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Background Glioblastoma (GBM) is an aggressive brain cancer that typically results in death in the first 15 months after diagnosis. There have been limited advances in finding new treatments for GBM. In this study, we investigated molecular differences between patients with extremely short (≤ 9 months, Short term survivors, STS) and long survival (≥ 36 months, Long term survivors, LTS). Methods Patients were selected from an in-house cohort (GLIOTRAIN-cohort), using defined inclusion criteria (Karnofsky score > 70; age Results Transcriptomic analysis of tumour samples identified cilium gene signatures as enriched in LTS. Moreover, Immunohistochemical analysis confirmed the presence of cilia in the tumours of LTS. Notably, reverse phase protein array analysis (RPPA) demonstrated increased phosphorylated GAB1 (Y627), SRC (Y527), BCL2 (S70) and RAF (S338) protein expression in STS compared to LTS. Next, we identified 25 unique master regulators (MR) and 13 transcription factors (TFs) belonging to ontologies of integrin signalling and cell cycle to be upregulated in STS. Conclusion Overall, comparison of STS and LTS GBM patients, identifies novel biomarkers and potential actionable therapeutic targets for the management of GBM. Graphical abstract

Supplementary Table 1: Mouse Strains Used to Develop PDX Models. Supplementary Table 2: Collection of PDX Models Available by the EuroPDX Consortium.

Genomics Mimicry for Personalized Cancer Treatment.

Supplementary Figure and Tables Legends.

Purpose:Regorafenib (REG) is approved for the treatment of metastatic colorectal cancer, but has modest survival benefit and associated toxicities. Robust predictive/early response biomarkers to aid patient stratification are outstanding. We have exploited biological pathway analyses in a patient-derived xenograft (PDX) trial to study REG response mechanisms and elucidate putative biomarkers.Experimental Design:Molecularly subtyped PDXs were annotated for REG response. Subtyping was based on gene expression (CMS, consensus molecular subtype) and copy-number alteration (CNA). Baseline tumor vascularization, apoptosis, and proliferation signatures were studied to identify predictive biomarkers within subtypes. Phospho-proteomic analysis was used to identify novel classifiers. Supervised RNA sequencing analysis was performed on PDXs that progressed, or did not progress, following REG treatment.Results:Improved REG response was observed in CMS4, although intra-subtype response was variable. Tumor vascularity did not correlate with outcome. In CMS4 tumors, reduced proliferation and higher sensitivity to apoptosis at baseline correlated with response. Reverse phase protein array (RPPA) analysis revealed 4 phospho-proteomic clusters, one of which was enriched with non-progressor models. A classification decision tree trained on RPPA- and CMS-based assignments discriminated non-progressors from progressors with 92% overall accuracy (97% sensitivity, 67% specificity). Supervised RNA sequencing revealed that higher basal EPHA2 expression is associated with REG resistance.Conclusions:Subtype classification systems represent canonical “termini a quo” (starting points) to support REG biomarker identification, and provide a platform to identify resistance mechanisms and novel contexts of vulnerability. Incorporating functional characterization of biological systems may optimize the biomarker identification process for multitargeted kinase inhibitors.

Patient-derived tumor xenograft (PDX) mouse models have emerged as an important oncology research platform to study tumor evolution, mechanisms of drug response and resistance, and tailoring chemotherapeutic approaches for individual patients. The lack of robust standards for reporting on PDX models has hampered the ability of researchers to find relevant PDX models and associated data. Here we present the PDX models minimal information standard (PDX-MI) for reporting on the generation, quality assurance, and use of PDX models. PDX-MI defines the minimal information for describing the clinical attributes of a patient's tumor, the processes of implantation and passaging of tumors in a host mouse strain, quality assurance methods, and the use of PDX models in cancer research. Adherence to PDX-MI standards will facilitate accurate search results for oncology models and their associated data across distributed repository databases and promote reproducibility in research studies using these models. Cancer Res; 77(21); e62–66. ©2017 AACR.

Supplementary Figures S1 - S8 and Table S1. Fig S1: Analysis of copy number burden in a PDX population trial of REG treated mCRC PDXs. Fig S2: Effect of REG on microvessel density and proliferation according to CNA cluster. Fig S3 - S6: BCL-2 family profiling of mCRC PDX models via quantitative Western blotting. Fig S7: RPPA protein scores indicating proteins' association with the PDX models' response to REG. Fig S8: Western blot validation of differential EPHA2 protein expression between REG post- and pre-treatment progressor and non-progressor PDX models. Table S1: List of antibodies and dilution factors used against desired targets in RPPA analysis.

A figure showing the process of generating and using PDX models.

Suppl Table 2

Suppl Fig. S1

Suppl Material & Suppl. Table S1

Intrinsic and acquired resistance to HER-targeting drugs occurs in a significant proportion of HER2-overexpressing breast cancers. Thus, there remains a need to identify predictive biomarkers that could improve patient selection and circumvent these types of drug resistance. Here, we report the identification of neuromedin U (NmU) as an extracellular biomarker in cells resistant to HER-targeted drugs. NmU overexpression occurred in cells with acquired or innate resistance to lapatinib, trastuzumab, neratinib, and afatinib, all of which displayed a similar trend upon short-term exposure, suggesting NmU induction may be an early response. An analysis of 3,489 cases of breast cancer showed NmU to be associated with poor patient outcome, particularly those with HER2-overexpressing tumors independent of established prognostic indicators. Ectopic overexpression of NmU in drug-sensitive cells conferred resistance to all HER-targeting drugs, whereas RNAi-mediated attenuation sensitized cells exhibiting acquired or innate drug resistance. Mechanistic investigations suggested that NmU acted through HSP27 as partner protein to stabilize HER2 protein levels. We also obtained evidence of functional NmU receptors on HER2-overexpressing cells, with the addition of exogenous NmU eliciting an elevation in HER2 and EGFR expression along with drug resistance. Finally, we found that NmU seemed to function in cell motility, invasion, and anoikis resistance. In vivo studies revealed that NmU attenuation impaired tumor growth and metastasis. Taken together, our results defined NmU as a candidate drug response biomarker for HER2-overexpressing cancers and as a candidate therapeutic target to limit metastatic progression and improve the efficacy of HER-targeted drugs. Cancer Res; 74(14); 3821–33. ©2014 AACR.

