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Multivalent second-generation TRAIL-R2 agonists are currently in late preclinical development and early clinical trials. Herein, we use a representative second-generation agent, MEDI3039, to address two major clinical challenges facing these agents: lack of predictive biomarkers to enable patient selection and emergence of resistance. Genome-wide CRISPR knockout screens were notable for the lack of resistance mechanisms beyond the canonical TRAIL-R2 pathway (caspase-8, FADD, BID) as well as p53 and BAX in TP53 wild-type models, whereas a CRISPR activatory screen identified cell death inhibitors MCL-1 and BCL-XL as mechanisms to suppress MEDI3039-induced cell death. High-throughput drug screening failed to identify genomic alterations associated with response to MEDI3039; however, transcriptomics analysis revealed striking association between MEDI3039 sensitivity and expression of core components of the extrinsic apoptotic pathway, most notably its main apoptotic effector caspase-8 in solid tumor cell lines. Further analyses of colorectal cell lines and patient-derived xenografts identified caspase-8 expression ratio to its endogenous regulator FLIP(L) as predictive of sensitivity to MEDI3039 in several major solid tumor types and a further subset indicated by caspase-8:MCL-1 ratio. Subsequent MEDI3039 combination screening of TRAIL-R2, caspase-8, FADD, and BID knockout models with 60 compounds with varying mechanisms of action identified two inhibitor of apoptosis proteins (IAP) that exhibited strong synergy with MEDI3039 that could reverse resistance only in BID-deleted models. In summary, we identify the ratios of caspase-8:FLIP(L) and caspase-8:MCL-1 as potential predictive biomarkers for second-generation TRAIL-R2 agonists and loss of key effectors such as FADD and caspase-8 as likely drivers of clinical resistance in solid tumors.

Supplementary Figure from Functional Genomic Identification of Predictors of Sensitivity and Mechanisms of Resistance to Multivalent Second-Generation TRAIL-R2 Agonists

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

Supplemental Figure 3. COO correlations across platforms

Supplemental Table 2. Identification of BCL2 translocation events

Supplemental Figure 4. Comparison of NanoString codeset with Scott et al

Supplemental Figure 2. COO designations across cell lines

Supplemental Table Legends and Supplemental Figure Legends

Supplemental Figure 1A: Variability due to number of FOV captured. A total of 287 genes were ranked on expression level and grouped as LOW, MEDIUM or HIGH expression for each FOV category. The Standard Deviation (SD) is calculated from mean of 3 fresh clinical DLBCL samples. A sample was determined below LOD if one or both technical replicates were Not-Detected. Data was normalised against 33 housekeeping genes. Supplemental Figure 1B: Reduction in raw counts observed after re-scanning the same cartridge at 280 FOV for a total number of 10 times. The mean % reduction in raw counts of the top positive control spike of 5 independent samples (4 FFPE prostate and UHR) is illustrated. The CodeSet size used was 516 genes including 9 housekeeping genes. Supplemental Figure 1C: Variability due to Cartridge Lane and Analyser Station Slot Position; A human Reference RNA sample was replicated across the 12 lanes of the same cartridge. The cartridge was read at 25 FOV in each of the 6 slots in the Analyser Station. The normalised log2 expression values of a HIGH (mean = 18.1{plus minus}0.14) and a LOW abundance gene (mean = 10.1{plus minus}0.40) are illustrated from a CodeSet consisting of 48 housekeeping genes. Data was normalised against 2 randomly selected housekeeping genes. Supplemental Figure 1D: Correlation scatter plot of normalised log2 counts of representative gastric FFPE sample replicated at 100ng on nCounter GEN1 and GEN2 Prep Stations. Only genes above the LOD are shown from a CodeSet consisting of 506 genes including 8 housekeeping genes.

Correlation scatter plot of a representative lung cell line (NCI-H520) showing correlation of 118 overlapping genes in non-identical Codesets. An unusual outlier is marked with a circle. Data was normalised against 8 housekeeping genes.

Summary of standard deviation calculations based on human Reference RNA sample replicates (R) tested independently on two Prep Stations (S1 and S2). The standard deviation calculations (based on log2 data) are measured as the difference for each gene between each sample replicate (4 replicates on S1 and 3 replicates on S2). The average for each variable is calculated and represented in bold to enable assessment of a trend.

