Regency EF
Visualization of Affinity Maturation Based on Next-Generation Sequencing B Cell Receptor Sequencing Data (304048)
Jason Cham, University of California, San Francisco
Lawrence Fong, University of California, San Francisco
Tao He, San Francisco State University
Harini Kandadi, Dendreon Pharmaceuticals
David Oh, University of California, San Francisco
Nadeem Sheikh, Dendreon Pharmaceuticals
*Hai Yang, University of California, San Francisco
Li Zhang, University of California, San Francisco
Keywords: Cancer immunotherapy, B cell receptor, Affinity Maturation, Social network visualization
Cancer immunotherapy has demonstrated significant clinical activity in different cancers. B cells represent a crucial component of the adaptive immune system and are thought to mediate antitumoral immunity. As successive generations of B cells mutate, only those that recognize the antigen with high affinity will survive, while B cells producing low affinity antibodies will be eliminated, a process known as affinity maturation. Next generation sequencing was used to profile the B cell receptor (BCR) repertoire. We proposed a visualization pipeline of affinity maturation while solving the computational burden. For each subject, pairwise distance matrix was calculated based on levenshtein distance (R: RecordLinkage) for each pair of clones. A convergence group was defined as the cluster including the clones with the distance less than 2. Social network visualization and Phylogenetic tree were performed across clusters (R: Ape, igraph, and ggtree). For a representative convergent group, chord diagram (R: circlize) was plotted to show the clonal development across timepoints. A real example of prostate patients who received FDA-approved immunotherapy is used for illustration.