The Role of the Microbiota in Esophageal Cancer

Abstract

Simple Summary
Esophageal cancer has very high mortality and morbidity rates. In this study, we reviewed the current literature on the impact of microbiota on esophageal cancer and its precursor lesions. Globally, a decrease in microbiota richness and evenness in esophageal cancer is identified, which is accompanied by an increase in the abundance of Gram-negative bacteria.

Abstract
Esophageal cancer is a major health problem, being the seventh most incidence cancer worldwide. Due to the often-late diagnosis and lack of efficient treatments, the overall 5-year survival is as low as 10%. Therefore, understanding the etiology and the mechanisms that drive the development of this type of cancer could improve the management of patients, increasing the chance of achieving a better clinical outcome. Recently, the microbiome has been studied as a putative etiological factor for esophageal cancer. Nevertheless, the number of studies tackling this issue is low, and the heterogeneity in the study design and data analysis has hindered consistent findings. In this work, we reviewed the current literature on the evaluation of the role of microbiota in the development of esophageal cancer. We analyzed the composition of the normal microbiota and the alterations found in precursor lesions, namely Barrett’s esophagus and dysplasia, as well as in esophageal cancer. Additionally, we explored how other environmental factors can modify microbiota and contribute to the development of this neoplasia. Finally, we identify critical aspects to be improved in future studies, with the aim of refining the interpretation of the relationship between the microbiome and esophageal cancer.

Full text

Citation: Moreira, C.; Figueiredo, C.;
Ferreira, R.M. The Role of the
Microbiota in Esophageal Cancer.
Cancers 2023,15, 2576. https://
doi.org/10.3390/cancers15092576
Academic Editor: B.P.L. (Bas)
Wijnhoven
Received: 13 April 2023
Revised: 28 April 2023
Accepted: 29 April 2023
Published: 30 April 2023
Copyright: © 2023 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
cancers
Review
The Role of the Microbiota in Esophageal Cancer
Clara Moreira 1,2, Ceu Figueiredo 1,2,3 and Rui Manuel Ferreira 1, 3, *
1Instituto de Investigação e Inovação em Saúde, Universidade do Porto (i3S), 4200-135 Porto, Portugal
2Department of Pathology, Faculty of Medicine of the University of Porto, 4200-319 Porto, Portugal
3Institute of Molecular Pathology and Immunology of the University of Porto (IPATIMUP),
4200-135 Porto, Portugal
*Correspondence: ruif@i3s.up.pt
Simple Summary:
Esophageal cancer has very high mortality and morbidity rates. In this study, we
reviewed the current literature on the impact of microbiota on esophageal cancer and its precursor
lesions. Globally, a decrease in microbiota richness and evenness in esophageal cancer is identified,
which is accompanied by an increase in the abundance of Gram-negative bacteria.
Abstract:
Esophageal cancer is a major health problem, being the seventh most incidence cancer
worldwide. Due to the often-late diagnosis and lack of efficient treatments, the overall 5-year
survival is as low as 10%. Therefore, understanding the etiology and the mechanisms that drive
the development of this type of cancer could improve the management of patients, increasing the
chance of achieving a better clinical outcome. Recently, the microbiome has been studied as a
putative etiological factor for esophageal cancer. Nevertheless, the number of studies tackling this
issue is low, and the heterogeneity in the study design and data analysis has hindered consistent
findings. In this work, we reviewed the current literature on the evaluation of the role of microbiota
in the development of esophageal cancer. We analyzed the composition of the normal microbiota
and the alterations found in precursor lesions, namely Barrett’s esophagus and dysplasia, as well
as in esophageal cancer. Additionally, we explored how other environmental factors can modify
microbiota and contribute to the development of this neoplasia. Finally, we identify critical aspects to
be improved in future studies, with the aim of refining the interpretation of the relationship between
the microbiome and esophageal cancer.
Keywords:
microbiota; esophageal cancer; esophageal squamous cell carcinoma; esophageal
adenocarcinoma; dysbiosis; bacteria
1. Introduction
The human microbiome comprises the whole set of microbial taxa and their genomes
that inhabit different niches in the human body, including bacteria, fungi, and viruses.
Usually, the term microbiota refers only to the collection of microorganisms themselves [
1
].
The number of bacteria colonizing the human body is frequently reported as outnumbering
the number of host cells, but updated estimates propose a ratio of 1.3 bacterial cells for every
human cell [
2
]. Although the number and abundance of bacteria are high, the diversity
of the genomic information can be even greater since each species contains thousands
of genes that contribute to a substantially more flexible and diverse metagenome than
the human genome alone [
3
]. The microbiota plays important roles in the maintenance
of human health, including metabolic activities, such as the production of vitamins and
anti-inflammatory compounds, and also contributes contributing to the maturation of the
immune system [4].
In recent years, the implementation of next-generation sequencing techniques has
enabled in-depth characterization of the gastrointestinal microbiota, circumventing the
limitations of the traditional culturing methods that only allowed the identification of
Cancers 2023,15, 2576. https://doi.org/10.3390/cancers15092576 https://www.mdpi.com/journal/cancers