The factors driving therapy resistance in diffuse glioma remain poorly understood. To identify treatment-associated cellular and genetic changes, we analyzed RNA and/or DNA sequencing data from the temporally separated tumor pairs of 304 adult patients with isocitrate dehydrogenase (IDH)-wild-type and IDH-mutant glioma. Tumors recurred in distinct manners that were dependent on IDH mutation status and attributable to changes in histological feature composition, somatic alterations, and microenvironment interactions. Hypermutation and acquired CDKN2A deletions were associated with an increase in proliferating neoplastic cells at recurrence in both glioma subtypes, reflecting active tumor growth. IDH-wild-type tumors were more invasive at recurrence, and their neoplastic cells exhibited increased expression of neuronal signaling programs that reflected a possible role for neuronal interactions in promoting glioma progression. Mesenchymal transition was associated with the presence of a myeloid cell state defined by specific ligand-receptor interactions with neoplastic cells. Collectively, these recurrence-associated phenotypes represent potential targets to alter disease progression.

Purpose: Cell-free DNA (cfDNA) analysis in plasma is an emerging technique with numerous applications in oncology. We employed cfDNA to determine chromosomal instability (CIN), nucleosome footprints (NF) and methylation profiles in metastatic colorectal cancer (mCRC) patients and to predict outcome to bevacizumab (BVZ) combination therapy. Experimental Design: Low coverage whole-genome sequencing (LC-WGS) was performed on matched tumor and plasma samples from 74 mCRC patients participating in the CTRIAL-IE 12-16 AC-ANGIOPREDICT Phase II clinical trial (NCT01822444), prior to receiving BVZ, and analyzed for CIN (3 subclusters with low, intermediate and high CIN, respectively) and nucleosomes. For 61/74 mCRC patients, plasma samples before and after BVZ treatment were available and used for targeted methylation sequencing. A validation cohort of mCRC plasma samples (n= 24) from the University Medical Center Mannheim (UMM) was similarly profiled. Results: Based on cfDNA CIN profiles, we subtyped mCRC patients with 92.3% accuracy of sample distinction into low and high CIN clusters (cluster 1 against cluster 2 and 3), demonstrating concordance between matched plasma and tumor samples. Improved survival outcome was observed in CIN high patients. Plasma-based CIN clustering and improved survival for CIN high patients was also confirmed in the UMM cohort. NF and methylation profiles differed between CIN clusters and healthy individuals, and could reliably separate cluster 1 from cluster 2 and 3 samples (AUC=0.72 and 0.85 respectively). A large methylation score decrease after BVZ treatment was associated with improved overall survival (p = 0.013). Conclusions: cfDNA can be analyzed to predict outcome to BVZ in mCRC patients. Detection of CNAs, NFs and methylation profiles facilitated stratification of samples into CIN clusters and informed patient response to treatment. Citation Format: Ian S. Miller, Valentina Thomas, Tom Venken, Ingrid Arijs, Ana Barat, Johannes Betge, Tianzuo Zhan, Timo Gaiser, Matthias P. Ebert, Jochen Prehn, Rut Klinger, Darran P. O’Connor, Brian Brian Moulton, Verena Murphy, Ray McDermott, Brian Bird, Gregory Leonard, Liam Grogan, Anne Horgan, Nadine Schulte, Markus Moehler, Nicole Prannikar, Judith Franz-Werner, Hans-Peter Feustel, Diether Lambrechts, Annette T. Byrne. Analysis of cell free DNA to predict outcome to Bevacizumab combination therapy in metastatic colorectal cancer patients. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5584.

Glioblastoma represents the most common primary malignancy of the central nervous system in adults and remains a largely incurable disease. The elucidation of disease subtypes based on mutational profiling, gene expression and DNA methylation has so far failed to translate into improved clinical outcomes. However, new knowledge emerging from the subtyping effort in the IDH-wild-type setting may provide directions for future precision therapies. Here, we review recent learnings in the field, and further consider how tumour microenvironment differences across subtypes may reveal novel contexts of vulnerability. We discuss recent treatment approaches and ongoing trials in the IDH-wild-type glioblastoma setting, and propose an integrated discovery stratagem incorporating multi-omics, single-cell technologies and computational approaches.

Purpose: Regorafenib (REG) is approved for the treatment of metastatic colorectal cancer, but has modest survival benefit and associated toxicities. Robust predictive/early response biomarkers to aid patient stratification are outstanding. We have exploited biological pathway analyses in a patient-derived xenograft (PDX) trial to study REG response mechanisms and elucidate putative biomarkers. Experimental Design: Molecularly subtyped PDXs were annotated for REG response. Subtyping was based on gene expression (CMS, consensus molecular subtype) and copy-number alteration (CNA). Baseline tumor vascularization, apoptosis, and proliferation signatures were studied to identify predictive biomarkers within subtypes. Phospho-proteomic analysis was used to identify novel classifiers. Supervised RNA sequencing analysis was performed on PDXs that progressed, or did not progress, following REG treatment. Results: Improved REG response was observed in CMS4, although intra-subtype response was variable. Tumor vascularity did not correlate with outcome. In CMS4 tumors, reduced proliferation and higher sensitivity to apoptosis at baseline correlated with response. Reverse phase protein array (RPPA) analysis revealed 4 phospho-proteomic clusters, one of which was enriched with non-progressor models. A classification decision tree trained on RPPA- and CMS-based assignments discriminated non-progressors from progressors with 92% overall accuracy (97% sensitivity, 67% specificity). Supervised RNA sequencing revealed that higher basal EPHA2 expression is associated with REG resistance. Conclusions: Subtype classification systems represent canonical “termini a quo” (starting points) to support REG biomarker identification, and provide a platform to identify resistance mechanisms and novel contexts of vulnerability. Incorporating functional characterization of biological systems may optimize the biomarker identification process for multitargeted kinase inhibitors.

