Relationship between tumor microbiota transcriptional activity and gene expression in breast cancer.

BACKGROUND: A few studies have reported the distribution of the microbiota in breast cancer tissues, but few reports have compared the microbiota in different subtypes of breast cancer tissue. Moreover, no study has reported on the relationship between the microbiota and gene expression in breast tumor. METHODS: Sections of formalin-fixed paraffin-embedded (FFPE) tissue were prepared from the breast tumors of 70 patients and were subjected to microarray analysis to identify gene expression profiles. The same total RNA samples were also used to analyze the microbiota activity in tumor tissues by performing 16 S rRNA sequencing and internal transcribed spacer (ITS) sequencing of reverse transcript cDNA with Illumina Miseq. Pearson's correlation coefficient was used for calculating the correlation between microbial relative activity and gene expression. RESULTS: The microbiota transcriptional activity of 70 FFPE samples mainly consisted of the phyla Bacteroidetes, Firmicutes and Proteobacteria. Prevotella_9, Bacteroides and Alloprevotella were the most active genera in ER+/HER2-, ER+/HER2 + and ER-/HER2 + tumors, while triple-negative samples exhibited a higher activity of Lactobacillus. In ER-negative samples (triple-negative and ER-/HER2+), 479 genes, including the breast carcinogenesis genes phospholipase A2, histone cluster 2, Crk-like, and cyclin D1, were significantly positive associated with the activity of Lactobacillus. CONCLUSION: This was the first study to clarify an association between the breast tumor microbiota transcriptional activity and the expression of carcinogenesis genes in ER-negative breast cancer. Changes in the microbiota of breast tissue induced by external factors might be one of the key causes of ER negative breast cancer.

Integrated proteogenomic characterization of medullary thyroid carcinoma.

Medullary thyroid carcinoma (MTC) is a rare neuroendocrine malignancy derived from parafollicular cells (C cells) of the thyroid. Here we presented a comprehensive multi-omics landscape of 102 MTCs through whole-exome sequencing, RNA sequencing, DNA methylation array, proteomic and phosphoproteomic profiling. Integrated analyses identified BRAF and NF1 as novel driver genes in addition to the well-characterized RET and RAS proto-oncogenes. Proteome-based stratification of MTCs revealed three molecularly heterogeneous subtypes named as: (1) Metabolic, (2) Basal and (3) Mesenchymal, which are distinct in genetic drivers, epigenetic modification profiles, clinicopathologic factors and clinical outcomes. Furthermore, we explored putative therapeutic targets of each proteomic subtype, and found that two tenascin family members TNC/TNXB might serve as potential prognostic biomarkers for MTC. Collectively, our study expands the knowledge of MTC biology and therapeutic vulnerabilities, which may serve as an important resource for future investigation on this malignancy.