Grant Funds Research on Pazopanib (Votrient) Response in Sarcoma

Pazopanib (Votrient)

April 28, 2015: The Liddy Shriver Sarcoma Initiative is pleased to announce the funding of a $50,000 grant for sarcoma research at the Institute of Cancer Research in the United Kingdom. In the study, Paul Huang, PhD and Ian Judson, MD will be working with the targeted therapy pazopanib (Votrient) in advanced soft tissue sarcomas. The investigators aim to better understand which patients are most likely to respond to paxopanib in order to spare those who are unlikely to benefit from unnecessary chemotherapy.

Sarcomas are rare cancers that are often aggressive and difficult to cure. Researchers continue to investigate new therapies that might improve outcomes for sarcoma patients. Pazopanib, a drug that targets a class of genes known as "kinases," was recently approved for the treatment of advanced sarcomas.

According to the Drs. Huang and Judson, some patients respond well to pazopanib, but the drug does not work in all cases. This means that there are subsets of patients who are exposed to the potential side effects of treatment for little or no benefit. Clinical trials have shown that leiomyosarcoma, synovial sarcoma and solitary fibrous tumour patients who are treated with pazopanib have a higher survival rate than those with other sarcoma subtypes. The reasons for these differences in drug response are not known, and are somewhat puzzling, considering that each of these sarcoma subtypes has a different genetic makeup.

At present, it is challenging to predict who will respond to pazopanib therapy. It would be helpful to identify tumour markers that enable doctors to choose the right patients for pazopanib treatment. This project should reveal the mechanisms of pazopanib resistance and will facilitate the identification of new candidates for prognostic biomarkers and combination therapy in leiomyosarcoma, synovial sarcoma and solitary fibrous tumour patients.

The Challenge of Pazopanib Resistance

By Dr. Paul Huang

There is currently a poor understanding of the determinants of pazopanib resistance, which hinders the development of predictive biomarkers for early patient stratification and the rational identification of new combination targets to overcome resistance. This study aims to address this challenge by identifying the molecular mechanisms of intrinsic pazopanib resistance in a panel of leiomyosarcoma, synovial sarcoma and solitary fibrous tumour specimens using an integrated proteomic, transcriptomic and genomic strategy.

We will employ phosphoproteomics, in combination with RNA Sequencing and Array-based Comparative Genomic Hybridisation technologies to characterise the proteins and genes in tumours from sarcoma patients who will undergo pazopanib therapy. A bioinformatics analysis of the molecular profiling data with patient outcome and drug response will enable the identification of biomarkers for pazopanib response. Significantly, this project will advance our understanding of the mechanisms of pazopanib resistance and will facilitate the identification of new candidates for prognostic biomarkers and combination therapy in leiomyosarcoma, synovial sarcoma and solitary fibrous tumour patients.

About the Investigators

Drs. Huang and Judson

This project leverages the combined expertise of the two principle investigators: Dr Huang, a group leader at the Institute of Cancer Research in London, who will lead the laboratory component of the project and Prof. Judson, Head of the Sarcoma Unit at the Royal Marsden Hospital (RMH) and Chair of Cancer Pharmacology at the ICR, who will provide the expertise to enable the translation of our laboratory findings into the clinical setting. The questions in this study require a multi-disciplinary approach - scientists (Dr. Huang) working closely with clinicians (Prof. Judson) to understand the molecular factors that drive pazopanib resistance in sarcoma patients.


The Liddy Shriver Sarcoma Initiative gratefully acknowledges a very generous donation from the Florence & Marshall Schwid Memorial Donor Advised Fund of the Jewish Community Foundation which was responsible for the funding of this research study.

Identifying the Molecular Determinants of Pazopanib Response in Advanced Soft Tissue Sarcoma


Pazopanib (Votrient) is a tyrosine kinase inhibitor (TKI) that increases progression free survival of most subsets of soft tissue sarcoma (STS) patients after failure of standard chemotherapy.1 A recent analysis of clinical trial data showed that a fifth of patients who were treated with pazopanib were both long term responders and long-term survivors.2 As a consequence of these data, pazopanib has been approved as a third line treatment for patients with metastatic non-adipocytic STS. Distinct STS subtypes show different response rates to pazopanib therapy. A higher survival for leiomyosarcomas and synovial sarcomas versus other STS types has been reported.3 Solitary fibrous tumours (SFT), which are fairly refractory to standard therapy, also respond to pazopanib treatment.4 The mechanisms of disease control for these three tumour subtypes are not well established and it is not currently possible to predict a priori which patients will benefit from this treatment.

