Clinical trial NCT03885648: Breast Cancer and Its Relationship With the Microbiota
Official title: Association of Breast and Gut Microbiota Dysbiosis and the Risk of Breast Cancer
Study type: OBSERVATIONAL
Overall status: ACTIVE_NOT_RECRUITING
Conditions: Breast Cancer
Keywords: Breast cancer
Microbiota
Endocrine disruptors
Estrogens
Lead sponsor: Universidad de Granada
Sponsor class: OTHER
First posted: 2019-03-21
Enrollment: 150
Sex: FEMALE
Minimum age (years): 25
Maximum age (years): 70
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: CASE_CONTROL
Time perspective: CROSS_SECTIONAL
Sampling method: PROBABILITY_SAMPLE
Study population: Women diagnosed of breast cancer, stages I and II.

Brief summary: Breast cancer ranks first in women, and is the second cause of death in this gender. In addition to genetics, the environment contributes to the development of the disease, although the factors involved are not well known. Among the latter is the influence of microorganisms and, therefore, attention is recently being paid to the mammary microbiota. The hypothesis of this study is that the risk of breast cancer could be associated with the composition and functionality of the mammary/gut microbiota, and that exposure to environmental contaminants (endocrine disruptors, EDCs) might contribute to alter the microbiota.

This is a case-control clinical study that will be performed in women between 25 and 70 years of age. Cases will be women diagnosed and surgically intervened of breast cancer (stages I and II). Women with antecedents of cancer or advanced tumor stage (metastasis), or who have received antibiotic treatment within 3 months prior to recruitment, or any neoadjuvant therapy, will be excluded. Controls will be women surgically intervened of breast augmentation or reduction. Women with oncological, gynecological or endocrine history, and those who have received antibiotic treatment within 3 months prior to recruitment will also be excluded. Blood, urine, breast tissue and stool samples will be collected. Data regarding anthropometric, sociodemographic, reproductive history, tumor features and dietary habits will be gathered.

Metabolomic studies will be carried out in stool and breast tissue samples. Metagenomic studies will also be performed in stool and breast tissue samples to ascertain the viral, fungal, bacterial and archaea populations of the microbiota. Quantitation of estrogens, estrogen metabolites and EDCs in samples of serum, urine and breast tissue will also be performed.

This is the first time that the contribution of bacteria, archaea, viruses and fungi together with their alteration by environmental contaminants to the risk of breast cancer will be evaluated in the same study. Results obtained could contribute to elucidate risk factors, improve the prognosis, as well as to propose novel intervention studies in this disease.

Detailed description: The study will follow the Declaration of Helsinki and the Spaniard legislation regarding clinical research. Data obtained will be confidential and only the researchers and participants, upon request, will have access to them. The study will also follow the data protection legislation of Spain to guarantee data confidentiality, treatment and availability.

Participation is volunteer. Participants will be informed about the nature of the research and the usage of biological samples. In addition to verbal information, participants will be presented and read an informed consent. Permission has been granted by the Ethics Committee of Andalusia (Spain).

Inclusion and exclusion criteria. Women's age will range 25-70 years. Cases will be women diagnosed and surgically intervened of incident breast cancer, stages I and II. Controls will be women surgically intervened of breast augmentation or reduction. Women with antecedents of cancer or advanced tumor stage (metastasis), or who have received antibiotic treatment 3 months prior to recruitment, or any neoadjuvant therapy, will be excluded of the study. Women with oncological, gynecological or endocrine antecedents and those who have received of antibiotic treatment 3 months prior to recruitment will be also excluded. Controls will be matched to cases by age (± 2 years), category of body mass index and hospital of recruitment.

Sample size. The number of breast cancer cases will include at least 100 women, matched with 100 control women. Three hospitals will participate in the recruitment: The University Hospital of Jaén, Spain; the University Hospital Campus de la Salud of Granada, Spain; and Ana Moreno Clinic (Granada, Spain).

Biological samples. Blood, breast tissue, stool and urine samples from cases and controls will be collected. Serum will be separated from blood by centrifugation. Breast tissue samples will be taken during surgery, from a marginal area 3-5 cm apart from the tumor. For controls, samples will be taken from any available breast tissue during breast reduction or augmentation surgery.

