Exploring potential biomarkers of early stage esophageal squamous cell carcinoma in pre- and post-operative serum metabolomic fingerprint spectrum using 1H-NMR method

Abstract

Esophageal squamous cell carcinoma (ESCC) is one of the most prevalent types of upper gastrointestinal malignancy. Here, we used ¹H nuclear magnetic resonance spectroscopy (¹H-NMR) to identify potential pre- and post-operative serum biomarkers in patients with early stage ESCC using metabolomic fingerprint spectrum. Serum samples from preoperative patients with ESCC (ESCC, n = 25), postoperative patients with ESCC (PO, n = 24), and controls (n = 40) were analysed using ¹H-NMR spectroscopy. Using orthogonal partial least squares-discriminant analysis, 31 altered serum metabolites were successfully identified among the three groups. These metabolites are indicative of the changes that occur with glycometabolism, the metabolism of fatty acids, amino acids, choline, ketone bodies, nucleotides, and lipids. Based on receiver operating characteristic (ROC) curve analysis and a biomarker panel with an area under the curve (AUC) of 0.969, six serum metabolites (α-glucose, choline, glutamine, glutamate, valine, and dihydrothymine) were selected as potential diagnostic biomarkers for early stage ESCC. Additionally, four potential PO biomarkers (α-glucose, pyruvate, glutamate, and valine) with an AUC of 0.985 were selected to distinguish ESCC and PO. Many metabolites trended towards normalisation in PO patients, with only choline remaining high with an AUC of 0.858, suggesting that it may be a valuable potential biomarker for neoplasm progression, recurrence, chemoradiotherapy, and prognosis. ¹H-NMR spectroscopy may be a useful tumour detection approach in the early diagnosis of ESCC. These results also indicate that it is useful to differentiate pre- and post-operative ESCC, evaluate surgery therapeutic responses, and monitor postoperative chemoradiotherapy.

Keywords: 1H-NMR spectroscopy; Esophageal squamous cell carcinoma; biomarker; metabolomics.

Figure 1

¹H-NMR spectra (δ 0.5-9.0 ppm) of serum obtained from the controls (C), preoperative esophageal squamous cell carcinoma (ESCC), and postoperative ESCC patients (PO). The region of δ6.0-9.0 ppm (in the dashed box) was magnified 20 times compared with corresponding region of δ0.5-6.0 ppm for the purpose of clarity. Keys: 1-MH: 1-methylhistidene; 3-HB: 3-hydroxybutyrate; 3-MH: 3-methylhistidene; AA: acetoacetate; Ace: acetate; Ace: acetone; Ala: alanine; Asc: ascorbate; Cho: choline; Ci: citrate; Cn: creatinine; Cr: creatine; DHT: dihydrothymine; DMG: N, N-dimethylglycine; EA: ethanolamine; For: formate; G: glycerol; Gln: glutamine; Glu: glutamate; Gly: glycine; GPC: glycerolphosphocholine; HG: homogentisate; HOD: the residual water resonance; IB: isobutyrate; Ile: isoleucine; IP: isopropanol; L: lipid; Lac: lactate; LDL: low density lipoprotein; Leu: leucine; Lys: lysine; M: malonate; Met: methionine; MG: methylguanidine; m-I: myo-inositol; Mol: methanol; NAS: N-acetyl glycoprotein signals; OAS: O-acetyl glycoprotein signals; Phe: phenylalanine; Py: pyruvate; Sar: sarcosine; Thr: threonine; TMAO: trimethylamine N-oxide; Tyr: tyrosine; Val: valine; VLDL: very low density lipoprotein; α-Glc: α-glucose; β-Glc: β-glucose.

Figure 2

A. 3D PCA score plots based on ¹H CPMG NMR spectra of serum obtained from controls (C), ESCC, and PO groups. PCA score plots revealed separation trends and group clustering based on ¹H-NMR spectra of the three groups (R²X = 69.0%, Q² = 0.658). B. 3D PLS-DA score plots based on ¹H CPMG NMR spectra of serum obtained from controls (C), ESCC, and PO groups (R²X = 68.6%, R²Y = 0.837, Q² = 0.814).

Figure 3

Orthogonal partial least squares-discriminant analysis score plots (A, E, I) derived from ¹H CPMG NMR spectra of serum and corresponding coefficient loading plots (C, D, G, H, K, L) obtained from control (C), ESCC, and PO groups and cross validation (B, F, J) by permutation test (n = 300). The colour map shows the significance of metabolite variations between the two classes. Peaks in the positive direction indicate metabolites that are more abundant in the groups in the positive direction of the first principal component. Consequently, metabolites that are more abundant in the groups in the negative direction of the first primary component are presented as peaks in the negative direction.

Figure 4

Hierarchical cluster analysis of serum metabolic profile for distinguishing ESCC and PO from controls (C). Each column represents one serum sample, and each row represents a single metabolite. The expression values are represented by the color scale. The intensity increases from green (relatively down-regulated) to red (relatively up-regulated).

Figure 5

ROC curves of the discriminatory power of the combined potential biomarker panel for ESCC and controls (A, AUC = 0.969), ESCC and PO patients (B, AUC = 0.985).

Figure 6

Metabolic pathways of the altered metabolites that include controls, preoperative and postoperative early stage ESCC metabolite biomarkers identified in this study. The bold in metabolites with histograms represents potential biomarkers among three groups. Red texts mean up-regulated with respect to controls, and green texts mean down-regulated with respect to controsl. ‘▲▲’ means P < 0.01, ‘▲’ means P < 0.05.