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Sarcoma

1973 - A molecular signature predictive of clinical outcome following pazopanib therapy in advanced soft tissue sarcoma (485O)

Date

18 Nov 2017

Session

Sarcoma

Presenters

Paul Huang

Citation

Annals of Oncology (2017) 28 (suppl_10): x149-x152. 10.1093/annonc/mdx675

Authors

P. Huang1, A. Lee2, F. McCarthy1, K. Thway2, J. Morden3, C. Messiou2, F. Daley4, R. Buus4, C. Fisher2, M. Cheang3, I. Judson2, R. Jones2

Author affiliations

  • 1 Division Of Cancer Biology, Institute of Cancer Research ICR, SW3 6JB - London/GB
  • 2 Sarcoma Unit, The Royal Marsden NHS Foundation Trust, London/GB
  • 3 Clinical Trials And Statistics Unit (icr-ctsu), Institute of Cancer Research ICR, Sutton/GB
  • 4 The Breast Cancer Now Toby Robins Research Centre, Institute of Cancer Research ICR, SW3 6JB - London/GB
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Resources

Abstract 1973

Background

Pazopanib (PZP) is a kinase inhibitor approved for the treatment of advanced soft tissue sarcoma (STS). There are no predictive biomarkers for PZP response.

Methods

Pre-treatment primary formalin-fixed paraffin-embedded tumours from PZP-treated STS patients (RMH-SARC, n = 38) with mixed histological subtypes were assessed for: (i) levels of PZP targets FGFR1 and PDGFR by immunohistochemistry (IHC), (ii) TP53 mutational status by Sanger sequencing and (iii) 730 cancer pathway-related gene expression. Consensus clustering was used to identify biological subgroups blinded to patient outcome. Multivariable Cox regression analyses of pre-defined biomarkers with patient outcome was determined for RMH-SARC and evaluated in an independent, PZP-naïve STS dataset (TCGA-SARC, n = 261).

Results

Within RMH-SARC, seven cases were classified as low FGFR1 (F) and high PDGFRA (P) expression (F-Lo/P-Hi). Ten cases had TP53 mutation (TP53mut). These two patient subgroups had significantly worse progression free survival (PFS) and overall survival (OS) compared to their counterparts and were independent biomarkers for survival (Table 1). Among the 22 TP53wt cases which were not F-Lo/P-Hi, 3 molecular subgroups were identified and characterised with an optimal reduced list of 115 genes (Subgroups A, B, C). Integrating these multiple analytes into one decision tree classifier (defined as Pazopanib Activity and Response in SARComa - PARSARC) performed best at predicting post-PZP outcome. Subgroup A had a superior PFS and OS (median (m) PFS 13 months (ms); mOS 34ms) compared to the F-Lo/P-Hi (mPFS 1.4ms; mOS 1.7ms) and the TP53mut (mPFS 3.0ms; mOS 5.4ms) subgroups. In the independent PZP-naïve STS dataset (TCGA-SARC), these biomarkers were not associated with differential outcome, suggesting that the PARSARC classifier is a potential predictor for PZP benefit.Table: 485O

Univariate and multivariate analysis analysis of PFS and OS

Progression Free Survival (PFS)Overall Survival (OS)
NUnivariateMultivariate*UnivariateMultivariate*
HRPHRPHRPHRP
IHC
F-Hi and/ or P-Lo311-1-1-1-
F-Lo and P-Hi79.6

Conclusions

We have developed the PARSARC classifier consisting of FGFR1 and PDGFRA IHC, TP53 sequencing and a 115 gene expression signature that appears to identify STS patients most likely to benefit from PZP therapy.

Clinical trial identification

Legal entity responsible for the study

The Institute of Cancer Research: Royal Cancer Hospital

Funding

National Institute for Health Research (NIHR) Liddy Shriver Sarcoma Initiative The Royal Marsden Cancer Charity

Disclosure

All authors have declared no conflicts of interest.

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