Abordagens ômicas na busca de potenciais marcadores associados às lesões intraepiteliais cervicais de alto grau e ao câncer de colo de útero

Abstract

Cervical cancer (CC) is one of the most prevalent neoplasms in the Brazilian female population. Especially in Amazonas, CC is the leading cause of cancer deaths in women, in addition to being the most common. This disease is generally preceded by lesions known as cervical intraepithelial neoplasia (CIN), graded from 1 to 3. Stages 2 and 3 refer to high-grade cervical lesions (HSIL), which, if not diagnosed and treated early, promote progression to CC. Despite efforts to contain the disease's progression, incidence and mortality remain high, necessitating the search for new methods to understand the progression of high-grade CIN to CC and improve its early detection. In this context, multiomic approaches, such as proteomics, metabolomics, and lipidomics, contribute to oncology research by enabling the characterization and identification of proteins, metabolites, and lipids, enabling the investigation of their alterations and interactions in biological materials. Therefore, this study aims to characterize protein, metabolic, and lipid markers associated with precancerous and cancerous lesions in cervical cancer. For this purpose, women with a histopathological diagnosis of CIN 2/3 and CC were selected. From these women, cervical tissue samples (lesion, tumor, and margin) and peripheral blood were collected for protein and/or metabolic/lipid characterization and analysis. The proteomic study adopted a shotgun approach to comprehensively infer the protein profile of the samples, employing multivariate analyses to identify markers capable of distinguishing patients with HSIL and CC. In metabolomics and lipidomics, mass spectrometry and multivariate statistical analyses were used to understand the progression of neoplasms and identify markers capable of differentiating precancerous lesions. Lowfield nuclear magnetic resonance spectroscopy (1H NMR) with chemometric modeling was also applied to differentiate healthy individuals from patients with CIN 2/CIN 3 and CC. Proteomic analysis revealed protein differences between the samples, with some proteins unique to each condition and others in abundance associated with tumor development, particularly SERPINA3, RPL9, and MX1. Metabolomics and lipidomics identified panels of metabolites (serine, guanosine 5-monophosphate, succinic acid, mannose 6-phosphate, taurine, and glutamic acid) and triglyceride lipids (TG 49:1, TG 50:1, and TG 52:2), which may be potential markers for discriminating CIN 2 and CIN 3 lesions. Additionally, the chemometric model combined with low-field 1H NMR obtained excellent calibration values, and the prediction demonstrated greater efficacy in detecting CC, representing a promising screening tool for this neoplasm and potentially complementing traditional methods for early detection of cervical tumors and lesions in the future. Furthermore, it is hoped that the data and information obtained in this study will contribute to a more comprehensive understanding of the neoplastic progression process, which could, in the future, aid in the screening of cervical cancer and its highgrade precursor lesions.