Serum metabolomics analysis of colon cancer
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo Sapiens
SUBMITTER: 
Shuting Yu
PROVIDER: PXD075480 | iProX | Wed Mar 11 00:00:00 GMT 2026
REPOSITORIES: iProX
Similar Datasets
Project description:<p>In this era of precision medicine, there is an increasingly urgent need for highly sensitive tests for detecting tumors such as colon cancer (CC), a silent disease where the first symptoms may take 10-15 yr to appear. Mass spectrometry-based lipidomics is an emerging tool for such clinical diagnosis. We used ultra-performance liquid chromatography coupled to electrospray ionization quadrupole time-of-flight mass spectrometry operating in high energy collision spectral acquisition mode (MSE) mode (UPLC-QTOF-MSE) and gas chromatography (GC) to investigate differences between the plasmatic lipidic composition of CC patients and control (CTR) subjects. Key enzymes in lipidic metabolism were investigated using immuno-based detection assays. Our partial least squares discriminant analysis (PLS-DA) resulted in a suitable discrimination between CTR and CC plasma samples. 42 statistically significant discriminating lipids were putatively identified. Ether lipids showed a prominent presence and accordingly, a decrease in glyceronephosphate O-acyltransferase (GNPAT) enzyme activity was found. A receiver operating characteristic (ROC) curve built for three plasmalogens of phosphatidylserine (PS), named PS(P-36:1), PS(P-38:3) and PS(P-40:5), presented an area under the curve (AUC) of 0.998, and sensitivity and specificity of 100 and 85.7% respectively. These results show significant differences in CC patients' plasma lipid composition that may be useful in discriminating them from CTR individuals with a special role for plasmalogens.</p>
2023-11-13 | MTBLS1584 | MetaboLights
Project description:We used Sequence-Scope (Seq-Scope), which can generate ultra-high definition images of sequence-based molecular signatures resolved at a submicrometer scale, for profiling spatial transcriptome associated with biopsy-associated colon injury. Raw 1st-Seq FASTQ with intact tile and coordinate information could be retrieved from https://doi.org/10.5281/zenodo.13118097
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Project description:From a clinical and molecular perspective, colon cancer (CC) is a heterogeneous disease but to date no classification based on high-density transcriptome data has been established. The aim of this study was to build up a robust molecular classification of mRNA expression profiles (Affymetrix U133Plus2) of a large series of 443 CC and to validate it on an independent serie of 123 CC and 906 public dataset. We identified and validated six molecular subtypes in this large cohort as a combination of multiple molecular processes that complement current disease stratification based on clinicopathological variables and molecular markers. The biological relevance of these subtypes was consolidated by significant differences in survival. These insights open new perspectives for improving prognostic models and targeted therapies. Among a large series of colon cancers collected for the Cartes d'Identité des Tumeurs (CIT) program from the French Ligue Nationale Contre le Cancer (http://cit.ligue-cancer.net), 566 were analyzed for mRNA expression profiles using Affymetrix U133plus2 chip and, among theses, 463 could also be analyzed for DNA alteration profiles using the CGH Array ( CIT-CGHarray V6). The 566 tumors was divided into a discovery dataset of 443 CC and a validation dataset of 123 CC.
2013-05-22 | E-GEOD-39582 | biostudies-arrayexpress
Project description:From a clinical and molecular perspective, colon cancer (CC) is a heterogeneous disease but to date no classification based on high-density transcriptome data has been established. The aim of this study was to build up a robust molecular classification of mRNA expression profiles (Affymetrix U133Plus2) of a large series of 443 CC and to validate it on an independent serie of 123 CC and 906 public dataset. We identified and validated six molecular subtypes in this large cohort as a combination of multiple molecular processes that complement current disease stratification based on clinicopathological variables and molecular markers. The biological relevance of these subtypes was consolidated by significant differences in survival. These insights open new perspectives for improving prognostic models and targeted therapies. Among a large series of colon cancers collected for the Cartes d'Identité des Tumeurs (CIT) program from the French Ligue Nationale Contre le Cancer (http://cit.ligue-cancer.net), 566 were analyzed for mRNA expression profiles using Affymetrix U133plus2 chip and, among theses, 463 could also be analyzed for DNA alteration profiles using the CGH Array ( CIT-CGHarray V6). The 566 tumors was divided into a discovery dataset of 443 CC and a validation dataset of 123 CC.
2013-05-22 | E-GEOD-40966 | biostudies-arrayexpress
Project description:From a clinical and molecular perspective, colon cancer (CC) is a heterogeneous disease but to date no classification based on high-density transcriptome data has been established. The aim of this study was to build up a robust molecular classification of mRNA expression profiles (Affymetrix U133Plus2) of a large series of 443 CC and to validate it on an independent serie of 123 CC and 906 public dataset. We identified and validated six molecular subtypes in this large cohort as a combination of multiple molecular processes that complement current disease stratification based on clinicopathological variables and molecular markers. The biological relevance of these subtypes was consolidated by significant differences in survival. These insights open new perspectives for improving prognostic models and targeted therapies.
