International Journal of Molecular Medical Science, 2025, Vol.15, No.1, 33-41 http://medscipublisher.com/index.php/ijmms 39 compressive symptoms to asymptomatic cases. Some affected individuals required surgical intervention, such as cyst fenestration, while others were managed conservatively (Porath et al., 2016). In another cohort, researchers identified mutations in GANAB and ALG8, genes associated with glycoprotein biogenesis in the ER. These mutations were linked to diffuse cystic liver involvement, resulting in progressive hepatomegaly. Notably, environmental factors and hormonal influences appeared to modulate disease severity. For instance, postmenopausal females exhibited a slower progression of cyst growth compared to premenopausal counterparts, further demonstrating the role of hormonal regulation (Masyuk et al., 2018; Lee-Law et al., 2019). These cases underscore the importance of genetic analysis in understanding the wide spectrum of liver cyst phenotypes. Genetic testing not only aids in diagnosis but also informs prognosis and therapeutic planning. Variability in clinical manifestations highlights the interplay of genetic and environmental factors in disease progression, emphasizing the need for personalized management approaches in patients with liver cyst disorders. 7 Concluding Remarks The study of liver cysts has revealed a complex interplay of genetic and molecular mechanisms underlying their development and progression. Advances in genetic analysis have identified key mutations in genes such as PKD1, PKD2, PRKCSH, and GANAB, among others. These mutations disrupt cellular processes such as calcium signaling, protein folding, and Endoplasmic Reticulum (ER) function, leading to cystogenesis. Autosomal Dominant Polycystic Kidney Disease (ADPKD) and isolated Polycystic Liver Disease (PCLD) share overlapping yet distinct genetic underpinnings, which influence the severity and distribution of cystic lesions. Clinically, liver cysts range from asymptomatic findings to severe manifestations, including hepatomegaly, abdominal discomfort, and complications such as cyst rupture or infection. This variability underscores the importance of genetic testing and personalized management strategies. Together, these insights have deepened our understanding of liver cyst pathophysiology, enabling more precise diagnostic and therapeutic approaches. Recent years have seen significant progress in the management of liver cysts, moving beyond symptomatic relief to targeting the underlying molecular pathways. Pharmacological advancements include somatostatin analogues, which have demonstrated efficacy in reducing liver volume by decreasing cyst fluid secretion. Additionally, mTOR inhibitors and adenylyl cyclase inhibitors show promise in experimental models for mitigating cyst growth by targeting dysregulated signaling pathways. Emerging therapies focusing on ER stress modulation and hormonal regulation offer novel avenues for intervention. For patients with severe disease unresponsive to medical management, minimally invasive techniques such as percutaneous sclerotherapy and surgical fenestration remain effective. Liver transplantation is a definitive option for end-stage disease. Collectively, these therapeutic advancements highlight the transition from symptom-focused care to molecularly informed strategies, improving outcomes for patients with polycystic liver disease. Despite these advancements, several gaps remain in our understanding of liver cystogenesis and its management. Interdisciplinary research combining genetics, molecular biology, bioinformatics, and clinical medicine is essential to address these challenges. Future studies should prioritize identifying novel genetic mutations and elucidating their functional impact on cyst formation. Investigating the role of epigenetic modifications and environmental factors in disease progression is also critical. Translational research focused on preclinical and clinical trials of new therapeutic agents, such as ER stress modulators and hormonal inhibitors, is necessary to expand treatment options. Furthermore, incorporating artificial intelligence and machine learning tools into imaging and genetic analyses could enhance diagnostic accuracy and risk stratification. Collaborative efforts between researchers, clinicians, and pharmaceutical companies will be key to accelerating progress and improving patient outcomes. Acknowledgments The authors extend gratitude to the two anonymous peer reviewers from Peking Union Medical College and Wenzhou Medical University for their thorough and meticulous reading and review of this manuscript. They provided valuable critiques of the manuscript and offered detailed suggestions for revisions.
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