Cancer is a molecular disease associated with alterations in the genome, which, thanks to the highly improved sensitivity of mutation detection techniques, can be identified in cell-free DNA (cfDNA) circulating in blood, a method also called liquid biopsy. This is a non-invasive alternative to surgical biopsy and has the potential of revealing the molecular signature of tumors to aid in the individualization of treatments. In this review, we focus on cfDNA analysis, its advantages, and clinical applications employing genomic tools (NGS and dPCR) particularly in the field of oncology, and highlight its valuable contributions to early detection, prognosis, and prediction of treatment response.

Liquid-based cytology (LBC) has been used as a diagnostic tool for cervical cancer for years and is now being adopted for other gynecological cancers. LBC represents an important challenge to ensure that the process yields representative biospecimens for quality control (QC) of diagnostic procedures. In this study, we compare QC parameters (integrity, yield and purity, and polymerase chain reaction [PCR] amplification) of DNA isolated from LBC (N = 296) using two different nucleic acid isolation methods, manual (n = 233) or automated (n = 63). We also evaluated two different types of cytological brushes for sampling from the cervix. Our results suggest that manual isolation (yield 22.81 ± 1.92 μg) resulted in increased DNA recovery when compared with automated isolation (yield 9.96 ± 1.11 μg) from LBC samples, with a p-value of <0.0003. We estimated that 98% (53/54) of the samples preserved the integrity of DNA and were suitable for standard molecular biology analyses. The β-globin gene was amplified in 100% (296/296) of the DNA samples by endpoint PCR. We found no significant difference between the performance of the cytological brushes (p value of <0.6711) in a general overview. However, when looking at the results from using each brush individually, the manual isolation method was statistically superior to the automated method. Our work illustrates the impact of good QC of preanalytic conditions, which will be important for the application of LBC for developing early detection methods for gynecological cancers.

Ovarian cancer (OC) represents a serious health problem worldwide. In Mexico, most OC patients are detected at late stages, consequently making OC one of the leading causes of death in women after reaching puberty. Personalized medicine (PM) provides an individualized therapeutic opportunity for treating each patient relying on "omic" tools to match the correct drug with the specific pathogenic genomic signature. PM can help predict the best therapeutic option for each affected woman suffering from OC. In recent years, Mexico has made contributions to the PM of OC; however, it still has a long way to go for its full implementation in the country's health system.