Serum Metabolomic and Lipoprotein Profiling of Pancreatic Ductal Adenocarcinoma Patients of African Ancestry

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is a lethal cancer with a characteristic dysregulated metabolism. Abnormal clinicopathological features linked to defective metabolic and inflammatory response pathways can induce PDAC development and progression. In this study, we investigated the metabolites and lipoproteins profiles of PDAC patients of African ancestry. Nuclear Magnetic Resonance (NMR) spectroscopy was conducted on serum obtained from consenting individuals (34 PDAC, 6 Chronic Pancreatitis, and 6 healthy participants). Seventy-five signals were quantified from each NMR spectrum. The Liposcale test was used for lipoprotein characterization. Spearman’s correlation and Kapan Meier tests were conducted for correlation and survival analyses, respectively. In our patient cohort, the results demonstrated that levels of metabolites involved in the glycolytic pathway increased with the tumour stage. Raised ethanol and 3-hydroxybutyrate were independently correlated with a shorter patient survival time, irrespective of tumour stage. Furthermore, increased levels of bilirubin resulted in an abnormal lipoprotein profile in PDAC patients. Additionally, we observed that the levels of a panel of metabolites (such as glucose and lactate) and lipoproteins correlated with those of inflammatory markers. Taken together, the metabolic phenotype can help distinguish PDAC severity and be used to predict patient survival and inform treatment intervention.

KODAMA exploratory analysis in metabolic phenotyping

“…If further validated, the metabotype IV represents a well-defined high-risk metabolomic profile that, in future, could be used to predict patients who will be more likely to benefit from combination therapy that associates androgen deprivation with drugs that are able to reduce the level of systemic inflammation. Elebo et al (2021) conducted a pilot serum NMR-based metabolomic and lipoproteomic study on 34 patients diagnosed with pancreatic ductal adenocarcinoma (PDAC), 6 patients with chronic pancreatitis, and 6 healthy participants. In this study, KODAMA highlighted three distinct clusters: all healthy controls and patients with chronic pancreatitis were allocated in the cluster named N, whereas PDAC patients of clusters A and B were characterized by higher free cholesterol and cholesterol ester ratio (ratio >.45).…”

“…Partitional clustering methods, such as partition around medoids (PAM) clustering, were applied to the KODAMA dimensions to identify different phenotypes in a dataset of urine metabolome of women with lower urinary tract symptoms ( Bray et al, 2017 ) and in a dataset of lipoprotein profiles of patients with pancreatic ductal adenocarcinoma ( Elebo et al, 2021 ). Hierarchical clustering algorithms are largely used for the visualization of metabolic data through heatmap plots.…”

“…It computes the coefficients of each point from the measure of how much that point is similar to its own cluster compared to other clusters. The silhouette algorithm has been used to determine the optimal number of clusters both in PAM ( Elebo et al, 2021 ) and hierarchical clustering ( Cacciatore et al, 2021 ) on the KODAMA score. Identification of the number of clusters has shown their benefit when applied to the analysis of KODAMA scores ( Cacciatore et al, 2017a ).…”

“… Elebo et al (2021) conducted a pilot serum NMR-based metabolomic and lipoproteomic study on 34 patients diagnosed with pancreatic ductal adenocarcinoma (PDAC), 6 patients with chronic pancreatitis, and 6 healthy participants. In this study, KODAMA highlighted three distinct clusters: all healthy controls and patients with chronic pancreatitis were allocated in the cluster named N, whereas PDAC patients of clusters A and B were characterized by higher free cholesterol and cholesterol ester ratio (ratio >.45).…”

Comparative Immune profiling in Pancreatic Ductal Adenocarcinoma Progression Among South African patients

“…Immuno-inflammatory responses have been shown to differ between population groups because of ancestral and environmental factors (26). Furthermore, a recent study from our laboratory showed that the inflammatory markers GlycA and GlycB were significantly elevated in PDAC patients of African descent when compared to healthy individuals (27). These differential immune responses contribute to cancer disparities because of their impacts on cancer progression (28).…”