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Citation: Plaza-Diaz, J.; Ruiz-Ojeda,
F.J.; López-Plaza, B.; Brandimonte-
Hernández, M.; Álvarez-Mercado,
A.I.; Arcos-Castellanos, L.;
Feliú-Batlle, J.; Hummel, T.;
Palma-Milla, S.; Gil, A. Effect of a
Novel Food Rich in Miraculin on the
Oral Microbiome of Malnourished
Oncologic Patients with Dysgeusia.
Cancers 2024,16, 3414. https://
doi.org/10.3390/cancers16193414
Academic Editor: Judith
E. Raber-Durlacher
Received: 30 August 2024
Revised: 30 September 2024
Accepted: 6 October 2024
Published: 8 October 2024
Copyright: © 2024 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
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4.0/).
cancers
Article
Effect of a Novel Food Rich in Miraculin on the Oral Microbiome
of Malnourished Oncologic Patients with Dysgeusia
Julio Plaza-Diaz 1,2,3,*,† , Francisco Javier Ruiz-Ojeda 1,2,4,5,6,† , Bricia López-Plaza 7,8 ,
Marco Brandimonte-Hernández 1, Ana Isabel Álvarez-Mercado 2,5,9 , Lucía Arcos-Castellanos 7,
Jaime Feliú-Batlle 10, 11, 12 , Thomas Hummel 13, Samara Palma-Milla 12 ,14 ,‡ and Angel Gil 1,2,5,6,*, ‡
1Department of Biochemistry and Molecular Biology II, School of Pharmacy, University of Granada,
18071 Granada, Spain; fruizojeda@ugr.es (F.J.R.-O.); mbrandimonte@ugr.es (M.B.-H.)
2Instituto de Investigación Biosanitaria ibs.GRANADA, Complejo Hospitalario Universitario de Granada,
18014 Granada, Spain; alvarezmercado@ugr.es
3Children’s Hospital of Eastern Ontario Research Institute, Ottawa, ON K1H 8L1, Canada
4
RU Adipocytes and Metabolism, Helmholtz Diabetes Center at Helmholtz Munich, German Research Center
for Environmental Health GmbH, 85764 Neuherberg, Germany
5Institute of Nutrition and Food Technology “JoséMataix”, Center of Biomedical Research, University of
Granada, Avda. del Conocimiento s/n. Armilla, 18016 Granada, Spain
6CIBEROBN (CIBER Physiopathology of Obesity and Nutrition), Instituto de Salud Carlos III,
28029 Madrid, Spain
7Food, Nutrition and Health Platform, Hospital La Paz Institute for Health Research (IdiPAZ), 28046 Madrid,
Spain; bricia.plaza@idipaz.es (B.L.-P.); lucia.arcos.castellanos@idipaz.es (L.A.-C.)
8
Medicine Department, Faculty of Medicine, Complutense University of Madrid, Plaza de Ramón y Cajal, s/n,
28040 Madrid, Spain
9Department of Pharmacology, University of Granada, 18071 Granada, Spain
10
Oncology Department, Hospital La Paz Institute for Health Research-IdiPAZ, Hospital Universitario La Paz,
28029 Madrid, Spain; jaime.feliu@salud.madrid.org
11 CIBERONC (CIBER Cancer), Instituto de Salud Carlos III, 28029 Madrid, Spain
12 Medicine Department, Faculty of Medicine, Autonomous University of Madrid, Arzobispo Morcillo 4,
28029 Madrid, Spain; samara.palma@salud.madrid.org
13
Smell & Taste Clinic, Department of Otorhinolaryngology, Technische Universität Dresden, Fetscherstraße 74,
01307 Dresden, Germany; thomas.hummel@tu-dresden.de
14 Nutrition Department, Hospital University La Paz, 28046 Madrid, Spain
*Correspondence: jrplaza@ugr.es (J.P.-D.); agil@ugr.es (A.G.); Tel.: +34-958241000 (ext. 41599) (J.P.-D.);
+34-695466922 (A.G.)
†These authors contributed equally to this work.
‡These authors contributed equally to this work.
Simple Summary: Patients suffering from taste disorders have been unable to find treatments in the
pharmaceutical industry. In this study, a novel strategy has been presented to reduce side effects
in patients suffering from cancer by administering dried miracle berries (DMBs), which contain the
taste-modifying glycoprotein miraculin, as an adjuvant to medical-nutritional therapy. During a three-
month pilot randomized, parallel, triple-blind, and placebo-controlled clinical trial, malnourished
patients with cancer and dysgeusia received either a standard dose of DMB, a high dose of DMB,
or a placebo. We analyzed the oral microbiome of patients who consumed a DMB or placebo tablet
before each main meal. Patients with cancer and dysgeusia who consumed DMB regularly displayed
changes to their oral microbiome, which may have contributed to the maintenance of an appropriate
immune response.
Abstract: Background/Objectives: Dysgeusia contributes to the derangement of nutritional status
in patients with cancer as well as worsening the quality of life. There has been a lack of effective
treatments for taste disorders provided by the pharmaceutical industry. Methods: This was a pilot
randomized, parallel, triple-blind, and placebo-controlled intervention clinical trial in which 31 mal-
nourished patients with cancer and dysgeusia receiving antineoplastic treatment were randomized
into three arms [standard dose of DMB (150 mg DMB/tablet), high dose of DMB (300 mg DMB/tablet)
or placebo (300 mg freeze-dried strawberry)] for three months. Patients consumed a DMB or placebo
Cancers 2024,16, 3414. https://doi.org/10.3390/cancers16193414 https://www.mdpi.com/journal/cancers
Cancers 2024,16, 3414 2 of 24
tablet before each main meal. Using the nanopore methodology, we analyzed the oral microbiome
of patients with cancer using saliva samples. Results: All patients with cancer and dysgeusia had
dysbiosis in terms of lower bacterial diversity and richness. DMB consumption was associated with
changes in oral microbiome composition. Neither selected bacteria nor taste perception, type of diet,
and cytokine levels were associated with mucositis. Likewise, alcohol and tobacco consumption
as well as general and digestive toxicity due to systemic therapy were not associated with specific
changes of the oral microbiome, according to logistic binary regression. The standard dose of DMB
resulted in a lower abundance of Veillonella compared with the high DMB dose and placebo at
3 months after intervention with DMB. In particular, some species such as Streptococcus parasanguinis,
Veillonella parvula, and Streptococcus mutans were less abundant in the DMB standard-dose group.
Additionally, the consumption of a standard dose of DMB revealed a negative association between the
concentrations of TNF-
α
and the abundance of species such as Streptococcus thermophilus,Streptococcus
pneumoniae,Streptococcus dysgalactiae and Streptococcus agalactiae. Conclusions: Accordingly, regular
DMB consumption could modify the oral microbiome in patients with cancer and dysgeusia, which
may contribute to maintaining an appropriate immune response. However, as the present pilot study
involved a small number of participants, further studies are necessary to draw robust conclusions
from the data.
Keywords: cancer; neoplasms; dysgeusia; malnutrition; oral microbiome; dried miracle berries;
taste disorders
1. Introduction
Cancer is a group of diseases characterized by uncontrolled cell proliferation [
1
], affect-
ing people in a multitude of ways, encompassing psychological, physiological, economic,
and social aspects [
2
]. The 2020 data from the World Health Organization (WHO) indicate
that 19.3 million new cancer cases were diagnosed, and the number of rising cancer cases
might reach 30.2 million by 2040. Hence, seeking treatments and prevention can reduce
those costs, improve patients’ quality of life, and possibly increase survival rates.
Systemic cancer treatments such as chemotherapy, immunotherapy, and radiotherapy
may lead to undesirable side effects that affect taste and smell [
3
,
4
]. Indeed, patients with
cancer undergoing systemic treatments often experience taste disorders in the range of
20–86% [
5
–
7
]. Different types of taste disorders have been reported in patients with cancer
depending on the type of antineoplastic treatment, the location of the cancer, and its charac-
teristics [
8
,
9
]. Dysgeusia is the most frequent qualitative and quantitative taste dysfunction,
including taste distortions with bitter, metallic, salty, or unpleasant tastes [10,11].
Additionally, antineoplastic therapies have also been associated with reduced saliva
production [
12
–
15
]. Thus, xerostomia may also cause the saliva to be thicker and contain
high concentrations of salt, influencing the sense of taste [12,16].
A reduction in quality of life in patients with cancer is observed when taste is impaired
with further deterioration of their nutritional status [
17
]. In addition to reducing the
patient’s quality of life, dysgeusia can lead to weight loss during treatment and worsen
the patient’s prognosis [
18
]. The pharmaceutical industry has failed to provide effective
treatments for dysgeusia. The treatments used for taste disorders are zinc supplementation,
amifostine, selenium, lactoferrin, and cannabinoids; however, these treatments exhibit
limited efficacy [
19
,
20
]. Indeed, to reduce dysgeusia and improve patient health and quality
of life, novel strategies are needed [21,22].
The oral microbiota includes protozoans, fungi, yeast, bacteria, archaea, viruses, and
phages [
23
,
24
] with bacteria being the most studied element [
25
]. Many factors affect indi-
vidual oral microbiota, including age, diet, and lifestyle habits (e.g., smoking and alcohol
consumption) [
26
,
27
]. Moreover, the oral microbiota plays a significant role in health,
especially in terms of the oral cavity. Indeed, this microbial community is correlated with
several oral pathologies, such as oral and other types of cancer [
24
]. The majority of studies
Cancers 2024,16, 3414 3 of 24
showing an association between derangement of the oral microbiota and oral diseases
induced by cancer therapies were performed in patients undergoing radiotherapy [
28
,
29
].
Hence, a reduction in diversity and richness seems to be associated with the development
of oral diseases [30].
Over the past decade, there has been a significant increase in research into the preven-
tion and treatment of oral diseases [
31
]. This includes the identification of bioactive food
components and the development of functional foods with health-promoting benefits [
32
].
