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Genome and Transcriptome Analysis of Lung Cancer Cell Lines

ABSTRACT:

We have used a "chemistry first" approach to discover druggable acquired vulnerabilities that arised in the pathogenesis of non-small cell lung cancer (NSCLC). We screened chemical libraries (~200,000 compounds) for chemical toxins that killed subsets of NSCLC but not normal human lung epithelial cells (HBECs). We first screened a panel of 12 NSCLC lines that represented a variety of known oncogenotypes and identified chemicals with large Z scores and appropriate properties including re-supply, chemistry, and reproducible drug response phenotypes. This was then narrowed down to a list of 202 chemicals and 18 drugs with known targeting (henceforth called "Precision Oncology Probe Set", or POPS). These, and a panel of 30 clinically available drugs, targeted therapies, and drug combinations, already in use or in trials for NSCLC treatment, were then tested on a panel of 96 NSCLC lines for their drug response phenotypes in 12-point dose response curves. This information was analyzed using scanning ranked KS (Kolmogorov-Smirnov) and elastic net biostatistics approaches to identify molecular biomarkers (mutations, mRNA expression, copy number variation, protein expression, and metabolomics) which could predict for sensitivity or resistance to a particular chemical toxin or treatment regimen. From this we have discovered that: our approach identifies already known molecular biomarker of drug sensitivities (e.g. EGFR mutations and EGFR TK inhibitors); many clinically available chemotherapy agents have molecular biomarkers predicting preclinical model drug responses; the POP set of chemical toxins provides novel drug response phenotype patterns in the large NSCLC panel different from those found with clinically available agents including a therapeutic window; many of the POP toxins only hit a small percentage (~5%) of the NSCLC panel but the POP set as a whole provides "coverage" of the entire NSCLC panel; there are simple, one or 2 component molecular biomarkers (mutations, mRNA expression) that predict responses to the different chemical toxins in the NSCLC panel; and that the molecular biomarkers provide some information on the targets and pathways involved in response to the chemical toxins. Thus, we have identified a group of chemical toxins with selectivity for subsets of NSCLC and associated tumor molecular biomarkers to facilitate their development for precision medicine, and also, in some cases, information on the targets and pathways interdicted by these chemical compounds. In addition, we have discovered NSCLC predictive biomarkers for clinically available agents.

PROVIDER: phs001823 | dbGaP |

REPOSITORIES: dbGaP

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			Action	DRS
	GapExchange_phs001823.v1.p1.xml	Xml
	dbGaPEx2.1.5.xsd	Other
	Study_Report.phs001823.LungCancerCellLines.v1.p1.MULTI.pdf	Pdf
	manifest_phs001823.LungCancerCellLines.v1.p1.c1.DS-LC-IRB.pdf	Pdf
	datadict_v2.xsl	Other

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Project description:Purpose: Despite advances in radical surgery and chemotherapy delivery, ovarian cancer is the most lethal gynecologic malignancy. Most of these patients are treated with platinum-based chemotherapies, but there is no biomarker model to guide their responses to these therapeutic agents. We have developed and independently tested our novel multivariate molecular predictors for forecasting patients' responses to individual drugs on a cohort of 58 ovarian cancer patients. Experimental Design: We adapted and applied the previously-published COXEN algorithm to develop molecular predictors for therapeutic responses of patients' tumors based on expression signatures derived from the NCI-60 in vitro drug activities and genomic expression data. Genome-wide candidate biomarkers were first triaged by examining expression patterns of frozen and formalin-fixed paraffin embedded (FFPE) tissue samples. We then identify initial drug sensitivity biomarkers for carboplatin and paclitaxel, respectively. These biomarkers were further narrowed by examining concordant expression patterns between cell lines and a historical set of ovarian cancer patients. Multivariate predictors were obtained from the NCI-60 cell lines and refined using historical patient cohorts. To independent validate these molecular predictors, we performed genome-wide profiling on FFPE samples of 58 ovarian cancer patients obtained prior to adjuvant chemotherapy. Results: Carboplatin predictor significantly stratified platinum sensitive and resistant patients (p = 0.019) with sensitivity = 93%, specificity = 33%, PPV = 65%, and NPV = 78%. Paclitaxel predictor also significantly stratified patients' responses (p = 0.033) with sensitivity = 96%, specificity = 26%, PPV = 61%, and NPV = 86%. The combination predictor for platinum-taxane combination demonstrated a significant survival difference between the predicted responders and nonresponders with median survival of 12.9 months vs. 8.1 months (p = 0.045). Conclusions: COXEN predictors successfully stratified platinum resistance and taxane response in this retrospective cohort, especially based on their FFPE tumor samples. Accurate prediction of chemotherapeutic response, especially to platinum agents is highly clinically relevant and could alter primary management of ovarian cancer. Gene expression data from 58 stage III-IV ovarian cancer patients treated with Carboplatin and Taxol agents

Project description:Two-year rodent bioassays play a central role in evaluating both the carcinogenic potential of a chemical and generating quantitative information on the dose-response behavior for chemical risk assessments. The bioassays involved are expensive and time-consuming, requiring nearly lifetime exposures (two years) in mice and rats and costing $2 to $4 million per chemical. Since there are approximately 80,000 chemicals registered for commercial use in the United States and 2,000 more are added each year, applying animal bioassays to all chemicals of concern is clearly impossible. To efficiently and economically identify carcinogens prior to widespread use and human exposure, alternatives to the two-year rodent bioassay must be developed. In this study, animals were exposed for 13 weeks to 10 chemicals that were positive for liver tumors in the two-year rodent bioassay, 14 chemicals that were negative for liver tumors, and two chemicals that produced an equivocal response. Matched vehicle control groups were run concurrently with each chemical treatment. Gene expression analysis was performed on the livers of the animals to assess the potential for identifying gene expression biomarkers and signaling pathways that can predict tumor formation in a two-year bioassay following a 13 week exposure. Five-week-old female B6C3F1 mice were exposed for 13 weeks to 26 chemicals. The chemical and dose information are provided with the individual sample annotations. With each chemical treatment, a matched vehicle control group was run concurrently with the exposure. A subset of five chemicals, methylene chloride, naphthalene, 1,2,3-trichloropropane, propylene glycol mono-t-butyl ether, and 1,4-dichlorobenzene, were performed in a five-point dose response with matched control groups. The concentrations for these exposures overlapped those in the original cancer bioassay. Gavage exposures were administered 5 days per week and feed exposures were provided 7 days per week. For inhalation exposures, mice were exposed 6 hr per day, 5 days per week. After 13 weeks, animals were euthanized and livers were collected. The right, caudate and median liver lobes were minced together and used for microarray analysis. Microarray analysis was performed on the livers of three to five mice per treatment group.

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Genome and Transcriptome Analysis of Lung Cancer Cell Lines

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