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Bryan Schneider on Muck Rack

Bryan Schneider

As seen in: Nature, The Oncologist, Medscape, MedPage Today, HemOnc Today, Journal of Clinical Oncology, Future Medicine, OncLive
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Articles

Genomic, transcriptomic, and immunogenomic landscape of over 1300 sarcomas of diverse histology subtypes - Nature Communications

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By Alex C Soupir, Oliver Hampton, Michelle Churchman, Nathan D. Seligson, Raphael E. Pollock, Martin D. McCarter, Bryan Schneider, David Joyce, Odion T. Binitie, G. Douglas Letson, Damon R. Reed, Erin M. Siegel, Jamie K Teer, Brooke Fridley
| Nature Verified
Abstract Given their rarity and diversity, a fundamental understanding of the genomic underpinnings for many sarcoma subtypes is still lacking. To better define the molecular landscape of this group of diseases, we perform matched whole exome sequencing and RNA sequencing on a cohort of 1340 sarcoma tumor specimens. We identify recurrent somatic mutations and observe an increased mutational burden in metastatic vs. primary samples (p < 0.001).
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IU research targets debilitating side effects for Black breast cancer patients

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By Bryan Schneider
| news.iu.edu
Breast cancer remains the most common cancer diagnosis in women in the United States, and enduring the often debilitating cancer treatments can become as harrowing as the diagnosis itself. That’s especially true for Black women, who face disparate outcomes in breast cancer and are more likely to experience neuropathy.
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Optimization of a human induced pluripotent stem cell-derived sensory neuron model for the in vitro evaluation of taxane-induced neurotoxicity - Scientific Reports

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By Bryan Schneider
| Nature Verified
Abstract Human induced pluripotent stem cell-derived sensory neuron (iPSC-dSN) models are a valuable resource for the study of neurotoxicity but are affected by poor replicability and reproducibility, often due to a lack of optimization. Here, we identify experimental factors related to culture conditions that substantially impact cellular drug response in vitro and determine optimal conditions for improved replicability and reproducibility.
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