Despite magnetic resonance imaging (MRI) being the gold-standard imaging modality in the glioblastoma (GBM) setting, the availability of rodent MRI scanners is relatively limited. CT is a clinically relevant alternative which is more widely available in the pre-clinic. To study the utility of contrast-enhanced (CE)-CT in GBM xenograft modelling, we optimized CT protocols on two instruments (IVIS-SPECTRUM-CT;TRIUMPH-PET/CT) with/without delivery of contrast. As radiomics analysis may facilitate earlier detection of tumors by CT alone, allowing for deeper analyses of tumor characteristics, we established a radiomic pipeline for extraction and selection of tumor specific CT-derived radiomic features (inc. first order statistics/texture features). U87R-Luc2 GBM cells were implanted orthotopically into NOD/SCID mice (n=25) and tumor growth monitored via weekly BLI. Concurrently mice underwent four rounds of CE-CT (IV iomeprol/iopamidol; 50kV-scan). N=45 CE-CT images were semi-automatically delineated and radiomic features were extracted (Pyradiomics 2.2.0) at each imaging timepoint. Differences between normal and tumor tissue were analyzed using recursive selection. Using either CT instrument/contrast, tumors > 0.4cm3 were not detectable until week-9 post-implantation. Radiomic analysis identified three features (waveletHHH_firstorder_Median, original_glcm_Correlation and waveletLHL_firstorder_Median) at week-3 and -6 which may be early indicators of tumor presence. These features are now being assessed in CE-CT scans collected pre- and post-temozolomide treatment in a syngeneic model of mesenchymal GBM. Nevertheless, BLI is significantly more sensitive than CE-CT (either visually or using radiomic-enhanced CT feature extraction) with luciferase-positive tumors detectable at week-1. In conclusion, U87R-Luc2 tumors > 0.4cm3 are only detectable by Week-8 using CE-CT and either CT instrument studied. Nevertheless, radiomic analysis has defined features which may allow for earlier tumor detection at Week-3, thus expanding the utility of CT in the preclinical setting. Overall, this work supports the discovery of putative prognostic pre-clinical CT-derived radiomic signatures which may ultimately be assessed as early disease markers in patient datasets.

Glioblastoma (GBM) is the most frequent and aggressive adult brain tumor with 85% of patients dying within two years. New effective precision medicine therapies are urgently required, especially for isocitrate dehydrogenase wild-type (IDHwt) disease. Despite efforts to subtype patients based on molecular profiles, this approach has yet failed to direct treatment strategies. Further interrogation of the tumor microenvironment (TME) across molecular subtypes and identification of new TME specific subtypes may guide new directions for future therapies. Here, we analysed transcriptomic data from selected GLIOTRAIN(www.gliotrain.eu)(n=120) and TCGA(n=69) IDHwt patients. Firstly, the microenvironment cell population (MCP)-counter method (a gene-expression-based TME deconvolution tool) was validated for use in the brain tumor setting using quantitative multiplex immunohistochemistry. In this context, immune markers (CD20/CD3/CD68/CD8) were significantly correlated with MCP-counter scores. We are currently optimizing and validating a vessel-density and microglial RNA-signature to provide a more robust representation of brain TME. Next, using MCP-counter, the TME composition of IDHwt tumors was assessed within proneural (24%), classical (38%) and mesenchymal (38%) subtypes. We initially classified the GLIOTRAIN cohort into 3 novel clusters characterised by differences in TME composition and validated our findings in the TCGA cohort. A TME-high group (37%) is characterized by elevated presence of lymphocytes and myeloid cells, and presents a high level of immune checkpoint genes: PDCD1(PD1) and CTLA4. In addition, the presence of tertiary lymphoid structures (TLS) is a feature of TMEhigh/mesenchymal+ patients. This finding has been validated by IHC and RNA-signature. TME-med (38%) displayed heterogenous immune populations and the TME-low (25%) represented an ‘immune-desert’ group. There was no significant difference in OS based on these TME subtypes(p=0.50). We hypothesise that PD1/CTLA4 blockade might be an effective treatment strategy in TME-high patients. These hypotheses will be tested (in the adjuvant setting) using appropriate syngeneic disease models which incorporate surgical resection.

Resistance to chemotherapy often results from dysfunctional apoptosis, however multiple proteins with overlapping functions regulate this pathway. We sought to determine whether an extensively validated, deterministic apoptosis systems model, &lsquo, DR_MOMP&rsquo, could be used as a stratification tool for the apoptosis sensitiser and BCL-2 antagonist, ABT-199 in patient-derived xenograft (PDX) models of colorectal cancer (CRC). Through quantitative profiling of BCL-2 family proteins, we identified two PDX models which were predicted by DR_MOMP to be sufficiently sensitive to 5-fluorouracil (5-FU)-based chemotherapy (CRC0344), or less responsive to chemotherapy but sensitised by ABT-199 (CRC0076). Treatment with ABT-199 significantly improved responses of CRC0076 PDXs to 5-FU-based chemotherapy, but showed no sensitisation in CRC0344 PDXs, as predicted from systems modelling. 18F-Fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG-PET/CT) scans were performed to investigate possible early biomarkers of response. In CRC0076, a significant post-treatment decrease in mean standard uptake value was indeed evident only in the combination treatment group. Radiomic CT feature analysis of pre-treatment images in CRC0076 and CRC0344 PDXs identified features which could phenotypically discriminate between models, but were not predictive of treatment responses. Collectively our data indicate that systems modelling may identify metastatic (m)CRC patients benefitting from ABT-199, and that 18F-FDG-PET could independently support such predictions.

Chemotherapy combined with the angiogenesis inhibitor bevacizumab (BVZ) is approved as a first-line treatment in metastatic colorectal cancer (mCRC). Limited clinical benefit underpins the need for improved understanding of resistance mechanisms and the elucidation of novel predictive biomarkers. We assessed germline single-nucleotide polymorphisms (SNPs) in 180 mCRC patients (Angiopredict [APD] cohort) treated with combined BVZ + chemotherapy and investigated previously reported predictive SNPs. We further employed a machine learning approach to identify novel associations. In the APD cohort IL8 rs4073 any A carriers, compared to TT carriers, were associated with worse progression-free survival (PFS) (HR = 1.51, 95% CI:1.03–2.22, p-value = 0.037) and TBK1 rs7486100 TT carriers, compared to any A carriers, were associated with worse PFS in KRAS wild-type (wt) patients (HR = 1.94, 95% CI:1.04–3.61, p-value = 0.037), replicating previous findings. Machine learning identified novel associations in genes encoding the inflammasome protein NLRP1 and the ER protein Sarcalumenin (SRL). A negative association between PFS and carriers of any A at NLRP1 rs12150220 and AA for SRL rs13334970 in APD KRAS wild-type patients (HR = 4.44, 95% CI:1.23–16.13, p-value = 0.005), which validated in two independent clinical cohorts involving BVZ, MAVERICC and TRIBE. Our findings highlight a key role for inflammation and ER signalling underpinning BVZ + chemotherapy responsiveness.

