Correlation of levels and patterns of genomic instability with histological grading of invasive breast tumors (original) (raw)

Abstract

Pathological grade is a useful prognostic factor for stratifying breast cancer patients into favorable (well-differentiated tumors) and less favorable (poorly-differentiated tumors) outcome groups. The current system of tumor grading, however, is subjective and a large proportion of tumors are characterized as intermediate-grade tumors, making determination of optimal treatments difficult. To determine whether molecular profiles can discriminate breast disease by grade, patterns and levels of allelic imbalance (AI) at 26 chromosomal regions frequently altered in breast disease were examined in 185 laser microdissected specimens representing well-differentiated (grade 1; n = 55), moderately-differentiated (grade 2; n = 71), and poorly-differentiated (grade 3; n = 59) stage I–IV breast tumors. Overall levels of AI were significantly higher in grade 3 compared to grade 1 tumors (P < 0.05). Grades 1 and 3 showed distinct genetic profiles - grade 1 tumors were associated with large deletions of chromosome 16q22, while alterations at 9p21, 11q23, 13q14, 17p13.1 and 17q12 were characteristics of grade 3 carcinomas. In general, levels and patterns of AI in grade 2 carcinomas were intermediate between grade 1 and grade 3 tumors. Patterns of AI accurately categorized ∼70% of samples into high- or low-grade disease groups, suggesting that the majority of breast tumors have genetic profiles consistent with high- or low-grade, and that molecular signatures of breast tumors can be useful for more accurate characterization of invasive breast cancer.

Access this article

Log in via an institution

Subscribe and save

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Millis RR et al (1998) Tumor grade does not change between primary and recurrent mammary carcinoma. Eur J Cancer 34:548–553
    Article PubMed CAS Google Scholar
  2. Roylance R et al (2002) Allelic imbalance analysis of chromosome 16q shows that grade I and grade III invasive ductal breast cancers follow different genetic pathways. J Pathol 196:32–36
    Article PubMed CAS Google Scholar
  3. Roylance R et al (1999) Comparative genomic hybridization of breast tumors stratified by histological grade reveals new insights into the biological progression of breast cancer. Cancer Res 59:1433–1436
    PubMed CAS Google Scholar
  4. Buerger H et al (2001) Ductal invasive G2 and G3 carcinomas of the breast are the end stages of at least two different lines of genetic evolution. J Pathol 194(2):165–170
    Article PubMed CAS Google Scholar
  5. Sotiriou C et al (2006) Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis. J Natl Cancer Inst 98(4):262–272
    Article PubMed CAS Google Scholar
  6. Henson DE et al (1991) Relationship among outcome, stage of disease, and histologic grade for 22,616 cases of breast cancer. Cancer 68(10):2142–2149
    Article PubMed CAS Google Scholar
  7. Elston CW, Ellis IO (1998) Systemic pathology 3E. In: Elston CW, Ellis IO (eds) The breast. Churchill Livingstone, Edinburgh pp. 3–10
    Google Scholar
  8. American Joint Committee on Cancer. 2002. AJCC Cancer Staging Manual. 6 ed. Greene FL et al (eds). New York: Springer
  9. Bloom HJ, Richardson WW (1957) Histological grading and prognosis in breast cancer. Br J Cancer 11:359–377
    PubMed CAS Google Scholar
  10. Elston CW, Ellis IO (1991) Pathological prognostic factors in breast cancer. I. The value of histological grade in breast cancer: experience from a large study with long-term follow up. Histopathology 19:403–410
    Article PubMed CAS Google Scholar
  11. Ellsworth DL et al (2003a) Laser capture microdissection of paraffin-embedded tissues. Biotechniques 34(1):42–46
    CAS Google Scholar
  12. Ellsworth RE et al (2003b) High-throughput loss of heterozygosity mapping in 26 commonly deleted regions in breast cancer. Cancer Epidemiol Biomarkers Prev 12(9):915–919
    CAS Google Scholar
  13. Medintz IL et al (2000) Loss of heterozygosity assay for molecular detection of cancer using energy-transfer primers and capillary array electrophoresis. Genome Res 10:1211–1218
    Article PubMed CAS Google Scholar
  14. Ellsworth RE et al (2005) Allelic imbalance in primary breast carcinomas and metastatic tumors of the axillary lymph nodes. Mol Cancer Res 3:71–77
    Article PubMed CAS Google Scholar
  15. Fearon ER, Vogelstein B (1990) A genetic model for colorectal tumorigenesis. Cell 61(5):759–767
    Article PubMed CAS Google Scholar
  16. Cleton-Jansen AM et al (2004) Different mechanisms of chromosome 16 loss of heterozygosity in well- versus poorly differentiated ductal breast cancer. Genes Chromosomes Cancer 41:109–116
    Article PubMed CAS Google Scholar
  17. Bieche I, Lidreau R (2000) Loss of heterozygosity at 13q14 correlates with RB1 gene underexpression in human breast cancer. Mol Carcinog 29(3):151–158
    Article PubMed CAS Google Scholar
  18. Lukas J et al (1995) Retinoblastoma-protein-dependent cell-cycle inhibition by the tumour suppressor p16. Nature 375:503–506
    Article PubMed CAS Google Scholar
  19. Seitz S et al (2001) Detailed deletion mapping in sporadic breast cancer at chromosomal region 17p13 distal to the TP53 gene: association with clinicopathological parameters. J Pathol 194:318–326
    Article PubMed CAS Google Scholar
  20. Winqvist R et al (1995) Loss of heterozygosity for chromosome 11 in primary human breast tumors is associated with poor survival after metastasis. Cancer Res 55(12):2660–2664
    PubMed CAS Google Scholar

Download references

Acknowledgements

The authors thank Sue Lubert for assistance in genotyping and Dr. Michael Dunn for critical review of this manuscript.

Author information

Authors and Affiliations

  1. Clinical Breast Care Project, Windber Research Institute, Windber, PA, USA
    Rachel E. Ellsworth, Jennifer L. Kane, Heather L. Patney & Darrell L. Ellsworth
  2. Clinical Breast Care Project, Walter Reed Army Medical Center, Washington, DC, USA
    Jeffrey A. Hooke & Craig D. Shriver
  3. Invitrogen Informatics, Carlsbad, CA, USA
    Brad Love

Authors

  1. Rachel E. Ellsworth
    You can also search for this author inPubMed Google Scholar
  2. Jeffrey A. Hooke
    You can also search for this author inPubMed Google Scholar
  3. Brad Love
    You can also search for this author inPubMed Google Scholar
  4. Jennifer L. Kane
    You can also search for this author inPubMed Google Scholar
  5. Heather L. Patney
    You can also search for this author inPubMed Google Scholar
  6. Darrell L. Ellsworth
    You can also search for this author inPubMed Google Scholar
  7. Craig D. Shriver
    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence toRachel E. Ellsworth.

Additional information

The opinion and assertions contained herein are the private views of the authors and are not to be construed as official or as representing the views of the Department of the Army or the Department of Defense.

This work was performed under the auspices of the Clinical Breast Care Project with funding provided by federal appropriations from the United States Department of Defense and the Henry M. Jackson Foundation for the Advancement of Military Medicine [grant MDA-905-00-1-0022 to C.D.S.]

Rights and permissions

About this article

Cite this article

Ellsworth, R.E., Hooke, J.A., Love, B. et al. Correlation of levels and patterns of genomic instability with histological grading of invasive breast tumors.Breast Cancer Res Treat 107, 259–265 (2008). https://doi.org/10.1007/s10549-007-9547-2

Download citation

Keywords