: Kwon Hyun J. , Uppala Padma P. Tadi , Rivera Elmer C. , Neto Mabio R. , Marsh Daniel , Swerdlow Jonathan J. , Summerscales Rodney L.
Published: September 2020

Introduction: Studies conducted in our laboratory on proteomic profiling of breast cancer serum among women by shotgun LC-MS methodology have identified several biomarkers for early detection of breast cancer. However, not all of the identified biomarkers have been validated due to costs involved with validation tests. The development of a reliable, cost-effective highly sensitive portable system, the Electrochemiluminescence (ECL) biosensor will enable us to validate identified biomarkers that have valuable diagnostic applications.

The purpose of this study was to detect dopamine, which has been identified as a biomarker in advanced breast cancer. Dopamine and its receptors act as novel therapeutic agents in advanced breast cancer. Dopamine significantly enhances the efficacy of commonly used anticancer drugs through its antiangiogenic action.

Methods: In this work, a compact, mobile phone-based ECL sensor apparatus was developed using the phone cameras, screen-printed electrodes (SPE), and mobile app for dopamine detection. Methods of DC voltage application for ECL reaction were comprehensively studied from the mobile phone itself or external power. Under optimized sensing conditions, with disposable carbon SPE and 20 mM coreactant tri-n-propylamine (TPrA), acceptable repeatability and reproducibility were achieved in terms of relative standard deviation (RSD) of intra- and interassays, which were 6.7 and 5.5 %, respectively. The biochemical compound dopamine was measured due to its ECL quenching characteristics and its clinical significance in breast cancer detection and therapeutic properties. The quenching mechanism of Ru(bpy)32+/TPrA by dopamine was investigated based on the estimation of the constants of the Stern-Volmer equations.

Results: The linear range for detectable dopamine concentration was from 1.0 to 50 µM (R2 = 0.982). As the developed mobile phone-based ECL sensor is simple, small and assembled from low-cost components, it offers new opportunities for the development of inexpensive analytical methods and compact sensors.

Conclusion: The ECL sensor demonstrated that a new instrumentation with mobile technology in the point-of-care diagnostics of breast cancer could provide reliability and sensitivity of a high-end equipment. This project is funded by the NSF CBET division.

Citation Format: Hyun J. Kwon, Padma P. Tadi Uppala, Elmer C. Rivera, Mabio R. Neto, Daniel Marsh, Jonathan J. Swerdlow, Rodney L. Summerscales. Development of a smartphone-based electrochemiluminescence biosensor for dopamine detection in advanced breast 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 871.
Abstract 879: Functional and single-cell assessment of CRISPR-modified CAR-T cells from NSCLC patients and healthy donors
Authors: Padalia Zinkal , Dunn Andrew , Karagiannis Konstantinos , McEwan Brigid , Kuppuraju Meghna , Sagert Jason , Karnik Sushant , Dequeant Mary-Lee , Terrett Jonathan , Kalaitzidis Demetrios
Published: September 2020

Cancer patients that have undergone multiple lines of treatment can have dysfunctional immune systems. In both solid tumors and hematological malignancies, T cells have been reported to be in various states of dysfunction including senescence or exhaustion. In order to assess the potency of CAR-T cells derived from cancer patients, we created CAR-T cells targeting CD70 from non-small cell lung cancer (NSCLC) patients as well as healthy donors. Anti-CD70 CAR-T cells were created by using CRISPR/Cas9 to insert the CAR cassette into a knocked-out TRAC locus. The TRAC knock-out eliminates any TCR-mediated effector functions. CAR-T preparations from either NSCLC patients or healthy donors were assessed in vitro for T cell effector functions including cell killing, cytokine secretion and expansion in the presence of lung tumor cells expressing antigen. CAR-T cells from NSCLC patients and healthy donors were also assessed for their ability to control human lung cancer-derived tumors in immunocompromised mice. Following these functional assessments, the heterogeneity of CAR-T preparations derived from different sources was characterized further by performing single-cell RNA sequencing analysis and single-cell protein analysis (CITE-Seq and single cell cytokine secretion). A superior understanding of CAR-T cell heterogeneity and donor variability could aid in producing more efficacious drug products for cancer.