Supplemental Figure 4A: Mean FOV and Mean % endogenous gene raw count between the first test (month 0) and the last test (month 9) shown to illustrate effect of storage of a cartridge at 4ºC over a nine month period. Mean raw counts were determined from 2 DLBCL cell line samples HBL-1 and SU-DHL-10 (n=6 each) with a CodeSet consisting of 320 genes including 33 housekeeping genes. Supplemental Figure 4B: Correlation scatter plot of Mean normalised log2 counts between the first test (month 0) and the last test (month 9) (C) shown to illustrate effect of storage of a cartridge at 4ºC over a nine month period. Mean normalised log2 values were determined from 2 DLBCL cell line samples HBL-1 and SU-DHL-10 (n=6 each) with a CodeSet consisting of 320 genes including 33 housekeeping genes.

Heatmap showing unsupervised hierarchical clustering of matching clinical DLBCL Fresh, Frozen and FFPE tissues with a CodeSet consisting of 320 genes including 33 housekeeping genes. Genes below the LOD were omitted from the analysis.

Supplemental Figure 5A: Correlation scatter plot of normalised log2 values illustrating stability of a CodeSet after expiry date. A CodeSet consisting of 30 genes including 4 housekeeping genes was tested with a set of 6 identical samples (5 Fresh DLBCL tissues and 1 DLBCL cell line HBL-1) over an extended time-period of 2.5 years; the second test was performed 1.5 years after the CodeSet expiry date. Supplemental Figure 5B: Correlation scatter plot of mean normalised log2 counts of triplicate UHR samples tested with a CodeSet consisting of 463 genes including 18 housekeeping genes subjected to 4 freeze/thaw cycles.

Cancer cachexia is a metabolic wasting syndrome characterized by weight loss, anorexia and anemia as a result of tumor burden, and affects up to 80% of advanced cancer patients #1. Cachexia is particularly prevalent in pancreatic, lung, colorectal and gastro-intestinal cancers and can lead to reduced tolerance and responsiveness to chemotherapy, increased treatment-related toxicity and morbidity, and poor overall quality of life. There are currently no approved therapies for cancer cachexia. The development and maintenance of muscle tissue is dependent on the balance between protein synthesis and protein degradation, controlled through various anabolic and catabolic signaling pathways. Dysregulation of these pathways can result in muscle atrophy, which arises in many chronic illnesses. The ubiquitin proteasome system (UPS) has a central role in regulating skeletal muscle physiology. Previous work utilizing USP19 knock out mouse models has demonstrated that USP19 plays an important role in muscle wasting and can protect against denervation-induced muscle atrophy #2. We have previously demonstrated that inhibition of USP19 enzymatic activity spares the muscle wasting observed in limb-casted and denervated mouse models of muscle wasting. Here, we report the discovery of a novel, highly potent and selective inhibitor of USP19 (ADC-846) and demonstrate its utility in a cancer-induced muscle atrophy model in vivo. Pharmacological inhibition of USP19 by ADC-846 increased lean muscle and fat mass following oral dosing in a Lewis Lung Carcinoma-induced cachexia model and reduced the cachexic index by >60% compared to controls. This data, in combination with our previous work detailing the effect of USP19 inhibition on muscle force and function, provides a much-needed novel pharmacological strategy for therapeutic intervention in muscle wasting conditions. Citation Format: Natalie Page, Vignesh Karthikaisamy, Darren O'Hara, Aaron N. Cranston, Colin R. O'Dowd, Xavier Jacq, Richard Wilkinson, Stephanie Burton, Hayley Gibson, Joana Costa, Daniel Longley, Matthew Helm, Chris McGivern, Steven Shepherd, Christina Bell, Peter Hewitt, Mary McFarland, Hugues Miel, Steven Whitehead, Lauren Proctor, Shane J. Rountree, Mark Wappett, Mauricio Berriel Diaz, Stephan Herzig, Timothy Harrison. A novel first-in-class USP19 inhibitor for the treatment of cancer-induced muscle atrophy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 2 (Clinical Trials and Late-Breaking Research); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(8_Suppl):Abstract nr LB022.