Breast and intestinal microbiota. Bacteria, archaea, fungi and viruses will be investigated in feces and breast tissue samples. Samples will be pre-treated with pathogen lysis tubes L and S (QIAGEN, Barcelona, Spain). DNA will be extracted with the QIAamp cador Pathogen Mini kit (QIAGEN, Barcelona, Spain).

DNA quantification. The DNA concentration of the samples will be evaluated in a NanoDrop2000c (Thermo Fisher Scientific, Waltham, MA, USA).

Metagenomic library construction and sequencing. The Nextera XT DNA Library Preparation Kit (Illumina, San Diego, CA, USA) will be used for metagenomic library construction. The amplicon tagment mix (ATM) in Nextera XT, which includes the enzyme used for tagmentation, will be diluted 1:10 in nuclease-free water for library construction using 1 to 100 pg input DNA. Each 20 μL of the tagmentation reaction mixture consists of 10 μL TD buffer, 5 μL of input DNA, and 5 μL of diluted ATM. PCR cycles for library construction will be 12, 14, 17, and 20 cycles for 1,000, 100, 10, and 1 pg DNA, respectively, following the manufacturer's protocol. The manufacturer recommends 12 cycles of the PCR reaction for no less than 1 ng input DNA. Amplified libraries will be purified using AMPure XP (Agencourt, Brea, CA, USA). The quality of the purified libraries will be assessed using an Agilent High Sensitivity DNA Kit on an Agilent 2100 Bioanalyzer (Santa Clara, CA, USA). The sequencing libraries will be further quantified using the KAPA Library Quantification Kit. Metagenomic libraries will be mixed with PhiX Control v3 (Illumina) at a ratio of 9:1 and sequenced with an Illumina MiSeq Reagent Kit v3 (600 cycles). All samples to be analyzed will be combined in a pool before starting the massive sequencing. The latter will be done with the MiSeq apparatus (Illumina).

Data processing for metagenomic libraries. Metagenomic reads will be subjected to adaptor clipping and quality trimming using Trimmomatic v0.3. The first three nucleotides with quality scores less than 20 will be cut from the 3' and 5' read ends. Reads will be processed using a sliding window method, cutting once the average quality within the window (4 base) fell below the threshold (Q20). Reads with a length of fewer than 100 nucleotides will be then removed. Low-complexity reads will be filtered out using PRINSEQ version 0.20.4. PCR duplicates will be removed with Picard version 2.8.0 (http://broadinstitute.github.io/picard). The processed high-quality and clean reads in each library will be used in subsequent analyses. In the community analysis based on metagenomic sequences, small subunit (SSU) rRNA gene sequences will be identified using Metaxa2 software. Taxonomy assignments will be performed based on the results of a BLAST search against the SILVA123 database, using the MEGAN program \[23\] with the following settings: Min Support 1, Min Score 50, Max Expected 1xe-5, Top Percent 10.0. SSU rRNA gene community compositions were compared among the metagenomic libraries.

Metabolomic study. Sample preparation. The samples will be prepared using the automated MicroLab STARR (Hamilton Company, Salt Lake City, UT, USA) robot system. For quality control (QC) purposes, a recovery standard will be added to 100 L of the serum samples before the first step in the extraction process. The proteins will be precipitated with methanol by vigorously shaking for 2 min. Next, the samples will be centrifuged to remove the proteins, dissociate the small molecules bound to the proteins or trapped in the precipitated protein matrix, and to recover chemically diverse metabolites (Glen Mills GenoGrinder 2000, Lebanon, USA). Then, the samples will be placed on a TurboVapR (Zymark, California, USA) to remove the organic solvent. For liquid chromatography (LC) analysis, the samples will be stored overnight in nitrogen before preparation. For gas chromatography (GC) analysis, each sample will be dried overnight under vacuum before preparation.

Quality controls. Several types of control experiments will be performed in parallel with the experimental samples. A pooled matrix sample, generated by taking a small volume of each experimental sample, will serve as a technical replicate throughout the extracted data set. Water aliquots will serve as process blanks. Moreover, a cocktail of QC standards carefully chosen not to interfere with the measurement of endogenous compounds will be spiked into every analyzed sample. This will allow instrument performance monitoring and aid in the chromatographic alignment. The instrument variability will be determined by calculating the median relative standard deviation (RSD) for the standards that will be added to each sample before injection into the mass spectrometers (MS). The entire process variability will be determined by calculating the median RSD for all the endogenous metabolites (i.e., non-instrument standards) present in 100% of the pooled matrix samples. The experimental samples will be randomized across the platform run with the QC samples spaced every 5 or 10 injections to verify overall assay performance. The internal standards will be used to measure the instrument variability and will have a median RSD of 3%. Additionally, the total process variability will be 8%.

