Skip to main content
  • Poster presentation
  • Open access
  • Published:

Transcriptome analysis of breast cancer in African American women

Background

Breast cancer is the second most lethal cancer in women. Further, death rates for African American women are the highest for any racial/ethnic group. Hormone receptor status is one of the major prognostic factors and a determinant of treatment options for breast cancer, thus suggesting the importance of molecular level characterization for precision treatments. In this study, we have identified transcriptome level differences correlating to receptor specific molecular subtypes of breast cancer in African American women.

Materials and methods

Clinical and gene expression data from 18 African American women samples were obtained from The Cancer Genome Atlas (TCGA: http://cancergenome.nih.gov/), yielding transcriptome level analysis between four specific subtypes of breast cancer (Table 1).

Table 1 Sample data classification for receptor specific subtype breast cancer. (ER = Estrogen receptor, PgR = Progesterone receptor, Her2 = Human EGF receptor 2).

The samples were analyzed using One-way ANOVA with Welch's correction for unequal sample sizes with type 3 sum of squares. Genes with ANOVA p-value < 0.01 and with relative expression fold change > |2.0| were considered significantly altered; this yielded 90 differentially expressed genes between cancer subtypes in our dataset (Figure 1). Next, we constructed a biological interaction network to impute neighboring genes and proteins using the Michigan Molecular Interactions database (MIMI) and Cytoscape (Figure 2)[1, 2].

Figure 1
figure 1

Hierarchical clustering heat map of significantly altered breast cancer subtype genes in African American women: Green color indicates down-regulated genes and red color indicates up-regulated genes between differing breast cancer subtypes. + and – of subtype are for ER, PgR and Her2.

Figure 2
figure 2

Interactions network Breast Cancer subtypes: Diamond nodes are seed nodes of significantly altered gene transcripts varying between Triple Negative, Her2 over-expressing, Luminal A, and ER+PgR- Her2- Breast Cancer subtypes in African American Women; circular nodes are 1 degree of biological interactions. Red color indicates genes significant in the group (---,++-), yellow indicates genes significant in the group (--+,---), and orange color indicates genes significant in the group (+--,---).

Results

The biological interaction network included important DNA repair sub-networks consisting of BRCA1, SMAD3, SMAD4, EGFR and MDC1 genes[3, 4]. Specifically, MDC1 showed altered expression for all subtypes of breast cancer and a significant p-value for the Luminal A subtype compared to the Triple negative subtype. The MDC1 protein has been previously implicated in the DNA damage response[5] and significant changes similar to the ones observed in this study may provide clues in understanding novel ways to treat breast cancer. Clustering of genes among subtypes, based on significance and fold change data, suggest Luminal A and ER positive subtypes are the most similar. Conversely, the least similar subtypes, based on our analysis, was observed between Her2 over-expressing and Triple negative subtypes.

Conclusions

In conclusion, our results highlight a significant difference in the transcriptome levels of critical DNA repair proteins among the different breast cancer subtypes in African American women. The differentials that were observed stress the importance of molecular level characterizations to understand this disease. Understanding the protein interactions involved in this network will have a major role in predicting best courses of action and aid in precision medicine-based approaches to treating breast cancer.

References

  1. Gao J, Ade AS, Tarcea VG, Weymouth TE, Mirel BR, Jagadish HV, States DJ: Integrating and annotating the interactome using the MiMI plugin for cytoscape. Bioinformatics. 2009, 25 (1): 137-138.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  2. Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, et al: Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003, 13 (11): 2498-2504.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  3. Tommiska J, Bartkova J, Heinonen M, Hautala L, Kilpivaara O, Eerola H, et al: The DNA damage signalling kinase ATM is aberrantly reduced or lost in BRCA1/BRCA2-deficient and ER/PR/ERBB2-triple-negative breast cancer. Oncogene. 2008, 27 (17): 2501-2506.

    Article  PubMed  CAS  Google Scholar 

  4. Guler G, Himmetoglu C, Jimenez RE, Geyer SM, Wang WP, Costinean S, et al: Aberrant expression of DNA damage response proteins is associated with breast cancer subtype and clinical features. Breast Cancer Res Treat. 2011, 129 (2): 421-432.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  5. Prat A, Perou CM: Deconstructing the molecular portraits of breast cancer. Mol Onc. 2011, 5 (1): 5-23.

    Article  CAS  Google Scholar 

Download references

Acknowledgements

NIH grants MD007586 and MD007593 from the National Institute on Minority Health and Health Disparities (NIMHD) and CA166544 from the National Cancer Institute (NCI).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Siddharth Pratap.

Additional information

Shruti S Sakhare, Jamaine Davis contributed equally to this work.

Rights and permissions

Open Access  This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.

The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/.

The Creative Commons Public Domain Dedication waiver (https://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sakhare, S.S., Davis, J., Mandape, S.N. et al. Transcriptome analysis of breast cancer in African American women. BMC Bioinformatics 16 (Suppl 15), P14 (2015). https://doi.org/10.1186/1471-2105-16-S15-P14

Download citation

  • Published:

  • DOI: https://doi.org/10.1186/1471-2105-16-S15-P14

Keywords