Citation Format: Zinkal Padalia, Andrew Dunn, Konstantinos Karagiannis, Brigid McEwan, Meghna Kuppuraju, Jason Sagert, Sushant Karnik, Mary-Lee Dequeant, Jonathan Terrett, Demetrios Kalaitzidis. Functional and single-cell assessment of CRISPR-modified CAR-T cells from NSCLC patients and healthy donors [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 879.
Abstract 880: Allogeneic CAR-T cell products containing 10 gene edits using CRISPR/Cas9 can retain full functionality in vivo and in vitro
Authors: McEwan Brigid , Kuppuraju Meghna , Padalia Zinkal , Terrett Jonathan , Kalaitzidis Demetrios
Published: September 2020

Hematologic malignancies have proven most responsive to CAR-T therapies. However, there is significant variability in the depth and duration of response to autologous CAR-T cells. Furthermore, CAR-T responses in solid malignancies have been minimal. T cells from cancer patients can be compromised by the disease and prior treatments, and the use of allogeneic CAR-T products could potentially provide a more robust therapy. However, even CAR-T cells from healthy donors may benefit from additional gene edits that could enhance effector function, increase durability, evade immune mechanisms and/or combat the tumor microenvironment. These types of additional CAR-T features are readily enabled by CRISPR/Cas9 technology. While recent clinical data has demonstrated the persistence of therapeutic T cells that had been edited with CRISPR, the extent of gene editing that therapeutic T cells can tolerate has not been fully described. Herein, we have generated CAR-T cells with 10 gene edits. Loss of function alleles were produced in 9 genes and a CAR cassette was knocked into the TRAC locus via homology-directed repair. CD19-directed CAR-T cells with these 10 gene edits were fully functional in vitro, as shown by their ability to expand and kill target cells and secrete cytokines while remaining non-transformed. These cells were also highly efficacious in an in vivo model of CD19+ malignancy. Importantly, these edits, which produced insertions and deletions in target genes, could be detected in the blood of mice several months post injection. These data demonstrate that CRISPR/Cas9 can be used to create highly edited allogeneic CAR-T cells, unlocking the potential to enhance many functions relevant to CAR-T health and anti-tumor activity.

Citation Format: Brigid McEwan, Meghna Kuppuraju, Zinkal Padalia, Jonathan Terrett, Demetrios Kalaitzidis. Allogeneic CAR-T cell products containing 10 gene edits using CRISPR/Cas9 can retain full functionality in vivo and in vitro [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 880.
Abstract 89: Role of CDK8 and CDK19 in STAT1 phosphorylation at serine 727
Authors: Li Jing , Liang Jiaxin , Wang Lili , Broude Eugenia , Roninson Igor , Chen Mengqian
Published: September 2020

Transcription factor STAT1 is part of the JAK/STAT signaling cascade; it plays an essential role in mediating responses to interferons (IFN). STAT1 modulates many cellular processes and has been implicated in both tumor-suppressing and tumor-promoting activities. IFNγ treatment induces STAT1 phosphorylation at tyrosine 701, enabling the translocation of STAT1 from cytoplasm to the nucleus. STAT1 is also phosphorylated at serine 727; S727 phosphorylation modulates the transcriptional activity of STAT1. Transcription-regulating kinase CDK8 was shown to be primarily responsible for IFNγ-induced STAT1 S727 phosphorylation, and serine-phosphorylated form of STAT1 was proposed as a potential pharmacodynamic (PD) marker for the activity of CDK8, an emerging cancer drug target. However, the role of CDK8 in STAT1 S727 phosphorylation in the absence of IFNγ treatment is controversial, as is the role of CDK19, a closely related paralog of CDK8, as well as the relative contributions of kinase-dependent and kinase-independent activities of CDK8 and CDK19. We have found that Senexin B, a selective CDK8/19 inhibitor, decreased both IFNγ-induced and basal STAT1 S727 phosphorylation in all the tested types of tumor cells but some phosphorylation was maintained even at the highest concentrations of Senexin B. We then generated a series of derivatives of human 293 cells with CRISPR-mediated knockout of CDK8, CDK19 and both CDK8 and CDK19 (double knockout, dKO), with subsequent reconstitution of dKO with wild-type (WT) CDK8 or CDK19 or with kinase-dead (KD) mutants of these proteins. The knockout of CDK8 or CDK19 individually had only a moderate effect on IFNγ-induced and basal STAT1 S727 phosphorylation, which remained susceptible to Senexin B. In contrast, such phosphorylation was strongly decreased in dKO cells, where it was unaffected by Senexin B. Senexin B-sensitive STAT1 S727 phosphorylation was restored by re-introduction of WT CDK8 or CDK19 but not of their KD mutants. Hence, both CDK8 and CDK19 mediate STAT1 S727 phosphorylation in kinase-dependent manner. We also tested different cytokines and stress-inducing agents for the ability to induce STAT1 S727 phosphorylation in WT and dKO cells. Several treatments, including serum stimulation, EGF, TNFα, etoposide and taxol, increased this phosphorylation in dKO cells, indicating that STAT1 serine phosphorylation induced by many treatments was CDK8/19-independent. Hence, great caution needs to be utilized in using STAT1 S727 phosphorylation as a PD marker for CDK8 activity.