Indeed, it is possible to increase patients’ quality of life with the supplementation of func-
tional foods. Consequently, concerning taste disorders, oncologic patients may switch from
traditional therapies to innovative alternatives that can have a positive outcome [33].
Miraculin is a glycoprotein that converts sour flavors into sweet ones and increases
enjoyment of meals [
34
,
35
]. This protein is present in Synsepalum dulcificum, which is a plant
native to West Africa that is commonly known as the “miracle berry”. The taste-modifying
effect of this miracle fruit is effective under acidic conditions and lasts for approximately
30–60 min [
36
]. The freeze-dried extract of the miracle berries’ pulp, rich in miraculin,
is called dried miracle berries (DMBs) and was approved by the European Commission
as a Novel Food in December 2021 [
37
]. DMBs are not only interesting because of the
taste-modifying effects but also because of their bioactive ingredients, including fiber and
phenolic compounds [38,39].
Only two small trials have reported the potential of this berry for improving dysgeusia
caused by chemotherapy [18,40]. Recently, the research group generated clinical evidence
on the efficacy of the DMB for the management of dysgeusia in a pilot randomized, par-
allel, triple-blind, and placebo-controlled clinical trial (the CLINMIR study) [
41
,
42
]. In
that study, we observed improvements in electrochemical food perception, energy and
nutrient intake, nutritional status, and quality of life in malnourished patients with cancer
receiving antineoplastic treatment [
41
]. Nevertheless, no assessment of the oral microbiome
and the relationship between microbial profile changes and the main outcome was con-
ducted. As a result, the objective of the present study was to evaluate the oral microbiome
of malnourished patients with cancer and dysgeusia following DMB consumption as a
medical–nutritional adjuvant therapy as well as its relationship with other variables.
2. Materials and Methods
2.1. Ethical Statement
Scientific Research and Ethics Committee approval was obtained in June 2022 from
the University Hospital La Paz (HULP, Code 6164). This study adheres to the Ethical
Standards of the Declaration of Helsinki concerning recommendations that guide physicians
conducting biomedical research on humans. All researchers should become familiar with
and follow the ICH Harmonized Tripartite Guidelines to follow good clinical practice [
43
].
Participants signed the informed consent form; researchers informed them of the study
characteristics and what participation in the trial entailed (verbally and in writing). We
followed several legal requirements when processing personal information, including the
Spanish Organic Law 3/2018 of 5 December and the General Data Protection Regulation of
the European Union (EU) 2016/679 of 27 April 2016.
2.2. Experimental Design and Participants
The CLINMIR study is a pilot randomized, parallel, triple-blind, and placebo-controlled
clinical trial. Using the number NCT05486260, the present protocol was registered at
http://clinicaltrials.gov, accessed on 14 March 2024. The oncology service and the clinical
nutrition unit at HULP in Madrid recruited 31 malnourished patients with cancer and
dysgeusia [42].
Patients over 18 years of age who were treated for cancer using chemotherapy, ra-
diotherapy, and/or immunotherapy and had lost 5% of their weight were defined as
malnourished according to GLIM criteria [
44
], and those who suffered dysgeusia, mea-
Cancers 2024,16, 3414 4 of 24
sured by electrogustometry, were included in the study. Additionally, these patients should
have a three-month life expectancy [41].
The study excluded participants who were involved in another clinical trial, received
enteral or parenteral nutrition or had poorly controlled diabetes mellitus (HbA1c > 8%),
hypertension or uncontrolled hyperthyroidism, severe digestive toxicity as a result of
chemotherapy and radiotherapy, or who were suffering from severe kidney or liver disease
(chronic renal failure, nephrotic syndrome, cirrhosis, etc.). Additionally, participants should
not suffer from severe dementia, brain metastases, eating disorders, a history of severe
neurological or psychiatric disorders that may interfere with treatment, alcoholism or
substance abuse, or severe gastrointestinal diseases.
Malnourished patients with cancer and dysgeusia who were receiving active treatment
were randomly assigned to one of three treatment arms. In a three-month study, each patient
was instructed to dissolve a miraculin-based food supplement tablet five minutes before
each main meal (breakfast, lunch, and dinner). Patients meeting the selection criteria were
randomly assigned to one of the three groups in the clinical trial. The first group received a
standard dose of DMB (150 mg DMB, equivalent to 2.8 mg of miraculin + 150 mg freeze-
dried strawberry per orodispersible tablet). The second group had a higher dose of DMB
(300 mg DMB, equivalent to 5.6 mg of miraculin). Finally, the third group took a placebo
dose (300 mg of freeze-dried strawberry). All three treatments were isocaloric (Table S1).
The clinical trial consisted of two phases. There were six face-to-face meetings in each. The
selection phase had one selection visit, whereas the experimental phase had five visits.
All participants were undergoing active treatment with at least chemotherapy, and taste
alterations were measured by electrogustometry and taste strip tests [
42
]. To complete the
three-month intervention period, the subjects received as many tablets as necessary during
scheduled visits to the HULP. Participants were asked to return all packaging regardless of
whether it was empty or partially consumed in order to assess compliance by comparing
the number of tablets provided and returned. DMB was administered as an adjuvant
medical–nutritional treatment [41,42,45].
2.3. Biological Samples and DNA Sequencing
A three-month trial was conducted. Saliva samples from each intervention group
(standard dose, high dose, and placebo), were analyzed for the oral microbiome. We
collected saliva samples at baseline (before supplementation with DMB), 1 month after
treatment with DMB, and 3 months after intervention with DMB. These samples were
placed in OMNIgene Oral OM-501 tubes (DNA Genotek Inc., Ottawa, ON, Canada).
2.3.1. Saliva DNA Extraction
DNA was extracted from saliva samples using a QIAamp DNA Microbiome Kit (Ref.
ID: 51704, Qiagen Inc., Hilden, Germany) according to the manufacturer’s instructions.
DNA purity and integrity were assessed using spectrophotometry (NanoDrop, Thermo
Fisher Scientific, Massachusetts, MA, USA).
2.3.2. Whole 16S rRNA Gene Sequencing and Taxonomic Assignment
Following the instructions of the 16S Barcoding kit ref SQK-16S024 (Oxford Nanopore
Technologies, Oxford, UK), the 16S rRNA gene was PCR-amplified using redesigned 16S
primers (27F and 1492R) with 5
′
tags that facilitate the ligase-free attachment of Rapid
Sequencing Adapters. A 0.2 mL PCR tube was filled with RNA-free water, 14
µ
L; 10 ng
of input DNA, 10
µ
L; 16S barcodes at 10 ng/mL, 1
µ
L; and LongAmp Taq 2X Master mix,
25
µ
L, for a total volume of 50
µ
L per sample. The following conditions were used for PCR:
denaturation at 95
◦
C for 1 min, 25 cycles of denaturation at 95
◦
C for 20 s, banding at 55
◦
C
for 30 s, and extension at 65
◦
C for 2 min, which was followed by a final extension at 65
◦
C
for 5 min.
A new 1.5 mL Eppendorf DNA LoBind tube was used to transfer the PCR product.
By vortexing 30
µ
L of AMPure XP beads and mixing by pipetting, PCR products from
Cancers 2024,16, 3414 5 of 24
each sample were resuspended in AMPure XP beads (Beckman Coulter, ThermoScientific,
Barcelona, Spain) and cleaned in 10
µ
L of 10 mM Tris-HCl pH 8.0 with 50 mM NaCl. Finally,
all barcoded libraries from each sample were combined in the appropriate ratios to obtain
a total concentration of 50–100 fmoles. The 16S amplicon of 1500 bp corresponds to those
50–100 fmoles. In the final step, 1
µ
L of rapid adapter tube was added to the previously
mixed barcoded DNA with which each sample was identified. The mixture should be
mixed gently by shaking the tube and centrifuged. A final volume of 11
µ
L is obtained by
incubating the reaction for 5 min at room temperature.
A fresh tube of the library was prepared for loading into SpotON Flow Cell Mk R9
Version (ref FLO-MIN106D, Oxford Nanopore Technologies, Oxford, UK) using the Minion
M1kc and M1kb sequencers (Oxford Nanopore Technologies, Oxford, UK). A total of 75
µ
L
was used for the following components: sequencing buffer (SQB) 34
µ
L, loading beads (LB),
mixed immediately before use 25.5
µ
L, RNA-free water 4.5
µ
L, and a previously prepared
DNA library incubated at room temperature, 11 µL.
Once the raw data were generated, the base calling was performed with Guppy version
6.5.7 (Oxford Nanopore Technologies, Oxford, UK), and the resulting sequences were iden-
tified using Kraken2 (with Refseq Archaea, bacteria, viral, plasmid, human, UniVec_Core,
protozoa, fungi & plant database) and further analyzed using QIIME (2-2020.8) [
46
]. The
taxonomy was assigned to ASVs using the sklearn naïve Bayes taxonomy classifier (via
q2-feature-classifier) [
47
] against SILVA 16S V3-V4 v132_99 [
48
] with a similarity threshold
of 99%. The data filtering process excluded samples with fewer than 10,000 reads. There
were two samples that were excluded from the analysis because of a low number of counts.
The phylum, family, genus, and species levels were used for the interpretation of the
results. Using the vegan library [
49
], the Shannon and Simpson’s indices were used to
examine the diversity of the samples, and the Chao1 index was used to estimate species
richness. The beta-diversity measure (Bray–Curtis dissimilarity distance) was calculated
using the vegan R package (version 2.6.4) [
49
]. When testing differences in beta diversity,
we used the ADONIS-2 function from the vegan package using permutations for calculating
p-values [49].
