Esther P. Black

Gene expression patterns that predict sensitivity to epidermal growth factor receptor tyrosine kinase inhibitors in lung cancer cell lines and human lung tumors

BackgroundIncreased focus surrounds identifying patients with advanced non-small cell lung cancer (NSCLC) who will benefit from treatment with epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKI). EGFR mutation, gene copy number, coexpression of ErbB proteins and ligands, and epithelial to mesenchymal transition markers all correlate with EGFR TKI sensitivity, and while prediction of sensitivity using any one of the markers does identify responders, individual markers do not encompass all potential responders due to high levels of inter-patient and inter-tumor variability. We hypothesized that a multivariate predictor of EGFR TKI sensitivity based on gene expression data would offer a clinically useful method of accounting for the increased variability inherent in predicting response to EGFR TKI and for elucidation of mechanisms of aberrant EGFR signalling. Furthermore, we anticipated that this methodology would result in improved predictions compared to single parameters alone both in vitro and in vivo.ResultsGene expression data derived from cell lines that demonstrate differential sensitivity to EGFR TKI, such as erlotinib, were used to generate models for a priori prediction of response. The gene expression signature of EGFR TKI sensitivity displays significant biological relevance in lung cancer biology in that pertinent signalling molecules and downstream effector molecules are present in the signature. Diagonal linear discriminant analysis using this gene signature was highly effective in classifying out-of-sample cancer cell lines by sensitivity to EGFR inhibition, and was more accurate than classifying by mutational status alone. Using the same predictor, we classified human lung adenocarcinomas and captured the majority of tumors with high levels of EGFR activation as well as those harbouring activating mutations in the kinase domain. We have demonstrated that predictive models of EGFR TKI sensitivity can classify both out-of-sample cell lines and lung adenocarcinomas.ConclusionThese data suggest that multivariate predictors of response to EGFR TKI have potential for clinical use and likely provide a robust and accurate predictor of EGFR TKI sensitivity that is not achieved with single biomarkers or clinical characteristics in non-small cell lung cancers.

A microRNA gene expression signature predicts response to erlotinib in epithelial cancer cell lines and targets EMT.

Background:Treatment with epidermal growth factor receptor (EGFR) inhibitors can result in clinical response in non-small-cell lung cancer (NSCLC) and pancreatic ductal adenocarcinoma (PDAC) for some unselected patients. EGFR and KRAS mutation status, amplification of EGFR, or gene expression predictors of response can forecast sensitivity to EGFR inhibition.Methods:Using an NSCLC cell line model system, we identified and characterised microRNA (miRNA) gene expression that predicts response to EGFR inhibition.Results:Expression of 13 miRNA genes predicts response to EGFR inhibition in cancer cell lines and tumours, and discriminates primary from metastatic tumours. Signature genes target proteins that are enriched for epithelial-to-mesenchymal transition (EMT) genes. Epithelial-to-mesenchymal transition predicts EGFR inhibitor resistance and metastatic behaviour. The EMT transcription factor, ZEB1, shows altered expression in erlotinib-sensitive NSCLC and PDAC, where many signature miRNA genes are upregulated. Ectopic expression of mir-200c alters expression of EMT proteins, sensitivity to erlotinib, and migration in lung cells. Treatment with TGFβ1 changes expression of signature miRNA and EMT proteins and modulates migration in lung cells.Conclusion:From these data, we hypothesise that the tumour microenvironment elicits TGFβ1 and stimulates a miRNA gene expression program that induces resistance to anti-EGFR therapy and drives lung tumour cells to EMT, invasion, and metastasis.

Induction of gene pattern changes associated with dysfunctional lipid metabolism induced by dietary fat and exposure to a persistent organic pollutant

Environmental modulators of chronic diseases can include nutrition, lifestyle, as well as exposure to environmental toxicants such as persistent organic pollutants. A study was designed to explore gene expression changes as affected by both dietary fat and exposure to the polychlorinated biphenyl PCB77. Mice were fed for 4 months diets enriched with high-linoleic acid oils (20% and 40% as calories), and during the last 2 months half of each group was exposed to PCB77. Ribonucleic acids (RNA) were extracted from liver tissue to determine gene expression changes using DNA microarray analysis. Our microarray data demonstrated a significant interaction between dietary fat and PCB exposure. Deregulated genes were organized into patterns describing the interaction of diet and PCB exposure. Annotation of the deregulated genes matching these probe sets revealed a significant high-fat mediated induction of genes associated with fatty acid metabolism, triacylglycerol synthesis and cholesterol catabolism, which was down-regulated in animals exposed to PCB77. Many of these genes are regulated by the peroxisome proliferator activated receptor-alpha (PPARalpha), and changes in PPARalpha gene expression followed the same gene pattern as described above. These results provide insight into molecular mechanisms of how dietary fat can interact with environmental pollutants to compromise lipid metabolism.

