B7-H1 (aka PD-L1) blocking antibodies have been used in treatment of human cancers through blocking B7-H1 expressed by tumor cells; however, their impact on B7-H1 expressing tumor-reactive CD8+ T cells is still unknown. Here, we report that tumor-reactive CD8+ T cells expressing B7-H1 are functional effector cells. In contrast to normal B7-H1 blocking antibody, B7-H1 antibodies capable of activating p38 MAPK lose their antitumor activity by deleting B7-H1+ tumor-reactive CD8+ T cells via p38 MAPK pathway. B7-H1 deficiency or engagement with certain antibody results in more activation of p38 MAPK that leads to T cell apoptosis. DNA-PKcs is a new intracellular partner of B7-H1 in the cytoplasm of activated CD8+ T cells. B7-H1 suppresses p38 MAPK activation by sequestering DNA-PKcs in order to preserve T cell survival. Our findings provide a new mechanism of action of B7-H1 in T cells and have clinical implications in cancer immunotherapy when anti-B7-H1 (PD-L1) antibody is applied.

Although 70-80% of newly diagnosed ovarian cancer patients respond to first-line therapy, almost all relapse and five-year survival remains below 50%. One strategy to increase five-year survival is prolonging time to relapse by improving first-line therapy response. However, no biomarker today can accurately predict individual response to therapy. In this study, we present analytical and prospective clinical validation of a new test that utilizes primary patient tissue in 3D cell culture to make patient-specific response predictions prior to initiation of treatment in the clinic. Test results were generated within seven days of tissue receipt from newly diagnosed ovarian cancer patients obtained at standard surgical debulking or laparoscopic biopsy. Patients were followed for clinical response to chemotherapy. In a study population of 44, the 32 test-predicted Responders had a clinical response rate of 100% across both adjuvant and neoadjuvant treated populations with an overall prediction accuracy of 89% (39 of 44, p < 0.0001). The test also functioned as a prognostic readout with test-predicted Responders having a significantly increased progression-free survival compared to test-predicted Non-Responders, p = 0.01. This correlative accuracy establishes the test's potential to benefit ovarian cancer patients through accurate prediction of patient-specific response before treatment.

As patient derived xenograft (PDX) models are increasingly used for preclinical drug development, strategies to account for the nonhuman component of PDX RNA expression data are critical to its interpretation. A bioinformatics pipeline to separate donor tumor and mouse stroma transcriptome profiles was devised and tested. To examine the molecular fidelity of PDX versus donor tumors, we compared mRNA differences between paired PDX-donor tumors from nine ovarian cancer patients. 1,935 differentially expressed genes were identified between PDX and donor tumors. Over 90% (n = 1767) of these genes were down-regulated in PDX models and enriched in stroma-specific functions. Several protein kinases were also differentially expressed in PDX tumors, e.g. PDGFRA, PDGFRB and CSF1R. Upon in silico removal of these PDX-donor tumor differentially expressed genes, a stronger transcriptional resemblance between PDX-donor tumor pairs was seen (average correlation coefficient increases from 0.91 to 0.95). We devised and validated an effective bioinformatics strategy to separate mouse stroma expression from human tumor expression for PDX RNAseq. In addition, we showed most of the PDX-donor differentially expressed genes were implicated in stromal components. The molecular similarities and differences between PDX and donor tumors have implications in future therapeutic trial designs and treatment response evaluations using PDX models.

Very little is known about how the adaptive immune system responds to clonal evolution and tumor heterogeneity in non-small cell lung cancer. We profiled the T-cell receptor β complementarity determining region 3 in 20 patients with fully resected non-small cell lung cancer primary lesions and paired brain metastases. We characterized the richness, abundance and overlap of T cell clones between pairs, in addition to the tumor mutation burden and predicted neoantigens. We found a significant contraction in the number of unique T cell clones in brain metastases compared to paired primary cancers. The vast majority of T cell clones were specific to a single lesion, and there was minimal overlap in T cell clones between paired lesions. Despite the contraction in the number of T cell clones, brain metastases had higher non-synonymous mutation burdens than primary lesions. Our results suggest that there is greater richness of T cell clones in primary lung cancers than their paired metastases despite the higher mutation burden observed in metastatic lesions. These results may have implications for immunotherapy.