Search

Pevonedistat (MLN4924), a selective inhibitor of the NEDD8-activating enzyme E1 regulatory subunit (NAE1), has demonstrated significant therapeutic potential in several malignancies. Although multiple mechanisms-of-action have been identified, how MLN4924 induces cell death and its potential as a combinatorial agent with standard-of-care (SoC) chemotherapy in colorectal cancer (CRC) remains largely undefined. In an effort to understand MLN4924-induced cell death in CRC, we identified p53 as an important mediator of the apoptotic response to MLN4924. We also identified roles for the extrinsic (TRAIL-R2/caspase-8) and intrinsic (BAX/BAK) apoptotic pathways in mediating the apoptotic effects of MLN4924 in CRC cells, as well as a role for BID, which modulates a cross-talk between these pathways. Depletion of the anti-apoptotic protein FLIP, which we identify as a novel mediator of resistance to MLN4924, enhanced apoptosis in a p53-, TRAIL-R2/DR5-, and caspase-8-dependent manner. Notably, TRAIL-R2 was involved in potentiating the apoptotic response to MLN4924 in the absence of FLIP, in a ligand-independent manner. Moreoever, when paired with SoC chemotherapies, MLN4924 demonstrated synergy with the irinotecan metabolite SN38. The cell death induced by MLN4924/SN38 combination was dependent on activation of mitochondria through BAX/BAK, but in a p53-independent manner, an important observation given the high frequency of TP53 mutation(s) in advanced CRC. These results uncover mechanisms of cell death induced by MLN4924 and suggest that this second-generation proteostasis-disrupting agent may have its most widespread activity in CRC, in combination with irinotecan-containing treatment regimens.

The receptor tyrosine kinase ROR1 is a cell-surface onco-fetal protein expressed on a variety of solid tumours and haematological malignancies, which has limited expression on normal adult tissue. A functional role for ROR1 in tumorigenesis and disease progression has been demonstrated in a number of cancer indications. ROR1 is also involved in mediating drug resistance (for example to chemotherapies as well as to the targeted therapy T-DM1), activation of YAP/TAZ signalling and up-regulation of BMI-1. Consistent with this pleiotropic role, increased ROR1 expression correlates with poor clinical outcome in a number of cancer indications including triple negative breast cancer, ovarian cancer and lung adenocarcinoma. As a result, ROR1 has emerged as a highly attractive target for cancer therapy, and its limited expression on normal tissues make it particularly well suited for antibody and protein-drug conjugate (ADC and PDC) approaches. This has been fuelled by recent Phase I clinical data for the ROR1 ADC, VLS-101, in patients with advanced MCL and DLBCL and the potential of ROR1-targeting drug conjugates for the treatment of ROR1+ solid tumour indications. We report the development of novel, differentiated protein drug conjugates targeting ROR1 based on Variable New Antigen Receptor domains (VNARs). VNARs are the smallest antigen binding domain in the vertebrate kingdom and their small size and modular nature offer a number of potential benefits over full-length antibodies as the payload delivery vehicle in PDC approaches. We have applied our VNAR drug discovery platform, which includes novel linker-toxin combinations, to the development of potent and selective ROR1 targeting PDCs that are highly efficacious in ROR1+ patient derived xenograft (PDX) models of cancer. Homogenous drug conjugates were generated by Fc-fusion reformatting of ROR1 binding VNARs, and novel cleavable linker-toxin conjugates attached in a site-specific fashion. By exploiting proprietary crystal-structure information, a structure-guided approach was used to deliver VNAR-hFc drug conjugates with optimised drug-like properties. Though iterations of this approach, lead PDCs have been developed which cause potent ROR1-dependant killing of selected cancer cell-lines and elicit complete and durable regressions in PDX models of TNBC at doses that are very well tolerated. As the lead Candidate progresses toward clinical development, we anticipate that this excellent pre-clinical profile will translate to a highly differentiated product for the treatment of both solid tumor and haematological cancer indications. In addition, the flexible formatting accessible using our drug discovery platform has allowed us to readily access ROR1-targeting bi-paratopic and bi-specific therapeutic formats. Citation Format: Graham Cotton, Jennifer Thom, Paul Trumper, Stacey Bell, Mark Wappett, Caroline Barelle, Marina Kovaleva, Andrew Porter, Estelle McLean, Chiara Saladino, Aidan McCann, Aaron Cranston, Tim Harrison. Development of a next generation ROR1 targeting Protein Drug Conjugate (PDC) [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 LB096.