Cancers 2023,15, 2576 2 of 15
cultivable species [
4
]. The study of the microbiota in a specific niche may involve the
identification and quantification of each member of the community and the estimation
of the diversity of the entire community, the latter varying from individual to individual
and between groups of individuals. The composition of the microbial communities can be
affected by diet, exercise, stress, aging, the intake of probiotics/prebiotics, antibiotics, or
other drugs, as well as by the host immune system and host genetic factors [
5
]. Importantly,
alterations in the equilibrium between the human host and the microbiota have been associ-
ated with the development of several diseases, namely cancer [
6
]. In several gastrointestinal
cancers, including the stomach and the colon, dysbiosis has been consistently associated
with cancer [
6
,
7
]. However, the mechanisms by which microbial dysbiosis can promote
cancer are far from understood. One can speculate that the microbiota has direct oncogenic
effects through the release of oncogenic toxins or secretion of oncometabolites, and/or
indirect oncogenic actions, by the promotion and maintenance of local inflammation or by
alteration of the systemic immune response.
Regarding esophageal cancer, the microbiota of the upper gastrointestinal tract has
been suggested to play a role in the etiology of this malignancy, particularly in esophageal
adenocarcinoma. Here, we review and discuss the literature that addresses the role of
microbiota in the development of esophageal cancer. For this purpose, we conducted a
search in the PubMed database for the query “esophageal cancer” AND “microbiota” in
July 2022.
2. Esophageal Cancer
Esophageal cancer occupies the sixth position on the global ranking of cancer-related
death, and it is the seventh most incident malignancy. This type of cancer was responsible
for more than 544,000 deaths worldwide in 2020 [
8
]. Esophageal cancer incidence and
mortality are unequally distributed around the world, being more incident and deadly in
Eastern Asia and Southern Africa than in Western countries, such as France, Canada, and
the USA [9].
The overall 5-year survival rate of esophageal cancer is approximately 10%, and the
5-year post-esophagectomy survival rate is between 15% to 40% [
10
]. Unfortunately, this
disease is diagnosed at an advanced stage due to the lack of clinical symptoms, which
contributes to the high mortality rate [
10
]. Since there are a small number of targeted
therapies for esophageal cancer, the main treatment options are surgery, chemotherapy, and
radiotherapy, as well as endoscopic therapies, such as radiofrequency ablation, endoscopic
mucosal resection, and endoscopic submucosal dissection [11].
The great majority of esophageal cancers are esophageal squamous cell carcinomas
(ESCC) or esophageal adenocarcinomas (EAC). ESCC is the most common type, repre-
senting 90% of esophageal cancers, having higher incidences in Asian and Eastern coun-
tries [
12
,
13
]. ESCC predominates in the upper and mid-thirds of the esophagus. It is
thought to develop through the progression of premalignant precursor lesions of the squa-
mous lining of the esophagus (squamous dysplasia), which result from the presence of
chronic inflammation [
14
,
15
] that causes architectural changes such as disordered cellular
stratification, loss of cellular polarity, and premature keratinization. Several risk factors
have been associated with the development of ESCC, namely smoking, tobacco chewing,
alcohol consumption, intake of hot beverages, and diets with reduced consumption of fresh
fruits and vegetables [16–18].
At the molecular level, the ESCC subtype contains frequent mutations in TP53, NFE2L2,
MLL2, ZNF750, NOTCH1, and TGFBR2 genes and is characterized by upregulation of Wnt,
syndecan, and p63 pathways, which are associated with the development and differen-
tiation of squamous epithelial cells [
19
]. Epidermal growth factor receptor (EGFR) and
receptor tyrosine kinase, or RAS signaling alterations, have been associated with ESCC and
with a worse prognosis. In addition, vascular endothelial growth factor (VEGF) signaling
pathway activation was also linked to ESCC and correlated with higher tumor stages and
lymph node metastasis [10].

Cancers 2023,15, 2576 3 of 15
Although in Western countries, the incidence of EAC is typically low, EAC has been
rapidly increasing, and in countries such as the United Kingdom, the Netherlands, the
United States, Denmark, Canada, and Sweden, it has already overtaken ESCC [
20
,
21
]. The
male sex, the Caucasian race, tobacco smoking, and obesity are the main risk factors for
EAC. Helicobacter pylori infection in the stomach appears to be inversely associated with
the incidence of EAC [
22
,
23
]. EAC occurs predominantly in the lower esophagus near the
gastric junction and develops in the context of Barrett’s esophagus [
24
]. This condition in
the esophagus arises from gastroesophageal reflux disease, which is a chronic digestive
condition in which acidic contents from the stomach, frequently mixed with duodenal bile,
enter the esophagus leading to esophageal tissue injury. At the cellular level, progression to
EAC is underlined by continuous DNA damage caused by reflux and chronic inflammatory
factors, which likely increase the mutation rate and promote genomic instability. TP53 is the
most frequently mutated gene in EAC tumors. A high frequency of mutations is also found
in CDKN2, which is known to regulate the cell cycle [
20
]. These molecular alterations are
consistent with the predominance of CDKN2A and TP53 mutations in dysplastic Barrett’s
esophagus, a precursor lesion of EAC. In addition, in EAC, mutations are frequently present
in ARID1A,SMAD4, and ERBB2 genes. Increased E-cadherin signaling and overexpression
of FOXA and ARF6, which regulate E-cadherin during the endocytic pathway, may also be
present in EAC [25].
3. Esophagus Microbiota in Healthy Conditions
The analysis of the bacterial community in the normal esophagus has been explored
in a small number of studies (Table 1), probably due to difficulties in the recruitment of
healthy volunteers for invasive sampling by upper endoscopy.
Table 1. Summary of the studies evaluating the esophageal microbiota in healthy individuals.
Reference Country No. Participants Specimen and Measurement Taxonomic Findings in Healthy Individuals *
Vuik et al. 2019 [26] The Netherlands HC (13)
RE (1)
Biopsy specimens
16S rRNA gene sequencing
Veillonellacea (F)
Psudomonadaceae (F)
Streptoccaceae (F)
Peter et al. 2020 [27] USA
HC (10)
IM (10)
HGD (10)
LGD (10)
EAC (12)
Biopsy specimens
16S rRNA gene sequencing
At the phylum-level:
Firmicutes
Proteobacteria
Bacteriodetes
Actinobacteria
Fusobacteria
At the genus-level:
Tissierella
Streptococcus
Lactobacillus
Acinetobacter
Prevotela
Fusobacterium
Staphylococcus
Akkermansia
Blautia
Yin et al. 2020 [28] China HC (27) Esophageal brush specimens
16S rRNA gene sequencing
At the phylum-level:
Proteobacteria
Firmicutes
Bacteroidetes
Actinobacteria
Fusobacteria
TM7
At the genus-level:
Streptococcus
Actinobacillus
Sphingomonas
unclassified Enterobacteriaceae
Neisseria
Haemophilus
Prevotella
Veillonella
Porphyromonas

