Using cell-free RNA in monitoring immune system and the demonstration of significant systemic deficiency in lymphoid and myeloid biomarkers in patients with cancer.

Abstract

3048 Background: Immune system plays a major role in the clinical course of cancer. Evaluating the local interaction between tumor cells and the immune cells (microenvironment) at the cancer site provides important information. However, currently little is known about the immune system as a whole in patients with cancer. Since cell-free circulating RNA (cfRNA) may reflect the entire body, we hypothesized that cfRNA might provide important information on the health and the status of the immune system. To simplify our approach, we evaluated only cellular biomarkers characteristic for lymphoid and myeloid cells using only the expression of 55 genes typically used in flow cytometry evaluation of hematologic cells. We compared findings between patients with cancer, patients with CHIP (clonal hematopoiesis of indeterminate potential), and normal individuals. Methods: cfRNA was extracted from plasma samples of 681 patients with various types of solid tumors, 113 patients with CHIP, and 34 normal individuals. cfRNA was sequenced via a hybrid capture-based panel targeting 55 genes reflecting immune cells including T-cells, B-cells, histiocytes, monocytes, and myeloid cells. The RNA was quantified using TPM (transcript per million). Results: There was significant difference (P<0.0001) between normal individuals and patients with cancers in the levels of circulating biomarkers specific for immune cells. Surprisingly, expression of B-cell, T-cell, monocytic/histiocytic genes were significantly lower in patients with solid tumors when compared to normal individuals. This included CD19, CD20, CD2, CD22, CD3D, CD3E, CD3G, CD4, CD52, CD7, CD79A, CD79B, CD8A, CD8B,CD33, FCER2(CD23), IL2RA(CD25), ITGAM(CD11B), and ITGAX(CD11C). In contrast, there was no significant difference between CHIP and normal for B- or T-cell markers. After adjusting for multiple testing, no deficiency in immune stimulatory markers was present in patients with CHIP. Patients with CHIP showed significantly (P<0.001) lower levels of CD38, CD58, CD16, CD15, CD25, and CD123 mRNA as compared with normal. Furthermore, using 35 immune cell biomarkers in a machine learning algorithm using 2/3 of samples for training and 1/3 for testing predicted the presence of cancer vs no cancer (AUC =0.820), and CHIP from cancer (AUC =0.0830) and CHIP vs normal (AUC =0.871). Conclusions: Immune related biomarkers using cfRNA provide important information on the immune system that can be used to monitor patients and to predict the presence of cancer or CHIP. The demonstration that patients with cancer have deficiency in overall systemic immune elements suggests that further studies are needed in monitoring the immune system and exploring means to boost systemic immunity to prevent the development of overt cancers.