VEGF (vascular endothelial growth factor) signaling inhibitors are widely used in different cancer types; however, patient selection remains a challenge. Analyses of samples from a phase III clinical trial in metastatic colorectal cancer testing chemotherapy versus chemotherapy with the small molecule VEGF receptors inhibitor cediranib identified circulating leptin levels, BMI, and a tumor metabolic and angiogenic gene expression signature associated with improved clinical outcome in patients treated with cediranib. Patients with a glycolytic and hypoxic/angiogenic profile were associated with increased benefit from cediranib, whereas patients with a high lipogenic, oxidative phosphorylation and serine biosynthesis signature did not gain benefit. These findings translated to pre-clinical tumor xenograft models where the same metabolic gene expression profiles were associated with in vivo sensitivity to cediranib as monotherapy. These findings suggest a link between patient physiology, tumor biology, and response to antiangiogenics, which may guide patient selection for VEGF therapy in the future.

During the transition from healthy tissue to cancer and metastasis, the tumor microenvironment (TME) initiates crucial changes that licenses the progression from primary tumors to aggressive and metastatic disease. Our understanding of the specific factors and molecular mechanisms underpinning these transitions in the TME is critical for influencing the potency and scope of existing cancer therapy strategies but is still evolving and subject to substantial and widespread investigations. Here we uncover a novel molecular mechanism actioned by fibroblasts in the TME to modulate the secretion of the vascular endothelial growth factor (VEFG) via the hypoxia-inducible transcription factor (HIF1α). Utilizing primary human cells co-culture systems in combination with highly potent and selective USP7 inhibitors, we demonstrate that the deubiquitinating enzyme USP7 modulates the stability of HIF1α in primary human fibroblasts and secreted VEGF levels in primary fibroblasts as well as cancer-associated fibroblasts. This USP7-mediated modulation of VEGF secretion in the TME does not occur in cancer cells, immune cells or endothelial cells, rather it is restricted to the fibroblastic compartment. Importantly, the modulation of VEGF secretion by USP7 in fibroblasts is not mediated via the Mdm2 axis: Mdm2 antagonists are unable to recapitulate the VEGF modulation in fibroblasts. Knock-down of USP7 in primary fibroblasts validates the phenotype obtained with potent and selective USP7 inhibitors. In line with their effects on the TME in primary cell cultures, potent, selective USP7 inhibitors demonstrated tumour growth inhibition in vivo in a syngeneic cancer xenograft model that does not respond to USP7 inhibitors in vitro. Collectively, our studies reveal a molecular mechanism whereby USP7 inhibition leads to TME reprogramming mediated by an increased destabilization of HIF1α leading to reduced levels of VEGF in the TME and improved anti-tumor activity. Our results support further investigations of combination of a USP7 inhibitor with immune checkpoint inhibitors, as well as other TME modulating agents. Citation Format: Xavier Jacq, Anamarija Jurisic, Julien Daubriac, Ian T. Lobb, Mark Wappett, Aaron Cranston, Peggy Sung, Gerald Gavory, Colin O'Dowd, Tim Harisson. Discovery of a novel function for USP7 inhibitors: Reprogramming the tumor microenvironment [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 6057.

