5104 - A metabolomic recurrence score for risk-stratification of elderly patients (pts) with early colorectal cancer (eCRC)

Background

Adjuvant treatment decisions for pts with eCRC are currently based on suboptimal risk stratification factors, especially for elderly pts. Metabolomics measures multiple cancer-related metabolites with potential to identify new biomarkers in this setting. We have shown that serum metabolomics can discriminate pts with eCRC from pts with metastatic CRC (mCRC). We hypothesized that a metabolomic score derived from pts with mCRC may identify pts with eCRC with an increased risk of relapse. This hypothesis was tested in a cohort of elderly pts with eCRC.

Methods

Serum samples from 103 pts aged ≥70 were collected from four clinical trials with 5 years follow up. These samples were derived from 55 pts with eCRC, and 48 with mCRC. Samples were retrospectively analyzed via proton nuclear magnetic resonance (¹H NMR), to assess their metabolomic fingerprints. A Random Forest (RF) classification model was built using a training set of 30 eCRC pts free from relapse at 5 years and all mCRC pts (N = 48). This model was then applied to a validation set constituted by the remaining eCRC pts (10 relapse-free and 15 relapsed). A risk-of-recurrence score was built on the basis of the likelihood of the sample being misclassified as metastatic.

Results

In the eCRC group, 44% (n = 24) received adjuvant chemotherapy, and 27% (n = 15) experienced relapse. In the training set, the RF model discriminated eCRC from mCRC with an accuracy of 74.4%. The RF risk of recurrence score correlated with relapse, with an AUC of 0.754 in ROC analysis. In the training set, by maximizing specificity and sensitivity, a threshold for the RF score was set at 0.55. In the validation set, using this threshold, an AUC of 0.727 in ROC analysis, and a prediction accuracy of 76% (73.3% sensitivity, 80% specificity) were obtained in predicting relapse.

Conclusions

Serum metabolomics performed on post-operative samples of elderly pts with eCRC identifies pts with higher risk of relapse with good accuracy. This may represent a tool to refine risk stratification in this population, to maximize the benefit from adjuvant chemotherapy. Based on these results, a prospective trial is ongoing (LIquid BIopsy and METabolomics in CRC - LIBIMET).

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

The authors.

Funding

Fondazione Sandro Pitigliani per la Lotto Contro i Tumori - ONLUS.

Disclosure

S. Di Donato: Advisory / Consultancy, Travel / Accommodation / Expenses: Amgen; Advisory / Consultancy, Travel / Accommodation / Expenses: Lilly; Advisory / Consultancy, Travel / Accommodation / Expenses: Roche; Advisory / Consultancy, Travel / Accommodation / Expenses: Servier; Travel / Accommodation / Expenses: Celgene; Advisory / Consultancy, Travel / Accommodation / Expenses: Sanofi; Advisory / Consultancy, Travel / Accommodation / Expenses: Bayer. E. Mori: Travel / Accommodation / Expenses: Bayer. L. Malorni: Honoraria (self): AstraZeneca; Advisory / Consultancy: Novartis; Travel / Accommodation / Expenses: Janssen; Honoraria (self), Advisory / Consultancy, Research grant / Funding (self): Pfizer; Travel / Accommodation / Expenses: Roche. D. Becheri: Travel / Accommodation / Expenses: Daiichi-Sankyo; Travel / Accommodation / Expenses: Bristol-Myers Squibb. A. Di Leo: Honoraria (self), Advisory / Consultancy, Research grant / Funding (institution), Travel / Accommodation / Expenses: AstraZeneca; Honoraria (self), Advisory / Consultancy, Travel / Accommodation / Expenses: Bayer; Honoraria (self), Advisory / Consultancy, Travel / Accommodation / Expenses: Celgene; Advisory / Consultancy, Travel / Accommodation / Expenses: Daiichi-Sankyo; Honoraria (self), Advisory / Consultancy, Travel / Accommodation / Expenses: Eisai; Advisory / Consultancy: Genentech; Honoraria (self), Advisory / Consultancy, Travel / Accommodation / Expenses: Genomic Health; Honoraria (self), Advisory / Consultancy, Research grant / Funding (self): Lilly; Honoraria (self), Advisory / Consultancy, Research grant / Funding (self), Travel / Accommodation / Expenses: Novartis; Honoraria (self), Advisory / Consultancy, Research grant / Funding (self), Travel / Accommodation / Expenses: Pfizer; Honoraria (self), Advisory / Consultancy, Travel / Accommodation / Expenses: Pierre Fabre; Advisory / Consultancy, Travel / Accommodation / Expenses: Puma Biotechnology; Honoraria (self), Advisory / Consultancy, Travel / Accommodation / Expenses: Roche. L. Biganzoli: Honoraria (self), Advisory / Consultancy, Travel / Accommodation / Expenses: Astrazeneca; Honoraria (self), Advisory / Consultancy, Research grant / Funding (self), Travel / Accommodation / Expenses: Celgene; Honoraria (self), Advisory / Consultancy, Travel / Accommodation / Expenses: Eisai; Advisory / Consultancy, Research grant / Funding (self), Travel / Accommodation / Expenses: Genomic Health; Honoraria (self), Advisory / Consultancy, Travel / Accommodation / Expenses: Ipsen; Honoraria (self), Advisory / Consultancy, Travel / Accommodation / Expenses: Lilly; Honoraria (self), Advisory / Consultancy, Research grant / Funding (self), Travel / Accommodation / Expenses: Novartis; Honoraria (self), Advisory / Consultancy, Travel / Accommodation / Expenses: Pfizer; Honoraria (self), Advisory / Consultancy, Travel / Accommodation / Expenses: Pierre Fabre; Honoraria (self), Advisory / Consultancy, Travel / Accommodation / Expenses: Roche. All other authors have declared no conflicts of interest.