The blockade of programmed cell death protein 1 (PD-1) as monotherapy has been widely used in melanoma, but to identify melanoma patients with survival benefit from anti-PD-1 monotherapy is still a big challenge. There is an urgent need for prognostic signatures improving the prediction of immunotherapy responses of these patients. We analyzed transcriptomic data of pre-treatment tumor biopsies and clinical profiles in advanced melanoma patients receiving only anti-PD-1 monotherapy (nivolumab or pembrolizumab) from the PRJNA356761 and PRJEB23709 data sets as the training and validation cohort, respectively. Weighted gene co-expression network analysis was used to identify the key module, then least absolute shrinkage and selection operator was conducted to determine prognostic-related long noncoding RNAs (lncRNAs). Subsequently, the differentially expressed genes between different clusters were identified, and their function and pathway annotation were performed. In this investigation, 92 melanoma patients with complete survival information (51 from training cohort and 41 from validation cohort) were included in our analyses. We initiallyidentified the key module (skyblue) by weighted gene co-expression network analysis, and then identified a 15 predictive lncRNAs (AC010904.2, LINC01126, AC012360.1, AC024933.1, AL442128.2, AC022211.4, AC022211.2, AC127496.5, NARF-AS1, AP000919.3, AP005329.2, AC023983.1, AC023983.2, AC139100.1, and AC012615.4) signature in melanoma patients treated with anti-PD-1 monotherapy by least absolute shrinkage and selection operator in the training cohort. These results were then validated in the validation cohort. Finally, enrichment analysis showed that the functions of differentially expressed genes between two consensus clusters were mainly related to the immune process and treatment. In summary, the 15 lncRNAs signature is a novel effective predictor for prognosis in advanced melanoma patients treated with anti-PD-1 monotherapy.

The circular RNA (circRNA) family is a group of endogenous non-coding RNAs (ncRNAs) that have critical functions in multiple physiological and pathological processes, including inflammation, cancer, and cardiovascular diseases. However, their roles in regulating innate immune responses remain unclear. Here, we define Cell division cycle 42 (CDC42)−165aa, a protein encoded by circRNA circCDC42, which is overexpressed in Klebsiella pneumoniae (KP)-infected alveolar macrophages. High levels of CDC42-165aa induces the hyperactivation of Pyrin inflammasomes and aggravates alveolar macrophage pyroptosis, while the inhibition of CDC42-165aa reduces lung injury in mice after KP infection by inhibiting Pyrin inflammasome-mediated pyroptosis. Overall, these results demonstrate that CDC42-165aa stimulates Pyrin inflammasome by inhibiting CDC42 GTPase activation and provides a potential clinical target for pathogenic bacterial infection in clinical practice.