Background: Transcriptional predictors are increasingly important for sub-typing cancer patients and understanding disease aetiology, predicting patient outcomes and response to treatment. Colorectal cancers (CRC) can be classified by transcriptionally inferred consensus (CMS) and intrinsic (CRIS) sub-types, annotating transcriptional profiles derived from colorectal cancer samples with these sub-types and other transcriptionally inferred predictors requires an experienced bioinformatician and is time-consuming. Methods: Publically available R packages CMSclassifier, CRISclassifier, MCP-counter and DoRothEA have been integrated into a web interface using the R/Shiny framework which allows users to upload gene expression data which can be additionally normalized with DESeq2. Visualization of this data can be interacted with through using plotly. Results: To address this bottleneck, we developed the classifieRC Shiny app, which enables rapid analysis, annotation of colorectal cancer transcriptional profiles with state-of-the-art transcriptional CRC sub-typing (CMS and CRIS) as well as estimation of cellular composition (MCP-Counter) and transcription factor activity predictions (DoRothEA). classifieRC can be accessed through a web-based interface, a locally deployable R-script or executable software, with capability of publishing datasets and their resulting analysis to Shiny.IO. Conclusions: classifieRc enables researchers to rapidly annotate colorectal transcriptomic datasets with molecular sub-types and of functional predictions without the need for a dedicated bioinformatician, expediting insights related patient cohort analyses and novel discoveries. classifieRc provides an easy to use flexible framework for functional annotation transcriptomic datasets and a platform for development of other disease specific apps. Citation Format: Gerard Quinn, Tamas Sessler, Wendy Allen, Sarah Maguire, Philip Dunne, Darragh McArt, Harper VanSteenhouse, Peter Gallagher, Andrea Lees, Dan Longley, Bruce Seligmann, Mark Wappett, Simon McDade. classifieRc: An interactive web interface for the molecular classification of colorectal cancer from RNA-sequencing data [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 3205.

The onco-embryonic receptor tyrosine kinase ROR1is a cell-surface protein expressed on a broad range of solid tumours and haematological malignancies but is largely absent from normal adult tissue. Increased ROR1 expression correlates with poor clinical outcome in a number of cancer indications, consistent with its functional role in tumorigenesis and disease progression. In addition, elevated expression has been associated with increased metastatic potential and drug resistance in breast cancer and non-small cell lung cancer. The oncofetal expression pattern of ROR1 coupled with its role in cancer pathology and therapy resistance makes it a highly attractive target for a protein-drug conjugate approach. Shark-derived Variable New Antigen Receptor domains (VNARs) are the smallest antigen binding domain in the vertebrate kingdom. We have developed a platform to enable VNAR-based drug discovery and used it to identify a series of highly potent protein-drug conjugates that target ROR1. Through screening VNAR phage libraries, high affinity ROR1 specific binders were isolated that bind distinct regions of the extracellular domain and showed species cross reactivity (mouse, rat and human). By exploiting the modular nature of the VNAR domains, multiple different therapeutic formats have been engineered, including multimeric binders and Fc fusion proteins. Subsequent site-specific attachment of highly potent toxins yielded homogeneous VNAR-based drug conjugates which demonstrated potent ROR1-dependant killing of selected cancer cell-lines in vitro with IC50 values in the picomolar range. In a series of in vivo studies, VNAR-hFc fusions conjugated with novel linker payloads were well tolerated in mice and showed significant anti-tumor activity in mouse xenograft models of cancer, including complete and sustained tumour regressions in a patient-derived xenograft (PDX) model of triple negative breast cancer. Lead VNAR-hFc conjugates have been successfully ‘humanized' guided by de novo structural biology. These engineered VNAR-hFc drug conjugates represent exciting new candidates for the treatment of a variety of both solid tumor and haematological cancer indications. Additionally, bi-paratopic and bi-specific ROR1 binders have been generated which fully leverage the modular design of VNAR-based therapeutics. These provide second generation drug conjugates which can be tailored to specific additional therapeutic applications, further extending the applicability of this approach. Citation Format: Graham Cotton, Jennifer Thom, Paul Trumper, Andrei Kamenski, Stacey Bell, Mark Wappett, Caroline Barelle, Marina Kovaleva, Alicia Campion, Elisa Persiani, Andrew Porter, Estelle McLean, Aidan McCann, Chiara Saladino, Aaron Cranston, Tim Harrison. Exploiting the properties of VNAR domains for the development of novel efficacious protein drug conjugates targeting the oncofetal protein ROR1 [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 538.