The placental alkaline phosphatases, ALPP and ALPPL2, are glycosylphosphatidylinositol (GPI)-anchored cell-surface proteins that are expressed in the placenta during fetal development but have very little expression on normal adult tissue. These proteins are over-expressed in a number of different solid tumor indications including ovarian, endometrial, gastric, pancreatic and non-small cell lung cancers. As a result of the highly restricted normal tissue expression and over-expression in cancer, ALPP and ALPPL2 are attractive targets for antibody and protein-drug conjugate (ADC and PDC) approaches. The recent initiation of a Phase I clinical trial utilizing a full-length antibody ADC has fueled further interest in these oncology targets. Small protein domain binders, which have the capacity to penetrate deeper into solid tumors and can be engineered into multiple therapeutic formats in a modular fashion, offer a number of potential benefits over full-length antibodies as the targeting vehicle in PDC therapeutics. We report the identification and characterization of a series of high affinity ALPP/ALPPL2 specific single domain VHH binders which, importantly, show no binding to the closely related ALPI or ALPL isoforms (which have high normal tissue expression). Through application of the Almac Discovery PDC technology platform, these VHH domains have been reformatted into a suite of homogenous site-specifically labelled drug conjugates, with defined drug to antibody ratios, in high yields. These conjugates, which are based on mono- and bi-paratopic Fc fusion formats, employ both clinically established and novel linker-toxin combinations. In pre-clinical studies, the lead bi-paratopic PDCs were well tolerated in vivo and showed excellent anti-tumor efficacy in ALPP/ALPPL2 positive cell-line derived xenograft models of gastric and pancreatic carcinoma, with sustained regressions still observed 10 weeks after administration of the final dose of agent. These agents have physicochemical and pharmaceutical properties suitable for further development and we anticipate that the excellent pre-clinical efficacy profile of lead PDCs will translate to a highly differentiated product for the treatment of a variety of solid tumor indications. Citation Format: Graham Cotton, Paul Trumper, Estelle McLean, Mark Wappett, Stacey Bell, Greg Papadakos, Jennifer Thom, Chiara Saladino, Aaron Cranston, Georgiana Parau, Stephanie Gatdula, Stephanie Burton, Aidan McCann, Tim Harrison. Development of novel protein drug conjugates (PDCs) for the selective targeting of ALPP/ALPPL2 expressing tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 2 (Clinical Trials and Late-Breaking Research); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(8_Suppl):Abstract nr LB011.

p53 is the most frequently mutated, well-studied tumor-suppressor gene, yet the molecular basis of the switch from p53-induced cell-cycle arrest to apoptosis remains poorly understood. Using a combination of transcriptomics and functional genomics, we unexpectedly identified a nodal role for the caspase-8 paralog and only human pseudo-caspase, FLIP(L), in regulating this switch. Moreover, we identify FLIP(L) as a direct p53 transcriptional target gene that is rapidly up-regulated in response to Nutlin-3A, an MDM2 inhibitor that potently activates p53. Genetically or pharmacologically inhibiting expression of FLIP(L) using siRNA or entinostat (a clinically relevant class-I HDAC inhibitor) efficiently promoted apoptosis in colorectal cancer cells in response to Nutlin-3A, which otherwise predominantly induced cell-cycle arrest. Enhanced apoptosis was also observed when entinostat was combined with clinically relevant, p53-activating chemotherapy in vitro, and this translated into enhanced in vivo efficacy. Mechanistically, FLIP(L) inhibited p53-induced apoptosis by blocking activation of caspase-8 by the TRAIL-R2/DR5 death receptor; notably, this activation was not dependent on receptor engagement by its ligand, TRAIL. In the absence of caspase-8, another of its paralogs, caspase-10 (also transcriptionally up-regulated by p53), induced apoptosis in Nutlin-3A-treated, FLIP(L)-depleted cells, albeit to a lesser extent than in caspase-8-proficient cells. FLIP(L) depletion also modulated transcription of canonical p53 target genes, suppressing p53-induced expression of the cell-cycle regulator p21 and enhancing p53-induced up-regulation of proapoptotic PUMA. Thus, even in the absence of caspase-8/10, FLIP(L) silencing promoted p53-induced apoptosis by enhancing PUMA expression. Thus, we report unexpected, therapeutically relevant roles for FLIP(L) in determining cell fate following p53 activation.

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.

