Retrospective Cohort Study
Copyright ©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Apr 14, 2021; 27(14): 1465-1482
Published online Apr 14, 2021. doi: 10.3748/wjg.v27.i14.1465
Impact of preoperative antibiotics and other variables on integrated microbiome-host transcriptomic data generated from colorectal cancer resections
Sarah A Malik, Chencan Zhu, Jinyu Li, Joseph F LaComb, Paula I Denoya, Igor Kravets, Joshua D Miller, Jie Yang, Melissa Kramer, W Richard McCombie, Charles E Robertson, Daniel N Frank, Ellen Li
Sarah A Malik, Joseph F LaComb, Igor Kravets, Joshua D Miller, Ellen Li, Department of Medicine, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY 11794, United States
Chencan Zhu, Jie Yang, Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY 11794, United States
Jinyu Li, Jie Yang, Stony Brook Cancer Center Biostatistics and Bioinformatics Shared Resource, Stony Brook University, Stony Brook, NY 11794, United States
Jinyu Li, Department of Pathology, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY 11794, United States
Paula I Denoya, Department of Surgery, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY 11794, United States
Jie Yang, Department of Family, Population and Preventive Medicine, Stony Brook University, Stony Brook, NY 11794, United States
Melissa Kramer, W Richard McCombie, Cold Spring Harbor Laboratory Cancer Center Sequencing Technologies and Analysis Shared Resource, Cold Spring Harbor, NY 11724, United States
Charles E Robertson, Daniel N Frank, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, United States
Author contributions: Li E, McCombie WR, Denoya PI, Frank DN, Kravets I and Miller JD contributed study concept and design; Malik SA, LaComb JF, Li E, Kramer M contributed data collection; Zhu C, Yang J, Li J, Robertson CE and Frank DN contributed statistical analysis; Malik SA, Li E and Frank DN contributed drafting of manuscript; Yang J, LaComb JF, Denoya PI, Kravets I, Miller JD, Kramer M, McCombie WR and Robertson CE contributed critical review for important intellectual content; all authors approved the final version of the manuscript.
Supported by National Cancer Institute, No. P20 CA192994; National Cancer Institute, No. P20 CA192996; and Simons Foundation, No. 415604.
Institutional review board statement: This study was approved by the Stony Brook University Institutional Review Board (approval No. 163184).
Informed consent statement: All study participants, or their legal guardian, provided informed written consent prior to study enrollment.
Conflict-of-interest statement: All authors declare no conflicts-of-interest related to this article.
Data sharing statement: All de-multiplexed, paired-end 16S rRNA gene sequence files and RNA-sequence data along with associated metadata were deposited into the Gene Expression Omnibus, which is a public repository that archives and freely distributes comprehensive sets of microarray, next-generation sequencing, and other forms of high-throughput functional genomic data submitted by the scientific community data base under project accession number GSE165255. All the tissues analyzed were collected from patients that gave informed consent for sharing results of the analysis of their anonymized tissues on public databases, where the risk of identification is very low. The statistical code used in this study is available from the corresponding author at
STROBE statement: The authors have read the STROBE Statement-checklist of items, and the manuscript was prepared and revised according to the STROBE Statement-checklist of items.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See:
Corresponding author: Ellen Li, MD, PhD, Emeritus Professor, Department of Medicine, Renaissance School of Medicine, Stony Brook University, 101 Nicolls Road, Stony Brook, NY 11794, United States.
Received: January 21, 2021
Peer-review started: January 21, 2021
First decision: February 9, 2021
Revised: March 3, 2021
Accepted: March 24, 2021
Article in press: March 24, 2021
Published online: April 14, 2021

Integrative multi-omic approaches have been increasingly applied to discovery and functional studies of complex human diseases. Short-term preoperative antibiotics have been adopted to reduce site infections in colorectal cancer (CRC) resections. We hypothesize that the antibiotics will impact analysis of multi-omic datasets generated from resection samples to investigate biological CRC risk factors.


To assess the impact of preoperative antibiotics and other variables on integrated microbiome and human transcriptomic data generated from archived CRC resection samples.


Genomic DNA (gDNA) and RNA were extracted from prospectively collected 51 pairs of frozen sporadic CRC tumor and adjacent non-tumor mucosal samples from 50 CRC patients archived at a single medical center from 2010-2020. The 16S rRNA gene sequencing (V3V4 region, paired end, 300 bp) and confirmatory quantitative polymerase chain reaction (qPCR) assays were conducted on gDNA. RNA sequencing (IPE, 125 bp) was performed on parallel tumor and non-tumor RNA samples with RNA Integrity Numbers scores ≥ 6.


PERMANOVA detected significant effects of tumor vs nontumor histology (P = 0.002) and antibiotics (P = 0.001) on microbial β-diversity, but CRC tumor location (left vs right), diabetes mellitus vs not diabetic and Black/African Ancestry (AA) vs not Black/AA, did not reach significance. Linear mixed models detected significant tumor vs nontumor histology*antibiotics interaction terms for 14 genus level taxa. QPCR confirmed increased Fusobacterium abundance in tumor vs nontumor groups, and detected significantly reduced bacterial load in the (+)antibiotics group. Principal coordinate analysis of the transcriptomic data showed a clear separation between tumor and nontumor samples. Differentially expressed genes obtained from separate analyses of tumor and nontumor samples, are presented for the antibiotics, CRC location, diabetes and Black/AA race groups.


Recent adoption of additional preoperative antibiotics as standard of care, has a measurable impact on -omics analysis of resected specimens. This study still confirmed increased Fusobacterium nucleatum in tumor.

Keywords: Colorectal cancer, Antibiotics, African Continental Ancestry Group, Diabetes mellitus, 16S rRNA gene, RNA-sequencing

Core Tip: This pilot study explored the effect of five variables [tumor histology, preoperative antibiotics, laterality of colorectal cancer (CRC) location, diabetes mellitus, Black/African Ancestry (AA) race] on analysis of microbiome and host transcriptome among archived frozen CRC resection samples. The introduction of short-term preoperative antibiotics as standard of care has a measurable effect on the analysis. Despite the small sample size and variable exposure to preoperative antibiotics, it was still possible to use the data for discovery studies. Fusobacterium abundance was increased in tumor vs nontumor regions. Expression of VBP1 was decreased in expression in both Black/AA tumor and nontumor samples.