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Biology subjects

Oneka, M.

Publications and source records attributed to Oneka, M..

3 recordsLinked to original sources

Subclonal evolution and expansion of THY1-positive cells is associated with recurrence in glioblastoma

PurposeGlioblastoma (GBM) is a lethal disease characterized by inevitable recurrence. Here we investigate the molecular pathways mediating resistance, with the goal of identifying therapeutic opportunities to target this tumor. Experimental DesignWe developed a longitudinal in vivo recurrence model utilizing patient-derived explants to produce paired specimens (pre- and post-recurrence) following temozolomide(TMZ) and radiation(IR). These specimens were evaluated for treatment response and to identify gene expression pathways driving treatment resistance. Findings were clinically validated using spatial transcriptomics of human GBMs. ResultsThese studies reveal in replicate cohorts, a gene expression profile characterized by upregulation of mesenchymal and stem-like genes at recurrence. Analyses of clinical databases revealed increased expression of this transcriptional profile to be significantly associated with worse median overall survival (248 days vs 430 days, p=0.0004), and upregulation of this profile at recurrence. Most notably, we identified upregulation of TGF{beta} signaling, and more than one-hundred-fold increase in THY1 levels at recurrence. Utilizing cell sorting, we observed that THY1-positive cells represented <10% of cells in the treatment-naive tumors and 75-96% in the recurrent tumors. We then isolated THY1-positive cells from treatment-naive patient samples and determined that they were inherently resistant to chemoradiation in orthotopic models. Additionally, using image-guided biopsies from treatment-naive human GBM, we conducted spatial transcriptomic analyses. This revealed rare THY1+ regions characterized by mesenchymal/stem-like gene expression, analogous to our recurrent mouse model samples, which co-localized with macrophages within the perivascular niche. Since TGF{beta} signaling contributes to a mesenchymal/stem-like phenotype, we inhibited TGF{beta}RI activity in vivo which resulted in decreased mesenchymal/stem-like protein levels, including THY1, and restored sensitivity to TMZ/IR in recurrent tumors. ConclusionsThese findings reveal that GBM recurrence may result from tumor repopulation by pre-existing, therapy-resistant, THY1-positive, mesenchymal/stem-like cells within the perivascular niche. Furthermore, our data demonstrate the promise of targeting upregulated pathways in resistant subclones as a novel mechanism to achieve therapeutic response, and specifically that THY1 expression may represent a biomarker of response to TGF{beta} inhibition.

cancer biology

Teaching Python for Data Science: Collaborative development of a modular & interactive curriculum

We are bioinformatics trainees at the University of Michigan who started a local chapter of Girls Who Code to provide a fun and supportive environment for high school women to learn the power of coding. Our goal was to cover basic coding topics and data science concepts through live coding and hands-on practice. However, we could not find a resource that exactly met our needs. Therefore, over the past three years, we have developed a curriculum and instructional format using Jupyter notebooks to effectively teach introductory Python for data science. This method, inspired by The Carpentries organization, uses bite-sized lessons followed by independent practice time to reinforce coding concepts, and culminates in a data science capstone project using real-world data. We believe our open curriculum is a valuable resource to the wider education community and hope that educators will use and improve our lessons, practice problems, and teaching best practices. Anyone can contribute to our educational materials on GitHub.

scientific communication and education

Developing and deploying an integrated workshop curriculum teaching computational skills for reproducible research

Inspired by well-established material and pedagogy provided by The Carpentries (Wilson 2016), we developed a two-day workshop curriculum that teaches introductory R programming for managing, analyzing, plotting and reporting data using packages from the tidyverse (Wickham et al. 2019), the Unix shell, version control with git, and GitHub. While the official Software Carpentry curriculum is comprehensive, we found that it contains too much content for a two-day workshop. We also felt that the independent nature of the lessons left learners confused about how to integrate the newly acquired programming skills in their own work. Thus, we developed a new curriculum that aims to teach novices how to implement reproducible research principles in their own data analysis. The curriculum integrates live coding lessons with individual-level and group-based practice exercises, and also serves as a succinct resource that learners can reference both during and after the workshop. Moreover, it lowers the entry barrier for new instructors as they do not have to develop their own teaching materials or sift through extensive content. We developed this curriculum during a two-day sprint, successfully used it to host a two-day virtual workshop with almost 40 participants, and updated the material based on instructor and learner feedback. We hope that our new curriculum will prove useful to future instructors interested in teaching workshops with similar learning objectives.

scientific communication and education