Hepatocellular carcinoma (HCC) represents one of the most prevalent and deadly forms of cancer globally, contributing significantly to cancer-related mortality. Despite advances in therapeutic strategies, the prognosis for HCC patients remains poor due to late-stage diagnosis and the aggressive nature of the disease. As such, there is a pressing need for reliable biomarkers that can aid in early detection, prognosis, and personalized treatment of HCC. One such promising biomarker is the hypermethylation of the glutathione S-transferase pi 1 (GSTP1) gene (Boudal et al., 2012).

GSTP1 is a member of the glutathione S-transferase family, enzymes involved in the detoxification of a wide range of carcinogens, including reactive oxygen species and electrophilic compounds (Tchou et al., 2000). The GSTP1 gene is located on chromosome 11q13 and plays a critical role in cellular defense mechanisms against oxidative stress and xenobiotics (Cairns et al., 2001). The silencing of GSTP1 through promoter hypermethylation has been implicated in the pathogenesis of various cancers, including prostate, breast, and lung cancers (Gurioli et al., 2018). This epigenetic alteration results in the inactivation of GSTP1, leading to increased susceptibility to oxidative damage and mutagenesis, thereby contributing to carcinogenesis (Lee, 2007).

In HCC, the aberrant methylation of the GSTP1 promoter has been reported with varying frequencies, suggesting a potential role in liver carcinogenesis (Boudal et al., 2012). Numerous studies have investigated the relationship between GSTP1 hypermethylation and HCC, aiming to elucidate its diagnostic, prognostic, and therapeutic implications. However, the findings have been inconsistent, with some studies indicating a strong association between GSTP1 hypermethylation and HCC progression, while others have reported no significant correlation. This discrepancy underscores the need for a comprehensive synthesis of the existing evidence to better understand the clinical relevance of GSTP1 hypermethylation in HCC. The process of DNA methylation, particularly in the context of tumor suppressor genes like GSTP1, involves the addition of a methyl group to the cytosine residue of CpG islands in the promoter region. This epigenetic modification typically leads to transcriptional repression and subsequent gene silencing (Zhong et al., 2002a). In cancer, hypermethylation of tumor suppressor genes disrupts normal cellular regulatory mechanisms, thereby promoting oncogenesis. In the case of GSTP1 (Witt et al., 2022), its inactivation through hypermethylation can diminish the cell’s capacity to detoxify carcinogens, thus facilitating the accumulation of genetic damage and tumor development (Lasabova et al., 2010).

The clinical implications of GSTP1 hypermethylation in HCC are multifaceted. As a potential biomarker, GSTP1 methylation status could serve as an early indicator of malignant transformation in the liver (Haluskova et al., 2015). This is particularly important given the asymptomatic nature of early-stage HCC and the lack of effective screening methods. Additionally, assessing GSTP1 methylation could provide prognostic information, as some studies have suggested a correlation between hypermethylation and poor clinical outcomes, including advanced tumor stage, higher recurrence rates, and reduced overall survival.

Furthermore, the methylation status of GSTP1 may have therapeutic relevance. Epigenetic therapies, such as DNA methyltransferase inhibitors (e.g., azacitidine and decitabine), aim to reverse abnormal methylation patterns and restore the expression of silenced tumor suppressor genes. In HCC, such strategies could potentially reactivate GSTP1 and enhance the cellular defense against carcinogens, thereby inhibiting tumor growth and progression. However, the efficacy and safety of these therapies in the context of HCC require further investigation through well-designed clinical trials (Nakayama et al., 2004).

