Exometabolome and Molecular Signatures Associated with HPV 16 in Cervical Cancer: Integrative Metabolomic and Transcriptomic Analysis for Biomarker Discovery

TL;DR

This study identifies specific metabolites and genes linked to HPV 16 in cervical cancer, offering potential biomarkers for diagnosis and treatment.

Contribution

The study integrates metabolomic and transcriptomic data to discover novel biomarkers associated with HPV 16 in cervical cancer.

Findings

HPV 16-positive cell lines showed higher levels of specific amino acids and metabolites.

Genes involved in key metabolic pathways were upregulated in HPV 16-positive cells.

The findings suggest potential non-invasive biomarkers and therapeutic targets for cervical cancer.

Abstract

Cervical cancer (CC) represents a major public health concern, ranking as the fourth most frequently diagnosed cancer and one of the leading causes of cancer-related mortality among middle-aged women worldwide. CC is caused by persistent infection with high-risk human papillomaviruses (HR-HPVs), with HPV 16 being the cause of more than 50% of CC cases. In this study, the exometabolome of the HPV 16-positive cell lines SiHa and Ca Ski, as well as the HPV 16-negative control cell line C-33 A, was evaluated. The exometabolome was validated through molecular signatures using a transcriptomic approach to identify genes encoding cellular metabolic enzymes. The exometabolome was analyzed using 1H nuclear magnetic resonance spectroscopy (1H-NMR). Exometabolomic profiles were subsequently compared through both multivariate and univariate statistical analyses to identify significant differences between cell lines. Molecular signatures were analyzed from the GSE9750 dataset obtained from the GEO database. Exometabolic profiling of the HPV 16 positive cell lines showed higher concentrations of leucine, isoleucine, valine, lysine, methionine, glutamine, ornithine, choline, glucose, and tryptophan. An expression analysis showed increased expression of enzymes involved in amino acid synthesis, the tricarboxylic acid cycle, glycolysis, the pentose phosphate pathway, galactose metabolism, and HIF-1α. These data suggest metabolites and metabolism-associated genes that can be used as non-invasive, stable diagnostic and prognostic biomarkers, as well as therapeutic targets for CC in the presence of HPV 16.

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