Down-regulation of MLLT1 super elongation complex subunit impairs the anti-tumor activity of natural killer cells in esophageal cancer

Immune Escape Strategies in Head and Neck Cancer: Evade, Resist, Inhibit, Recruit

Head and neck cancers (HNCs) arise from the mucosal lining of the aerodigestive tract and are often associated with alcohol use, tobacco use, and/or human papillomavirus (HPV) infection. Over 600,000 new cases of HNC are diagnosed each year, making it the sixth most common cancer worldwide. Historically, treatments have included surgery, radiation, and chemotherapy, and while these treatments are still the backbone of current therapy, several immunotherapies have recently been approved by the Food and Drug Administration (FDA) for use in HNC. The role of the immune system in tumorigenesis and cancer progression has been explored since the early 20th century, eventually coalescing into the current three-phase model of cancer immunoediting. During each of the three phases-elimination, equilibrium, and escape-cancer cells develop and utilize multiple strategies to either reach or remain in the final phase, escape, at which point the tumor is able to grow and metastasize with little to no detrimental interference from the immune system. In this review, we summarize the many strategies used by HNC to escape the immune system, which include ways to evade immune detection, resist immune cell attacks, inhibit immune cell functions, and recruit pro-tumor immune cells.

Janus Silica Nanoparticle-Based Tumor Microenvironment Modulator for Restoring Tumor Sensitivity to Programmed Cell Death Ligand 1 Immune Checkpoint Blockade Therapy

An immunosuppressive tumor microenvironment (TME) with inadequate and exhausted tumor-infiltrating cytotoxic lymphocytes and abundant cellular immunosuppressors is the major obstacle responsible for the poor efficacy of PD-1/PD-L1 (programmed cell death 1 and its ligand 1) immune checkpoint blockade (ICB) therapy. Herein, a Janus silica nanoparticle (JSNP)-based immunomodulator is explored to reshape the TME for boosting the therapeutic outcomes of αPD-L1 therapy. The designed JSNP has two distinct domains, namely, an ultra pH-responsive side (UPS), which could encapsulate PI3Kγ inhibitor IPI549 in the pore structure, and a polycation-grafted intra-glutathione (GSH)-sensitive side (IGS), which could absorb CXCL9 cDNA on the surface. The final IPI549@UPS-IGS-PDMAEMA@CXCL9 cDNA (IUIPC) could release IPI549 in weak acid TME to target myeloid-derived suppressor cells (MDSCs) to reverse negative immunoregulation and then release CXCL9 cDNA in tumor cells with abundant GSH for sustained CXCL9 chemokine expression and secretion to improve cytotoxic lymphocyte recruitment signals, thereby jointly restoring tumor sensitivity to PD-1/PD-L1 ICB therapy. As expected, the IUIPC-mediated TME remodeling during αPD-L1 therapy significantly ameliorated TME immunosuppression, as well as induced potent systemic antitumor immune responses, which ultimately achieved a robustly boosted antitumor efficacy proven by remarkable suppression of primary tumor growth, obvious prevention of tumor recurrence, and significant regression of abscopal tumors. Hence, the IUIPC-mediated TME-regulating strategy provides an enormous perspective for the improvement of PD-1/PD-L1 ICB therapy.

Weighted gene co-expression network analysis revealed T cell differentiation associated with the age-related phenotypes in COVID-19 patients

The risk of severe condition caused by Corona Virus Disease 2019 (COVID-19) increases with age. However, the underlying mechanisms have not been clearly understood. The dataset GSE157103 was used to perform weighted gene co-expression network analysis on 100 COVID-19 patients in our analysis. Through weighted gene co-expression network analysis, we identified a key module which was significantly related with age. This age-related module could predict Intensive Care Unit status and mechanical-ventilation usage, and enriched with positive regulation of T cell receptor signaling pathway biological progress. Moreover, 10 hub genes were identified as crucial gene of the age-related module. Protein-protein interaction network and transcription factors-gene interactions were established. Lastly, independent data sets and RT-qPCR were used to validate the key module and hub genes. Our conclusion revealed that key genes were associated with the age-related phenotypes in COVID-19 patients, and it would be beneficial for clinical doctors to develop reasonable therapeutic strategies in elderly COVID-19 patients.