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...
Saved in:
Published in | Journal of clinical oncology Vol. 40; no. 16_suppl; p. 10541 |
---|---|
Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
Published |
American Society of Clinical Oncology
01.06.2022
|
Online Access | Get full text |
Cover
Loading…
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. |
Author_xml | – sequence: 1 givenname: Christina Ann surname: Nowicki fullname: Nowicki, Christina Ann – sequence: 2 givenname: Lucille surname: Ray fullname: Ray, Lucille – sequence: 3 givenname: Phillip surname: Engen fullname: Engen, Phillip – sequence: 4 givenname: Andrea surname: Madrigrano fullname: Madrigrano, Andrea – sequence: 5 givenname: Thomas R. surname: Witt fullname: Witt, Thomas R. – sequence: 6 givenname: Thomas E. surname: Lad fullname: Lad, Thomas E. – sequence: 7 givenname: Melody A. surname: Cobleigh fullname: Cobleigh, Melody A. – sequence: 8 givenname: Ece surname: Mutlu fullname: Mutlu, Ece |
BookMark | eNqNkN1KwzAYhoNMcJveQ_C8NUmTpnggyPCXyU4UPAtJlq6daVOSlOndm7pdgEcfvH98PAsw611vALjGKMcEoZvX1SYniJCcJqEUYRwGm2PEKD4Dc8wIzzhnbAbmiBckw1XxeQEWIewRwrQq2ByYt9HG1nWthnIYvJO6gdFB8y27tm_7HdyNESbXO5VSBgbZDXbSOxMbtw2w7aHyRoYItey18VD2W6hdH72zMIxqb3QMl-C8ljaYq9Ndgo_Hh_fVc7bePL2s7teZxqjEWYEo4zU1RiKKKllpJSlLFlFbzClnSumyprWmHDNW1YQYWSs6dXRZ4YoXS3B73E3_huBNLQbfdtL_CIzEBEwkYGICJmgSTsDEH7BUvjuWD85G48OXHQ_Gi8ZIG5v_DPwC5al5xg |
ContentType | Journal Article |
Copyright | 2022 by American Society of Clinical Oncology |
Copyright_xml | – notice: 2022 by American Society of Clinical Oncology |
DBID | AAYXX CITATION |
DOI | 10.1200/JCO.2022.40.16_suppl.10541 |
DatabaseName | CrossRef |
DatabaseTitle | CrossRef |
DatabaseTitleList | CrossRef |
DeliveryMethod | fulltext_linktorsrc |
Discipline | Medicine Pharmacy, Therapeutics, & Pharmacology |
EISSN | 1527-7755 |
EndPage | 10541 |
ExternalDocumentID | 10_1200_JCO_2022_40_16_suppl_10541 377067 |
Genre | meeting-report |
GrantInformation_xml | – fundername: U.S. National Institutes of Health. |
GroupedDBID | --- .55 0R~ 18M 2WC 34G 39C 4.4 53G 5GY 5RE 8F7 AAQQT AARDX AAWTL AAYEP ABJNI ABOCM ACGFO ACGFS ACGUR ADBBV AEGXH AENEX AIAGR ALMA_UNASSIGNED_HOLDINGS BAWUL BYPQX C45 CS3 DIK EBS EJD F5P F9R FBNNL FD8 GX1 HZ~ IH2 IPNFZ K-O KQ8 L7B LSO MJL N9A O9- OK1 OVD OWW P2P QTD R1G RHI RIG RLZ RUC SJN TEORI TR2 TWZ UDS VVN WH7 X7M YFH YQY AAYXX ABBLC CITATION |
ID | FETCH-LOGICAL-c1061-30457f4eea0408a8cba45c102bd17475bbc6f4fc471558f22eafb4457fc681873 |
ISSN | 0732-183X |
IngestDate | Tue Jul 01 00:40:22 EDT 2025 Wed Apr 16 02:28:55 EDT 2025 |
IsPeerReviewed | true |
IsScholarly | true |
Issue | 16_suppl |
Language | English |
LinkModel | OpenURL |
MergedId | FETCHMERGED-LOGICAL-c1061-30457f4eea0408a8cba45c102bd17475bbc6f4fc471558f22eafb4457fc681873 |
Notes | Abstract Disclosures |
PageCount | 1 |
