Breast cancer is the most commonly diagnosed non-skin cancer and is a main cause of cancer-related mortality in women worldwide . Breast tumors are highly heterogeneous and are classified based on the expression of estrogen and progesterone receptors and HER2 into ER+, HER2+, and ER-PR-HER2- (triple negative breast cancer, TNBC) disease. The categorization of breast tumors based on hormone receptor and HER2 status and the use of endocrine and HER2-targeted therapy, respectively, are some of the first examples of a molecular-based classification and personalized cancer treatment leading to a meaningful improvement in cancer clinical outcomes [2-7]. Unfortunately, TNBC still lack effective targeted therapy, which in combination with the propensity of this tumor type for early metastatic dissemination results in poor five-year survival rates .
Inflammatory breast cancer (IBC) is a rare, very aggressive subset of the disease accounting for 2-5% of all breast tumors [9, 10]. IBC is characterized by a younger age at diagnosis, a rapid onset of erythema, edema, breast enlargement and pain usually occurring over a three months duration. The incidence of IBC in the US has increased by approximately 25% over the last decade. The overall median survival for IBC remains low (2.9 years) despite improvements in multimodal therapy (i.e., chemotherapy, mastectomy, radiation therapy). Thus, a greater understanding of the molecular etiology of IBC is needed in order to decipher the pathophysiology of the disease and to develop rationally-designed and more effective therapies. IBCs are divided into the same major subtypes non-IBC tumors; however, IBCs are enriched in TNBCs [11, 12]. Preventing the outgrowth of clinically relevant metastatic lesions and their successful treatment are the most challenging areas in breast cancer with the highest impact on survival, as cancer-related death is largely due to metastatic disease. These clinical observations highlight the importance of disease heterogeneity in therapeutic responses and the inadequacy of our knowledge in this area.
The overwhelming majority of breast cancer-related deaths are a result of complications from metastatic disease, which develops due to our inability to effectively prevent the outgrowth of macro-metastatic lesions by neo-adjuvant and adjuvant therapy. Distant metastases are also relatively resistant to treatment in part due to a large tumor burden and selection for cancer cells with the highest fitness during ineffective therapies. Therefore, understanding the mechanisms underlying tumor progression and metastasis is crucial for improved disease control. Intratumor heterogeneity is a major determinant of both metastatic progression and resistance to treatment.
Our laboratories have been analyzing intratumor cellular heterogeneity in breast cancer for genetic and phenotypic features in clinical patient samples, developing xenograft models to test the functional relevance of intratumor heterogeneity for disease progression and therapeutic resistance, and creating mathematical and statistical models based on these experimental data. Building on our prior studies, we now propose to use mathematical models to develop novel treatment strategies for TNBCs and IBCs that more effectively prevent the outgrowth of macro-metastatic lesions and eliminate or control the ones that still emerge despite therapy. The high scientific impact of the proposed studies lies in providing a deeper understanding of how intratumor heterogeneity alters treatment outcome and metastatic progression in breast cancer. As a direct bridge to the clinic, this project will test treatment strategies designed based on our comprehensive understanding of intratumor heterogeneity, its role in disease progression to metastasis, and physical sciences-based approaches to identify best treatment modalities. Enabled by the essential pre-clinical insights gained by this study, our ultimate goal is rapid transition to one or more clinical trials upon completion of the project. Because IBC and TNBC are still only treated with chemotherapies and the majority of patients die of their disease, any new treatment that is predicted to significantly improve survival can quickly be tested in patients and, if proven effective, be adapted as the new standard of care.
Current cancer treatment strategies are designed largely based on empirical traditions and the potential effect of alterations in dosing schedules on therapeutic responses has not been investigated. Similarly, intratumor heterogeneity for targets of cancer therapies and the effects of this on clinical outcomes has not been explored. During the course of the proposed project, we will investigate cellular and molecular changes within breast tumors during different treatments (including novel investigational drugs), design physical sciences-based approaches that will predict the best treatment strategy for a specific tumor, and experimentally test the validity of these predictions.
1. Cancer Trends Progress Report - 2009/2010 Update. Bethesda, MD: National Cancer Institute, NIH, DHHS; 2009.
2. Higgins MJ, Baselga J. Targeted therapies for breast cancer. J Clin Invest. 2011;121(10):3797-803.
3. Higgins MJ, Baselga J. Breast cancer in 2010: Novel targets and therapies for a personalized approach. Nat Rev Clin Oncol. 2011;8(2):65-6.
4. Rexer BN, Arteaga CL. Intrinsic and acquired resistance to HER2-targeted therapies in HER2 gene-amplified breast cancer: mechanisms and clinical implications. Crit Rev Oncog. 2012;17(1):1-16.
5. Arteaga CL, Sliwkowski MX, Osborne CK, Perez EA, Puglisi F, Gianni L. Treatment of HER2-positive breast cancer: current status and future perspectives. Nat Rev Clin Oncol. 2012;9(1):16-32.
6. Geyer FC, Rodrigues DN, Weigelt B, Reis-Filho JS. Molecular classification of estrogen receptor-positive/luminal breast cancers. Adv Anat Pathol. 2012;19(1):39-53.
7. Grann VR, Troxel AB, Zojwalla NJ, Jacobson JS, Hershman D, Neugut AI. Hormone receptor status and survival in a population-based cohort of patients with breast carcinoma. Cancer. 2005;103(11):2241-51.
8. Metzger-Filho O, Tutt A, de Azambuja E, Saini KS, Viale G, Loi S, et al. Dissecting the heterogeneity oftriple-negative breast cancer. J Clin Oncol. 2012;30(15):1879-87.
9. Anderson WF, Schairer C, Chen BE, Hance KW, Levine PH. Epidemiology of inflammatory breast cancer (IBC). Breast Dis. 2005;22:9-23.
10. Hance KW, Anderson WF, Devesa SS, Young HA, Levine PH. Trends in inflammatory breast carcinoma incidence and survival: the surveillance, epidemiology, and end results program at the National Cancer Institute. J Natl Cancer Inst. 2005;97(13):966-75.
11. Van Laere S, Van der Auwera I, Van den Eynden G, Van Hummelen P, van Dam P, Van Marck E, et al. Distinct molecular phenotype of inflammatory breast cancer compared to non-inflammatory breast cancer using Affymetrix-based genome-wide gene-expression analysis. Br J Cancer. 2007;97(8):1165-74.
12. Van Laere SJ, Van der Auwera I, Van den Eynden GG, van Dam P, Van Marck EA, Vermeulen PB, et al. NF-kappaB activation in inflammatory breast cancer is associated with oestrogen receptor downregulation, secondary to EGFR and/or ErbB2 overexpression and MAPK hyperactivation. Br J Cancer. 2007;97(5):659-69.