Search

206 Background: Human serum metabolome profiles have been analyzed to explore the molecular changes that occur with aging. We hypothesized that deep metabolic profiling of sera with different ages would allow the identification of distinct metabolic chronologic patterns as a normal biological baseline to study personal aging. We further hypothesized that metabolic assessment of this chronologic deviation, resulting from advanced precancerous lesion (APL) and stage I/II/III CRC, from the normal reference baseline, would be instrumental for prognosis of relapse revealing underlying pathophysiology. Methods: A cohort of normal (n=3,616, training; n=1,170, testing), 631 advanced adenoma, 1,019 stage I, 404 stage II and 417 stage III serum samples were assembled. Innovative global LCMS metabolomic production were applied to deep profile these subjects. Identification of the age-associated molecular patterns in normal subjects, modeled with an elastic net algorithm, established the reference baseline to mirror a metabolic clock. CRC associated deviation from the precise chronologically paced metabolic patterns was quantified to associate the clinical endpoints of relapse, OSF and PFS, and to identify the tightly associated metabolic pathways. Results: We observed that for those CRCs, the predicted metabolic age can differ from the chronological age with consistent variations, resulting “older” or “younger” metabolic age subgroup in reference to the chronological age. Significant disruptions from the normal baseline were observed in CRCs patients, and consistent stage specific patterns were observed. Outlier, “Older” or “younger” metabolic age subgroup, CRC patients were found with significant future relapse enrichment. Predictive models were derived to case find the patients at risk of future relapse at the CRC diagnosis timepoint. Conclusions: Deviations from the meticulously timed metabolic aging patterns may provide utility to allow prognosis of future clinical endpoints of relapse and overall survival. Close examination of the underlying metabolic pathways, associated with CRC stage specific metabolic patterns, disrupting the baseline ageotypes, not only may improve the sensitivity and specificity of prognostic tests of CRC relapse, but also shed new insights into CRC therapeutics.

3613 Background: One-third of colorectal cancer (CRC) recurs following curative surgery and chemotherapy. Accordingly, novel methods are needed to predict recurrence to enable clinical course mitigating strategies. Serial monitoring of plasma by mass spectrometry (MS) and multi-omics modeling (MMO) of CRC relapse chronology provide the framework for liquid biopsy test development to supersede existing imaging modalities such as CT scans according to relapse related pathologies. We hypothesized that plasma MS and MMO analysis of relapse related pathologies can deconvolute high risk stratification for CRC recurrence within the cancer continuum of care pre/post-surgery and/or pre/post adjuvant chemotherapy (ACT). Methods: 189 CRC patients (Stage I-III) underwent one of three treatment modalities: Modality 1 (Surgery followed by ACT), Modality 2 (Surgery only), Modality 3 (Neoadjuvant chemotherapy followed by surgery and ACT). Plasma samples (n = 441) were collected from patients before surgery, 30 days post-op, and every 3 months until death or month 24 whichever came first. The MMO approach was used to analyze biological features encompassing native peptides, proteins, metabolites, lipids, and ceramides. MMO panels were developed comprising the significantly perturbed features as per the treatment modalities. These panels were used to predict relapse from plasma collected pre-op, 30-day post-op or after adjuvant chemotherapy. CEA levels were monitored in parallel. Results: Follow-up data was available for 135 patients (Stage I-III) and 25/135 had evidence of radiological recurrence. Irrespective of the treatment modality, longitudinal follow-up using the MMO panel was able to predict disease recurrence greater than 7 months before clinical progression was confirmed by CT scan. There was no significant correlation between longitudinal CEA levels and recurrence status, hence CEA levels alone did not provide any lead time advantage over the MMO panel or radiological surveillance. Kaplan-Meier (KM) survival analysis revealed that patients that were MMO panel positive had a poor survival irrespective of treatment modalities used: Modality 1 (HR = 6.2, p value = 0.003, test immediately post-surgery and immediately before ACT; HR = 31.6, p value = 0.01, test immediately after ACT); Modality 2 (HR = 11.2; p value = 0.01, test immediately after-surgery); Modality 3 (HR > 40, p value = 0.08, test immediately after neo-ACT and before-surgery; HR > 40, p value = 0.004, test immediately after-surgery). Conclusions: The MMO panel predicts CRC recurrence several months prior to detection by conventional CT scans, thus providing opportunity for alternative therapeutic strategies much earlier in the disease course.

e16098 Background: Human serum proteome and metabolome profiles have been analyzed to explore the molecular changes that occur with aging. We hypothesized that deep phenomic profiling of longitudinal sera would allow the identification of distinct phenomic chronologic patterns as a normal biological clock baseline to study personal aging. We further hypothesized that molecular assessment of this chronologic deviation, due to advance adenoma and early CRC, from the normal reference ageotypes would be instrumental as potential early diagnostics and reveal underlying pathophysiology. Methods: A cohort of 7673 normal, 746 advanced adenoma, 1177 stage I, 103 stage II and 119 stage III blood samples were assembled. Innovative multi-omics approaches, with global and targeted LCMS data production (metabolomics, lipidomics, and 2D proteomics), were applied to deep profile these subjects. Identification of the age-associated molecular patterns in normal subjects, modeled with an elastic net algorithm, established the reference baseline to mirror a biological clock. CRC associated deviation from this chronologically paced multi-omics clock was quantified to screen for early CRCs and explore the underlying pathophysiology. Results: Multiple mProbe aging indices of proteins and metabolites were identified, strongly predicting chronologic age ( P < 0.001, R > 0.90). Significant disruptions from normal molecular patterns were observed in advanced adenoma and early CRCs patients (R < 0.7). Pathway analysis of the proteins/metabolites with deviating patterns revealed both known and new pathways underlying CRC. Unsupervised cluster analysis identified unique aging subgroups among advanced adenoma and different stage CRC patients, indicating unique underlying biology relating to aging with different severities of cancer burdens. Conclusions: Deviations from the meticulously timed phenomic aging patterns may provide utility to allow future early CRC screening. Close examination of the underlying pathophysiology associated with early CRC, relating to ageotypes, not only may improve the sensitivity and specificity of prognostic and diagnostic tests of early CRCs, but also shed new insights into CRC therapeutics.