Serum levels of oxidative stress, IL-8, and pepsinogen I/II ratio in Helicobacter pylori and gastric cancer patients: potential diagnostic biomarkers

Abstract

Background and aim: Helicobacter pylori (H.pylori), a gram-negative bacterial pathogen associated with an increased risk of gastric cancer. This study investigates potential factors in the incidence of gastric cancer in patients with H.pylori, including oxidative stress, inflammatory biomarkers, serum pepsinogens (PG) of I and II, and PG-I/PG-II ratio.

Methods: The study comprised individuals with Helicobacter pylori (H.pylori) infection, gastric cancer patients, and healthy individuals. Biochemical parameters such as FBS (fasting blood sugar), lipid profile, and liver and kidney functional factors were evaluated using colorimetric techniques. Oxidative markers such as total oxidant status (TOS) and malondialdehyde (MDA) were quantified through colorimetric methods. IL-8, PG-II, and PG-II levels were also determined using the ELISA technique.

Results: Individuals with H. pylori infection exhibited elevated levels of IL-8 (940.5 ± 249.7 vs. 603.4 ± 89.1 pg/ml, P < 0.0001) and oxidative species (5.47 ± 0.7 vs. 1.64 ± 0.7 nM, P < 0.05) compared to gastric cancer patients, who, despite having lower levels of IL-8 and oxidative species, showed higher levels of MDA. H.pylori patients exhibited significantly higher levels of PG-I (7.28 ± 2.1 vs. 2.61 ± 1.4 ng/ml, P < 0.001), PG-II (3.21 ± 1 vs. 2.6 ± 0.6 ng/ml, P < 0.001), and the PG-I/PG-II ratio (2.27 ± 1.2 vs. 1 ± 0.4, P < 0.001) compared to gastric cancer patients. The findings were substantiated using various data analysis platforms such as Gene Expression Profiling Interactive Analysis (GEPIA), UALCAN (The University of ALabama at Birmingham CANcer data analysis), cBioPortal, and TIMER (Tumor IMmune Estimation Resource). These parameters could serve as potential diagnostic biomarkers for screening and therapeutic interventions based on the cut-off values derived from ROC (receiver operating characteristic) curves for IL-8, PGI, PGII, and PGI/PGII across the three groups.

Conclusions: IL-8, PGI, PGII, and PGI/PGII parameters could serve as potential diagnostic markers for the screening and treatment of gastric conditions.

Keywords: Gastric cancer; Helicobacter pylori; Oxidative stress; Pepsinogen-I; Pepsinogen-I, PG-I/PG-II interleukin-8.

Fig. 1

It shows the profiles of IL8 expression levels in both cancerous and normal tissues. The green box corresponds to the normal state and the gray box indicates the tumor state

Fig. 2

IL8 mutation landscape. (A) The connection between various cancer types and the expression of IL8, highlighting those mutations predominantly correlated with RNA expression. (B) The potential changes in copy numbers of IL8 as determined by GISTIC in numerous TCGA cancer types, accessed through the cBioPortal database. (C) mutational profile of IL8 across different cancer types. (D) ​Point Mutation

Fig. 3

(A) Kaplan-Meier plots exhibit the association between IL8 expression and overall survival (OS) in various types of cancers, emphasizing notable results. The pink curve represents cohorts with high expression, whereas the black curve represents those with low expression. (B) Kaplan-Meier assessments for RFS (Recurrence-Free Survival) based on IL8, employing the most suitable threshold values across diverse groups of cancer patients. The pink curve corresponds to high-expression cohorts, while the black curve represents the low-expression group

Fig. 4

IL8 expression based on TCGA-STAD. The IL8 expression in STAD is based on (A) sample type, (B) individual cancer stages, (C) gender, and (D) histological subtypes

Fig. 5

(A) Functions of the interactive genes of IL8 (CXCL8). (B) Investigating the relationship between the expression of IL8, IL1B, IL6, TNF, and ROS1(C) gastric cancer-related survival in association with IL8 expression

Fig. 6

Correlations between IL8 expression and immune cell infiltration in gastric cancer. (A) Heatmaps illustrate the correlations between IL8 expression and markers of tumor-infiltrating immune cells (TIICs) in gastric cancer. Correlation coefficients that hold statistical significance are highlighted in bold, with red or blue colors indicating positive or negative correlations, respectively. (B) The correlations between the expression of IL8 and various factors, including tumor purity, as well as the levels of infiltration of neutrophils and macrophages. (C) Correlations between expression of IL8 with tumor purity, infiltration level of neutrophils, and macrophages in gastric cancer (TIMER)

Fig. 7

Comparison of mean levels of (A) FBS, (B) triglycerides, (C) cholesterol, (D) HDL, (E) Creatinine, (F) BUN, (G) ALT, and (H) AST between study groups including normal subjects, H.pylori and gastric cancer (G. cancer) patients. The table presents the original and BH-adjusted p-values. *P < 0.05, **P < 0.1, ***P < 0.005, ****P < 0.0001

Fig. 8

Comparison of mean levels of (A) TOS (total oxidant status), (B) MDA (malondialdehyde), and (C) IL-8 between study groups of normal subjects, H.pylori, and gastric cancer (G. cancer) patients. The table presents the original and BH-adjusted p-values. *P < 0.05, **P < 0.1, ***P < 0.005, ****P < 0.0001

Fig. 9

Comparison of mean levels of (A) PG-I (pepsinogen I), (B) PG-II (pepsinogen II), and (C) PG-I/PG-II between study groups of normal subjects, H.pylori and gastric cancer (G. cancer) patients. The table presents the original and BH-adjusted p-values. *P < 0.05, **P < 0.1, ***P < 0.005, ****P < 0.0001

Fig. 10

ROC curves of IL8, PG-I, PG-II, PG-I/PG-II. (A): H.pylori patients versus Normal; (B): H.pylori patients versus gastric cancer patients; (C): Gastric cancer patients versus Normal