Clinical Implications of profiling tumor heterogeneity in triple negative breast cancer
Rabia A. Gilani1, Evelyn M. Jiagge1, Eric J. Lachacz2,Li Wei Bao1, Xu Cheng1, Sameer Phadke2, Matthew B. Soellner2,Sofia D. Merajver1
1Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA; 2 Departments of Medicinal Chemistry and Chemistry, University of Michigan, Ann Arbor, MI, USA
Triple negative breast cancers (TNBCs) are lethal due to their high metastatic potential and high propensity to recur. Despite initial high sensitivity of TNBCs to chemotherapies, the risk of recurrence within 5 years is around 40%, which is substantially higher than other breast cancer subtypes. One of the key challenges in targeting tnbc is the heterogeneity within the tumor and the complex cellular interactions of the tumor cells with surrounding cells that influence the overall response of cancer cells to chemotherapeutics. To explore cellular heterogeneity inTNBC, we studied patient derived xenograft (PDX) models generated from African (Ghana), African-American, and Caucasian breast cancer patients. Using C1 and BioMark platform for single cell analysis gene expression of a selected panel of genes associated with cancer proliferation metastasis and caner stem cell were determined. RT-qPCR data from the single cells revealed both intertumoral and intratumoral heterogeneity in mRNA expression of the genes associated with metastasis e.g. Vimentin, EpCAM,CDH1, CDH2, TGFb1, cytokeratins, GATA3 and MKI67, YAP1, TM4SF1, TSPAN6, AMOTL2, STAP2 and ANXA3. Among the selected breast cancer stem cell markers, ALDH1a1, ALDH1a3, CD44, CD24, and CD133 were differentially expressed in single cell samples from the PDXs. These data highlight the importance of studying heterogeneous tumors at single-cell resolution to understand the complexity and variability in the gene expression levels within a tumor and thus, discover tarrgets for different clonal populations. Multiplexing and profiling hundreds of these single-cell clones from a patient’s tumor will enable the identification of specific cellular diversity existing within tumors to detect rare preexisting chemo-resistant clones likely to be responsible for drug resistance and tumor relapse.
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