Demography-dependent variability in the human tumor mycobiome

Recent studies have shown that the tumor mycobiome may have prognostic and diagnostic significance in cancer patients. We aimed to gain a better understanding of how patient characteristics (age, sex, body mass index [BMI], and race) influence the composition of the tumor mycobiome, using the data of these studies. We first tested the data in view of recent critiques of tumor microbiome data processing procedures and concluded that the batch correction and transformation used on it may produce false signals. Instead, we explored 14 combinations of data transformation and batch correction methods on data of 224 fungal species across 13 cancer types. Propensity scores were utilized to adjust for potential confounders such as histological type and tumor stage. To minimize false outcomes, we identified as positive results only those fungi species that showed significant difference in abundance across a demographic factor within a particular cancer type, using data normalized according to all 14 combinations. We observed significant differences in 24 fungal species abundance within tumors for certain demographic characteristics. A total of 20 of these differences were among races in specific cancers. The findings indicate that there are intricate interactions between the mycobiome, cancer type, and patient demographics. Our study highlights the need to account for race in order to understand the role of the mycobiome in cancer development and treatment response. The study also underscores the importance of data processing techniques.

This study analyzes the demographic-dependent variability of the intratumor mycobiome, providing a novel understanding of fungal abundance across different cancer types and patient demographics. By analyzing over 5,000 tumor samples from The Cancer Genome Atlas, the research identified 24 fungal species with significant abundance variations linked to demographic factors such as race, age, sex, and body mass index. These findings underscore the complexity of the tumor microenvironment and the importance of accounting for demographic diversity in cancer research. The study emphasizes the necessity of using robust data normalization and batch correction techniques to avoid spurious associations in order to ensure the reliability of mycobiome analysis. This work highlights the mycobiome as a new frontier in precision oncology and paves the way for future personalized cancer diagnostics and treatments that account for the influence of demographic factors on tumor biology.