2.4. Plasma Cytokines
Tumor necrosis factor-alpha (TNF-
α
) and human proteolysis-inducing factor/dermcidin
(PIF) were determined and analyzed as previously described [
41
,
42
,
45
]. To avoid more
punctures and hospital visits than necessary, blood samples were collected by trained
personnel at the HULP Extraction Unit in the morning (approximately 8:00 am) during
blood tests before chemotherapy. Briefly, blood samples were collected in vacuum tubes,
labeled, transported, and centrifuged for 10 min at 1500
×
g. Aliquots of blood samples
were prepared and labeled according to a numerical code and stored at
−
80
◦
C [
41
],
and they were collected at baseline (before supplementation with DMB) and 3 months
after intervention with DMB. The X-MAP Luminex multiplex enzyme immunoassay plat-
form (HSTCMAG-28SK-06, EMD Millipore Corporation, Michigan, MI, USA) was used to
analyze TNF-alpha using specific antibodies as previously described [
50
]. The PIF was de-
termined by enzyme-linked immunosorbent assay (ELISA) according to the manufacturer’s
instructions (CSB-E13626h, Cusabio, Wuhan, China).
2.5. Electrical Taste Perception
Electrogustometry was used to evaluate taste perception. To quantify objectively the
human taste, electrical taste testing is an excellent method [
51
]. According to functional
imaging studies, lingual electrical stimulation activates the same brain regions as chemical
stimulation [
52
]. Patients who have cancer and taste distortion and who consume miraculin-
based food supplements are expected to improve their taste perception by reducing their
taste perception threshold (measured using decibel, dB) via electrical stimulation from
baseline to one and three months after the intervention with DMB, as measured by electrical
stimulation [
41
,
45
]. The threshold for an electric-induced taste stimulus was measured
Cancers 2024,16, 3414 6 of 24
using an electrogustometer (SI-03 Model, Sensonics International, Haddon Heights, NJ,
USA). The electric stimulus is applied with an electrode placed on the tongue. A first
stimulus (30 dB) is administered to familiarize the patient with the electrical stimulus.
Once the threshold is checked, the stimulation starts at the zero-stimulus amplitude and
increasingly progressively until the patient identifies the stimulus. To measure detection
thresholds, the two-down one-up forced-choice single staircase procedure and a stimulus-
response staircase was used [41,45].
2.6. Dietary Pattern Assessment
Food daily records were recorded for three days, one of which was a holiday (weekend
day, a day off, or a day out of the usual routine). In the absence of weight recording,
patients were advised to record household measurements (spoonful, cups, etc.) or to record
household weights. During the review of all records, a nutritionist ensured that all the
information collected was accurate and complete in the presence of the patient. With the
help of DIAL software version 1 (Alce Ingeniera, Madrid, Spain), the energy and nutrients
contained in foods, drinks, dietary supplements, and preparations were converted into
energy and nutrients. The 72 h food daily record of dietary intake allowed us to transform
food consumption into energy intake, water, macronutrient intake (proteins, fats (total
fat, saturated fatty acids, monounsaturated fatty acids, and polyunsaturated fatty acids)
as well as carbohydrates, fiber, and micronutrient intake (vitamins and minerals). Based
on this information, it was possible to calculate the caloric and lipid profiles as well as
the coverage of recommended intakes for the population. The data were analyzed using
dietary reference values established by the European Food Safety Authority [
53
] and the
Nutritional Objectives of the Consensus Document of the Spanish Community Nutrition
Society [41,54].
2.7. Mucositis
At baseline, participants were scheduled for appointments. Participants underwent
an oral examination with the use of mouth mirrors and a high-power headlamp at each
appointment (5 visits) by a previously calibrated investigator. Oral mucositis clinical
signs were recorded using the clinical component of the National Cancer Institute Com-
mon Terminology Criteria for Adverse Events version 3 (NCI-CTCAE v. 3) [
55
] and
the clinical component of the Oral Mucositis Assessment Scale during the course of the
intervention [56].
2.8. Statistical Analysis
A linear mixed model was used to evaluate the differences between placebo, DMB
150 mg, and DMB 300 mg, as well as the differences between visits: the effects of treatment,
time, and their interaction (time
×
treatment) were considered. The linear mixed model
was developed using the lme4 package [
57
] in the R program [
58
]. Further, general linear
mixed models (GLMs) of covariance (ANCOVA) were used to evaluate differences between
means for treatment, time, and treatment
×
time using baseline data as covariates (SPSS
Inc., Chicago, IL, USA). Post hoc analyses were determined using the Bonferroni test.
Compared to other programs, the lme4 package version 1.1-35.5 may be faster and more
memory-efficient because it employs modern, efficient linear algebra methods, such as
those in the Eigen package, and reference classes to prevent undue copying of large objects.
Moreover, the software version 1.1-35.5 provides the ability to construct generalized linear
mixed models, which maximizes the amount of information available when loss patients
are included in some of the analyzed conditions [57].
This study examined the relationships between oral microbiome variables, inflamma-
tory parameters, dietary variables, and electrical taste perception outcomes using Pearson’s
correlations. R Studio’s corrplot function [
59
] was used to express associations by correcting
multiple tests with the false discovery rate (FDR) procedure [
60
]. The graphs show only
significant and corrected associations. In the graphs, red and blue lines indicate the correla-
Cancers 2024,16, 3414 7 of 24
tion values, with negative correlations highlighted in red (
−
1) and positive correlations
highlighted in blue (+1). In this study, we examined only a subset of dietary variables
(energy intake (%), lipids (%), saturated fatty acids (%), and monounsaturated fatty acids
(%)) that were significantly correlated; a complete list of the dietary variables is available in
our previous study [41].
Based on a Rivera–Pinto analysis, it is possible to identify microbial signatures, i.e.,
groups of microbes that can predict particular phenotypes of interest [
61
]. These micro-
bial signatures correspond to an individual’s unique microbiome and may be used to
diagnose, prognosticate, or predict therapeutic responses. For the purpose of identifying
microbial signatures, we can model the response variables (all variables derived from the
oral microbiome) and select those that provide the highest accuracy in classification or
prediction. As part of the Rivera–Pinto method and the Selbal algorithm, we evaluated
specific signatures at the phylum and genus levels to select a sparse model that adequately
explains the response variable. The microbial signatures were calculated using geometric
means based on data collected from two groups of taxa. The name implies that these groups
are those with relative abundances, or balances, that are related to the response variable of
interest [61].
Finally, it was examined whether the presence or appearance of mucositis could be
independently correlated with the response to the DMB treatment, the levels of cytokine,
taste perception, dietary parameters, and the presence of selected species. Additionally,
we examined clinical outcomes to determine whether they could be independently corre-
lated with the presence of specific bacterial species. Our study evaluated the presence or
absence of immunotherapeutic agents (including atezolizumad, becacizumab, paclitaxel,
pembrolizumab, nivolumab, panitumumab, folfirinox, among others), general toxicity
(including neutropenia, diarrhea, thrombocytopenia, among others), digestive toxicity,
tobacco use and alcohol consumption. To achieve this, we used the SPSS statistical package
version 29 (SPSS Inc., Chicago, IL, USA) to perform a binary logistic regression with the
Wald regression backward option and a significance level of p< 0.05.
3. Results
Patients were recruited from November 2022 to May 2023, and 62 were assessed for
eligibility. Thirty-one patients with cancer and dysgeusia were included in the study for
meeting the selection criteria and were randomly assigned to one of three intervention
groups, which were adjusted according to the type of cancer. The standard-dose DMB and
placebo groups consisted of ten patients each, whereas the high-dose DMB group consisted
of eleven patients. During the follow-up period, which extended from November 2022 to
August 2023, ten participants dropped out of the study. The majority of these drop-outs
were due to the taste distortion of non-sweet acidic foods (n = 6) and the difficulty that the
prescription derived from the intervention added to their already complex antineoplastic
treatment (n = 2). Furthermore, two placebo patients died. Finally, a total of 21 oncological
patients completed the clinical trial. There were eight patients in the DMB standard-dose
group, six in the placebo group, and seven in the high-dose group who completed the study.
All variables were evaluated following the intention-to-treat principle [
42
]. The sample
comprised 58.1% women and 41.9% men with a mean age of 60.0
±
10.9 years. Baseline
data for the population have been published previously elsewhere [41].
3.1. Beta Diversity
We compared saliva samples from each intervention group (standard dose, high
dose, and placebo) at baseline (before supplementation with DMB), one month after DMB
treatment, and three months after treatment with DMB. Treatment and time did not produce
distinct microbial community structures (Bray–Curtis distance, R
2
= 0.18, p= 0.890 for
treatment (Figure 1A) and R2= 0.15, p= 0.920 for time (Figure 1B)).
Cancers 2024,16, 3414 8 of 24
Cancers 2024, 16, x FOR PEER REVIEW 8 of 22
of 21 oncological patients completed the clinical trial. There were eight patients in the
DMB standard-dose group, six in the placebo group, and seven in the high-dose group
who completed the study. All variables were evaluated following the intention-to-treat
principle [42]. The sample comprised 58.1% women and 41.9% men with a mean age of
60.0 ± 10.9 years. Baseline data for the population have been published previously else-
where [41].
3.1. Beta Diversity
We compared saliva samples from each intervention group (standard dose, high
dose, and placebo) at baseline (before supplementation with DMB), one month after DMB
treatment, and three months after treatment with DMB. Treatment and time did not pro-
duce distinct microbial community structures (Bray–Curtis distance, R
2
= 0.18, p = 0.890
for treatment (Figure 1A) and R
2
= 0.15, p = 0.920 for time (Figure 1B)).
Figure 1. Plots of beta diversity metrics based on principal coordinate analysis. The R
2
and p-values
are from the Adonis function measured using the vegan package. (A) Treatment, the black points
and line correspond to standard-dose DMB, the red points and line correspond to high-dose DMB,
and the green points and line correspond to placebo. (B) Time, the black points and line correspond
to baseline, the red points and line correspond to 1 month, and the green points and line correspond
to 3 months.
3.2. Phylum and Family Levels
In all groups, the relative abundances at the phylum level were similar at baseline,
after one month, and after three months. Bacillota accounted for more than 98% of the
relative abundance of the oral microbiome in our study. As for the other main phyla, Ac-
tinobacteriota, Fusobacteria, Bacteroidota, Pseudomonadota, and Saccharibacteria, there were no
significant changes or trends among the groups (Table S2). According to Shannon and
Simpson indices, related to bacterial diversity, there was no significant difference between
the groups. Additionally, there were no differences among the groups in terms of the
Chao1 index, which is related to bacterial species richness. The patients with cancer and
dysgeusia showed dysbiosis in terms of diversity and richness compared with healthy
individuals [62]. At the family level, we did not observe significant changes in the oral
microbiome of patients with cancer either during treatment or time (Table S3).