Multivalent second-generation TRAIL-R2 agonists are currently in late preclinical development and early clinical trials. Herein, we use a representative second-generation agent, MEDI3039, to address two major clinical challenges facing these agents: lack of predictive biomarkers to enable patient selection and emergence of resistance. Genome-wide CRISPR knockout screens were notable for the lack of resistance mechanisms beyond the canonical TRAIL-R2 pathway (caspase-8, FADD, BID) as well as p53 and BAX in TP53 wild-type models, whereas a CRISPR activatory screen identified cell death inhibitors MCL-1 and BCL-XL as mechanisms to suppress MEDI3039-induced cell death. High-throughput drug screening failed to identify genomic alterations associated with response to MEDI3039; however, transcriptomics analysis revealed striking association between MEDI3039 sensitivity and expression of core components of the extrinsic apoptotic pathway, most notably its main apoptotic effector caspase-8 in solid tumor cell lines. Further analyses of colorectal cell lines and patient-derived xenografts identified caspase-8 expression ratio to its endogenous regulator FLIP(L) as predictive of sensitivity to MEDI3039 in several major solid tumor types and a further subset indicated by caspase-8:MCL-1 ratio. Subsequent MEDI3039 combination screening of TRAIL-R2, caspase-8, FADD, and BID knockout models with 60 compounds with varying mechanisms of action identified two inhibitor of apoptosis proteins (IAP) that exhibited strong synergy with MEDI3039 that could reverse resistance only in BID-deleted models. In summary, we identify the ratios of caspase-8:FLIP(L) and caspase-8:MCL-1 as potential predictive biomarkers for second-generation TRAIL-R2 agonists and loss of key effectors such as FADD and caspase-8 as likely drivers of clinical resistance in solid tumors.

Achilles’ heel relationships arise when the status of one gene exposes a cell's vulnerability to perturbation of a second gene, such as chemical inhibition, providing therapeutic opportunities for precision oncology. SynLeGG (www.overton-lab.uk/synlegg) identifies and visualizes mutually exclusive loss signatures in ‘omics data to enable discovery of genetic dependency relationships (GDRs) across 783 cancer cell lines and 30 tissues. While there is significant focus on genetic approaches, transcriptome data has advantages for investigation of GDRs and remains relatively underexplored. SynLeGG depends upon the MultiSEp algorithm for unsupervised assignment of cell lines into gene expression clusters, which provide the basis for analysis of CRISPR scores and mutational status in order to propose candidate GDRs. Benchmarking against SynLethDB demonstrates favourable performance for MultiSEp against competing approaches, finding significantly higher area under the Receiver Operator Characteristic curve and between 2.8-fold to 8.5-fold greater coverage. In addition to pan-cancer analysis, SynLeGG offers investigation of tissue-specific GDRs and recovers established relationships, including synthetic lethality for SMARCA2 with SMARCA4. Proteomics, Gene Ontology, protein-protein interactions and paralogue information are provided to assist interpretation and candidate drug target prioritization. SynLeGG predictions are significantly enriched in dependencies validated by a recently published CRISPR screen., Graphical Abstract Graphical AbstractSynLeGG utilizes MultiSEp gene expression clusters to partition CRISPR essentiality scores (top) and mutations from whole exome sequencing (bottom), in order to predict candidate genetic dependency relationships, including synthetic lethality.

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.

The tumor microenvironment is emerging as a key regulator of cancer growth and progression, however the exact mechanisms of interaction with the tumor are poorly understood. Whilst the majority of genomic profiling efforts thus far have focused on the tumor, here we investigate RNA-Seq as a hypothesis-free tool to generate independent tumor and stromal biomarkers, and explore tumor-stroma interactions by exploiting the human-murine compartment specificity of patient-derived xenografts (PDX).Across a pan-cancer cohort of 79 PDX models, we determine that mouse stroma can be separated into distinct clusters, each corresponding to a specific stromal cell type. This implies heterogeneous recruitment of mouse stroma to the xenograft independent of tumor type. We then generate cross-species expression networks to recapitulate a known association between tumor epithelial cells and fibroblast activation, and propose a potentially novel relationship between two hypoxia-associated genes, human MIF and mouse Ddx6. Assessment of disease subtype also reveals MMP12 as a putative stromal marker of triple-negative breast cancer. Finally, we establish that our ability to dissect recruited stroma from trans-differentiated tumor cells is crucial to identifying stem-like poor-prognosis signatures in the tumor compartment.In conclusion, RNA-Seq is a powerful, cost-effective solution to global analysis of human tumor and mouse stroma simultaneously, providing new insights into mouse stromal heterogeneity and compartment-specific disease markers that are otherwise overlooked by alternative technologies. The study represents the first comprehensive analysis of its kind across multiple PDX models, and supports adoption of the approach in pre-clinical drug efficacy studies, and compartment-specific biomarker discovery.

