Identification of two distinct head and neck squamous cell carcinoma subtypes based on fatty acid metabolism-related signatures: Implications for immunotherapy and chemotherapy.

The dysregulation of lipid metabolism is a critical factor in the initiation and progression of tumors. In this investigation, we aim to characterize the molecular subtypes of head and neck squamous cell carcinoma (HNSCC) based on their association with fatty acid metabolism and develop a prognostic risk model. The transcriptomic and clinical data about HNSCC were obtained from public databases. Clustering analysis was conducted on fatty acid metabolism genes (FAMG) associated with prognosis, utilizing the non-negative matrix factorization algorithm. The immune infiltration, response to immune therapy, and drug sensitivity between molecular subtypes were evaluated. Differential expression genes were identified between subtypes, and a prognostic model was constructed using Cox regression analyses. A nomogram for HNSCC was constructed and evaluated. Thirty FAMGs have been found to exhibit differential expression in HNSCC, out of which three are associated with HNSCC prognosis. By performing clustering analysis on these 3 genes, 2 distinct molecular subtypes of HNSCC were identified that exhibit significant heterogeneity in prognosis, immune landscape, and treatment response. Using a set of 7778 genes that displayed differential expression between the 2 molecular subtypes, a prognostic risk model for HNSCC was constructed comprising 11 genes. This model has the ability to stratify HNSCC patients into high-risk and low-risk groups, which exhibit significant differences in prognosis, immune infiltration, and immune therapy response. Moreover, our data suggest that this risk model is negatively correlated with B cells and most T cells, but positively correlated with macrophages, mast cells, and dendritic cells. Ultimately, we constructed a nomogram incorporating both the risk signature and radiotherapy, which has demonstrated exceptional performance in predicting prognosis for HNSCC patients. A molecular classification system and prognostic risk models were developed for HNSCC based on FAMGs. This study revealed the potential involvement of FAMGs in modulating tumor immune microenvironment and response to treatment.

Surface display of major capsid protein on Bacillus subtilis spores against largemouth bass virus (LMBV) for oral administration.

Largemouth bass virus (LMBV) infections resulting in enormous loss are becoming an increasing problem in the largemouth bass industry. Oral vaccination is considered to be an effective and economical measure because of the advantages of non-invasion, no size limitation, lower cost and easily-operated. Based on Bacillus subtilis (B. subtilis) spores, this study successfully constructed the CotC-LMBV recombinant B. subtilis spores and its protective efficacy and immune responses were evaluated. After challenged, the survival rate of largemouth bass orally vaccinated with CotC-LMBV spores was 53.3% and the relative percent survival (RPS) was 45.0% compared to the PBS group. In addition, the specific IgM level in serum in the CotC-LMBV group was significantly higher than in the control groups. In the spleen, the immune-related genes expression detected by quantitative real-time PCR (qRT-PCR) exhibited an increasing trend in different degrees in the CotC-LMBV group, suggesting that innate and adaptive immune responses were activated. This study indicated that oral administration of CotC-LMBV recombinant spores could stimulate an effective immune response and enhance fish immunity against LMBV infection. Therefore, oral vaccination could be an effective approach for the prevention of largemouth bass virus disease.

Prediction of Minor Salivary Gland Carcinoma: A Novel Nomogram and Risk Classification System for Overall Survival and Cancer-Specific Survival.

OBJECTIVE: Minor salivary gland carcinoma (MiSGC) is rare, and the understanding of this disease is insufficient. This study aimed to identify independent risk factors and develop a nomogram for evaluating the overall survival (OS) and cancer-specific survival (CSS) of patients with MiSGC. STUDY DESIGN: Retrospective cohort study. SETTING: SEER database (Surveillance, Epidemiology, and End Results). SUBJECTS AND METHODS: We collected data from patients diagnosed with MiSGC between 2004 and 2015 from the SEER database. According to patient registration, all patients were randomly allocated to training sets and validation sets (2:1). Then, Kaplan-Meier product limit curves and Cox proportional hazard regressions were performed to estimate the prognostic effect of variables. Nomograms based on Cox proportional hazard regressions were established to estimate 3- and 5-year OS and CSS. Finally, the nomogram was developed by the training set, and validation was performed with the concordance index, calibration curves, and decision curve analyses. RESULTS: In total, 1787 MiSGC cases were registered in SEER. The concordance index for internal validation of OS and CSS prediction was 0.842 and 0.816; that of external validation was 0.871 and 0.831. The calibration plots showed good consistency between nomogram prediction and actual survival. The decision curve analysis showed substantial net benefits of the new predictive model. CONCLUSIONS: We constructed nomograms and a corresponding risk classification system predicting the OS and CSS of patients with MiSGC. These tools can generate simple-to-use clinical risk grouping and determine the relationship between adjuvant therapy and active surveillance.