Discriminating high-risk cervical Human Papilloma Virus infections with urinary biomarkers via non-targeted GC-MS-based metabolomics.

Genital human papillomavirus (HPV) is the world's most commonly diagnosed sexually transmitted infection, and high-risk HPV types are strongly linked to cervical dysplasia and carcinoma. Puerto Ricans are among the US citizens with higher HPV prevalence and lower screening rates and access to treatment. This bleak statistic was as a motivation to detect biomarkers for early diagnosis of HPV in this population. We collected both urine and cervical swabs from 43 patients attending San Juan Clinics. Cervical swabs were used for genomic DNA extractions and HPV genotyping with the HPV SPF10-LiPA25 kit, and gas chromatography-mass spectrometry (GC-MS) was employed on the urine-derived products for metabolomics analyses. We aimed at discriminating between patients with different HPV categories: HPV negative (HPV-), HPV positive with simultaneous low and high-risk infections (HPV+B) and HPV positive exclusively high-risk (HPV+H). We found that the metabolome of HPV+B is closer to HPV- than to HPV+H supporting evidence that suggests HPV co-infections may be antagonistic due to viral interference leading to a lower propensity for cervical cancer development. In contrast, metabolites of patients with HPV+H were significantly different from those that were HPV-. We identified three urinary metabolites 5-Oxoprolinate, Erythronic acid and N-Acetylaspartic acid that discriminate HPV+H cases from negative controls. These metabolites are known to be involved in a variety of biochemical processes related to energy and metabolism and may likely be biomarkers for HPV high-risk cervical infection. However, further validation should follow using a larger patient cohort and diverse populations to confirm our finding.

Abstract licence: CC BY

• Translational Metabolomics: Current Challenges and Future Opportunities · 2019

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