Citation Format: Jing Li, Jiaxin Liang, Lili Wang, Eugenia Broude, Igor Roninson, Mengqian Chen. Role of CDK8 and CDK19 in STAT1 phosphorylation at serine 727 [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 89.
Abstract 893: A chimeric PD1-CD28 switch receptor enhances the activity of TRuC-T cells
Authors: McCarthy Derrick P. , Guyette Sarah , Lofgren Michael , Sethuraman Jyothi , DeSilva Thamara , Aziz Ahmar , Patterson Troy , Datari Shruti , Chan Tiffany , Kieffer-Kwon Philippe , Rold Christopher J. , Singh Reshma , Ding Jian , Horton Holly , Barnitz R. Anthony , Cornforth Andrew , Tighe Robert , Hofmeister Robert J. , Gutierrez Dario A.
Published: September 2020

Cluster of differentiation 28 (CD28) and programmed death receptor 1 (PD-1) are members of the CD28 superfamily of co-receptors that have critical roles in the regulation of T cell-mediated immunity and inflammation. Ligation of CD28 synergizes with T cell receptor (TCR) signaling to enhance T cell activation through the PI3K-Akt pathway, while PD-1 ligation by its ligands (PD-L1/L2) sequesters critical mediators of signaling from the TCR complex, thereby shunting T cell activation and effector function. Thus, the expression of PD-L1/L2 in solid tumors may pose a significant barrier to anti-tumor immunity and the efficacy of adoptive T cell therapies (ACT). We have recently described a novel class of engineered T cells that integrate a T cell receptor fusion construct (TRuC®) into the natural TCR complex, thereby reprogramming the specificity of the T cell to recognize tumor surface antigen in a human leukocyte antigen (HLA)-independent fashion. TC-210 T cells expressing mesothelin (MSLN) specific TRuCs demonstrate robust anti-tumor immunity in preclinical models of mesothelioma, protecting mice from tumor re-challenge while inducing lower levels of inflammatory cytokine release when compared to a 2nd generation MSLN-targeted CAR T. Here, we show that co-expression of a PD-1:CD28 switch receptor comprising the PD-1 extracellular domain fused to the CD28 intracellular domain, enhances the activity of TC-210 T cells. When compared to TC-210 expressing only the TRuC, co-expression of PD1:CD28 was able to restore PD-L1 mediated inhibition of cytokine production and proliferation in co-culture with tumor cells. In vivo and molecular mechanistic studies are currently underway.

Citation Format: Derrick P. McCarthy, Sarah Guyette, Michael Lofgren, Jyothi Sethuraman, Thamara DeSilva, Ahmar Aziz, Troy Patterson, Shruti Datari, Tiffany Chan, Philippe Kieffer-Kwon, Christopher J. Rold, Reshma Singh, Jian Ding, Holly Horton, R. Anthony Barnitz, Andrew Cornforth, Robert Tighe, Robert J. Hofmeister, Dario A. Gutierrez. A chimeric PD1-CD28 switch receptor enhances the activity of TRuC-T cells [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 893.
Abstract 899: Remarkable anti-tumor response in a HCC transgenic mouse model treated with GNS561 in combination with anti-PD1
Authors: Rachid Madani , Tijeras-Raballand Annemilaï , Serdjebi Cindy , Brun Sonia , Ansaldi Christelle , Raymond Eric , Halfon Philippe
Published: September 2020

