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Feasibility of analyzing DNA copy number variation in breast cancer tumor specimens from 1950 to 2010: how old is too old?

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Abstract

Purpose

The purpose of the study was to assess the feasibility of quantifying long-term trends in breast tumor DNA copy number variation (CNV) profiles.

Methods

We evaluated CNV profiles in formalin-fixed paraffin-embedded (FFPE) tumor specimens from 30 randomly selected Kaiser Permanente Northern California health plan women members diagnosed with breast cancer from 1950 to 2010. Assays were conducted for five cases per decade who had available tumor blocks and pathology reports.

Results

As compared to the tumors from the 1970s to 2000s, the older tumors dating back to the 1950s and 1960s were much more likely to (1) fail quality control, and (2) have fewer CNV events (average 23 and 31 vs. 58 to 69), fewer CNV genes (average 5.1 and 3.7k vs. 8.1 to 10.3k), shorter CNV length (average 2,440 and 3,300k vs. 5,740 to 9,280k), fewer high frequency Del genes (37 and 25% vs. 54 to 76%), and fewer high frequency high_Amp genes (20% vs. 56 to 73%). On average, assay interpretation took an extra 60 min/specimen for cases from the 1960s versus 20 min/specimen for the most recent tumors.

Conclusions

Assays conducted in the mid-2010s for CNVs may be feasible for FFPE tumor specimens dating back to the 1980s, but less feasible for older specimens.

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References

  1. Zhang F, Gu W, Hurles ME, Lupski JR (2009) Copy number variation in human health, disease, and evolution. Annu Rev Genomics Hum Genet. https://doi.org/10.1146/annurev.genom.9.081307.164217

    Article  PubMed  PubMed Central  Google Scholar 

  2. Tang Y-C, Amon A (2013) Gene copy-number alterations: a cost–benefit analysis. Cell 152:394–405

    Article  CAS  Google Scholar 

  3. Hart L, O’Driscoll M (2013) Causes and consequences of structural genomic alterations in the human genome. eLS https://doi.org/10.1002/9780470015902.a0024976

    Article  Google Scholar 

  4. Thompson PA, Brewster AM, Kim-Anh D, Baladandayuthapani V, Broom BM, Edgerton ME, Hahn KM, Murray JL, Sahin A, Tsavachidis S, Wang Y, Zhang L, Hortobagyi GN, Mills GB, Bondy ML (2011) Selective genomic copy number imbalances and probability of recurrence in early-stage breast cancer. PLoS ONE 6:e23543

    Article  CAS  Google Scholar 

  5. Brewster AM, Thompson P, Sahin AA, Do K, Edgerton M, Murray JL, Tsavachidis S, Zhou R, Liu Y, Zhang L, Mills G, Bondy M (2011) Copy number imbalances between screen- and symptom-detected breast cancers and impact on disease-free survival. Cancer Prev Res (Phila) 4:1609e1616

    Article  Google Scholar 

  6. Liu Y, Zhou R, Baumbusch LO, Tsavachidis S, Brewster AM, Do K-A, Sahin A, Horobagyi GN, Taube JH, Mani SA, Aarøe J, Wärnberg F, Børresen-Dale A-L, Mills GB, Thompson PA, Bondy ML (2014) Genomic copy number imbalances associated with bone and non-bone metastasis of early-stage breast cancer. Breast Cancer Res 143:189–201

    Article  CAS  Google Scholar 

  7. Cava C, Bertoli G, Castiglioni I (2015) Integrating genetics and epigenetics in breast cancer: biological insights, computational methods and therapeutic potential. BMC Syst Biol 9:62. https://doi.org/10.1186/s12918-015-0211-x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Santarpia L, Bottai G, Kelly CM, Gyoffry B, Székely B, Puszlai L (2016) Deciphering and targeting oncogenic mutations and pathways in breast cancer. Oncologist 21:1063–1078

