Citations

Abstract Glioblastoma is the most common and lethal primary brain tumor in adults, with a median survival less than 15 months despite current standard of care. Oncolytic immunovirotherapies (OVs) have shown promise in early clinical trials. OVs are engineered to specifically target cancer cells, trigger autophagic programmed cell death, and release tumor antigens in the context of T-cell activating cytokines. Cellular communication network factor 1 (CCN1) is an extracellular matrix protein expressed in 70% of glioblastomas that has been shown to drastically reduce OV efficacy, particularly herpes simplex virus type 1 (HSV-1). Our objectives were to decode protein-protein interaction (PPI) networks activated by CCN1, identify critical nodes in resistance networks, and use this analysis to design OVs that overcome CCN1-mediated resistance. We used NetDecoder to elucidate phenotype-specific PPI subnetworks in LN229 human glioblastoma cells with tetracycline-inducible CCN1 expression. Publicly available microarray data on CCN1-induced and control samples established differentially expressed genes, which served as sources in our PPI network to derive prioritized context-specific subnetworks. We found that 11 source genes collaborate via 39 deep nodes to confer OV resistance to CCN1-expressing glioblastomas. Of these, a router (IKBKE) and a sink (YBX1) have been previously implicated in glioblastoma pathogenesis. We conclude that autophagy regulator HSP90AA1, a critical node, may be targeted to improve OV efficacy in CCN1-expressing glioblastomas. Furthermore, WebGestalt overrepresentation analysis of subnetwork nodes suggests that oncolytic adenovirus may be more effective than HSV-1 as a synthetic biology chassis.

Abstract Understanding the function of non-coding genomic sequence variants represents a challenge for biomedicine. Many diseases are products of gene-by-environment interactions with complex mechanisms. This study addresses these themes by mechanistic characterization of non-coding variants that influence gene expression only after drug or hormone exposure. Using glucocorticoid signaling as a model system, we integrated genomic, transcriptomic, and epigenomic approaches to unravel mechanisms by which variant function could be revealed by hormones or drugs. Specifically, we identified cis-regulatory elements and 3D interactions underlying ligand-dependent associations between variants and gene expression. One-quarter of the glucocorticoid-modulated variants that we identified had already been associated with clinical phenotypes. However, their affected genes were ‘unmasked’ only after glucocorticoid exposure and often with function relevant to the disease phenotypes. These diseases involved glucocorticoids as risk factors or therapeutic agents and included autoimmunity, metabolic and mood disorders, osteoporosis and cancer. For example, we identified a novel breast cancer risk gene, MAST4, with expression that was repressed by glucocorticoids in cells carrying the risk genotype, repression that correlated with MAST4 expression in breast cancer and treatment outcomes. These observations provide a mechanistic framework for understanding non-coding genetic variant-chemical environment interactions and their role in disease risk and drug response.

BACKGROUND A patient-derived organoid (PDO) platform may serve as a promising tool for translational cancer research. In this study, we evaluated PDO’s ability to predict clinical response to gastrointestinal (GI) cancers. METHODS We generated PDOs from primary and metastatic lesions of patients with GI cancers, including pancreatic ductal adenocarcinoma, colorectal adenocarcinoma, and cholangiocarcinoma. We compared PDO response with the observed clinical response for donor patients to the same treatments. RESULTS We report an approximately 80% concordance rate between PDO and donor tumor response. Importantly, we found a profound influence of culture media on PDO phenotype, where we showed a significant difference in response to standard-of-care chemotherapies, distinct morphologies, and transcriptomes between media within the same PDO cultures. CONCLUSION While we demonstrate a high concordance rate between donor tumor and PDO, these studies also showed the important role of culture media when using PDOs to inform treatment selection and predict response across a spectrum of GI cancers. TRIAL REGISTRATION Not applicable. FUNDING The Joan F. & Richard A. Abdoo Family Fund in Colorectal Cancer Research, GI Cancer program of the Mayo Clinic Cancer Center, Mayo Clinic SPORE in Pancreatic Cancer, Center of Individualized Medicine (Mayo Clinic), Department of Laboratory Medicine and Pathology (Mayo Clinic), Incyte Pharmaceuticals and Mayo Clinic Hepatobiliary SPORE, University of Minnesota-Mayo Clinic Partnership, and the Early Therapeutic program (Department of Oncology, Mayo Clinic).