3.3. Genus Level
At the genus level, Streptococcus was the most common in all studied groups (more
than 63%). Overall, significant differences in the interaction between treatment and time
were observed for Enterococcus (p = 0.044) and Veillonella (p = 0.015). Based on a post hoc
analysis and Bonferroni correction, Enterococcus abundance was higher in the standard-
dose DMB group than in the high-dose DMB and placebo groups at 3 months of interven-
tion (p = 0.044, Table 1). Veillonella genus relative abundance decreased significantly over
Figure 1. Plots of beta diversity metrics based on principal coordinate analysis. The R
2
and p-values
are from the Adonis function measured using the vegan package. (A) Treatment, the black points and
line correspond to standard-dose DMB, the red points and line correspond to high-dose DMB, and
the green points and line correspond to placebo. (B) Time, the black points and line correspond to
baseline, the red points and line correspond to 1 month, and the green points and line correspond to
3 months.
3.2. Phylum and Family Levels
In all groups, the relative abundances at the phylum level were similar at baseline,
after one month, and after three months. Bacillota accounted for more than 98% of the
relative abundance of the oral microbiome in our study. As for the other main phyla,
Actinobacteriota,Fusobacteria,Bacteroidota,Pseudomonadota, and Saccharibacteria, there were
no significant changes or trends among the groups (Table S2). According to Shannon and
Simpson indices, related to bacterial diversity, there was no significant difference between
the groups. Additionally, there were no differences among the groups in terms of the
Chao1 index, which is related to bacterial species richness. The patients with cancer and
dysgeusia showed dysbiosis in terms of diversity and richness compared with healthy
individuals [
62
]. At the family level, we did not observe significant changes in the oral
microbiome of patients with cancer either during treatment or time (Table S3).
3.3. Genus Level
At the genus level, Streptococcus was the most common in all studied groups (more
than 63%). Overall, significant differences in the interaction between treatment and time
were observed for Enterococcus (p= 0.044) and Veillonella (p= 0.015). Based on a post hoc
analysis and Bonferroni correction, Enterococcus abundance was higher in the standard-dose
DMB group than in the high-dose DMB and placebo groups at 3 months of intervention
(p= 0.044, Table 1). Veillonella genus relative abundance decreased significantly over the
treatment period in the standard-dose DMB group compared to the high-dose DMB and
placebo groups (Table 1). In addition, we observed a trend of increase for Granulicatella
(p= 0.066), Bacillus (p= 0.061), and Staphylococcus (p= 0.053) in DMB groups (Table 1). The
remaining genera did not show any significant changes in either the treatment or time.
3.4. Species Level
Three species dominated the oral microbiome of patients with cancer, Streptococcus
pneumoniae,Streptococcus thermophilus and Veillonella parvula. We observed significant differ-
ences in the interaction between treatment and time for Granulicatella elegans, Streptococcus
mutans,Streptococcus parasanguinis and Veillonella parvula as well as a trend for Gemella
morbillorum (p= 0.054), Granulicatella adiacens (p= 0.069), Streptococcus australis (p= 0.063),
and Streptococcus cristatus (p= 0.087) (Table 2).
Cancers 2024,16, 3414 9 of 24
Table 1. Relative abundances at the genus levels of oral bacteria in malnourished patients with cancer and dysgeusia who received the standard dose of DMB
(150 mg/tablet), the high dose of DMB (300 mg/tablet), or the placebo for 3 months.
Standard-Dose DMB (150 mg)
(n= 8) High-Dose DMB (300 mg) (n= 6) Placebo (n= 7) p-Value
Genus Baseline 1 Month 3 Months Baseline 1 Month 3 Months Baseline 1 Month 3 Months
Treatment (T)
Time (t) T ×t
Actinomyces 0.1
(0.02–0.3)
0.2
(0.03–0.3)
0.08
(0.02–0.3)
0.09
(0.04–0.2)
0.08
(0.04–0.2)
0.07
(0.04–0.1)
0.1
(0.07–0.6)
0.1
(0.04–0.7)
0.1
(0.05–0.6) 0.238 0.308 0.846
Aminipila 0.1
(0.01–0.5)
0.1
(0.02–0.8)
0.2
(0.03–0.5)
0.1
(0.06–0.4)
0.1
(0.03–0.3)
0.08
(0.07–0.2)
0.2
(0.006–1.6)
0.5
(0.2–2.8)
0.2
(0.1–4.7) 0.138 0.229 0.237
Atopobium 0.4
(0.1–0.7)
0.4
(0.1–0.7)
0.6
(0.1–1.1)
0.06
(0.02–0.1)
0.3
(0.3–0.3)
0.1
(0.07–0.1)
0.01
(0.01–0.01)
0.02
(0.02–0.02)
0.03
(0.03–0.03) 0.319 0.913 0.962
Bacillus 0.68
(0.3–1.6)
0.5
(0.4–1.1)
0.9
(0.5–1.2)
0.3
(0.1–0.9)
0.3
(0.2–0.5)
0.4
(0.2–2.5)
0.4
(0.3–1.1)
0.6
(0.4–0.8)
0.4
(0.3–0.4) 0.179 0.26 0.061
Bulleidia 0.1
(0.06–0.4)
0.1
(0.04–0.3)
0.07
(0.02–0.2)
0.06
(0.02–0.5)
0.07
(0.03–0.2)
0.1
(0.01–0.2)
0.08
(0.02–0.5)
0.2
(0.1–0.5)
0.1
(0.02–0.3) 0.328 0.752 0.74
Clostridioides 0.4
(0.02–1.0)
0.5
(0.01–3.1)
0.8
(0.02–2.9)
0.4
(0.01–4.8)
1.2
(0.7–1.9)
0.4
(0.06–0.7)
1.3
(0.1–2.9)
2.3
(0.1–6.4)
1.2
(0.1–4.4) 0.076 0.37 0.388
Enterococcus 0.5
(0.2–1.4)
0.4
(0.3–0.8)
0.5 a
(0.4–0.9)
0.2
(0.03–0.7)
0.1
(0.04–0.4)
0.3 b
(0.08–2.4)
0.3
(0.1–0.8)
0.5
(0.2–0.5)
0.3 b
(0.1–0.3) 0.251 0.234 0.044
Gemella 4.8
(2.1–13.3)
5.9
(1.0–17.5)
8.6
(1.6–15.0)
6.3
(0.5–11.7)
3.7
(1.3–6.7)
3.4
(0.6–11.6)
4.4
(1.9–12.5)
6.0
(4.1–13.0)
8.6
(4.6–14.2) 0.605 0.512 0.309
Granulicatella 4.8
(1.6–14.7)
3.2
(2.2–8.0)
4.8
(1.4–9.2)
1.6
(0.09–7.4)
1.6
(0.3–4.8)
4.0
(0.8–23.4)
3.0
(1.4–8.8)
4.7
(1.3–7.4)
2.7
(1.3–3.1) 0.411 0.468 0.066
Herbinix 0.4
(0.1–1.0)
0.2
(0.07–1.6)
1.0
(0.3–1.3)
0.2
(0.01–0.9)
0.4
(0.3–1.9)
0.2
(0.03–0.5)
0.9
(0.07–1.7)
0.3
(0.09–4.2)
0.9
(0.1–2.5) 0.246 0.436 0.575
Lachnoanaerobaculum 1.3
(0.06–4.0)
1.4
(0.2–3.8)
0.9
(0.1–8.9)
0.1
(0.04–3.9)
0.9
(0.1–1.7)
0.5
(0.03–5.4)
1.1
(0.5–2.5)
2.0
(0.2–5.1)
1.3
(0.2–4.6) 0.464 0.632 0.835
Lachnoclostridium 0.5
(0.3–0.5)
0.4
(0.2–1.7)
1.2
(0.1–3.2)
0.6
(0.008–1.0)
0.5
(0.03–1.8)
0.3
(0.01–0.7)
0.3
(0.2–0.5)
0.5
(0.1–2.3)
0.4
(0.2–1.0) 0.376 0.304 0.172
Listeria 0.4
(0.1–1.1)
0.3
(0.2–0.6)
0.5
(0.3–0.8)
0.1
(0.01–0.7)
0.2
(0.06–0.3)
0.5
(0.5–0.5)
0.2
(0.08–0.7)
0.3
(0.1–0.4)
0.2
(0.07–0.2) 0.159 0.242 0.103
Mediterraneibacter 0.9
(0.2–2.1)
1.1
(0.3–2.5)
1.1
(0.2–9.7)
0.6
(0.02–4.2)
1.0
(0.2–1.7)
0.9
(0.09–6.0)
0.9
(0.5–3.4)
1.5
(0.7–2.7)
1.6
(0.3–2.7) 0.783 0.213 0.706
Megasphaera 0.3
(0.02–1.9)
0.2
(0.03–2.7)
0.1
(0.03–2.0)
0.4
(0.05–2.1)
0.8
(0.3–2.2)
1.0
(0.2–4.5)
0.6
(0.3–3.9)
0.5
(0.07–1.5)
0.3
(0.1–1.3) 0.709 0.724 0.129
Mogibacterium 0.4
(0.05–1.1)
0.3
(0.06–1.8)
0.5
(0.07–6.3)
0.3
(0.04–0.7)
0.3
(0.08–0.7)
0.2
(0.05–0.4)
1.0
(0.2–1.9)
0.4
(0.06–2.6)
0.6
(0.03–3.0) 0.405 0.7 0.705
Cancers 2024,16, 3414 10 of 24
Table 1. Cont.
