This application proposes the formation of a University of Michigan (UM) EDRN Biomarker Development Lab (BDL). Through previous EDRN BDLs, our team has characterized multiple important prostate cancer biomarkers, most notably TMPRSS2-ETS gene fusions. Through collaboration with an EDRN Clinical Validation Center (CVC; Dr. Sanda PI), we have developed, validated and clinically implemented Mi-Prostate Score (MiPS), a prostate cancer early detection test incorporating urine quantification of two prostate cancer specific transcripts?the TMPRSS2:ERG gene fusion and PCA3?with serum PSA. Introduced in our CLIA laboratory (and now with New York State approval), MiPS helps shared decision making after PSA testing based on individualized risk predictions of aggressive prostate cancer on biopsy. Here, using this work as a model, we will discover and characterize aggressive prostate cancer transcriptomic biomarkers, focusing on long non-coding RNAs (lncRNAs). Although lncRNA biomarker utility has been largely unexplored, we recently characterized the lncRNA compendium (?MiTranscriptome?), identifying several prostate cancer-specific and aggressive prostate cancer-specific lncRNAs. Supporting our proposed approach, we have performed initial validation of the lncRNA SChLAP1 as an aggressive prostate cancer specific biomarker in tissues. Likewise, we have developed RT-PCR based next generation sequencing (NGS) panels capable of quantifying multiplexed transcriptomic biomarkers in archived tissue and urine. Here, in three Aims, we will nominate and develop transcriptomic biomarkers as predictors of aggressive prostate cancer both at and prior to diagnosis.
In Aim 1, we will identify novel aggressive prostate cancer-associated transcriptomic alterations from our MiTranscriptome analysis. We will develop single gene and multiplexed NGS assays to study these lncRNAs/coding transcripts as aggressive prostate cancers specific biomarkers.
In Aim 2 we will characterize transcripts from Aim 1 as tissue based aggressive prostate cancer biomarkers. Following our previous approach with SChLAP1, we will develop individual in situ hybridization assays and a multiplexed NGS panel to characterize these transcripts in well characterized prostate cancer tissue cohorts.
In Aim 3, we will characterize transcripts identified in Aim 1 as non-invasive, urine-based aggressive prostate cancer early detection biomarkers. Through collaboration with Hologic/Gen-Probe (our industry partner on MiPS), we will develop and assesses the performance of individual prioritized biomarkers using their platform on our biobanked urine samples. Additionally, using multiplexed NGS, we will also characterize the performance of a panel of transcriptomic biomarkers as an alternative/complementary approach. As recognized by the EDRN, novel aggressive prostate cancer specific biomarkers are urgently needed. Importantly, our approach extends beyond prostate cancer and our BDL, and our group has actively participated in the EDRN biomarker community and anticipates continuing work with other BDLs and CVCs to facilitate the overall EDRN mission.

Public Health Relevance

Project Summary Recent studies suggest that regardless of clinical treatment offered, most men with clinically localized prostate cancer at time of initial diagnosis do not die of their disease; however those that develop aggressive, metastatic prostate cancer invariable succumb to disease. Thus, we urgently need the next generation prostate cancer screening biomarkers that will have high specificity and are associated with clinically significant disease. The overarching goal of this project is to identify the subset of prostate cancer patients that will require early and aggressive therapeutic intervention while preventing invasive over-treatment of men with indolent disease.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01CA214170-04
Application #
9772878
Study Section
Special Emphasis Panel (ZCA1)
Program Officer
Kagan, Jacob
Project Start
2016-09-15
Project End
2021-08-31
Budget Start
2019-09-01
Budget End
2020-08-31
Support Year
4
Fiscal Year
2019
Total Cost
Indirect Cost
Name
University of Michigan Ann Arbor
Department
Pathology
Type
Schools of Medicine
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109
Zhang, Yajia; Pitchiaya, Sethuramasundaram; Cie?lik, Marcin et al. (2018) Analysis of the androgen receptor-regulated lncRNA landscape identifies a role for ARLNC1 in prostate cancer progression. Nat Genet 50:814-824
Salami, Simpa S; Hovelson, Daniel H; Kaplan, Jeremy B et al. (2018) Transcriptomic heterogeneity in multifocal prostate cancer. JCI Insight 3:
Ankerst, Donna P; Goros, Martin; Tomlins, Scott A et al. (2018) Incorporation of Urinary Prostate Cancer Antigen 3 and TMPRSS2:ERG into Prostate Cancer Prevention Trial Risk Calculator. Eur Urol Focus :
Niknafs, Yashar S; Pandian, Balaji; Gajjar, Tilak et al. (2018) MiPanda: A Resource for Analyzing and Visualizing Next-Generation Sequencing Transcriptomics Data. Neoplasia 20:1144-1149
Wu, Yi-Mi; Cie?lik, Marcin; Lonigro, Robert J et al. (2018) Inactivation of CDK12 Delineates a Distinct Immunogenic Class of Advanced Prostate Cancer. Cell 173:1770-1782.e14
Hosono, Yasuyuki; Niknafs, Yashar S; Prensner, John R et al. (2017) Oncogenic Role of THOR, a Conserved Cancer/Testis Long Non-coding RNA. Cell 171:1559-1572.e20
Wang, Xiaoju; Qiao, Yuanyuan; Asangani, Irfan A et al. (2017) Development of Peptidomimetic Inhibitors of the ERG Gene Fusion Product in Prostate Cancer. Cancer Cell 31:532-548.e7
Robinson, Dan R; Wu, Yi-Mi; Lonigro, Robert J et al. (2017) Integrative clinical genomics of metastatic cancer. Nature 548:297-303
Blattner, Mirjam; Liu, Deli; Robinson, Brian D et al. (2017) SPOP Mutation Drives Prostate Tumorigenesis In Vivo through Coordinate Regulation of PI3K/mTOR and AR Signaling. Cancer Cell 31:436-451
Niknafs, Yashar S; Pandian, Balaji; Iyer, Hariharan K et al. (2017) TACO produces robust multisample transcriptome assemblies from RNA-seq. Nat Methods 14:68-70

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