Glioblastoma (GBM), a highly invasive and vascular malignancy is shown to rapidly develop resistance and evolve to a more invasive phenotype following bevacizumab (Bev) therapy. Rho Guanine Nucleotide Exchange Factor proteins (RhoGEFs) are mediators of key components in Bev resistance pathways, GBM and Bev-induced invasion. To identify GEFs with enhanced mRNA expression in the leading edge of GBM tumours, a cohort of GEFs was assessed using a clinical dataset. The GEF &beta, Pix/COOL-1 was identified, and the functional effect of gene depletion assessed using 3D-boyden chamber, proliferation, and colony formation assays in GBM cells. Anti-angiogenic effects were assessed in endothelial cells using tube formation and wound healing assays. In vivo effects of &beta, Pix/COOL-1-siRNA delivered via RGD-Nanoparticle in combination with Bev was studied in an invasive model of GBM. We found that siRNA-mediated knockdown of &beta, Pix/COOL-1 in vitro decreased cell invasion, proliferation and increased apoptosis in GBM cell lines. Moreover &beta, Pix/COOL-1 mediated endothelial cell migration in vitro. Mice treated with &beta, Pix/COOL-1 siRNA-loaded RGD-Nanoparticle and Bev demonstrated a trend towards improved median survival compared with Bev monotherapy. Our hypothesis generating study suggests that the RhoGEF &beta, Pix/COOL-1 may represent a target of vulnerability in GBM, in particular to improve Bev efficacy.

Patient-derived tumor xenograft (PDX) mouse models have emerged as an important oncology research platform to study tumor evolution, mechanisms of drug response and resistance, and tailoring chemotherapeutic approaches for individual patients. The lack of robust standards for reporting on PDX models has hampered the ability of researchers to find relevant PDX models and associated data. Here we present the PDX models minimal information standard (PDX-MI) for reporting on the generation, quality assurance, and use of PDX models. PDX-MI defines the minimal information for describing the clinical attributes of a patient's tumor, the processes of implantation and passaging of tumors in a host mouse strain, quality assurance methods, and the use of PDX models in cancer research. Adherence to PDX-MI standards will facilitate accurate search results for oncology models and their associated data across distributed repository databases and promote reproducibility in research studies using these models. Cancer Res; 77(21); e62–66. ©2017 AACR.

// Bruce Moran 1, 10, * , Sudipto Das 1, 10, * , Dominiek Smeets 2, 3 , Gillian Peutman 2, 3 , Rut Klinger 1, 10 , Bozena Fender 4 , Kate Connor 1, 5, 10 , Matthias Ebert 6 , Timo Gaiser 6 , Jochen HM Prehn 5 , Orna Bacon 5, 7 , Elaine Kay 7 , Bryan Hennessy 7 , Verena Murphy 8 , Bauke Ylstra 9 , Diether Lambrechts 2, 3 , Annette T. Byrne 5 , William M. Gallagher 4, 10, ** and Darran P. O’Connor 1, 10, ** 1 Department of Molecular and Cellular Therapeutics, Royal College of Surgeons in Ireland, Dublin, Ireland 2 Department of Oncology, Laboratory of Translational Genetics, VIB Center for Cancer Biology, Leuven, Belgium 3 Department of Oncology, Laboratory of Translational Genetics, Department of Oncology, KU Leuven, Leuven, Belgium 4 OncoMark Ltd., NovaUCD, Belfield Innovation Park, Dublin, Ireland 5 Department of Physiology and Medical Physics, Royal College of Surgeons in Ireland, Dublin, Ireland 6 Department of Internal Medicine, University of Heidelberg, Mannheim, Germany 7 Department of Pathology, Beaumont Hospital, Dublin, Ireland 8 Cancer Trials Ireland, Dublin, Ireland 9 Department of Pathology, VU University Medical Center, Amsterdam, The Netherlands 10 Cancer Biology and Therapeutics Laboratory, UCD School of Biomolecular and Biomedical Science, UCD Conway Institute, University College, Dublin, Ireland * These authors have contributed equally to this work ** Senior co-authors Correspondence to: Darran P. O’Connor, email: darranoconnor@rcsi.ie Keywords: targeted bisulfite sequencing, methylation, epigenetics, FFPE, tumor preservation Received: July 20, 2016 Accepted: April 03, 2017 Published: May 30, 2017 ABSTRACT DNA methylation is altered in many types of disease, including metastatic colorectal cancer. However, the methylome has not yet been fully described in archival formalin-fixed paraffin embedded (FFPE) samples in the context of matched fresh-frozen (FF) tumor material at base-pair resolution using a targeted approach. Using next-generation sequencing, we investigated three pairs of matched FFPE and FF samples to determine the extent of their similarity. We identified a ‘bowing’ pattern specific to FFPE samples categorized by a lower CG proportion at the start of sequence reads. We have found no evidence that this affected methylation calling, nor concordance of results. We also found no significant increase in deamination, measured by C>T transitions, previously considered a result of crosslinking DNA by formalin fixation and a barrier to the use of FFPE in methylation studies. The methods used in this study have shown sensitivity of between 60-70% based on positions also methylated in colorectal cancer cell lines. We demonstrate that FFPE material is a useful source of tumor material for methylation studies using targeted sequencing.