Introduction:Hepatocellular carcinoma (HCC) is the most frequent primary liver cancer, leading to 75,000 deaths annually. Immunotherapeutic intervention has emerged as a novel effective treatment to delay the progression of aggressive tumors and suppress tumor recurrence and metastasis. However, few clinical immunotherapy trials have been conducted in HCC patients and there is an unmet need for novel therapeutic strategies. Combinations of conventional and novel treatments with immune-oncologic agents are now regarded as a therapy that can dramatically improve the outcome of patients with HCC.GNS561 is a lysosomotropic small molecule that was investigated in the context of antitumor activity alone or in combination with a PD-1 inhibitor using a transgenic immunocompetent mouse model (ASV-B).

Materials and Methods: 40 ASV-B mice were treated with either the vehicle (p.o. water pH= 4, 5 days per week), GNS561 (p.o. 50 mg/kg/5 days per week), mouse anti-PD1 antibody (i.p. 10 mg/kg/twice a week [BIW]) or a combination of GNS561 and mouse anti-PD1 (p.o. 50 mg/kg/5 days per week and i.p. 10 mg/kg/BIW respectively) for 8 weeks. Tumor burden was evaluated by measuring the liver volume and blood flow velocity in the coeliac trunk by US/doppler 4 and 8 weeks (W8) after treatment start, the macronodules count and liver weight at sacrifice (W8). Intra and peritumoral CD8+ cells were counted.

Results: All treatments were well tolerated. No significant response was observed with the anti-PD1 monotherapy compared with the vehicle. At W8, GNS561 alone or in combination with an anti-PD-1 showed a significant rapid and durable tumor response based on the macronodule count, decreased liver blood flow in the coeliac trunk, liver volume and weight (-59% and -77%; -18% and -31%; -36% and -37%; -37% and -52%, respectively). Based on preliminary mechanistic data, GNS561 alone or in combination showed an increase in the count of CD8+ cells penetrating the tumor site compared to the vehicle and the anti-PD1 alone, suggesting GNS561 may reinstore the anti-PD1 activity by facilitating CD8+ cells to reach the tumor site to exert their antitumoral activity.

Conclusion: GNS561 alone or in combination with an anti-PD1 showed a significant antitumoral response. A combination of GNS561 with an anti-PD1 could then be of clinical interest in the treatment of hepatocelullar carcinoma.

Citation Format: Madani Rachid, Annemilaï Tijeras-Raballand, Cindy Serdjebi, Sonia Brun, Christelle Ansaldi, Eric Raymond, Philippe Halfon. Remarkable anti-tumor response in a HCC transgenic mouse model treated with GNS561 in combination with anti-PD1 [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 899.
Abstract 901: Ferritin nanocages to deliver CD47 antagonist, SIRPγ, for cancer immunotherapy
Authors: Choi Yoonjeong , Kim Insan
Published: September 2020

Eliciting effective tumor antigen-specific immunity requires targeting the initial stages of the anticancer immunity cycle, including activation of antigen presenting cells (APCs) for tumor antigen uptake and presentation, and T cell priming. Here, the research aimed to explore the novel immunotherapeutic strategy using protein nanocage platform that enhances the phagocytic activity of phagocytes in combination with treatment of immunogenic cell death inducing agents, which could boost processing of antigens by APCs, thereby trigger efficient antitumor immunity. The recombinant ferritin protein nanocages expressing SIRPγ peptides, named FHSirpγ, was designed to interact with CD47 of cancer cells, which could effectively blocking ‘don't eat me signal', CD47. The binding affinity of FHSirpγ to cancer cells was reinforced by adapting several mutations on protein sequence, which showed up to 10 folds of improvement. Therefore, FHSirpγ was able to successfully stimulate phagocytosis of phagocytes toward various cancer cells, e.g. HT29, B16F10, CT26.CL25 and J558, up to approximately 2 folds in vitro. In the aspect of improvement in antigen release, Carfilzomib(CFZ), the FDA approved 2nd generation proteasome inhibitor on multiple myeloma, was treated to cancer cells, which showed tolerable level of cell cytotoxicities and enhanced release of danger associated molecular patterns(DAMPs), such as HSP70 and HMGB1, which were detected from cell culture medium after 24hrs of incubation on above mentioned cell lines. The antitumorigenic efficacy was preliminary verified in the case of B16F10 and J558 implanted murine tumor model, which showed approximately 75% of tumor growth regression when FHSirpγ and CFZ were treated intravenously. Overall, treatment of FHSirpγ showed antitumor efficacy via enhancement of phagocytosis in vivo and in vitro, especially when combined with immunogenic cell death inducer.

