To evaluate cMET and phospho-cMET (p-cMET) levels in breast cancer subtypes and its impact on survival outcomes.
We measured protein levels of cMET and p-cMET in 257 breast cancers using reverse phase protein array. Regression tree method and Martingale residual plots were applied to find best cutoff point for high and low levels. Kaplan-Meier survival curves were used to estimate relapse-free (RFS) and overall (OS) survival. Cox proportional hazards models were fit to determine associations of cMET/p-cMET with outcomes after adjustment for other characteristics.
Median age was 51years. There were 140 (54.5%) hormone receptor (HR)-positive, 53 (20.6%) HER2-positive and 64 (24.9%) triple-negative tumors. Using selected cutoffs, 181 (70.4%) and 123 (47.9%) cancers had high levels of cMET and p-cMET, respectively. There were no significant differences in mean expression of cMET (P<0.128) and p-cMET (P<0.088) by breast cancer subtype. Dichotomized cMET and p-cMET level was a significant prognostic factor for RFS (HR:2.44,95%CI:1.34-4.44,P=0.003 and HR:1.64,95%CI:1.04-2.60,P=0.033) and OS (HR:3.18,95%CI:1.43-7.11,P=0.003 and HR:1.92,95% CI:1.08-3.44,P=0.025). Within breast cancer subtypes, high cMET levels were associated with worse RFS (P=0.014) and OS (P=0.006) in HR-positive tumors, and high p-cMET levels were associated with worse RFS (P=0.019) and OS (P=0.014) in HER2-positive breast cancers. In multivariable analysis patients with high cMET had a significantly higher risk of recurrence (HR:2.06; 95%CI:1.08-3.94,P=0.028) and death (HR:2.81; 95%CI:1.19-6.64,P=0.019). High p-cMET level was associated with higher risk of recurrence (HR:1.79,95%CI 1.08-2.95.77,P=0.020).
High levels of cMET and p-cMET were seen in all breast cancer subtypes and correlated with poor prognosis.
cMET; phospho-cMET; breast cancer prognosis; breast cancer subtype
The Tuberous Sclerosis Complex 2 (TSC2) gene product, tuberin, acts as a negative regulator of mTOR signaling, and loss of tuberin function leads to tumors of the brain, skin, kidney, heart and lungs. Previous studies have shown that loss of tuberin function affects the stability and subcellular localization of the cyclin-dependent kinase inhibitor (CKI) p27, although the mechanism(s) by which tuberin modulates p27 stability have not been elucidated. Previous studies have also shown that AMPK, which functions in an energy-sensing pathway in the cell, becomes activated in the absence of tuberin. Here we show that in Tsc2-null tumors and cell lines, AMPK activation correlates with an increase in p27 levels, and inhibition of AMPK signaling decreases p27 levels in these cells. In addition, activation of AMPK led to phosphorylation of p27 at the conserved terminal threonine residue of murine p27 (T197) in both in vitro kinase assays and in cells. Phosphorylation of p27 at T197 led to increased interaction between p27 and 14-3-3 proteins and increased the protein stability of p27. Furthermore, activation of AMPK signaling promoted the interaction between p27 and 14-3-3 proteins and increased the stability of the p27 protein in a manner that was dependent on T197. These data identify a conserved mechanism for regulation of p27 stability via phosphorylation at the terminal threonine (mT197/hT198), which when AMPK is activated, results in stabilization of the p27 protein.
Tuberous sclerosis complex; TSC2; energy sensing
Motivation: Protein signaling networks play a key role in cellular function, and their dysregulation is central to many diseases, including cancer. To shed light on signaling network topology in specific contexts, such as cancer, requires interrogation of multiple proteins through time and statistical approaches to make inferences regarding network structure.
