International Journal of Clinical Case Reports 2024, Vol.14, No.2, 107-116 http://medscipublisher.com/index.php/ijccr 110 André et al. (2014) hoped that molecular screening could identify genomic abnormalities in individual metastatic breast cancer patients and provide personalized targeted treatment. The results showed that out of 423 patients, 195 (46%) were identified with targetable genomic alterations, but only 55 (13%) received personalized treatment. This study confirmed the feasibility of personalized medicine, including rare genomic changes, in the treatment of metastatic breast cancer (André et al., 2014). With the continuous advancement of genomic sequencing technology, not only can genetic information be understood more deeply, but this information can also be applied to personalized medicine, offering patients more precise and effective medical services. 2 Case Studies in Personalized Medicine 2.1 Cancer treatment In the field of personalized medicine, cancer treatment strategies are rapidly evolving, especially through the use of tumor genomic characteristics to tailor treatment plans. This process begins with extracting DNA from patient tumor tissues, performing whole-genome sequencing to identify specific gene mutations, copy number variations, and other genomic abnormalities. The analysis of these data reveals key genes and signaling pathways related to tumor development, spread, and drug sensitivity. Based on this genomic information, physicians can select targeted therapeutic drugs that specifically address the genetic variations of the tumor. During the treatment process, by monitoring tumor markers and regularly conducting imaging studies, physicians can assess the effectiveness of the treatment and adjust the treatment plan as needed. Moreover, the genomic characteristics of the tumor may change over time, therefore, periodic re-sequencing of the genome can help identify new mutations that arise during treatment, which may lead to the development of drug resistance. In such cases, physicians can adjust the treatment strategy based on the latest genomic information. For example, tumors exhibiting EGFR mutations can be treated with inhibitors targeting this specific marker. This personalized treatment approach can enhance efficacy while minimizing damage to normal cells, thereby reducing unnecessary side effects. A study by Liu et al. (2016) found that the EML4-ALK fusion gene is present in approximately 5% of non-small cell lung cancer (NSCLC) patients and is an important target gene. The study analyzed the sensitivity and specificity of immunohistochemistry (IHC) in detecting EML4-ALK fusion gene mutations, evaluating the accuracy and clinical utility of this method, thus providing a basis for "individualized molecular treatment" for lung cancer patients. The results demonstrated that the specific antibody IHC method for detecting the EML4-ALK fusion gene is highly specific and sensitive, making it a simple and rapid screening method (Liu et al., 2016). Further research by Liu et al. (2023) found significant differences in the expression of the cAMP-dependent protein kinase inhibitor gamma (PKIG) in lung squamous carcinoma (LUSC) compared to normal tissue, and it has important reference value for the diagnosis and prognosis assessment of LUSC. The expression of PKIG is positively correlated with the infiltration level of regulatory T cells (Tregs), as well as with the expression levels of various chemokines/receptors and immunosuppressants, indicating that PKIG is highly related to the prognosis and immune microenvironment of LUSC, and it holds promise as a potential biomolecular marker for LUSC immune therapy (Liu et al., 2023). However, personalized cancer treatment strategies face multiple challenges, including how to deal with the internal heterogeneity of tumors, how to manage side effects during treatment, and how to cope with the high costs of treatment. To overcome these challenges, ongoing research, technological advancements, and clinical trials are essential. With the continuous progress of genomics, bioinformatics, and related technologies, personalized medicine will be able to provide more effective and safer treatment options for more cancer patients, greatly improving their quality of life and survival rates.
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