Cancers 2023,15, 2576 4 of 15
Table 1. Cont.
Reference Country No. Participants Specimen and Measurement Taxonomic Findings in Healthy Individuals *
Li et al. 2020 [29] China
HC (16)
ESCC (17)
EGJ (11)
Esophageal brush specimens
16S rRNA gene sequencing
At the phylum-level:
Proteobacteria
Firmicutes
Bacteroidetes
Actinobacteria
At the genus-level:
Streptococcus
Ralstonia
Burkholderia–Caballeronia–Paraburkholderia
Fusobacterium
Li et al. 2021 [30] China
HC (82)
LGD (60)
HGD (64)
ESCC (70)
Esophageal brush specimens
16S rRNA gene sequencing
At the phylum-level:
Firmicutes
Proteobacteria
Bacteroidetes
Actinobacteria
Fusobacteria
At the genus-level:
Streptococcus
Neisseria
Haemophilus
Prevotella
EAC—esophageal adenocarcinoma; EGJ—esophagogastric junction cancer, F—family; HC—Healthy controls;
HGD—high-grade dysplasia; IM—Intestinal metaplasia, LGD—low-grade dysplasia; RE—reflux esophagitis.
* When data are available, taxa are displayed in descending order of abundance.
A Dutch study analyzed the mucosal microbiota composition along the entire gastroin-
testinal tract to find that the esophageal microbiota closely resembles the stomach micro-
biota rather than other communities in the gastrointestinal tract [
26
]. Proteobacteria were
the most abundant phylum in the esophagus, followed by Firmicutes and Bacteroidetes [
26
].
Accordingly, the families Veillonellaceae, Streptococcaceae of the phylum Firmicutes, and
Pseudomonadaceae of the phylum Proteobacteria were identified as the most abundant in
the distal esophagus [
26
]. Subsequent studies that characterized the esophageal microbiota
in biopsy specimens of American individuals and in mucosal brushings of Chinese subjects
confirmed the high abundance of Firmicutes, followed by Proteobacteria, Bacteroidetes,
Actinobacteria, and Fusobacteria [
27
,
28
,
30
]. Analysis of the esophageal mucosa microbiota
of American individuals revealed that the top-5 most abundant genera were Tissierella,
Lactobacillus,Streptococcus,Acinetobacter, and Prevotella [
27
]. Streptococcus,Actinobacillus,
Sphingomonas,Enterobacteriaceae,Neisseria,Haemophilus,Prevotella, Veillonella, and Porphyromonas
were identified as the most abundant members of the esophageal microbial community in a Chi-
nese study that characterized the microbiota in brush specimens from 27 healthy individuals [
28
].
Of note, all the studies that profiled the microbiome at the genus level consistently identified
the genus Streptococcus as one of the most abundant genera in the normal esophagus [
28
–
30
].
Despite the effort to characterize the normal esophagus microbiota, most publications
included a low number of individuals and presented limitations regarding sequencing and
data analysis sensitivity.
4. Modulators of the Esophageal Microbiota and of the Esophageal Cancer Risk
Several factors can disturb the esophageal microbiota, including alcohol consumption,
dietary habits, smoking, obesity, and the intake of drugs, such as antibiotics or proton-
pump inhibitors (PPIs) [
31
,
32
]. These elements are also important risk factors for the
development of esophageal cancer, despite the fact that their association is restricted to
specific cancer subtypes. For example, the intake of alcohol has been consistently associated
with ESCC, but its association with EAC is unclear [
33
]. Regarding the esophageal micro-
biota, a recent study that analyzed 120 patients with ESCC, 60 of which were drinkers and
60 were non-drinkers, found that alcohol consumption was associated with alterations
in the diversity and composition of the esophageal microbiota in ESCC patients. The
microbiota of drinkers showed significantly lower alpha-diversity (within sample diversity)
than that of non-drinkers, and their microbial profiles could be distinguished. Drinkers
showed an enrichment of the order Pasteurellales, particularly the family Pasteurellaceae.

Cancers 2023,15, 2576 5 of 15
In contrast, non-drinkers had a higher abundance of the class Clostridia, with specific en-
richment of the bacterial families Clostridiaceae, Lanchnospiraceae, and Helicobacteraceae,
and of the genera Clostridium,Helicobacter, and Catonella [34].
Diet can rapidly alter the structure and activity of the human gut microbiome [
35
].
Diets rich in lipids and sugars result in an increased body mass index and obesity, which
are strongly associated with an increased risk of EAC [
36
]. Whether obesity modulates
the human esophageal microbiota has not yet been addressed, but a study conducted in a
mouse model suggests that high-fat diets influence the gut microbiota, contributing to the
development of esophageal cancer [
37
]. Accordingly, the study reported that mice fed with
a high-fat diet developed esophageal dysplasia and tumors more rapidly than those fed
with a control diet. The high-fat diet resulted in an increased ratio of neutrophils to natural
killer cells, which favors cancer development. Moreover, a high-fat diet led to a shift in
the gut microbiota in comparison with a control diet. Analysis of microbial beta-diversity
(between sample diversity) showed separation between mice fed with a high-fat diet and
mice fed with the control diet. This differentiation was characterized by an altered ratio of
Firmicutes to Bacteroidetes.
The exposure of fecal microbiota from mice fed the high-fat diet to mice fed the control
diet accelerated tumor development in the esophagus. The relevance of the microbiota in
the development of esophageal cancer was further demonstrated in animals raised in germ-
free housing, which developed less dysplasia than mice grown under specific pathogen-free
conditions [
37
]. In contrast to high-fat diets, the consumption of dietary fibers can modu-
late the microbial composition of the esophagus and have a protective role in esophageal
neoplasia. A study comprising 47 patients demonstrated that fiber intake was positively
associated with the relative abundance of Firmicutes [
38
]. In contrast, fiber intake was
inversely associated with the relative abundance of Gram-negative Proteobacteria, which
can be found in the abnormal esophagus, including reflux esophagitis and Barrett’s esopha-
gus [
39
–
41
]. Altogether, these results are in line with those observed in the colon cancer
model, where changes in the dietary content of fiber and fat have an impact on the colonic
microbiome and metabolome, resulting in significant changes in mucosal inflammation
and proliferation, thereby increasing colon cancer risk [
42
]. Smoking is a well-known risk
factor for the development of cancer, but it can also shape the esophageal microbial commu-
nities through chemicals, heavy metals, and other constituents of tobacco [
43
]. A study of
278 male Chinese participants argued that current smokers tended to have increased micro-
bial alpha-diversity compared to never smokers. The same study identified the enrichment
of two anaerobes, Dialister invisus, and Megasphaera micronuciformis, in current smokers in
comparison with never smokers [44].
PPIs can also modulate microbiota. These drugs are used to relieve symptoms caused
by excessive acid production in the stomach, such as heartburn or gastroesophageal reflux
disease. Despite anti-acid drugs targeting the acid-producing glands of the stomach, they
can affect not only the gastric bacterial community but also the microbiota of the esoph-
agus and the intestine [
45
]. It has been proposed that anti-acid drugs directly target the
proton pumps containing P-type ATPase enzymes of specific bacteria, such as Streptococcus
pneumonia, or indirectly increase the pH to levels that cause the death of certain bacterial
species [
46
]. An investigation comparing the microbiota before and after PPI treatment
in 16 patients with heartburn and normal-appearing mucosa and in 29 patients with ab-
normal mucosa due to esophagitis and Barrett’s esophagus found significantly different
microbial profiles [
47
]. The treatment with PPIs was associated with increased abundance
of the Comamonadaceae family and decreased abundance of the families Clostridiaceae,
Lachnospiraceae, and two unclassified families of the orders Clostridia, Lactobacillales,
and Gemelalles [47].
Antibiotics have been used to treat bacterial infections, but they can also disturb the
resident bacteria. Despite this negative effect, in the context of cancer, specific antibiotics
have been used to eradicate opportunistic microbes in cancer patients, resulting in poten-
tially beneficial clinical outcomes [
48
]. Whether antibiotics have a protective effect against