Results: In this study, we use dynamic Bayesian networks to make inferences regarding network structure and thereby generate testable hypotheses. We incorporate existing biology using informative network priors, weighted objectively by an empirical Bayes approach, and exploit a connection between variable selection and network inference to enable exact calculation of posterior probabilities of interest. The approach is computationally efficient and essentially free of user-set tuning parameters. Results on data where the true, underlying network is known place the approach favorably relative to existing approaches. We apply these methods to reverse-phase protein array time-course data from a breast cancer cell line (MDA-MB-468) to predict signaling links that we independently validate using targeted inhibition. The methods proposed offer a general approach by which to elucidate molecular networks specific to biological context, including, but not limited to, human cancers.
http://mukherjeelab.nki.nl/DBN (code and data).
email@example.com; firstname.lastname@example.org; email@example.com
Supplementary data are available at Bioinformatics online.
Platinum (Pt)-based antitumor agents are widely used in cancer chemotherapy. Drug resistance is a major obstacle to the successful use of these agents because once drug resistance develops, other effective treatment options are limited. Recently, we have conducted a clinical trial using a copper (Cu)-lowering agent to overcome Pt drug resistance in ovarian cancer patients and the preliminary results are encouraging. In supporting this clinical study, using three pairs of cisplatin (cDDP)-resistant cell lines and two ovarian cancer cell lines derived from patients who had failed in Pt-based chemotherapy, we demonstrated that cDDP resistance associated with reduced expression of the high affinity copper transporter (hCtr1) which is also a cDDP transporter, can be preferentially re-sensitized by copper-lowering agents due to enhanced hCtr1 expression, as compared with their drug-sensitive counterparts. Such a preferential induction of hCtr1 expression in cDDP-resistant variants by Cu chelation can be explained by the mammalian Cu homeostasis regulatory mechanism. Enhanced cell-killing efficacy by a Cu-lowering agent was also observed in animal xenografts bearing cDDP-resistant cells. Finally, by analyzing a public gene expression dataset, we found that ovarian cancer patients with elevated levels of hCtr1 in their tumors, but not ATP7A and ATP7B, had more favorable outcomes after Pt-drug treatment than those expressing low hCtr1 levels. This study reveals the mechanistic basis for using Cu chelation to overcome cDDP resistance in clinical investigations.
Cisplatin; high-affinity copper transporter; Cu-lowering agents; drug-resistance
Driver mutations are somatic mutations that provide growth advantage to tumor cells, while passenger mutations are those not functionally related to oncogenesis. Distinguishing drivers from passengers is challenging because drivers occur much less frequently than passengers, they tend to have low prevalence, their functions are multifactorial and not intuitively obvious. Missense mutations are excellent candidates as drivers, as they occur more frequently and are potentially easier to identify than other types of mutations. Although several methods have been developed for predicting the functional impact of missense mutations, only a few have been specifically designed for identifying driver mutations. As more mutations are being discovered, more accurate predictive models can be developed using machine learning approaches that systematically characterize the commonality and peculiarity of missense mutations under the background of specific cancer types. Here, we present a cancer driver annotation (CanDrA) tool that predicts missense driver mutations based on a set of 95 structural and evolutionary features computed by over 10 functional prediction algorithms such as CHASM, SIFT, and MutationAssessor. Through feature optimization and supervised training, CanDrA outperforms existing tools in analyzing the glioblastoma multiforme and ovarian carcinoma data sets in The Cancer Genome Atlas and the Cancer Cell Line Encyclopedia project.
We tested the hypothesis that allosteric Akt inhibitor MK-2206 inhibits tumor growth, and that PTEN/PIK3CA mutations confer MK-2206 sensitivity.
MK-2206 effects on cell signaling were assessed in vitro and in vivo. Its antitumor efficacy was assessed in vitro in a panel of cancer cell lines with differing PIK3CA and PTEN status. Its in vivo efficacy was tested as a single agent and in combination with paclitaxel.