Purpose: Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease with distinct molecular subtypes. The most established subtyping approach, the “Cell of Origin” (COO) algorithm, categorizes DLBCL into activated B-cell (ABC) and germinal center B-cell (GCB)-like subgroups through gene expression profiling. Recently developed immunohistochemical (IHC) techniques and other established methodologies can deliver discordant results and have various technical limitations. We evaluated the NanoString nCounter gene expression system to address issues with current platforms. Experimental Design: We devised a scoring system using 145 genes from published datasets to categorize DLBCL samples. After cell line validation, clinical tissue segmentation was tested using commercially available diagnostic DLBCL samples. Finally, we profiled biopsies from patients with relapsed/refractory DLBCL enrolled in the fostamatinib phase IIb clinical trial using three independent RNA expression platforms: NanoString, Affymetrix, and qNPA. Results: Diagnostic samples showed a typical spread of subtypes with consistent gene expression profiles across matched fresh, frozen, and formalin-fixed paraffin-embedded tissues. Results from biopsy samples across platforms were remarkably consistent, in contrast to published IHC data. Interestingly, COO segmentation of longitudinal fostamatinib biopsies taken at initial diagnosis and then again at primary relapse showed 88% concordance (15/17), suggesting that COO designation remains stable over the course of disease progression. Conclusions: DLBCL segmentation of patient tumor samples is possible using a number of expression platforms. However, we found that NanoString offers the most flexibility and fewest limitations in regards to robust clinical tissue subtype characterization. These subtype distinctions should help guide disease prognosis and treatment options within DLBCL clinical practice. Clin Cancer Res; 21(10); 2367–78. ©2014 AACR. See related commentary by Rimsza, p. 2204

Background Identification of synthetic lethal interactions in cancer cells could offer promising new therapeutic targets. Large-scale functional genomic screening presents an opportunity to test large numbers of cancer synthetic lethal hypotheses. Methods enriching for candidate synthetic lethal targets in molecularly defined cancer cell lines can steer effective design of screening efforts. Loss of one partner of a synthetic lethal gene pair creates a dependency on the other, thus synthetic lethal gene pairs should never show simultaneous loss-of-function. We have developed a computational approach to mine large multi-omic cancer data sets and identify gene pairs with mutually exclusive loss-of-function. Since loss-of-function may not always be genetic, we look for deleterious mutations, gene deletion and/or loss of mRNA expression by bimodality defined with a novel algorithm BiSEp. Results Applying this toolkit to both tumour cell line and patient data, we achieve statistically significant enrichment for experimentally validated tumour suppressor genes and synthetic lethal gene pairings. Notably non-reliance on genetic loss reveals a number of known synthetic lethal relationships otherwise missed, resulting in marked improvement over genetic-only predictions. We go on to establish biological rationale surrounding a number of novel candidate synthetic lethal gene pairs with demonstrated dependencies in published cancer cell line shRNA screens. Conclusions This work introduces a multi-omic approach to define gene loss-of-function, and enrich for candidate synthetic lethal gene pairs in cell lines testable through functional screens. In doing so, we offer an additional resource to generate new cancer drug target and combination hypotheses. Algorithms discussed are freely available in the BiSEp CRAN package at http://cran.r-project.org/web/packages/BiSEp/index.html. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2375-1) contains supplementary material, which is available to authorized users.

Refractory/relapsed diffuse large B-cell lymphoma (DLBCL) has a poor prognosis. Novel drugs targeting the constitutively activated NF-κB pathway characteristic of ABC-DLBCL are promising, but evaluation depends on accurate activated B cell-like (ABC)/germinal center B cell-like (GCB) molecular classification. This is traditionally performed on gene microarray expression profiles of fresh biopsies, which are not routinely collected, or by immunohistochemistry on formalin-fixed, paraffin-embedded (FFPE) tissue, which lacks reproducibility and classification accuracy. We explored the possibility of using routine archival FFPE tissue for gene microarray applications. We examined Affymetrix HG U133 Plus 2.0 gene expression profiles from paired archival FFPE and fresh-frozen tissues of 40 ABC/GCB-classified DLBCL cases to compare classification accuracy and test the potential for this approach to aid the discovery of therapeutic targets and disease classifiers in DLBCL. Unsupervised hierarchical clustering of unselected present probe sets distinguished ABC/GCB in FFPE with remarkable accuracy, and a Bayesian classifier correctly assigned 32 of 36 cases with >90% probability. Enrichment for NF-κB genes was appropriately seen in ABC-DLBCL FFPE tissues. The top discriminatory genes expressed in FFPE separated cases with high statistical significance and contained novel biology with potential therapeutic insights, warranting further investigation. These results support a growing understanding that archival FFPE tissues can be used in microarray experiments aimed at molecular classification, prognostic biomarker discovery, and molecular exploration of rare diseases.

