Outlier Kinase Expression by RNA Sequencing As Targets for Precision Therapy

Published OnlineFirst February 5, 2013; DOI: 10.1158/2159-8290.CD-12-0336 RESEARCH ARTICLE Outlier Kinase Expression by RNA Sequencing as Targets for Precision Therapy Vishal Kothari 1 , Iris Wei 2 , Sunita Shankar 1 , 3 , Shanker Kalyana-Sundaram 1 , 3 , 8 , Lidong Wang 2 , Linda W. Ma 1 , Pankaj Vats 1 , Catherine S. Grasso 1 , Dan R. Robinson 1 , 3 , Yi-Mi Wu 1 , 3 , Xuhong Cao 7 , Diane M. Simeone 2 , 4 , 5 , Arul M. Chinnaiyan 1 , 3 , 4 , 6 , 7 , and Chandan Kumar-Sinha 1 , 3 ABSTRACT Protein kinases represent the most effective class of therapeutic targets in cancer; therefore, determination of kinase aberrations is a major focus of cancer genomic studies. Here, we analyzed transcriptome sequencing data from a compendium of 482 cancer and benign samples from 25 different tissue types, and defi ned distinct “outlier kinases” in individual breast and pancreatic cancer samples, based on highest levels of absolute and differential expression. Frequent outlier kinases in breast cancer included therapeutic targets like ERBB2 and FGFR4 , distinct from MET , AKT2 , and PLK2 in pancreatic cancer. Outlier kinases imparted sample-specifi c dependencies in various cell lines, as tested by siRNA knockdown and/or pharmacologic inhibition. Outlier expression of polo-like kinases was observed in a subset of KRAS -dependent pancreatic cancer cell lines, and conferred increased sensitivity to the pan-PLK inhibitor BI-6727. Our results suggest that outlier kinases represent effective precision therapeutic targets that are readily identifi able through RNA sequencing of tumors. SIGNIFICANCE: Various breast and pancreatic cancer cell lines display sensitivity to knockdown or pharmacologic inhibition of sample-specifi c outlier kinases identifi ed by high-throughput transcriptome sequencing. Outlier kinases represent personalized therapeutic targets that could improve com- binatorial therapy options. Cancer Discov; 3(3); 280–93. ©2013 AACR. See related commentary by Yegnasubramanian and Maitra, p. 252. Authors’ Affi liations: 1 Michigan Center for Translational Pathology, V. Kothari, I. Wei, and S. Shankar contributed equally to this work. Departments of 2 Surgery and 3 Pathology, University of Michigan Medical A.M. Chinnaiyan and C. Kumar-Sinha shared senior authorship. School; 4 Comprehensive Cancer Center, Departments of 5 Molecular and Integrative Physiology and 6 Urology, University of Michigan Medical Center; Corresponding Author: Chandan Kumar-Sinha, Michigan Center for Transla- 7 Howard Hughes Medical Institute, Ann Arbor, Michigan; and 8 Department tional Pathology, Department of Pathology, University of Michigan Medical of Environmental Biotechnology, Bharathidasan University, Tiruchirappalli, School, 1400 East Medical Center Drive 5316 CCGC, Ann Arbor, MI 48109. India Phone: 734-936-2592; Fax: 734-615-4055; E-mail: [email protected] Note: Supplementary data for this article are available at Cancer Discovery doi: 10.1158/2159-8290.CD-12-0336 Online (http://cancerdiscovery.aacrjournals.org/). © 2013 American Association for Cancer Research. 280 | CANCER DISCOVERYMARCH 2013 www.aacrjournals.org Downloaded from cancerdiscovery.aacrjournals.org on September 28, 2021. © 2013 American Association for Cancer Research. Published OnlineFirst February 5, 2013; DOI: 10.1158/2159-8290.CD-12-0336 INTRODUCTION kinome) to identify and test “personalized kinase targets” in a panel of pancreatic cancer cell lines. The dependence of cancers on a primary driver, most often Next-generation sequencing of transcriptomes offers sig- a kinase ( 1, 2 ), forms the guiding principle of targeted therapy nifi cant advantages over microarrays in terms of throughput, that has had some notable clinical successes, such as imatinib elimination of probe bias, and simultaneous monitoring of for BCR - ABL –positive chronic myeloid leukemia, trastuzumab diverse components of transcriptome biology ( 15 ), including and lapatinib for ERBB2 -positive breast cancers, gefi tinib for gene expression ( 15–18 ), alternative splicing ( 19, 20 ), chimeric/ lung cancers with kinase domain mutations in EGFR ( 3, 4 ), read-through transcripts ( 21, 22 ), and noncoding transcripts and, more recently, crizotinib for lung cancers with ALK gene ( 23, 24 ). Furthermore, transcriptome sequencing affords a fusions ( 5 ). Thus, protein kinases are the mainstay of a major- direct and quantitative readout of transcript abundance, facili- ity of the current targeted therapeutic strategies for cancers, tating sample-wise gene expression analyses using a digital and inhibitors of several oncogenic kinases such as AKT, metric of normalized fragment reads, which are not possible BRAF, CDKs, KIT, RET, SRC, MAPKs, MET, PIK3CA, PLKs, using microarrays. Here, we set out to use