Standard-Dose DMB (150 mg)
(n= 8) High-Dose DMB (300 mg) (n= 6) Placebo (n= 7) p-Value
Genus Baseline 1 Month 3 Months Baseline 1 Month 3 Months Baseline 1 Month 3 Months
Treatment (T)
Time (t) T ×t
Novisyntrophococcus 0.1
(0.01–0.4)
1.2
(0.02–1.9)
1.8
(0.07–4.0)
3.2
(0.01–6.3)
1.1
(0.01–2.2)
5.4
(5.4–5.4)
0.6
(0.04–2.3)
2.8
(0.3–5.5)
0.6
(0.06–4.4) 0.317 0.366 0.249
Parvimonas 0.4
(0.04–2.8)
0.3
(0.06–3.4)
1.4
(0.02–5.2)
1.4
(0.3–2.0)
0.8
(0.3–2.5)
0.7
(0.2–1.6)
0.2
(0.01–6.1)
0.2
(0.003–6.9)
1.5
(0.05–17.7) 0.406 0.427 0.581
Romboutsia 0.2
(0.07–0.6)
0.09
(0.05–0.9)
0.5
(0.2–0.8)
0.3
(0.09–0.6)
0.3
(0.2–1.0)
0.2
(0.02–0.3)
0.4
(0.03–1.0)
0.1
(0.04–2.8)
0.5
(0.05–1.6) 0.385 0.536 0.557
Rothia 0.2
(0.02–0.3)
0.06
(0.01–0.2)
0.08
(0.03–0.3)
0.06
(0.02–0.5)
0.05
(0.02–0.1)
0.04
(0.009–0.1)
0.08
(0.01–0.3)
0.2
(0.01–0.3)
0.07
(0.01–0.7) 0.627 0.661 0.147
Schaalia 0.1
(0.07–0.8)
0.1
(0.02–0.9)
0.3
(0.2–0.4)
0.1
(0.02–0.4)
0.1
(0.03–0.3)
0.2
(0.07–0.2)
0.2
(0.08–1.1)
0.2
(0.07–0.5)
0.1
(0.05–0.2) 0.553 0.211 0.52
Staphylococcus 0.2
(0.1–0.5)
0.2
(0.1–0.4)
0.3
(0.3–0.3)
0.1
(0.03–0.5)
0.1
(0.07–0.3)
0.6
(0.6–0.6)
0.2
(0.07–0.3)
0.3
(0.2–1.6)
0.1
(0.1–0.3) 0.693 0.478 0.053
Streptococcus 69.5
(61.3–71.2)
64.4
(56.6–75.3)
68.7
(37.2–77.3)
72.0
(53.1–94.0)
76.3
(60.0–84.6)
69.0
(53.3–84.9)
65.0
(49.7–85.3)
63.0
(33.7–76.9)
68.0
(41.3–72.6) 0.236 0.525 0.789
Veillonella 9.3
(3.3–19.6)
6.6
(3.5–24.8)
2.4 a
(0.06–5.5)
4.3
(1.4–5.6)
7.9
(3.8–23.7)
6.6 b
(2.7–10.6)
10.5
(3.1–20.1)
5.4
(2.3–13.3)
5.6 b
(4.1–8.0) 0.956 0.052 0.015
Shannon index 1.4
(1.2–1.5)
1.5
(1.1–2.0)
1.4
(1.1–2.6)
1.2
(0.4–2.1)
0.8
(0.6–1.7)
1.3
(0.8–1.7)
1.5
(0.8–1.9)
1.6
(1.1–2.6)
1.4
(1.1–2.2) 0.516 0.373 0.591
Simpson’s index 0.5
(0.5–0.6)
0.6
(0.4–0.7)
0.5
(0.4–0.8)
0.5
(0.1–0.7)
0.4
(0.3–0.6)
0.5
(0.3–0.7)
0.6
(0.3–0.7)
0.6
(0.4–0.9)
0.5
(0.5–0.8) 0.673 0.428 0.714
Chao1 index 41.0
(22.8–60.0)
39.9
(32.0–57.2)
38.0
(24.3–64.0)
37.5
(21.0–47.0)
32.4
(4.0–79.0)
38.6
(30.2–52.0)
36.2
(22.0–49.0)
39.6
(24.8–66.0)
41.5
(23.8–54.7) 0.575 0.411 0.405
Values are presented as median and range. Different letters mean significant differences (p< 0.05) and were calculated following a general linear model of covariance followed by the
Bonferroni correction for multiple tests.
Cancers 2024,16, 3414 11 of 24
Table 2. Relative abundances of species for oral bacteria in malnourished patients with cancer and dysgeusia who received the standard dose of DMB (150 mg), the
high dose of DMB (300 mg), or the placebo for 3 months.
Standard-Dose DMB (150 mg)
(n= 8) High-Dose DMB (300 mg) (n= 6) Placebo (n= 7) p-Value
Species Baseline 1 Month 3 Months Baseline 1 Month 3 Months Baseline 1 Month 3 Months
Treatment (T)
Time (t) T ×t
Gemella
haemolysans
0.3
(0.06–1.4)
0.2
(0.03–0.6)
0.3
(0.07–1.2)
0.6
(0.03–7.6)
0.5
(0.2–0.7)
0.5
(0.03–2.7)
0.7
(0.1–6.1)
0.7
(0.1–2.2)
1.8
(0.3–6.7) 0.105 0.297 0.517
Gemella
morbillorum
0.1
(0.06–0.9)
0.2
(0.07–0.6)
0.3
(0.07–1.2)
0.4
(0.04–2.2)
0.4
(0.03–1.7)
0.08
(0.06–0.5)
0.3
(0.03–3.9)
0.6
(0.08–9.4)
2.5
(0.2–7.2) 0.103 0.17 0.054
Gemella
sanguinis
3.7
(1.4–12.8)
5.3
(0.6–16.8)
7.5
(1.3–15.1)
1.0
(0.009–8.0)
1.9
(0.1–6.0)
1.1
(0.06–9.7)
2.2
(1.2–6.1)
3.2
(1.8–6.2)
4.0
(0.4–7.0) 0.312 0.352 0.769
Gemella
sp. zg-570
0.06
(0.01–0.5)
0.06
(0.02–0.2)
0.1
(0.04–0.3)
0.3
(0.04–1.8)
0.3
(0.2–0.4)
0.4
(0.01–0.6)
0.2
(0.04–1.3)
0.4
(0.06–0.5)
0.4
(0.06–0.8) 0.102 0.3 0.584
Granulicatella
adiacens
4.8
(1.6–14.7)
3.7
(2.2–8.0)
4.8
(1.4–9.2)
1.4
(0.09–7.4)
1.6
(0.3–4.1)
4.0
(0.8–23.6)
3.0
(1.4–8.8)
4.7
(1.3–7.5)
2.6
(1.3–3.1) 0.396 0.484 0.069
Granulicatella
elegans
0.01
(0.004–0.1)
0.02
(0.01–0.1)
0.03 a
(0.01–0.07)
0.02
(0.009–0.5)
0.6
(0.6–0.6)
0.01 b
(0.006–
0.02)
0.03
(0.01–0.2)
0.01
(0.01–0.3)
0.02 b
(0.005–
0.05)
<0.001 <0.001 <0.001
Streptococcus
agalactiae
10.5
(5.1–15.4)
10.0
(5.6–14.2)
9.8
(6.0–13.9)
10.9
(5.5–14.1)
7.8
(6.6–11.9)
8.0
(5.9–11.4)
9.2
(7.3–12.6)
8.7
(6.2–14.2)
7.9
(7.3–16.3) 0.878 0.385 0.586
Streptococcus
australis
0.1
(0.01–0.7)
0.07
(0.02–0.2)
0.06
(0.006–0.2)
0.03
(0.02–0.03)
0.03
(0.03–0.03)
0.06
(0.06–0.06)
0.01
(0.01–0.07)
0
(0–0)
0.6
(0.6–0.6) 0.218 0.301 0.063
Streptococcus
cristatus
0.4
(0.04–1.6)
0.3
(0.06–1.5)
0.1
(0.03–3.0)
0.4
(0.1–4.0)
1.2
(0.1–1.5)
0.2
(0.04–0.7)
0.7
(0.06–3.4)
0.4
(0.06–0.7)
0.3
(0.05–2.2) 0.733 0.149 0.087
Streptococcus
dysgalactiae
5.0
(3.3–6.3)
4.8
(2.9–7.5)
4.2
(2.5–5.8)
4.5
(3.3–5.6)
3.8
(3.3–6.0)
3.6
(2.7–5.3)
3.9
(2.8–6.2)
3.6
(3.1–5.5)
3.9
(3.1–6.3) 0.583 0.261 0.666
Streptococcus
infantis
1.0
(0.7–2.4)
1.0
(0.6–2.8)
0.9
(0.4–2.3)
0.9
(0.5–1.2)
0.7
(0.5–1.3)
0.7
(0.6–1.0)
0.9
(0.7–1.6)
0.9
(0.6–1.7)
1.1
(0.7–1.2) 0.321 0.844 0.307
Streptococcus
mutans
0.3
(0.2–2.9)
0.3
(0.2–3.5)
0.4 a
(0.2–3.4)
1.9
(0.3–2.7)
2.2
(0.4–7.2)
0.6 b
(0.3–1.8)
0.4
(0.2–1.2)
0.3
(0.2–0.3)
0.6 b
(0.2–0.9) 0.022 0.125 0.012
Streptococcus
parasanguinis
1.2
(0.09–3.9)
1.2
(0.5–1.6)
0.8 a
(0.2–2.2)
0.3
(0.09–1.4)
0.6
(0.09–1.8)
1.5 b
(0.1–2.5)
0.5
(0.2–1.3)
0.8
(0.09–3.6)
0.5 c
(0.1–2.3) 0.78 0.746 0.018
Cancers 2024,16, 3414 12 of 24
Table 2. Cont.