Over the past decade, protein ubiquitination has emerged as an important post-translational modification with regulatory functions in all important cellular processes. Deubiquitinating enzymes (DUBs) including ubiquitin specific proteases (USPs) are cysteine proteases that catalyse the de-ubiquitination of protein substrates. As a result of their increasing implications in the etiology of numerous pathological conditions including cancer and immuno-oncology, DUBs have emerged as an attractive and promising target class for the development of first-in-class medicines with high therapeutic impact. However, despite 15 years of intense research DUBs have proven largely refractory to drug discovery efforts. Herein, we further describe the application of UbiPlex™, our purpose-built drug discovery platform for the identification and development of DUB inhibitors. In particular, we will highlight the versatility and robustness of UbiPlex™ by reporting the outcome of our focussed library screening campaign on multiple DUBs in parallel and by describing the de novo hit ID, orthogonal validation and hit optimization activities on two USPs of relevance to cancer. Multiple series of novel, highly potent (e.g. IC50 < 20 nM) and non-covalent inhibitors have been developed. Excellent selectivity profiles against a large panel of DUBs and other non-related enzymes (e.g. proteases) will be described. Further profiling indicated that these inhibitors are cell-permeable and exhibit potent target engagement in cells (e.g. EC50 < 30 nM). Finally, we will describe our progress towards the development of lead molecules with drug-like properties with the aim of rapidly establishing proof-of-concept studies in vivo. In summary, this work further exemplifies the broad tractability and druggability of the DUBome and reports the discovery and profiling of novel highly potent and selective inhibitors beyond USP7. These molecules may provide opportunities for the development of new therapeutics for cancer and associated disorders. Citation Format: Gerald Gavory, Colin O'Dowd, Oliver Barker, Christina Bell, Frank Burkamp, Stephanie Burton, Eamon Cassidy, Joana Costa, Anthony Dossang, Matt Helm, Ashling Henderson, Peter Hewitt, Caroline Hughes, Mary McFarland, Hugues Miel, Natalie Page, Lauren Proctor, Shane Rountree, Ewelina Rozycka, Steven Shepherd, Adam Treder, Mark Wappett, Steven Whitehead, Tim Harrison. Accessing the cancer DUBome with UbiPlex: A bespoke drug discovery platform for deubiquitinase enzymes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1935.

Pre-clinical models of tumour biology often rely on propagating human tumour cells in a mouse. In order to gain insight into the alignment of these models to human disease segments or investigate the effects of different therapeutics, approaches such as PCR or array based expression profiling are often employed despite suffering from biased transcript coverage, and a requirement for specialist experimental protocols to separate tumour and host signals. Here, we describe a computational strategy to profile transcript expression in both the tumour and host compartments of pre-clinical xenograft models from the same RNA sample using RNA-Seq. Key to this strategy is a species-specific mapping approach that removes the need for manipulation of the RNA population, customised sequencing protocols, or prior knowledge of the species component ratio. The method demonstrates comparable performance to species-specific RT-qPCR and a standard microarray platform, and allowed us to quantify gene expression changes in both the tumour and host tissue following treatment with cediranib, a potent vascular endothelial growth factor receptor tyrosine kinase inhibitor, including the reduction of multiple murine transcripts associated with endothelium or vessels, and an increase in genes associated with the inflammatory response in response to cediranib. In the human compartment, we observed a robust induction of hypoxia genes and a reduction in cell cycle associated transcripts. In conclusion, the study establishes that RNA-Seq can be applied to pre-clinical models to gain deeper understanding of model characteristics and compound mechanism of action, and to identify both tumour and host biomarkers.

To the editor: In a recent issue of Blood , Quentin et al[1][1] reported on genomic abnormalities in Fanconi anemia (FA)–associated leukemic transformation. They confirmed 3q gains as an FA-characteristic chromosomal aberration and discussed the potential role of EVI1 . Complementing this