    Article  CAS  Google Scholar 

  9. Rennhack J, To B, Wermuth H, Andrecheck ER (2017) Mouse models of breast cancer share amplification and deletion events with human breast cancer. J Mammary Gland Biol Neoplasia 22:71–84

    Article  Google Scholar 

  10. Krieger N (2013) History, biology, and health inequities: emergent embodied phenotypes & the illustrative case of the breast cancer estrogen receptor. Am J Public Health 103:22–27

    Article  Google Scholar 

  11. Krieger N, Habel LA, Waterman PD, Shabani M, Ellison-Loschmann L, Achacoso NS, Acton L, Schnitt SJ (2015) Analyzing historical trends in breast cancer biomarker expression: a feasibility study (1947–2009). npj Breast Cancer 1:15016. https://doi.org/10.1038/npjbcancer.2015.16

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Kokkat TJ, Patel MS, McGarvey D, LiVolsi VA, Baloch ZW (2013) Archived formalin-fixed paraffin-embedded (FFPE) blocks: a valuable underexploited resource for extraction of DNA, RNA, and protein. Biopreserv Biobank 11:101–106

    Article  CAS  Google Scholar 

  13. Valla M, Vatten LJ, Engstrøm MJ, Haugen OA, Akslen LA, Bjørngaard JH, Hagen AI, Ytterhus B, Bofin AM, Ordahl S (2016) Molecular subtypes of breast cancer: long-term incidence trends and prognostic differences. Cancer Epidemiol Biomark Prev 25:1625–1634

    Article  CAS  Google Scholar 

  14. Wang Y, Cottman ME, Schiffman JD (2012) Molecular inversion probes: a novel microarray technology and its application in cancer research. Cancer Genet 205:341–355

    Article  CAS  Google Scholar 

  15. Affymetrix. OncoScan® CNV FFPE assay kit. http://www.affymetrix.com/support/technical/byproduct.affx?product=oncoscan_cnv_ffpe_assay_kit. Accessed 8 Jan 2018

  16. Mittempergher L, de Ronde JJ, Nieuwland M, Kerkhoveen RM, Simon I, Rutgers EEJT., Wessels LFA, Van’t Veer LJ (2011) Gene expression profiles from formalin fixed paraffin embedded breast cancer tissue are largely comparable to fresh frozen matched tissue. PLoS ONE 6(2):e17163

    Article  CAS  Google Scholar 

  17. Herrmann B, Hummel S (eds) (1994) Ancient DNA: recovery and analysis of genetic material from paleontological, archeological, museum, medical, and forensic specimens. Springer, New York

    Google Scholar 

  18. Hendricks RL (1993) A model for national health care: the history of Kaiser Permanente. Rutgers University Press, New Brunswick

    Google Scholar 

  19. Gordon N (2008) What the member health surveys project tells us about the Kaiser Permanent Northern California adult membership: demographics, IT access, behavioral/lifestyle risks, and health: trends, race-ethnic differences, and variation across service populations. Kaiser Permanente Division of Research, Oakland, February 2008. https://divisionofresearch.kaiserpermanente.org/projects/memberhealthsurvey/SiteCollectionDocuments/What_Member_Health_Surveys_Project_Tells_about_KPNC_Population_Feb_2008.pdf. Accessed 8 Jan 2018

  20. Kaiser Permanente Division of Research (2017) Cancer genomics. https://divisionofresearch.kaiserpermanente.org/Pages/cancergenomics.aspx. Accessed 8 Jan 2018

  21. OncoScan™ Nexus express software. https://www.affymetrix.com/products_services/software/specific/oncoscan_nexus.affx#1_1 and https://tools.thermofisher.com/content/sfs/manuals/oncoscan_nexus_express_software_qrc.pdf. Accesed 8 Jan 2018

  22. Jung H, Lefferts JA, Tsongalis GJ (2017) Utilization of the Oncoscan microarray assay in cancer diagnostics. Appl Cancer Res 37:1