Standard-Dose DMB (150 mg)
(n= 8) High-Dose DMB (300 mg) (n= 6) Placebo (n= 7) p-Value
Species Baseline 1 Month 3 Months Baseline 1 Month 3 Months Baseline 1 Month 3 Months
Treatment (T)
Time (t) T ×t
Streptococcus pneumoniae 13.5
(5.5–17.3)
13.1
(6.1–24.2)
11.3
(6.8–20.3)
12.2
(4.8–17.4)
9.6
(5.3–15.5)
8.9
(5.2–14.5)
10.4
(6.8–15.5)
9.5
(6.8–14.0)
10.7
(6.8–21.5) 0.577 0.734 0.429
Streptococcus pyogenes 2.9
(2.5–3.4)
2.8
(2.1–3.3)
2.8
(1.4–3.1)
2.8
(2.0–4.4)
2.6
(2.1–3.6)
2.5
(2.1–3.6)
2.4
(2.0–3.5)
2.6
(1.6–3.7)
2.6
(2.3–3.4) 0.948 0.363 0.727
Streptococcus salivarius 2.9
(1.3–22.1)
2.6
(1.4–11.7)
2.4
(1.0–22.8)
3.1
(1.6–35.2)
4.2
(2.0–34.8)
12.6
(1.3–23.5)
3.8
(1.0–26.5)
6.3
(1.4–12.4)
10.0
(1.7–10.6) 0.57 0.758 0.713
Streptococcus
sp. HSISS1
5.9
(1.0–12.6)
7.1
(0.1–12.7)
4.3
(0.5–11.5)
4.6
(0.4–12.8)
4.3
(1.3–6.5)
3.8
(1.8–9.7)
5.0
(2.1–10.0)
4.5
(0.3–9.4)
3.5
(1.5–8.8) 0.809 0.814 0.681
Streptococcus
sp. LPB0220
1.8
(0.6–10.7)
3.3
(0.9–6.8)
1.3
(0.5–9.8)
3.5
(0.5–13.0)
5.9
(1.4–10.8)
8.0
(2.7–11.1)
5.9
(0.3–12.4)
0.8
(0.1–11.3)
1.6
(0.08–7.2) 0.446 0.802 0.308
Streptococcus
suis
3.4
(2.0–6.3)
3.5
(1.9–4.8)
2.9
(1.5–4.9)
3.5
(1.6–8.4)
3.6
(2.0–7.6)
4.1
(1.3–6.2)
2.6
(1.4–7.0)
3.5
(1.1–4.9)
3.2
(1.6–4.5) 0.635 0.885 0.927
Streptococcus thermophilus 8.9
(7.7–10.1)
8.5
(7.3–10.3)
8.6
(3.9–9.5)
9.6
(6.4–16.7)
9.5
(6.9–16.8)
9.2
(6.4–13.5)
7.4
(6.4–12.9)
8.3
(4.4–10.1)
8.6
(5.6–10.2) 0.401 0.329 0.243
Lachnoanaerobaculum
umeaense
1.4
(0.06–4.0)
1.4
(0.2–3.8)
0.9
(0.1–9.0)
0.1
(0.05–3.9)
0.9
(0.1–1.7)
0.5
(0.03–5.4)
1.1
(0.5–2.5)
2.0
(0.2–5.2)
1.6
(0.2–4.6) 0.458 0.62 0.868
Veillonella
atypica
1.5
(0.01–10.2)
1.6
(0.02–13.7)
0.3
(0.03–3.0)
0.5
(0.07–3.3)
0.6
(0.6–6.2)
2.5
(1.0–4.0)
4.1
(0.3–10.7)
1.4
(0.1–8.4)
2.8
(1.0–4.3) 0.437 0.64 0.129
Veillonella
nakazawae
0.7
(0.1–1.0)
0.5
(0.1–1.7)
0.3
(0.2–0.3)
0.1
(0.1–0.3)
0.3
(0.2–0.5)
0.3
(0.1–0.4)
0.1
(0.04–0.6)
0.4
(0.4–0.4)
0.05
(0.05–0.08) 0.158 0.683 0.946
Veillonella
parvula
6.9
(2.8–9.6)
4.8
(2.9–15.8)
2.1 a
(0.03–4.9)
3.4
(1.3–3.9)
5.1
(3.1–7.1)
4.7 b
(0.5–7.9)
4.6
(1.3–9.6)
3.6
(0.5–8.9)
2.9 b
(1.8–5.2) 0.608 0.053 0.043
Shannon index 3.1
(2.8–3.3)
3.1
(2.7–3.5)
3.0
(2.9–3.6)
3.1
(2.6–3.5)
3.1
(2.6–3.4)
3.0
(2.9–3.2)
3.2
(2.7–3.5)
3.2
(2.9–3.7)
3.3
(2.8–3.4) 0.473 0.851 0.948
Simpson’s index 0.9
(0.9–0.9)
0.9
(0.9–1.0)
0.9
(0.9–1.0)
0.9
(0.8–0.9)
0.9
(0.8–0.9)
0.9
(0.9–0.9)
0.9
(0.9–0.9)
0.9
(0.9–1.0)
0.9
(0.9–0.9) 0.584 0.998 0.895
Chao1 index 48.0
(21.0–89.0)
40.1
(21.9–80.0)
42.6
(26.6–65.7)
39.2
(27.2–51.8)
46.5
(26.0–69.3)
33.1
(24.1–52.3)
37.0
(26.6–55.7)
36.7
(30.0–59.0)
36.3
(26.5–59.0) 0.339 0.339 0.588
Values are presented as median and range. Different letters mean significant differences (p< 0.05) and were calculated following a general linear model of covariance followed by the
Bonferroni correction for multiple tests.
Cancers 2024,16, 3414 13 of 24
Granulicatella elegans exhibited the greatest variation (p< 0.01). Patients with cancer
receiving a standard dose of DMB were found to have a greater presence of that bacte-
ria in their oral microbiome compared with patients receiving a high dose of DMB and
placebo. There were substantial changes in two species of Streptococcus,Streptococcus mutans
(p= 0.012) and Streptococcus parasanguinis (p= 0.018). For Streptococcus mutans, we did
not find statistical differences among groups at baseline; however, we observed higher
abundances in the standard-dose DMB group compared to both the high dose of DMB
and placebo groups at 3 months after intervention with DMB. The levels of Streptococcus
parasanguinis in the DMB groups exhibited an inverse pattern, with lower abundances in
the standard dose DMB group, whereas the abundances in the placebo group remained
unchanged. Within the DMB groups, Veillonella parvula exhibited opposite variations, with
significantly lower abundances in the standard dose DMB group compared with both the
high-dose DMB and the placebo groups (Table 2).
3.5. Microbiome Balance
The Rivera–Pinto method [
61
] was employed to ascertain the microbiome balance
at the end of the trial. The analysis revealed that the standard-dose DMB group was
characterized by lower balance scores for Streptococcus mutans and Bacillus when compared
to Gemella sp. zg-570 and Veillonella genera (Figure 2A). On the contrary, Gemella sp. zg-570
and Veillonella genera were more associated with the placebo group than with the standard-
dose DMB group (Figure 2A). Concerning the high-dose DMB group versus the placebo
group, Gemella sanguinis and Streptococcus lutetiensis were most associated with the placebo
group (Figure 2B). Thus, at the higher dose of DMB, lower balance scores were associated
with lower relative abundances of Streptococcus intermedius and Streptococcus agalactiae when
compared to Gemella sanguinis and Streptococcus lutetiensis (Figure 2B).
3.6. Analysis of the Relationships between Oral Microbiome, Inflammatory Cytokines, Nutritional
Status, and Electrical Taste Perception in the Three Groups
There were significant correlations between the abundance of several species in the
standard dose DMB group and a variety of outcomes, as shown in Figure 3A. The abun-
dance of Streptococcus genus, particularly species of Streptococcus thermophilus,Streptococcus
pneumoniae,Streptococcus dysgalactiae and Streptococcus agalactiae, correlated negatively with
the concentration levels of TNF-
α
in patients with cancer. Furthermore, energy intake
(%) and lipid percentage of energy, as well as monounsaturated fatty acids (MUFAs) and
polyunsaturated fatty acids (PUFAs) expressed as percentages of energy, were positively
correlated with those bacteria. Additionally, the MUFAs and PUFAs percentages of en-
ergy were positively associated with Veillonella parvula levels (Figure 3A). The group that
received the highest dose of DMB showed several correlations with other outcomes of the
study (Figure 3B). Indeed, the relative abundance of Streptococcus pneumoniae,Streptococcus
dysgalactiae, and Streptococcus agalactiae was positively correlated with energy intake. Satu-
rated fatty acids were positively associated with Streptococcus pneumoniae and Streptococcus
dysgalactiae levels. Lastly, Granulicatella adiacens was negatively associated with TNF-
α
concentration (Figure 3B). In the placebo group, the relative abundance of Granulicatella
adiacens was negatively correlated with the energy intake. The levels of Streptococcus ther-
mophilus were negatively correlated with electric taste perception on both the right and left
sides. The PUFAs intake was positively associated with Streptococcus agalactiae (Figure 3C).
Neither selected bacteria (Granulicatella adiacens,Streptococcus agalactiae,Streptococcus dys-
galactiae,Streptococcus pneumoniae, and Veillonella parvula) nor electrogustometry, the type
of diet, or cytokine levels were associated with mucositis, according to the binary logistic
regression. There were only two variables that remained in the equation without reaching
statistical significance: TNF-
α
levels (p= 0.109) and saturated fatty acids (p= 0.142). More-
over, no independent correlation was found between the presence of selected species and
clinical outcomes evaluated as immunotherapeutic agents used for the cancer treatment
(Wald, 0.011; p-value, 0.918; OR, 1.010; 95% CI of OR, 0.832–1.227), general toxicity (Wald,
Cancers 2024,16, 3414 14 of 24
0.605;
p-value
, 0.437; OR, 0.928; 95% CI of OR, 0.768–1.121), digestive toxicity (Wald, 0.931;
p-value
, 0.335; OR, 1.877; 95% CI of OR, 0.520–6.748), or consumption of tobacco (Wald,
1.438; p-value, 0.230; OR, 2.302; 95% CI of OR, 0.586–9.182) and alcohol (Wald, 1.042; p-value,
0.307; OR, 0.674; 95% CI of OR, 0.316–1.438).