Ultra-performance liquid chromatography-tandem mass spectrometry. The liquid chromatography/mass spectrometry (LC/MS) portion of the platform to be used will employ a Waters ACQUITY ultra performance liquid chromatography (UPLC), a Thermo Scientific Q-Exactive high-resolution/accurate MS interfaced with a heated electrospray ionization (HESI-II) source, and an Orbitrap mass analyzer operated at a 35,000 mass resolution. The sample extract will be dried and reconstituted in acidic or basic LC-compatible solvents, each of which will contain eight or more injected QC standards at fixed concentrations to ensure injection and chromatographic consistency. One aliquot will be analyzed using acidic, positive ion-optimized conditions, and another will be performed using basic, negative ion optimized conditions in two independent injections using separate dedicated columns (Waters UPLC BEH C18-2.1 × 100 mm, 1.7 m). The extracts reconstituted in acidic conditions will be gradient-eluted from a C18 column using water and methanol containing 0.1% formic acid. A second aliquot, from the basic extract, will be similarly eluted from a C18 column using methanol, water, and 6.5 mM ammonium bicarbonate. A third aliquot will be analyzed via negative ionization following elution from a hydrophilic interaction chromatography column (Waters UPLC BEH Amide 2.1 × 150 mm, 1.7 m) using a gradient consisting of water and acetonitrile with 10 mM ammonium formate.

Gas chromatography-mass spectrometry. The samples destined for analysis by GC-MS will be dried under a vacuum for a minimum of 18 h before being derivatized under dried nitrogen with bistrimethylsilyltrifluoroacetamide. The derivatized samples will be separated on a 5% diphenyl/95% dimethyl polysiloxane fused silica column (20 m × 0.18 mm id; 0.18 m film thickness) with helium as the carrier gas and a temperature ramp from 60C to 340C over a 17.5-min period. The samples will be analyzed on a Thermo-Finnigan Trace DSQ fast-scanning single-quadrupole MS using electron impact ionization (EI) operated at unit mass resolving power. The scan range will be 50-750 m/z.

Data extraction and compound identification. The raw data will be extracted, and the peaks will be aligned and identified. QCs will be processed using specific hardware and software. The peaks will be quantified using the area-under-the-curve (AUC) calculation. The compounds will be identified comparing the data to library entries of purified standards or recurrent unknown entities. The biochemical identifications will be based on three criteria: the retention index (RI) within a narrow RI window of the proposed identification, an accurate mass match to the library ± 0.005 amu, and the MS/MS forward and reverse scores between the experimental data and authentic standards. The MS/MS scores will be based on a comparison of the ions present in the experimental spectrum with the ions present in the library spectrum. Although there may be similarities between these molecules based on one of these factors, the use of all three data points can be utilized to distinguish and differentiate the biochemicals with precision.

Quantitation of the exposure to EDCs in urine samples. Analysis of non-persistent EDCs will be carried out by dispersive liquid-liquid microextraction (DLLME) and ultra-high performance liquid chromatography with tandem mass spectrometry detection (UHPLC-MS/MS). Briefly, urine samples are thawed completely at room temperature, centrifuge at 2600 x g for 10 min to sediment particulate matter and 0.75 mL are taken to carry out the analysis. In order to determine total EDCs amount (free plus conjugated), each sample is spiked with 50 μL of enzyme solution (β-glucuronidase/sulfatase) and incubated at 37 °C for 24 h. The treated urine is placed in a 15 mL screw-cap glass tube and spiked with 30 μL of the surrogate standard solution (1.25 mg/L of BPA-d16). Urine is diluted to 10.0 mL with 5% NaCl aqueous solution (w/v) and the pH is adjusted to 2.0. Next, 0.75 mL of acetone and 0.75 mL of trichloromethane are mixed and injected rapidly into the aqueous sample with a syringe. After manual shaking, centrifugation and evaporation of the extract, the residue is dissolved with 100 μL of a mixture consisting of water (0.1% ammonia)/acetonitrile (0.1% ammonia), 70:30 (v/v), and finally 10 μL is injected in the LC system. Urinary creatinine concentration is determined using an automated colorimetric determination in the same urine samples in which the environmental chemical is assessed.

