Deciphering Repertoire of B16 Melanoma Reactive TCRs by Immunization, In Vitro Restimulation and Sequencing of IFNγ-Secreting T Cells.

Recent advances in cancer immunotherapy have great promise for the treatment of solid tumors. One of the key limiting factors that hamper the decoding of physiological responses to these therapies is the inability to distinguish between specific and nonspecific responses. The identification of tumor-specific lymphocytes is also the most challenging step in cancer cell therapies such as adoptive cell transfer and T cell receptor (TCR) cloning. Here, we have elaborated a protocol for the identification of tumor-specific T lymphocytes and the deciphering of their repertoires. B16 melanoma engraftment following anti-PD1 checkpoint therapy provides better antitumor immunity compared to repetitive immunization with heat-shocked tumor cells. We have also revealed that the most error-prone part of dendritic cell (DC) generation, i.e., their maturation step, can be omitted if DCs are cultured at a sufficiently high density. Using this optimized protocol, we have achieved a robust IFNγ response to B16F0 antigens, but only within CD4+ T helper cells. A comparison of the repertoires of IFNγ-positive and -negative cells shows a prominent enrichment of certain clones with putative tumor specificity among the IFNγ+ fraction. In summary, our optimized protocol and the data provided here will aid in the acquisition of broad statistical data and the creation of a meaningful database of B16-specific TCRs.

RNA-Seq-Based TCR Profiling Reveals Persistently Increased Intratumoral Clonality in Responders to Anti-PD-1 Therapy.

Substantial effort is being invested in the search for peripheral or intratumoral T cell receptor (TCR) repertoire features that could predict the response to immunotherapy. Here we demonstrate the utility of MiXCR software for TCR and immunoglobulin repertoire extraction from RNA-Seq data obtained from sorted tumor-infiltrating T and B cells. We use this approach to extract TCR repertoires from RNA-Seq data obtained from sorted tumor-infiltrating CD4+ and CD8+ T cells in an HKP1 (KrasG12Dp53-/-) syngeneic mouse model of lung cancer after anti-PD-1 treatment. For both subsets, we demonstrate decreased TCR diversity in response to therapy. At a later time point, repertoire diversity is restored in progressing disease but remains decreased in responders to therapy in both CD4+ and CD8+ subsets. These observations complement previous studies and suggest that stably increased intratumoral CD4+ and CD8+ T cell clonality after anti-PD-1/PD-L1 therapy could serve as a predictor of long-term response.

Measuring Intratumoral Heterogeneity of Immune Repertoires.

There is considerable clinical and fundamental value in measuring the clonal heterogeneity of T and B cell expansions in tumors and tumor-associated lymphoid structures-along with the associated heterogeneity of the tumor neoantigen landscape-but such analyses remain challenging to perform. Here, we propose a straightforward approach to analyze the heterogeneity of immune repertoires between different tissue sections in a quantitative and controlled way, based on a beta-binomial noise model trained on control replicates obtained at the level of single-cell suspensions. This approach allows to identify local clonal expansions with high accuracy. We reveal in situ proliferation of clonal T cells in a mouse model of melanoma, and analyze heterogeneity of immunoglobulin repertoires between sections of a metastatically-infiltrated lymph node in human melanoma and primary human colon tumor. On the latter example, we demonstrate the importance of training the noise model on datasets with depth and content that is comparable to the samples being studied. Altogether, we describe here the crucial basic instrumentarium needed to facilitate proper experimental setup planning in the rapidly evolving field of intratumoral immune repertoires, from the wet lab to bioinformatics analysis.