Cancers 2024, 16, x FOR PEER REVIEW 12 of 22
Figure 2. Group microbial balances are presented in an overview. It is indicated at the top of the
plot that groups of taxa constitute the global balance. Box plots illustrate the distribution of balance
scores for the DMB 150 mg (standard dose) and placebo groups (A) and the DMB 300 mg (high
dose) and placebo groups (B). On the right, the ROC curve with its AUC value and the density curve
are displayed.
3.6. Analysis of the Relationships between Oral Microbiome, Inflammatory Cytokines,
Nutritional Status, and Electrical Taste Perception in the Three Groups
There were significant correlations between the abundance of several species in the
standard dose DMB group and a variety of outcomes, as shown in Figure 3A. The abun-
dance of Streptococcus genus, particularly species of Streptococcus thermophilus, Streptococ-
cus pneumoniae, Streptococcus dysgalactiae and Streptococcus agalactiae, correlated negatively
with the concentration levels of TNF-α in patients with cancer. Furthermore, energy intake
(%) and lipid percentage of energy, as well as monounsaturated fay acids (MUFAs) and
polyunsaturated fay acids (PUFAs) expressed as percentages of energy, were positively
correlated with those bacteria. Additionally, the MUFAs and PUFAs percentages of en-
ergy were positively associated with Veillonella parvula levels (Figure 3A). The group that
received the highest dose of DMB
showed several correlations with other outcomes of the
study (Figure 3B). Indeed, the relative abundance of Streptococcus pneumoniae, Streptococ-
cus dysgalactiae, and Streptococcus agalactiae was positively correlated with energy intake.
Figure 2. Group microbial balances are presented in an overview. It is indicated at the top of the
plot that groups of taxa constitute the global balance. Box plots illustrate the distribution of balance
scores for the DMB 150 mg (standard dose) and placebo groups (A) and the DMB 300 mg (high dose)
and placebo groups (B). On the right, the ROC curve with its AUC value and the density curve
are displayed.
Cancers 2024,16, 3414 15 of 24
Cancers 2024, 16, x FOR PEER REVIEW 13 of 22
Saturated fay acids were positively associated with Streptococcus pneumoniae and Strep-
tococcus dysgalactiae levels. Lastly, Granulicatella adiacens was negatively associated with
TNF-α concentration (Figure 3B). In the placebo group, the relative abundance of Granu-
licatella adiacens was negatively correlated with the energy intake. The levels of Streptococ-
cus thermophilus were negatively correlated with electric taste perception on both the right
and left sides. The PUFAs intake was positively associated with Streptococcus agalactiae
(Figure 3C). Neither selected bacteria (Granulicatella adiacens, Streptococcus agalactiae, Strep-
tococcus dysgalactiae, Streptococcus pneumoniae, and Veillonella parvula) nor electrogustome-
try, the type of diet, or cytokine levels were associated with mucositis, according to the
binary logistic regression. There were only two variables that remained in the equation
without reaching statistical significance: TNF-α levels (p = 0.109) and saturated fay acids
(p = 0.142). Moreover, no independent correlation was found between the presence of se-
lected species and clinical outcomes evaluated as immunotherapeutic agents used for the
cancer treatment (Wald, 0.011; p-value, 0.918; OR, 1.010; 95% CI of OR, 0.832–1.227), gen-
eral toxicity (Wald, 0.605; p-value, 0.437; OR, 0.928; 95% CI of OR, 0.768–1.121), digestive
toxicity (Wald, 0.931; p-value, 0.335; OR, 1.877; 95% CI of OR, 0.520–6.748), or consumption
of tobacco (Wald, 1.438; p-value, 0.230; OR, 2.302; 95% CI of OR, 0.586–9.182) and alcohol
(Wald, 1.042; p-value, 0.307; OR, 0.674; 95% CI of OR, 0.316–1.438).
Cancers 2024, 16, x FOR PEER REVIEW 14 of 22
Figure 3. Correlations between the oral microbiome, inflammatory cytokines, nutritional status, and
electrical taste perception. (A). DMB 150 mg (standard dose), (B). DMB 300 mg (high dose), and (C).
placebo. Right and left side measures refer to electrogustometry variables; dB, the threshold of taste
perception measured in decibels.
Figure 3. Cont.
Cancers 2024,16, 3414 16 of 24
Cancers 2024, 16, x FOR PEER REVIEW 14 of 22
Figure 3. Correlations between the oral microbiome, inflammatory cytokines, nutritional status, and
electrical taste perception. (A). DMB 150 mg (standard dose), (B). DMB 300 mg (high dose), and (C).
placebo. Right and left side measures refer to electrogustometry variables; dB, the threshold of taste
perception measured in decibels.
Figure 3. Correlations between the oral microbiome, inflammatory cytokines, nutritional status, and
electrical taste perception. (A). DMB 150 mg (standard dose), (B). DMB 300 mg (high dose), and
(C). placebo. Right and left side measures refer to electrogustometry variables; dB, the threshold of
taste perception measured in decibels.
4. Discussion
In the present study, patients with cancer, malnourished and with dysgeusia presented
dysbiosis. We have shown that the regular consumption of 150 mg of DMB (standard dose),
as an adjuvant to medical–nutritional treatment, changed the oral microbiome composition
in these patients receiving antineoplastic treatment. In particular, the consumption of the
standard dose of DMB resulted in a greater relative abundance of Enterococcus and a lower
abundance of the Veillonella genus than the consumption of a high dose of DMB or placebo.
Additionally, some species such as Granulicatella elegans,Granulicatella adiacens, Streptococcus
mutans, and Gemella morbillorum exhibited greater relative abundances in patients receiving
the standard dose of DMB. However, lower abundances of Streptococcus parasanguinis,
Veillonella parvula,Streptococcus australis and Streptococcus cristatus were detected. The
consumption of the standard dose of DMB revealed a link between several Streptococcus
species and lower TNF-
α
plasma levels as well as higher energy and plasma MUFAs and
PUFAs dietary intake.
The oral microbiota is composed of a multitude of bacterial species, including Acti-
nomycetota (formerly Actinobacteria), Bacteroidota (Bacteroidetes), Bacillota (Firmicutes), Fu-
sobacteriota (Fusobacteria), Pseudomonadota (Proteobacteria), Saccharibacteria and Spirochaetota
(Spirochaetes) [
24
]. These bacterial species are generally conserved across individuals, mak-
ing up the bulk of the oral microbiota [
63
], which plays a relevant role in oral health [
64
].
The mechanism by which commensals promote healthy oral microbiota involves outcompet-
ing pathogens for colonization [
65
]. Microbes temporarily overpower the immune system
in the event of reduced diversity and richness, which is described as dysbiosis [
66
,
67
].
Nevertheless, the oral microbiome serves more than just a local function, as microbes are
capable of communicating with the entire body [
68
]. The presence of oral dysbiosis can
Cancers 2024,16, 3414 17 of 24
contribute to the maintenance of chronic low-grade systemic inflammation by causing a
localized inflammatory state within the oral cavity [69].
Cancer can be affected by microbes in a variety of ways, including contact-dependent
effects occurring locally at the mucosal surface or within the tumor microenvironment. The
second type of effect is contact-independent effects, which are caused by the metabolites
produced by microbes and the vesicles of their outer membranes that circulate in the
blood [
70
,
71
]. Thus, several types of cancer may be associated with specific patterns of
salivary and fecal microbiomes as well as circulating microbial DNA in blood plasma [
72
].
Alterations in the oral microbiome that are associated with cancer treatments cause
dysbiosis, which is a condition characterized by an imbalanced status of the oral micro-
bial community [
73
]. Thus, the dysbiosis of the oral microbiome is characterized by an
increase in the prevalence of pathogenic microbial species at the expense of commensal
microorganisms and a markedly reduced richness and diversity of species [
74
,
75
]. Taste
disorders are frequently reported by oncologic patients undergoing antineoplastic treat-
ments [
3
,
4
]. Consequently, taste disorders have a significant impact on eating behaviors
and, as a result, have a major influence on overall health [
64
]. In addition, this alteration
might cause oral microbiome dysbiosis during cancer therapies, which is characterized
by a markedly reduced richness and diversity of species [
75
]. Here, we observed that the
richness and diversity, measured by the Shannon and Simpson indices, along with the
Chao1 index, were reduced in our patients with cancer compared to the levels reported in
healthy individuals [62], indicating basal dysbiosis in all groups.
Gemella was the fourth most prevalent genera in our study, which is followed by
Streptococcus,Veillonella, and Granulicatella.Gemella sanguinis was the most prevalent
Gemella species in our study. A significantly greater enrichment of the Gemella genus in
oral squamous cell carcinoma has been reported. In oral leukoplakia and oral squamous
cell carcinoma, Streptococcus sp. NPS 308, Streptococcus agalactiae,Gemella hemolysans, and
Gemella morbillorum were slightly increased [
76
]. A high relative abundance of Gemella
morbillorum is present in oral cavity squamous cell carcinoma tumor tissues compared
with the paired adjacent normal tissues [
77
]. Here, we observed a tendency for Gemella
morbillorum to be more abundant in the standard dose of DMB group; however, lower
levels were observed in the high dose of DMB group, indicating a different profile that
was dose-dependent for this bacterium.
In vitro
studies with three oral squamous cell
carcinoma cell lines (CAL27, SCC4, and SCC25) have demonstrated the positive effects
of oral commensals belonging to the Streptococcus genus [
78
]. In our patients with cancer,
these species make up more than 63% of the total oral microbiome. According to the above
data, these bacteria are capable of acting as anticancer agents.
Veillonella parvula is elevated in oral cancer [
79
], especially in oral squamous cell
carcinoma, by promoting the expression of inflammatory cytokines, including interleukins
(IL-6, IL-8) and TNF-
α
[
80
]. We found that the regular consumption of a standard dose of
DMB decreases the abundance of Veillonella parvula, which is an important oncologically
related bacteria after 3 months of treatment [
80
]. The lower relative abundance of this
bacteria in the standard-dose DMB group could be related to the association with the
TNF-
α
levels observed in the present study. After 3 months of intervention, the high-
dose DMB group presented increased Veillonella parvula, and the dose here might have
contradictory results.
