TNBC response to paclitaxel phenocopies interferon response which reveals cell cycle-associated resistance mechanisms.

Paclitaxel is a standard of care neoadjuvant therapy for patients with triple negative breast cancer (TNBC); however, it shows limited benefit for locally advanced or metastatic disease. Here we used a coordinated experimental-computational approach to explore the influence of paclitaxel on the cellular and molecular responses of TNBC cells. We found that escalating doses of paclitaxel resulted in multinucleation, promotion of senescence, and initiation of DNA damage induced apoptosis. Single-cell RNA sequencing (scRNA-seq) of TNBC cells after paclitaxel treatment revealed upregulation of innate immune programs canonically associated with interferon response and downregulation of cell cycle progression programs. Systematic exploration of transcriptional responses to paclitaxel and cancer-associated microenvironmental factors revealed common gene programs induced by paclitaxel, IFNB, and IFNG. Transcription factor (TF) enrichment analysis identified 13 TFs that were both enriched based on activity of downstream targets and also significantly upregulated after paclitaxel treatment. Functional assessment with siRNA knockdown confirmed that the TFs FOSL1, NFE2L2 and ELF3 mediate cellular proliferation and also regulate nuclear structure. We further explored the influence of these TFs on paclitaxel-induced cell cycle behavior via live cell imaging, which revealed altered progression rates through G1, S/G2 and M phases. We found that ELF3 knockdown synergized with paclitaxel treatment to lock cells in a G1 state and prevent cell cycle progression. Analysis of publicly available breast cancer patient data showed that high ELF3 expression was associated with poor prognosis and enrichment programs associated with cell cycle progression. Together these analyses disentangle the diverse aspects of paclitaxel response and identify ELF3 upregulation as a putative biomarker of paclitaxel resistance in TNBC.

Analysis and modeling of cancer drug responses using cell cycle phase-specific rate effects.

Identifying effective therapeutic treatment strategies is a major challenge to improving outcomes for patients with breast cancer. To gain a comprehensive understanding of how clinically relevant anti-cancer agents modulate cell cycle progression, here we use genetically engineered breast cancer cell lines to track drug-induced changes in cell number and cell cycle phase to reveal drug-specific cell cycle effects that vary across time. We use a linear chain trick (LCT) computational model, which faithfully captures drug-induced dynamic responses, correctly infers drug effects, and reproduces influences on specific cell cycle phases. We use the LCT model to predict the effects of unseen drug combinations and confirm these in independent validation experiments. Our integrated experimental and modeling approach opens avenues to assess drug responses, predict effective drug combinations, and identify optimal drug sequencing strategies.

A multi-omic analysis of MCF10A cells provides a resource for integrative assessment of ligand-mediated molecular and phenotypic responses.

The phenotype of a cell and its underlying molecular state is strongly influenced by extracellular signals, including growth factors, hormones, and extracellular matrix proteins. While these signals are normally tightly controlled, their dysregulation leads to phenotypic and molecular states associated with diverse diseases. To develop a detailed understanding of the linkage between molecular and phenotypic changes, we generated a comprehensive dataset that catalogs the transcriptional, proteomic, epigenomic and phenotypic responses of MCF10A mammary epithelial cells after exposure to the ligands EGF, HGF, OSM, IFNG, TGFB and BMP2. Systematic assessment of the molecular and cellular phenotypes induced by these ligands comprise the LINCS Microenvironment (ME) perturbation dataset, which has been curated and made publicly available for community-wide analysis and development of novel computational methods ( synapse.org/LINCS_MCF10A ). In illustrative analyses, we demonstrate how this dataset can be used to discover functionally related molecular features linked to specific cellular phenotypes. Beyond these analyses, this dataset will serve as a resource for the broader scientific community to mine for biological insights, to compare signals carried across distinct molecular modalities, and to develop new computational methods for integrative data analysis.

INHBA is a mediator of aggressive tumor behavior in HER2+ basal breast cancer.

BACKGROUND: Resistance to HER2-targeted therapeutics remains a significant clinical problem in HER2+ breast cancer patients with advanced disease. This may be particularly true for HER2+ patients with basal subtype disease, as recent evidence suggests they receive limited benefit from standard of care HER2-targeted therapies. Identification of drivers of resistance and aggressive disease that can be targeted clinically has the potential to impact patient outcomes. METHODS: We performed siRNA knockdown screens of genes differentially expressed between lapatinib-responsive and -resistant HER2+ breast cancer cells, which corresponded largely to luminal versus basal subtypes. We then validated hits in 2-d and 3-d cell culture systems. RESULTS: Knockdown of one of the genes, INHBA, significantly slowed growth and increased sensitivity to lapatinib in multiple basal HER2+ cell lines in both 2-d and 3-d cultures, but had no effect in luminal HER2+ cells. Loss of INHBA altered metabolism, eliciting a shift from glycolytic to oxidative phosphorylative metabolism, which was also associated with a decrease in tumor invasiveness. Analysis of breast cancer datasets showed that patients with HER2+ breast cancer and high levels of INHBA expression had worse outcomes than patients with low levels of INHBA expression. CONCLUSIONS: Our data suggest that INHBA is associated with aggressiveness of the basal subtype of HER2+ tumors, resulting in poor response to HER2-targeted therapy and an invasive phenotype. We hypothesize that targeting this pathway could be an effective therapeutic strategy to reduce invasiveness of tumor cells and to improve therapeutic response.

