Summary of Study ST003599

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 PR002227. The data can be accessed directly via it's Project DOI: 10.21228/M8RR8B 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.

Perform statistical analysis  |  Show all samples  |  Show named metabolites  |  Download named metabolite data  
Download mwTab file (text)   |  Download mwTab file(JSON)   |  Download data files (Contains raw data)
Study IDST003599
Study TitleMulti-omic profiling of squamous cell lung cancer identifies metabolites and related genes associated with squamous cell carcinoma
Study SummarySquamous cell lung carcinoma (SqCC) is the second most common histological subtype of lung cancer. Besides tumor-initiating and promoting DNA, RNA, and epigenetic alterations, aberrant cell metabolism is a hallmark of carcinogenesis. This study aimed to identify SqCC-specific metabolites and key gene regulators that could eventually be used as new anticancer targets. Transcriptional, proteomic, and metabolomic data were gathered for a cohort of resected lung cancers. SqCC-specific differentially expressed genes were integrated with proteogenomic and metabolic data using genome scale metabolic models (GEMs). Findings were validated in cohorts of tumors, normal specimens, and cell lines. In-situ protein expression of SLC6A8 was investigated. Differential gene expression analysis identified a list of 280 strictly SqCC-specific genes. Metabolic profiling identified 7 SqCC-specific metabolites, of which increased creatine and decreased phosphocholine levels matched to SqCC-specific expression of SLC6A8 and CHKA, by matching genes to metabolites through genome scale metabolic models (GEMs) and the Reactome pathways database. Expression of both genes appeared tumor cell-associated, and in particular, the elevated expression of SLC6A8 identified SqCC also in stage IV disease. Elevated creatine levels and overexpression of its transporter SLC6A8 appear a distinct metabolic feature of SqCC. Considering ongoing clinical trials in other malignancies, exploring SLC6A8-inhibition in SqCC appears motivated based on a metabolic addiction hypothesis.
Institute
Lund University
Departmentoncology
LaboratoryMaria Planck and Johan Staaf
Last NameArbajian
First NameElsa
AddressMedicin Village 404, 22381 Lund, SWEDEN
Emailelsa.arbajian@med.lu.se
Phone0046700253200
Submit Date2024-11-26
Total Subjects73
Raw Data AvailableYes
Raw Data File Type(s)mzML, raw(Thermo)
Analysis Type DetailLC-MS
Release Date2025-07-25
Release Version1
Elsa Arbajian Elsa Arbajian
https://dx.doi.org/10.21228/M8RR8B
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

Select appropriate tab below to view additional metadata details:

Project:

Project ID:PR002227
Project DOI:doi: 10.21228/M8RR8B
Project Title:Multi-omic profiling of squamous cell lung cancer identifies metabolites and related genes associated with squamous cell carcinoma
Project Summary:Squamous cell lung carcinoma (SqCC) is the second most common histological subtype of lung cancer. Besides tumor-initiating and promoting DNA, RNA, and epigenetic alterations, aberrant cell metabolism is a hallmark of carcinogenesis. This study aimed to identify SqCC-specific metabolites and key gene regulators that could eventually be used as new anticancer targets. Transcriptional, proteomic, and metabolomic data were gathered for a cohort of resected lung cancers. SqCC-specific differentially expressed genes were integrated with proteogenomic and metabolic data using genome scale metabolic models (GEMs). Findings were validated in cohorts of tumors, normal specimens, and cell lines. In-situ protein expression of SLC6A8 was investigated. Differential gene expression analysis identified a list of 280 strictly SqCC-specific genes. Metabolic profiling identified 7 SqCC-specific metabolites, of which increased creatine and decreased phosphocholine levels matched to SqCC-specific expression of SLC6A8 and CHKA, by matching genes to metabolites through genome scale metabolic models (GEMs) and the Reactome pathways database. Expression of both genes appeared tumor cell-associated, and in particular, the elevated expression of SLC6A8 identified SqCC also in stage IV disease. Elevated creatine levels and overexpression of its transporter SLC6A8 appear a distinct metabolic feature of SqCC. Considering ongoing clinical trials in other malignancies, exploring SLC6A8-inhibition in SqCC appears motivated based on a metabolic addiction hypothesis.
Institute:Lund University
Department:Oncology
Laboratory:Maria Planck and Johan Staaf
Last Name:Arbajian
First Name:Elsa
Address:Medicon Village 404, 22381 Lund, SWEDEN
Email:elsa.arbajian@med.lu.se
Phone:0046700253200

