BACKGROUND: A diverse and abundant gut microbiome can improve cancer patients' treatment response; however, the effect of pelvic chemoradiotherapy (CRT) on gut diversity and composition is unclear. The purpose of this prospective study was to identify changes in the diversity and composition of the gut microbiome during and after pelvic CRT. MATERIALS AND METHODS: Rectal swabs from 58 women with cervical, vaginal, or vulvar cancer from two institutions were prospectively analyzed before CRT (baseline), during CRT (weeks 1, 3, and 5), and at first follow-up (week 12) using 16Sv4 rRNA gene sequencing of the V4 hypervariable region of the bacterial 16S rRNA marker gene. 42 of these patients received antibiotics during the study period. Observed operational taxonomic units (OTUs; representative of richness) and Shannon, Simpson, Inverse Simpson, and Fisher diversity indices were used to characterize alpha (within-sample) diversity. Changes over time were assessed using a paired t-test, repeated measures ANOVA, and linear mixed modeling. Compositional changes in specific bacteria over time were evaluated using linear discriminant analysis effect size. RESULTS: Gut microbiome richness and diversity levels continually decreased throughout CRT (mean Shannon diversity index, 2.52 vs. 2.91; all P <0.01), but were at or near baseline levels in 60% of patients by week 12. Patients with higher gut diversity at baseline had the steepest decline in gut microbiome diversity. Gut microbiome composition was significantly altered during CRT, with increases in Proteobacteria and decreases in Clostridiales, but adapted after CRT, with increases in Bacteroides species. CONCLUSION: After CRT, the diversity of the gut microbiomes in this population tended to return to baseline levels by the 12 week follow-up period, but structure and composition remained significantly altered. These changes should be considered when designing studies to analyze the gut microbiome in patients who receive pelvic CRT for gynecologic cancers.
BACKGROUND: A diverse and abundant gut microbiome can improve cancerpatients' treatment response; however, the effect of pelvic chemoradiotherapy (CRT) on gut diversity and composition is unclear. The purpose of this prospective study was to identify changes in the diversity and composition of the gut microbiome during and after pelvic CRT. MATERIALS AND METHODS: Rectal swabs from 58 women with cervical, vaginal, or vulvar cancer from two institutions were prospectively analyzed before CRT (baseline), during CRT (weeks 1, 3, and 5), and at first follow-up (week 12) using 16Sv4 rRNA gene sequencing of the V4 hypervariable region of the bacterial 16S rRNA marker gene. 42 of these patients received antibiotics during the study period. Observed operational taxonomic units (OTUs; representative of richness) and Shannon, Simpson, Inverse Simpson, and Fisher diversity indices were used to characterize alpha (within-sample) diversity. Changes over time were assessed using a paired t-test, repeated measures ANOVA, and linear mixed modeling. Compositional changes in specific bacteria over time were evaluated using linear discriminant analysis effect size. RESULTS:Gut microbiome richness and diversity levels continually decreased throughout CRT (mean Shannon diversity index, 2.52 vs. 2.91; all P <0.01), but were at or near baseline levels in 60% of patients by week 12. Patients with higher gut diversity at baseline had the steepest decline in gut microbiome diversity. Gut microbiome composition was significantly altered during CRT, with increases in Proteobacteria and decreases in Clostridiales, but adapted after CRT, with increases in Bacteroides species. CONCLUSION: After CRT, the diversity of the gut microbiomes in this population tended to return to baseline levels by the 12 week follow-up period, but structure and composition remained significantly altered. These changes should be considered when designing studies to analyze the gut microbiome in patients who receive pelvic CRT for gynecologic cancers.
Authors: Anamaria R Yeung; Stephanie L Pugh; Ann H Klopp; Karen M Gil; Lari Wenzel; Shannon N Westin; David K Gaffney; William Small; Spencer Thompson; Desiree E Doncals; Guilherme H C Cantuaria; Brian P Yaremko; Amy Chang; Vijayananda Kundapur; Dasarahally S Mohan; Michael L Haas; Yong Bae Kim; Catherine L Ferguson; Snehal Deshmukh; Deborah W Bruner; Lisa A Kachnic Journal: J Clin Oncol Date: 2020-02-19 Impact factor: 44.544
Authors: Yinghong Wang; Diana H Wiesnoski; Beth A Helmink; Vancheswaran Gopalakrishnan; Kati Choi; Hebert L DuPont; Zhi-Dong Jiang; Hamzah Abu-Sbeih; Christopher A Sanchez; Chia-Chi Chang; Edwin R Parra; Alejandro Francisco-Cruz; Gottumukkala S Raju; John R Stroehlein; Matthew T Campbell; Jianjun Gao; Sumit K Subudhi; Dipen M Maru; Jorge M Blando; Alexander J Lazar; James P Allison; Padmanee Sharma; Michael T Tetzlaff; Jennifer A Wargo; Robert R Jenq Journal: Nat Med Date: 2018-11-12 Impact factor: 53.440
Authors: N Chaput; P Lepage; C Coutzac; E Soularue; K Le Roux; C Monot; L Boselli; E Routier; L Cassard; M Collins; T Vaysse; L Marthey; A Eggermont; V Asvatourian; E Lanoy; C Mateus; C Robert; F Carbonnel Journal: Ann Oncol Date: 2017-06-01 Impact factor: 32.976
Authors: Alexa Weingarden; Antonio González; Yoshiki Vázquez-Baeza; Sophie Weiss; Gregory Humphry; Donna Berg-Lyons; Dan Knights; Tatsuya Unno; Aleh Bobr; Johnthomas Kang; Alexander Khoruts; Rob Knight; Michael J Sadowsky Journal: Microbiome Date: 2015-03-30 Impact factor: 14.650
Authors: Yang Song; Shashank Garg; Mohit Girotra; Cynthia Maddox; Erik C von Rosenvinge; Anand Dutta; Sudhir Dutta; W Florian Fricke Journal: PLoS One Date: 2013-11-26 Impact factor: 3.240