Pendekatan Multi-Omics untuk Eksplorasi Senyawa Antikanker Fungi Endofit - Elfira Jumrah (Education and Talent Development Center Indonesia (ETDC Indonesia), 2026)
Cancer remains one of the leading causes of mortality worldwide, while conventional therapies are often limited by drug resistance, toxicity, and poor selectivity toward cancer cells. Endophytic fungi represent a promising source of anticancer compounds due to their ability to produce a wide variety of bioactive secondary metabolites. However, much of their biosynthetic potential remains unexplored because many biosynthetic gene clusters (BGCs) are cryptic or remain silent under standard laboratory conditions. This review aims to evaluate the roles of genomics, transcriptomics, proteomics, metabolomics, and epigenomics in the discovery of anticancer compounds from endophytic fungi and to highlight the potential of multi-omics integration for accelerating natural product discovery. The review was conducted using a systematic literature review approach based on the PRISMA 2020 guidelines.. The findings demonstrate that genomics facilitates BGC identification, transcriptomics reveals gene expression dynamics, proteomics identifies key enzymes and molecular targets, metabolomics enables metabolite characterization, and epigenomics contributes to the activation of cryptic gene clusters. The integration of these omics platforms provides a more comprehensive understanding of the relationship between genotype and metabolic phenotype, thereby enhancing the efficiency of discovering novel anticancer compounds. Nevertheless, challenges related to data integration, functional validation, and clinical translation remain significant. Therefore, multi-omics approaches combined with artificial intelligence and machine learning are expected to play a crucial role in advancing endophytic fungi as a valuable source of future anticancer drug candidates.