Lung cancer is the leading cause of cancer mortality worldwide. Dendritic cells (DCs) are the key factors providing protective immunity against lung tumors and clinical trials have proven that DC function is reduced in lung cancer patients. It is evident that the immunoregulatory network may play a key role in the failure of the immune response to terminate tumors. Lung tumors likely employ numerous strategies to suppress DC‐based anti‐tumor immunity. Here, we summarize the recent advances in our understanding on lung tumor‐induced immunosuppression in DCs, which affects the initiation and development of T‐cell responses. We also describe which existing measures to restore DC function may be useful for clinical treatment of lung tumors. Furthering our knowledge of how lung cancer cells alter DC function to generate a tumor‐supportive environment will be essential in order to guide the design of new immunotherapy strategies for clinical use.

Specific types of nephroblastoma (Wilms' tumor, WT) are known to associate with poor overall survival. Emerging experimental evidence has demonstrated that competitive endogenous RNA (ceRNA) networks have important roles in regulating cancer occurrence, but the roles of ceRNAs in regulating the WT progression and the patient outcomes remain unclear. Using the multi-omics data of 132 WT patients collected from TARGET database, an integration analysis pipeline was performed to construct a highly reliable ceRNA network. As results, a total of 147 nodes (116 mRNAs, 15 miRNAs, and 16 lncRNAs) were identified and used to explore the underlying mechanism for WT progression. WGCNA analysis further identified several prognostic molecules, including hsa-mir-93, LINC00087 and RP5-1086K13, that significantly associated with the overall survival rate. And, enrichment analysis verified the participation of these molecules in tumor-related pathways, such as those controlling autophagy and cadherin-mediated adhesion. Importantly, the WT patients were classified into three categories according to the ceRNA network, which significantly correlated with the overall survival. In conclusion, the ceRNA network could be a promising tool to further validate the prognostic biomarkers and categories of patients diagnosed with WT.

Long non-coding RNA (lncRNA)-mediated competitive endogenous RNA (ceRNA) networks act as essential mechanisms in tumor initiation and progression, but their diagnostic and prognostic significance in prostate cancer (PCa) remains poorly understood. Presently, using the RNA expression data derived from multiple independent PCa-related studies, we constructed a high confidence and PCa-specific core ceRNA network by employing three lncRNA-gene inference approaches and key node filter strategies and then established a logistic model and risk score formula to evaluate its diagnostic and prognostic values, respectively. The core ceRNA network consists of 10 nodes, all of which are significantly associated with clinical outcomes. Combination of expression of the 10 ceRNAs with a logistic model achieved AUC of ROC and PR curve up to ∼96 and 99% in excluding normal prostate samples, respectively. Additionally, a risk score formula constructed with the ceRNAs exhibited significant association with disease-free survival. More importantly, utilizing the expression of RNAs in the core ceRNA network as a molecular signature, the TCGA-PRAD cohort was divided into four novel clinically relevant subgroups with distinct expression patterns, highlighting a feasible way for improving patient stratification in the future. Overall, we constructed a PCa-specific core ceRNA network, which provides diagnostic and prognostic value.