Summary of Study ST003506

This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR002152. The data can be accessed directly via it's Project DOI: 10.21228/M8FR6S This work is supported by NIH grant, U2C- DK119886.

See: https://www.metabolomicsworkbench.org/about/howtocite.php

This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.

Study ID	ST003506
Study Title	Comparison of serum and interstitial fluid from patients with breast cancer-related lymphedema and healthy control subjects with NMR-based metabolomics
Study Summary	Diagnosing and treating diseases such as breast cancer-related lymphedema (BCRL) is challenging due to a limited understanding of the underlying mechanisms. Despite recent advancements, BCRL significantly impacts patients' quality of life, as current treatments only manage symptoms. Leveraging modern high-throughput omics technologies, particularly metabolomics, holds potential to address these challenges. Metabolomics offers insights into dynamic changes influenced by internal and external factors, aiding in understanding the tissue physiology and detecting pathological conditions. The investigation of metabolomic biomarkers holds promise for early lymphedema diagnosis and personalized treatment. The deposited dataset represent high-resolution nuclear magnetic resonance (NMR) data for patients' blood serum and interstitial fluid, obtained after breast cancer treatment and with diagnosed BCRL, as well as control samples. Simple statistical analysis yielded increased concentrations of pyruvate, citrate, 2-ketoisovalerate, ketoleucine, 3-methyl-2-oxovalerate, tryptophan, and ascorbate in serum samples from patients with lymphedema. This dataset can aid in identifying early-stage lymphedema biomarkers and deepen insights into lymphatic system function thus leading to the development of effective diagnostic and therapeutic tools.
Institute	International Tomography Center SB RAS
Laboratory	Laboratory of Proteomics and Metabolomics
Last Name	Yanshole
First Name	Vadim
Address	Institutskaya 3a, Novosibirsk, Russia
Email	vadim.yanshole@tomo.nsc.ru
Phone	+73833303136
Submit Date	2024-09-16
Num Groups	3
Total Subjects	34
Raw Data Available	Yes
Raw Data File Type(s)	fid
Analysis Type Detail	NMR
Release Date	2024-10-03
Release Version	1

Select appropriate tab below to view additional metadata details:

Project:

Project ID:	PR002152
Project DOI:	doi: 10.21228/M8FR6S
Project Title:	Metabolomics of breast cancer-related lymphedema
Project Summary:	Diagnosing and treating diseases such as breast cancer-related lymphedema (BCRL) is challenging due to a limited understanding of the underlying mechanisms. Despite recent advancements, BCRL significantly impacts patients' quality of life, as current treatments only manage symptoms. Leveraging modern high-throughput omics technologies, particularly metabolomics, holds potential to address these challenges.
Institute:	International Tomography Center SB RAS
Laboratory:	Laboratory of Proteomics and Metabolomics
Last Name:	Yanshole
First Name:	Vadim
Address:	Institutskaya 3a, Novosibirsk, Russia
Email:	vadim.yanshole@tomo.nsc.ru
Phone:	+73833303136
Funding Source:	Russian Science Foundation, grant number 23-25-00462
Contributors:	Vadim V. Yanshole, Lyudmila V. Yanshole, Daria S. Gorina, Nataliya A. Osik, Vadim V. Nimaev, and Yuri P. Tsentalovich

Subject:

Subject ID:	SU003635
Subject Type:	Human
Subject Species:	Homo sapiens
Taxonomy ID:	9606
Age Or Age Range:	50-79
Gender:	Female

Factors:

Subject type: Human; Subject species: Homo sapiens (Factor headings shown in green)

mb_sample_id	local_sample_id	Sample source	Group
SA385821	K10	Blood serum	Control
SA385822	K2	Blood serum	Control
SA385823	K13	Blood serum	Control
SA385824	K12	Blood serum	Control
SA385825	K11	Blood serum	Control
SA385826	K1	Blood serum	Control
SA385827	K9	Blood serum	Control
SA385828	K3	Blood serum	Control
SA385829	K7	Blood serum	Control
SA385830	K5	Blood serum	Control
SA385831	K4	Blood serum	Control
SA385832	K8	Blood serum	Control
SA385833	s345	Blood serum	Lymphedema
SA385834	s339	Blood serum	Lymphedema
SA385835	s336	Blood serum	Lymphedema
SA385836	s330	Blood serum	Lymphedema
SA385837	s318	Blood serum	Lymphedema
SA385838	s315	Blood serum	Lymphedema
SA385839	s313	Blood serum	Lymphedema
SA385840	s303	Blood serum	Lymphedema
SA385841	s294	Blood serum	Lymphedema
SA385842	s299	Blood serum	Lymphedema
SA385843	s293	Blood serum	Lymphedema
SA385844	250c	Blood serum	Lymphedema
SA385845	s251	Blood serum	Lymphedema
SA385846	248c	Blood serum	Lymphedema
SA385847	249c	Blood serum	Lymphedema
SA385848	245c	Blood serum	Lymphedema
SA385849	252c	Blood serum	Lymphedema
SA385850	253c	Blood serum	Lymphedema
SA385851	257c	Blood serum	Lymphedema
SA385852	258c	Blood serum	Lymphedema
SA385853	259c	Blood serum	Lymphedema
SA385854	s253	Blood serum	Lymphedema
SA385855	245t	Interstitial fluid	Lymphedema
SA385856	248t	Interstitial fluid	Lymphedema
SA385857	249t	Interstitial fluid	Lymphedema
SA385858	250t	Interstitial fluid	Lymphedema
SA385859	252t	Interstitial fluid	Lymphedema
SA385860	253t	Interstitial fluid	Lymphedema
SA385861	257t	Interstitial fluid	Lymphedema
SA385862	258t	Interstitial fluid	Lymphedema
SA385863	259t	Interstitial fluid	Lymphedema

