Lele Zhang

BACKGROUND: Immunotherapy has revolutionized cancer treatment, but most patients are refractory to immunotherapy or acquire resistance, with the underlying mechanisms remaining to be explored. METHODS: We characterized the transcriptomes of ~92,000 single cells from 3 pre-treatment and 12 post-treatment patients with non-small cell lung cancer (NSCLC) who received neoadjuvant PD-1 blockade combined with chemotherapy. The 12 post-treatment samples were categorized into two groups based on pathologic response: major pathologic response (MPR; n = 4) and non-MPR (NMPR; n = 8). RESULTS: Distinct therapy-induced cancer cell transcriptomes were associated with clinical response. Cancer cells from MPR patients exhibited a signature of activated antigen presentation via major histocompatibility complex class II (MHC-II). Further, the transcriptional signatures of FCRL4+FCRL5+ memory B cells and CD16+CX3CR1+ monocytes were enriched in MPR patients and are predictors of immunotherapy response. Cancer cells from NMPR patients exhibited overexpression of estrogen metabolism enzymes and elevated serum estradiol. In all patients, therapy promoted expansion and activation of cytotoxic T cells and CD16+ NK cells, reduction of immunosuppressive Tregs, and activation of memory CD8+T cells into an effector phenotype. Tissue-resident macrophages were expanded after therapy, and tumor-associated macrophages (TAMs) were remodeled into a neutral instead of an anti-tumor phenotype. We revealed the heterogeneity of neutrophils during immunotherapy and identified an aged CCL3+ neutrophil subset was decreased in MPR patients. The aged CCL3+ neutrophils were predicted to interact with SPP1+ TAMs through a positive feedback loop to contribute to a poor therapy response. CONCLUSIONS: Neoadjuvant PD-1 blockade combined with chemotherapy led to distinct NSCLC tumor microenvironment transcriptomes that correlated with therapy response. Although limited by a small patient sample size subjected to combination therapy, this study provides novel biomarkers to predict therapy response and suggests potential strategies to overcome immunotherapy resistance.

Abstract N 6 -methyladenosine (m 6 A), the most abundant modification in eukaryotic cells, regulates RNA transcription, processing, splicing, degradation, and translation. Circular RNA (circRNA) is a class of covalently closed RNA molecules characterized by universality, diversity, stability and conservatism of evolution. Accumulating evidence shows that both m 6 A modification and circRNAs participate in the pathogenesis of multiple diseases, such as cancers, neurological diseases, autoimmune diseases, and infertility. Recently, m 6 A modification has been identified for its enrichment and vital biological functions in regulating circRNAs. In this review, we summarize the role of m 6 A modification in the regulation and function of circRNAs. Moreover, we discuss the potential applications and possible future directions in the field.

Significance cGAS (cytosolic DNA sensor cyclic AMP-GMP synthase)-STING (stimulator of interferon genes) signaling is critical for sensing cytosolic DNA to initiate host immune responses against invading pathogens and cancer. However, inappropriate activation of STING signaling causes severe and often fatal autoimmune or autoinflammatory diseases. Hence, STING is an attractive drug target for the treatment of STING-driven autoimmune and inflammatory disorders. Therefore, there is a need to identify lead compounds that effectively inhibit human STING for further drug development. Here, we identified and characterized a STING-specific inhibitor SN-011 with high efficiency, specificity, and safety, paving the way for therapeutically manipulating STING-mediated clinical diseases.

Abstract Purpose: The purpose of this study is to develop and validate a nomogram model combing radiomics features and clinical characteristics to preoperatively differentiate grade 1 and grade 2/3 tumors in patients with pancreatic neuroendocrine tumors (pNET). Experimental Design: A total of 137 patients who underwent contrast-enhanced CT from two hospitals were included in this study. The patients from the second hospital (n = 51) were selected as an independent validation set. The arterial phase in contrast-enhanced CT was selected for radiomics feature extraction. The Mann–Whitney U test and least absolute shrinkage and selection operator regression were applied for feature selection and radiomics signature construction. A combined nomogram model was developed by incorporating the radiomics signature with clinical factors. The association between the nomogram model and the Ki-67 index and rate of nuclear mitosis were also investigated respectively. The utility of the proposed model was evaluated using the ROC, area under ROC curve (AUC), calibration curve, and decision curve analysis (DCA). The Kaplan–Meier (KM) analysis was used for survival analysis. Results: An eight-feature–combined radiomics signature was constructed as a tumor grade predictor. The nomogram model combining the radiomics signature with clinical stage showed the best performance (training set: AUC = 0.907; validation set: AUC = 0.891). The calibration curve and DCA demonstrated the clinical usefulness of the proposed nomogram. A significant correlation was observed between the developed nomogram and Ki-67 index and rate of nuclear mitosis, respectively. The KM analysis showed a significant difference between the survival of predicted grade 1 and grade 2/3 groups (P = 0.002). Conclusions: The combined nomogram model developed could be useful in differentiating grade 1 and grade 2/3 tumor in patients with pNETs.