Speakers: Nadia Atallah Lanman

Nadia Atallah Lanman

Research Assistant Professor
Department of Comparative Pathobiology
Purdue University

 

Dr. Lanman is a research assistant professor in the Department of Comparative Pathobiology at Purdue University.  Dr. Lanman holds an undergraduate degree in Biochemistry and a PhD, both from Purdue University.  During her time in graduate school, Dr. Lanman became increasingly interested in bioinformatics and computational biology.  In 2015, Dr. Lanman took a position with the Purdue University Center for Cancer Research, directing the Computational Genomics Shared Resource (CG-SR) and managing the Purdue side of the Collaborative Core for Cancer Bioinformatics (C³B), a joint bioinformatics core shared between IU and Purdue.  Dr. Lanman’s work at the cancer center focuses on managing the bioinformatics core, training, and data analysis.  Dr. Lanman’s research is focused on utilizing large genomics datasets to expand our knowledge of the molecular basis of cancer as well as immune and inflammatory diseases.  Dr. Lanman is particularly interested in data integration and in developing methods for datasets that provide temporal or spatial resolution.

 

Characterization of the Cellular Landscape in Benign Prostatic Hyperplasia

Benign prostatic hyperplasia (BPH) is the most common urologic disease in aging men and presents as lower urinary tract symptoms. Chronic non-resolving inflammation is frequently associated with BPH and recent work suggests that BPH shares similarities with immune inflammatory diseases, however the mechanisms behind the observed immune dysregulation and disease progression are unknown. Single cell mRNA sequencing (scRNA-seq) was performed in order to understand the composition of immune cells in this disease as well as the signaling mechanisms that promote BPH progression. Sequencing of CD45+ inflammatory cells from the transition zone of small (<40 grams) and large (>90 grams) human prostates was performed. BPH data were combined with published scRNA-seq data from three normal non-BPH prostate samples. The resulting data were used to identify distinct immune cell clusters based on gene expression, cellular signaling anomalies, and to identify differentially expressed genes between small BPH, large BPH, and normal prostates. The results indicate that T cells may contribute to BPH-associated clinical symptoms, and that mixed inflammatory signaling among T cells and macrophages may promote the non-resolving inflammation observed in BPH. These data suggest that these interactions may play a role in the pathogenesis of BPH and identify potential immune-related treatment targets.