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Transcription profiling of human pancreatic cancer samples: coordinated over-expression of genes in the EGFR pathway predicts sensitivity to EGFR inhibition

ABSTRACT: Tumors from pancreatic cancer specimens obtained at surgery were used for efficacy testing and biologic analysis Experiment Overall Design: Eighteen tumor samples were profiled in duplicates. Ten samples were used in the training set and eight samples were used as the validation set.

ORGANISM(S): Homo sapiens

SUBMITTER: Aik Choon Tan

PROVIDER: E-GEOD-9599 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Coordinated epidermal growth factor receptor pathway gene overexpression predicts epidermal growth factor receptor inhibitor sensitivity in pancreatic cancer.

Jimeno Antonio A Tan Aik Choon AC Coffa Jordy J Rajeshkumar N V NV Kulesza Peter P Rubio-Viqueira Belen B Wheelhouse Jenna J Diosdado Begoña B Messersmith Wells A WA Iacobuzio-Donahue Christine C Maitra Anirban A Varella-Garcia Marileila M Hirsch Fred R FR Meijer Gerrit A GA Hidalgo Manuel M

Cancer research 20080401 8

The epidermal growth factor receptor (EGFR) inhibitor erlotinib is approved for treatment of pancreatic cancer but the overall activity is minimal, and known predictive factors for EGFR inhibitor efficacy are infrequent in this disease. We tested the hypothesis that global activation of the EGFR pathway is predictive of EGFR inhibitor efficacy. Pancreatic cancer tumors directly xenografted at surgery were treated with the EGFR inhibitors erlotinib and cetuximab and analyzed for biological featur ...[more]

PMID: 18413752

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Coordinated over-expression of genes in the EGFR pathway predicts sensitivity to EGFR inhibition in pancreatic cancer

Project description:Tumors from pancreatic cancer specimens obtained at surgery were used for efficacy testing and biologic analysis Keywords: Pharmacogenetics

2008-04-16 | GSE9599 | GEO

Kindlin-1 modulates the EGFR pathway and predicts sensitivity to EGFR inhibitors across cancer types.

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RNAseq of maize stem at three developmental stages

Project description:Eighteen samples from the low, middle and high hybrid at three development stages were used for RNA sequencing.

2018-06-15 | GSE115796 | GEO

Microsecond-timescale MD simulation of EGFR minor mutation predicts the structural flexibility of EGFR kinase core that reflects EGFR inhibitor sensitivity.

Project description:Approximately 15-30% of patients with lung cancer harbor mutations in the EGFR gene. Major EGFR mutations (>90% of EGFR-mutated lung cancer) are highly sensitive to EGFR tyrosine kinase inhibitors (TKIs). Many uncommon EGFR mutations have been identified, but little is known regarding their characteristics, activation, and sensitivity to various EGFR-TKIs, including allosteric inhibitors. We encountered a case harboring an EGFR-L747P mutation, originally misdiagnosed with EGFR-del19 mutation using a routine diagnostic EGFR mutation test, which was resistant to EGFR-TKI gefitinib. Using this minor mutation and common EGFR-activating mutations, we performed the binding free energy calculations and microsecond-timescale molecular dynamic (MD) simulations, revealing that the L747P mutation considerably stabilizes the active conformation through a salt-bridge formation between K745 and E762. We further revealed why several EGFR inhibitors, including the allosteric inhibitor, were ineffective. Our computational structural analysis strategy would be beneficial for future drug development targeting the EGFR minor mutations.

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A Gene Expression Signature Predicts Bladder Cancer Cell Line Sensitivity to EGFR Inhibition.

Project description:Background:Bladder cancer remains a cancer type in need of novel and alternative therapies. While multiple inhibitors of EGFR have been evaluated for efficacy in bladder cancer, the results have largely been disappointing with few patients responding to these therapies. Yet, there is a subset of patients that positively responds to EGFR inhibition with tumor shrinkage, indicating it is an effective treatment for a targeted set of bladder tumors. Objective:To derive a gene expression signature capable of predicting the response to EGFR inhibition in bladder cancer cell lines. Methods:he response to cetuximab for 68 colorectal cancer patients was used as training data to generate a gene expression signature. We applied this signature to bladder cancer cell lines and predictions were compared to the responses to seven EGFR inhibitors. Results:A novel 67-gene signature derived from colorectal cancer was able to significantly identify bladder cancer cell lines by their response to several EGFR inhibitors. Conclusions:The 67-gene signature can determine bladder cancer cell line sensitivity to EGFR inhibition. This work demonstrates a preclinical strategy to identify bladder cancer cell lines for EGFR-targeted therapy.

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Transcriptome analysis of maize hybrid An’nong 591 and its parental lines under heat stress

Project description:Eighteen samples (three replicates) of the maize hybrid An’nong 591 and its parental lines under control and heat treatment were used for RNA sequencing

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An EGFR signature predicts cell line and patient sensitivity to multiple tyrosine kinase inhibitors.