Background: Combining bevacizumab and chemotherapy produced superior response rates compared with chemotherapy alone in metastatic breast cancer. As bevacizumab may cause hypertension (HTN) and increase the risk of cardiac failure, we performed a pilot study to evaluate the feasibility and toxicity of a non-anthracycline-containing combination of docetaxel with cyclophosphamide and bevacizumab in early stage breast cancer patients. Methods: Treatment consisted of four 3-weekly cycles of docetaxel and cyclophosphamide (75/600 mg/m2). Bevacizumab was administered 15 mg/kg intravenously on day 1, and then every 3 weeks to a total of 18 cycles of treatment. Serum biomarker concentrations of vascular endothelial growth factor (VEGF), cardiac troponin-I (cTnI), myeloperoxidase (MPO), and placental growth factor (PlGF) were quantified using enzyme-linked immunosorbent assay (ELISA) in 62 patients at baseline and whilst on treatment to determine their utility as biomarkers of cardiotoxicity, indicated by left ventricular ejection fraction (LVEF). Results: A total of 106 patients were accrued in nine sites. Median follow up was 65 months (1–72 months). Seventeen protocol-defined relapse events were observed, accounting for an overall disease-free survival (DFS) rate of 84%. The DFS rates for hormone receptor positive (HR+) and triple-negative (TN) patients were 95% versus 43%, respectively. The median time to relapse was 25 (12–54) months in TN patients versus 38 (22–71) months in HR+ patients. There have been 13 deaths related to breast cancer . The overall survival (OS) rate was 88%. The 5-year OS rate in HR+ versus TN was 95% versus 57%. None of the measured biomarkers predicted the development of cardiotoxicity. Conclusions: We observed a low relapse rate in node-positive, HR+ patients; however, results in TN breast cancer were less encouraging. Given the negative results of three large phase III trials, it is unlikely that this approach will be investigated further. Trial Registration ClinicalTrials.gov Identifier: NCT00911716.

Heme sensor Nuclear Receptor Subfamily 1 Group D Member 1 (NR1D1/REVERBA) and its target gene Aryl Hydrocarbon Receptor Nuclear Translocator-Like (ARNTL/BMAL1) regulate circadian rhythm and angiogenesis. Given their involvement in the interplay between clock disruptions (e.g. by mutations or sleep deprival), cancer risk and vascular biology, we hypothesized that these transcription factors contribute to resistance against anti-angiogenic therapy with vascular endothelial growth factor (VEGFA) neutralizing antibody (bevacizumab, abbrev. Beva) in colorectal cancer (CRC). REVERBA bound to a predicted -672 bp Retinoic Acid Receptor-Related Orphan Receptor Alpha (RORA)-responsive element (RORE) adjacent to a BMAL1 DNA-binding motif (E-box) in the proximal promoter of the human VEGFA gene. REVERBA, indirectly and together with BMAL1, increased VEGFA mRNA and protein expression. Conversely, REVERBA siRNA and REVERBA-antagonist hemin decreased VEGFA synthesis. Beva treatment inhibited CRC growth in a C57BL/6J Apc min/+ genetically modified mouse model (GEMM) and BALB/c nu/nu mouse HCT116 xenografts, without attenuating BMAL1 levels or microvessel density (MVD). In CRC patient tumors (n=74), high BMAL1 protein expression was associated with clinical non-response to combination chemotherapy with Beva (*p=0.0061) and reduced progression-free survival (PFS) [*p=0.0223, Hazard Ratio (HR)=1.69]. In addition, single nucleotide polymorphisms (SNPs) in the BMAL1 (ARNTL) gene correlated with shorter overall survival (OS) [rs11022780, *p=0.014, HR=1.61] and PFS (rs7396943, rs7938307, rs2279287) in patients undergoing combination chemotherapy with Beva. Thus, BMAL1 is associated with Beva resistance in CRC. Since the REVERBA-BMAL1-VEGFA axis can be pharmacologically targeted, interference with this signaling pathway could circumvent resistance to anti-angiogenic therapy in CRC. Funding Statement: This study was supported by grants to EB from the Deutsche Krebshilfe (#108287 and #111086). FE received a fellowship from the “Studienstiftung des deutschen Volkes”. JB was supported by the Translational Physician Scientist (TraPS) Program of the Medical Faculty Mannheim of the Heidelberg University. WW was awarded a fellowship from the Chinese Scholarship Council (#201408080116). ME was supported by the State of Baden-Wurttemberg for “Center of Geriatric Biology and Oncology (ZOBEL) – Perspektivforderung” and “Biology of Frailty - Sonderlinie Medizin”. ATB and ME received funds from the European Commission Seventh Framework Programme (Contract No. 278981 [ANGIOPREDICT]) and are supported by the European Commission Horizon 2020 Programme (Contract No. 754923 [COLOSSUS]). ATB is further supported by Science Foundation Ireland under grant 13/CDA/2183 ”Coloforetell”. HJL was partly funded by the National Cancer Institute (grant number P30CA014089), the Gloria Borges WunderGlo Foundation -The Wunder Project, the Dhont Family Foundation, the San Pedro Peninsula Cancer Guild, the Daniel Butler Research Fund, and the Call to Cure Research Fund Declaration of Interests: The authors declare no conflicts of interest. The reagent mBeva was obtained on the basis of a material transfer agreement (MTA#10082012) from Roche Diagnostics GmbH (Penzberg, Germany). HJL has received clinical trial financial support from Merck Serono and Roche and honoraria for advisory board membership and lectures from Bayer, Boehringer Ingelheim, Genentech, Merck Serono and Roche Ethics Approval Statement: Xenograft studies conformed to the 2010/63/EU guidelines and were approved by the Dept. of Health and Children, Dublin, Ireland (B100/3654) and University College Dublin Animal Research Ethics Committee (P12-27). Therapy studies were conducted in accordance with ethical guidelines (Declaration of Helsinki) and approved by the local ethics committees for each participating site. All patients provided written informed consent for the analysis of molecular correlates.

Angiogenesis is a key tumor microenvironment (TME) event underpinning tumor growth and metastasis. Nevertheless, the relatively poor performance of anti-angiogenic therapies in clinical trials compared to pre-clinical studies implies that classical subcutaneous xenograft models have limited predictive potential in this setting. To address this issue, we established orthotopic surgical resection models of breast cancer, which replicate the phenotype of clinical post-resection micro-metastasis. To demonstrate the power and precision of these models, we recapitulated the BETH adjuvant trial (NCT00625898) where the addition of bevacizumab (BVZ) to chemotherapy plus trastuzumab (Trast) failed to provide additional benefit. SCID mice were orthotopically implanted with bioluminescent Her2+ MDA-MB-231 or HCC1954 cells and tumors resected c.5 weeks later. Following resection, mice were treated with 10 mg/kg Trast +5 mg/kg paclitaxel (PAC) IP once weekly for 6 cycles +/− weekly BVZ (5 mg/kg IP). Metastasis was monitored by imaging. Using these models our data confirms that the addition of the anti-angiogenic antibody BVZ to adjuvant Trast + chemotherapy provides no additional benefit compared with Trast + chemotherapy alone. Previous studies using non-resection subcutaneously engrafted xenografts failed to predict this outcome. Our results provide compelling evidence for the utility of cell line xenograft resection models to predict clinical outcome for TME targeting agents.