Molecular profiling has the potential to define biomarkers that would enable patient stratification for response to pazopanib therapy. Significantly, while synovial sarcomas and leiomyosarcomas both display improved survival when treated with pazopanib, these two subtypes are driven by distinct genetic drivers with transcriptomic profiles that cluster into unique molecular groups.5 Collectively, these data suggest that transcriptomic analysis alone is insufficient to explain the clinical response to pazopanib. This lack of concordance may reflect genomic-independent factors such as epigenetic alterations, post-translational protein modifications or tumour microenvironmental influences. A recent computational analysis demonstrates that an integrated strategy incorporating transcriptomic and phosphoproteomic data can readily uncover novel mechanisms of tumourigenesis and candidate drug targets in kinase induced signalling.6 An integrated molecular profiling dataset may similarly improve patient stratification and therapeutic target identification in STS patients.

Purpose of Investigation

We have a poor understanding of the molecular factors that dictate sensitivity to pazopanib and cannot accurately predict which patients are likely to respond to this drug. This proposal seeks to address these challenges through the following specific aims:

1. To identify a phosphoproteomic signature for pazopanib response.

2. To investigate the utility of integrated molecular profiling analysis for the identification of predictive markers of pazopanib sensitivity.

3. To develop a defined assay for biomarker validation in future cohorts of STS patients.

Using a tool known as mass spectrometry, we propose to generate individualised high resolution signalling profiles of baseline tumours from an investigational study of STS patients that will be treated with pazopanib at the Royal Marsden Hospital (RMH) Sarcoma Unit. The tumours will additionally be subjected to transcriptomic analysis using RNA-Seq and genomic analysis using high-resolution Array-based Comparative Genomic Hybridisation (aCGH) technology. These molecular data will be integrated and correlated with patient survival to identify potential biomarkers of pazopanib response. In light of the small number of patients in this study, the cohort will be augmented by incorporating a retrospective analysis of pre-existing specimens from an additional 25 patients that have previously been treated with pazopanib at the RMH.4 At the end of the study period, we anticipate the identification of promising candidate markers for drug response which will be experimentally validated in future studies in STS cell line models and clinical cohorts.

Aim 1: Identification of a phosphoproteomic signature for pazopanib response.

The Sarcoma Unit at the RMH is conducting an open-label, non-randomised observational study of patients with advanced soft tissue sarcoma treated with pazopanib. Baseline biopsies will be collected two weeks prior to treatment for molecular profiling analysis. To determine the tumour cell signalling networks that are activated in the tissue, phosphoproteomic analysis will be performed using mass spectrometry assays developed in Dr Huang’s laboratory. This assay measures 200 phosphorylation sites across 100 phosphorylated proteins representing major components of tyrosine kinase signalling pathways. The major kinase targets of pazopanib are well represented in this assay (Table 1).

Table 1: A Subset of Kinase Targets Inhibited by Pazopanib









































Figure 1

Figure 1

Tissues which are assessed to have >70% tumour cells will be subjected to mechanical disruption and cell lysis. Extracted proteins will be processed and subjected to mass spectrometry analysis as previously described.7 The individualised proteomic profiles will be quantified and a subset of the proteins identified from proteomic experiments will be independently confirmed with western blotting where commercial antibodies are available. We will subsequently perform a statistical comparative analysis of the proteomic data between different tumour subtypes which will enable the identification of unique molecular signatures between different STS subtypes and may shed light on candidate molecular signalling drivers in leiomyosarcoma, SFT and synovial sarcoma (Fig 1. Dataset A). To identify potential signalling markers of pazopanib response, we will apply computational analysis to visualize the correlations between our phosphoproteomic profiles and the clinical endpoint of progression free survival. This computational analysis will allow us to prioritize a phosphoproteomic signature that correlates with pazopanib response (Fig 1. Dataset B).

Aim 2: To investigate the utility of integrated molecular profiling analysis for the identification of predictive markers of pazopanib sensitivity.

As part of this study, we propose to evaluate the utility of unbiased integrated molecular profiling analysis of genomic, transcriptomic and phosphoproteomic data to identify candidate predictive markers of pazopanib response (A workflow of the proposed analysis is summarised in Figure 1). RNA will be extracted from tissue specimens and subjected to transcriptomic analysis by RNA-Seq while array-based CGH will be used for genomic level analysis with DNA extraction, labelling, array hybridisation and image acquisition being performed as described.8,9 Integration of the genomic and transcriptomic analysis will be implemented in a similar fashion as previously described to identify molecular drivers in distinct breast cancer subtypes.8,9

To identify the genes which are significantly associated with clinical endpoints of pazopanib response, two-class unpaired significance analysis of microarray (SAM) will be performed. Genes that are differentially expressed in pazopanib sensitive versus resistant tumours will then be integrated with the phosphoproteomic data using Ingenuity Pathway Analysis (IPA) and visualised using the Cytoscape software. This strategy will reveal the networks and pathways that have been enriched in genes/proteins whose expression or activation levels correlate with patient outcome. To that end, our proposed analysis will identify a proteogenomic signature of pazopanib response. Additionally, since components of these signalling networks/pathways may constitute therapeutic targets, our analysis will also reveal novel candidates for future drug development.