Citation Format: Yoonjeong Choi, Insan Kim. Ferritin nanocages to deliver CD47 antagonist, SIRPγ, for cancer immunotherapy [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 901.
Abstract 904: Stimulation and expansion of oncogene-reactive tumor infiltrating T cells through combined Ad-HER2Δ16 vaccination and anti-PD1 enable anti-tumor responses against established HER2 BC
Authors: Crosby Erika J. , Acharya Chaitanya , Rabiola Christopher , Muller William J. , Chodosh Lewis A. , Broadwater Gloria , Shepherd Jonathan , Hollern Daniel , He Xiaping , Perou Charles M. , Ashby Benjamin K. , Vincent Benjamin G. , Morse Michael A. , Lyerly Herbert K. , Hartman Zachary C.
Published: September 2020

Despite promising advances, overcoming immune suppression and driving productive immune responses in the tumor microenvironment remains a significant challenge. Using a spontaneous breast cancer model, we found that vaccination targeting HER2d16, a highly expressed driver of oncogenicity and HER2-therapeutic resistance, elicited significant anti-tumor responses. In contrast, vaccines targeting a non-driver tumor-specific antigen (GFP) or unique non-driver tumor neoepitopes had no impact on tumor occurrence or progression. While vaccine-induced HER2-specific CD8+ T cells were essential for responses, tumors treated therapeutically with a vaccine alone ultimately progressed. However, long-term tumor control and complete tumor regression was only achieved when vaccine was combined with immune-checkpoint blockade (anti-PD1). Single cell RNAsequencing of tumor-infiltrating T cells (TILs) revealed that while vaccination expanded CD8 T cells within the tumor, only the combination of vaccine with anti-PD1 therapy induced a tumor rejection activation signature that was identified in the expanded T cell clones. We go on to use the single cell data to clone and reexpress the TCRs from expanded TILs from vaccinated mice and show that they are HER2-reactive. This data conclusively demonstrates the efficacy of this vaccination strategy in expanding tumor rejection T cells and supports its further evaluation in an ongoing Phase II trial (NCT03632941). The workflow used to identify and clone expanded, tumor specific T cells has broad potential applications across tumor types and treatment platforms.

Citation Format: Erika J. Crosby, Chaitanya Acharya, Christopher Rabiola, William J. Muller, Lewis A. Chodosh, Gloria Broadwater, Jonathan Shepherd, Daniel Hollern, Xiaping He, Charles M. Perou, Benjamin K. Ashby, Benjamin G. Vincent, Michael A. Morse, Herbert K. Lyerly, Zachary C. Hartman. Stimulation and expansion of oncogene-reactive tumor infiltrating T cells through combined Ad-HER2Δ16 vaccination and anti-PD1 enable anti-tumor responses against established HER2 BC [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 904.
Abstract 917: Functional blocking of CD5 on T cells to enhance the efficacy of therapeutic PD-1 blockade in treatment of mouse 4T1 breast tumors
Authors: Alotaibi Faizah , Rytelewski Mateusz , Figueredo Rene , Zareardalan1 Ronak , Vareki Saman Maleki , Zheng Xiufen , Zhang Meng , Ferguson Peter , El-Hajjar Mikal , Najajreh Yousef , Min Wei-ping , Koropatnick James
Published: September 2020