A gene expression predictor of response to EGFR-targeted therapy stratifies progression-free survival to cetuximab in KRAS wild-type metastatic colorectal cancer.

BackgroundThe anti-EGFR monoclonal antibody cetuximab is used in metastatic colorectal cancer (CRC), and predicting responsive patients garners great interest, due to the high cost of therapy. Mutations in the KRAS gene occur in ~40% of CRC and are a negative predictor of response to cetuximab. However, many KRAS-wildtype patients do not benefit from cetuximab. We previously published a gene expression predictor of sensitivity to erlotinib, an EGFR inhibitor. The purpose of this study was to determine if this predictor could identify KRAS-wildtype CRC patients who will benefit from cetuximab therapy.MethodsMicroarray data from 80 metastatic CRC patients subsequently treated with cetuximab were extracted from the study by Khambata-Ford et al. The study included KRAS status, response, and PFS for each patient. The gene expression data were scaled and analyzed using our predictive model. An improved predictive model of response was identified by removing features in the 180-gene predictor that introduced noise.ResultsForty-three of eighty patients were identified as harboring wildtype-KRAS. When the model was applied to these patients, the predicted-sensitive group had significantly longer PFS than the predicted-resistant group (median 88 days vs. 56 days; mean 117 days vs. 63 days, respectively, p = 0.008). Kaplan-Meier curves were also significantly improved in the predicted-sensitive group (p = 0.0059, HR = 0.4109. The model was simplified to 26 of the original 180 genes and this further improved stratification of PFS (median 147 days vs. 56.5 days in the predicted sensitive and resistant groups, respectively, p < 0.0001). However, the simplified model will require further external validation, as features were selected based on their correlation to PFS in this dataset.ConclusionOur model of sensitivity to EGFR inhibition stratified PFS following cetuximab in KRAS-wildtype CRC patients. This study represents the first true external validation of a molecular predictor of response to cetuximab in KRAS-WT metastatic CRC. Our model may hold clinical utility for identifying patients responsive to cetuximab and may therefore minimize toxicity and cost while maximizing benefit.

Oncogenic Ras and B-Raf Proteins Positively Regulate Death Receptor 5 Expression through Co-activation of ERK and JNK Signaling*

Background: The oncogene Ras induces DR5 expression with undefined mechanism. Results: Both Ras and B-Raf induce DR5 expression through co-activation of ERK and JNK signaling and subsequent cooperative effects among CHOP, Elk1, and c-Jun. Conclusion: Co-activation of ERK and JNK signaling accounts for Ras-induced DR5 expression. Significance: A novel function of DR5 in Ras- or B-Raf-mediated oncogenesis may be suggested. Oncogenic mutations of ras and B-raf frequently occur in many cancer types and are critical for cell transformation and tumorigenesis. Death receptor 5 (DR5) is a cell surface pro-apoptotic death receptor for tumor necrosis factor-related apoptosis-inducing ligand and has been targeted in cancer therapy. The current study has demonstrated induction of DR5 expression by the oncogenic proteins Ras and B-Raf and revealed the underlying mechanisms. We demonstrated that both Ras and B-Raf induce DR5 expression by enforced expression of oncogenic Ras (e.g. H-Ras12V or K-Ras12V) or B-Raf (i.e. V600E) in cells and by analyzing gene expression array data generated from cancer cell lines and from human cancer tissues. This finding is further supported by our results that knockdown of endogenous K-Ras or B-Raf (V600E) reduced the expression of DR5. Importantly, we have elucidated that Ras induces DR5 expression through co-activation of ERK/RSK and JNK signaling pathways and subsequent cooperative effects among the transcriptional factors CHOP, Elk1, and c-Jun to enhance DR5 gene transcription. Moreover, we found that the majority of cancer cell lines highly sensitive to the DR5 agonistic antibody AMG655 have either Ras or B-Raf mutations. Our findings warrant further study on the biology of DR5 regulation by Ras and B-Raf, which may provide new insight into the biology of Ras and B-Raf, and on the potential impact of Ras or B-Raf mutations on the outcome of DR5-targeted cancer therapy.

