Characterization and ex vivo expansion of rare in situ cytokine secreting T cell populations from tumor tissue and blood of oral squamous cell carcinoma patients.

Rare subpopulations of tumor antigen-reactive memory T cells, which actively secrete type-1 effector cytokines, particularly TNF-α in situ, possess anti-tumor activity and prognostic relevance. These cells are relevant for cancer immunotherapy; however, their low frequencies make them difficult to study and novel protocols for their culture and expansion ex vivo are needed. Here, we studied the presence of T cells secreting type-1 cytokines (Cy+T cells) in the blood and tumors of 24 patients with oral squamous cell carcinomas (OSCC) and explored possibilities for their isolation and expansion. More than 90% of OSCC patients contained enriched numbers Cy+T cells in the blood and tumors compared to healthy donors in which these were hardly detectable. The majority of TNF-α+T cells were CD4+ T helper cells while IFN-γ+TIL were predominantly CD8+. Cy+T helper cells in the blood were early-differentiated memory T cells while Cy+TIL and Cy+CD8+T cells showed advanced-differentiated memory T cell phenotypes. We explored different conditions for their in vitro culture and found that Cy+T cells can be efficiently expanded in vitro to similar levels as Cy-T cells and after expansion maintained their TNF-α secreting capacity. However, for optimal expansion they required specific culture conditions to support the maintenance of stem-like and central memory T cell phenotype. In conclusion, we show that Cy+T cells are enriched in OSCC patients and report a novel cell culture protocol optimized to specifically expand and functionally maintain these cells for further functional characterization or for their exploitation in immunotherapy of OSCC.

Causal Modeling of Cancer-Stromal Communication Identifies PAPPA as a Novel Stroma-Secreted Factor Activating NFκB Signaling in Hepatocellular Carcinoma.

Inter-cellular communication with stromal cells is vital for cancer cells. Molecules involved in the communication are potential drug targets. To identify them systematically, we applied a systems level analysis that combined reverse network engineering with causal effect estimation. Using only observational transcriptome profiles we searched for paracrine factors sending messages from activated hepatic stellate cells (HSC) to hepatocellular carcinoma (HCC) cells. We condensed these messages to predict ten proteins that, acting in concert, cause the majority of the gene expression changes observed in HCC cells. Among the 10 paracrine factors were both known and unknown cancer promoting stromal factors, the former including Placental Growth Factor (PGF) and Periostin (POSTN), while Pregnancy-Associated Plasma Protein A (PAPPA) was among the latter. Further support for the predicted effect of PAPPA on HCC cells came from both in vitro studies that showed PAPPA to contribute to the activation of NFκB signaling, and clinical data, which linked higher expression levels of PAPPA to advanced stage HCC. In summary, this study demonstrates the potential of causal modeling in combination with a condensation step borrowed from gene set analysis [Model-based Gene Set Analysis (MGSA)] in the identification of stromal signaling molecules influencing the cancer phenotype.