Lisa Turner

Bio: Lisa Turner is an academic researcher from Van Andel Institute. The author has contributed to research in topics: Biology & Cancer research. The author has an hindex of 5, co-authored 10 publications receiving 5067 citations.

The Genotype-Tissue Expression (GTEx) project

Abstract: Genome-wide association studies have identified thousands of loci for common diseases, but, for the majority of these, the mechanisms underlying disease susceptibility remain unknown. Most associated variants are not correlated with protein-coding changes, suggesting that polymorphisms in regulatory regions probably contribute to many disease phenotypes. Here we describe the Genotype-Tissue Expression (GTEx) project, which will establish a resource database and associated tissue bank for the scientific community to study the relationship between genetic variation and gene expression in human tissues.

Identification of Mithramycin Analogues with Improved Targeting of the EWS-FLI1 Transcription Factor

Abstract: Purpose: The goal of this study was to identify second-generation mithramycin analogs that better target the EWS-FLI1 transcription factor for Ewing sarcoma. We previously established mithramycin as an EWS-FLI1 inhibitor, but the compound9s toxicity prevented its use at effective concentrations in patients. Experimental Design: We screened a panel of mithralogs to establish their ability to inhibit EWS-FLI1 in Ewing sarcoma. We compared the IC50 to the maximum tolerated dose established in mice to determine the relationship between efficacy and toxicity. We confirmed the suppression of EWS-FLI1 at the promoter, mRNA, gene signature, and protein levels. We established an improved therapeutic window by using time-lapse microscopy to model the effects on cellular proliferation in Ewing sarcoma cells relative to HepG2 control cells. Finally, we established an improved therapeutic window using a xenograft model of Ewing sarcoma. Results: EC-8105 was found to be the most potent analog and was able to suppress EWS-FLI1 activity at concentrations nontoxic to other cell types. EC-8042 was substantially less toxic than mithramycin in multiple species but maintained suppression of EWS-FLI1 at similar concentrations. Both compounds markedly suppressed Ewing sarcoma xenograft growth and inhibited EWS-FLI1 in vivo. Conclusions: These results provide a basis for the continued development of EC-8042 and EC-8105 as EWS-FLI1 inhibitors for the clinic.

Lurbinectedin Inactivates the Ewing Sarcoma Oncoprotein EWS-FLI1 by Redistributing It within the Nucleus.

Abstract: There is a great need to develop novel approaches to target oncogenic transcription factors with small molecules. Ewing sarcoma is emblematic of this need, as it depends on the continued activity of the EWS-FLI1 transcription factor to maintain the malignant phenotype. We have previously shown that the small molecule trabectedin interferes with EWS-FLI1. Here, we report important mechanistic advances and a second-generation inhibitor to provide insight into the therapeutic targeting of EWS-FLI1. We discovered that trabectedin functionally inactivated EWS-FLI1 by redistributing the protein within the nucleus to the nucleolus. This effect was rooted in the wild-type functions of the EWSR1, compromising the N-terminal half of the chimeric oncoprotein, which is known to be similarly redistributed within the nucleus in the presence of UV light damage. A second-generation trabectedin analogue lurbinectedin (PM01183) caused the same nuclear redistribution of EWS-FLI1, leading to a loss of activity at the promoter, mRNA, and protein levels of expression. Tumor xenograft studies confirmed this effect, and it was increased in combination with irinotecan, leading to tumor regression and replacement of Ewing sarcoma cells with benign fat cells. The net result of combined lurbinectedin and irinotecan treatment was a complete reversal of EWS-FLI1 activity and elimination of established tumors in 30% to 70% of mice after only 11 days of therapy. Our results illustrate the preclinical safety and efficacy of a disease-specific therapy targeting the central oncogenic driver in Ewing sarcoma. Cancer Res; 76(22); 6657-68. ©2016 AACR.

Targeting MET and EGFR crosstalk signaling in triple-negative breast cancers.

Abstract: There is a vital need for improved therapeutic strategies that are effective in both primary and metastatic triple-negative breast cancer (TNBC). Current treatment options for TNBC patients are restricted to chemotherapy; however tyrosine kinases are promising druggable targets due to their high expression in multiple TNBC subtypes. Since coexpression of receptor tyrosine kinases (RTKs) can promote signaling crosstalk and cell survival in the presence of kinase inhibitors, it is likely that multiple RTKs will need to be inhibited to enhance therapeutic benefit and prevent resistance. The MET and EGFR receptors are actionable targets due to their high expression in TNBC; however crosstalk between MET and EGFR has been implicated in therapeutic resistance to single agent use of MET or EGFR inhibitors in several cancer types. Therefore it is likely that dual inhibition of MET and EGFR is required to prevent crosstalk signaling and acquired resistance. In this study, we evaluated the heterogeneity of MET and EGFR expression and activation in primary and metastatic TNBC tumorgrafts and determined the efficacy of MET (MGCD265 or crizotinib) and/or EGFR (erlotinib) inhibition against TNBC progression. Here we demonstrate that combined MET and EGFR inhibition with either MGCD265 and erlotinib treatment or crizotinib and erlotinib treatment were highly effective at abrogating tumor growth and significantly decreased the variability in treatment response compared to monotherapy. These results advance our understanding of the RTK signaling architecture in TNBC and demonstrate that combined MET and EGFR inhibition may be a promising therapeutic strategy for TNBC patients.