Sensitivity to targeted therapy differs between HER2-amplified breast cancer cells harboring kinase and helical domain mutations in PIK3CA.

BACKGROUND: HER2-amplified breast cancer is a clinically defined subtype of breast cancer for which there are multiple viable targeted therapies. Resistance to these targeted therapies is a common problem, but the mechanisms by which resistance occurs remain incompletely defined. One mechanism that has been proposed is through mutation of genes in the PI3-kinase pathway. Intracellular signaling from the HER2 pathway can occur through PI3-kinase, and mutations of the encoding gene PIK3CA are known to be oncogenic. Mutations in PIK3CA co-occur with HER2-amplification in ~ 20% of cases within the HER2-amplified subtype. METHODS: We generated isogenic knockin mutants of each PIK3CA hotspot mutation in HER2-amplified breast cancer cells using adeno-associated virus-mediated gene targeting. Isogenic clones were analyzed using a combinatorial drug screen to determine differential responses to HER2-targeted therapy. Western blot analysis and immunofluorescence uncovered unique intracellular signaling dynamics in cells resistant to HER2-targeted therapy. Subsequent combinatorial drug screens were used to explore neuregulin-1-mediated resistance to HER2-targeted therapy. Finally, results from in vitro experiments were extrapolated to publicly available datasets. RESULTS: Treatment with HER2-targeted therapy reveals that mutations in the kinase domain (H1047R) but not the helical domain (E545K) increase resistance to lapatinib. Mechanistically, sustained AKT signaling drives lapatinib resistance in cells with the kinase domain mutation, as demonstrated by staining for the intracellular product of PI3-kinase, PIP3. This resistance can be overcome by co-treatment with an inhibitor to the downstream kinase AKT. Additionally, knockout of the PIP3 phosphatase, PTEN, phenocopies this result. We also show that neuregulin-1, a ligand for HER-family receptors, confers resistance to cells harboring either hotspot mutation and modulates response to combinatorial therapy. Finally, we show clinical evidence that the hotspot mutations have distinct expression profiles related to therapeutic resistance through analysis of TCGA and METABRIC data cohorts. CONCLUSION: Our results demonstrate unique intracellular signaling differences depending on which mutation in PIK3CA the cell harbors. Only mutations in the kinase domain fully activate the PI3-kinase signaling pathway and maintain downstream signaling in the presence of HER2 inhibition. Moreover, we show there is potentially clinical importance in understanding both the PIK3CA mutational status and levels of neuregulin-1 expression in patients with HER2-amplified breast cancer treated with targeted therapy and that these problems warrant further pre-clinical and clinical testing.

Enzalutamide response in a panel of prostate cancer cell lines reveals a role for glucocorticoid receptor in enzalutamide resistant disease.

Representative in vitro model systems that accurately model response to therapy and allow the identification of new targets are important for improving our treatment of prostate cancer. Here we describe molecular characterization and drug testing in a panel of 20 prostate cancer cell lines. The cell lines cluster into distinct subsets based on RNA expression, which is largely driven by functional Androgen Receptor (AR) expression. KLK3, the AR-responsive gene that encodes prostate specific antigen, shows the greatest variability in expression across the cell line panel. Other common prostate cancer associated genes such as TMPRSS2 and ERG show similar expression patterns. Copy number analysis demonstrates that many of the most commonly gained (including regions containing TERC and MYC) and lost regions (including regions containing TP53 and PTEN) that were identified in patient samples by the TCGA are mirrored in the prostate cancer cell lines. Assessment of response to the anti-androgen enzalutamide shows a distinct separation of responders and non-responders, predominantly related to status of wild-type AR. Surprisingly, several AR-null lines responded to enzalutamide. These AR-null, enzalutamide-responsive cells were characterized by high levels of expression of glucocorticoid receptor (GR) encoded by NR3C1. Treatment of these cells with the anti-GR agent mifepristone showed that they were more sensitive to this drug than enzalutamide, as were several of the enzalutamide non-responsive lines. This is consistent with several recent reports that suggest that GR expression is an alternative signaling mechanism that can bypass AR blockade. This study reinforces the utility of large cell line panels for the study of cancer and identifies several cell lines that represent ideal models to study AR-null cells that have upregulated GR to sustain growth.