Cancers 2023,15, 2576 6 of 15
the development of esophageal cancer is poorly explored. In fact, one study using a rat
mouse model showed a slight but non-significant reduction in the incidence of esophageal
adenocarcinoma in animals treated with penicillin G and streptomycin in comparison
with the control group [
49
]. This reduction was accompanied by an increased proportion
of Clostridium clusters XIVa and XVIII and a decreased proportion of the Lactobacillales
order [49].
5. Alterations in the Microbiota of Esophageal Premalignant Lesions
The role of the esophageal microbiota in the transition of normal epithelium to prema-
lignant lesions and in the progression towards esophageal cancer is mostly unknown. So
far, only a few studies have addressed this issue, and most of them presented limitations
in sensitivity and depth of coverage, impairing the ability to draw clear and statistically
based conclusions (Table 2). One of the first studies used an oral microbe identification
microarray to characterize the presence of 272 microbial species in 142 Chinese patients
with esophageal dysplasia and in 191 patients without esophageal dysplasia [
50
]. The
study revealed an association between microbial richness and esophageal squamous dys-
plasia [
50
]. These results were confirmed in a more recent study that profiled the esophageal
microbiota in 227 patients with normal esophageal function, low-grade dysplasia, high-
grade dysplasia, and ESCC [
30
]. Disease progression was associated with decreased
alpha-diversity and with a small but significant beta-diversity. Comparing the microbiota
of dysplastic lesions with that of the normal esophagus, the genera Atopobium,Enterococcus,
Granulicatella,Lachnoanaerobaculum,Rothia, Solobacterium, and Streptococcus were found to
be enriched in low-grade dysplasia, while the genera Bacillus,Lactobacillus and Streptococcus
were identified as markers of high-grade dysplasia [30].
Table 2. Studies characterizing the esophageal microbiota in esophageal premalignant lesions.
Reference Country (N) Specimen and Measurement Diversity Taxonomic Findings
Alpha Beta
Macfarlane et al.
2007 [51]
USA
No BE (7)
BE (7)
Biopsy; Aspirate
16S rRNA gene sequencing
↑BE NS
↑Veillonella (G)
↑Neisseria (G)
↑Camplylobacter (G)
↑Fusobacterium (G)
↑Megasphaera (G)
↑Staphylococcus (G)
↓Lactobacillus (G)
Yang et al.
2009 [40]
USA
HC (12)
ES (12)
BE (10)
Biopsy
16S rRNA gene sequencing
↑Type II compared to
type I
Distinguished
Type I and Type
II microbiome
Type I microbiome:
Normal esophagus
Type II microbiome: Abnormal
esophagus
Type II vs. Type I:
↑Gram-negative bacteria
↑Veillonella (G)
↑Prevotella (G)
↑Haemophilus (G)
↑Neisseria (G)
↑Rothia (G)
↑Granulicatella (G)
↑Campylobacter (G)
↑Porphyromonas (G)
↑Fusobacterium (G)
↑Actinomyces (G)
↓Firmicutes (P)
↓Streptoccocus (G)
Liu et al.
2013 [52]
Japan
HC (6)
ES (6)
BE (6)
Biopsy
16S rRNA gene sequencing
NS NS
ES/HC vs. BE:
↓Streptococcus (G)
ES/BE vs. HC:
↑Veillonella (G)
↑Neisseria (G)
↑Fusobacterium (G)
Yu et al.
2014 [50]
China
No ESD (191)
ESD (142)
Brush
Human oral microbe
identification microarray
↓ESD Distinguished
ESD and No ESD
Inverse association
between microbial richness
and ESD when comparing with
non ESD

