Limits...
A metabolic study on colon cancer using (1)h nuclear magnetic resonance spectroscopy.

Zamani Z, Arjmand M, Vahabi F, Eshaq Hosseini SM, Fazeli SM, Iravani A, Bayat P, Oghalayee A, Mehrabanfar M, Haj Hosseini R, Tashakorpour M, Tafazzoli M, Sadeghi S - Biochem Res Int (2014)

Bottom Line: Discussion.Our observations corroborated earlier studies that suggest the importance of lowering serum LCA/DCA and increasing vitamin B6 intake to help prevent colon cancer.This work can be looked upon as a preliminary step in using (1)HNMR analysis as a screening test before invasive procedures.

View Article: PubMed Central - PubMed

Affiliation: Biochemistry Department, Pasteur Institute of Iran, Tehran 1316943551, Iran.

ABSTRACT
Background. Colorectal carcinoma is the third cause of cancer deaths in the world. For diagnosis, invasive methods like colonoscopy and sigmoidoscopy are used, and noninvasive screening tests are not very accurate. We decided to study the potential of (1)HNMR spectroscopy with metabolomics and chemometrics as a preliminary noninvasive test. We obtained a distinguishing pattern of metabolites and metabolic pathways between colon cancer patient and normal. Methods. Sera were obtained from confirmed colon cancer patients and the same number of healthy controls. Samples were sent for (1)HNMR spectroscopy and analysis was carried out Chenomex and MATLAB software. Metabolites were identified using Human Metabolic Data Base (HDMB) and the main metabolic cycles were identified using Metaboanalyst software. Results. 15 metabolites were identified such as pyridoxine, orotidine, and taurocholic acid. Main metabolic cycles involved were the bile acid biosynthesis, vitamin B6 metabolism, methane metabolism, and glutathione metabolism. Discussion. The main detected metabolic cycles were also reported earlier in different cancers. Our observations corroborated earlier studies that suggest the importance of lowering serum LCA/DCA and increasing vitamin B6 intake to help prevent colon cancer. This work can be looked upon as a preliminary step in using (1)HNMR analysis as a screening test before invasive procedures.

No MeSH data available.


Related in: MedlinePlus

Score plot of PLS after OSC shows very good separation of samples. Odd numbers indicate normal and even numbers patient samples.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4150403&req=5

fig1: Score plot of PLS after OSC shows very good separation of samples. Odd numbers indicate normal and even numbers patient samples.

Mentions: PLS was applied after OSC using the Y matrix including 0 for normal and 1 for abnormal for all the data set. PLS was performed with and without OSC and results were obtained with more than 95% confidence level. Figures 1 and 2 show a complete separation pattern between the colon cancer and the normal groups. Figure 3 shows loading plot of the samples which is an indicator of ascending and descending level of metabolites. With the help of the numbers and chemical shifts, 13 metabolites were identified as shown in Table 1. 15 metabolic pathways were detected from the above-differentiating metabolites after an enrichment analysis was carried out in Figure 4. Overrepresentation analysis, as shown in Table 2, was done to detect the impact of pathways, depending on the number of changed metabolites and to test if a particular group of compounds is represented more than expected by chance within the user uploaded compound list in the Metaboanalyst software. In the context of pathway analysis, compounds involved in a particular pathway are enriched and compared by random hits as tested. The detailed results from the pathway analysis are depicted in Table 2, and, since many pathways are tested at the same time, the statistical P values from enrichment analysis are further adjusted for multiple tests.


A metabolic study on colon cancer using (1)h nuclear magnetic resonance spectroscopy.

Zamani Z, Arjmand M, Vahabi F, Eshaq Hosseini SM, Fazeli SM, Iravani A, Bayat P, Oghalayee A, Mehrabanfar M, Haj Hosseini R, Tashakorpour M, Tafazzoli M, Sadeghi S - Biochem Res Int (2014)

Score plot of PLS after OSC shows very good separation of samples. Odd numbers indicate normal and even numbers patient samples.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4150403&req=5

fig1: Score plot of PLS after OSC shows very good separation of samples. Odd numbers indicate normal and even numbers patient samples.
Mentions: PLS was applied after OSC using the Y matrix including 0 for normal and 1 for abnormal for all the data set. PLS was performed with and without OSC and results were obtained with more than 95% confidence level. Figures 1 and 2 show a complete separation pattern between the colon cancer and the normal groups. Figure 3 shows loading plot of the samples which is an indicator of ascending and descending level of metabolites. With the help of the numbers and chemical shifts, 13 metabolites were identified as shown in Table 1. 15 metabolic pathways were detected from the above-differentiating metabolites after an enrichment analysis was carried out in Figure 4. Overrepresentation analysis, as shown in Table 2, was done to detect the impact of pathways, depending on the number of changed metabolites and to test if a particular group of compounds is represented more than expected by chance within the user uploaded compound list in the Metaboanalyst software. In the context of pathway analysis, compounds involved in a particular pathway are enriched and compared by random hits as tested. The detailed results from the pathway analysis are depicted in Table 2, and, since many pathways are tested at the same time, the statistical P values from enrichment analysis are further adjusted for multiple tests.

Bottom Line: Discussion.Our observations corroborated earlier studies that suggest the importance of lowering serum LCA/DCA and increasing vitamin B6 intake to help prevent colon cancer.This work can be looked upon as a preliminary step in using (1)HNMR analysis as a screening test before invasive procedures.

View Article: PubMed Central - PubMed

Affiliation: Biochemistry Department, Pasteur Institute of Iran, Tehran 1316943551, Iran.

ABSTRACT
Background. Colorectal carcinoma is the third cause of cancer deaths in the world. For diagnosis, invasive methods like colonoscopy and sigmoidoscopy are used, and noninvasive screening tests are not very accurate. We decided to study the potential of (1)HNMR spectroscopy with metabolomics and chemometrics as a preliminary noninvasive test. We obtained a distinguishing pattern of metabolites and metabolic pathways between colon cancer patient and normal. Methods. Sera were obtained from confirmed colon cancer patients and the same number of healthy controls. Samples were sent for (1)HNMR spectroscopy and analysis was carried out Chenomex and MATLAB software. Metabolites were identified using Human Metabolic Data Base (HDMB) and the main metabolic cycles were identified using Metaboanalyst software. Results. 15 metabolites were identified such as pyridoxine, orotidine, and taurocholic acid. Main metabolic cycles involved were the bile acid biosynthesis, vitamin B6 metabolism, methane metabolism, and glutathione metabolism. Discussion. The main detected metabolic cycles were also reported earlier in different cancers. Our observations corroborated earlier studies that suggest the importance of lowering serum LCA/DCA and increasing vitamin B6 intake to help prevent colon cancer. This work can be looked upon as a preliminary step in using (1)HNMR analysis as a screening test before invasive procedures.

No MeSH data available.


Related in: MedlinePlus