Background: Recent studies have shown that tumor mycobiome may have prognostic and diagnostic significance in cancer patients. We aimed to gain a better understanding of how patient characteristics (age, sex, BMI, and race) influence the composition of the tumor mycobiome, using the data of that study.

Results: 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. 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.

Conclusions: 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.