We analyzed fungal communities in kidney tumors from 1,044 patients across four international studies. Patients with abundant tumor fungi had worse survival outcomes and reduced response to immunotherapy. These fungi may suppress fat breakdown processes and weaken immune T cells that fight cancer. We developed predictive tools using fungal signatures that accurately forecast treatment success in kidney and other cancers. One fungal species, Aspergillus tanneri, was particularly linked to poor outcomes.

Dissolved organic matter (DOM) plays a critical role in nutrient cycling and microbial dynamics across ecosystems, but its complexity poses major analytical challenges. To address this, a team led by Prof. Jianjun Wang from the Chinese Academy of Sciences has developed iDOM, a powerful new R package for the statistical analysis and visualization of DOM data. Designed to integrate DOM composition with environmental and microbial factors, iDOM enables researchers to unravel the ecological processes driving DOM dynamics under global change. With tools for trait analysis, diversity metrics, network inference, and temperature response modeling, iDOM offers a robust and reproducible framework for DOM studies worldwide.