Integrating p53-associated genes and infiltrating immune cell characterization as a prognostic biomarker in multiple myeloma.

Background: Tumor genetic anomalies and immune dysregulation are pivotal in the progression of multiple myeloma (MM). Accurate patient stratification is essential for effective MM management, yet current models fail to comprehensively incorporate both molecular and immune profiles. Methods: We examined 776 samples from the MMRF CoMMpass database, employing univariate regression with LASSO and CIBERSORT algorithms to identify 15 p53-related genes and six immune cells with prognostic significance in MM. A p53-TIC (tumor-infiltrating immune cells) classifier was constructed by calculating scores using the bootstrap-multicox method, which was further validated externally (GSE136337) and through ten-fold internal cross-validation for its predictive reliability and robustness. Results: The p53-TIC classifier demonstrated excellent performance in predicting the prognosis in MM. Specifically, patients in the p53low/TIChigh subgroup had the most favorable prognosis and the lowest tumor mutational burden (TMB). Conversely, those in the p53high/TIClow subgroup, with the least favorable prognosis and the highest TMB, were predicted to have the best anti-PD1 and anti-CTLA4 response rate (40 %), which can be explained by their higher expression of PD1 and CTLA4. The three-year area under the curve (AUC) was 0.80 in the total sample. Conclusions: Our study highlights the potential of an integrated analysis of p53-associated genes and TIC in predicting prognosis and aiding clinical decision-making in MM patients. This finding underscores the significance of comprehending the intricate interplay between genetic abnormalities and immune dysfunction in MM. Further research into this area may lead to the development of more effective treatment strategies.

Spatial and temporal change determined co-occurrence networks stability and community assembly processes of epipelagic seawater microbial community in the Nordic Sea.

The Nordic Sea has a vital impact on the global climate change, occupies a significant status in the physical oceanography research, on account of its intersection of complex ocean currents. To explore the influence of seasonal and spatial heterogeneity in its epipelagic seawater on the microbial community structure, a total of 54 seawater samples from 18 stations and 3 water layers (0 m, 50 m, 100 m) were collected in the summer of 2017 and the autumn of 2018 from the Norwegian Sea, the Greenland Sea and the vicinity of Jan Mayen Island in the Nordic Sea. Alpha- and Beta- diversity analysis showed that significant differences were found between characteristic bacterial groups in detached or mixed currents of corresponding seasons, as endemic OTUs with seasonal and ocean current characteristics which revealed the existence of spatiotemporal patterns of microbial communities in the Nordic Sea. Moreover, co-occurrence networks were conducted to show different degree of complexity and stability of microbial community response to spatiotemporal dynamic changes. Furthermore, the flow and collision between ocean currents do have an impact on the community assembly processes by affecting the migration and dispersal of microbial communities. This study reflects the response of microbial communities to the spatiotemporal dynamics and reveals the microbial community assembly mechanisms under complex hydrological condition represented in the Nordic Sea.