Abstract 5461: Gain early insights from single cell RNA-sequencing of clinical trial needle biopsy cores

Single cell RNA-sequencing (scRNA-seq) yields valuable insights into the molecular heterogeneity of multiple cell types in normal and cancer tissues. scRNA-seq approach has the potential to not only answer basic research questions but also enhance clinical studies and clinical trials and accelerate drug development and testing. However, a consistent and reproducible method for isolating viable single cells and generating high quality single cell data from needle biopsy cores has been challenging to develop. Based on our experience isolating single cells from a large number of surgical tumor tissues, we set out to optimize a dissociation and processing protocol to generate viable single cell suspensions in adequate quantity for scRNA-seq from needle biopsy cores. A total of 17 de-identified 18-gauge needle biopsy samples were collected in collaboration with MD Anderson Cancer Center investigators. Samples were from liver, lymph node, pelvis, abdominal, neck, and lung tissues and included matched pre- and post-treatment samples. Patient biopsies were kept in RPMI medium on ice and transferred to EMPIRI (time to capture ranged from 3 to 6.5 hours after biopsy collection). Samples were dissociated using mechanical and enzymatic methods to achieve a single cell suspension. Cells were washed and viability and cell counts were verified before capture via 10x Chromium Connect. Captured cells were processed through the 10x Genomics Chromium Next GEM Single Cell workflow before sequencing on Illumina NovaSeq 6000 sequencer. Raw sequencing data were processed through EMPIRI’s computational pipeline that includes QC steps, doublet removal, and Seurat and other downstream analyses. Recovery of viable cells from individual 18-gauge biopsy cores ranged from 2,000-300,000 cells per core, depending on the tissue type and cellularity. Cell viability was strictly monitored and was maintained above 80% for 16 of 17 samples (most samples >90%). Cell counts after sequencing and pipeline analysis averaged 6,466 cells per sample. The median number of UMI counts per cell was 5,580, and an average of 1,699 genes were identified per cell. Average sequencing saturation was 73%. Here, we demonstrate the feasibility of integrating scRNA-seq analysis into clinical trials or clinical studies to obtain rapid insights into on-target drug effects and anticipated cellular responses to therapies, including immunotherapies, within 3 weeks of biopsy collection. We have established a method for