Project description:EGFR is an oncogene with a high frequency of activating mutations in nonsmall cell lung cancer (NSCLC). EGFR inhibitors have been FDA-approved for NSCLC and have shown efficacy in patients with certain EGFR mutations. However, only 9% to 26% of these patients achieve objective responses. In our study, we developed an EGFR gene signature based on The Cancer Genome Atlas (TCGA) RNA-seq data of lung adenocarcinoma (LUAD) to direct the preselection of patients for more effective EGFR-targeted therapy. This signature infers baseline EGFR signaling pathway activity (denoted as EGFR score) in tumor samples, which is associated with tumor sensitivity to EGFR inhibitors and other tyrosine kinase inhibitors (TKIs). EGFR score predicted sensitivity of lung cancer cell lines to Erlotinib, Gefitinib and Sorafenib. Importantly, EGFR score calculated from pretreated samples was associated with patient response to Gefitinib and Sorafenib in lung cancer. Additionally, integration of the EGFR signature with TCGA LUAD data showed that it accurately predicted functional effects of different somatic EGFR mutations, and identified other mutations affecting EGFR pathway activity. Finally, using cancer cell line and clinical trial data, the EGFR score was associated with patient response to TKIs in liver cancer and other cancer types. The EGFR signature provides a useful biomarker that can expand the application of EGFR inhibitors or other TKIs and improve their treatment efficacy through patient stratification.

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Gene expression profiling predicts sensitivity of chronic lymphocytic leukemia cells to dasatinib

Project description:In this study, we used RNA-sequencing to characterize the gene-expression profiles of CLL cells sensitive and resistant to dasatinib and define a specific gene-expression signature associated with drug sensitivity. Specifically, cells were isolated from the blood of 16 newly diagnosed, unselected CLL patients prior to any treatment and classified as responders or non-responders based on in vitro drug cytotoxicity assays. RNA-sequencing analysis of both treated and untreated samples revealed 154 genes differentially expressed between responders and non-responders and, among these, 31 genes were predictive of response in untreated samples. Cells sensitive to dasatinib exhibit increased expression of genes associated with stress signaling, metabolic pathways, including glycolysis, and immune response, including proinflammatory components. Neither of the responder and non-responder groups was enriched for any of the genetic aberrations commonly associated with CLL, as determined by gene mutation and copy-number analysis. We employed the Library of Integrated Network-Based Cellular Signatures (LINCS) database for validation of the obtained gene expression profiles and show, in sum, that dasatinib may represent a viable therapeutic option in a group of CLL patients preselected by gene-expression profiling.

2020-12-29 | GSE151159 | GEO

MAP17 predicts sensitivity to platinum-based therapy, EGFR inhibitors and the proteasome inhibitor bortezomib in lung adenocarcinoma.

Project description:BACKGROUND:The high incidence and mortality of lung tumours is a major health problem. Therefore, the identification both of biomarkers predicting efficacy for therapies in use and of novel efficacious therapeutic agents is crucial to increase patient survival. MAP17 (PDZK1IP1) is a small membrane-bound protein whose upregulation is reported as a common feature in tumours from diverse histological origins. Furthermore, MAP17 is correlated with tumour progression. METHODS:We assessed the expression of MAP17 in preclinical models, including cell lines and patient-derived xenografts (PDXs), assessing its correlation with sensitivity to different standard-of-care drugs in lung adenocarcinoma, as well as novel drugs. At the clinical level, we subsequently correlated MAP17 expression in human tumours with patient response to these therapies. RESULTS:We show that MAP17 expression is induced during lung tumourigenesis, particularly in lung adenocarcinomas, and provide in vitro and in vivo evidence that MAP17 levels predict sensitivity to therapies currently under clinical use in adenocarcinoma tumours, including cisplatin, carboplatin and EGFR inhibitors. In addition, we show that MAP17 expression predicts proteasome inhibitor efficacy in this context and that bortezomib, an FDA-approved drug, may be a novel therapeutic approach for MAP17-overexpressing lung adenocarcinomas. CONCLUSIONS:Our results indicate a potential prognostic role for MAP17 in lung tumours, with particular relevance in lung adenocarcinomas, and highlight the predictive pot0065ntial of this membrane-associated protein for platinum-based therapy and EGFR inhibitor efficacy. Furthermore, we propose bortezomib treatment as a novel and efficacious therapy for lung adenocarcinomas exhibiting high MAP17 expression.

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Radiation induced gene signature predicts pathologic complete response to neoadjuvant chemotherapy in breast cancer patients

Project description:Purpose:The identification of biomarkers predictive of neoadjuvant chemotherapy response in breast cancer patients would be an important advancement in personalized cancer therapy. We hypothesized that due to similarities between radiation and chemotherapy induced cellular response mechanisms, radiation responsive genes may be useful in predicting response to neoadjuvant chemotherapy. Materials and Methods: Murine p53 null breast cancer cell lines representative of the luminal, basal-like and claudin-low human breast cancer subtypes were irradiated to identify radiation responsive genes. These murine radiation induced genes were then converted to their human orthologs. These genes were then used to develop a predictor of pathologic complete response (pCR) that was validated on two independent published neoadjuvant chemotherapy data sets of genomic data with response. Results: A radiation induced gene signature consisting of 30 genes was identified on a training set of 337 human primary breast cancer tumor samples that was prognostic for survival. Mean expression of this signature was calculated for individual samples in two independent published datasets and was found to be significantly predictive of pathologic complete response. Multivariate logistic regression analysis in both independent datasets showed that this 30 gene signature added significant predictive information independent of that provided by standard clinical predictors and other gene expression based predictors of pathologic complete response. Conclusion: This study provides new biologic information regarding response to neoadjuvant chemotherapy and a means of possibly improving the prediction of pathologic complete response.

2015-01-21 | GSE48073 | GEO

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