Multiomic approach to examining gut microbiome sampling methods in breast cancer and control subjects

10541Background: It is well known that estrogen exposure is a major risk factor for breast cancer (BC). Estrogen levels can be affected by the gut microbiome through enterohepatic circulation. No studies regarding gut microbiome changes in BC have examined the colonic mucosal microbiome; and there i...

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Published inJournal of clinical oncology Vol. 40; no. 16_suppl; p. 10541
Main Authors Nowicki, Christina Ann, Ray, Lucille, Engen, Phillip, Madrigrano, Andrea, Witt, Thomas R., Lad, Thomas E., Cobleigh, Melody A., Mutlu, Ece
Format Journal Article
LanguageEnglish
Published American Society of Clinical Oncology 01.06.2022
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Abstract 10541Background: It is well known that estrogen exposure is a major risk factor for breast cancer (BC). Estrogen levels can be affected by the gut microbiome through enterohepatic circulation. No studies regarding gut microbiome changes in BC have examined the colonic mucosal microbiome; and there is no data on which types of gut microbiome studies would be most relevant to the study of the microbiome in BC. Methods: We examined differences in the gut microbiome composition in BC and control subjects using the following sample types: Home-collected stool, endoscopically collected stool, and colonic biopsy samples (for all groups, n=48 total, n=24 BC, n=24 controls). Here, we used both operational taxonomic unit (OTU) and amplicon sequence variant (ASV) based approaches in QIIME2 for 16S rDNA sequencing analysis. 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 different between the three sample types when using both OTU or ASV-based analysis, however there were some minor differences between analysis types in these samples. Comparing the 3 sample types, Actinobacteria and Firmicutes (Log10 LDA score >4) were the predominant phyla in home stool samples, while Bacteroidetes and Proteobacteria (Log10 LDA score >4) were higher in abundance in the colonic biopsy samples. Conclusions: Our data shows that alpha and beta diversity metrics differ between sampling methods (home-collected stool, endoscopically collected stool, and colonic biopsies) when looking at the composition of the gut microbiome in BC. Results remained the same regardless of ASV or OTU-based analysis. Alpha and beta diversity metric p-values for home-collected stool, endoscopically-collected stool, and colonic biopsies using ASV and OTU-clustering approaches.Beta DiversityASV (DADA2)OTU (De novo 99%)OTU (De novo 97%)OTU (Open Reference 99%)OTU (Open Reference 97%)OTU (Normalized Open Reference 97%)Bray-Curtis1.00e-51.00e-51.00e-51.00e-51.00e-51.00e-5Unweighted Unifrac1.00e-51.00e-51.00e-51.00e-51.00e-51.00e-5Weighted Unifrac1.00e-51.00e-51.00e-51.00e-51.00e-51.00e-5Alpha DiversityChao11.32e-142.7e-184.17e-195.24e-181.82e-183.36e-9Evenness1.08e-40.0165810.3800710.0008214.98e-53.23e-15Faith PD1.61e-190.0124640.0004360.0001890.0001651.66e-18Shannon6.75e-50.0001590.0033272.35e-53.85e-68.45e-19Simpson0.0015870.0054270.0153690.0008430.0002002.57e-7
AbstractList 10541Background: It is well known that estrogen exposure is a major risk factor for breast cancer (BC). Estrogen levels can be affected by the gut microbiome through enterohepatic circulation. No studies regarding gut microbiome changes in BC have examined the colonic mucosal microbiome; and there is no data on which types of gut microbiome studies would be most relevant to the study of the microbiome in BC. Methods: We examined differences in the gut microbiome composition in BC and control subjects using the following sample types: Home-collected stool, endoscopically collected stool, and colonic biopsy samples (for all groups, n=48 total, n=24 BC, n=24 controls). Here, we used both operational taxonomic unit (OTU) and amplicon sequence variant (ASV) based approaches in QIIME2 for 16S rDNA sequencing analysis. 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 different between the three sample types when using both OTU or ASV-based analysis, however there were some minor differences between analysis types in these samples. Comparing the 3 sample types, Actinobacteria and Firmicutes (Log10 LDA score >4) were the predominant phyla in home stool samples, while Bacteroidetes and Proteobacteria (Log10 LDA score >4) were higher in abundance in the colonic biopsy samples. Conclusions: Our data shows that alpha and beta diversity metrics differ between sampling methods (home-collected stool, endoscopically collected stool, and colonic biopsies) when looking at the composition of the gut microbiome in BC. Results remained the same regardless of ASV or OTU-based analysis. Alpha and beta diversity metric p-values for home-collected stool, endoscopically-collected stool, and colonic biopsies using ASV and OTU-clustering approaches.Beta DiversityASV (DADA2)OTU (De novo 99%)OTU (De novo 97%)OTU (Open Reference 99%)OTU (Open Reference 97%)OTU (Normalized Open Reference 97%)Bray-Curtis1.00e-51.00e-51.00e-51.00e-51.00e-51.00e-5Unweighted Unifrac1.00e-51.00e-51.00e-51.00e-51.00e-51.00e-5Weighted Unifrac1.00e-51.00e-51.00e-51.00e-51.00e-51.00e-5Alpha DiversityChao11.32e-142.7e-184.17e-195.24e-181.82e-183.36e-9Evenness1.08e-40.0165810.3800710.0008214.98e-53.23e-15Faith PD1.61e-190.0124640.0004360.0001890.0001651.66e-18Shannon6.75e-50.0001590.0033272.35e-53.85e-68.45e-19Simpson0.0015870.0054270.0153690.0008430.0002002.57e-7
10541 Background: It is well known that estrogen exposure is a major risk factor for breast cancer (BC). Estrogen levels can be affected by the gut microbiome through enterohepatic circulation. No studies regarding gut microbiome changes in BC have examined the colonic mucosal microbiome; and there is no data on which types of gut microbiome studies would be most relevant to the study of the microbiome in BC. Methods: We examined differences in the gut microbiome composition in BC and control subjects using the following sample types: Home-collected stool, endoscopically collected stool, and colonic biopsy samples (for all groups, n=48 total, n=24 BC, n=24 controls). Here, we used both operational taxonomic unit (OTU) and amplicon sequence variant (ASV) based approaches in QIIME2 for 16S rDNA sequencing analysis. 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 different between the three sample types when using both OTU or ASV-based analysis, however there were some minor differences between analysis types in these samples. Comparing the 3 sample types, Actinobacteria and Firmicutes (Log10 LDA score >4) were the predominant phyla in home stool samples, while Bacteroidetes and Proteobacteria (Log10 LDA score >4) were higher in abundance in the colonic biopsy samples. Conclusions: Our data shows that alpha and beta diversity metrics differ between sampling methods (home-collected stool, endoscopically collected stool, and colonic biopsies) when looking at the composition of the gut microbiome in BC. Results remained the same regardless of ASV or OTU-based analysis. [Table: see text]
Author Witt, Thomas R.
Madrigrano, Andrea
Nowicki, Christina Ann
Mutlu, Ece
Engen, Phillip
Ray, Lucille
Lad, Thomas E.
Cobleigh, Melody A.
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Snippet 10541Background: It is well known that estrogen exposure is a major risk factor for breast cancer (BC). Estrogen levels can be affected by the gut microbiome...
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Title Multiomic approach to examining gut microbiome sampling methods in breast cancer and control subjects
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