2013-05-22 | GSE40966 | GEO
Project description:This is a transcriptomics analysis contributing to a bigger project that tries to shed light on the role of type 2 diabetes mellitus (T2DM) as a risk factor for colon cancer (CC). Here we present a gene expression screening of paired tumor and normal colon mucosa samples in a cohort of 42 CC patients, 23 of them with T2DM. Using gene set enrichment, we identified an unexpected overlap of pathways over-represented in diabetics compared to non-diabetics, both in tumor and normal mucosa, including diabetes-related metabolic and signaling processes. An integration with other -omic studies suggests that in diabetics, the local micro-environment in normal colon mucosa may be a factor driving field cancerization which may promote carcinogenesis. Several of these pathways converged on the tumor initiation axis TEAD/YAP-TAZ. Cell culture studies confirmed that high glucose concentrations upregulate this pathway in non-tumor colon cells. In conclusion, diabetes is associated to deregulation of cancer-related processes in normal colon mucosa adjacent to tissue which has undergone a malignant transformation. These data support the existence of the field of cancerization paradigm in diabetes and set a new framework to study link between diabetes and cancer.
2019-01-16 | GSE115313 | GEO
Project description:From a clinical and molecular perspective, colon cancer (CC) is a heterogeneous disease but to date no classification based on high-density transcriptome data has been established. The aim of this study was to build up a robust molecular classification of mRNA expression profiles (Affymetrix U133Plus2) of a large series of 443 CC and 19 non-tumoral colorectal mucosas, and to validate it on an independent serie of 123 CC and 906 public dataset. We identified and validated six molecular subtypes in this large cohort as a combination of multiple molecular processes that complement current disease stratification based on clinicopathological variables and molecular markers. The biological relevance of these subtypes was consolidated by significant differences in survival. These insights open new perspectives for improving prognostic models and targeted therapies.
2013-05-22 | GSE39582 | GEO
Project description:This is a transcriptomics analysis contributing to a bigger project that tries to shed light on the role of type 2 diabetes mellitus (T2DM) as a risk factor for colon cancer (CC). Here we present a gene expression screening of 7 colon tumor xenograft samples, 2 with diabetic mice and 5 with normal blood glucose levels. For xenograft model details see: Prieto I, et al. (2017) Colon cancer modulation by a diabetic environment: A single institutional experience. PLoS One 12(3):e0172300
2019-01-16 | GSE115329 | GEO
Project description:Elevated levels of circulating C-reactive protein (CRP) are associated with worse outcome for patients with colorectal cancer (CRC). Monomeric CRP (mCRP) has been demonstrated in tissues of various diseases, including colon cancer (CC). mCRP possesses proinflammatory properties and potentially contributes to tumour-promoting inflammation. Although considered tissue-based, mCRP can exist in the circulation bound to membranes or as aggregates. This project aimed to detect and quantify circulating mCRP in CC patients by mass spectrometry.
2025-06-16 | PXD046746 | Pride
Project description:BACKGROUND: Several in vitro assays have been used to identify “cancer stem cells” (CSC), including expression of cell surface markers and Hoechst dye efflux properties. However, each of these methods has potential pitfalls that complicate interpretation of the results. Focusing on colon cancers (CC), the CD133 antigen has been proposed as a marker of colon CSC. However, conflicting results have been reported in the literature indicating the need of a systematic analysis of CSC within CC and a complete validation of markers for the isolation of these cells. AIMS: Aim of this study was to confirm that CD133 expression is a valid method for isolating CSC in CC and verify if other antigens can increase the specificity of this marker for isolating CSC in CC. METHODS: CD133+ and CD133- cells were isolated from different human CC lines (CaCo-2, HT29, LOVO, HCT-116) by FACS sorter and the tumor-initiating potential of CD133+ cells was assessed in vitro, by soft-agar colony formation assay, and in vivo, upon transplantation into nude mice. Furthermore, the gene expression profile of CD133+ versus CD133- CaCo-2 cells was compared by the means of microarray analysis. Then, in the effort to identify a common “tumor stem cell” signature for CC, the most relevant transcripts resulting from gene expression profiling on CD133+ cells was assessed by real-time PCR on SP-fraction isolated by FACS sorter from the same CC cell lines. Finally, we deplete CD133 expression in the CaCo-2 cell line by the means of siRNA and verified by Western Blot analysis whether there was a functional correlation between CD133 and the target genes. Moreover, CaCo-2 and HCT116 cells were exposed to sodium butyrate (NaBu) for 72h. Colon cells differentiation was assessed by Alkaline phosphatase activity and expression of CD133 and target genes was tested by western blot. RESULTS: We confirmed that only CD133+ cells have a tumor-initiating potential in vitro and in vivo. Furthermore, microarray analysis of CD133+ versus CD133- CaCo-2 cells revealed a significant overexpression of various transcripts involved in cell proliferation, invasion and stemness in CD133+ cell fraction. Comparison of the transcripts by real-time PCR revealed that the genes of Endothelin-1 (END-1) and NR4A2 are highly expressed in both CD133 + cells and in SP fractions. Finally, when we deplete CD133 expression in Caco-2cells by siRNA, we observed a significant attenuation of END-1 and NR4A2 expression, thus demonstrating that CD133 is involved in the transcriptional regulation of these genes. Interestingly, we also showed that the expression of all three genes was inversely correlated with cell differentiation status as demonstrated by the fact that their expression decreases in a time- and dose-dependent manner after differentiation induced by NaBu. CONCLUSION: Overall, this study confirms the role of CD133antigen as CSC marker and showed for the first time the existence of a functional relationship between CD133, END-1 and NR4A2 expression, hypothesizing that CD133 is involved in the transcriptional regulation of these gene.
2011-01-04 | GSE24747 | GEO