Metabolomic studies of human gastric cancer: Review

Table 3 Overview of metabolomic studies on gastric cancer

Patients/xenograft model	Sample	Sample size (cancer + control)	Analytical method	Multivariate method	Major findings	Ref.
Both Xenograft model Patients	Urinary sample	33	GC-MS	PCA	Lactic acid, serine, proline, malic acid and fatty acids as potential markers for screening and early diagnosis	[93]
Patients	Serum	60	GC-MS	OPLS-DA	Sarcosine as a potential biomarker for the progression of gastric cancer metastasis	[98]
Patients	Plasma	80	GC-TOF-MS	PLS-DA	Azelaic acid, glutamate, urate, creatinine, threonate as markers for characterizing the precancerous stages and gastric cancer	[97]
Patients	Serum	50	GC-MS	PCA	3-hydroxypropionic acid and pyruvic acids as potential diagnostic markers for gastric cancer	[100]
Patients	Tissue	18	GC-MS with chemical derivatization	PCA	Valine, isoleucine, serine and phosphoserine for diagnosis and staging of gastric cancers	[99]
Xenograft model	Plasma	80	HPLC/Q-TOF-MS	PLS and hierarchical PLS	1-acyl-lysophosphatidylcholines and polyunsaturated fatty acids as potential indicators of chemosensitivity for gastric cancer	[75]
Xenograft model	Urinary sample	24	GC/MS	PCA	Lactic acid, butanedioic acid, malic acid and citric acids as potential markers for cancer screening. Alanine, proline, myo-inositol and glycerol as key markers for identifying cancer metastasis	[91]
Xenograft model	Tissue	22	GC/MS	PCA	Serine and proline metabolism pathways were enriched in cancer metastasis and may help elucidate the complex molecular mechanisms governing metastasis	[90]

PCA: Principal component analysis; PLS: Partial least squares; OPLS-DA: Orthogonal partial least squares discriminant analysis; GC-MS: Gas chromatography-mass spectrometry; PLS-DA: Partial least squares discriminant analysis; GC-TOF-MS: Gas chromatography coupled with time-of-flight mass spectrometry; HPLC/Q-TOF-MS: Uhra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry.