Russell William Jenkins

Many cancer patients treated with immune checkpoint blockade (ICB) do not have durable treatment responses. Circulating biomarkers have the potential to identify patients with primary resistance or early progression on therapy to alter treatment course and potentially avoid unnecessary toxicity. Unbiased multimodal proteomic profiling in blood has been underexplored due to the previously limited scalability of multiplexing technologies or cohorts lacking time-series sampling. To address this, we performed plasma proteomic profiling of >2900 proteins and high-dimensional mass cytometry of peripheral blood lymphocytes across serial time points in 250 metastatic melanoma patients on ICB treatment. We further obtained 92 patient-matched tumor samples, which were processed for single-cell and/or bulk RNA sequencing. Proteins upregulated post-ICB were associated with inflammatory pathways involving the activation of effector immune functions. Expression of genes corresponding to these proteins was higher in immune cells involved in recruitment and tumor reactivity. Expression of genes corresponding to plasma proteins more abundant in non-responders was highest in suppressive myeloid subsets and malignant cells. We further posit the involvement of these non-responder genes in immunosuppressive and pro-tumor interactions, which we confirm using publicly available spatial transcriptomic data. We also find that epithelial-specific proteins in the circulation of responders post-ICB associate with patient toxicity and likely originate from degradation of healthy tissues. Together, these data represent extensive potential peripheral biomarker characterization using paired blood and tumor samples in melanoma patients treated with ICB, and begin to elucidate the complex interplay between tumors and the systemic immune response within the host.

PDOTS patient data (accompanying Fig. 3)

Supplemental Figure S4 | Supporting data for ex vivo profiling of PD-1 blockade and TBK1 inhibition in combination with B7-H3.CAR-T cells using PDOTS.

Supplemental Figure S5 | Supporting data that targeting TBK1 prevents CAR-T cell dysfunction.

Supplemental Figure S6 | Supporting data that targeting TBK1 prevents CAR-T cell dysfunction.

Supplemental Figure S10 | Supporting data for single cell RNA sequencing of native tumor-infiltrating lymphocytes following CAR-T challenge in 3D co-cultures with PDOTS.

PDOTS patient data (accompanying Fig. 2)

Supplemental Figure S3 | Supporting data for ex vivo profiling of B7-H3.CAR-T cells using PDOTS.

PDOTS patient data (accompanying Fig. 1)

Supplemental Figure S11 | Supporting data that targeting TBK1 sensitizes cancer cells to CAR-T cell-derived TNFα/IFNγ.