Deciphering the impact of intra-tumoral bacterial infiltration on multi-omics profiles in low-grade gliomas.

BACKGROUND

Low-grade gliomas (LGGs) exhibit diverse bacterial infiltrations. This study delves into the intricate relationship between microbial infiltration in glioma samples and tumor multi-omics characteristics, aiming to elucidate its impact on tumor behavior and patient prognosis.

METHODS

We included low-grade glioma (LGG) samples from The Cancer Genome Atlas (TCGA) as analysis cohort and used LGG tumor samples from patients who underwent surgical treatment as validation cohort. For the TCGA samples, utilizing advanced machine learning algorithms, this study identified distinct patterns of bacterial infiltration within the LGG population and constructed a prognostically relevant intra-tumoral bacteria risk model (PRIBR Index). For the clinically derived samples, we performed 16S rRNA sequencing, bulk RNA sequencing, and proteomics analysis. Subsequently, the samples were stratified into high-risk and low-risk groups. We then explored clinical information, tumor microenvironment, methylation status, and sensitivity to targeted therapies between these groups to elucidate the impact of varying bacterial infiltration levels on glioma behavior.

RESULTS

A total of 32 common differentially expressed genes were identified between the TCGA-LGG samples and the clinical samples when comparing the high-risk and low-risk groups. The high-risk group demonstrated elevated bacterial infiltration levels, which were associated with increased infiltration of inflammatory factors. Patients in this group exhibited shorter survival periods, potentially attributable to the heightened expression of negative immune checkpoints. Predictive analysis for targeted drugs indicated that certain agents might achieve a lower half maximal inhibitory concentration (IC50) in the low-risk group compared to the high-risk group. Furthermore, while no significant differences were observed in tumor mutation burden or copy number variation between the two groups, the high-risk group showed increased methylation levels across multiple pathways.

CONCLUSION

These findings offer new insights into the biological characteristics of gliomas and provide novel avenues for exploring new therapeutic approaches, bringing fresh perspectives to the field of intra-tumoral bacteria.