Item does not contain fulltext PURPOSE: The tyrosine kinase inhibitor (TKI) sunitinib is a multi-targeted agent approved across multiple cancer indications. Nevertheless, since approval, data has emerged to describe a worrisome side effect profile including hypertension, hand-foot syndrome, fatigue, diarrhea, mucositis, proteinuria, and (rarely) congestive heart failure. It has been hypothesized that the observed multi-parameter toxicity profile is related to "on-target" kinase inhibition in "off-target" tissues. EXPERIMENTAL DESIGN: To interrogate off-target effects in pre-clinical studies, a reverse phase protein array (RPPA) approach is employed. Mice are treated with sunitinib (40 mg kg(-1) ) for 4 weeks, following which critical organs are removed. The Zeptosens RPPA platform is employed for protein expression analysis. RESULTS: Differentially expressed proteins associated with damage and/or stress are found in the majority of organs from treated animals. Proteins differentially expressed in the heart are associated with myocardial hypertrophy, ischaemia/reperfusion, and hypoxia. However, hypertrophy is not evidenced on histology. Mild proteinuria is observed; however, no changes in renal glomerular structure are visible via electron microscopy. In skin, proteins associated with cutaneous inflammation, keratinocyte hyper-proliferation, and increased inflammatory response are differentially expressed. CONCLUSIONS AND CLINICAL RELEVANCE: It is posited that pre-clinical implementation of a combined histopathological/RPPA approach provides a sensitive method to mechanistically elucidate the early manifestation of TKI on-target/organ off-target toxicities.

Patient-derived xenografts (PDXs) are resected human tumors engrafted into mice for preclinical studies and therapeutic testing. It has been proposed that the mouse host affects tumor evolution during PDX engraftment and propagation, affecting the accuracy of PDX modeling of human cancer. Here, we exhaustively analyze copy number alterations (CNAs) in 1,451 PDX and matched patient tumor (PT) samples from 509 PDX models. CNA inferences based on DNA sequencing and microarray data displayed substantially higher resolution and dynamic range than gene expression-based inferences, and they also showed strong CNA conservation from PTs through late-passage PDXs. CNA recurrence analysis of 130 colorectal and breast PT/PDX-early/PDX-late trios confirmed high-resolution CNA retention. We observed no significant enrichment of cancer-related genes in PDX-specific CNAs across models. Moreover, CNA differences between patient and PDX tumors were comparable to variations in multiregion samples within patients. Our study demonstrates the lack of systematic copy number evolution driven by the PDX mouse host.

Deregulation of the ubiquitin-proteasome pathway has been frequently observed in a number of malignancies. Using quantitative Western blotting of normal and matched tumour tissue, we here identified a significant increase in the 19S proteasome subunit Rpt4 in response to chemoradiation in locally advanced rectal cancer patients with unfavourable outcome. We therefore explored the potential of Rpt4 reduction as a therapeutic strategy in colorectal cancer (CRC). Utilizing siRNA to down regulate Rpt4 expression, we show that silencing of Rpt4 reduced proteasomal activity and induced endoplasmic reticulum stress. Gene silencing of Rpt4 also inhibited cell proliferation, reduced clonogenic survival and induced apoptosis in HCT-116 colon cancer cells. We next developed a cell penetrating peptide-based nanoparticle delivery system to achieve in vivo gene silencing of Rpt4. Administration of Rpt4 siRNA nanoparticles reduced tumour growth and improved survival in a HCT-116 colon cancer xenograft tumour model in vivo. Collectively, our data suggest that inhibition of Rpt4 represents a novel strategy for the treatment of CRC.

GBM is a devastating disease with peak incidence in the seventh decade. Pre-clinical models are essential for studying resistance mechanisms and screening novel therapies. However, historically these models have failed to predict response in humans. Current models seldom incorporate surgical resection, and commonly use young animals whose immune contexture differs from older patients. Here, we have established an orthotopic model employing the syngeneic mesenchymal-NFpp10a-cell line which incorporates surgical resection in aged mice. We further characterise response to ICI and temozolomide monotherapy. NFpp10a and GL261-cell lines were exposed in vitro to irradiation (0Gy/2Gy/5Gy) and response assessed using colony formation assays. NFpp10a formed significantly more colonies at 5Gy compared to GL261 at both day 10 (NFpp10a 5.167 vs GL261 1.4; p=0.0017) and day 14 (NFpp10a 3.5 vs GL261 0; p< 0.0001). Hence, NFpp10a displays increased radioresistance. Next, NFpp10a-luciferin expressing cells were orthotopically implanted into young (6-8weeks;n=16) and aged (18months;n=16) C57BL/6-mice. Weekly bioluminescence imaging (BLI) was performed to monitor growth. Mice undergoing resection showed a median 18.47-fold drop in BLI signal. We demonstrated resection survival advantage in aged mice (Resection:33.5 days vs Non-Resection:18 days, p= 0.0166) and showed young age to be a positive prognostic factor (Young:62 days vs Aged:22 days, p=0.0002). Subsequently, we orthotopically implanted NFpp10a-Luc2 cells into C57BL/6 mice and treated with temozolomide (n=24) or PBS control (n=23), and anti-PD1 (n=24) or IgG (n=23). We observed that temozolomide and anti-PD1 monotherapy had no impact on NFpp10-Luc2 growth (temozolomide-overall:p=0.9001, anti-PD1-overall:p=0.7933) or survival (temozolomide-overall:p=0.3035, anti-PD1-overall:p=0.6328). Overall, we have established an NFpp10-Luc2 mesenchymal-GBM model in aged mice which incorporates surgical resection and accurately displays significant resistance to temozolomide and anti-PD1 monotherapy. We are currently employing this model to study the efficacy of neoadjuvant anti-PD1 therapy. Mechanistic analyses with multiplex-immunohistochemistry, scRNA and whole exome sequencing are planned to interrogate treatment effects on the tumor microenvironment.

