Background Inhibitors targeting immune checkpoint were proved effective in cancer immunotherapy, such as PD-1/PD-L1 blockade. The novel immune checkpoint TIGIT/PVR plays critical roles in suppressing the anti-tumor effects of CD8+ T and NK cells, and dual blockade of TIGIT/PVR and PD-1/PD-L1 by antibody can elicit synergistic effects in tumor models and clinical trials. However, small molecules for TIGIT/PVR blockade have not been investigated. Methods The expression of PVR in tumors were analyzed by using TCGA, Oncomine and GEO database, and in cancer cell lines examined by flow cytometry. Natural product compounds were docked to PVR for virtual screening by using the software Molecular Operating Environment (MOE). Candidate compounds were further tested by biolayer interferometry-based binding assay, microscale thermophoresis assay and cell based blocking assay. The in vitro activity of the candidate compound was determined by MTT, peripheral blood mononuclear cells (PBMCs) activation assay and coculture assay. The anti-tumor effects and mechanism were also investigated by using MC38 tumor-bearing mice model and immune cell depletion tumor model. Results PVR was over-expressed in many tumor tissues and cancer cell lines, making it a promising therapeutic target. Through virtual screening, binding, and blocking assay, liothyronine was discovered to bind PVR and block the interaction of TIGIT/PVR. Liothyronine could enhance the function of CD4+ and CD8+ T cells in PBMCs. Besides, in the Jurkat-hTIGIT and CHOK1-hPVR coculture assay, liothyronine could reverse the IL-2 secretion inhibition resulted by TIGIT/PVR ligation. Although had no influence on the proliferation of tumor cells in vitro, liothyronine could significantly inhibit tumor growth when administrated in vivo, by enhancing CD8+ T cell infiltration and immune responses in the tumor bearing mice. The immune cell depletion model showed that the anti-tumor effects of liothyronine depends on CD4+ T cells, CD8+ T cells and NK cells. Conclusions A small molecule liothyronine was discovered to serve as a potential candidate for cancer immunotherapy by blocking the immune checkpoint TIGIT/PVR. Graphical abstract

In this paper, a calibration approach based on transfer function extraction for the Cartesian vector modulator (VM) is presented. Three kinds of VM models-the ideal VM model, the frequencydependent VM model and the modified frequency-dependent VM model, are introduced in the proposed calibration approach. The calibration approach starts with an initialization of the transfer function of the modified frequency-dependent VM model. Then, the parameters of the transfer function are modified and extracted from the data of the measured transmission state (transmission amplitude and phase) of the actual VM by iteration, until the transmission state predicted by the extracted transfer function agrees well with the measured transmission state. Subsequently, the extracted transfer function of the modified frequencydependent VM model is capable of describing the transmission characteristics of the actual VM, and the calibrated baseband control voltages for the desired transmission amplitude and phase of the actual VM are able to be obtained by using the extracted transfer function. An actual VM is used as an example to verify this method. By adopting the proposed method, the maximum amplitude and phase errors at different complex gain setpoints are reduced to 0.05 dB and 0.3 • respectively after only two iteration steps. Since the actual VM is able to be accurately calibrated in only a few iteration steps, the results reveal that high accuracy and efficiency can be obtained in this calibration technique, which is well suited for applications involving high-accuracy calibration, real-time calibration and multichannel VM system calibration. INDEX TERMS Calibration, gain control, phase control, transfer function, vector modulator (VM).