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Serum metabolomic profile as a means to distinguish stage of colorectal cancer.

ABSTRACT: BACKGROUND: Presently, colorectal cancer (CRC) is staged preoperatively by radiographic tests, and postoperatively by pathological evaluation of available surgical specimens. However, present staging methods do not accurately identify occult metastases. This has a direct effect on clinical management. Early identification of metastases isolated to the liver may enable surgical resection, whereas more disseminated disease may be best treated with palliative chemotherapy. METHODS: Sera from 103 patients with colorectal adenocarcinoma treated at the same tertiary cancer center were analyzed by proton nuclear magnetic resonance (1H NMR) spectroscopy and gas chromatography-mass spectroscopy (GC-MS). Metabolic profiling was done using both supervised pattern recognition and orthogonal partial least squares-discriminant analysis (O-PLS-DA) of the most significant metabolites, which enables comparison of the whole sample spectrum between groups. The metabolomic profiles generated from each platform were compared between the following groups: locoregional CRC (N = 42); liver-only metastases (N = 45); and extrahepatic metastases (N = 25). RESULTS: The serum metabolomic profile associated with locoregional CRC was distinct from that associated with liver-only metastases, based on 1H NMR spectroscopy (P = 5.10 × 10-7) and GC-MS (P = 1.79 × 10-7). Similarly, the serum metabolomic profile differed significantly between patients with liver-only metastases and with extrahepatic metastases. The change in metabolomic profile was most markedly demonstrated on GC-MS (P = 4.75 × 10-5). CONCLUSIONS: In CRC, the serum metabolomic profile changes markedly with metastasis, and site of disease also appears to affect the pattern of circulating metabolites. This novel observation may have clinical utility in enhancing staging accuracy and selecting patients for surgical or medical management. Additional studies are required to determine the sensitivity of this approach to detect subtle or occult metastatic disease.

SUBMITTER: Farshidfar F

PROVIDER: S-EPMC3506908 | biostudies-other | 2012

REPOSITORIES: biostudies-other

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Serum metabolomic profile as a means to distinguish stage of colorectal cancer.

Farshidfar Farshad F Weljie Aalim M AM Kopciuk Karen K Buie W Don WD Maclean Anthony A Dixon Elijah E Sutherland Francis R FR Molckovsky Andrea A Vogel Hans J HJ Bathe Oliver F OF

Genome medicine 20120514 5

<h4>Background</h4>Presently, colorectal cancer (CRC) is staged preoperatively by radiographic tests, and postoperatively by pathological evaluation of available surgical specimens. However, present staging methods do not accurately identify occult metastases. This has a direct effect on clinical management. Early identification of metastases isolated to the liver may enable surgical resection, whereas more disseminated disease may be best treated with palliative chemotherapy.<h4>Methods</h4>Ser ...[more]

PMID: 22583555

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Project description:BackgroundThe Immunoscore predicts prognosis in patients with colorectal cancer (CRC). However, a few studies have incorporated the Immunoscore into the construction of comprehensive prognostic models in CRC, especially stage II CRC. We aimed to construct and validate multidimensional models integrating clinicopathological characteristics and the Immunoscore to predict the prognosis of patients with stage II-III CRC.MethodsPatients (n = 254) diagnosed with stage II-III CRC from 2009 to 2016 were used to generate Cox models for predicting disease-free survival (DFS) and overall survival (OS). The variables included basic clinical indicators, blood inflammatory markers, preoperative tumor biomarkers, mismatch repair status, and the Immunoscore (CD3+ and CD8+ T-cell densities). Univariate and multivariate Cox proportional regressions were used to construct the prognostic models for DFS and OS. We validated the predictive accuracy and ability of the prognostic models in our cohort of 254 patients.ResultsWe constructed two predictive prognostic models with C-index values of 0.6941 for DFS and 0.7138 for OS in patients with stage II-III CRC. The Immunoscore was the most informative predictor of DFS (11.92%), followed by pN stage, carcinoembryonic antigen (CEA), and vascular infiltration. For OS, the Immunoscore was the most informative predictor (8.59%), followed by pN stage, age, CA125, and CEA. Based on the prognostic models, nomograms were developed to predict the 3- and 5-year DFS and OS rates. Patients were divided into three risk groups (low, intermediate, and high) according to the risk scores obtained from the nomogram, and significant differences were observed in the recurrence and survival of the different risk groups (p < 0.0001). Calibration curve and time-dependent receiver operating characteristic (ROC) analysis showed good accuracy of our models. Furthermore, the decision curve analysis indicated that our nomograms had better net benefit than pathological TNM (pTNM) stage within a wide threshold probability. Especially, we developed a website based on our prognostic models to predict the risks of recurrence and death of patients with stage II-III CRC.ConclusionsMultidimensional models including the clinicopathological characteristics and the Immunoscore were constructed and validated, with good accuracy and convenience, to evaluate the risks of recurrence and death of stage II-III CRC patients.

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Serum metabolomic profile as a means to distinguish stage of colorectal cancer.

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Serum metabolomic profile as a means to distinguish stage of colorectal cancer.

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