The outcome table, often describing millions of cells, indicates involved clones and is referred to as the Repertoire. Collectively, the sequencing step provides the CDR3 (and possibly flanking regions, with some longer-read technologies) for each of the collected cells. Nevertheless, tools to handle and observe the dynamics of this complexity have only recently started to emerge in parallel with sequencing technologies. High-throughput biology, needed to follow the T-cell repertoire, has made great leaps with the advent of massive parallel sequencing ( 1). The ability to account for the dynamics of the T cell repertoire is therefore critical to our understanding of immune response to tumor cells. An ability to respond to antigens is an ability coded into the T cell repertoire. The mirror image of these neoantigens lies in the immunological repertoire. The role of presentation of tumor specific antigens, Neoantigens, is rapidly taking center stage in such immunotherapy research and treatment, with recent major progress in the clinic ( 6) pushing the field forward. In some cases, the immune system is able to eliminate tumors before they become uncontrollable. Further, Immunotherapy, which over the past few years have been heralded as a great hope in the fight against cancer, relies on the ability to revert tumor progression, by encouraging some T cells to revert from a previous state of tolerance. The interaction between T cells and tumor cells during tumor progression is the subject of extensive study. This collection has been termed the T Cell Repertoire. As the sequences determining these recombined regions are unique to each T cell clone (mean length around 13-aa), and since they are relatively short, the recent progress in genome sequencing has made it possible to sequence millions of T cells in parallel, for their TCR type, thereby determining the collection of TCRs from those T cell. In T cells, these receptor are called T cell receptors (TCRs), and their sequence complexity is achieved through a delicate recombination mechanism ( 5) of T cell DNA. ![]() This regulation system relies on the ability of T cells and of B cells to present and to communicate through a set of highly variable receptors. The way by which the immune system deals with complexity of signals, is by building a complex regulation system through its arsenal of tools. Based on this representation we applied two different methods to demonstrate its effectiveness in identifying changes in the repertoire that correlate with changes in the phenotype: (1) network analysis of the TCR repertoire in which two measures were calculated and demonstrated the ability to differentiate control from transgenic samples, and, (2) machine learning classifier capable of both stratifying control and trangenic samples, as well as to stratify pre-cancer and cancer samples. Viewing the system as dynamical brings to the fore the notion of an attractors landscape, hence the possibility to chart this space and map the sample state at a given time to a vector in this large space. ![]() The Clone-Attractor is in fact an extension of the clone concept, i.e., instead of looking at particular clones we observe the extended clonal network by assigning clusters to graph nodes and edges to adjacent clusters (editing distance metric). The purpose of the clustering step is not merely data reduction and exposing structures, but rather to detect hubs, or attractors, within the T cell receptor repertoire that might shed light on the behavior of the immune system as a dynamic network. The crux of the approach here is at the network-motivated clustering. The transition from the T cell receptor as a feature, to network-based clustering, followed by network-based temporal analyses, provides novel insights to the workings of the system and provides novel tools to observe cancer progression via the perspective of the immune system. Here, we present a network-based view of the dynamics of the T cell repertoire, during the course of mammary tumors development in a mouse model. T cell based immune response is involved with practically every part of human physiology, and high-throughput biology needed to follow the T-cell repertoire has made great leaps with the advent of massive parallel sequencing. The T cell repertoire potentially presents complexity compatible, or greater than, that of the human brain. ![]() The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat Gan, Israel.Avner Priel *, Miri Gordin, Hagit Philip, Alona Zilberberg and Sol Efroni
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