Cancers 2023,15, 2576 7 of 15
Table 2. Cont.
Reference Country (N) Specimen and Measurement Diversity Taxonomic Findings
Alpha Beta
Elliot et al.
2017 [24]
UK
HC (20)
NDBE (24)
BE (23)
EAC (19)
Biopsy, Brushing, Cytosponge
16S rRNA gene sequencing
NS
Distinguished
HC
and BE
↑Proteobacteria (P)
Deshpande et al. 2018
[53]
Australia
HC (59)
GERD (29)
GM (7)
BE (5)
EAC (1)
EoE (1)
Esophageal brush specimens
16S rRNA gene sequencing
Whole metagenome
sequencing
NS NS
GERD vs. HC:
↑Flavobacteriaceae (F)
↑Acetoanaerobium (G)
↑Filifactor (G)
↑Campylobacter (G)
↑Prevotella intermedia (S)
↑Prevotella micans (S)
↑Neisseria macacae (S)
↑Neisseria meningitidis (S)
↑Haemophilus parainfluenzae (S)
↑Treponema medium (S)
BE vs. HC:
↑Leptotrichia (G)
↑Capnocytophaga (G)
↑Gemella (G)
↑Veillonella (G)
↑Streptococcus sanguinis (S)
Snider et al.
2019 [54]
USA
HC (16)
NDBE (14)
LGD (6)
HGD (5)
EAC (4)
Brush
16S rRNA gene sequencing
NS NS
HGD vs. LGD:
↑Proteobacteria (P)
↓Firmicutes (P)
↓Veillonella (G)
Lopetuso et al.
2020 [55]
Italy
HC (10)
BE (10)
BEU (10)
EAC (6)
Biopsy
16S rRNA gene sequencing
↓BE Distinguished
HC and BE
BE vs. HC:
↑Fusobacteria (P)
↑Leptotrichia (G)
BE vs. BEU:
↓Bacteroidetes (P)
↓TM7 (P)
↓Prevotellaceae (F)
↓Veillonellaceae (F)
↓Fusobacteriaceae (F)
↓Lachnospiraceae (F)
↓Campylobacteraceae (F)
↓Prevotella (G)
↓Fusobacterium (G)
↓Campylobacter (G)
↓Selenomonas (G)
Li et al.
2021 [30]
China
HC (82)
LGD (60)
HGD (64)
ESCC (70)
Brush
16S rRNA gene sequencing
↓HGD compared to
HC/LGD
Distinguished
HC/LGD group
and HGD
LGD vs. HC:
↑Atopobium (G)
↑Enterococcus (G)
↑Granulicatella (G)
↑Lachnnoanaerobaculum (G)
↑Rothia (G)
↑Solobacterium (G)
↑Streptococcus (G)
HGD vs. HC:
↑Bacillus (G)
↑Lactobacillus (G)
↑Streptococcus (G)
AHT—adjacent mucosa healthy tissue; BE—Barrett’s esophagus; BEU—unaffected esophageal mucosa of Barrett’s
esophagus patient; EAC—esophageal adenocarcinoma; ES—esophagitis; ESD—esophageal squamous dysplasia;
GERD—gastroesophageal reflux disease; GM—glandular mucosa; EoE—Eosinophilic esophagitis; HC—healthy
control, HGD—High grade dysplasia; LGD—Low grade dysplasia, NDBE—non-dysplastic Barrett’s esophagus;
NS—not significant; P—phylum; F—family; G—genus; S—species; ↑—increase; ↓—decrease.
Initial analyses of Barrett’s esophagus microbiota revealed that the esophageal mi-
crobiota could be categorized into two main types [
40
]. Type I was dominated by Gram-
positive Streptococcus sp. and comprised cases with a morphologically normal esophagus.
Conversely, type II was characterized by a high abundance of Gram-negative anaerobes
and microaerophiles and was associated with esophagitis and Barrett’s esophagus [
40
].
Comparing the microbial community of Barrett’s esophagus with that of healthy controls,
Lopetuso et al. identified only minor taxonomic differences, including the increase in the

Cancers 2023,15, 2576 8 of 15
relative abundance of Fusobacteria at the phylum level and of Leptotrichia genus. How-
ever, this study noted a decrease in the abundance of the genera Prevotella,Fusobacterium,
Campylobacter, and Selenomonas when metaplastic mucosa of Barrett’s esophagus was com-
pared with adjacent normal areas of Barrett’s esophagus [
55
]. A larger case-control study
reported marginal differences between the microbiota of Barrett’s esophagus and the mi-
crobial community of EAC. This study pointed to a significantly higher number of taxa
but not to an overall difference in the microbial alpha-diversity of Barrett’s esophagus
compared to that of EAC [24]. Moreover, Barrett’s lesions contained a significantly higher
abundance of Proteobacteria than that found in EAC and in normal controls [
24
]. A study
that combined 16S rRNA gene sequencing with whole metagenome sequencing identified
10 microbial taxa in gastroesophageal reflux disease patients in comparison with healthy
controls, including Prevotella intermedia,Prevotella micans,Neisseria macacae,Neisseria meningitidis,
Haemophilus parainfluenzae, and Treponema medium. The comparison of Barrett’s esophagus
patients with controls revealed an increase in abundance of Leptotrichia,Capnocytophaga,
Gemella,Veillonella, and Streptococcus sanguinis. The study pointed that distinct microbial
community types are mainly defined by the relative abundance of the genera Streptococcus
and Prevotella [53].
A study that aimed to reveal the potential role of the microbiota in the development of
esophageal cancer profiled the microbial community of 45 patients, following the progres-
sion from Barrett’s esophagus to cancer [
54
]. The study reported a shift in the microbial
composition of Barrett’s esophagus at the transition from low- to high-grade dysplasia.
This was characterized by decreased abundance of Firmicutes, namely of Veillonella sp., an
increased abundance of Proteobacteria of the Enterobacteriaceae family, and an increased
proportion of samples with Akkermansia muciniphila in high-grade dysplasia.
6. The Esophageal Microbiota in Esophageal Cancer
Considering that esophageal cancer develops in the context of chronic inflammation,
which is influenced by genetic and environmental factors, the esophageal microbiota is a
possible etiological factor of esophageal cancer (Table 3).
Table 3. Summary of the studies evaluating esophageal microbiota in esophageal cancer.
Reference Country (N) Specimen and Measurement Diversity Taxonomic Findings
Alpha Beta
Elliott et al.
2017 [24] *
UK
HC (20)
NDBE (24)
BE (23)
EAC (19)
Biopsy, Brushing, Cytosponge
16S rRNA gene sequencing
↓EAC in
comparison with HC
Distinguished EAC
and HC
EAC vs. HC:
↑Lactobacillales (O)
↑Coriobacteriacea (F)
↑Lactobacillaceae (F)
↑Streptococcus (G)
↑Lactobacillus (G)
Shao et al.
2019 [56] **
China
ESCC (67)
NAM (67)
Biopsy
16S rRNA gene sequencing
NS Distinguished ESCC
and NAM
ESCC vs. NAM:
↑Fusobacteria (P)
↓Firmicutes (P)
↓Fusobacterium (G)
↓Streptococcus (G)
Snider et al.
2019 [54] *
USA
HC (16)
NDBE (14)
LGD (6)
HGD (5)
EAC (4)
Brush
16S rRNA gene sequencing
↓EAC in
comparison with
NDBE, LGD
and HGD
NS
HGD/EAC vs. NDBE/LGD:
↓Firmicutes (P)
↑Proteobacteria (P)
↑Enterobacteriacea (F)
↑Akkermansia muciniphila (S)
↓Veillonella (G)
Lopetuso et al.
2020 [55] *
Italy
HC (10)
BE (10)
EAC (6)
Biopsy
16S rRNA gene sequencing
↑EAC in
comparison with HC
Distinguished EAC
and HC
EAC vs. HC:
↑Prevotella (G)
↑Leptotrichia (G)
↑Veillonella (G)
↑Bacteroidetes (G)
↓Streptococcus (G)
↓Granulicatella (G)

