Although great progresses have been made in the diagnosis and treatment of hepatocellular carcinoma (HCC), its prognostic marker remains controversial. In this current study, weighted correlation network analysis and Cox regression analysis showed significant prognostic value of five autophagy-related long non-coding RNAs (AR-lncRNAs) (including TMCC1-AS1, PLBD1-AS1, MKLN1-AS, LINC01063, and CYTOR) for HCC patients from data in The Cancer Genome Atlas. By using them, we constructed a five-AR-lncRNA prognostic signature, which accurately distinguished the high- and low-risk groups of HCC patients. All of the five AR lncRNAs were highly expressed in the high-risk group of HCC patients. This five-AR-lncRNA prognostic signature showed good area under the curve (AUC) value (AUC = 0.751) for the overall survival (OS) prediction in either all HCC patients or HCC patients stratified according to several clinical traits. A prognostic nomogram with this five-AR-lncRNA signature predicted the 3- and 5-year OS outcomes of HCC patients intuitively and accurately (concordance index = 0.745). By parallel comparison, this five-AR-lncRNA signature has better prognosis accuracy than the other three recently published signatures. Furthermore, we discovered the prediction ability of the signature on therapeutic outcomes of HCC patients, including chemotherapy and immunotherapeutic responses. Gene set enrichment analysis and gene mutation analysis revealed that dysregulated cell cycle pathway, purine metabolism, and TP53 mutation may play an important role in determining the OS outcomes of HCC patients in the high-risk group. Collectively, our study suggests a new five-AR-lncRNA prognostic signature for HCC patients.Vitreoretinal lymphoma (VRL) is a rare ocular malignancy that manifests as diffuse large B-cell lymphoma. Early and accurate diagnosis is essential to prevent mistreatment and to reduce the high morbidity and mortality associated with VRL. The disease can be diagnosed using various methods, including cytology, immunohistochemistry, cytokine analysis, flow cytometry, and molecular analysis of bulk vitreous aspirates. Despite these options, VRL diagnosis remains challenging, as samples are often confounded by low cellularity, the presence of debris and non-target immunoreactive cells, and poor cytological preservation. As such, VRL diagnostic accuracy is limited by both false-positive and false-negative outcomes. Missed or inappropriate diagnosis may cause delays in treatment, which can have life-threatening consequences for patients with VRL. In this review, we summarize current knowledge and the diagnostic modalities used for VRL diagnosis. We also highlight several emerging molecular techniques, including high-resolution single cell-based analyses, which may enable more comprehensive and precise VRL diagnoses.Background Lung cancer is one of the most common types of cancer, and it has a poor prognosis. It is urgent to identify prognostic biomarkers to guide therapy. Methods The immune gene expression profiles for patients with lung adenocarcinomas (LUADs) were obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). The relationships between the expression of 45 immune checkpoint genes (ICGs) and prognosis were analyzed. Additionally, the correlations between the expression of 45 biomarkers and immunotherapy biomarkers, including tumor mutation burden (TMB), mismatch repair defects, neoantigens, and others, were identified. Ultimately, prognostic ICGs were combined to determine immune subgroups, and the prognostic differences between these subgroups were identified in LUAD. Results A total of 11 and nine ICGs closely related to prognosis were obtained from the GEO and TCGA databases, respectively. CD200R1 expression had a significant negative correlation with TMB and neoantigens. CD200R1 showed a significant positive correlation with CD8A, CD68, and GZMB, indicating that it may cause the disordered expression of adaptive immune resistance pathway genes. Multivariable Cox regression was used to construct a signature composed of four prognostic ICGs (IDO1, CD274, CTLA4, and CD200R1) Risk Score = -0.002*IDO1+0.031*CD274-0.069*CTLA4-0.517*CD200R1. The median Risk Score was used to classify the samples for the high- and low-risk groups. We observed significant differences between groups in the training, testing, and external validation cohorts. Conclusion Our research provides a method of integrating ICG expression profiles and clinical prognosis information to predict lung cancer prognosis, which will provide a unique reference for gene immunotherapy for LUAD.Therapeutic, diagnostic, and imaging approaches based on nanotechnology offer distinct advantages in cancer treatment. Various nanotherapeutics have been presented as potential alternatives to traditional anticancer therapies such as chemotherapy, radiotherapy, and surgical intervention. Notably, the advantage of nanotherapeutics is mainly attributable to their accumulation and targeting ability toward cancer cells, multiple drug-carrying abilities, combined therapies, and imaging approaches. To date, numerous nanoparticle formulations have been developed for anticancer therapy and among them, metallic nanotherapeutics reportedly demonstrate promising cancer therapeutic and diagnostic efficiencies owing to their dense surface functionalization ability, uniform size distribution, and shape-dependent optical responses, easy and cost-effective synthesis procedure, and multiple anti-cancer effects. Metallic nanotherapeutics can remodel the tumor microenvironment by changing unfavorable therapeutic conditions into therapeutically accessible ones with the help of different stimuli, including light, heat, ultrasound, an alternative magnetic field, redox, and reactive oxygen species. The combination of metallic nanotherapeutics with both external and internal stimuli can be used to trigger the on-demand release of therapeutic molecules, augmenting the therapeutic efficacies of anticancer therapies such as photothermal therapy, photodynamic therapy, magnetic hyperthermia, sonodynamic therapy, chemodynamic therapy, and immunotherapy. PP2 chemical structure In this review, we have summarized the role of different metallic nanotherapeutics in anti-cancer therapy, as well as their combinational effects with multiple stimuli for enhanced anticancer therapy.