Blockade of programmed cell death protein 1 (PD-1) is approved for treatment of multiple human cancers and is the focus of multiple studies due to its key role in T cell function. However, only patients with ‘'hot'' tumors (i.e. those with increased numbers of tumor-infiltrating CD8+ T cells) respond well to the blockade. This suggests that new strategies to increase infiltration of CD8+ T cells into tumors will increase the number of tumor types and patients benefiting from anti-PD-1 therapy. CD5, a member of the scavenger receptor cysteine-rich (SRCR) superfamily, is expressed on T cells and a subset of B cells (B1a). It can attenuate TCR signaling and impair cytotoxic T lymphocyte (CTL) activation. CD5 knockout mice have increased anti-tumor immunity and reduced homograft tumor growth: reducing CD5 on CTLs may be therapeutically beneficial to enhance the anti-tumor response and increase tumor-infiltrating CD8+ T cells. We report that in vivo administration of anti-CD5 blocking MAb treatment increased primary T cell activation in response to 4T1 tumor cell homografts and ex vivo activation as measured by increased CD69, Fas, Fas ligand, IFNγ, PD-1, and apoptosis. Further, anti-CD5 treatment enhanced the capacity of primary T cells to kill 4T1 tumor cells ex vivo. Mice receiving anti-CD5 and anti-PD-1 in combination exhibited increased overall survival compared to mice treated with either agent alone. These data support the potential of blockade of CD5 function to enhance T cell-mediated anti-tumor immunity and PD-1 blockade treatment.

Citation Format: Faizah Alotaibi, Mateusz Rytelewski, Rene Figueredo, Ronak Zareardalan1, Saman Maleki Vareki, Xiufen Zheng, Meng Zhang, Peter Ferguson, Mikal El-Hajjar, Yousef Najajreh, Wei-ping Min, James Koropatnick. Functional blocking of CD5 on T cells to enhance the efficacy of therapeutic PD-1 blockade in treatment of mouse 4T1 breast tumors [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 917.
Abstract 921: TLR5 agonists enhance anti-tumor immunity and overcome resistance to immune checkpoint therapy
Authors: Gonzalez Caleb , Williamson Sarah , Gammon Seth , Piwnica-Worms David
Published: September 2020

Despite the success of immune checkpoint therapies (ICT) in achieving durable responses in subsets of cancer patients, not all patients respond to these types of therapies. Primary and adaptive resistance to immunotherapies present a considerable obstacle in achieving enhanced survival in a broader population of patients. Innate immune activators have been actively pursued for their antitumor potential. Herein, we report that a syngeneic 4T1 mammary carcinoma murine model for established highly refractory triple negative breast cancer showed enhanced survival when treated intra-tumorally with the TLR5 agonist flagellin, in combination with intra-peritoneal antibodies targeting CTLA-4 and PD-1. Long-term survivor mice showed immunologic memory upon tumor re-challenge and a distinctive immune activating cytokine profile that engaged both innate and adaptive components of the immune system. Of note, low serum levels of G-CSF at weeks 6 and 7 correlated highly with enhanced survival at week 18 (Hazzard Ratio 11, p < 0.01, n=11). Furthermore, we also observed enhanced survival with combination TLR5 agonist plus ICT in the poorly immunogenic B16-F10 melanoma tumor model. Combination immune checkpoint therapy plus innate immune activation with TLR5 agonists may offer a new therapeutic strategy to treat ICT-refractory solid tumors.

Citation Format: Caleb Gonzalez, Sarah Williamson, Seth Gammon, David Piwnica-Worms. TLR5 agonists enhance anti-tumor immunity and overcome resistance to immune checkpoint therapy [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 921.
Abstract 934: “GPCR-ome” modulation upon PD1 / PDL1 axis blockade
Authors: Nafia Imane , Leroy Xavier , Cerf Loic , Guegan Jean-Philippe , Blayo Anne-Laure , Italiano Antoine , Schann Stephan , Bessede Alban
Published: September 2020

Background: Immunotherapy represents a novel weapon within the cancer armamentarium with unprecedented response observed in several indications including among others metastatic melanoma and Lung cancer. However, the limited rate of response accounting for app. 30% requires further optimization and thus calls the interest in elucidating mechanisms underlying sensitivity to immune checkpoint inhibitors. G Protein-Coupled Receptors (GPCRs) are the largest gene family of cell membrane-associated molecules mediating signal transmission, involved in several physiological functions including the shaping of the immune response but their role in tumor biology and particularly in immune evasion and resistance to immunotherapy remains to be elucidated