Showing results 1 to 43 of 43

Showing results 1 to 43 of 43

Collection:

Collection ID:	CO003628
Collection Summary:	The investigations were conducted in accordance with the principles outlined in the Declaration of Helsinki 2008 (https://www.wma.net/what-we-do/medical-ethics/declaration-of-helsinki/doh-oct2008/, accessed on 01.08.2024), which delineate ethical principles for medical research involving human subjects. Ethical approval was obtained from the International Tomography Center SB RAS ( ECITC-2020-12 from 16.12.2020) and the Research Institute of Clinical and Experimental Lymphology – Branch of the Institute of Cytology and Genetics SB RAS ( 159 from 20.07.2020). Written informed consent was obtained from all patients after a thorough explanation of the study's nature and potential consequences. No special permission from national or local authorities was required. Blood (n=22) and interstitial fluid (n=9) samples were collected from patients who had previously undergone breast cancer treatment and who subsequently developed and were diagnosed with BCRL (n=22, age 69.6 ± 3.4 years). Control blood samples (n=12, age 63.7 ± 6.5 years) were collected from age-matched patients without diagnosed breast can-cer and without lymphedema. Peripheral blood was obtained from the ulnar vein in the morning after overnight fasting under aseptic conditions into a vacutainer containing a coagulation activator. Within 10-15 minutes of collection, the blood samples were centrifuged (3000×g, 10 min), and the plasma obtained was transferred into separate Eppendorf vials. We have developed a method for collecting interstitial fluid from the subcutaneous tissue of the affected area from the patients with limb lymphedema. For this purpose, an ultrasound examination of the affected limb was performed using a 5 MHz and 10 MHz linear array probe. Areas of interstitial fluid accumulation were identified and marked. At these areas, the skin was punctured with a 27G needle and the interstitial fluid that appeared at the puncture site was collected using a 22G plastic catheter and transferred into clean Eppendorf vials. The vials with biofluid samples were immediately frozen and stored at -70°C until analysis.
Sample Type:	Blood serum; Interstitial fluid

Treatment:

Treatment ID:	TR003644
Treatment Summary:	Not applicable

Sample Preparation:

Sampleprep ID:	SP003642
Sampleprep Summary:	Sample Preparation For the preparation of extracts from blood serum for metabolomic measurements, we adhered to a standard protocol. Serum volume was 300 μl, ISF volume varied from 50 to 200 μl. Briefly, after thawing human blood plasma, we removed the clot from the vial, thus obtaining blood serum. Then, we added 300 μL of H2O, 600 μL of cold (-20 °C) methanol and 600 μL of cold (-20 °C) chloroform to 300 µL of serum. The mixture was then stirred on a shaker at +4 °C for 15 minutes, followed by incubation at -20 °C for 30 minutes. Subsequently, the mixture was centrifuged at 16,100×g for 30 minutes at +4 °C. Upon centrifugation, the mixture separated into two immiscible phases. The upper water-methanol phase was collected and vacuum dried overnight. NMR Measurements The dried extracts were dissolved in 600 µL of D2O containing 20 µM of DSS (sodium 4,4-dimethyl-4-silapentane-1-sulfonic acid) as an internal standard and 50 mM of deuterated phosphate buffer (pH 7.2). The 1H NMR measurements were conducted at the Center of Collective Use "Mass Spectrometric Investigations" SB RAS, using an AVANCE III HD 700 MHz NMR spectrometer (Bruker BioSpin, Rheinstetten, Germany). NMR spectra for each sample were acquired in a standard 5 mm glass NMR tube using a 5 mm TXI ATMA NMR probe. We used 70-degree detection pulse (pulse sequence name zg) and summed 64 free induction decay (FID) signals while maintaining the sample temperature at 25°C. For two ISF samples with volumes below 100 µl, we collected 128 FIDs to improve the signal-to-noise ratio. Prior to acquisition, low-power radiation was applied at the water resonance frequency to presaturate the water signal. To allow for the relaxation of all spins, a repetition time of 6 seconds was used between scans. Identification and quantification of metabolites in NMR data Metabolite identification was conducted by analyzing their NMR spectra, which were sourced from literature, databases (HMDB, METLIN, BMRB, and SpectraBase), an in-house NMR library (AMDB). Baseline processing, identification, and integration of spectral NMR peaks (quantification) were performed using MestReNova v12.0 (Mestrelab Research, A Coruna, Spain). In instances where NMR signal assignment was not straightforward, the identification of metabolites was verified by spiking extracts with commercially available standard compounds. Despite these efforts, several signals in the NMR spectra remained unassigned. The metabolite concentrations in samples were determined in µM by integrating NMR signals relative to the internal standard DSS, and then normalized to the biofluid volume. On average, 60-80 compounds were identified in samples. However, quantifying some compounds was unreliable due to weak signals or overlapping with other signals. The final table contains only 51 reliably identified and quantified metabolites. The raw data could contain more information on as yet unidentified metabolites.