Abstract Background: Large scale genetic perturbations screens have been instrumental for many key discoveries. In the last decade sequence specific genetic perturbations created RNAi and CRISPR (PMID: 25446316). Recently, specific genome targeting approaches using single guide RNAs (sgRNAs) for the CRISPR-Cas9 system have been repurposed to induce sequence-specific repression or activation of gene expression at a genome-wide scale. Different perturbation approaches have different effects and encompass a trade-off between specificity and duration in establishing a measurable perturbation which can result in different biological readouts. However, bench-side strategies are time consuming and expensive. The method described here aims to build a systems-based computational platform to assess pharmacological and biological perturbations at genome-wide network level.Methods: Our network tool NetDecoder (Nucleic Acids Res. 2016; 44(10):e100) that models genome-wide information flow will be used to build context specific protein-protein interaction networks. These networks will be subsequently subjected to in silico perturbations and their impacts on network properties will be assessed. AVANA and Demeter datasets will be used during method validation procedures. Results: Using publicly available expression datasets we generated context specific Breast Cancer networks and individually manipulated nodes and edges of context-specific networks associated with pharmacological FDA approved targets. Our perturbation networks captured cellular rewiring by engulfing new gene players, alterations of the network size and its connectivity. Conclusions: Our in-silico genome wide perturbation platform provides a flexible approach to fine-tune single and tandem manipulations, allowing for inexpensively monitoring a range of pharmacological interventions using large omics data. Citation Format: Cristina Correia, Choong Yong Ung, Cheng Zhang, Scott H. Kaufmann, Hu Li. A genome wide pharmacological perturbation platform [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1226.

Abstract Current understandings of individual disease etiology and therapeutics are limited despite great need. To fill the gap, we propose a novel computational pipeline which collects potent disease gene cooperative pathways to envision individualized disease etiology and therapies. Our algorithm constructs individualized disease modules de novo which enable us to elucidate the importance of mutated genes in specific patients and to understand the synthetic penetrance of these genes across patients. We reveal that importance of notorious cancer drivers TP53 and PIK3CA fluctuate widely across breast cancers and peak in tumors with distinct numbers of mutations, and that rarely mutated genes such as XPO1 and PLEKHA1 have high disease module importance in specific individuals. Furthermore, individualized module disruption enables us to devise customized singular and combinatorial target therapies which were highly varied across patients demonstrating the need for precision therapeutics pipelines. As the first analysis of de novo individualized disease modules, we illustrate the power of individualized disease modules for precision medicine by providing deep novel insights on the activity of diseased genes in individuals. Citation Format: Taylor Weiskittel, Cristina Correia, Choong Ung, Cheng Zhang, Hu Li. De novo individualized disease modules reveal the synthetic penetrance of genes and inform personalized treatment regimens [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 490.

Background and Purpose Acamprosate is an anti‐craving drug used for the pharmacotherapy of alcohol use disorder (AUD). However, only some patients achieve optimal therapeutic outcomes. This study was designed to explore differences in metabolomic profiles between patients who maintained sobriety and those who relapsed, to determine whether those differences provide insight into variation in acamprosate treatment response phenotypes. Experimental Approach We previously conducted an acamprosate trial involving 442 AUD patients, and 267 of these subjects presented themselves for a 3‐month follow‐up. The primary outcome was abstinence. Clinical information, genomic data and metabolomics data were collected. Baseline plasma samples were assayed using targeted metabolomics. Key Results Baseline plasma arginine, threonine, α‐aminoadipic acid and ethanolamine concentrations were associated with acamprosate treatment outcomes and baseline craving intensity, a measure that has been associated with acamprosate treatment response. We next applied a pharmacometabolomics‐informed genome‐wide association study (GWAS) strategy to identify genetic variants that might contribute to variations in plasma metabolomic profiles that were associated with craving and/or acamprosate treatment outcome. Gene expression data for induced pluripotent stem cell‐derived forebrain astrocytes showed that a series of genes identified during the metabolomics‐informed GWAS were ethanol responsive. Furthermore, a large number of those genes could be regulated by acamprosate. Finally, we identified a series of single nucleotide polymorphisms that were associated with acamprosate treatment outcomes. Conclusion and Implications These results serve as an important step towards advancing our understanding of disease pathophysiology and drug action responsible for variation in acamprosate response and alcohol craving in AUD patients.

