All the RAGE

Although immunotherapy is a promising form of cancer therapy, not all patients respond well – and current methods to assess an individual’s immune cell behavior often fall short. Immune cells that recognize cancer are rare, making it difficult to identify those that will mount an effective response. But that’s exactly what Repertoire and Gene Expression by Sequencing (RAGE-Seq) – a new cellular barcode tracker – aims to do. Developed by scientists at the Garvan Institute of Medical Research, the new technology can spot the rare lymphocytes that are most reactive against cancer cells, all from within the patient’s own immune system (1).

Current approaches allow us to read the long stretches of RNA that encode immune cell receptors, but each comes with its own limitation. Bulk sequencing can identify lymphocyte expansion very sensitively, but tells us little about the cell’s phenotype or how receptors are paired in a cell. Plate-based methods, on the other hand, can be used to reconstruct gene expression and receptors from single cells, but are low-throughput and expensive.

“The key to finding the lymphocytes of interest lies in the structure of their antigen receptor,” says Alex Swarbrick, Head of the Tumor Progression Laboratory at Garvan and lead researcher of the RAGE-Seq study. “This tells us about the type of lymphocyte, whether they have proliferated and undergone clonal expansion in response to antigens, and other features, such as whether splicing or somatic hypermutation has occurred in B cell receptors.”

The breakthrough that has enabled such analysis came when the researchers combined three distinct technologies: high-throughput single-cell RNA-Seq, targeted capture of lymphocyte receptors, and long-read sequencing of cDNA libraries. “The key bottlenecks were in optimizing targeted capture from single cell libraries and developing the computational methods to match short-read Illumina sequencing with long-read Nanopore sequencing of the same cells,” Swarbrick says. After establishing a way to enrich the RNA that encodes immune cell receptors from single cells, the team then developed a computational tool that generates full-length sequences of antigen receptors at nucleotide resolution and analyzes them to infer B-cell clonal evolution. In this way, RAGE-Seq allows deep characterization of the subsets of lymphocytes in a sample, working much like a barcode tracker that scans the relevant receptors to show which cells might be most effective against a particular cancer.

Using RAGE-Seq to sample 7,138 cells from the tumor and metastasized sentinel lymph node of a breast cancer patient, the researchers were able to identify clones in both tissues that shared unique gene expression features. Both T cell receptor clonality and gene expression signatures have previously been linked to patients’ response to immune checkpoint inhibitors. Applying RAGE-Seq to biopsies before and after treatment could, therefore, help identify biomarkers or cell states that predict therapy response. Swarbrick says, “We think RAGE-Seq will lead to new discoveries in cancer immunotherapy and autoimmunity, allowing us to guide treatment strategies based on the individual.”