Deregulation of DUSP activity in EGFR-mutant lung cancer cell lines contributes to sustained ERK1/2 signaling

Lung cancers demonstrate loss of cellular signaling control pathways. EGFR-mutant non-small cell lung cancer cell lines constitutively express active ERK1/2 and require ERK activity for survival. DUSP4 is a negative regulator of ERK activity and is up-regulated in EGFR-mutant lung cancer cell lines relative to K-ras mutant cells. Both DUSP4 and family member, DUSP1, can bind ERK in vitro. However, only DUSP1 has detectable binding to ERK in vivo in cell lines of either genotype. Depletion of DUSP4 in EGFR-mutant cells unexpectedly results in loss of pERK whereas loss of DUSP4 in K-ras mutant cells predictably yields increased pERK. These data support a role for DUSP4, and perhaps DUSP1, as a positive activator of ERK in EGFR-mutant lung cancer cell lines independent of the ability to bind to ERK.

MEK and EGFR inhibition demonstrate synergistic activity in EGFR-dependent NSCLC.

Epidermal growth factor receptor (EGFR) inhibitors are highly effective in treating non-small cell lung cancers (NSCLC) expressing activated EGFR, particularly those harboring EGFR mutations. However, most patients who benefit from EGFR inhibitors achieve only partial responses or stable disease, facilitating the emergence of resistance. Thus, progression-free survival advantages in responding patients are modest. Combination therapy, preferably using agents with synergistic activity, could both improve responses and reduce acquired resistance rates. We hypothesized that combining MEK inhibitors with EGFR inhibitors could result in such a benefit. The MAPK pathway lies downstream of EGFR and transduces both proliferative and survival signals in a variety of cancer types. Inhibitors of this pathway are currently in clinical trials, but little evidence exists supporting the use of these agents as monotherapy in EGFR-dependent non-small cell lung cancer. In this study, we find EGFR-dependent NSCLC cell lines are moderately sensitive to loss of ERK1/2 activity, either by small molecule inhibition or by siRNA knockdown. The consequence of inhibition is dependent upon the trophic content of the culture media, primarily anti-proliferative in serum-rich conditions and pro-apoptotic in serum-poor conditions. However, when ERK inhibition combined with EGFR inhibitors, cytotoxic synergy was observed for all EGFR-dependent cell lines tested in serum-containing media. Enhanced cytotoxicity is demonstrated in cell lines with and without EGFR mutations, including those harboring the T790M escape mutation. These findings support future clinical studies that combine EGFR- and MEK1/2-targeted agents to investigate whether improved outcomes can be achieved in clinically screened EGFR-dependent NSCLC.

Gene Expression Phenotypes of Oncogenic Signaling Pathways

No abstract available.

A pilot common reading experience to integrate basic and clinical sciences in pharmacy education.

Objective. To use a common reading experience that engages students in academic discourse both before and during a PharmD degree program and introduces students to basic science and ethical foundations in health care. Design. First-year (P1) pharmacy students were assigned a nonfiction text to read during the summer prior to admission to be followed by facilitated discussions. Activities using the text were integrated into the first-year curriculum. Pre-experience and post-experience student and faculty survey instruments were administered. Assessment. Students and faculty members reported that 3 first-year courses used the text. Students noted that the texts historical perspective enhanced their understanding of both healthcare delivery and clinical research. Most students (78%) recommended continuation of the common reading experience activity. Conclusion. Students and participating faculty members found the common reading experience, which provided a hub for discussion around issues such as health literacy and ethical treatment of patients, to be a positive addition to the curriculum. Future intentions for this project include expansion across all healthcare colleges at the university.

Statin use and venous thromboembolism in cancer: A large, active comparator, propensity score matched cohort study

BACKGROUND Statins have been shown to have a protective effect for venous thromboembolism (VTE) in the general population. This study sought to assess the association between statins and the risk for cancer-associated deep vein thrombosis (DVT) and pulmonary embolism (PE). METHODS Patients with newly diagnosed cancer were followed for up to one year in a healthcare claims database (2010-2013). Three treatment groups included statin users, non-statin cholesterol lowering medication users, and an untreated group with pre-existing indications for statin therapy (hyperlipidemia, diabetes, or heart disease). Propensity score matched groups were compared using competing risks survival models for DVT and PE outcomes reporting the hazard ratios (HR) between the treatment groups. Sensitivity analyses assessed the influence of age and individual medications. RESULTS The total cohort included 170,459 patients, which, after matching, were similar on baseline characteristics. The overall model showed a statistically significant protective effect for statins compared to no treatment attributed only to leukemia for DVT (HR=0.77, 95% CI 0.61-0.99) and colorectal cancers for PE (HR=0.80, 95% CI 0.64-0.99) in stratified analyses. There were generally no differences in outcomes between statins and non-statins and no individual statin use showed results different from the class effect. CONCLUSIONS In this propensity score matched sample of patients with cancer, statins were shown to have a small protective effect in some cancers for DVT or PE compared to no treatment and little difference compared to an active control group. The lack of effect was consistent across statins and was also not found for any of the sensitivity analyses included.