Patient-derived xenografts (PDXs) are resected human tumors engrafted into mice for preclinical studies and therapeutic testing. It has been proposed that the mouse host affects tumor evolution during PDX engraftment and propagation, which could impact the capacity of PDXs for faithful modeling of patient treatment response. Such results contrast with reports that have observed genomic fidelity of PDX models with respect to the originating patient tumors and from early to late passages by direct DNA measurements (DNA sequencing or SNP arrays). Here we resolve these contradicting observations by systematically evaluating CNA changes and the genes they affect during engraftment and passaging in a large, internationally collected set of PDX models, comparing both RNA and DNA-based approaches. The data collected, as part of the U.S. National Cancer Institute (NCI) PDXNet (PDX Development and Trial Centers Research Network) Consortium and EurOPDX consortium, comprises 1548 patient (PT) and PDX datasets (1451 unique samples) from 509 models derived from American, European and Asian cancer patients, spanning across 16 tumor types. By assessing copy number changes by pairwise (PT-PDX or PDX-PDX) correlation and residual analysis to control for systematic biases, our study demonstrates that prior reports of systematic copy number divergence between PTs and PDXs are incorrect, and confirms the high retention of copy number during PDX engraftment and passaging. Moreover, only a small proportion of models show large CNA discordance between the samples, suggesting that the variations observed in PDX are mainly due to rare clonal selection of individual tumors rather than murine pressures. This large scale data analysis also reveals several other findings that clarify the evolutionary process in PDXs. We do observe larger deviations between PT-PDX than in PDX-PDX comparisons, likely due to dilution of PT signal by human stromal cells. Interestingly, we found that a major contributor to the differences between PDX samples is lineage-specific drift associated with splitting of tumors into fragments during PDX propagation. We observed no significant enrichment of cancer-related genes in PDX-specific CNAs across models, suggesting the lack of systematic copy number evolution driven by the PDX mouse host. Moreover, CNA differences between patient and PDX tumors were comparable to variations in multi-region tumor samples or intra-patient samples. Thus concerns about the genetic stability of the PDX system are likely to be less important than the spatial heterogeneity of solid tumors themselves. This result is consistent with our results on lineage effects during passaging, which indicate that intratumoral spatial evolution is the major reason for genetic drift. Our in-depth tracking of CNAs throughout PDX engraftment and passaging confirms that tumors engrafted and passaged in PDX models maintain a high degree of molecular fidelity to the original patient tumors and their suitability for pre-clinical drug testing. This work also finely enumerates the copy number profiles in hundreds of publicly available models, which will enable researchers to assess the suitability of each for individualized treatment studies. Citation Format: Xing Yi Woo, Jessica Giordano, Anuj Srivastava, Zi-Ming Zhao, Michael W. Lloyd, Roebi de Bruijn, Yun-Suhk Suh, Jong-Il Kim, Han-Kwang Yang, Charles Lee, Dennis A. Dean, Brandi Davis-Dusenbery, Yvonne A. Evrard, James H. Doroshow, Alana L. Welm, Bryan Welm, Michael T. Lewis, Bingliang Fang, Jack A. Roth, Funda Meric-Bernstam, Meenhard Herlyn, Michael Davies, Li Ding, Shunqiang Li, Ramaswamy Govindan, Claudio Isella, Jeffrey A. Moscow, Livio Trusolino, Annette Byrne, Jos Jonkers, Carol J. Bult, Enzo Medico, Jeffrey H. Chuang, PDXNET consortium & EurOPDX consortium. Conservation of copy number profiles during engraftment and passaging of patient-derived cancer xenografts [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 1673.

Patient-Derived Xenografts (PDXs) are preclinical models largely used to study tumor biology and drug response. Recent literature highlighted the possibility that growth of human tumors in a mouse microenvironment imposes a selection driving mouse-specific genetic evolution of PDXs, which may compromise their reliability as human cancer models. Conversely, independent studies observed a conservation of the genomic landscape during PDX engraftment and passaging. We noticed that PDX genetic evolution was particularly evident in studies based on copy number aberration (CNA) inferred from gene expression data, while it was negligible when DNA-based CNA profiles were employed. Therefore, in a joint international effort of the EurOPDX and PDXNet consortia, we assembled a dataset of 37 hepatocellular and 54 gastric carcinoma tumor or PDX samples with matched RNA-based and DNA-based CNA profiles. We found that DNA-based CNA profiles invariably yield higher concordance between patient's tumor and derived PDXs than those inferred from RNA. RNA-based profiles displayed poor concordance with matched DNA-based profiles, and much lower resolution, so that they missed many focal copy number events detected by DNA-based methods. These results revealed that CNA measurements cannot be accurately estimated by expression data and that a systematic reassessment of CNA dynamics in PDXs based on DNA data is required. To this aim, we generated CNA profiles by low-pass whole genome sequencing (WGS) of 87 colorectal and 43 breast cancer triplets, each composed of matched patient's tumor (PT) and PDX at early (PDX-early) and later (PDX-late) passage. In this way, for each tumor type, we generated three perfectly matched PT, PDX-early and PDX-late cohorts and performed CNA recurrence analysis by GISTIC in each cohort. The hypothesis was that if the mouse host induces a selective pressure capable of shaping the CNA landscape during PDX engraftment and propagation, GISTIC analysis would highlight systematic and progressive changes, from the PT to the PDX-early cohort, and then to the PDX-late cohort. Notably instead, the CNA profiles of the PT and PDX-early/late cohorts were virtually indistinguishable, with no progressive accumulation or loss of CNA during PDX passage and only minor changes not functionally related or associated to cancer-driver or actionable genes. These results were not consequence of insufficient capture of the CNA repertoire, since the GISTIC profiles recapitulated those generated by TCGA for colorectal and breast cancer. In summary, our analyses highlighted that while RNA-based CNA inferences have inadequate resolution and accuracy to study genomic evolution in PDXs, DNA-based CNA profiles confirm retention of CNAs in PTs and PDXs, excluding a systematic mouse driven selection via copy number changes. Ultimately, these results support the robustness of PDXs as preclinical models for predicting drug response. Citation Format: Jessica Giordano, Xing Yi Woo, Anuj Srivastava, Zi-Ming Zhao, Michael W. Lloyd, Roebi de Bruijn, Yun-Suhk Suh, Francesco Galimi, Andrea Bertotti, Adam Lafferty, Alice C. O'Farrell, Elodie Modave, Diether Lambrechts, Petra ter Brugge, Violeta Serra, Elisabetta Marangoni, Rania El Botty, Jong-Il Kim, Han-Kwang Yang, Charles Lee, Dennis A. Dean, Brandi Davis-Dusenbery, Yvonne A. Evrard, James H. Doroshow, Alana L. Welm, Bryan E. Welm, Michael T. Lewis, Bingliang Fang, Jack Roth, Funda Meric-Bernstam, Meenhard Herlyn, Michael Davies, Li Ding, Shunqiang Li, Ramaswamy Govindan, Jeffrey A. Moscow, Carol J. Bult, Claudio Isella, Livio Trusolino, Annette T. Byrne, Jos Jonkers, Jeffrey H. Chuang, Enzo Medico, EurOPDX consortium & PDXNET consortium. Absence of mouse-specific tumor evolution in patient-derived cancer xenografts [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 1118.

