International Journal of Molecular Medical Science, 2024, Vol.14, No.5, 274-292 http://medscipublisher.com/index.php/ijmms 277 Denmark (Maretty et al., 2017), Sweden (Eisfeldt et al., 2020), Papua New Guinea (Jacobs et al., 2019), Mongolia (Bai et al., 2018), and Africa (Gurdasani et al., 2015; Mathias et al., 2016a; Choudhury et al., 2017) , as well as large-scale surveys across the world (Auton et al., 2015; Sudmant et al., 2015; Mallick et al., 2016b; Telenti et al., 2016). By incorporating cancer genomics into diagnostic medicine, the precision of clinical care for cancer patients is improving. Over the past decade, large-scale parallel sequencing or next-generation sequencing (NGS) has been applied to extensive cancer genomics discovery projects, revealing remarkable new information about the underlying genomic drivers of cancer development and progression across multiple anatomical sites (Berger and Mardis, 2018). The application of NGS technology in characterizing human tumors has provided unprecedented opportunities to understand the biological foundations of different cancer types, develop targeted therapies and interventions, discover genomic biomarkers of drug response and resistance, and guide clinical decisions related to patient treatment (Garraway and Lander, 2013; Hyman et al., 2017). 3.1.2 Transcriptomics Transcriptomics involves the study of the complete set of RNA transcripts produced by the genome under specific circumstances or in a specific cell. This type of data helps in understanding gene expression patterns and how they change in response to cancer. In recent decades, transcriptome analysis has rapidly gained popularity in cancer research, providing remarkable insights into the field of cancer immunotherapy. The revolution from bulk RNA sequencing to single-cell RNA sequencing (scRNA-seq) has made transcriptome analysis more accurate and powerful. The transcriptomic profiles of millions of individual cells have deepened our understanding of cancer heterogeneity and the tumor microenvironment (Lei et al., 2021). microRNAs (miRNAs) can also influence cell signaling pathways, acting as oncogenes or suppressors involved in tumor initiation or recurrence. With advancements in gene sequencing, miRNAs are viewed as potential biomarkers, not only for early cancer detection but also for predicting prognosis (He et al., 2019).Transcriptomic data is crucial for identifying differentially expressed genes and understanding the regulatory mechanisms at play(Sathyanarayanan et al., 2020). 3.1.3 Epigenomics Epigenomics is the study of the complete set of epigenetic modifications on the genetic material of a cell. These modifications, such as DNA methylation and histone modification, do not change the DNA sequence but can affect gene expression. Epigenetic mechanisms, including cytosine base methylation, play a crucial role in regulating gene expression during normal mammalian development. However, disruption of these regulatory mechanisms can lead to hypermethylation or hypomethylation of gene promoter regions, resulting in the silencing of critical tumor suppressor functions (Baylin, 2005). Epigenomic data is essential for understanding how epigenetic changes contribute to cancer progression and for identifying potential epigenetic biomarkers. 3.1.4 Proteomics Proteomics is the large-scale study of proteins, particularly their structures and functions. Since proteins are the functional molecules in cells, proteomic data provides direct insights into the functional state of the cell. This type of data is valuable for identifying protein biomarkers and understanding the molecular mechanisms of cancer. Proteomics is the large-scale study of proteins, including their expression levels, post-translational modifications, and protein-protein interactions, with a particular focus on their structure and function. It provides a comprehensive understanding of disease development, cellular metabolism, and other processes at the protein level. Since proteins are functional molecules within cells, proteomic data offer direct insights into cellular functional states. By comparing proteomes between normal and pathological individuals, we can identify 'disease-specific protein molecules' that could serve as molecular targets for new drug design or provide molecular markers for early diagnosis of diseases. Such data are highly valuable for identifying protein biomarkers and understanding the molecular mechanisms of cancer. 3.1.5 Metabolomics Metabolomics, inspired by the research approaches of genomics and proteomics, involves the quantitative analysis of all metabolites within an organism and seeks to identify the relationships between metabolites and physiological or pathological changes. Metabolites are small molecules that are intermediates and products of
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