Microenvironment-Mediated Mechanisms of Resistance to HER2 Inhibitors Differ between HER2+ Breast Cancer Subtypes.

Extrinsic signals are implicated in breast cancer resistance to HER2-targeted tyrosine kinase inhibitors (TKIs). To examine how microenvironmental signals influence resistance, we monitored TKI-treated breast cancer cell lines grown on microenvironment microarrays composed of printed extracellular matrix proteins supplemented with soluble proteins. We tested ∼2,500 combinations of 56 soluble and 46 matrix microenvironmental proteins on basal-like HER2+ (HER2E) or luminal-like HER2+ (L-HER2+) cells treated with the TKIs lapatinib or neratinib. In HER2E cells, hepatocyte growth factor, a ligand for MET, induced resistance that could be reversed with crizotinib, an inhibitor of MET. In L-HER2+ cells, neuregulin1-ß1 (NRG1ß), a ligand for HER3, induced resistance that could be reversed with pertuzumab, an inhibitor of HER2-HER3 heterodimerization. The subtype-specific responses were also observed in 3D cultures and murine xenografts. These results, along with bioinformatic pathway analysis and siRNA knockdown experiments, suggest different mechanisms of resistance specific to each HER2+ subtype: MET signaling for HER2E and HER2-HER3 heterodimerization for L-HER2+ cells.

Pathway-Enriched Gene Signature Associated with 53BP1 Response to PARP Inhibition in Triple-Negative Breast Cancer.

Effective 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 who will most benefit from anti-PARP therapy. We determined the responses 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 as 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 and 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 who had not received 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. Mol Cancer Ther; 16(12); 2892-901. ©2017 AACR.

Akt3 controls vascular endothelial growth factor secretion and angiogenesis in ovarian cancer cells.

The PI3 kinase/Akt pathway is commonly deregulated in human cancers, functioning in such processes as proliferation, glucose metabolism, survival and motility. We have previously described a novel function for one of the Akt isoforms (Akt3) in primary endothelial cells: the control of VEGF-induced mitochondrial biogenesis. We sought to determine if Akt3 played a similar role in carcinoma cells. Because the PI3 kinase/Akt pathway has been strongly implicated as a key regulator in ovarian carcinoma, we tested the role of Akt3 in this tumor type. Silencing of Akt3 by shRNA did not cause an overt reduction in mitochondrial gene expression in a series of PTEN positive ovarian cancer cells. Rather, we find that blockade of Akt3, results in smaller, less vascularized tumors in a xenograft mouse model that is correlated with a reduction in VEGF expression. We find that blockade of Akt3, but not Akt1, results in a reduction in VEGF secretion and retention of VEGF protein in the endoplasmic reticulum (ER). The reduction in secretion under conditions of Akt3 blockade is, at least in part, due to the down regulation of the resident golgi protein and reported tumor cell marker, RCAS1. Conversely, over-expression of Akt3 results in an increase in RCAS1 expression and in VEGF secretion. Silencing of RCAS1 using siRNA inhibits VEGF secretion. These findings suggest an important role for Akt3 in the regulation of RCAS1 and VEGF secretion in ovarian cancer cells.

VEGF stimulation of mitochondrial biogenesis: requirement of AKT3 kinase.

The growth factor, vascular endothelial growth factor (VEGF), induces angiogenesis and promotes endothelial cell (EC) proliferation. Affymetrix gene array analyses show that VEGF stimulates the expression of a cluster of nuclear-encoded mitochondrial genes, suggesting a role for VEGF in the regulation of mitochondrial biogenesis. We show that the serine threonine kinase Akt3 specifically links VEGF to mitochondrial biogenesis. A direct comparison of Akt1 vs. Akt3 gene silencing was performed in ECs and has uncovered a discrete role for Akt3 in the control of mitochondrial biogenesis. Silencing of Akt3, but not Akt1, results in a decrease in mitochondrial gene expression and mtDNA content. Nuclear-encoded mitochondrial gene transcripts are also found to decrease when Akt3 expression is silenced. Concurrent with these changes in mitochondrial gene expression, lower O(2) consumption was observed. VEGF stimulation of the major mitochondrial import protein TOM70 is also blocked by Akt3 inhibition. In support of a role for Akt3 in the regulation of mitochondrial biogenesis, Akt3 silencing results in the cytoplasmic accumulation of the master regulator of mitochondrial biogenesis, PGC-1alpha, and a reduction in known PGC-1alpha target genes. Finally, a subtle but significant, abnormal mitochondrial phenotype is observed in the brain tissue of AKT3 knockout mice. These results suggest that Akt3 is important in coordinating mitochondrial biogenesis with growth factor-induced increases in cellular energy demands.