Cancers 2023,15, 2576 9 of 15
Table 3. Cont.
Reference Country (N) Specimen and Measurement Diversity Taxonomic Findings
Alpha Beta
Li et al.
2020 [29] *
China
HC (16)
RE (15)
EGJ (11)
ESCC (17)
Brush
16S rRNA gene sequencing
↓ESCC and EGJ
in comparison
with HC
Distinguished ESCC
and HC
ESCC vs. HC:
↑Fusobacteria (P)
↓Actinobacteria (P)
Peter et al.
2020 [27] *
USA
IM (10)
LGD (10)
HGD (10)
EAC (12)
HC (10)
Biopsy
16S rRNA gene sequencing
NS NS
EAC vs. HC:
↓Planctomycetes (P)
↓Crenachaeota (P)
↓Siphonobacter (G)
↓Nitrosopumilus (G)
↓Planctomyces (G)
Li et al.
2021 [30] *
China
HC (82)
LGD (60)
HGD (64)
ESCC (70)
Brush
16S rRNA gene sequencing
↓ESCC in
comparison with HC
Distinguished ESCC
and HC
ESCC vs. HC:
↑Peptoniphilus (G)
↑Petostreptococcus (G)
↑Lachnospiraceae_[G9] (G)
↑Bosea (G)
↑Gemella (G)
↑Solabacterium (G)
↑Streptococcus (G)
Li et al.
2021 [57] **
China
ESCC (41)
NAM (41)
Biopsy
16S rRNA gene sequencing
↓ESCC in
comparison
with NAM
Distinguished ESCC
and NAM
ESCC vs. NAM:
↑Bacteroidetes (P)
↑Fusobacteria (P)
↑Spirochaetae (P)
↓Proteobacteria (P)
↓Firmicutes (P)
↓Actinobacteria (P)
↑Streptococcus (G)
↑Fusobacterium (G)
↑Prevotella (G)
↓Butyrivibrio (G)
↓Lactobacillus (G)
Jiang et al.
2021 [15] *
China
HC (21)
ES (15)
ESCC (32)
Biopsy
16S rRNA gene sequencing
↑ESCC in
comparison with HC
Distinguished ESCC
and HC
ESCC vs. HC:
↓Fusobacteria (P)
↑Streptococcus (G)
↑Actinobacillus (G)
↑Peptostreptococcus (G)
↑Fusobacterium (G)
↑Prevotella (G)
↓Bacteroides (G)
↓Faecalibacterium (G)
↓Curvibacter (G)
↓Blautia (G)
Shen
2022 et al. [58] **
China
ESCC (51)
NAM (51)
Biopsy
16S rRNA gene sequencing
Species-specific qPCR
NS NS
ESCC vs. NAM:
↓Deinococcus-Thermus (P)
↑Spirochaetes (P)
↑Tenericutes (P)
↓Actinobacteria (P)
↓Verrumicrobia (P)
↑Lentimicrobiaceae (F)
↑Treponema (G)
↑Selenomonas (G)
↑Peptonaerobacter (G)
↓Methylobacter (G)
↓Akkermansia (G)
↑Blautia (G)
↑Labrys ginsengisoli (S)
↑Peptoanaerobacter stomatis (S)
↑Selenomonas sputigena (S)
↑Streptococcus constellatus (S)
↑Fusobacterium periodonticum (S)
↓Lactobacillus murinus (S)
↓Escherichia coli (S)
* Studies comparing esophageal cancer with healthy subjects. ** Studies comparing paired normal adjacent mucosa
with tumor tissue. BE—Barrett’s esophagus; C—class; EAC—esophageal adenocarcinoma; EC—esophageal cancer;
EGJ—esophagogastric junction cancer; ES—esophagitis; ESCC—esophageal squamous cell carcinoma; ESD—
esophageal squamous dysplasia; F—family; G—genus; HC—healthy controls; HGD—high grade dysplasia;
IM—intestinal metaplasia; LGD—low grade dysplasia; MEE—mid-esophageal esophagitis; NAM—normal
adjacent mucosa; NDBE—non-dysplastic Barrett’s esophagus; NS—no significant difference; RE—after radical
esophagectomy; P—phylum; O—order; F—family; S—species; ↑—increase; ↓—decrease.