Kinome Profiling of NF1-Related MPNSTs in Response to Kinase Inhibition and Doxorubicin Reveals Therapeutic Vulnerabilities

Abstract: Neurofibromatosis Type 1 (NF1)-related Malignant Peripheral Nerve Sheath Tumors (MPNST) are highly resistant sarcomas that account for significant mortality. The mechanisms of therapy resistance are not well-understood in MPNSTs, particularly with respect to kinase inhibition strategies. In this study, we aimed to quantify the impact of both the genomic context and targeted therapy on MPNST resistance using reverse phase phosphoproteome array (RPPA) analysis. We treated tumorgrafts from three genetically engineered mouse models using MET (capmatinib) and MEK (trametinib) inhibitors and doxorubicin, and assessed phosphosignaling at 4 h, 2 days, and 21 days. Baseline kinase signaling in our mouse models recapitulated an MET-addicted state (NF1-MET), P53 mutation (NF1-P53), and HGF overexpression (NF1). Following perturbation with the drug, we observed broad and redundant kinome adaptations that extended well beyond canonical RAS/ERK or PI3K/AKT/mTOR signaling. MET and MEK inhibition were both associated with an initial inflammatory response mediated by kinases in the JAK/STAT pathway and NFkB. Growth signaling predominated at the 2-day and 21-day time points as a result of broad RTK and intracellular kinase activation. Interestingly, AXL and NFkB were strongly activated at the 2-day and 21-day time points, and tightly correlated, regardless of the treatment type or genomic context. The degree of kinome adaptation observed in innately resistant tumors was significantly less than the surviving fractions of responsive tumors that exhibited a latency period before reinitiating growth. Lastly, doxorubicin resistance was associated with kinome adaptations that strongly favored growth and survival signaling. These observations confirm that MPNSTs are capable of profound signaling plasticity in the face of kinase inhibition or DNA damaging agent administration. It is possible that by targeting AXL or NFkB, therapy resistance can be mitigated.

GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses.

Abstract: Tremendous amount of RNA sequencing data have been produced by large consortium projects such as TCGA and GTEx, creating new opportunities for data mining and deeper understanding of gene functions. While certain existing web servers are valuable and widely used, many expression analysis functions needed by experimental biologists are still not adequately addressed by these tools. We introduce GEPIA (Gene Expression Profiling Interactive Analysis), a web-based tool to deliver fast and customizable functionalities based on TCGA and GTEx data. GEPIA provides key interactive and customizable functions including differential expression analysis, profiling plotting, correlation analysis, patient survival analysis, similar gene detection and dimensionality reduction analysis. The comprehensive expression analyses with simple clicking through GEPIA greatly facilitate data mining in wide research areas, scientific discussion and the therapeutic discovery process. GEPIA fills in the gap between cancer genomics big data and the delivery of integrated information to end users, thus helping unleash the value of the current data resources. GEPIA is available at http://gepia.cancer-pku.cn/.

Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype

Abstract: The human reference genome represents only a small number of individuals, which limits its usefulness for genotyping. We present a method named HISAT2 (hierarchical indexing for spliced alignment of transcripts 2) that can align both DNA and RNA sequences using a graph Ferragina Manzini index. We use HISAT2 to represent and search an expanded model of the human reference genome in which over 14.5 million genomic variants in combination with haplotypes are incorporated into the data structure used for searching and alignment. We benchmark HISAT2 using simulated and real datasets to demonstrate that our strategy of representing a population of genomes, together with a fast, memory-efficient search algorithm, provides more detailed and accurate variant analyses than other methods. We apply HISAT2 for HLA typing and DNA fingerprinting; both applications form part of the HISAT-genotype software that enables analysis of haplotype-resolved genes or genomic regions. HISAT-genotype outperforms other computational methods and matches or exceeds the performance of laboratory-based assays. A graph-based genome indexing scheme enables variant-aware alignment of sequences with very low memory requirements.

The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans

Abstract: Understanding the functional consequences of genetic variation, and how it affects complex human disease and quantitative traits, remains a critical challenge for biomedicine. We present an analysi...

Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma

Abstract: Human cancers are complex ecosystems composed of cells with distinct phenotypes, genotypes, and epigenetic states, but current models do not adequately reflect tumor composition in patients. We used single-cell RNA sequencing (RNA-seq) to profile 430 cells from five primary glioblastomas, which we found to be inherently variable in their expression of diverse transcriptional programs related to oncogenic signaling, proliferation, complement/immune response, and hypoxia. We also observed a continuum of stemness-related expression states that enabled us to identify putative regulators of stemness in vivo. Finally, we show that established glioblastoma subtype classifiers are variably expressed across individual cells within a tumor and demonstrate the potential prognostic implications of such intratumoral heterogeneity. Thus, we reveal previously unappreciated heterogeneity in diverse regulatory programs central to glioblastoma biology, prognosis, and therapy.

10 Years of GWAS Discovery: Biology, Function, and Translation

Abstract: Application of the experimental design of genome-wide association studies (GWASs) is now 10 years old (young), and here we review the remarkable range of discoveries it has facilitated in population and complex-trait genetics, the biology of diseases, and translation toward new therapeutics. We predict the likely discoveries in the next 10 years, when GWASs will be based on millions of samples with array data imputed to a large fully sequenced reference panel and on hundreds of thousands of samples with whole-genome sequencing data.