MK-2206 inhibited Akt signaling and cell-cycle progression, and increased apoptosis in a dose-dependent manner in breast cancer cell lines. Cell lines with PTEN or PIK3CA mutations were significantly more sensitive to MK-2206; however, several lines with PTEN/PIK3CA mutations were MK-2206 resistant. siRNA knockdown of PTEN in breast cancer cells increased Akt phosphorylation concordant with increased MK-2206 sensitivity. Stable transfection of PIK3CA E545K or H1047R mutant plasmids into normal-like MCF10A breast cells enhanced MK-2206 sensitivity. Cell lines that were less sensitive to MK-2206 had lower ratios of Akt1/Akt2 and had less growth inhibition with Akt siRNA knockdown. In PTEN-mutant ZR75-1 breast cancer xenografts, MK-2206 treatment inhibited Akt signaling, cell proliferation, and tumor growth. In vitro, MK-2206 showed a synergistic interaction with paclitaxel in MK-2206–sensitive cell lines, and this combination had significantly greater antitumor efficacy than either agent alone in vivo.
MK-2206 has antitumor activity alone and in combination with chemotherapy. This activity may be greater in tumors with PTEN loss or PIK3CA mutation, providing a strategy for patient enrichment in clinical trials.
Motivation: Network inference approaches are widely used to shed light on regulatory interplay between molecular players such as genes and proteins. Biochemical processes underlying networks of interest (e.g. gene regulatory or protein signalling networks) are generally nonlinear. In many settings, knowledge is available concerning relevant chemical kinetics. However, existing network inference methods for continuous, steady-state data are typically rooted in statistical formulations, which do not exploit chemical kinetics to guide inference.
Results: Herein, we present an approach to network inference for steady-state data that is rooted in non-linear descriptions of biochemical mechanism. We use equilibrium analysis of chemical kinetics to obtain functional forms that are in turn used to infer networks using steady-state data. The approach we propose is directly applicable to conventional steady-state gene expression or proteomic data and does not require knowledge of either network topology or any kinetic parameters. We illustrate the approach in the context of protein phosphorylation networks, using data simulated from a recent mechanistic model and proteomic data from cancer cell lines. In the former, the true network is known and used for assessment, whereas in the latter, results are compared against known biochemistry. We find that the proposed methodology is more effective at estimating network topology than methods based on linear models.
Supplementary data are available at Bioinformatics online.
Cell lines are an important tool in understanding all aspects of cancer growth, development, metastasis, and tumor cell death. There has been a dramatic increase in the number of cell lines and diversity of the cancers they represent; however, misidentification and cross-contamination of cell lines can lead to erroneous conclusions. One method that has gained favor for authenticating cell lines is the use of short tandem repeats (STR) to generate a unique DNA profile. The challenge in validating cell lines is the requirement to compare the large number of existing STR profiles against cell lines of interest, particularly when considering that the profiles of many cell lines have drifted over time and original samples are not available. We report here methods that analyze the variations and the proportional changes extracted from tetra-nucleotide repeat regions in the STR analysis. This technique allows a paired match between a target cell line and a reference database of cell lines to find cell lines that match within a user designated percentage cut-off quality matrix. Our method accounts for DNA instability and can suggest whether the target cell lines are misidentified or unstable.
Short Tandem Repeat (STR); Cell Line Validation
The hepatocyte growth factor (HGF) and its receptor, the transmembrane tyrosine kinase cMET, promote cell proliferation, survival, motility, and invasion as well as morphogenic changes that stimulate tissue repair and regeneration in normal cells but can be co-opted during tumor growth. MET overexpression, with or without gene amplification, has been reported in a variety of human cancers, including breast, lung, and GI malignancies. Furthermore, high levels of HGF and/or cMET correlate with poor prognosis in several tumor types, including breast, ovarian, cervical, gastric, head and neck, and non–small-cell lung cancers. Gene amplification and protein overexpression of cMET drive resistance to epidermal growth factor receptor family inhibitors, both in preclinical models and in patients. It is increasingly apparent that the HGF-cMET axis signaling network is complex, and rational combinatorial therapy is needed for optimal clinical efficacy. Better understanding of HGF-cMET axis signaling and the mechanism of action of HGF-cMET inhibitors, along with the identification of biomarkers of response and resistance, will lead to more effective targeting of this pathway for cancer therapy.
