Cancer Genetics and Epigenetics 2024, Vol.12, No.6, 317-328 http://medscipublisher.com/index.php/cge 318 2 Genetic Mutation Landscape of Colorectal Cancer 2.1 Common genetic mutations associated with CRC The genetic mutation landscape of colorectal cancer (CRC) is characterized by several key driver mutations that play crucial roles in tumorigenesis, progression, and response to treatment. These mutations occur in specific genes that regulate critical cellular processes such as cell division, DNA repair, and apoptosis. Understanding the prevalence and impact of these mutations is essential for improving diagnostic, prognostic, and therapeutic strategies in CRC. 2.1.1 APC (adenomatous polyposis coli) The APC gene is one of the most frequently mutated genes in colorectal cancer, with mutations observed in approximately 70-80% of CRC cases (Santos et al., 2019; Li et al., 2023). APC acts as a tumor suppressor gene, and its inactivation leads to the accumulation of β-catenin, driving uncontrolled cell proliferation through the Wnt signaling pathway. APC mutations are often early events in colorectal carcinogenesis, contributing to the formation of adenomas, which can later progress to invasive cancer (Zhuang et al., 2021). 2.1.2 KRAS (kirsten rat sarcoma viral oncogene) Mutations in the KRAS gene occur in about 35-45% of colorectal cancers and are associated with poor prognosis and resistance to certain targeted therapies (Tsilimigras et al., 2018; Hassani et al., 2023). KRAS mutations are typically found in codons 12 and 13, leading to constitutive activation of the MAPK/ERK signaling pathway, which promotes cell growth and survival. These mutations are more prevalent in left-sided colorectal tumors and are strongly linked to resistance to anti-EGFR therapies, making them critical markers in the management of CRC (Telysheva et al., 2022). 2.1.3 TP53 (tumor protein p53) TP53, another key tumor suppressor gene, is mutated in approximately 50-60% of colorectal cancers (Nakayama and Oshima, 2018; Lee et al., 2021). Mutations in TP53 often occur late in colorectal cancer progression and are associated with increased tumor aggressiveness and poor prognosis. TP53 mutations disrupt the gene’s role in regulating the cell cycle, apoptosis, and genomic stability, leading to the accumulation of additional genetic alterations that drive cancer progression. 2.1.4 BRAF (B-raf proto-oncogene) The BRAF gene, particularly the V600E mutation, is present in about 5-10% of colorectal cancers and is more commonly associated with right-sided tumors and poor prognosis (Huang et al., 2018). BRAF mutations lead to the activation of the MAPK/ERK signaling pathway, similar to KRAS mutations, and are associated with a distinct clinical and molecular phenotype. BRAF-mutated tumors often exhibit high microsatellite instability (MSI-H) and poor response to conventional chemotherapy (Yan et al., 2019). 2.2 Mutation frequency and patterns The mutation frequency and patterns in colorectal cancer can vary based on tumor location, patient ethnicity, and other factors. Studies have shown that mutations in APC, KRAS, TP53, and BRAF occur with varying frequencies across different populations and tumor subtypes (Marbun et al., 2022). For example, TP53 and APC mutations are more common in left-sided tumors, while BRAF mutations are more frequently observed in right-sided tumors. The coexistence of multiple mutations, such as those in APC, KRAS, and TP53, often indicates a more aggressive tumor phenotype with a poorer prognosis (Yang et al., 2020). Marbun et al. (2022) investigated the pathogenic mutations in the APC, KRAS, TP53, PIK3CA, and MLH1 genes among Indonesian colorectal cancer (CRC) patients. The study, based on samples from 22 patients across three hospitals, utilized next-generation sequencing technology to conduct genetic analysis. The findings revealed mutation rates of 100% for APC, TP53, and PIK3CA, 64% for KRAS, and 45% for MLH1 among these patients. The study identified five types of mutations: nonsense mutations, missense mutations, frameshift mutations, splice site mutations, and silent mutations. It also analyzed the co-occurrence of these mutations and categorized patients into different mutation combination groups to examine their biological behavior and survival rates. The study
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