Sampleprep ID:

SP003642

Sampleprep Summary:

Sample Preparation For the preparation of extracts from blood serum for metabolomic measurements, we adhered to a standard protocol. Serum volume was 300 μl, ISF volume varied from 50 to 200 μl. Briefly, after thawing human blood plasma, we removed the clot from the vial, thus obtaining blood serum. Then, we added 300 μL of H2O, 600 μL of cold (-20 °C) methanol and 600 μL of cold (-20 °C) chloroform to 300 µL of serum. The mixture was then stirred on a shaker at +4 °C for 15 minutes, followed by incubation at -20 °C for 30 minutes. Subsequently, the mixture was centrifuged at 16,100×g for 30 minutes at +4 °C. Upon centrifugation, the mixture separated into two immiscible phases. The upper water-methanol phase was collected and vacuum dried overnight. NMR Measurements The dried extracts were dissolved in 600 µL of D2O containing 20 µM of DSS (sodium 4,4-dimethyl-4-silapentane-1-sulfonic acid) as an internal standard and 50 mM of deuterated phosphate buffer (pH 7.2). The 1H NMR measurements were conducted at the Center of Collective Use "Mass Spectrometric Investigations" SB RAS, using an AVANCE III HD 700 MHz NMR spectrometer (Bruker BioSpin, Rheinstetten, Germany). NMR spectra for each sample were acquired in a standard 5 mm glass NMR tube using a 5 mm TXI ATMA NMR probe. We used 70-degree detection pulse (pulse sequence name zg) and summed 64 free induction decay (FID) signals while maintaining the sample temperature at 25°C. For two ISF samples with volumes below 100 µl, we collected 128 FIDs to improve the signal-to-noise ratio. Prior to acquisition, low-power radiation was applied at the water resonance frequency to presaturate the water signal. To allow for the relaxation of all spins, a repetition time of 6 seconds was used between scans. Identification and quantification of metabolites in NMR data Metabolite identification was conducted by analyzing their NMR spectra, which were sourced from literature, databases (HMDB, METLIN, BMRB, and SpectraBase), an in-house NMR library (AMDB). Baseline processing, identification, and integration of spectral NMR peaks (quantification) were performed using MestReNova v12.0 (Mestrelab Research, A Coruna, Spain). In instances where NMR signal assignment was not straightforward, the identification of metabolites was verified by spiking extracts with commercially available standard compounds. Despite these efforts, several signals in the NMR spectra remained unassigned. The metabolite concentrations in samples were determined in µM by integrating NMR signals relative to the internal standard DSS, and then normalized to the biofluid volume. On average, 60-80 compounds were identified in samples. However, quantifying some compounds was unreliable due to weak signals or overlapping with other signals. The final table contains only 51 reliably identified and quantified metabolites. The raw data could contain more information on as yet unidentified metabolites.

Analysis:

Analysis ID:	AN005756
Laboratory Name:	Laboratory of proteomics and metabolomics
Analysis Type:	NMR
Num Factors:	3
Num Metabolites:	49
Units:	uM

NMR:

NMR ID:	NM000291
Analysis ID:	AN005756
Instrument Name:	AVANCE III HD 700 MHz NMR spectrometer (Bruker BioSpin)
Instrument Type:	FT-NMR
NMR Experiment Type:	1D-1H
Spectrometer Frequency:	700 MHz
NMR Probe:	5 mm TXI ATMA
NMR Solvent:	50 mM of deuterated phosphate buffer (pH 7.2)
NMR Tube Size:	5 mm
Pulse Sequence:	zg
Water Suppression:	presat
Temperature:	25
Number Of Scans:	64