Subject:

Subject ID:SU003728
Subject Type:Human
Subject Species:Homo sapiens
Taxonomy ID:9606
Species Group:Mammals

Factors:

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

mb_sample_id local_sample_id Group_Histology
SA392407JS-51AC
SA392408JS-32AC
SA392409JS-33AC
SA392410JS-35AC
SA392411JS-36AC
SA392412JS-40AC
SA392413JS-41AC
SA392414JS-43AC
SA392415JS-44AC
SA392416JS-48AC
SA392417JS-49AC
SA392418JS-55AC
SA392419JS-27AC
SA392420JS-56AC
SA392421JS-57AC
SA392422JS-59AC
SA392423JS-63AC
SA392424JS-64AC
SA392425JS-66AC
SA392426JS-68AC
SA392427JS-71AC
SA392428JS-72AC
SA392429JS-73AC
SA392430JS-31AC
SA392431JS-01AC
SA392432JS-26AC
SA392433JS-17AC
SA392434JS-05AC
SA392435JS-06AC
SA392436JS-08AC
SA392437JS-09AC
SA392438JS-13AC
SA392439JS-15AC
SA392440JS-14AC
SA392441JS-21AC
SA392442JS-22AC
SA392443JS-23AC
SA392444JS-58LCC
SA392445JS-42LCC
SA392446JS-70LCC
SA392447JS-07LCC
SA392448JS-16LCC
SA392449JS-34LCC
SA392450JS-50LCC
SA392451JS-65LCC
SA392452JS-25LCC
SA392453JS-24LCC
SA392454JS-39LCNEC
SA392455JS-03LCNEC
SA392456JS-29LCNEC
SA392457JS-69LCNEC
SA392458JS-67LCNEC
SA392459JS-61LCNEC
SA392460JS-11LCNEC
SA392461JS-46LCNEC
SA392462JS-19LCNEC
SA392463JS-53LCNEC
SA392464JS-12SqCC
SA392465JS-04SqCC
SA392466JS-18SqCC
SA392467JS-02SqCC
SA392468JS-45SqCC
SA392469JS-30SqCC
SA392470JS-28SqCC
SA392471JS-47SqCC
SA392472JS-20SqCC
SA392473JS-52SqCC
SA392474JS-62SqCC
SA392475JS-54SqCC
SA392476JS-60SqCC
SA392477JS-10SqCC
SA392478JS-37SqCC
SA392479JS-38SqCC
Showing results 1 to 73 of 73

Collection:

Collection ID:CO003721
Collection Summary:Tumor pieces were collected from patients with early-stage lung cancer undergoing tumor removal surgery at the Skåne University Hospital in Lund. The samples were fresh frozen and kept at -80℃.
Sample Type:Lung
Storage Conditions:-80℃

Treatment:

Treatment ID:TR003737
Treatment Summary:The patients included in this study underwent surgical removal of their lung tumors, they had not been subjected to neoadjuvant cancer treatment.

Sample Preparation:

Sampleprep ID:SP003735
Sampleprep Summary:Metabolite extraction solution (50% methanol, 30% acetonitrile, 20% ultrapure water, 5 µM final concentration valine-d8) was added to each sample tube and incubated at -20°C for one hour. The samples were placed on a Thermomixer for 15 min at 4°C and maximum speed . After final centrifugation at max speed for 10 min at 4°C, the supernatants were transferred into LC-MS vials and kept at -80°C prior to mass spectrometry analysis

Chromatography:

Chromatography ID:CH004491
Instrument Name:Thermo Dionex Ultimate 3000
Column Name:SeQuant ZIC-HILIC (150 x 2.1mm,5um)
Column Temperature:40°C
Flow Gradient:0-2 min: 80% B; 2-17 min: linear gradient from 80% B to 20% B; 17-17.1 min: linear gradient from 20% B to 80% B; 17.1-22.5min: hold at 80% B
Flow Rate:0.200 mL/min
Solvent A:100% Water; 20 mM ammonium carbonate; 0.05% ammonium hydroxide
Solvent B:100% Acetonitrile
Chromatography Type:HILIC

Analysis:

Analysis ID:AN005914
Analysis Type:MS
Chromatography ID:CH004491
Num Factors:4
Num Metabolites:139
Units:peak area
  logo