ParticipantIDs | crossref_primary_10_1200_JCO_2022_40_16_suppl_10541 wolterskluwer_health_10_1200_JCO_2022_40_16_suppl_10541 |
ProviderPackageCode | CITATION AAYXX |
PublicationCentury | 2000 |
PublicationDate | 20220601 2022-06-01 |
PublicationDateYYYYMMDD | 2022-06-01 |
PublicationDate_xml | – month: 6 year: 2022 text: 20220601 day: 1 |
PublicationDecade | 2020 |
PublicationTitle | Journal of clinical oncology |
PublicationTitleAbbrev | ASCO MEETING ABSTRACTS |
PublicationYear | 2022 |
Publisher | American Society of Clinical Oncology |
Publisher_xml | – name: American Society of Clinical Oncology |
SSID | ssj0014835 |
Score | 2.392177 |
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... 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... |
SourceID | crossref wolterskluwer |
SourceType | Index Database Publisher |
StartPage | 10541 |
Title | Multiomic approach to examining gut microbiome sampling methods in breast cancer and control subjects |
URI | https://ovidsp.ovid.com/ovidweb.cgi?T=JS&NEWS=n&CSC=Y&PAGE=fulltext&D=ovft&DO=10.1200/JCO.2022.40.16_suppl.10541 |
Volume | 40 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3db9MwELfKkBASQjBAbHzID2gvXQpznKR9nArTxljbh07qW2Q7zhRBk6lJBOOv5y52nFQwaewlah05cnq_-j58vztCPmgwQtVEcu_IT8BBSbXvSRYmXuSLBDRimhwlyB2-mIWnl_zrKlgNBv0KwXUlR-r3P3kl95EqjIFckSX7H5J1D4UB-AzyhStIGK53knHDnkVasSsNjqak_iXWTduH4VVdDdeZKbW01sNSYPo4jJu20U0mrMSk9Apzv5TeWJKbSV4va4kxmvIW89VRKotcbYXmZwV2Z8-6ygVZLobHecc4EyZIXiukITqLHjlebYTnh0msNpHyZJNdgUItXPql6EcqwMl1GVU9cgDuWjYfFfNN2rXO-2s121_kMw82nFV_rzalnVpMhnGJrU97-y9Yi6aOllXm7vtfmoKZJtjT-QiXOuIwZB836j2kX557No8Xn0_ib2ez8-2bxhqIIlD8D8hDBv5K49ufnbvjLD42nV7bV7LVb2ENH29fwZal9ORngdkT5feGPNEzgZbPyFMrfHpsgPicDHS-Sx5d2OyMXXKwMHXQbw7psqP1lYf0gC66Cuk3L4h2wKUtcGlVUAdcCsClHXBpC1xqgUuznBrgUgNcCsClFri0Be5LcnnyZTk99Wy_D09hYMLDQ_so5VoL0CxjMVZS8ABuMZmA3xwFUqow5akCeyoIxiljWqSS4xwVgt0Z-a_ITl7k-jWhIlRMyZBLf5zyQCQTEYFhHHD9KQnYRPh7xG9_2_jalHWJ0R1meLY7nccokZjDgJVI3Ehkj0RbYogNV_kOM_fvPfMNedz9l96SnWpT63dgB1fyfYOxPyYuuYI |
linkProvider | Flying Publisher |
openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Multiomic+approach+to+examining+gut+microbiome+sampling+methods+in+breast+cancer+and+control+subjects&rft.jtitle=Journal+of+clinical+oncology&rft.au=Nowicki%2C+Christina+Ann&rft.au=Ray%2C+Lucille&rft.au=Engen%2C+Phillip&rft.au=Madrigrano%2C+Andrea&rft.date=2022-06-01&rft.pub=American+Society+of+Clinical+Oncology&rft.issn=0732-183X&rft.volume=40&rft.issue=16_suppl&rft.spage=10541&rft.epage=10541&rft_id=info:doi/10.1200%2FJCO.2022.40.16_suppl.10541&rft.externalDBID=NO_PDF_LINK&rft.externalDocID=377067 |
thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0732-183X&client=summon |
thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0732-183X&client=summon |
thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0732-183X&client=summon |