Use of samples in research rhabdomyosarcomas
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Use of Samples in Research - Rhabdomyosarcomas. Janet Shipley Sarcoma Molecular Pathology Team The Institute of Cancer Research Sutton, UK. Childhood Cancers. ~ 1,500 new cases in UK p.a. 1% Liver 3% Germ cell 3% Eye 5% Bone 6% Wilms 6% Soft tissue 7% Neuroblastoma

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Use of Samples in Research - Rhabdomyosarcomas

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Use of Samples in Research - Rhabdomyosarcomas

Janet Shipley

Sarcoma Molecular Pathology Team

The Institute of Cancer Research

Sutton, UK

Childhood Cancers

~ 1,500 new cases in UK p.a.

1% Liver

3% Germ cell

3% Eye

5% Bone

6% Wilms

6% Soft tissue

7% Neuroblastoma

14% Lymphoma

18% CNS

30% Leukaemia

7% Other

6-8% soft tissue sarcomas (1% in adults)

> 50% rhabdomyosarcoma (RMS)

~ 70 new cases in UK p.a.

Clinical issues:

  • Overall survival rhabdomyosarcomas (RMS) ~70%

  • Certain categories and metastatic disease - dismal

  • Major cause from cancer death in children

  • Toxicity leads to survivorship issues

  • Rhabdomyosarcoma (RMS) histology

  • Small round blue cell tumours

  • Resemble developing skeletal muscle

  • Two main histological subtypes:

    • Embryonal (ERMS)

    • Alveolar (ARMS)

Embryonal RMS (ERMS) (60-80% of RMS cases)

  • Cells resemble embryonic

    skeletal muscle

  • Predominant in younger


  • Generally good prognosis

ERMS genetics

Ploidy changes and aneuploidy (2, 8, 12, 13, 17 and 20)

- chromosomal instability CIN

Abnormalities of 11p:

Increased IGF2 expression through:

- Loss of heterozygosity (LOH)

80% affects IGF2, H19 and CDKN1C (p57KIP2) loci

(duplication of paternal non-silenced locus)

- Loss of imprinting (LOI) – 20%

(loss of maternal IGF2 imprinting)

- RAS mutations including HRAS at 11p

Alveolar RMS (ARMS) (20-40% of RMS cases)

  • Older children

  • Poor prognosis

  • Characteristic translocations

ARMS genetics

  • Ploidy changes, aneuploidy and amplification events

  • TP53 mutations

  • LOI loss of maternal silencing of IGF2 - biallelic expression

    H19 affects IGF2 imprinting

  • Characteristic chromosome translocations present in most, but not all cases

  • Characteristic translocations present in ~70% of ARMS

    • ~80% of which t(2;13)(q35;q14) PAX3/FOXO1

    • ~20% t(1;13)(p36;q14) PAX7/FOXO1 and rare variants



Paired DNA

binding domain




Survival from rhabdomyosarcoma in GB, 1991-2000

Charles Stiller, CCLG data

Use of PAX-FOXO1 Fusion vs Histology in clinical stratification

  • PAX fusion gene status has been used for years as “unofficial” diagnostic aid

  • Current and past treatment stratifications incorporate histology into risk management strategies

  • The definition of Alveolar histology changed in the 90s (from majority to any)

  • Differentiating Alveolar from Embryonal involves finding histological evidence of alveolar spaces (with the exception of solid alveolar)

As 30% of RMS with alveolar histology

do not appear to have fusion gene

Q: Clinical and biological impact of fusion gene status and histology

Williamson et al 2010 JCO

Criteria for Inclusion

  • Patients with RMS all stages less than 21 years old, both sexes

  • RMS diagnosed or treated in France or UK (through CCLG) between 1989 and 2005 - SIOP protocols

  • Review of histological diagnosis of RMS alveolar and embryonal according to morphology and immunohistochemistry by members of the French/UK panel of pathologists