transcriptome data AURKs, S6Ks, and VEGFR are in various stages of clinical use, from a compendium of 482 cancer and benign samples from 25 trials, or development ( 4 , 6 ). While activating somatic muta- different tissue types to carry out gene expression profi ling of tions are associated with a few of these genes, overexpression the complete complement of kinases in the human genome, the of kinases (resulting from genomic amplifi cation or other kinome, to identify “individual sample-specifi c outlier kinases” underlying somatic aberrations) is often a strong indicator of inspired by the concept of cancer outlier profi le analysis (COPA; aberrant activity that may impart dependence of cancer cells. refs. 25, 26 ). Importantly, while COPA analysis was used to iden- Pancreatic cancer is the fourth leading cause of cancer- tify subsets of “samples displaying outlier expression of candi- related deaths in the United States, with the worst prognosis date genes,” here, we interrogated subsets of “outlier genes in (5-year survival <3%) of all major malignancies ( 7 ), due to individual samples,” focusing on kinases that display the high- diagnosis of the disease at an advanced, unresectable stage est levels of absolute expression among all the kinases in a sam- and poor responsiveness to chemo-/radiotherapy ( 8, 9 ). The ple and the highest levels of differential expression compared overarching oncogenic driver of pancreatic cancer is mutant with the median level of expression of the respective gene(s) KRAS , which has eluded therapeutic interventions ( 10, 11 ), across the compendium. As proof-of-concept, we observed out- spurring the search for alternative targets ( 11 ). The identifi ca- lier expression of the therapeutic target ERBB2 specifi cally in all tion of distinct kinases in independent screens for synthetic the breast cancer cell lines analyzed that are known to be ERBB2 lethal interactors of KRAS ( 12–14 ) led us to systematically positive. Thus, we hypothesized that specifi c outlier kinases in explore the expression profi les of all 468 human kinases (the other samples may also impart “dependence” owing to clonal MARCH 2013CANCER DISCOVERY | 281 Downloaded from cancerdiscovery.aacrjournals.org on September 28, 2021. © 2013 American Association for Cancer Research. Published OnlineFirst February 5, 2013; DOI: 10.1158/2159-8290.CD-12-0336 RESEARCH ARTICLE Kothari et al. selection for extremely high expression and may thereby repre- outlier expression across multiple pancreatic cancer samples sent personalized therapeutic targets. included EPHA2 , MET , PLK2 , MST1R , and AKT2 . Interest- Here, we analyzed kinome expression profi les of breast and ingly, AXL and EGFR showed outlier expression in both pan- pancreatic cancer samples to identify sample-specifi c outlier creatic and breast cancer samples. kinases. Next, focusing on cell lines displaying outlier expres- Before proceeding to test outlier kinase–specifi c dependen- sion of kinases with available therapeutics or pharmacologic cies in individual cell lines, we validated the gene expression inhibitors, we tested their dependence on specifi c outlier readout provided by the RNA-Seq data. First, comparing the kinases compared with nonspecifi c targets using short hairpin gene expression profi les of a prostate cancer cell line DU145 RNA (shRNA) or siRNA and/or small-molecule inhibitors to across 4 independent RNA-Seq runs, we observed a robust assess their effects on cell proliferation. Using this approach, correlation ( R 2 > 0.96) between the technical replicates (Sup- we identifi ed several cell line–specifi c dependencies as well as plementary Fig. S1A). Next, we analyzed the variance across kinase targets showing enhanced effects with ERBB2 inhibi- RNA-Seq data from a breast cancer cell line, MCF-7, treated tion in breast and KRAS knockdown in pancreatic cancer cells. with estrogen (0, 3, and 6 hours) as biologic quasi-replicates. Interestingly, we observed an overall high correlation 2 > RESULTS ( R 0.91) here also, albeit less than the technical replicates (Sup- plementary Fig. S1B). Next , we validated the expression profi les Delineation of Cancer-Specifi c Kinome Outlier of kinase genes derived from RNA-Seq by quantitative reverse- Profi les Using Transcriptome Sequencing Data transcription PCR (qRT-PCR) and Western blot analyses. As an Taking advantage of the direct and unbiased readout of gene example, a strong correlation ( R 2 > 0.88) was observed between expression in terms of defi ned RNA sequencing (RNA-Seq) reads, the levels of MET expression by RNA-Seq and qRT-PCR, over a we carried out a systematic analysis of the human kinome expres- range of expression values across a panel of samples ( Fig. 2A ). sion in cancer. RNA-Seq–based, normalized read-counts

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