Integrative Multi-Omics Approaches for Identifying Cervical Cancer Therapeutic Targets

Abstract

After breast cancer, cervical cancer (CC) is one of the most common malignancies in women globally. Over 90% of chronic infections are caused by human papillomavirus (HPV) and its subtypes. Extensive research efforts are required to identify the treatment targets and prognostic indicators for recurring and metastatic cancers. It may be possible because of omics methods, including genomes, epigenomics, transcriptomics, proteomics, and metabolomics. High throughput (HT) data on the differential mRNA and miRNA expression and their crucial interrelationships enable promising integration and interpretation of the results. Clinical data and multi-omics have risen to the top of the heap in delivering molecular and cellular activities. They aid in comparing data from different omics approaches and bridging the gap between genotype and phenotype. Therefore, multi-omic techniques may improve the knowledge of the molecular basis of the physiology and primary cause of disease, revealing a new route for the prognosis, diagnosis, prevention, and therapy of human diseases.