Mitigating pitfalls and approaches for interpretation of TCRseq data
Potential confounders | Pitfall | Mitigation |
Batch effect | Circulating T-cell clones may be ‘shared’ by multiple specimens collected at the same time point. | Control normal tissue(s) collected at the same timepoint can be used to identify these background clones. |
Blood | During active immune responses,* both relevant and non-relevant clones circulate in blood. | Functional assays enable identification of disease-relevant clones (vs batch background). |
Tissue compartment effect | Specimens from the same organ share tissue resident T cells, including antitumor clones.19 | Clonotype sharing with ‘paired’ normal tissue does not preclude biological relevance. Measurements such as abundance and antigen specificity (antigen-driven clustering/functional assays) are needed for further discernment. |
Library size variation | Increased read count→more clones sampled→a larger proportion of shared clones | Analyses must correct for sample size variation (eg, Morisita Overlap Index, normalization, etc) |
LNs/lymphoid-rich tissues | Increased probability of repertoire overlap given large, diverse T-cell populations | Avoid analysis of background lymphoid tissue in LN metastases; interpret LN data with caution. |
Interpretation | Definition | Approach |
Clonal abundance (relative read count) | Relative proportion of sequencing reads for a unique clonotype (surrogate for clonal proliferation) | Assess for signals of clonal proliferation in relevant tissues to suggest functional relevance.† |
Low abundance | Meaningful threshold for exclusion of ‘background’ clones has not been rigorously defined | Exclude specimens with <1000 reads. Sample size informs interpretation of low-read clones. |
High abundance | Increasing abundance suggests clonal proliferation (and antigen exposure) in a given tissue.* | Proliferation of shared clones in disease-relevant tissues supports potential mechanistic overlap. |
TCR repertoire sharing | Mechanistic interpretations of TCR repertoire overlap are limited by several confounders. | Multispecimen analyses, antigen-driven clustering (such as GLIPH2), and functional assays maximize interpretability of TCRseq data. |
*During tumor killing (early in treatment) or active autoimmunity (immune-related adverse events).
†Assuming systemic clonal proliferation (batch effect) has been excluded.
GLIPH2, grouping lymphocyte interactions by paratope hotspots 2; LN, lymph node; TCR, T-cell receptor; TCRseq, T-cell receptor sequencing.