Phosphorylation and activation of Akt1 is a crucial signaling event that promotes adipogenesis. However, neither the complex multistep process that leads to activation of Akt1 through phosphorylation at Thr308 and Ser473 nor the mechanism by which Akt1 stimulates adipogenesis is fully understood. We found that the BSD domain–containing signal transducer and Akt interactor (BSTA) promoted phosphorylation of Akt1 at Ser473 in various human and murine cells, and we uncovered a function for the BSD domain in BSTA-Akt1 complex formation. The mammalian target of rapamycin complex 2 (mTORC2) facilitated the phosphorylation of BSTA and its association with Akt1, and the BSTA-Akt1 interaction promoted the association of mTORC2 with Akt1 and phosphorylation of Akt1 at Ser473 in response to growth factor stimulation. Furthermore, analyses of bsta gene-trap murine embryonic stem cells revealed an essential function for BSTA and phosphorylation of Akt1 at Ser473 in promoting adipocyte differentiation, which required suppression of the expression of the gene encoding the transcription factor FoxC2. These findings indicate that BSTA is a molecular switch that promotes phosphorylation of Akt1 at Ser473 and reveal an mTORC2-BSTA-Akt1-FoxC2–mediated signaling mechanism that is critical for adipocyte differentiation.
The Hippo pathway is crucial in organ size control and its dysregulation contributes to tumorigenesis. However, upstream signals that regulate the mammalian Hippo pathway have remained elusive. Here we report that the Hippo pathway is regulated by G-protein coupled receptor (GPCR) signaling. Serum-borne lysophosphatidic acid (LPA) and sphingosine 1-phosphophate (S1P) act through G12/13-coupled receptors to inhibit the Hippo pathway kinases Lats1/2 thereby activating YAP and TAZ transcription co-activators, which are oncoproteins repressed by Lats1/2. YAP and TAZ are involved in LPA-induced gene expression, cell migration, and proliferation. In contrast, stimulation of Gs-coupled receptors by glucagon or epinephrine activates Lats1/2 kinase activity, thereby inhibiting YAP function. Thus, GPCR signaling can either activate or inhibit the Hippo-YAP pathway depending on the coupled G-protein. Our study identifies extracellular diffusible signals that modulate the Hippo pathway and also establishes the Hippo-YAP pathway as a critical signaling branch downstream of GPCR.
Patients with ovarian cancer are at high risk of tumor recurrence. Prediction of therapy outcome may provide therapeutic avenues to improve patient outcomes. Using reverse-phase protein arrays, we generated ovarian carcinoma protein expression profiles on 412 cases from TCGA and constructed a PRotein-driven index of OVARian cancer (PROVAR). PROVAR significantly discriminated an independent cohort of 226 high-grade serous ovarian carcinomas into groups of high risk and low risk of tumor recurrence as well as short-term and long-term survivors. Comparison with gene expression–based outcome classification models showed a significantly improved capacity of the protein-based PROVAR to predict tumor progression. Identification of protein markers linked to disease recurrence may yield insights into tumor biology. When combined with features known to be associated with outcome, such as BRCA mutation, PROVAR may provide clinically useful predictions of time to tumor recurrence.
Once stimulated, the epidermal growth factor receptor (EGFR) undergoes self-phosphorylation, which, on the one hand, instigates signaling cascades, and on the other hand, recruits CBL ubiquitin ligases, which mark EGFRs for degradation. Using RNA interference screens, we identified a deubiquitinating enzyme, Cezanne-1, that opposes receptor degradation and enhances EGFR signaling. These functions require the catalytic and ubiquitin-binding domains of Cezanne-1, and they involve physical interactions and trans-phosphorylaton of Cezanne-1 by EGFR. In line with the ability of Cezanne-1 to augment EGF-induced growth and migration signals, the enzyme is overexpressed in breast cancer. Congruently, the corresponding gene is amplified in approximately one third of mammary tumors, and high transcript levels predict an aggressive disease course. In conclusion, deubiquitination by Cezanne-1 curtails degradation of growth factor receptors, thereby promotes oncogenic growth signals.
gene amplification; deubiquitination; endocytosis; growth factor
To assess the prognostic value of EGFR molecular characteristics of head and neck squamous cell carcinoma (HNSCC).