The clock is ticking for senescent cells Senescent cells promote their own recognition and removal through the immune system by generating a bioactive secretome called the senescence-associated secretory phenotype (SASP). Sturmlechner et al . report that the cell cycle regulator p21 directs an early form of the SASP, which they call the p21-activated secretory phenotype (PASP) (see the Perspective by Reen and Gil). As part of the PASP, the chemokine CXCL14 attracts macrophages, which monitor stressed cells expressing elevated p21. If stressed cells recuperate and p21 levels return to normal within 4 days, then macrophages disengage from their targets. Otherwise, macrophages recruit cytotoxic T cells that facilitate target cell removal. Other cell cycle regulators such as p16 can induce many factors overlapping with the PASP, but p21 uniquely drives this CXCL14-mediated “timer” mechanism of senescent cell immunosurveillance. —STS

Abstract Glioblastoma multiforme (GBM) is a particularly aggressive primary brain tumor that is relatively common in adults. The disease comes with a dismal prognosis, often with expected survival just over a year when treated with surgery, chemotherapy, and radiation. A promising addition to our GBM treatment arsenal are oncolytic viruses (OVs), a class of immunotherapy now in clinical trials. The most effective OVs home in on tumor cells, killing them and releasing tumor-associated antigens that elicit antitumor immunity. This effectiveness, however, varies depending on the cell state—a property that may be influenced by the composition of the extracellular matrix (ECM) of GBM. Cellular communication network factor 1 (CCN1) is found in the ECM of the majority of GBMs and is predictive of resistance to OVs, particularly those derived from herpes simplex virus type 1 (HSV-1). In this study, our aim is to understand how extracellular CCN1 alters the GBM intracellular state in a manner that confers resistance to OVs. We began by using our NetDecoder platform to build CCN1-specific prioritized protein-protein interaction (PPI) networks from published LN229 human GBM transcriptomic datasets. From this network, we identified 12 PPI edges that dominate the network flow in CCN1-high LN229 cells when compared to CCN1-low controls. The 21 unique nodes that comprise these binary PPI edges were extracted and subjected to downstream biological process overrepresentation analyses using Gene Ontology. We found that the cytokine-mediated signaling pathway (FDR = 4.2 x 10-11; enrichment ratio = 15.8) and the cellular response to cytokine stimulus (FDR = 3.1 x 10-9; enrichment ratio = 10.9) were highly enriched when mapped to these nodes. We conclude that CCN1, acting as a paracrine signal in the GBM tumor microenvironment, primes the cell to inhibit HSV-1 and other candidate OV replication prior to any virus interactions, thus contributing to immunovirotherapy resistance. While CCN1 and its cell surface integrin binding partners are ostensible drug targets for overcoming this resistance, pharmacologic interventions that target CCN1-specific high flow edges in our prioritized PPI network may be more effective. Citation Format: Dileep D. Monie, Cristina Correia, Cheng Zhang, Choong Ung, Richard G. Vile, Hu Li. Innate immunity and cytokine signaling pathways drive resistance to HSV-1 oncolytic immunovirotherapy in glioblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1679.

Abstract One of the greatest barriers to curative treatment of neuroblastoma is its frequent metastatic outgrowth prior to diagnosis, especially in cases driven by amplification of the MYCN oncogene. However, only a limited number of regulatory proteins that contribute to this complex MYCN-mediated process have been elucidated. Here we show that the growth arrest-specific 7 (GAS7) gene, located at chromosome band 17p13.1, is preferentially deleted in high-risk MYCN-driven neuroblastoma. GAS7 expression was also suppressed in MYCN-amplified neuroblastoma lacking 17p deletion. GAS7 deficiency led to accelerated metastasis in both zebrafish and mammalian models of neuroblastoma with overexpression or amplification of MYCN. Analysis of expression profiles and the ultrastructure of zebrafish neuroblastoma tumors with MYCN overexpression identified that GAS7 deficiency led to (i) downregulation of genes involved in cell–cell interaction, (ii) loss of contact among tumor cells as critical determinants of accelerated metastasis, and (iii) increased levels of MYCN protein. These results provide the first genetic evidence that GAS7 depletion is a critical early step in the cascade of events culminating in neuroblastoma metastasis in the context of MYCN overexpression. Significance: Heterozygous deletion or MYCN-mediated repression of GAS7 in neuroblastoma releases an important brake on tumor cell dispersion and migration to distant sites, providing a novel mechanism underlying tumor metastasis in MYCN-driven neuroblastoma. See related commentary by Menard, p. 2815