At the species level, we also found that the relative abundance of Granulicatella elegans,
Granulicatella adiacens, and Streptococcus mutans was greater in patients receiving the stan-
dard dose of DMB. However, lower abundances of Streptococcus parasanguinis,Streptococcus
australis and Streptococcus cristatus were detected.
Regarding the genus Granulicatella, we observed a significant variation in the abun-
dance of Granulicatella elegans with an increase in the standard dose DMB group and a
decrease in the high-dose DMB group. This is of interest, since a positive association has
been found between the abundance of Granulicatella elegans and inflammation [
81
]. In
Cancers 2024,16, 3414 18 of 24
the case of Granulicatella adiacens, higher levels at both standard and high doses of DMB
were observed.
Microbiome-associated pathology can arise from changes in general bacterial compo-
sition, such as those found in periodontitis, and from the colonization and overgrowth of
keystone species [
82
]. The infiltration of immunosuppressive cells and the interference of
immune killer cells by commonly occurring oral microorganisms, such as Fusobacterium
nucleatum and Porphyromonas gingivalis, can prevent tumor cells from being observed and
cleared by the immune system [
83
–
85
]. There is evidence that a high abundance of Fusobac-
terium nucleatum in the oral microbiome of patients with colorectal cancer is associated
with tumor metastasis, recurrence, chemo-resistant cancer, and reduced radiotherapy effi-
cacy [
86
–
89
]. In our study, the absence of periodontitis and gingivitis in these patients with
cancer may explain why the aforementioned species were not detected in the samples. It is
still necessary to conduct large cohort and case-control studies to validate the hypothesis
that periodontal disease contributes to the initiation and development of cancer [90].
Further, in our study, neither of the highly represented bacteria was associated with the
presence or absence of mucositis at the end of the study based on binary logistic regression.
It is also important to note that no independent correlation was found between the presence
of selected species and clinical outcomes evaluated as immunotherapeutic agents used
for cancer treatment, general toxicity, digestive toxicity, or the consumption of tobacco
and alcohol.
The oral Streptococcus genus plays a key role in oral dysbiosis and a wide range
of clinical conditions, including dental caries, gingivitis, periodontal disease, and oral
cancer [
91
]. We found that Streptococcus thermophilus,Streptococcus pneumoniae,Streptococcus
dysgalactiae, and Streptococcus agalactiae were negatively associated with the plasma levels
of TNF-
α
in malnourished patients with cancer receiving a standard dose of DMB, which
might be associated with the overall improvement of systemic inflammation after DMB
supplementation. There are some strains of Streptococcus that have inherent antitumor
activity or that can activate the immune system of the host to fight tumors [
92
]. Several
studies have suggested that the frequent and/or excessive consumption of sugar (especially
sucrose) contributes to tooth decay [
93
]. Streptococcus mutans is thought to play a critical
role in the metabolism of sucrose, producing lactic acid, which is capable of demineralizing
enamel [
94
]. A possible relationship between Streptococcus species, diet, and caries etiology
is illustrated here. As a result of our study, the evaluated Streptococcus species were
positively associated with energy intake, lipid percentage of energy, plasma MUFAs and
PUFAs, expressed as energy percentages, indicating that diet can have a significant impact
on the main genus of the oral microbiome.
Moreover, the percentages of energy-related MUFAs and PUFAs were positively
associated with Veillonella parvula levels. This finding is of interest, since we observed an
improvement in the quality of life in malnourished patients with cancer who received
a standard dose of DMB [
41
]. Therefore, the oral intake of DMB might improve the
pattern of oral bacteria and in turn reduce inflammation. In the case of the group that
received high doses of DMB, we observed that the relative abundances of Streptococcus
pneumoniae,Streptococcus dysgalactiae, and Streptococcus agalactiae were positively correlated
with energy intake. Saturated fatty acids were positively associated with Streptococcus
pneumoniae and Streptococcus dysgalactiae levels. The abundance of Granulicatella adiacens
was negatively associated with the plasma TNF-
α
concentration, which could be related to
a slight anti-inflammatory effect. It should be necessary to evaluate a complete panel of
cytokines to assess the potential systemic inflammation associated with oral dysbiosis. It
is necessary to evaluate a panel of cytokines in order to assess the systemic inflammation
associated with oral dysbiosis. Finally, there was no correlation between changes in the oral
microbiome of the DMB groups and electric taste perception. It was only in the placebo
group that Streptococcus thermophilus abundance was negatively correlated with electric
taste perception.
Cancers 2024,16, 3414 19 of 24
Streptococcus mutans is involved in the etiology of several oral diseases [
95
–
97
]. In
particular, Streptococcus mutans is implicated as the main etiologic agent of caries [98–100].
Dysbiosis of the dental plaque microbiome is associated with an abundance of biofilm-
forming, acid-producing, and acid-tolerant species. In the standard-dose DMB group, the
relative abundance of Streptococcus mutans increased slightly, whereas the increase in the
placebo group was twice as high. This slight increase in the standard-dose DMB group
might be linked to increased energy consumption by those patients.
In contrast, a lower relative abundance of Streptococcus mutans was observed in pa-
tients receiving high doses of DMB. Nevertheless, compared with patients in the standard
dose group, these patients did not show an improvement in quality of life [
41
]. While
Streptococcus mutans is associated with caries, Streptococcus cristatus plays a relevant role
in the development of periodontitis, a common oral disease, and it may contribute to the
pathogenicity of the oral microbiome [
101
,
102
]. We observed that Streptococcus cristatus was
lower in all three groups post-intervention, which was possibly as a result of the absence of
periodontitis in the present population.
Overall, the changes in the oral microbiota observed in patients having the standard
dose of DMB differed from those having the higher dose. This could be due to the fact that
the latter group manifested a sweet taste for a longer period of time after the consumption of
the DMB tablet, compared to the former, which in turn results in a lower dietary intake [
41
].
5. Conclusions
To identify innovative therapies for the treatment of taste disorders in patients with
cancer, we conducted this pilot randomized, parallel, triple-blind, and placebo-controlled
clinical trial aimed at providing a novel strategy for reducing the side effects of chemother-
apy, radiotherapy, and immunotherapy, including alterations in body composition, nutri-
tional status, and quality of life [
41
]. All patients presented dysbiosis in terms of bacterial
diversity and richness compared with healthy individuals. Here, we showed that the
regular consumption of a standard dose of DMB, as an adjuvant to medical–nutritional
treatment, could modify the oral microbiome composition in malnourished patients with
cancer receiving antineoplastic treatment. Thus, we reported that the relative abundances
of Enterococcus were higher in patients with cancer receiving a standard dose of DMB at
3 months after intervention. However, lower abundances of Streptococcus parasanguinis,
Veillonella parvula, and Streptococcus mutans were detected. Furthermore, DMB consumption
was negatively associated with Streptococcus thermophilus,Streptococcus pneumoniae,Strep-
tococcus dysgalactiae, and Streptococcus agalactiae and with TNF-
α
plasma concentrations
in patients with cancer and taste disorders. The presence of Streptococcus thermophilus
and Veillonella parvula was positively associated with plasma MUFAs with only Veillonella
parvula being associated with plasma PUFAs. Overall, DMB intake could modify the oral
microbiome in patients with cancer and dysgeusia, which may contribute to a better im-
mune response. There is still a need for further studies with a large number of patients and
variables to be measured.
Supplementary Materials: The following supporting information can be downloaded at https:
//www.mdpi.com/article/10.3390/cancers16193414/s1, Table S1: Nutritional composition of the
food supplement enriched in miraculin (DMB) and placebo; Table S2. Cancer types and chemotherapy
characteristics of the general population; Table S3: Distribution of phyla and alpha diversity indices
for microbiota of saliva from cancer patients of the CLINMIR study; Table S4: Distribution of selected
families for microbiota of saliva from cancer patients of the CLINMIR study.
Author Contributions: Conceptualization, B.L.-P., A.G. and S.P.-M.; methodology, B.L.-P., T.H. and
J.F.-B.; software, J.P.-D.; validation, F.J.R.-O., A.I.Á.-M. and M.B.-H.; formal data analysis, J.P.-D.,
F.J.R.-O. and M.B.-H.; investigation, B.L.-P. and
L.A.-C.
; resources, S.P.-M.; data curation,
L.A.-C.
;
writing—original
draft preparation, J.P.-D., F.J.R.-O., M.B.-H. and A.G.; writing—review and editing,
J.P.-D., F.J.R.-O., M.B.-H. and A.G.; supervision, S.P.-M. and A.G.; project administration, B.L.-P.; fund-
ing acquisition, S.P.-M. All authors have read and agreed to the published version of the manuscript.
Cancers 2024,16, 3414 20 of 24
Funding: This study is funded by the Medicinal Gardens S.L. through the Center for Industrial
Technological Development (CDTI), “Cervera” Transfer R&D Projects. Ref. IDI-20210622. (Science
and Education Ministry, Spain).
Institutional Review Board Statement: The study was conducted under the Declaration of Helsinki and
approved by the Ethics Committee of La Paz University Hospital (protocol code 6164, 23 June 2022).
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.
Data Availability Statement: A reasonable request should be made to the corresponding author for
access to the datasets used and/or analyzed in the current study.
Acknowledgments: J.P.-D. is part of the “UGR Plan Propio de Investigación 2016” and the “Excellence
Actions: Unit of Excellence in Exercise and Health (UCEES), University of Granada”. F.J.R.-O. is
supported by a grant from the Spanish Government’s “Agencia Estatal de Investigación-Juan de la
Cierva-Incorporación” program (IJC2020-042739-I). We thank (Lucía Tadeo, Helena Torrell, Adría
Cereto and Núria Canela) from the Genomics facility of the Centre for Omic Sciences (COS) Joint
Unit of the Universitat Rovira i Virgili-Eurecat for their contribution to sequencing analysis.
Conflicts of Interest: The authors declare that they have no commercial or financial relationships
that could be construed as potential conflicts of interest.
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