Cancers 2023,15, 2576 10 of 15
In comparison with healthy controls, the microbial community of ESCC is characterized
by reduced bacterial diversity [
15
,
29
,
30
] and by the enrichment of several genera, including
Streptococcus,Peptostreptococcus,Prevotella,Fusobacterium,Actinobacillus,Gemella,Rothia, and
Prevotella [
15
,
29
,
30
]. However, the analysis of the microbial community of tumor tissues
and paired adjacent normal tissues did not identify consistent significant differences in the
bacterial richness and diversity [
56
,
57
] but revealed a significant enrichment of Fusobacterium
and Streptococcus and a decrease in the abundance of Lactobacillus in the ESCC tissue [
57
–
59
].
Interestingly, one study that included patients with ESCC and combined several genomics
methods showed that the abundance of Fusobacterium nucleatum was significantly associated
with the tumor tissue and not with the normal adjacent epithelium. This study pointed
out that F. nucleatum was closely related to increased tumor staging and to the presence of
mutations in genes such as TP53,COL22A1,TRBV10–1, CSMD3,SCN7A, and PSG11 [57].
The microbial community of EAC is less characterized than ESCC. In fact, so far,
only four studies evaluated the microbiota in EAC, with inconsistent results, proba-
bly due to differences in methodology, study design, and the limited number of cases
included [
24
,
27
,
54
,
55
]. A study that performed a microbiome survey in only four patients
with EAC, 25 with Barrett’s esophagus, and 16 healthy controls showed a decrease in
the alpha-diversity in cases with non-dysplastic Barrett’s esophagus and EAC [
54
]. This
study identified the enrichment of Enterobacteriaceae and Akkermansia municiphila and the
decrease in Veillonella in cancer cases [
54
]. Another study that compared six EAC patients
with 10 healthy controls identified a decrease in the microbial alpha-diversity in cancer
in comparison with healthy controls, which was accompanied by a significant increase
in the abundance of Prevotella sp., Veillonella sp., and Leptotrichia sp. [
55
]. On the other
hand, Peter et al. identified in the EAC mucosa a significant decrease in the abundance of
Siphonobacter,Nitrosopumilus, and Planctomyces in comparison tissue of healthy controls [
27
].
A larger study that compared the mucosal microbiota of 19 EAC with 20 healthy controls
detected a significant increase in the abundance of Streptococcus and Lactobacillus in cancer
cases [
24
]. This study suggested that Lactobacillus sp. dominate the niche of EAC due to
their capability to resist low pH and to inhibit the growth of competitor bacteria through
the production of lactic acid [24].
7. Non-Esophageal Microbiota and Esophageal Cancer
In recent years, several studies reported associations between the oral or the gut mi-
crobiota and increased risk of esophageal cancer. Given the invasive nature of sampling the
esophagus through upper endoscopy for microbiome analysis, access to non-invasive oral
or fecal specimens can be viewed as an opportunity to easily detect microbial biomarkers
of esophageal cancer (Table 4).
Table 4. Studies show relationships between non-esophageal microbiota and esophageal cancer.
Reference Country (N) Specimen and Measurement Diversity Taxonomic Findings
Alpha Beta
Peters et al.
2017 [60]
USA
HC (210)
ESCC (25)
EAC (81)
Mouthwash
16S rRNA gene sequencing
NS NS
EAC:
↑Selenomonas (G)
↑Veillonella (G)
↑Tannerella forsythia (S)
↑Actinomyces cardiffensis (S)
ESCC:
↑Bergeyella (G)
↑Porphyromonas gingivales (S)
↑Prevotella nanceiensis (S)
↑Neisseria weaver (S)
↑Treponema vincentii (S)
Wang et al.
2019 [61]
China
HC (21)
ESCC (20)
Saliva
16S rRNA gene sequencing
NS Distinguished HC
and ESCC
ESCC vs. HC:
↑Firmicutes (P)
↓Gammaproteobacteria (C)
↑Bacillus (G)
↑Lactobacillus (G)

Cancers 2023,15, 2576 11 of 15
Table 4. Cont.
Reference Country (N) Specimen and Measurement Diversity Taxonomic Findings
Alpha Beta
Ishaq et al.
2021 [62]
China
HC (10)
EC (15)
Biopsy
DGGE
16S rRNA gene sequencing
↑EC Distinguished HC
and EC
EC vs. HC:
↑Bacteroidetes (P)
↑Bacteroidaceae (F)
↑Enterobacteriaceae (F)
↑Bacteroides (G)
↑Escherichia-Shigella (G)
↓Prevotellaceae (F)
↓Veillonellaceae (F)
↓Prevotella (G)
↓Dialister (G)
Chen et al.
2021 [6]
Taiwan
HC (18)
ESCC (34)
Oral biofilm; Biopsy
P. gingivalis qPCR;
16S rRNA gene sequencing
↓ESCC Distinguished HC
and ESCC
ESCC vs. HC:
Oral biofilm:
↑Streptococcus (G)
↑Veillonella (G)
↑Porphyromonas gingivalis (S)
Biopsy:
↑P. gingivalis (S)
Zhao et al.
2020 [63]
China
HC (51)
EC (49)
Saliva
16S rRNA gene sequencing
NS Distinguished HC
and EC
EC vs. HC:
↑Firmicutes (P)
↓Proteobacteria (P)
↑Negativicutes (C)
↓Betaproteobacteria (C)
↑Selenomonadales (O)
↓Neisseriales (O)
↑Veillonellaceae (F)
↑Prevotellaceae (F)
↓Neisseriaceae (F)
↑Prevotella (G)
↓Neisseria (G)
Deng et al.
2021 [64]
China
HC (23)
EC (23)
Stool
16S rRNA gene sequencing
↑richness in EC Distinguished HC
and EC
EC vs. HC:
↓Bacteroides (P)
↑Streptococcus (G)
↑Bifidobacterium (G)
↑Subdoligranulum (G)
↑Blautia (G)
↑Romboutsia (G)
↑Collinsella (G)
↑Paeniclostridium (G)
↑Dorea (G)
↑Atopobium (G)
↓Lachnospira (G)
↓Bacteroides (G)
↓Agathobacter (G)
↓Lachnoclostridium (G)
↓Parabacteroides (G)
↓Paraprevotella (G)
↓Butyricicoccus (G)
↓Tyzzerella (G)
↓Fusicatenibacter (G)
↓Sutterella (G)
Wu et al.
2022 [65]
China
HC (40)
EC (40)
Stool
Culture
– –
EC vs. HC:
↑Enterococcus (G)
↑Escherichia coli (S)
↓Bifidobacterium (G)
↓Lactobacillus (G)
C—class; DS—dysplasia; EAC—esophageal adenocarcinoma; EC—esophageal cancer; ESCC—esophageal squa-
mous cell carcinoma; F—family; G—genus; NS—no significant difference; O—order; P—phylum,
↑
—increase;
↓—decrease.
Comparing the salivary bacterial community of 34 ESCC patients and 18 healthy
controls from China, Chen et al. showed an overall decrease in alpha-diversity and clear
separation of patient groups in beta-diversity matrices [
6
]. In accordance with these data,
a Taiwanese study reported a decrease in bacterial richness in the saliva of patients with
ESCC [
6
]. In contrast, two studies that also included Chinese patients did not find significant
differences in the oral microbial alpha-diversity between ESCC and healthy controls [
61
,
63
].
When evaluating taxonomic differences, the relative abundance of Prevotella,Streptococcus,
Porphyromonas [
6
], and Neisseria [
63
] was significantly higher in patients than in controls.
In another study that examined the oral microbiome of 25 ESCC, 81 EAC patients, and
50 controls from the United States, Peters et al. did not find significant differences in the

