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A gene expression signature of RAS pathway dependence predicts response to PI3K and RAS pathway inhibitors and expands the population of RAS pathway activated tumors.

ABSTRACT: Hyperactivation of the Ras signaling pathway is a driver of many cancers, and RAS pathway activation can predict response to targeted therapies. Therefore, optimal methods for measuring Ras pathway activation are critical. The main focus of our work was to develop a gene expression signature that is predictive of RAS pathway dependence.We used the coherent expression of RAS pathway-related genes across multiple datasets to derive a RAS pathway gene expression signature and generate RAS pathway activation scores in pre-clinical cancer models and human tumors. We then related this signature to KRAS mutation status and drug response data in pre-clinical and clinical datasets.The RAS signature score is predictive of KRAS mutation status in lung tumors and cell lines with high (> 90%) sensitivity but relatively low (50%) specificity due to samples that have apparent RAS pathway activation in the absence of a KRAS mutation. In lung and breast cancer cell line panels, the RAS pathway signature score correlates with pMEK and pERK expression, and predicts resistance to AKT inhibition and sensitivity to MEK inhibition within both KRAS mutant and KRAS wild-type groups. The RAS pathway signature is upregulated in breast cancer cell lines that have acquired resistance to AKT inhibition, and is downregulated by inhibition of MEK. In lung cancer cell lines knockdown of KRAS using siRNA demonstrates that the RAS pathway signature is a better measure of dependence on RAS compared to KRAS mutation status. In human tumors, the RAS pathway signature is elevated in ER negative breast tumors and lung adenocarcinomas, and predicts resistance to cetuximab in metastatic colorectal cancer.These data demonstrate that the RAS pathway signature is superior to KRAS mutation status for the prediction of dependence on RAS signaling, can predict response to PI3K and RAS pathway inhibitors, and is likely to have the most clinical utility in lung and breast tumors.

SUBMITTER: Loboda A

PROVIDER: S-EPMC2911390 | biostudies-literature | 2010 Jun

REPOSITORIES: biostudies-literature

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A gene expression signature of RAS pathway dependence predicts response to PI3K and RAS pathway inhibitors and expands the population of RAS pathway activated tumors.

Loboda Andrey A Nebozhyn Michael M Klinghoffer Rich R Frazier Jason J Chastain Michael M Arthur William W Roberts Brian B Zhang Theresa T Chenard Melissa M Haines Brian B Andersen Jannik J Nagashima Kumiko K Paweletz Cloud C Lynch Bethany B Feldman Igor I Dai Hongyue H Huang Pearl P Watters James J

BMC medical genomics 20100630

<h4>Background</h4>Hyperactivation of the Ras signaling pathway is a driver of many cancers, and RAS pathway activation can predict response to targeted therapies. Therefore, optimal methods for measuring Ras pathway activation are critical. The main focus of our work was to develop a gene expression signature that is predictive of RAS pathway dependence.<h4>Methods</h4>We used the coherent expression of RAS pathway-related genes across multiple datasets to derive a RAS pathway gene expression s ...[more]

PMID: 20591134

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Project description:Epithelial/mesenchymal transition (EMT) is associated with loss of cell adhesion molecules, such as E-cadherin, and increased invasion, migration, and proliferation in epithelial cancers. In non-small cell lung cancer (NSCLC), EMT is associated with greater resistance to EGFR inhibitors. However, its potential to predict response to other targeted drugs or chemotherapy has not been well characterized. The goal of this study was to develop a robust, platform-independent EMT gene expression signature and to investigate the association of EMT and drug response in NSCLC. A 76-gene EMT signature was derived in 54 DNA-fingerprinted NSCLC cell lines and tested in an independent set of cell lines and in NSCLC patients from the BATTLE clinical trial. The signature classified cell lines as epithelial or mesenchymal independent of the microarray platform and correlated strongly with E-cadherin protein levels, as measured by reverse phase protein array. Higher protein expression of Rab25 (in epithelial lines) and Axl (in mesenchymal lines), two signature genes associated with in EMT in other cancer types, was also confirmed. Mesenchymal cell lines demonstrated significantly greater resistance to EGFR inhibition, independent of EGFR mutation status and were more resistant to drugs targeting the PI3K/Akt pathway. We observed no association between EMT and response to cytotoxic chemotherapies, including cisplatin, pemetrexed, and docetaxel monotherapy and/or doublets (p-values ≥0.2). In NSCLC patients, the EMT signature predicted 8-week disease control in the erlotinib arm, but not in other treatment arms. In conclusion, we have developed a robust EMT signature that predicts resistance to EGFR inhibitors and PI3K/Akt pathway inhibitors. Gene expression profiles were measured in 131 core biopsies from patients with refractory non-small cell lung cancer in the Biomarker-integrated Approaches of Targeted Therapy for Lung Cancer Elimination (BATTLE) trial. We used the BATTLE dataset to test an EMT gene expression signature trained in cell lines and independant of the microarray platform.

Project description:BackgroundPI3K pathway is the most frequently mutated pathway in head and neck squamous cell carcinoma (HNSC), which plays a crucial role in tumorigenesis and progression. In the present study, we aimed to investigate the role of PI3K pathway mutation in clinical prognosis prediction and the relationship with immune microenvironment and response rate to immunotherapy.MethodsWe collected 129 samples with immunotherapy information from MSKCC-2019 cohort as well as 501 and 40 samples from TCGA-HNSC and MD-Anderson non-immunotherapy cohorts, respectively. Somatic mutation data was utilized to characterize the mutational status of the PI3K pathway. Subsequently, we further analyzed the differences in prognosis, immunotherapy response, genomic alterations, functional characteristics, and immune microenvironment between the mutation and wild groups.ResultsThe Kaplan-Meier survival curves displayed that PI3K pathway mutation predicted observably prolonged overall survival (OS) in the immunotherapy cohort MSKCC-2019 (p = 0.012) but did not reach statistical significance in the non-immunotherapy cohorts TCGA-HNSC (p = 0.68) and MD-Anderson (p = 0.68). After incorporating several clinicopathologic features such as age, gender, and tumor mutation burden (TMB), the results of multivariate Cox regression analysis also demonstrated that the PI3K pathway mutation could indicate better immunotherapy outcomes in HNSC patients with a hazard ratio (HR) of 0.533 (95% CI: 0.313-0.910; p = 0.021) in the immunotherapy cohort MSKCC-2019, compared with 0.888 (95% CI: 0.636-1.241; p = 0.487) and 1.939 (95% CI: 0.483-7.781; p = 0.351) in the non-immunotherapy cohorts TCGA-HNSC and MD-Anderson. In addition, the results of the subclass mapping (SubMap) and the tumor immune dysfunction and exclusion (TIDE) also consistently suggested that patients in the mutation group are more likely to benefit from immunotherapy. And further studies showed that the mutation group owned significantly higher TMB, activated immune-related pathways, richer abundance of immune cells, and higher expression levels of immunomodulators. To improve the prognosis of the wild group, we identified five relatively sensitive potential drugs for the wild group, including "BMS-536924," "linsitinib," "NVP-TAE684," "PLX-4720," and "clonazepam."ConclusionsThe PI3K pathway mutation status could be considered as a potential biomarker to predict better immunotherapeutic efficacy and clinical outcomes after immunotherapy in HNSC patients.

Dataset Information

A gene expression signature of RAS pathway dependence predicts response to PI3K and RAS pathway inhibitors and expands the population of RAS pathway activated tumors.

Publications

A gene expression signature of RAS pathway dependence predicts response to PI3K and RAS pathway inhibitors and expands the population of RAS pathway activated tumors.

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