Methods: Using a preclinical syngeneic mouse model of sarcoma based on the inoculation of murine sarcoma MCA205 cell line, we investigated - besides the evaluation of tumor growth and survival - a large set of GPCRs upon PDL1 or PD1 blockade. Gene expression analysis was performed on tumor samples by mean of RNA sequencing. Data were analyzed using computational methodology including CIBERSORT and GSEA algorithms to evaluate immune cell subset within the tumor and specific gene datasets enrichment respectively. A large set of GPCRs (1412 in total) was then investigated through conventional Differential Gene Expression (DGE) analysis.

Results: PDL1/PD1 axis blockade, using specific antibodies, exhibited a strong anti-tumor effect. As highlighted by CIBERSORT analysis, anti-PD1/PDL1 antibodies triggered a CD8 and activated NK cells infiltration within the tumor. The recruitment of such effectory populations was associated with enrichment in genes from different hallmarks datasets including allograft rejection and interferon signaling thus confirming the induction of an efficient anti-tumor immune response. Concomitantly, this study revealed a significant up-regulation of several GPCRs already known to be involved in immune evasion - including Adenosine, Prostaglandins and chemokines receptors - but also highlighted the modulation of unexpected orphan or peptidic receptors. Altogether, this novel dataset confirms the induction of an effective anti-tumor immune response upon PD1 / PDL1 blockade and highlights the modulation of GPCRs that warrants further investigation to delineate their exact participation in sensitivity to immunotherapy.

Citation Format: Imane Nafia, Xavier Leroy, Loic Cerf, Jean-Philippe Guegan, Anne-Laure Blayo, Antoine Italiano, Stephan Schann, Alban Bessede. “GPCR-ome” modulation upon PD1 / PDL1 axis blockade [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 934.
Abstract 942: HPK1, hematopoietic progenitor kinase 1, is a promising therapeutic target for cancer immunotherapy
Authors: Ciccone David , Rocnik Jennifer , Lazari Vad , Linney Ian , Briggs Michael , Collis Alan , Loh Christine , Ashwell Mark , Montana John , Tummino Peter , Kaila Neelu
Published: September 2020

Introduction: HPK1, a member of the MAP4K family of protein serine/threonine kinases, is involved in regulating signal transduction cascades in cells of hematopoietic lineage. Recent data from HPK1 knockout animals and kinase-inactive knock-in animals underscores the role of HPK1 in negatively regulating lymphocyte activation. This negative-feedback role of HPK1 downstream of lymphocyte activation and function combined with its restricted expression in cells of hematopoietic origin make it an ideal drug target for enhancing anti-tumor immunity.

Experimental Procedures: A structure-based drug design approach was used to identify potent and selective inhibitors of HPK1. Various biochemical and biophysical assays, as well as a primary in vitro T cell activation assay, were utilized for multiple rounds of structure-activity relationship (SAR) studies. In vivo target engagement and pharmacodynamic data were generated using an anti-CD3 mouse model.

Results: In vitro, HPK1 small molecule inhibition resulted in enhanced IL-2 production in primary mouse T cells and in purified human T cells stimulated with a suboptimal dose of anti-CD3/anti-CD28. Increased selectivity of HPK1 inhibitors relative to T cell-specific kinases and within the MAP4K family was responsible for further enhancing the IL-2 response in activated T cells. In vivo, qd oral dosing of an HPK1 inhibitor completely abrogated phosphorylated SLP-76, induced by administration of anti-CD3. Furthermore, inflammatory cytokine production was enhanced in vivo upon HPK1 inhibition.

Conclusion: Pharmacological blockade of HPK1 kinase activity represents a novel and powerful immunomodulatory approach for anti-tumor immunity.

Citation Format: David Ciccone, Jennifer Rocnik, Vad Lazari, Ian Linney, Michael Briggs, Alan Collis, Christine Loh, Mark Ashwell, John Montana, Peter Tummino, Neelu Kaila. HPK1, hematopoietic progenitor kinase 1, is a promising therapeutic target for cancer immunotherapy [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 942.