Abstract 3298: Distinct microbiome populations within breast cancer microenvironments
Authors: Thompson Kevin J. , Sinnwell Jason , Tang Xiaojia , Ingle James N. , Goetz Matthew P. , Kalari Krishna R. 
Published: July 2016

INTRODUCTION:

The tumor microenvironment consists of a complicated interplay between a heterogeneous mixture of tumor cells and the surrounding tissue and there is a burgeoning interest in the role of the tissue microbiota within this microenvironment. Our group has investigated the breast tumor microbiome using the unaligned (non-human) reads from 796 RNASequencing data obtained from The Cancer Genome Atlas (TCGA) repository of Breast Cancer.

METHODS:

Unmapped sequences for 720 TCGA tumor samples and 76 paired normal samples were analyzed with Kraken v0.10.5 using the RefSeq 16S and standard genomes. To minimize false discoveries Kraken results were filtered to species that have bacterial genomic and 16S read support. Cluster analysis of the T-distributed Stochastic Neighbor Embedding (tsne) was performed and consensus voting of 26 maximum scoring metrics identified 3 distinct clusters. Differential abundance analysis was performed with the edgeR package. Covariate association analysis was performed for tumor clinical characteristics, as well as sample heterogeneity characteristics.

RESULTS:

There were three microbiome clusters we identified using TCGA breast samples. The average silhouette width of the third cluster was deemed statistically insignificant (0.071), suggesting further stratification of this cluster is necessary. The remaining two TCGA clusters (467) shared an average silhouette width of 0.39, using Bray's dissimilarity index. Differential abundance analysis of the two clusters after Bonferroni correction identified 450 significant species. The biomes were represented by 63 triple negative, 93 HER2+, 258 Luminal, and 50 tumor adjacent normals. Concordant cluster assignment was observed in 93.7 +/- 7.3% of the normal-tumor pairings, averaged across clinical subtypes. We observed clear delineation of biome populations at the order taxonomic level, which was not associated with the clinical subtype or the tumor/tumor adjacent pairings. We found enrichment of Burkholderiales in the first biome and enrichment of Bacillales and Lactobacillales within the second biome. The second biome appears to be deplete of representatives from the Asian population (p value 0.005) and survival associations were observed to be significantly reduced for HER2 patients associated with Biome 1 (p value 0.025). Geneset enrichment analysis of the expression signatures indicated drug metabolism and chemical carcinogenesis pathways to be associated with biome 2.

CONCLUSIONS:

In our study, we observed two significantly different microbiomes among TCGA breast cancer samples that were not associated with the clinical subtypes. Current efforts include validating these biomes, using 16S sequencing on matching fresh frozen paraffin embedded samples. Additionally, we are evaluating the influence of the biomes in independent adjuvant and neo-adjuvant studies with next generation sequencing data.

Citation Format: Kevin J. Thompson, Jason Sinnwell, Xiaojia Tang, James N. Ingle, Matthew P. Goetz, Krishna R. Kalari. Distinct microbiome populations within breast cancer microenvironments. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3298.