{'fraction_non_alphanumeric': 0.016523463317911435, 'fraction_numerical': 0.0, 'mean_word_length': 4.868217054263566, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Heteroplasmy as a biomarker and therapeutic target in cancer

T T cell receptor (TCR) repertoire holds clues to the functioning of the immune system. Profiling the repertoire can provide a systemic view of the health of an individual. T-seq, our novel method of sequencing the T cell receptor (TCR) repertoire, enables its unbiased sampling. This has enabled inexpensive, deep profiling of the TCR repertoire in both mouse and human T cells. The method does not require T cell isolation and can be used to study infiltrates in tissues. By applying it to a variety of samples from mouse and human, we have improved the annotation of the TCR loci in both genomes. We have also characterized the RSS signals and identified evolutionary constraints, as well as their potential to shape the statistics of segment usage. We describe methods of characterizing the usage of V and J segments in the alpha and beta chains and comparing TCR repertoire data across samples. This study enhances our understanding of the “normal” TCR repertoire, and provides the tools and annotations needed to characterize disease states, in order to help identify biomarkers and potential targets of therapy. We propose methods of identifying signatures of repertoires in cancer and the potential implications of this signature for outcomes of cancer immunotherapy. We are using these tools to study the role of the TCR repertoire in disease progression and potential for use of the diversity of the TCR repertoire as a prognostic indicator.