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.

Background: How p53 differentially activates cell cycle arrest versus cell death remains poorly understood. Understanding the mechanisms governing the switch from p53-induced cell-fates is important for optimising efficacy of p53-activating therapies, such as DNA damaging chemotherapy and radiotherapy. HDAC inhibitors (HDACi) have potential to enhance p53 induced cell death through enhancing p53 activation and altering regulation of other cell death regulatory proteins. Methods: We utilised a panel of matched p53 wild-type and deficient colorectal cancer cell line models to the potential for HDACi to augment cell death induced by direct and indirect p53 activating agents. A number of molecular (Western blot, RT-PCR), phenotypic (cell death) and functional genomic (RNA-seq, CRISPR, ChIP-seq) analyses were used to investigate the importance of p53 and its downstream transcriptional programs. Results: Here we report that upregulation of canonical pro-apoptotic p53 target genes in colon cancer cells imposes critical dependence on the long splice form of the caspase-8 regulator FLIP (FLIP(L)), which we identify as a direct p53 transcriptional target. Inhibiting FLIP(L) expression with siRNA or Class-I HDAC inhibitors promotes apoptosis in response to p53 activation by the MDM2 inhibitor Nutlin-3A, which otherwise predominantly induces cell-cycle arrest. When FLIP(L) upregulation is inhibited, apoptosis is induced in response to p53 activation via a ligand-independent TRAIL-R2/caspase-8 complex, which is distinct from the ligand-dependent DISC. Notably, FLIP(L) depletion inhibits p53-induced expression of the cell cycle regulator p21 and enhances p53-mediated upregulation of PUMA, with the latter activating mitochondrial-mediated apoptosis in FLIP(L)-depleted, Nutlin-3A-treated cells lacking TRAIL-R2/caspase-8. Conclusion: Acute p53-mediated transcriptional upregulation of FLIP(L) plays an unexpected nodal role in determining cell fate following p53 activation. This is mediated through two previously undescribed mechanisms, preventing apoptosis by a ligand-independent TRAIL-R2 complex and by suppressing expression of pro-apoptotic PUMA. Which, importantly imposes a critical dependence on FLIP(L) which can be overcome through combinations with class-I HDAC inhibitors such as Entinostat. Citation Format: Andrea Lees, Alexander J. McIntyre J. McIntyre, Nyree T. Crawford, Fiammetta Falcone, Chris McCann, Gerard P. Quinn, Jamie Z. Roberts, Thomas Sessler, Peter F. Gallagher, Gemma M. Gregg, Katherine McAllister, Kirsty M. McLaughlin, Wendy L. Allen, Caitriona Holohan, Laurence J. Egan, Aideen E. Ryan, Melissa Labonte-Wilson, Phillip D. Dunne, Mark Wappett, Vicky M. Coye, Patrick G. Johnston, Emma M. Kerr, Daniel B. Longley, Simon S. McDade. FLIP(L) determines colon cancer cell fate following p53 activation [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 2409.

