Jana Rolff

Establishment of Patient-Derived Non–Small Cell Lung Cancer Xenografts as Models for the Identification of Predictive Biomarkers

Purpose: It was the aim of our study to establish an extensive panel of non-small cell lung cancer (NSCLC) xenograft models useful for the testing of novel compounds and for the identification of biomarkers. Experimental Design: Starting from 102 surgical NSCLC specimens, which were obtained from primarily diagnosed patients with early-stage tumors (T2/T3), 25 transplantable xenografts were established and used for further investigations. Results: Early passages of the NSCLC xenografts revealed a high degree of similarity with the original clinical tumor sample with regard to histology, immunohistochemistry, as well as mutation status. The chemotherapeutic responsiveness of the xenografts resembled the clinical situation in NSCLC with tumor shrinkage obtained with paclitaxel (4 of 25), gemcitabine (3 of 25), and carboplatin (3 of 25) and lower effectiveness of etoposide (1 of 25) and vinorelbine (0 of 11). Twelve of 25 NSCLC xenografts were >50% growth inhibited by the anti-epidermal growth factor receptor (EGFR) antibody cetuximab and 6 of 25 by the EGFR tyrosine kinase inhibitor erlotinib. The response to the anti-EGFR therapies did not correlate with mutations in the EGFR or p53, but there was a correlation of K-ras mutations and erlotinib resistance. Protein analysis revealed a heterogeneous pattern of expression. After treatment with cetuximab, we observed a down-regulation of EGFR in 2 of 6 sensitive xenograft models investigated but never in resistant models. Conclusion: An extensive panel of patient-derived NSCLC xenografts has been established. It provides appropriate models for testing marketed as well as novel drug candidates. Additional expression studies allow the identification of stratification biomarkers for targeted therapies.

Radiosensitisation of U87MG brain tumours by anti-epidermal growth factor receptor monoclonal antibodies.

As epidermal growth factor receptor (EGFR) has been reported to be a radiation response modulator, HER inhibitors are regarded to act as potential radiosensitisers. Our study examined the role of nimotuzumab and cetuximab both, the two monoclonal antibodies (mAbs) to EGFR, as radiosensitisers in a murine glioma model in vivo. Co-administration of both the antibodies with radiation increased the radiosensitivity of U87MG, resulting in a significant delay of subcutaneous (s.c.) tumour growth. Furthermore, the addition of antibodies to the radiation decreased brain tumour sizes and is inhibited by 40–80% the increased tumour cell invasion provoked by radiotherapy, although promoted tumour cell apoptosis. Whereas nimotuzumab led to a reduction in the size of tumour blood vessels and proliferating cells in s.c. tumours, cetuximab had no significant antiangiogenic nor antiproliferative activity. In contrast, cetuximab induced a more marked inhibition of EGFR downstream signalling compared with nimotuzumab. Moreover, both antibodies reduced the total number of radioresistant CD133+ cancer stem cells (CSCs). These results were encouraging, and showed the superiority of combined treatment of mAbs to EGFR and radiation over each single therapy against glioblastoma multiforme (GBM), confirming the role of these drugs as radiosensitisers in human GBM. In addition, we first showed the ability of mAb specifics against EGFR to target radioresistant glioma CSC, supporting the potential use in patients.

Patient-derived xenografts of non-small-cell lung cancer: a pre-clinical model to evaluate adjuvant chemotherapy? §

OBJECTIVE Recent trials have evaluated adjuvant chemotherapy in patients with non-small-cell lung cancer (NSCLC). For stage IB to IIIA, a significant improvement of treatment results for platin-based chemotherapy was shown, but only one of the 20 patients treated has a benefit of disease-free and overall 5-year survival. In future the implementation of biomarkers, novel agents and individual selection may contribute to better treatment results in adjuvant therapy. Pre-clinical models are one way to study treatment innovations. MATERIALS AND METHODS We have developed a lung cancer xenograft model. Fresh tumour material of patients with NSCLC was subcutaneously transplanted to immunodeficient mice shortly after surgical resection. In total, 102 samples have been transplanted from which 25 passagable models could be generated. Of the established xenograft lines, 48% were derived from squamous cell carcinomas and 24% from adenocarcinomas. All but one originated from long-term smokers. RESULTS It could be shown that the early murine passages (maximum 10) were similar to the original tumour with regard to histology and the expression of the surface proteins as E-cadherin, EpCAM or the cell proliferation marker Ki-67. The growth rate of the established xenografts was a unique feature of the different models and not related to patient characteristics or to the histology type. All xenograft models showed a wide variability in response to both classical chemotherapy and targeted anti-epidermal growth factor receptor agents. Response rates were in good accordance with the results of recent clinical studies. DISCUSSION In summary, we have developed a panel of patient-derived NSCLC xenografts. These xenograft models could be used for pre-clinical studies to evaluate chemotherapy, novel targeted therapies and expression of potential biomarkers.

