Tumor Response to Combination Celecoxib and Erlotinib Therapy in Non-small Cell Lung Cancer Is Associated with a Low Baseline Matrix Metalloproteinase-9 and a Decline in Serum-Soluble E-Cadherin

IntroductionCyclooxygenase-2 overexpression may mediate resistance to epidermal growth factor receptor tyrosine kinase inhibition through prostaglandin E2-dependent promotion of epithelial to mesenchymal transition (EMT). Suppression of epithelial markers, such as E-cadherin, can lead to resistance to erlotinib. Prostaglandin E2 down-regulates E-cadherin expression by up-regulating transcriptional repressors, including ZEB1 and Snail. Furthermore, E-cadherin can be modulated by matrix metalloproteinases (MMPs) and tissue inhibitors of MMPs (TIMPs), promoting tumor invasion and metastasis. Markers of EMT and tumor invasion were evaluated in patient serum from a phase I clinical trial investigating the combination of celecoxib and erlotinib in non-small cell lung cancer (NSCLC) patients.MethodsSamples from 22 subjects were evaluated. Soluble E-cadherin (sEC) was evaluated by enzyme linked immunosorbent assay in patient serum at baseline, week 4, and week 8 of treatment. Other markers of EMT and angiogenesis were evaluated by enzyme linked immunosorbent assay, including MMP-9, TIMP-1, and CCL15.ResultsSerum sEC, MMP-9, TIMP-1, and CCL15 levels were determined at baseline and week 8. Patients with a partial response to therapy had a significant decrease in sEC, TIMP-1, and CCL15 at week 8. In patients who responded to the combination therapy, baseline MMP-9 was significantly lower compared with nonresponders (p = 0.006).ConclusionssEC, MMP-9, TIMP-1, and CCL15 levels correlate with response to combination therapy with erlotinib and celecoxib in patients with NSCLC. A randomized phase II trial is planned comparing erlotinib and celecoxib with erlotinib plus placebo in advanced NSCLC. This study will prospectively assess these and other biomarkers in serum and tumor tissue

Chronic IL-1β-induced inflammation regulates epithelial-to-mesenchymal transition memory phenotypes via epigenetic modifications in non-small cell lung cancer.

Chronic inflammation facilitates tumor progression. We discovered that a subset of non-small cell lung cancer cells underwent a gradually progressing epithelial-to-mesenchymal (EMT) phenotype following a 21-day exposure to IL-1β, an abundant proinflammatory cytokine in the at-risk for lung cancer pulmonary and the lung tumor microenvironments. Pathway analysis of the gene expression profile and in vitro functional studies revealed that the EMT and EMT-associated phenotypes, including enhanced cell invasion, PD-L1 upregulation, and chemoresistance, were sustained in the absence of continuous IL-1β exposure. We referred to this phenomenon as EMT memory. Utilizing a doxycycline-controlled SLUG expression system, we found that high expression of the transcription factor SLUG was indispensable for the establishment of EMT memory. High SLUG expression in tumors of lung cancer patients was associated with poor survival. Chemical or genetic inhibition of SLUG upregulation prevented EMT following the acute IL-1β exposure but did not reverse EMT memory. Chromatin immunoprecipitation and methylation-specific PCR further revealed a SLUG-mediated temporal regulation of epigenetic modifications, including accumulation of H3K27, H3K9, and DNA methylation, in the CDH1 (E-cadherin) promoter following the chronic IL-1β exposure. Chemical inhibition of DNA methylation not only restored E-cadherin expression in EMT memory, but also primed cells for chemotherapy-induced apoptosis

Author Correction: Chronic IL-1β-induced inflammation regulates epithelial-to-mesenchymal transition memory phenotypes via epigenetic modifications in non-small cell lung cancer.

An amendment to this paper has been published and can be accessed via a link at the top of the paper

Summarizing performance for genome scale measurement of miRNA: reference samples and metrics

Background: The potential utility of microRNA as biomarkers for early detection of cancer and other diseases is being investigated with genome-scale profiling of differentially expressed microRNA. Processes for measurement assurance are critical components of genome-scale measurements. Here, we evaluated the utility of a set of total RNA samples, designed with between-sample differences in the relative abundance of miRNAs, as process controls. Results: Three pure total human RNA samples (brain, liver, and placenta) and two different mixtures of these components were evaluated as measurement assurance control samples on multiple measurement systems at multiple sites and over multiple rounds. In silico modeling of mixtures provided benchmark values for comparison with physical mixtures. Biomarker development laboratories using next-generation sequencing (NGS) or genome-scale hybridization assays participated in the study and returned data from the samples using their routine workflows. Multiplexed and single assay reverse-transcription PCR (RT-PCR) was used to confirm in silico predicted sample differences. Data visualizations and summary metrics for genome-scale miRNA profiling assessment were developed using this dataset, and a range of performance was observed. These metrics have been incorporated into an online data analysis pipeline and provide a convenient dashboard view of results from experiments following the described design. The website also serves as a repository for the accumulation of performance values providing new participants in the project an opportunity to learn what may be achievable with similar measurement processes. Conclusions: The set of reference samples used in this study provides benchmark values suitable for assessing genome-scale miRNA profiling processes. Incorporation of these metrics into an online resource allows laboratories to periodically evaluate their performance and assess any changes introduced into their measurement process

Summarizing performance for genome scale measurement of miRNA: reference samples and metrics

Background: The potential utility of microRNA as biomarkers for early detection of cancer and other diseases is being investigated with genome-scale profiling of differentially expressed microRNA. Processes for measurement assurance are critical components of genome-scale measurements. Here, we evaluated the utility of a set of total RNA samples, designed with between-sample differences in the relative abundance of miRNAs, as process controls. Results: Three pure total human RNA samples (brain, liver, and placenta) and two different mixtures of these components were evaluated as measurement assurance control samples on multiple measurement systems at multiple sites and over multiple rounds. In silico modeling of mixtures provided benchmark values for comparison with physical mixtures. Biomarker development laboratories using next-generation sequencing (NGS) or genome-scale hybridization assays participated in the study and returned data from the samples using their routine workflows. Multiplexed and single assay reverse-transcription PCR (RT-PCR) was used to confirm in silico predicted sample differences. Data visualizations and summary metrics for genome-scale miRNA profiling assessment were developed using this dataset, and a range of performance was observed. These metrics have been incorporated into an online data analysis pipeline and provide a convenient dashboard view of results from experiments following the described design. The website also serves as a repository for the accumulation of performance values providing new participants in the project an opportunity to learn what may be achievable with similar measurement processes. Conclusions: The set of reference samples used in this study provides benchmark values suitable for assessing genome-scale miRNA profiling processes. Incorporation of these metrics into an online resource allows laboratories to periodically evaluate their performance and assess any changes introduced into their measurement process