Counteracting high failure rates in oncology drug development and improving therapeutic management of cancer patients requires preclinical models that can account for the complexity and heterogeneity of human tumors. Patient-derived cancer xenografts (PDXs) maintain histopathological features and genetic profiles of the original patient tumors and are increasingly recognized as reliable models to predict treatment efficacy and discover sensitivity and resistance biomarkers with immediate clinical relevance.Launched in 2013, the EurOPDX Consortium now gathers 18 academic research institutions throughout Europe and in the US (www.europdx.eu). The goal of the Consortium is to maximize exploitation of PDXs and other patient-derived models for cancer research by: (i) integrating institutional collections into a multicentre repository; (ii) defining common standards to improve the quality and reproducibility of oncology preclinical data; (iii) sharing models within and outside the consortium to perform collaborative precision oncology “xenopatient” trials. Building on its first successes, EurOPDX is now teaming up with other key academic and SME partners in a four-year project to build the “EurOPDX Distributed Infrastructure for Research on patient-derived Xenografts" (EDIReX project, Horizon 2020 grant no. 731105).This new cutting-edge European infrastructure offers access to PDX resources for academic and industrial cancer researchers through 6 state-of-the-art installations or “nodes”. We will present the specific objectives of the project, including our work towards standardization and optimization of biobanking, quality control and data tracking, and the performance of in vivo drug efficacy experiments. Access to the resource, including the distribution of cryopreserved samples from established models, the structured biobanking of user-developed models and the performance of drug efficacy studies, is offered through a grant application system which last deadline is planned mid-June 2020. Selection of the models by users and browsing of PDXs annotation data is made possible thanks to the newly-developed EurOPDX Data Portal (dataportal.europdx.eu), which will display approximately 1,000 models by April 2020 (including 700+ models of colorectal cancer, 80+ gastric and 80+ breast cancer models).We aim to improve preclinical and translational cancer research and promote innovation in oncology by integrating a European PDX repository and facilitating access to this much-needed resource for European and worldwide researchers. Citation Format: Emilie Vinolo, Joaquin Arribas, Andrea Bertotti, Alejandra Bruna, Annette T. Byrne, Robert B. Clarke, Nathalie Conte, Steven de Jong, Didier Decaudin, Zdenka Dudova, Jos Jonkers, Daniela Krasser, Ales Krenek, Luisa Lanfrancone, Eleonora Leucci, Elisabetta Marangoni, Gunhild Mari Maelandsmo, Michaela Th. Mayrhofer, Terrence F. Meehan, Jens Henrik Norum, Hector G. Palmer, Alejandro Piris Gimenez, Leo Price, Sergio Roman-Roman, Francesca Sarno, Violeta Serra, Laura Soucek, Livio Trusolino, Marieke van de Ven, Luca Vezzadini, Alberto Villanueva, Andrea Wutte, Enzo Medico, on behalf of the EurOPDX Research Infrastructure. The EurOPDX Research Infrastructure: Supporting European and worldwide cancer research with patient-derived xenografts [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 1685.

Glioblastoma (GBM), a highly invasive brain malignancy, remains an incurable disease. Angiogenesis, the formation of new vasculature, is a defining feature of this disease. Targeting GBM angiogenesis with Bevacizumab (Bev) is associated with improved progression free survival, but may also enhance tumour invasion into the surrounding parenchyma (Norden et al., 2008) and is not curative. Rho GTPases and their activators, guanine nucleotide exchange factors (GEFs), play central roles in the invasive process (4). Herein, we sought to identify and target GEFs of importance in mediating GBM invasion with a view to improving Bev response. We report a novel mechanism by which GBM tumours invade and proliferate via overexpression of the GEF beta-PIX gene which was shown to be increased at the invasive edge in 74% of GBM tumours assessed (n=19), compared with tumour core (Hoelzinger et al., 2005). We have further demonstrated that siRNA-mediated knockdown of beta-PIX in GBM patient-derived xenograft cell cultures and cell lines resulted in decreased cell invasion in 3D, cell proliferation and survival assays in vitro. An in vivo pilot study whereby beta-Pix knockdown was achieved using commercially available alphaV-beta3 integrin targeting nanoparticles (InVivoPlex Aparna Bio Corp), suggested that treatment with beta-PIX siRNA nanoparticles in combination with Bev could improve survival compared with Bev- alone in tumour-bearing animals. To further develop this strategy, we have recently designed and characterized a proprietary novel biodegradable, RGD-targeting and cholesterol-stabilized polyplex system for siRNA delivery in GBM. This novel nanoparticle system supports efficient gene silencing, and demonstrates a low toxicity profile in vitro and in vivo. We are currently performing advanced pre-clinical efficacy studies employing a clinically relevant GBM rodent resection model (Sweeney et al., 2014), to determine if nanoparticle mediated beta-PIX gene silencing will improve survival outcomes when combined with Bevacizumb and delivered in the adjuvant setting.