RESUMO
Aim: The goal of this study is to compare microbiome composition in three different sample types in women, namely stool brought from home vs. solid stool samples obtained at the time of an unprepped sigmoidoscopy vs. biopsies of the colonic mucosa at the time of an unprepped sigmoidoscopy, using alpha- and beta-diversity metrics following bacterial 16S rRNA sequencing. The findings may have relevance to health and disease states in which bacterial metabolism has a significant impact on molecules/metabolites that are recirculated between the gut lumen and mucosa and systemic circulation, such as estrogens (as in breast cancer) or bile acids. Methods: Concomitant at-home-collected stool, endoscopically-collected stool, and colonic biopsy samples were collected from 48 subjects (24 breast cancer, 24 control.) After 16S rRNA sequencing, an amplicon sequence variant (ASV) based approach was used to analyze the data. Alpha diversity metrics (Chao1, Pielou's Evenness, Faith PD, Shannon, and Simpson) and beta diversity metrics (Bray-Curtis, Weighted and Unweighted Unifrac) were calculated. LEfSe was used to analyze differences in the abundance of various taxa between sample types. Results: Alpha and beta diversity metrics were significantly different between the three sample types. Biopsy samples were different than stool samples in all metrics. The highest variation in microbiome diversity was noted in the colonic biopsy samples. At-home and endoscopically-collected stool showed more similarities in count-based and weighted beta diversity metrics. There were significant differences in rare taxa and phylogenetically-diverse taxa between the two types of stool samples. Generally, there were higher levels of Proteobacteria in biopsy samples, with significantly more Actinobacteria and Firmicutes in stool (all p < 0.001, q-value < 0.05). Overall, there was a significantly higher relative abundance of Lachnospiraceae and Ruminococcaceae in stool samples (at-home collected and endoscopically-collected) and higher abundances of Tisserellaceae in biopsy samples (all p < 0.001, q-value < 0.05). Conclusion: Our data shows that different sampling methods can impact results when looking at the composition of the gut microbiome using ASV-based approaches.
RESUMO
Fibroblasts are a critical component of tumor microenvironments and associate with cancer cells physically and biochemically during different stages of the disease. Existing cell culture models to study interactions between fibroblasts and cancer cells lack native tumor architecture or scalability. We developed a scalable organotypic model by robotically encapsulating a triple negative breast cancer (TNBC) cell spheroid within a natural extracellular matrix containing dispersed fibroblasts. We utilized an established CXCL12 - CXCR4 chemokine-receptor signaling in breast tumors to validate our model. Using imaging techniques and molecular analyses, we demonstrated that CXCL12-secreting fibroblasts have elevated activity of RhoA/ROCK/myosin light chain-2 pathway and rapidly and significantly contract collagen matrices. Signaling between TNBC cells and CXCL12-producing fibroblasts promoted matrix invasion of cancer cells by activating oncogenic mitogen-activated protein kinase signaling, whereas normal fibroblasts significantly diminished TNBC cell invasiveness. We demonstrated that disrupting CXCL12 - CXCR4 signaling using a molecular inhibitor significantly inhibited invasiveness of cancer cells, suggesting blocking of tumor-stromal interactions as a therapeutic strategy especially for cancers such as TNBC that lack targeted therapies. Our organotypic tumor model mimics native solid tumors, enables modular addition of different stromal cells and extracellular matrix proteins, and allows high throughput compound screening against tumor-stromal interactions to identify novel therapeutics.