Through the tumor necrosis factor (TNF) receptor type II (TNFR2), TNF preferentially activates, expands, and promotes the phenotypic stability of CD4⁺Foxp3⁺ regulatory T (T_reg) cells. Those T_reg cells that have a high abundance of TNFR2 have the maximal immunosuppressive capacity. We investigated whether targeting TNFR2 could effectively suppress the activity of T_reg cells and consequently enhance the efficacy of cancer immunotherapy. We found that, relative to a suboptimal dose of the immunostimulatory Toll-like receptor 9 ligand CpG oligodeoxynucleotide (ODN), the combination of the suboptimal dose of CpG ODN with the TNFR2-blocking antibody M861 more markedly inhibited the growth of subcutaneously grafted mouse CT26 colon tumor cells. This resulted in markedly fewer TNFR2⁺ T_reg cells and more interferon-γ–positive (IFN-γ⁺) CD8⁺ cytotoxic T lymphocytes infiltrating the tumor and improved long-term tumor-free survival in the mouse cohort. Tumor-free mice were resistant to rechallenge by the same but not unrelated (4T1 breast cancer) cells. Treatment with the combination of TNFR2-blocking antibody and a CD25-targeted antibody also resulted in enhanced inhibition of tumor growth in a syngeneic 4T1 mouse model of breast cancer. Thus, the combination of a TNFR2 inhibitor and an immunotherapeutic stimulant may represent a more effective treatment strategy for various cancers.

Immune cells constitute a large fraction of the tumor microenvironment and modulate tumor progression. Clinical data indicate that chronic inflammation is present at tumor sites and that IL4 in particular is upregulated. Here, we demonstrate that T follicular helper (Tfh) cells arise in tumor-draining lymph nodes where they produce an abundance of IL4. Deletion of IL4-expressing Tfh cells improves antitumor immunity, delays tumor growth, and reduces the generation of immunosuppressive myeloid cells in the lymph nodes. These findings suggest that IL4 from Tfh cells affects antitumor immunity and constitutes an attractive therapeutic target to reduce immunosuppression in the tumor microenvironment, and thus enhance the efficacy of cancer immunotherapy. Cancer Immunol Res; 5(1); 61–71. ©2016 AACR.

Epithelial ovarian cancer (EOC) is a fatal gynecologic cancer, and its poor prognosis is mainly due to delayed diagnosis. Therefore, biomarker identification and prognosis prediction are crucial in EOC. Altered cell metabolism is a characteristic feature of cancers, and metabolomics reflects an individual’s current phenotype. In particular, plasma metabolome analyses can be useful for biomarker identification. In this study, we analyzed 624 metabolites, including uremic toxins (UTx) in plasma derived from 80 patients with EOC using ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). Compared with the healthy control, we detected 77 significantly increased metabolites and 114 significantly decreased metabolites in EOC patients. Especially, decreased concentrations of lysophosphatidylcholines and phosphatidylcholines and increased concentrations of triglycerides were observed, indicating a metabolic profile characteristic of EOC patients. After calculating the parameters of each metabolic index, we found that higher ratios of kynurenine to tryptophan correlates with worse prognosis in EOC patients. Kynurenine, one of the UTx, can affect the prognosis of EOC. Our results demonstrated that plasma metabolome analysis is useful not only for the diagnosis of EOC, but also for predicting prognosis with the variation of UTx and evaluating response to chemotherapy.

Background: A paradigm shift has occurred in cancer chemotherapy from tumor‐specific treatment with cytotoxic agents to personalized medicine with molecular‐targeted drugs. Thus, it is essential to identify genomic alterations and molecular features to recommend effective targeted molecular medicines regardless of the tumor site. Nevertheless, it takes considerable expertise to identify treatment targets from primary‐sequencing data in order to provide drug recommendations. The Molecular Tumor Board (MTB) denotes a platform that integrates clinical and molecular features for clinical decisions.Methods: This study retrospectively analyses all the cases of discussion and decision at the MTB in Tohoku University Hospital and summarizes genetic alterations and treatment recommendations.Results: The MTB discussed 1003 comprehensive genomic profiling (CGP) tests conducted in patients with solid cancer, and the resulting rate of assessing treatment recommendations was approximately 19%. Among hundreds of genes in the CGP test, only 30 genetic alterations or biomarkers were used to make treatment recommendations. The leading biomarkers that led to treatment recommendations were tumor mutational burden‐high (TMB‐H) (n = 32), ERBB2 amplification (n = 24), BRAF V600E (n = 16), and BRCA1/2 alterations (n = 32). Thyroid cancer accounted for most cancer cases for which treatment recommendation was provided (81.3%), followed by non‐small cell lung cancer (42.4%) and urologic cancer (31.3%). The number of tests performed for gastrointestinal cancers was high (n = 359); however, the treatment recommendations for the same were below average (13%).Conclusion: The results of this study may be used to simplify treatment recommendations from the CGP reports and help select patients for testing, thereby increasing the accuracy of personalized medicine.