Cancers 2023,15, 2576 12 of 15
alpha-diversity [
60
]. The same study reported an association between the presence of
Porphyromonas gingivalis, a pathogen associated with periodontal disease, and an increased
risk of ESCC [
60
]. Moreover, the presence of the pathogen Tannerella forsythia and the enrich-
ment of Actinomyces cardiffensis,Selenomonas, and Veillonella were significantly associated
with an increased risk of EAC [
60
]. Zhao et al. compared the microbiota of 49 esophageal
cancers with 51 healthy controls and detected higher abundances of Prevotella nanceiensis,
Neisseria weaveri, and Treponema vincentii in cancer cases [63].
The relationship between the gut microbiome and esophageal cancer has been poorly
explored [
62
,
64
]. In a case-control study that characterized the microbiome in fecal samples
from 15 patients with esophageal cancer and 10 healthy controls, significant alterations
in the microbiota were identified, which are compatible with gut microbial dysbiosis in
cancer patients [
62
]. This study detected increased diversity in the fecal microbiota of
cancer patients in comparison with that of healthy controls. Moreover, significant en-
richment in the abundances of Bacteroidetes, Bacteroidaceae, Enterobacteriaceae, and of
Escherichia-Shigella, was identified in esophageal cancer patients [
62
]. In another study that
included 23 esophageal cancers and 23 healthy controls, a significant increase in microbial
richness was detected in the gut microbiota of cancer patients [
64
]. Analysis of the microbial
profile by hierarchical clustering revealed a clear separation of the microbial community be-
tween esophageal cancer patients and controls. These differences were mainly attributed to
the enrichment in cancer patients of several genera, including Streptococcus,Bifidobacterium,
Subdoligranulum,Blautia,Romboutsia,Collinsella,Paeniclostridium,Dorea, and Atopobium [
64
].
8. Conclusions and Future Directions
Esophageal cancer is a very relevant pathology both in terms of mortality and morbidity.
It is now accepted that the esophageal microbiome is altered in esophageal carcinogenesis.
Some of the classical risk factors associated with esophageal cancer appear to be
associated with changes in the normal microbiota of the esophagus. Alcohol consumption
has been linked with alterations of the diversity of the microbiota in ESCC patients. Diets
rich in high-fat contents in animal studies have been linked with esophageal dysplasia and
alterations of the microbiota. The low intake of fibers was also associated with an increase
in Gram-negative species, which can be found in esophageal cancer precursor lesions.
Smoking, and drugs such as PPIs and antibiotics, have been associated to changes in the
esophageal bacterial population. Overall, the microbiota of the normal esophagus is mainly
composed of Firmicutes, Proteobacteria, Bacteriodetes, Actinobacteria, and Fusobacteria. In
contrast, esophageal cancer is characterized by reduced microbial diversity, which appears
to begin in the precursor stages of esophageal cancer. At the taxonomic level, the esophageal
cancer microbiota is characterized by a shift from Gram-positive to Gram-negative bacteria.
The genera most commonly enriched in esophageal cancer are Fusobacterium,Streptococcus,
Veilonella, and Prevotella.
Even though one can pinpoint specific alterations in the esophageal cancer microbiota,
a consistent esophageal cancer-associated microbiota profile has not yet been identified.
This lack of consistency can be due to the different technical approaches, such as the
sampling method, the type of samples analyzed, and the analytic strategy used to profile
the microbiome, as well as to the relatively small number of individuals included in each
study. Future studies should consider the standardization of the methods, namely DNA
isolation, 16S rRNA amplification and sequencing, and data analysis, which will positively
impact the reliability of the results. In addition, the inclusion of blanks to control potential
microbial contaminations, which can arise during sample processing, will improve the
quality of the final datasets. The use of molecular approaches alternative to 16S rRNA gene
sequencing, such as whole metagenome sequencing, may help disclose in greater detail the
taxonomic profile to the species level and also allow the evaluation of the functional content
of the microbiome. Although these methods have never been applied to the mucosal
esophageal microbiome, they have the potential to identify microbial toxins, virulence
factors, and enzymes that can influence carcinogenesis in the esophagus.

Cancers 2023,15, 2576 13 of 15
Additional relevant aspects need to be considered when addressing the relationship
between the microbiome and esophageal cancer. The inclusion of patients of distinct
geographic origins will be important to control the influences of the host genetic diversity
and distinct cultural lifestyles. Furthermore, the collection of data on dietary habits, use
of medication, and lifestyle factors of each individual will be relevant to control potential
confounding variables in the observed microbiota profiles. In future studies in the setting
of esophageal carcinogenesis associated with the microbiome, multidisciplinary research
efforts will be fundamental to analyze and integrate the effects of multiple exposures,
including those of the diet, with the microbiome and with the changes that occur along
the process of carcinogenesis [
66
]. The dissection of such complex interactions would
benefit from large and well-characterized prospective cohort studies and would certainly
contribute to designing novel prevention and treatment strategies to reduce the burden of
esophageal cancer.
Author Contributions:
Conceptualization: R.M.F.; Literature search and data retrieval: C.M, C.F.
and R.M.F.; Data retrieval and interpretation: C.M., C.F. and R.M.F.; Writing—original draft: C.M.
and R.M.F.; Writing—critical review and editing: all authors; Visualization: all authors; Supervision:
R.M.F. All authors have read and agreed to the published version of the manuscript.
Funding:
R.M.F. has a Fundação para a Ciência e a Tecnologia (FCT) researcher position under the
Individual Call to Scientific Employment Stimulus (CEECIND/01854/2017). The team is also funded
by national funds through FCT (PTDC/BTM-TEC/0367/2021 and 2022.02141.PTDC).
Conflicts of Interest: The authors declare no conflict of interest.
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