![]() ![]() ![]() The results of our benchmarking provide an additional appealing argument to incorporate the RNA-Seq into immune repertoire screening of cancer patients as it offers broader knowledge into the transcriptomic changes that exceed the limited information provided by TCR-Seq. However, RNA-Seq-based TCR profiling methods have limited power in T cell poor tissues, especially in polyclonal repertoires of T cell poor tissues. Our results show that RNA-Seq-based methods are able to effectively capture the clonotypes and estimate the diversity of TCR repertoires, as well as to provide relative frequencies of clonotypes in T cell rich tissues and monoclonal repertoires. We also highlighted scenarios under which the RNA-Seq approach is suitable and can provide comparable accuracy to the TCR-Seq approach. We have performed a comprehensive evaluation of the existing RNA-Seq-based repertoire profiling methods using targeted TCR-Seq as the gold standard. In this paper, we have benchmarked the ability of RNA-Seq-based methods to profile TCR repertoires by examining 19 bulk RNA-Seq samples across four cancer cohorts including both T cell rich and poor tissue types. However, the available TCR-Seq data is limited compared to RNA sequencing (RNA-Seq). The available high-throughput method to profile T cell receptor repertoires is generally referred to as TCR sequencing (TCR-Seq). Tracking genetically engineered T cells expressing TCRs that target specific tumor antigens is important to determine the persistence of these cells and quantify tumor responses. The ability to identify and track T cell receptor (TCR) sequences from patient samples is becoming central to the field of cancer research and immunotherapy. ![]()
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