  • Molecular analysis of a representative sample by the Institut Curie or ICR for presence of PAX3/FOXO1, PAX7/FOXO1 or PAX3/NCOA1 by multiplex RT-PCR

  • DNA array CGH profiling

  • Gene expression profiling (Affymetrix Plus 2)

  • Issue of RNA quality critical – rapid snap freezing

Overall and Event Free Survival

Cox Regression – Risk of Recurrence

  • Fusion gene positive cases greater risk of recurrence

Cox Regression – Risk of Death

  • Fusion gene positive cases greater risk of death

Frequency of Metastases

Expression profiling of 101 RMS


This Study



Davicioni et al





Wachtel et al



Laé et al



Negative Matrix Factorisation (NMF) - Metagenes

  • HGU133 plus 2 Our Study

    • 101

      • 69 Alveolar

      • 37 Embryonal

  • HGU133a – Davicioni et al

    • 118

      • 64 Alveolar

      • 55 Embryonal

  • HGU133a – Wachtel et al

    • 30

      • 15 Alveolar

      • 15 Embryonal

  • HGU133a – Laé

    • 38

      • 23 Alveolar

      • 15 Embryonal

Negative Matrix Factorisation (NMF) - Metagenes






Supervised Analysis - Support Vector Machine Classification

Supervised Analysis – SAM (Significance Analysis Microarray)

DNA analysis - ArrayCGH – 128 RMS

Gain of Chromosome 8 is Characteristic of Fusion Negative RMS


Copy number

Chromosome 8 genes are enriched in Metagene F2 linked to fusion neg cases

Highly correlated with F2 metagene

Highly anti-correlated with F2 metagene

Metagenes associated with outcome

  • Davicioni et al MG34

  • New metagene we derived, less efficient in their dataset

  • - overfitting

  • Heavy association with fusion gene status, PAX3-FOXO1 versus PAX7-FOXO1 cases

  • PAX3-FOXO1 versus PAX7-FOXO1 cases

  • Similar gene expression profiles

  • Predictive metagenes linked to PAX3 v PAX7-FOXO1

  • Direct comparison?

  • - COG study, PAX7-FOXO1 better outcome

  • German study, no difference

  • Limited numbers

Pilot data

N=450 from MMT89, 95 , 98

Plus current EpSSG cases

PAX3-FOXO1 fusion dual-color assay

5’ PAX3 Telomeric Probes (BACs)

3’ FOXO1 Centromeric Probes (BACs)








Chimeric der(13) t(2;13) (q35,q14)



PAX7-FOXO1 fusion dual color assay

5’ PAX7 Telomeric Probes (BACs)

3’ FOXO1 Centromeric Probes (BACs)








Chimeric der(13) t(1;13) (p36;q14)



Plus RT-PCR analyses where possible

Conclusions 1

  • PAX fusion negative ARMS clinically and molecularly indistinguishable from ERMS

  • Fusion negative RMS characterised by a distinct and common expression signature including chromosome 8 gain

  • Implications for the ongoing risk stratification strategies in current RMS treatment protocols - under versus over treatment


  • Prospective study to assess classifier

  • Additional/refinement of potential prognostic markers

  • Identify and validate presence of potential therapeutic targets

Children's Cancer and

Leukaemia Group

Thanks to…

INSERM U830 Institut Curie

Olivier Delattre

Daniel Williamson

Gaelle Pierron

Benedicte Thuille

Stephanie Reynaud

Départment de Pédiatrie, Institut Curie

Daniel Orbach

Gilles Palenzuela

Pathology Dept. Institut Curie

Paul Fréneaux

Marick Laé

Ligue Nationale Contre le Cancer

Aurélien de Reyniès

Manchester Children’s Hospital

Anna Kelsey

Swiss Bioinformatics Institute

Edoardo Missiaglia


Kathy Pritchard-Jones

Department of Pediatric and Adolescent Oncology,

Institut Gustave Roussy

Odile Oberlin

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