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A signature of chromosomal instability inferred from gene expression profiles predicts clinical outcome in multiple human cancers - Nature Genetics

  • ️Szallasi, Zoltan
  • ️Sun Aug 20 2006
  • Letter
  • Published: 20 August 2006

Nature Genetics volume 38, pages 1043–1048 (2006)Cite this article

Abstract

We developed a computational method to characterize aneuploidy in tumor samples based on coordinated aberrations in expression of genes localized to each chromosomal region. We summarized the total level of chromosomal aberration in a given tumor in a univariate measure termed total functional aneuploidy. We identified a signature of chromosomal instability from specific genes whose expression was consistently correlated with total functional aneuploidy in several cancer types. Net overexpression of this signature was predictive of poor clinical outcome in 12 cancer data sets1,2,3,4,5,6,7,8,9,10,11,12 representing six cancer types. Also, the signature of chromosomal instability was higher in metastasis samples than in primary tumors and was able to stratify grade 1 and grade 2 breast tumors according to clinical outcome. These results provide a means to assess the potential role of chromosomal instability in determining malignant potential over a broad range of tumors.

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Acknowledgements

We thank A. Amon, D. Botstein, M. Meyerson and T. Ried for helpful suggestions, and Novartis for the NCI60 expression data. This work was supported in part by the US National Institutes of Health through grant 1PO1CA-092644-01 and the Department of Defense through grant W81XWH-04-1-0549. I.S.K. was supported in part by National Institutes of Health National Center for Biomedical Computing grant 5U54LM008748-02.

Author information

Authors and Affiliations

  1. Children's Hospital Informatics Program at the Harvard-MIT Division of Health Sciences and Technology (CHIP@HST), Harvard Medical School, Boston, 02115, Massachusetts, USA

    Scott L Carter, Aron C Eklund, Isaac S Kohane & Zoltan Szallasi

  2. Laboratory of Functional Genomics, Brigham and Women's Hospital, Cambridge, 02139, Massachusetts, USA

    Aron C Eklund

  3. Breast Disease Unit, Yale School of Medicine, New Haven, 06520-8032, Connecticut, USA

    Lyndsay N Harris

  4. Center for Biological Sequence Analysis, Technical University of Denmark, Lyngby, DK-2800, Denmark

    Zoltan Szallasi

Authors

  1. Scott L Carter

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  2. Aron C Eklund

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  3. Isaac S Kohane

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  4. Lyndsay N Harris

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  5. Zoltan Szallasi

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Contributions

S.L.C. and Z.S. conceived of and designed the study. S.L.C. carried out all the analysis. S.L.C. and Z.S. wrote the manuscript. A.C.E., I.S.K. and L.N.H. provided guidance and participated in the preparation of the manuscript.

Corresponding author

Correspondence to Zoltan Szallasi.

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Competing interests

S.L.C., A.C.E. and Z.S. have applied for a patent on the diagnostic use of the chromosomal instability signature described in the manuscript.

Supplementary information

Supplementary Fig. 1

Relationship between functional aneuploidy and DNA-based measures of chromosomal abberations. (PDF 218 kb)

Supplementary Fig. 2

Total functional aneuploidy (tFA) is a significant predictor of clinical outcome in the four breast, lung and brain cancer data sets of 18 data sets evaluated. (PDF 48 kb)

Supplementary Fig. 3

Correlation between gene expression profiles and tFA is conserved in diverse human cancer data sets. (PDF 192 kb)

Supplementary Fig. 4

The CIN signature does not generate significant predictions of clinical outcome for 6 of 18 data sets evaluated. (PDF 47 kb)

Supplementary Fig. 5

The prognostic ability of cell cycle–regulated genes is dependent on CIN score. (PDF 130 kb)

Supplementary Fig. 6

Multivariate analysis of the CIN25 and proliferation signatures revealed that CIN25 was generally more relevant for risk stratification of cancer cohorts. (PDF 27 kb)

Supplementary Fig. 7

Removal of proliferation-associated genes from the CIN signature does not impair its predictive ability for clinical outcome. (PDF 591 kb)

Supplementary Table 1

Top 70 genes with the highest levels of consistent correlation with tFA in three cancer-associated data sets. (PDF 112 kb)

Supplementary Methods (PDF 107 kb)

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Cite this article

Carter, S., Eklund, A., Kohane, I. et al. A signature of chromosomal instability inferred from gene expression profiles predicts clinical outcome in multiple human cancers. Nat Genet 38, 1043–1048 (2006). https://doi.org/10.1038/ng1861

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  • Received: 09 May 2006

  • Accepted: 17 July 2006

  • Published: 20 August 2006

  • Issue Date: 01 September 2006

  • DOI: https://doi.org/10.1038/ng1861

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