Normalization Method for Better Estimation of Immune Status from Tumor Biopsy

Introduction

The field of cancer immunology advanced significantly during last decade. Great scientific efforts are invested in understanding patient’s immune status. Tumors’ transcriptome profile contains valuable information about immune system which can explain the differences in prognosis and drugs response between patients. We have recently demonstrated that immune signals are diffused by incorporation of noise due to the sampling methods and chance events occurring while obtaining cancer biopsies. Because of this, the amounts of immune cells in a biopsy may thus greatly differ between biopsies irrelevant of immune-related processes. Normalization of immune gene-expression can adjust for this variation, making it essential to investigate immune status.

Material and method

Level 3 RNA-Seq-V2 gene expression data and corresponding clinical data were analyzed from the TCGA Data Portal (https://tcga-data.nci.nih.gov/tcga/). The normalization method is based on defining immune-normalizing gene set (INGS), using this set to estimate the immune cell content in the sample biopsy and to adjust the measured expression with this fraction.

Results and discussion

We have demonstrated that the normalization help to significantly reduce the variation in gene expression and improve the prognostic power of immune-related genes.

Conclusion

Our results indicate that the normalization help to extract clearer signals for immune-related genes and could be utilized for better characterization of differential immune status in cancer stages and for the explanation of promising targets for cancer therapeutic approaches based on the blockade of immune checkpoints.