Patients and Methods
HNSCC tumors from patients prospectively enrolled in either an Early Detection Research Network (EDRN) study and treated with surgery without an EGFR-targeted agent (N=154) or enrolled in a chemoradiation trial involving the EGFR-targeted antibody cetuximab (N=39) were evaluated for EGFR gene amplification by fluorescence in situ hybridization (FISH) and EGFR protein by immunohistochemical (IHC) staining. Fresh-frozen tumors (EDRN) were also evaluated for EGFR protein and site-specific phosphorylation at Y992 and Y1068 using reverse-phase protein array (RPPA) (n=67). Tumor (n=50) EGFR and EGFRvIII mRNA levels were quantified using real-time PCR.
EGFR expression by IHC was significantly higher in the EDRN tumors with EGFR gene amplification (P<0.001), and a similar trend was noted in the cetuximab-treated cohort. In the EDRN and cetuximab-treated cohorts elevated EGFR by IHC was associated with reduced survival (p=0.019 and p=0.06, respectively). Elevated expression of total EGFR and EGFR PY1068 were independently significantly associated with reduced progression-free survival in the EDRN cohort (HR=2.75; 95% CI=1.26–6.00 and HR=3.29; 95% CI=1.34–8.14, respectively).
In two independent HNSCC cohorts treated with or without cetuximab, tumor EGFR levels were indicative of survival. Tumor EGFR PY1068 levels provided prognostic information independent of total EGFR.
epidermal growth factor receptor; receptor tyrosine kinase; site-specific phosphorylation; prognosis; head and neck cancer
We sought to determine whether PI3K pathway mutation or activation state and rapamycin-induced feedback-loop activation of Akt is associated with rapamycin sensitivity or resistance.
Cancer cell lines were tested for rapamycin-sensitivity, Akt phosphorylation and mTOR target inhibition. Mice injected with breast or neuroendocrine cancer cells and patients with neuroendocrine tumor (NET) were treated with rapalogs, and Akt phosphorylation was assessed.
31 cell lines were rapamycin-sensitive (RS) and 12 were relatively rapamycin-resistant (RR; IC50>100 nM). Cells with PIK3CA and/or PTEN mutations were more likely to be RS (p=0.0123). Akt phosphorylation (S473 and T308) was significantly higher in RS cells (p<0.0001). Rapamycin led to a significantly greater pathway inhibition and greater increase in p-Akt T308 (p<0.0001) and p-Akt S473 (p=0.0009) in RS cells. Rapamycin and everolimus significantly increased Akt phosphorylation but inhibited growth in an in vivo NET model (BON). In patients with NETs treated with everolimus and octreotide, progression-free survival correlated with p-Akt T308 in pretreatment (R=0.4762, p=0.0533) and on-treatment tumor biopsies (R=0.6041, p=0.0102). Patients who had a documented partial response were more likely to have an increase in p-Akt T308 with treatment compared to non-responders (p=0.0146).
PIK3CA/PTEN genomic aberrations and high p-Akt levels are associated with rapamycin sensitivity in vitro. Rapamycin-mediated Akt activation is greater in RS cells, with a similar observation in patients with clinical responses on exploratory biomarker analysis; thus feedback-loop activation of Akt is not a marker of resistance but rather may function as an indicator of rapamycin activity.
