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Background: Immune checkpoint inhibitors unleash inhibitory signals on T cells conferred by tumors and surrounding stromal cells. Despite the clinical efficacy of checkpoint inhibitors, the lack of target expression and persistence of immunosuppressive cells limit the pervasive effectiveness of the therapy. These limitations may be overcome by alternative approaches that co-stimulate T cells and the immune microenvironment., Methods: We analyzed single-cell RNA sequencing data from multiple human cancers and a mouse tumor transplant model to discover the pleiotropic expression of the Interleukin 7 (IL-7) receptor on T cells, macrophages, and dendritic cells., Results: Our experiment on the mouse model demonstrated that recombinant IL-7 therapy induces tumor regression, expansion of effector CD8 T cells, and pro-inflammatory activation of macrophages. Moreover, spatial transcriptomic data support immunostimulatory interactions between macrophages and T cells., Conclusion: These results indicate that IL-7 therapy induces anti-tumor immunity by activating T cells and pro-inflammatory myeloid cells, which may have diverse therapeutic applicability., (© 2024. The Author(s).)

To elucidate the epigenetic mechanisms of drug resistance, epigenetically reprogrammed H460 cancer cells (R-H460) were established by the transient introduction of reprogramming factors. Then, the R-H460 cells were induced to differentiate by the withdrawal of stem cell media for various durations, which resulted in differentiated R-H460 cells (dR-H460). Notably, dR-H460 cells differentiated for 13 days (13dR-H460 cells) formed a significantly greater number of colonies showing drug resistance to both cisplatin and paclitaxel, whereas the dR-H460 cells differentiated for 40 days (40dR-H460 cells) lost drug resistance; this suggests that 13dR-cancer cells present short-term resistance (less than a month). Similarly, increased drug resistance to both cisplatin and paclitaxel was observed in another R-cancer cell model prepared from N87 cells. The resistant phenotype of the cisplatin-resistant (CR) colonies obtained through cisplatin treatment was maintained for 2-3 months after drug treatment, suggesting that drug treatment transforms cells with short-term resistance into cells with medium-term resistance. In single-cell analyses, heterogeneity was not found to increase in 13dR-H460 cells, suggesting that cancer cells with short-term resistance, rather than heterogeneous cells, may confer epigenetically driven drug resistance in our reprogrammed cancer model. The epigenetically driven short-term and medium-term drug resistance mechanisms could provide new cancer-fighting strategies involving the control of cancer cells during epigenetic transition.

Background: Cell surface proteins have provided useful targets and biomarkers for advanced cancer therapies. The recent clinical success of antibody-drug conjugates (ADCs) highlights the importance of finding selective surface antigens for given cancer subtypes. We thus attempted to develop stand-alone software for the analysis of the cell surface transcriptome of patient cancer samples and to prioritize lineage- and/or mutation-specific over-expression markers in cancer cells., Results: A total of 519 genes were selected as surface proteins, and their expression was profiled in 14 cancer subtypes using patient sample transcriptome data. Lineage/mutation-oriented analysis was used to identify subtype-specific surface markers with statistical confidence. Experimental validation confirmed the unique over-expression of predicted surface markers (MUC4, MSLN, and SLC7A11) in lung cancer cells at the protein level. The differential cell surface gene expression of cell lines may differ from that of tissue samples due to the absence of the tumor microenvironment., Conclusions: In the present study, advanced 3D models of lung cell lines successfully reproduced the predicted patterns, demonstrating the physiological relevance of cell line-based 3D models in validating surface markers from patient tumor data. Also QSurface software is freely available at http://compbio.sookmyung.ac.kr/~qsurface .