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Genomic landscape of ductal carcinoma in situ and association with progression

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Abstract

Purpose

The detection rate of breast ductal carcinoma in situ (DCIS) has increased significantly, raising the concern that DCIS is overdiagnosed and overtreated. Therefore, there is an unmet clinical need to better predict the risk of progression among DCIS patients. Our hypothesis is that by combining molecular signatures with clinicopathologic features, we can elucidate the biology of breast cancer progression, and risk-stratify patients with DCIS.

Methods

Targeted exon sequencing with a custom panel of 223 genes/regions was performed for 125 DCIS cases. Among them, 60 were from cases having concurrent or subsequent invasive breast cancer (IBC) (DCIS + IBC group), and 65 from cases with no IBC development over a median follow-up of 13 years (DCIS-only group). Copy number alterations in chromosome 1q32, 8q24, and 11q13 were analyzed using fluorescence in situ hybridization (FISH). Multivariable logistic regression models were fit to the outcome of DCIS progression to IBC as functions of demographic and clinical features.

Results

We observed recurrent variants of known IBC-related mutations, and the most commonly mutated genes in DCIS were PIK3CA (34.4%) and TP53 (18.4%). There was an inverse association between PIK3CA kinase domain mutations and progression (Odds Ratio [OR] 10.2, p < 0.05). Copy number variations in 1q32 and 8q24 were associated with progression (OR 9.3 and 46, respectively; both p < 0.05).

Conclusions

PIK3CA kinase domain mutations and the absence of copy number gains in DCIS are protective against progression to IBC. These results may guide efforts to distinguish low-risk from high-risk DCIS.

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Acknowledgements

Short-read sequencing assays were performed by the OHSU Massively Parallel Sequencing Shared Resource. We thank Norman Cyr for his artistic contribution to Fig. 2.

Funding

This work is supported by NIH R01CA193694, the Susan and Richard Levy Gift Fund; the Suzanne Pride Bryan Fund for Breast Cancer Research; the Breast Cancer Research Foundation; the Jan Weimer Junior Faculty Chair in Breast Oncology; the BRCA Foundation; and the National Cancer Institute’s Surveillance, Epidemiology and End Results Program under contract HHSN261201000140C awarded to the Cancer Prevention Institute of California. The project was supported by an NIH CTSA award number UL1 RR025744. The collection of cancer incidence data used in this study was supported by the California Department of Health Services as part of the statewide cancer reporting program mandated by California Health and Safety Code Section 103885; the National Cancer Institute’s Surveillance, Epidemiology, and End Results Program under contract HHSN261201000140C awarded to the Cancer Prevention Institute of California, contract HHSN261201000035C awarded to the University of Southern California, and contract HHSN261201000034C awarded to the Public Health Institute; and the Centers for Disease Control and Prevention’s National Program of Cancer Registries, under agreement #1U58 DP000807-01 awarded to the Public Health Institute. The ideas and opinions expressed herein are those of the authors, and endorsements by the University or State of California, the California Department of Health Services, the National Cancer Institute, or the Centers for Disease Control and Prevention or their contractors and subcontractors are neither intentional nor should be inferred.

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Authors and Affiliations

  1. Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA

    Chieh-Yu Lin, Sujay Vennam, Eric Lin, Sushama Varma, Henning Stehr, Megan L. Troxell & Robert B. West

  2. Department of Medicine, Quantitative Sciences Unit, Stanford University, Stanford, CA, USA

    Natasha Purington & Summer Han

  3. Department of Medicine and of Biomedical Data Science, Quantitative Sciences Unit, Stanford University, Stanford, CA, USA

    Manisha Desa

  4. Research Information Technology, Stanford University School of Medicine, Stanford, CA, USA

    Tina Seto

  5. Department of Biomedical Engineering, Oregon Health and Science University, Portland, OR, USA

    Nicholas J. Wang

  6. Departments of Medicine and of Health Research and Policy, Stanford University School of Medicine, Stanford, CA, USA

    Allison W. Kurian

  7. Department of Pathology and Immunology, School of Medicine, Washington University in St. Louis, St. Louis, MO, USA

    Chieh-Yu Lin

Authors
  1. Chieh-Yu Lin
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  2. Sujay Vennam
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  4. Eric Lin
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  13. Robert B. West
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Contributions

RBW conceived and designed the study. CYL conceived and carried out experiments, as well as analyzed the data. S Vennam and HS analyzed the sequencing data (S Venname: single-nucleotide alteration; HS: copy number variations). EL and S Varma carried out the FISH experiments. NJW carried out the targeted exon sequencing. NP, SH, MD, and TS performed biostatistics analysis. MLT conceived the study. AK developed and led the Oncoshare data resource. All authors were involved in writing the paper and gave final approval to the submitted and published versions.

Corresponding author

Correspondence to Robert B. West.

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The authors declare that they have no conflict of interests.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. As stated in the Materials and Methods section, the study was performed with Health Insurance Portability and Accountability Act (HIPAA)-compliant Stanford University Institutional Review Board (IRB) approval (Protocol number 32496). Because archival tissue was used, a waiver of consent was obtained.

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Lin, CY., Vennam, S., Purington, N. et al. Genomic landscape of ductal carcinoma in situ and association with progression. Breast Cancer Res Treat 178, 307–316 (2019). https://doi.org/10.1007/s10549-019-05401-x

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