Quantitation of urinary concentrations of the parent estrogens and estrogen metabolites. Concentrations of estrone, estradiol and 13 estrogen metabolites will be determined adjusting for urinary creatinine levels (mg/dl). The quantitation of urinary estrogens will be assessed by gas chromatography tandem mass spectrometry using a triple quadrupole analyzer. Briefly, one mL of urine with 25 µL of internal standards solution is extracted using C18 SPE cartridge (Sep-Pack C18) previously conditioned with 4 mL of methanol and 4 mL of water. After loading the urine sample, the cartridge is washed with 4 mL of water. The treated urine is then evaporated. Three mL of acetate buffer 0.1 M (pH 4.5) and 3 µL of β-glucuronidase are added to the evaporated, and the mixture is incubated for 3 h at 55 °C. After cooling to room temperature, pH was increased to approximately 9.5. Then, samples are extracted with 6 mL of tert-butyl methyl ether by shaking and centrifuged. Finally, the organic layer is evaporated to dryness under a stream of nitrogen.

Other sources of information and covariables. Participants' anthropometric, sociodemographic and reproductive features will be recorded. They will also grant permission to access their clinical history. Tumor features and dietary habits will be recorded.

Eligibility criteria: Inclusion criteria:

* Cases will be women diagnosed and surgically intervened of breast cancer, stages I and II.
* Controls will be women surgically intervened of breast augmentation or reduction.

Exclusion criteria:

1. For cases:

   * Women with antecedents of cancer or advanced tumor stage (metastasis).
   * Women who have received antibiotic treatment 3 months prior to recruitment, or any neoadjuvant therapy.
2. For controls:

   * Women with oncological, gynecological or endocrine antecedents.
   * Women who have received antibiotic treatment 3 months prior to recruitment.

Primary outcomes:
measure: Metagenomic study of mammary microbiota
timeFrame: December 31, 2020
measure: Metagenomic study of intestinal microbiota
timeFrame: December 31, 2020
Secondary outcomes:
measure: Quantitation of the exposure to non-persistent EDCs (bisphenols) in urine samples
timeFrame: December 31, 2020
measure: Quantitation of the exposure to non-persistent EDCs (parabens) in urine samples
timeFrame: December 31, 2020
measure: Quantitation of the exposure to non-persistent EDCs (benzophenones) in urine samples
timeFrame: December 31, 2020
measure: Quantitation of urinary concentrations of estrogens
timeFrame: December 31, 2020
Other outcomes:
Locations:
city: Granada
country: Spain
facility: Unit of Mammary Pathology, General Surgery Service, University Hospital Campus de la Salud
Study officials:
affiliation: Universidad de Granada
name: Luis Fontana, Ph.D.
role: PRINCIPAL_INVESTIGATOR
References:
citation: Ruiz-Marin CM, Isabel Alvarez-Mercado A, Plaza-Diaz J, Rodriguez-Lara A, Gallart-Aragon T, Sanchez-Barron MT, Lartategui SR, Alcaide-Lucena M, Fernandez MF, Fontana L. A Clustering Study of Sociodemographic Data, Dietary Patterns, and Gut Microbiota in Healthy and Breast Cancer Women Participating in the MICROMA Study. Mol Nutr Food Res. 2024 Aug;68(15):e2400253. doi: 10.1002/mnfr.202400253. Epub 2024 Jul 1.
citation: Plaza-Diaz J, Alvarez-Mercado AI, Ruiz-Marin CM, Reina-Perez I, Perez-Alonso AJ, Sanchez-Andujar MB, Torne P, Gallart-Aragon T, Sanchez-Barron MT, Reyes Lartategui S, Garcia F, Chueca N, Moreno-Delgado A, Torres-Martinez K, Saez-Lara MJ, Robles-Sanchez C, Fernandez MF, Fontana L. Association of breast and gut microbiota dysbiosis and the risk of breast cancer: a case-control clinical study. BMC Cancer. 2019 May 24;19(1):495. doi: 10.1186/s12885-019-5660-y.