Comparative Profiling of the Novel Epothilone, Sagopilone, in Xenografts Derived from Primary Non–Small Cell Lung Cancer

Purpose: Characterization of new anticancer drugs in a few xenograft models derived from established human cancer cell lines frequently results in the discrepancy between preclinical and clinical results. To take the heterogeneity of tumors into consideration more thoroughly, we describe here a preclinical approach that may allow a more rational clinical development of new anticancer drugs. Experimental Design: We tested Sagopilone, an optimized fully synthetic epothilone, in 22 well-characterized patient-derived non–small cell lung cancer models and correlated results with mutational and genome-wide gene expression analysis. Results: Response analysis according to clinical trial criteria revealed that Sagopilone induced overall responses in 64% of the xenograft models (14 of 22), with 3 models showing stable disease and 11 models showing partial response. A comparison with response rates for established drugs showed the strong efficacy of Sagopilone in non–small cell lung cancer. In gene expression analyses, Sagopilone induced tubulin isoforms in all tumor samples, but genes related to mitotic arrest only in responder models. Moreover, tumors with high expression of genes involved in cell adhesion/angiogenesis as well as of wild-type TP53 were more likely to be resistant to Sagopilone therapy. As suggested by these findings, Sagopilone was combined with Bevacizumab and Sorafenib, drugs targeting vascular endothelial growth factor signaling, in Sagopilone-resistant models and, indeed, antitumor activity could be restored. Conclusion: Analyses provided here show how preclinical studies can provide hypotheses for the identification of patients who more likely will benefit from new drugs as well as a rationale for combination therapies to be tested in clinical trials. Clin Cancer Res; 16(5); 1452–65

Chemoresistance in non-small-cell lung cancer: can multidrug resistance markers predict the response of xenograft lung cancer models to chemotherapy?

OBJECTIVE In chemotherapy for non-small-cell lung cancer (NSCLC), some patients seem to exhibit an intrinsic resistance or develop an acquired resistance under treatment. Results on resistance markers for possible treatment failure as shown in studies on selected lung cancer cell lines could not be completely confirmed in clinical trials. As these conflicting data require further research, we created a model between cell culture and the clinical need to study this problem. METHODS Our study was based on patient-derived NSCLC xenografts in a mouse model, which revealed a high coincidence with the original tumour. Protein and messenger RNA (mRNA) expression of known resistance markers (breast cancer resistance protein (BCRP), multidrug resistance P-glycoprotein (MDR), lung cancer-related protein (LRP) and multidrug resistance protein 1 (MRP1)) were analysed by real-time polymerase chain reaction (PCR) and immunoblotting in 24 xenografts. Chemosensitivity to etoposide, carboplatin, gemcitabine, paclitaxel, cetuximab and erlotinib was determined in in vivo xenograft experiments and compared with the protein and mRNA expression of the multidrug resistance markers. RESULTS With the exception of a single correlation between chemosensitivity and mRNA expression of etoposide and bcrp (mRNA expression of BCRP), we found no significant correlation between the response rates and protein- and mRNA expression levels in our 24 xenografts. The present results indicate that in vivo expression levels of multidrug resistance proteins and their mRNAs may not play a comparable role in chemoresistance of NSCLC, as pointed out in selected tumour cell lines. CONCLUSIONS Patient-derived xenografts allow detailed investigation of therapy-related markers and their dynamic regulation in a well-standardised and clinically related way. As a consequence of our investigations, we regard multidrug resistance to be a multifactorial phenomenon, in which more factors than the markers analysed by the present study may be involved.

Response of Patient-Derived Non-Small Cell Lung Cancer Xenografts to Classical and Targeted Therapies Is Not Related to Multidrug Resistance Markers

Tumor cells that are nonsensitive to anticancer drugs frequently have a multidrug resistant (MDR) phenotype. Many studies with cell lines and patient material have been done to investigate the impact of different resistance markers at protein and mRNA level in drug resistance but with contradictory outcome. In the present study, 26 well-characterised patient-derived non-small cell lung cancer xenografts were used. The known chemosensitivity to etoposide, carboplatin, gemcitabine, paclitaxel and erlotinib was compared to the protein and mRNA expression of BCRP, LRP, MDR1, and MRP1. Further, four of these xenografts were short-term treated to analyse possible regulation mechanisms after therapeutic interventions. We found a borderline correlation between the bcrp mRNA expression and the response of xenografts to etoposide. All other constitutive mRNA and protein expression levels were not correlated to any drug response and were not significantly influenced by a short term treatment. The present results indicate that the expression levels of MDR proteins and mRNA investigated do not play an important role in the chemoresistance of NSCLC in the in vivo situation.

QSEA – modelling of genome-wide DNA methylation from sequencing enrichment experiments

Abstract Genome-wide enrichment of methylated DNA followed by sequencing (MeDIP-seq) offers a reasonable compromise between experimental costs and genomic coverage. However, the computational analysis of these experiments is complex, and quantification of the enrichment signals in terms of absolute levels of methylation requires specific transformation. In this work, we present QSEA, Quantitative Sequence Enrichment Analysis, a comprehensive workflow for the modelling and subsequent quantification of MeDIP-seq data. As the central part of the workflow we have developed a Bayesian statistical model that transforms the enrichment read counts to absolute levels of methylation and, thus, enhances interpretability and facilitates comparison with other methylation assays. We suggest several calibration strategies for the critical parameters of the model, either using additional data or fairly general assumptions. By comparing the results with bisulfite sequencing (BS) validation data, we show the improvement of QSEA over existing methods. Additionally, we generated a clinically relevant benchmark data set consisting of methylation enrichment experiments (MeDIP-seq), BS-based validation experiments (Methyl-seq) as well as gene expression experiments (RNA-seq) derived from non-small cell lung cancer patients, and show that the workflow retrieves well-known lung tumour methylation markers that are causative for gene expression changes, demonstrating the applicability of QSEA for clinical studies. QSEA is implemented in R and available from the Bioconductor repository 3.4 (www.bioconductor.org/packages/qsea).