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

Whilst antibody drug conjugates (ADCs) have been successfully used to target highly potent cytotoxic agents to tumours, there is a continued emphasis on developing technologies for improving the therapeutic effectiveness of this class of agents. The vast majority of ADCs that have entered the clinic have been based on large intact immunoglobulins, however, there is significant interest in exploiting small protein domains as the payload delivery vehicle. These offer a number of potential benefits over full length antibodies including increased tumour penetration, amenability to protein engineering and site-specific conjugation, and improved tolerability. To this end, we have developed a therapeutics platform based on shark Variable New Antigen Receptor (VNAR) proteins. Shark VNAR domains are the smallest naturally occurring antigen binding domain (~11 kDa), with a binding mechanism distinct from traditional antibodies. Here we report the application of this platform to the development of homogenous VNAR-drug conjugates targeting the onco-embryonic receptor tyrosine kinase ROR1. ROR1 expression has been observed across a broad range of solid tumours and haematological malignancies, and is reported to correlate with poor clinical outcome for a number of cancer indications, but is largely absent from normal adult tissue. As such, the expression pattern of ROR1, coupled with its functional role in tumourogenesis and disease progression, make it an attractive PDC target. Using a combination of direct immunisation and synthetic VNAR library screening, we have generated high affinity binders to the extracellular domain of ROR1 which show species cross-reactivity, do not bind the closely related family member ROR2, and can target distinct non-overlapping regions of the protein. By exploiting the ability of VNAR domains to be flexibly reformatted, the lead sequences have been configured as a series of bivalent Fc fusions, VNAR multimers and novel bi-paratopic binders, and constructs identified that show further enhanced binding to ROR1 and which can induce internalisation and lysosomal trafficking in ROR1 expressing cancer cell-lines. Subsequent attachment of highly potent DNA-damaging cytotoxic payloads yielded homogenous VNAR-drug conjugates which demonstrated extremely potent (sub-nanomolar) in vitro cytotoxicity against selected cancer cell-lines in a receptor mediated fashion. Studies to assess the in vivo efficacy of these conjugates are in progress. These ROR1 VNAR constructs have also been successfully fused to sdAbs and scFv directed to other cell-surface protein targets, demonstrating the power of the platform and opening the way for novel bi-specific approaches for targeting both solid and haematological tumours. Citation Format: Graham Cotton, Jennifer Thom, Paul Trumper, Stacey Bell, Andrei Kamenski, Mark Wappett, Caroline Barelle, Marina Kovaleva, John Steven, Andy Porter, Estelle McLean, Chiara Saladino, Aidan McCann, Aaron Cranston, Tim Harrison. Novel protein drug conjugates targeting ROR1 through the development and exploitation of a drug discovery platform based on small, engineered VNAR domains [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 222.

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) catalyse the de-ubiquitination of protein substrates, hence regulating their levels and/or function. As a result of their increasing implications in the aetiology of numerous pathological conditions including cancer, neurodegeneration and metabolic disorders, DUBs represent an attractive and promising target class for the development of innovative medicines with high therapeutic impact. However, despite 15 years of research DUBs have proved largely refractory to drug discovery efforts. As a result of genetic and other validation studies, USP19 has recently emerged as a potentially important target in muscular atrophy associated with various conditions including cancer, as well as in other disorders involving aberrant protein quality control. Herein, we describe the application of our Ubi-Plex™ drug discovery platform to the identification and optimisation of first in class USP19 inhibitors. Several series of novel, highly potent (e.g. IC50 < 5.0 nM) and reversible USP19 inhibitors have been identified. Further profiling has demonstrated excellent selectivity against a large panel of DUBs and other non-related enzymes (e.g. kinases, proteases). These inhibitors are cell-permeable and exhibit potent target engagement in both cancer and muscle cells with EC50 values < 30 nM. We will describe the development of lead molecules with drug-like properties which have allowed us to establish pharmacological target validation by demonstrating efficacy in a muscle wasting model in vivo. Recent developments in the programme leading to orally available USP19 inhibitors will also be presented. This work further exemplifies the tractability of the DUB target family and reports the discovery and detailed profiling of first-in-class inhibitors of USP19. These findings support the rationale to target USP19 for debilitating muscle wasting disorders associated with various conditions such as cancer, as well as for potentially other therapeutic indications, particularly those associated with aberrant protein quality control. Citation Format: Xavier Jacq, Gerald Gavory, Colin O'Dowd, Aaron Cranston, Oliver Baker, Christina Bell, Stephanie Burton, Eamon Cassidy, Joana Costa, Ashling Henderson, Matthew Helm, Peter Hewitt, Caroline Hughes, Mary McFarland, Hugues Miel, Lauren Proctor, Shane Roundtree, Rachel Church, Ewelina Rozycka, Mark Wappett, Steven Whitehead, Tim Harrison, Nathalie Bedard, Simon S. Wing. Discovery and development of first-in-class orally bioavailable USP19 inhibitors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr LB-087.

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