Metastatic breast cancer remains challenging to treat, and most patients ultimately progress on therapy. This acquired drug resistance is largely due to drug-refractory sub-populations (subclones) within heterogeneous tumors. Here, we track the genetic and phenotypic subclonal evolution of four breast cancers through years of treatment to better understand how breast cancers become drug-resistant. Recurrently appearing post-chemotherapy mutations are rare. However, bulk and single-cell RNA sequencing reveal acquisition of malignant phenotypes after treatment, including enhanced mesenchymal and growth factor signaling, which may promote drug resistance, and decreased antigen presentation and TNF-α signaling, which may enable immune system avoidance. Some of these phenotypes pre-exist in pre-treatment subclones that become dominant after chemotherapy, indicating selection for resistance phenotypes. Post-chemotherapy cancer cells are effectively treated with drugs targeting acquired phenotypes. These findings highlight cancer’s ability to evolve phenotypically and suggest a phenotype-targeted treatment strategy that adapts to cancer as it evolves.

Treatment of patients with triple negative (ER-negative, PR-negative, HER2-negative) breast cancer remains a challenge. Although PARP inhibitors are being evaluated in clinical trials, biomarkers are needed to identify patients that will most benefit from anti-PARP therapy. We determined the response of three PARP inhibitors: veliparib, olaparib, and talazoparib in a panel of eight triple-negative breast cancer cell lines. Therapeutic responses and cellular phenotypes were elucidated using high-content imaging and quantitative immunofluorescence to assess markers of DNA damage (53BP1) and apoptosis (cleaved-PARP). We determined the pharmacodynamic changes in percentage of cells positive for 53BP1, mean number of 53BP1 foci per cell, and percentage of cells positive for cleaved-PARP. Inspired by traditional dose-response measures of cell viability, an EC50 value was calculated for each cellular phenotype for each PARP inhibitor. The EC50 values for both 53BP1 metrics strongly correlated with IC50 values for each PARP inhibitor. Pathway enrichment analysis identified a set of DNA repair and cell cycle associated genes that were associated with 53BP1 response following PARP inhibition. The overall accuracy of our 63 gene set in predicting response to olaparib in seven breast cancer patient-derived xenograft tumors was 86%. In triple-negative breast cancer patients not treated with anti-PARP therapy, the predicted response rate of our gene signature was 45%. These results indicate that 53BP1 is a biomarker of response to anti-PARP therapy in the laboratory, and our DNA damage response gene signature may be used to identify patients who are most likely to respond to PARP inhibition.

Purpose: Imaging mass cytometry (IMC) uses metalconjugated antibodies to provide multidimensional, objective measurement of protein targets. We used this highthroughput platform to perform an 18-plex assessment of HER2 ICD/ECD, cytotoxic T-cell infiltration and other structural and signaling proteins in a cohort of patients treated with trastuzumab to discover associations with trastuzumab benefit. Experimental Design: An antibody panel for detection of 18 targets (pan-cytokeratin, HER2 ICD, HER2 ECD, CD8, vimentin, cytokeratin 7, b-catenin, HER3, MET, EGFR, ERK 1-2, MEK 1-2, PTEN, PI3K p110 a, Akt, mTOR, Ki67, and Histone H3) was used with a selection of trastuzumab-treated patients from the Hellenic Cooperative Oncology Group 10/ 05 trial (n ¼ 180), and identified a case-control series. Results: Patients that recurred after adjuvant treatment with trastuzumab trended toward a decreased fraction of HER2 ECD pixels over threshold compared with cases without recurrence (P ¼ 0.057). After exclusion of the lowest HER2 expressers, 5-year recurrence events were associated with reduced total extracellular domain (ECD)/intracellular domain (ICD) ratio intensity in tumor (P ¼ 0.044). These observations are consistent with our previous work using quantitative immunofluorescence, but represent the proof on identical cell content. We also describe the association of the ECD of HER2 with CD8 T-cell infiltration on the same slide. Conclusions: The proximity of CD8 cells as a function of the expression of the ECD of HER2 provides further evidence for the role of the immune system in the mechanism of action of trastuzumab.

We report here on experimental and theoretical efforts to determine how best to combine drugs that inhibit HER2 and AKT in HER2+ breast cancers. We accomplished this by measuring cellular and molecular responses to lapatinib and the AKT inhibitors (AKTi) GSK690693 and GSK2141795 in a panel of 22 HER2+ breast cancer cell lines carrying wild type or mutant PIK3CA. We observed that combinations of lapatinib plus AKTi were synergistic in HER2+/PIK3CAmut cell lines but not in HER2+/PIK3CAwt cell lines. We measured changes in phospho-protein levels in 15 cell lines after treatment with lapatinib, AKTi or lapatinib + AKTi to shed light on the underlying signaling dynamics. This revealed that p-S6RP levels were less well attenuated by lapatinib in HER2+/PIK3CAmut cells compared to HER2+/PIK3CAwt cells and that lapatinib + AKTi reduced p-S6RP levels to those achieved in HER2+/PIK3CAwt cells with lapatinib alone. We also found that that compensatory up-regulation of p-HER3 and p-HER2 is blunted in PIK3CAmut cells following lapatinib + AKTi treatment. Responses of HER2+ SKBR3 cells transfected with lentiviruses carrying control or PIK3CAmut sequences were similar to those observed in HER2+/PIK3CAmut cell lines but not in HER2+/PIK3CAwt cell lines. We used a nonlinear ordinary differential equation model to support the idea that PIK3CA mutations act as downstream activators of AKT that blunt lapatinib inhibition of downstream AKT signaling and that the effects of PIK3CA mutations can be countered by combining lapatinib with an AKTi. This combination does not confer substantial benefit beyond lapatinib in HER2+/PIK3CAwt cells.

BackgroundHigh mitotic activity is associated with the genesis and progression of many cancers. Small molecule inhibitors of mitotic apparatus proteins are now being developed and evaluated clinically as anticancer agents. With clinical trials of several of these experimental compounds underway, it is important to understand the molecular mechanisms that determine high mitotic activity, identify tumor subtypes that carry molecular aberrations that confer high mitotic activity, and to develop molecular markers that distinguish which tumors will be most responsive to mitotic apparatus inhibitors.MethodsWe identified a coordinately regulated mitotic apparatus network by analyzing gene expression profiles for 53 malignant and non-malignant human breast cancer cell lines and two separate primary breast tumor datasets. We defined the mitotic network activity index (MNAI) as the sum of the transcriptional levels of the 54 coordinately regulated mitotic apparatus genes. The effect of those genes on cell growth was evaluated by small interfering RNA (siRNA).ResultsHigh MNAI was enriched in basal-like breast tumors and was associated with reduced survival duration and preferential sensitivity to inhibitors of the mitotic apparatus proteins, polo-like kinase, centromere associated protein E and aurora kinase designated GSK462364, GSK923295 and GSK1070916, respectively. Co-amplification of regions of chromosomes 8q24, 10p15-p12, 12p13, and 17q24-q25 was associated with the transcriptional upregulation of this network of 54 mitotic apparatus genes, and we identify transcription factors that localize to these regions and putatively regulate mitotic activity. Knockdown of the mitotic network by siRNA identified 22 genes that might be considered as additional therapeutic targets for this clinically relevant patient subgroup.ConclusionsWe define a molecular signature which may guide therapeutic approaches for tumors with high mitotic network activity.Electronic supplementary materialThe online version of this article (doi:10.1186/s13058-016-0728-y) contains supplementary material, which is available to authorized users.