Activation of AMP-activated protein kinase sensitizes lung cancer cells and H1299 xenografts to erlotinib

OBJECTIVES The therapeutic scheme for non-small cell lung cancer (NSCLC) patients can be improved if adapted to the individual response. For example, 60-70% of adenocarcinoma patients show response to EGFR-tyrosine kinase inhibitors in the presence of mutated EGFR. We searched for additional target molecules involved in the action of the EGFR-tyrosine kinase inhibitor erlotinib in the absence of EGFR mutations, which might be suitable for combinatorial therapy approaches. MATERIALS AND METHODS Erlotinib-response associated proteins were investigated in patient-derived NSCLC mouse xenografts by reverse-phase protein array technology (RPPA) and Western blotting. A combinatorial treatment approach was carried out in NSCLC cell lines and H1299 mouse xenografts, and subsequently analyzed for consequences in cell growth and signal transduction. RESULTS AMP-activated protein kinase (AMPK) expression was increased in erlotinib responders before and after treatment. In a combinatorial approach, activation of AMPK by A-769662 and erlotinib treatment showed a synergistic effect in cell growth reduction and apoptosis activation in H1299 cells compared to the single drugs. AMPK pathway analyses revealed an effective inhibition of mTOR signaling by drug combination. In H1299 xenografts, the tumor size was significantly decreased after combinatorial treatment. CONCLUSION Our results suggest that AMPK activation status affects response to erlotinib in distinct lung tumor models.

Predictive In Vivo Models for Oncology

Experimental oncology research and preclinical drug development both substantially require specific, clinically relevant in vitro and in vivo tumor models. The increasing knowledge about the heterogeneity of cancer requested a substantial restructuring of the test systems for the different stages of development. To be able to cope with the complexity of the disease, larger panels of patient-derived tumor models have to be implemented and extensively characterized. Together with individual genetically engineered tumor models and supported by core functions for expression profiling and data analysis, an integrated discovery process has been generated for predictive and personalized drug development.Improved “humanized” mouse models should help to overcome current limitations given by xenogeneic barrier between humans and mice. Establishment of a functional human immune system and a corresponding human microenvironment in laboratory animals will strongly support further research.Drug discovery, systems biology, and translational research are moving closer together to address all the new hallmarks of cancer, increase the success rate of drug development, and increase the predictive value of preclinical models.

Epigenomic profiling of non-small cell lung cancer xenografts uncover LRP12 DNA methylation as predictive biomarker for carboplatin resistance

BackgroundNon-small cell lung cancer (NSCLC) is the most common cause of cancer-related deaths worldwide and is primarily treated with radiation, surgery, and platinum-based drugs like cisplatin and carboplatin. The major challenge in the treatment of NSCLC patients is intrinsic or acquired resistance to chemotherapy. Molecular markers predicting the outcome of the patients are urgently needed.MethodsHere, we employed patient-derived xenografts (PDXs) to detect predictive methylation biomarkers for platin-based therapies. We used MeDIP-Seq to generate genome-wide DNA methylation profiles of 22 PDXs, their parental primary NSCLC, and their corresponding normal tissues and complemented the data with gene expression analyses of the same tissues. Candidate biomarkers were validated with quantitative methylation-specific PCRs (qMSP) in an independent cohort.ResultsComprehensive analyses revealed that differential methylation patterns are highly similar, enriched in PDXs and lung tumor-specific when comparing differences in methylation between PDXs versus primary NSCLC. We identified a set of 40 candidate regions with methylation correlated to carboplatin response and corresponding inverse gene expression pattern even before therapy. This analysis led to the identification of a promoter CpG island methylation of LDL receptor-related protein 12 (LRP12) associated with increased resistance to carboplatin. Validation in an independent patient cohort (n = 35) confirmed that LRP12 methylation status is predictive for therapeutic response of NSCLC patients to platin therapy with a sensitivity of 80% and a specificity of 84% (p < 0.01). Similarly, we find a shorter survival time for patients with LRP12 hypermethylation in the TCGA data set for NSCLC (lung adenocarcinoma).ConclusionsUsing an epigenome-wide sequencing approach, we find differential methylation patterns from primary lung cancer and PDX-derived cancers to be very similar, albeit with a lower degree of differential methylation in primary tumors. We identify LRP12 DNA methylation as a powerful predictive marker for carboplatin resistance. These findings outline a platform for the identification of epigenetic therapy resistance biomarkers based on PDX NSCLC models.