Juuso Paajanen, MD, PhD

Postdoctoral Research Fellow
Thoracic Surgery
Juuso Paajanen*, Matthew Brian Couger, Ahmed Sadek, David T. Severson, Benjamin Wadowski, Corinne E. Gustafson, Eugene Kim, Sam Weinhouse, Kristina Sidopoulos, William G. Richards, Assunta De Rienzo, and Raphael Bueno
The use of single-nucleus RNA-sequencing in malignant pleural mesothelioma: a pilot study

Background: The tumor microenvironment (TME) of malignant pleural mesothelioma (MPM) remains poorly understood. Recent advances in next generation sequencing have transformed our ability to analyze the tumor ecosystem at a cellular level. Use of single-nucleus RNA-sequencing (sn-RNAseq) allows profiling of single nuclei isolated from frozen tissues.

Methods: Frozen tumors were collected at surgery. Tissues were minced on ice and dissociated using CST buffer. Nuclei were washed with PBS and filtered through 40-μm and 35-μm cell strainers. Suspensions were diluted to a concentration of 700-1200 nuclei/μl and loaded onto the 10x Chromium controller. Sn-libraries were constructed using the 10x Chromium 3′ workflow as per the manufacturers’ directions and sequenced using the Illumina NovaSeq S4 system.

Results: A previously published sn-RNAseq protocol has been optimized to establish a reliable and reproducible nuclei isolation for the three different MPM subtypes. Several nuclei isolation experiments have been performed to optimize buffers and nuclei isolation methods. The final protocol allows to isolate nuclei with high yield and good viability. Eight out of ten sn-libraries passed quality control for sequencing. Our preliminary analysis reveals diverse cellular landscape including putative malignant cells (CLDN15+), M2 macrophages, T cells, fibroblast, and endothelial cells. These cell groups correspond to known constituents of the MPM TME.

Conclusions: Sn-RNAseq was used to produce high quality transcriptomic data from frozen MPM tissues. Libraries representing a spectrum of TME components are present on preliminary analysis. Future work will compare the gene expression between sn-RNAseq and single-cell RNAseq data from frozen and fresh tissue, respectively.