Akt; mTOR; rapamycin sensitivity; RPPA; everolimus; pharmacodynamic markers
A central and unresolved question in cancer is how deregulated signaling leads to acquisition of an invasive cellular phenotype. Here, we modeled the invasive transition as a theoretical switch between focal adhesions and extracellular matrix (ECM)-degrading invadopodia and built molecular interaction network models of each structure. To identify upstream regulatory hubs, we added first degree binding partners and applied graph theoretic analyses. Comparison of the results to clustered reverse phase protein array signaling data from head and neck carcinomas led us to choose phosphatidylinositol 3-kinase (PI3K) and protein kinase C alpha (PKCα) for further analysis. Consistent with a previous report, PI3K activity promoted both the formation and activity of invadopodia. Furthermore, PI3K induction of invadopodia was increased by overexpression of SH2 domain-containing inositol 5′-phosphatase 2 (SHIP2), suggesting that a major part of the mechanism is synthesis of PI(3,4,5)P3, a precursor for PI(3,4)P2, which promotes invadopodia formation. Knockdown of PKCα led to divergent effects on invadopodia formation, depending on the activation state of PI3K. Loss of PKCα inhibited invadopodia formation in cells with wild-type PI3K pathway status. Conversely, in cells with either activating PI3K mutants or lacking the endogenous opposing enzyme phosphatase and tensin homolog (PTEN), PKCα knockdown increased invadopodia formation. Investigation of the mechanism revealed that a negative feedback loop from PKCα dampened PI3K activity and invasive behavior in cells with genetic overactivation of the PI3K pathway. These studies demonstrate the potential of network modeling as a discovery tool and identify PI3K and PKCα as critical interacting regulators of invasive behavior.
The interaction of autotaxin with its substrates leads to the production of lysophosphatidic acids (LPA), bioactive lipids with an emerging prominent role in inflammation and cancer. Two papers in this issue tell the previously unknown story of autotaxin, from substrate discrimination to highly efficient local delivery of LPA to target receptors.
To examine gene expression differences between pre- and post-NST specimens of breast cancers and identify biological changers that may lead to new therapeutic insights.
Gene expression data from pre-chemotherapy fine needle aspiration specimens were compared to resected residual cancers in 21 patients after 4-6 months of NST. We removed stroma-associated genes to minimize confounding effects. PAM50 was used to assign molecular class. Paired t-test and gene set analysis were used to identify differentially expressed genes and pathways.
The ER and HER2 status based on mRNA expression remained stable in all but two cases and there were no changes in proliferation metrics (Ki67 and PCNA expression). Molecular class changed in 8 cases (33.3%) usually to normal-like class and which was associated with low residual cancer cell cellularity. The expression of 200-600 probe sets changed between baseline and post-NST samples. In basal-like cancers, pathways driven by increased expression of PI3K, small G proteins and CAMK2 and energy metabolism were enriched while immune cell-derived and the sonic hedgehog pathways were depleted in residual cancer. In non-basal-like breast cancers, notch signaling and energy metabolism (e.g. fatty acid synthesis) were enriched and sonic hedgehog signaling and immune-related pathways were depleted in residual cancer. There was no increase in epithelial mesenchymal transition or cancer stem cell signatures.
Our data indicates that energy metabolism related processes are up-regulated and immune related signals are depleted in residual cancers. Targeting these biological processes may represent promising adjuvant treatment strategies for patients with residual cancer.
Breast Cancer; Neaodjuvant chemotherapy; Gene expression; Residual disease
The PI3K/mTOR-pathway is the most commonly dysregulated pathway in epithelial cancers and represents an important target for cancer therapeutics. Here we show that dual inhibition of PI3K/mTOR in ovarian cancer-spheroids leads to death of inner matrix-deprived cells, whereas matrix-attached cells are resistant. This matrix-associated resistance is mediated by drug-induced upregulation of cellular survival programs that involve both FOXO-regulated transcription and cap-independent translation. Inhibition of any one of several upregulated proteins, including Bcl-2, EGFR, or IGF1R, abrogates resistance to PI3K/mTOR inhibition. These results demonstrate that acute adaptive responses to PI3K/mTOR inhibition in matrix-attached cells resemble well-conserved stress responses to nutrient and growth factor deprivation. Bypass of this resistance mechanism through rational design of drug combinations could significantly enhance PI3K-targeted drug efficacy.