# An NGS-based assay for accurate detection and quantification of immune gene expression in mouse tumor models

## TL;DR

This paper introduces a new NGS-based assay for accurately measuring immune gene expression in mouse tumor models to better understand tumor immunity and improve cancer treatments.

## Contribution

The paper presents a novel NGS-based assay (NGSmIO) that outperforms microarrays and RNAseq in detecting and quantifying immune-related gene expression in mouse tumors.

## Key findings

- The NGSmIO panel includes 1080 TME-related genes and shows improved mRNA and protein expression correlation compared to flow cytometry.
- NGSmIO demonstrates higher sensitivity in measuring low-expressed genes and stronger correlation with mRNA expression than RNAseq.
- The assay effectively detects pharmacodynamic changes and benchmarks baseline TILs in syngeneic tumors.

## Abstract

Tumor microenvironment (TME) is a complex dynamic system with many tumor-interacting components including tumor-infiltrating leukocytes (TILs), cancer associated fibroblasts, blood vessels, and other stromal constituents. It intrinsically affects tumor development and pharmacology of oncology therapeutics, particularly immune-oncology (IO) treatments. Accurate measurement of TME is therefore of great importance for understanding the tumor immunity, identifying IO treatment mechanisms, developing predictive biomarkers, and ultimately, improving the treatment of cancer. Here, we introduce a mouse-IO NGS-based (NGSmIO) assay for accurately detecting and quantifying the mRNA expression of 1080 TME related genes in mouse tumor models. The NGSmIO panel was shown to be superior to the commonly used microarray approach by hosting 300 more relevant genes to better characterize various lineage of immune cells, exhibits improved mRNA and protein expression correlation to flow cytometry, shows stronger correlation with mRNA expression than RNAseq with 10x higher sequencing depth, and demonstrates higher sensitivity in measuring low-expressed genes. We describe two studies; firstly, detecting the pharmacodynamic change of interferon-γ expression levels upon anti-PD-1: anti-CD4 combination treatment in MC38 and Hepa 1–6 tumors; and secondly, benchmarking baseline TILs in 14 syngeneic tumors using transcript level expression of lineage specific genes, which demonstrate effective and robust applications of the NGSmIO panel.