Metabolomic NMR Fingerprinting to Identify and Predict Survival of Patients with Metastatic Colorectal Cancer

• Published in: Cancer research (Chicago, Ill.) Vol. 72; no. 1; pp. 356 - 364
• Main Authors: BERTINI, Ivano, CACCIATORE, Stefano, JENSEN, Benny V, SCHOU, Jakob V, JOHANSEN, Julia S, KRUHØFFER, Mogens, LUCHINAT, Claudio, NIELSEN, Dorte L, TURANO, Paola
• Format: Journal Article
• Language: English
• Published: Philadelphia, PA American Association for Cancer Research 2012
• Subjects: Adult; Antineoplastic agents; Biological and medical sciences; Case-Control Studies; Colorectal Neoplasms - metabolism; Colorectal Neoplasms - pathology; Female; Gastroenterology. Liver. Pancreas. Abdomen; Humans; Male; Medical sciences; Metabolomics; Middle Aged; Neoplasm Metastasis; Nuclear Magnetic Resonance, Biomolecular - methods; Pharmacology. Drug treatments; Stomach. Duodenum. Small intestine. Colon. Rectum. Anus; Survival Analysis; Tumors; Human; Metabolomics; Rectal disease; Colorectal cancer; Patient; Malignant tumor; Metastasis; Survival; Colonic disease; Metabonomics; Fingerprint method; Digestive diseases; Intestinal disease; Advanced stage; Predictive factor; Cancer
• ISSN: 0008-5472; 1538-7445
• DOI: 10.1158/0008-5472.CAN-11-1543

Earlier detection of patients with metastatic colorectal cancer (mCRC) might improve their treatment and survival outcomes. In this study, we used proton nuclear magnetic resonance ((1)H-NMR) to profile the serum metabolome in patients with mCRC and determine whether a disease signature may exist that is strong enough to predict overall survival (OS). In 153 patients with mCRC and 139 healthy subjects from three Danish hospitals, we profiled two independent sets of serum samples in a prospective phase II study. In the training set, (1)H-NMR metabolomic profiling could discriminate patients with mCRC from healthy subjects with a cross-validated accuracy of 100%. In the validation set, 96.7% of subjects were correctly classified. Patients from the training set with maximally divergent OS were chosen to construct an OS predictor. After validation, patients predicted to have short OS had significantly reduced survival (HR, 3.4; 95% confidence interval, 2.06-5.50; P = 1.33 × 10(-6)). A number of metabolites concurred with the (1)H-NMR fingerprint of mCRC, offering insights into mCRC metabolic pathways. Our findings establish that (1)H-NMR profiling of patient serum can provide a strong metabolomic signature of mCRC and that analysis of this signature may offer an independent tool to predict OS.