Jun S. Song - US grants

Uterine leiomyomas (UL), also known as uterine fibroids, are benign smooth muscle tumors with excessive depostition of extracellular matrix proteins. UL is a major health problem worldwide, because it affects almost 70-80% of all women and disproportionally African Americans, but still remains poorly understood. The long term goal of our team is to systematically discover novel mechanisms regulating key molecular events that contribute to leiomyoma. The immediate goal of this R01 application is to test the hypothesis that altered epigenomic signatures define normal myometrial tissues and leiomyomas, and therapy treated human tissues. Using genome-wide studies integrated with bioinformatic and other analyses, we will determine the epigenomic signatures in uterine fibrosis for the first time. This unbiased study will identify epigenomic differentiating features of normal and diseased tissues and may allow for development of Epitherapy (targeting the epigenome) for leiomyomas The proposed work is scientifically, translationally, and clinically significant and highly innovative because it represents the first systematic exploration of the epigenome in leiomyomas. Results obtained from this analysis will be used to generate new hypotheses to better understand the molecular underpinning of leiomyomas.

Limitless replicative potential is a key hallmark of cancer and critically depends on telomere maintenance. Many cancers thus aberrantly reactivate the telomerase reverse transcriptase (TERT), a catalytic subunit of the telomerase complex that elongates telomere. It has been recently discovered that this common path to immortality in multiple cancers is through two activating point mutations in the TERT promoter (TERTp), found in more than 50 different cancer types, often at strikingly high frequencies, e.g. roughly 83% in glioblastomas (GBM) and 71% in melanomas. In the previous funding period, the PI has identified the molecular function of these highly recurrent mutations, demonstrating that the transcription factor (TF) GABP binds the mutant TERTp with exquisite specificity, but not the wild-type TERTp. The high prevalence of TERTp mutations across multiple cancer types and the selectivity of GABP recruitment to mutant TERTp thus provide an unprecedented opportunity for treating a large number of cancer patients with minimal toxicity to healthy cells. Despite the clear significance of this opportunity, however, several important questions surrounding the molecular functions and modulators of TERTp mutations remain poorly understood, hindering the development of effective and safe therapeutic strategies. Our long-term goal is to establish a rigorous computational framework for understanding the aberrant transcriptional and epigenetic networks in cancers and to apply the resulting knowledge to devise novel therapeutic strategies that account for the genetic background of individual patients and that can a priori predict and avoid potential resistance mechanisms. The objective of our current renewal proposal is to develop powerful computational methods for transforming our knowledge about the non-coding TERTp mutations into an effective and safe molecular target. At the same time, the resulting methods will help resolve several outstanding challenges in the field of transcriptional gene regulation and have broad applications in cancer genomics. We will accomplish our objective my pursuing the following Aims: (1) Develop and test a computational framework for inferring sequence features that determine the distinct and shared binding patterns of paralogous TFs; (2) Develop and validate integrative tools for discovering the molecular basis of genetic interactions between germline variations and oncogenic mutations; (3) Develop and apply computational methods for studying the role of DNA helical phase between adjacent binding motifs in recruiting ETS factors to chromatin; (4) Perform a systematic genomic characterization of the effects of knocking out GABPB1L in TERTp-mutant cancer cells and healthy cells. The results of this proposal will have a broad impact on cancer research by providing powerful tools for studying paralogous oncogenic TFs and revealing novel insights into a highly promising therapeutic strategy.

PROJECT SUMMARY Racial and ethnic minorities and women have been historically under-represented in quantitative sciences. Even within biology, diversity in quantitative sub-branches is much lower than that in experimental counterparts, with the historical data clearly showing that the more mathematical and computational skills a discipline requires, the fewer the enrollment of these under-represented students. The proposed training program seeks to ameliorate these especially pronounced disparities with the biomedical sciences by establishing a streamlined bridge between Master?s programs at Fisk University and doctoral programs at the University of Illinois, Urbana- Champaign (UIUC). Our bridge program designed to nurture a diverse future generation of active minds specifically in the areas of biomedical data science and quantitative biology is named FUTURE-MINDS-QB (Fisk- UIUC Training of Under-represented Minds in Data Science and Quantitative Biology), where quantitative biology encompasses bioinformatics, computational biology, genomic biology, and biophysics. This training program will significantly contribute to diversifying the pool of Ph.D. researchers to include those currently under- represented in biomedical discovery and leadership To achieve our goal, we will accomplish the following short-term and medium-term objectives: (a) establish pathways for transitioning 20 Fisk M.S. students to UIUC Ph.D. programs over five years by providing ample opportunities to strengthen their background in relevant fields and acquire core computational and mathematical skill sets; (b) ensure the trainees? timely Ph.D. attainment within 5 years after Master?s degree; (c) accelerate the admission to and completion of Ph.D. programs by creating a new 4+1 M.S. track at Fisk, rigorously preparing undergraduates for a shortened 1-year M.S degree at Fisk and successful completion of a Ph.D. degree at UIUC; (d) create an inclusive and diverse inter-institutional environment by training both students and faculty in equity- focused teaching, mentoring, peer interactions, rigor, reproducibility, and the responsible conduct of research; (e) devise effective career development plans and opportunities; (f) implement a longitudinal survey of the development of individual trainees, and disseminate an open network of current trainees, graduates, and faculty; and, (g) make FUTURE-MINDS-QB a dynamic entity that continually improves by integrating feedback from trainees, faculty, oversight committees, and independent evaluators. As outcomes of our training, we expect that our seamless infrastructure and appealing inclusive environment will significantly increase the recruitment of under-represented students to quantitative biomedical sciences and that the reinforced academic and psychological preparation will increase the completion of doctoral degrees by under-represented students and ultimately improve their long-term retention in biomedical sciences. We thus expect FUTURE-MINDS-QB to establish an exemplary foundation for training under-represented graduate students and have a long-lasting scientific and socioeconomic impact stemming from their persistence and leadership in their careers.