Background: Adjuvant chemotherapy improves survival in stage II and III CRC, although a significant proportion of patients (pts) are cured by surgery alone. Improved risk stratification is required to reduce the number of pts treated unnecessarily, particularly in elderly populations at risk for higher toxicity. Serum metabolomic profiles may act as biomarkers of residual (micrometastatic) disease, a prerequisite for relapse, and have been prognostic in other tumor types. This study aims to (1) identify in elderly pts a metabolomic “signature” for metastatic disease (mCRC) that differentiates it from early disease (eCRC) and (2) create a metabolomic index for eCRC pts that correlates with clinical outcomes and may be predictive for relapse. Methods: Serum samples from 105 elderly pts (aged ≥ 70) with CRC, (48 mCRC and 57 eCRC with ≥ 5 years follow up) were pooled from 4 previous clinical trials. Samples were analyzed via Proton Nuclear Magnetic Resonance (NMR) and the spectra were used to characterize the metabolic profiles of the two cohorts. Principal component analysis (PCA) and canonical analysis (CA) were applied to obtain the supervised separation of eCRC and mCRC spectra. For the purpose of classification, the K-nearest neighbors (k-NN) method was applied to the PCA-CA scores. Wilcoxon test was then used to compare the levels of 34 quantified metabolites between eCRC and mCRC pts. A model that assigns a risk score is being built based on the degree to which an eCRC serum profile resembles the metastatic profiles. This risk score will be compared to the Adjuvant!Online estimated risk of relapse score and the actual outcome. Results: PCA-CA-kNN classification of NMR spectra was able to discriminate eCRC and mCRC with an accuracy of 74%. Four metabolites (2-methylbutyrate, 2-methylsuccinate, histidine and formate) were found to differ significantly (p < 0.05) between eCRC and mCRC metabolomic profiles. Conclusions: NMR metabolomic profiles can discriminate early and metastatic CRC. A model to assess the likelihood of relapse, based on the degree to which an eCRC serum profile resembles the metastatic profiles, is being built, and results will be presented at the meeting.

Serum metabolomics as biomarkers to differentiate early from metastatic disease and predict relapse in elderly colorectal cancer (CRC) patients / Mislang, Anna Rachelle; Vignoli, Alessia; Donato, Samantha Di; Hart, Christopher; Biagioni, Chiara; Vitale, Stefania; Mori, Elena; Becheri, Dimitri; Monte, Francesca Del; Luchinat, Claudio; Leo, Angelo Di; Mottino, Giuseppe; Tenori, Leonardo; Biganzoli, Laura. - In: JOURNAL OF CLINICAL ONCOLOGY. - ISSN 1527-7755. - STAMPA. - (2016), pp. 0-0. [10.1200/JCO.2016.34.15_suppl.10042]

Serum metabolomics as biomarkers to differentiate early from metastatic disease and predict relapse in elderly colorectal cancer (CRC) patients.

VIGNOLI, ALESSIA;BIAGIONI, CHIARA;MORI, ELENA;BECHERI, DIMITRI;LUCHINAT, CLAUDIO;TENORI, LEONARDO;
2016

Abstract

Background: Adjuvant chemotherapy improves survival in stage II and III CRC, although a significant proportion of patients (pts) are cured by surgery alone. Improved risk stratification is required to reduce the number of pts treated unnecessarily, particularly in elderly populations at risk for higher toxicity. Serum metabolomic profiles may act as biomarkers of residual (micrometastatic) disease, a prerequisite for relapse, and have been prognostic in other tumor types. This study aims to (1) identify in elderly pts a metabolomic “signature” for metastatic disease (mCRC) that differentiates it from early disease (eCRC) and (2) create a metabolomic index for eCRC pts that correlates with clinical outcomes and may be predictive for relapse. Methods: Serum samples from 105 elderly pts (aged ≥ 70) with CRC, (48 mCRC and 57 eCRC with ≥ 5 years follow up) were pooled from 4 previous clinical trials. Samples were analyzed via Proton Nuclear Magnetic Resonance (NMR) and the spectra were used to characterize the metabolic profiles of the two cohorts. Principal component analysis (PCA) and canonical analysis (CA) were applied to obtain the supervised separation of eCRC and mCRC spectra. For the purpose of classification, the K-nearest neighbors (k-NN) method was applied to the PCA-CA scores. Wilcoxon test was then used to compare the levels of 34 quantified metabolites between eCRC and mCRC pts. A model that assigns a risk score is being built based on the degree to which an eCRC serum profile resembles the metastatic profiles. This risk score will be compared to the Adjuvant!Online estimated risk of relapse score and the actual outcome. Results: PCA-CA-kNN classification of NMR spectra was able to discriminate eCRC and mCRC with an accuracy of 74%. Four metabolites (2-methylbutyrate, 2-methylsuccinate, histidine and formate) were found to differ significantly (p < 0.05) between eCRC and mCRC metabolomic profiles. Conclusions: NMR metabolomic profiles can discriminate early and metastatic CRC. A model to assess the likelihood of relapse, based on the degree to which an eCRC serum profile resembles the metastatic profiles, is being built, and results will be presented at the meeting.
2016
Mislang, Anna Rachelle; Vignoli, Alessia; Donato, Samantha Di; Hart, Christopher; Biagioni, Chiara; Vitale, Stefania; Mori, Elena; Becheri, Dimitri; Monte, Francesca Del; Luchinat, Claudio; Leo, Angelo Di; Mottino, Giuseppe; Tenori, Leonardo; Biganzoli, Laura
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1090979
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