Cancer Genetics and Epigenetics 2024, Vol.12, No.3, 125-136 http://medscipublisher.com/index.php/cge 126 The study is to explore the prospects of precision treatment for liver cancer based on findings from Genome-Wide Association Studies. By synthesizing current research, highlight the potential of GWAS in identifying actionable genetic alterations and guiding personalized therapeutic strategies. The ultimate goal is to improve clinical outcomes for liver cancer patients through the integration of genomic data into precision medicine frameworks. 2 Progress in Liver Cancer Research 2.1 Advancements in molecular profiling Recent advancements in molecular profiling have significantly enhanced our understanding of liver cancer and its treatment. The integration of genomic and transcriptomic profiling has been pivotal in expanding precision cancer medicine. For instance, the WINTHER trial demonstrated that both DNA and RNA profiling could improve therapy recommendations and patient outcomes by identifying actionable mutations and guiding personalized treatment strategies (Rodón et al., 2019). Similarly, the MSK-IMPACT initiative has provided comprehensive genomic data from over 10,000 patients, revealing clinically relevant somatic mutations and novel noncoding alterations that can be targeted therapeutically. These large-scale profiling efforts underscore the importance of extensive molecular characterization in developing effective precision treatments for liver cancer. 2.2 Identification of molecular subtypes The identification of molecular subtypes in liver cancer has been a crucial step towards personalized medicine. Genome sequencing studies have classified liver cancer into distinct molecular subtypes based on somatic mutation profiles, RNA expression profiles, and DNA methylation profiles, which are associated with patient prognosis (Nakagawa et al., 2019). This classification enables the stratification of patients into subgroups that may respond differently to specific therapies. For example, the I-PREDICT study highlighted the feasibility of using tumor DNA sequencing to recommend individualized combination therapies, which improved disease control rates and survival outcomes (Sicklick et al., 2019). These findings illustrate the potential of molecular subtyping to tailor treatments to the unique genetic makeup of each patient's tumor. 2.3 Genomic alterations in liver cancer Genomic alterations play a critical role in the pathogenesis and progression of liver cancer. Comprehensive genomic studies have identified key driver mutations and pathways involved in hepatocarcinogenesis, such as the Wnt/β-catenin pathway, TP53/cell-cycle pathways, and telomere maintenance mechanisms. Additionally, structural variants, copy-number alterations, and virus integrations, particularly HBV integration into cancer-related genes, have been recognized as significant contributors to liver cancer development. The PERMED-01 clinical trial further demonstrated that extensive molecular profiling could identify actionable genetic alterations in a majority of patients, leading to matched therapies that improve clinical outcomes (Bertucci et al., 2019). These insights into the genomic landscape of liver cancer are essential for developing targeted therapies and improving patient prognosis. In summary, the progress in liver cancer research, driven by advancements in molecular profiling, the identification of molecular subtypes, and the understanding of genomic alterations, holds great promise for the future of precision treatment in liver cancer. By leveraging these insights, researchers and clinicians can develop more effective, personalized treatment strategies that improve patient outcomes (Malone et al., 2020). 3 Genetic Insights from GWAS in Liver Cancer 3.1 Methodology of GWAS Genome-wide association studies (GWAS) have become a cornerstone in understanding the genetic underpinnings of various diseases, including liver cancer. The methodology involves scanning the entire genome of numerous individuals to identify genetic variants associated with specific traits or diseases. This approach has been instrumental in identifying biomarkers and genetic risk factors that contribute to liver cancer susceptibility and progression (Masotti et al., 2019). Typically, GWAS involves the collection of DNA samples from both affected individuals (cases) and unaffected individuals (controls). These samples are then genotyped to detect single nucleotide polymorphisms (SNPs) and other genetic variations. Advanced statistical methods are employed to analyze the data, aiming to find significant associations between genetic variants and liver cancer (Yadav et al., 2021).
RkJQdWJsaXNoZXIy MjQ4ODYzNQ==