Genomic and transcriptional studies have now been completed that resolve human breast tumors into distinct subpopulations that progress and respond differently to aggressive chemotherapy. The breast tumor subtypes designated luminal/amplifier and basal respond least well to aggressive chemotherapy so our goal now is to develop more effective therapies against these two subtypes. This will be accomplished through work in three specific aims.
Aim 1. An automated, high throughput approach will be used to assess responses to ~100 FDA approved and experimental drugs (including those developed in other SPORE projects) in a collection of >50 breast cancer cell lines grown in two dimensional cultures in order to identify drugs that are particularly effective against the basal and luminal/amplifier subtypes. Drugs will be ranked for relative effectiveness in the basal and luminal/amplifier subtypes. Those that show high efficacy in either of these subpopulations will be further evaluated in additional breast cancer cell lines developed in this project and then in 3D cultures representative of the basal and luminal/amplifier subtypes. The most effective basal-specific drugs will be passed to the SPORE Project 3 for packaging into nanoparticle constructs that deliver them specifically to the basal tumor cells and/or tested as existing drugs in new trials via our I-SPY neoadjuvant network or in advanced clinical trials.
Aim 2. CLIA compatible multi-gene molecular assays will be developed that define the luminal/amplifier and basal subtypes that can best be attacked using drugs and drug constructs identified in aim 1 in order to guide deployment of these drugs in clinical trials. Multi-gene assays developed in the last project period will be refined through analysis of formalin fixed paraffin embedded samples from the SPORE Tissue and Outcomes Core and then validated in 237 samples from the neoadjuvant I-SPY 1 Trial and further validated in 114 new samples resulting from the I-SPY 1 Amendment trial. Once basal and luminal/amplifier subtype specific drugs are identified, the multivariate assays will be refined to predict individual drug responses.
Aim 3. Molecular mechanisms/pathways that influence response/resistance to the drugs selected in aim 1 will be assessed in order to facilitate selection of synergistic drugs and to guide elucidation of mechanisms of resistance.

National Institute of Health (NIH)
National Cancer Institute (NCI)
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Special Emphasis Panel (ZCA1-RPRB-M)
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University of California San Francisco
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Rice, Megan S; Tamimi, Rulla M; Bertrand, Kimberly A et al. (2018) Does mammographic density mediate risk factor associations with breast cancer? An analysis by tumor characteristics. Breast Cancer Res Treat 170:129-141
Zhou, Yu; Zou, Hao; Yau, Christina et al. (2018) Discovery of internalizing antibodies to basal breast cancer cells. Protein Eng Des Sel 31:17-28
Campbell, Jeffrey I; Yau, Christina; Krass, Polina et al. (2017) Comparison of residual cancer burden, American Joint Committee on Cancer staging and pathologic complete response in breast cancer after neoadjuvant chemotherapy: results from the I-SPY 1 TRIAL (CALGB 150007/150012; ACRIN 6657). Breast Cancer Res Treat 165:181-191
Campbell, Michael J; Baehner, Frederick; O'Meara, Tess et al. (2017) Characterizing the immune microenvironment in high-risk ductal carcinoma in situ of the breast. Breast Cancer Res Treat 161:17-28
Bolan, Patrick J; Kim, Eunhee; Herman, Benjamin A et al. (2017) MR spectroscopy of breast cancer for assessing early treatment response: Results from the ACRIN 6657 MRS trial. J Magn Reson Imaging 46:290-302
Olow, Aleksandra; Chen, Zhongzhong; Niedner, R Hannes et al. (2016) An Atlas of the Human Kinome Reveals the Mutational Landscape Underlying Dysregulated Phosphorylation Cascades in Cancer. Cancer Res 76:1733-45
Takai, Ken; Le, Annie; Weaver, Valerie M et al. (2016) Targeting the cancer-associated fibroblasts as a treatment in triple-negative breast cancer. Oncotarget 7:82889-82901
Hu, Zhi; Mao, Jian-Hua; Curtis, Christina et al. (2016) Genome co-amplification upregulates a mitotic gene network activity that predicts outcome and response to mitotic protein inhibitors in breast cancer. Breast Cancer Res 18:70
Malkov, Serghei; Shepherd, John A; Scott, Christopher G et al. (2016) Mammographic texture and risk of breast cancer by tumor type and estrogen receptor status. Breast Cancer Res 18:122
Gu, Shenda; Hu, Zhi; Ngamcherdtrakul, Worapol et al. (2016) Therapeutic siRNA for drug-resistant HER2-positive breast cancer. Oncotarget 7:14727-41

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