Due to the small number of patients in this prospective study, the cohort will be augmented by a retrospective analysis of pre-existing specimens from STS patients who have undergone pazopanib therapy at the RMH.H4 Genes and proteins that are identified to be correlated with pazopanib response in our integrated molecular profiling analysis will be measured using in-situ hybridisation (ISH) and immunohistochemistry (IHC) respectively. Univariate and multivariate Cox regression analysis will be used to identify relationships between abundance of genes and activated proteins to patient survival.

Aim 3. To develop a defined phosphoproteomic assay for biomarker validation in future cohorts of STS patients.

Multiplexed biomarker analysis of tumour specimens remains a major challenge in clinical research. This problem is compounded by the lack of good specific antibodies for measuring phosphorylated proteins in tissue sections. In this final aim, we propose to develop a targeted STS-specific phosphoproteomic assay based on the proteomic signatures defined in Aims 1 and 2. This assay will be deployed to complement standard tissue analysis in multiplexed biomarker measurements. A stable isotope-labelled “heavy” peptide library containing the critical proteins important for predicting pazopanib response in STS patients will be generated and optimised for the reproducible and robust analysis of tissue using mass spectrometry. We aim to develop an assay for pazopanib treatment in STS which can be readily implemented into clinical studies.

Impact Statement and Future Directions

Pazopanib has been approved for advanced and recurrent STS but a significant patient population remains resistant to this drug. This research has the potential to influence patient stratification and personalisation of pazopanib therapy. By identifying STS subtypes whose proteomic profiles are prognostic for drug resistance, it is likely that we will be able to better assess which patients are most likely to respond to targeted therapy and spare those who are unlikely to benefit from unnecessary chemotherapy. The development of a STS-specific phosphoproteomic assay will also result in the rapid assessment of patients which will aid clinical decisions on therapy. The proteomic characterisation of three distinct STS subtypes will generate an invaluable resource for the sarcoma research community to mine for additional targets. In the longer term, we anticipate that our integrated molecular profiling studies will facilitate the identification of signalling proteins and genes that mediate resistance and drive the development of improved combination therapeutic strategies to circumvent pazopanib resistance.

By Ian Judson, MD
The Royal Marsden in the United Kingdom

and Paul Huang, PhD
The Institute of Cancer Research in the United Kingdom


1. van der Graaf, W.T., et al., Pazopanib for metastatic soft-tissue sarcoma (PALETTE): a randomised, double-blind, placebo-controlled phase 3 trial. Lancet, 2012. 379(9829): p. 1879-86.

2. Kasper, B., et al., Long-term responders and survivors on pazopanib for advanced soft tissue sarcomas: subanalysis of two European Organisation for Research and Treatment of Cancer (EORTC) clinical trials 62043 and 62072. Ann Oncol, 2014. 25(3): p. 719-24.

3. Sleijfer, S., et al., Pazopanib, a multikinase angiogenesis inhibitor, in patients with relapsed or refractory advanced soft tissue sarcoma: a phase II study from the European organisation for research and treatment of cancer-soft tissue and bone sarcoma group (EORTC study 62043). J Clin Oncol, 2009. 27(19): p. 3126-32.

4. Maruzzo, M., et al., Pazopanib as first line treatment for solitary fibrous tumours: the Royal Marsden Hospital experience. Clin Sarcoma Res, 2015. 5: p. 5.

5. Nielsen, T.O., et al., Molecular characterisation of soft tissue tumours: a gene expression study. Lancet, 2002. 359(9314): p. 1301-7.

6. Huang, S.S., et al., Linking proteomic and transcriptional data through the interactome and epigenome reveals a map of oncogene-induced signaling. PLoS Comput Biol, 2013. 9(2): p. e1002887.

7. Iwai, L.K., et al., Phosphoproteomics of collagen receptor networks reveals SHP-2 phosphorylation downstream of wild-type DDR2 and its lung cancer mutants. Biochem J, 2013. 454(3): p. 501-13.

8. Natrajan, R., et al., Functional characterization of the 19q12 amplicon in grade III breast cancers. Breast Cancer Res, 2012. 14(2): p. R53.

9. Natrajan, R., et al., An integrative genomic and transcriptomic analysis reveals molecular pathways and networks regulated by copy number aberrations in basal- like, HER2 and luminal cancers. Breast Cancer Res Treat, 2010. 121(3): p. 575-89.

  • Figure 1