    Article  Google Scholar 

  23. Curtis C, Shah SP, Chin SF, Turashvili G, Rueda OM, Dunning MJ, Speed D, Lynch AG, Samarajiwa S, Yuan Y, Gräf S, Ha G, Haffari G, Bashashati A, Russell R, McKinney S, Group METABRIC, Langerød A, Green A, Provenzano E, Wishart G, Pinder S, Watson P, Markowetz F, Murphy L, Ellis I, Purushotham A, Børresen-Dale AL, Brenton JD, Tavaré S, Caldas C, Aparicio S (2012) The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. Nature 486:346–352

    Article  CAS  Google Scholar 

  24. Singh RR, Mehrotra M, Chen H, Almohammedsalim A, Sahin A, Bosamra A, Patel KP, Routbort MJ, Lu X, Ronald A (2016) Comprehensive screening of gene copy number aberrations in formalin-fixed, paraffin-embedded solid tumors using molecular inversion probe-based single-nucleotide polymorphism array. J Mol Diagn 18:676–687

    Article  CAS  Google Scholar 

Download references

Acknowledgments

We also would like to thank Marvella A. Villasenor, BA (Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA 94612; email: Marvella.A.Villasenor@kp.org) for her administrative assistance with study logistics.

Funding

This study was funded by NIH grant 5R03CA193078 (PI: Krieger), which was supported by the National Cancer Institute (NCI) and the NIH Office of Behavioral and Social Sciences Research, in the Office of the Director, National Institutes of Health (OD). The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the article; and decision to submit the article for publication.

Author information

Authors and Affiliations

  1. Dept of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Kresge 717, Boston, MA, 02130, USA

    Nancy Krieger

  2. Dept of Computer Science and Engineering, University of Connecticut, 371 Fairfield Way, Storrs, CT, 06269, USA

    Sheida Nabavi

  3. Dept of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, 02130, USA

    Pamela D. Waterman

  4. Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA, 94612, USA

    Ninah S. Achacoso, Luana Acton & Laurel A. Habel

  5. Dana-Farber Cancer Institute/Brigham and Women’s Hospital Breast Oncology Program, Department of Pathology, Brigham and Women’s Hospital, 75 Francis Street, Boston, MA, 02115, USA

    Stuart J. Schnitt

Authors
  1. Nancy Krieger
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  2. Sheida Nabavi
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  3. Pamela D. Waterman
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  4. Ninah S. Achacoso
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  5. Luana Acton
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  6. Stuart J. Schnitt
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  7. Laurel A. Habel
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Contributions

NK led design of the study, arranged for the assays, oversaw the analyses, and led manuscript preparation. SN interpreted the assay results and contributed to text on the methods and results. LH oversaw the initial selection of cases and retrieval of the tumor specimens, and assisted in all logistics pertaining to handling of the specimens at KPNC, as carried out by LA and NA. PDW assisted with all logistics pertaining to the handling of the specimens and with arranging the assays, once the specimens were at Harvard. SJS oversaw the histological characterization of the tumor specimens and the extraction of tumor DNA for the study assay. All authors contributed to manuscript preparation and reviewed and approved the final manuscript prior to submission.

Corresponding author

Correspondence to Nancy Krieger.

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Conflicts of interest

The authors declare they have no conflicts of interest to declare.

Human Subjects and Informed Consent

This study was approved by the Institutional Review Boards (IRBs) of the Harvard T.H. Chan School of Public Health (#CR-20929-02) and Kaiser Permanente Northern California (#CN-13Labe-O3-H). All procedures involving human subjects were in accordance with the ethical standards of these IRBs and the 1964 Helsinki declaration and its later amendments or comparable ethical standards. For the type of retrospective study conducted, formal consent was not required for inclusion in this study.

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Krieger, N., Nabavi, S., Waterman, P.D. et al. Feasibility of analyzing DNA copy number variation in breast cancer tumor specimens from 1950 to 2010: how old is too old?. Cancer Causes Control 29, 305–314 (2018). https://doi.org/10.1007/s10552-018-1006-3

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  • DOI: https://doi.org/10.1007/s10552-018-1006-3

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