In addition to its role as a biomarker and therapeutic target, GSTP1 hypermethylation may also provide insights into the molecular mechanisms underlying HCC pathogenesis. Understanding the epigenetic regulation of GSTP1 and its interaction with other oncogenic pathways could reveal novel targets for intervention and contribute to the development of more effective treatment strategies (Meiers et al., 2007). Despite the potential significance of GSTP1 hypermethylation in HCC, several challenges and limitations exist in the current body of research. The heterogeneity of study designs, populations, and methodologies contributes to the variability in reported findings. Differences in sample size, tissue types (e.g., tumor tissue vs. adjacent non-tumor tissue), and methylation detection techniques (e.g., methylation-specific PCR, bisulfite sequencing) can affect the consistency and comparability of results. Additionally, the lack of standardization in defining hypermethylation thresholds further complicates the interpretation of data (Lou et al., 2008).

To address these gaps, our systematic review and meta-analysis aim to provide a robust synthesis of the existing literature on GSTP1 hypermethylation in HCC. By pooling data from multiple studies, we seek to quantify its association with HCC, evaluate its diagnostic and prognostic significance, and explore potential heterogeneity across studies. Additionally, our analysis contributes to advancing the field by offering insights into the clinical utility of GSTP1 hypermethylation as a biomarker and discussing its potential integration into diagnostic and therapeutic frameworks.

The literature selection process was conducted according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Initially, a total of 1,053 articles were identified through searches in PubMed, Embase, and the Cochrane Library. After screening titles and abstracts, 451 articles were excluded based on predefined inclusion and exclusion criteria. The remaining 80 articles underwent full-text assessment, and ultimately, 10 studies were included for the meta-analysis. The selection process is illustrated in Figure 1.

Figure 1. Study selection.

In the included studies, a total of 10 case-control studies were identified, with sample sizes ranging from 58 to 180 participants. These studies investigated the association between GSTP1 hypermethylation and hepatocellular carcinoma (HCC). The majority of the studies employed methylation-specific PCR or DNA methylation arrays to detect GSTP1 promoter methylation. The studies consistently concluded that GSTP1 methylation was significantly associated with HCC, supporting its potential as a biomarker for liver carcinogenesis. Detailed information on each study, including the study design, sample size, methodology, and conclusions, is summarized in the table (Tables 1, 2).

Table 1. Literature characteristic.

Table 2. Newcastle-Ottawa scale of included studies.

The Forest plot (Figure 2A) presents the comparison between liver cancer tissue (HCC) and liver tissue from patients with other liver diseases in terms of GSTP1 hypermethylation. A total of 5 studies were included in this comparison. The plot shows the effect size (odds ratio, OR) for each study, with corresponding 95% confidence intervals (CIs). The pooled analysis yielded a significant difference in GSTP1 hypermethylation between liver cancer tissue and liver tissue from patients with other diseases, with a combined OR of 6.64 (95% CI: 2.17–20.37), indicating that GSTP1 hypermethylation is more frequently observed in liver cancer tissue. Furthermore, the heterogeneity test (I2 = 0%) suggests moderate to high variability among the studies. Subgroup analysis based on factors such as study design, sample size, and detection methods did not reveal any significant changes in the pooled effect size (Figure 2B).

Figure 2. Liver Cancer Tissue vs. Liver Tissue from Patients with Other Diseases (A) Forest plot illustrating the comparison of GSTP1 hypermethylation between liver cancer tissue and liver tissue from patients with other diseases. The pooled odds ratio (OR = 6.64; 95% CI: 2.17–20.37) indicates that GSTP1 hypermethylation is significantly more frequent in HCC tissue, underscoring its potential as a diagnostic biomarker (B) Funnel plot.

In the meta-analysis, the forest plot (Figure 3A) shows that the pooled odds ratio (OR) is 2.56 (95% CI: 1.80–3.64), indicating that the experimental group has a significantly higher risk compared to the control group (P < 0.00001). There is moderate heterogeneity among studies (I2 = 68%, P = 0.002), suggesting variability in study results that should be further explored. The funnel plot (Figure 3B) demonstrates a slightly asymmetrical distribution, which may indicate the potential presence of publication bias, although further statistical tests, such as Egger’s test, are recommended for confirmation. Overall, the results highlight a significant association while acknowledging heterogeneity and potential bias (Figure 3).

Figure 3. Hepatocellular Carcinoma Tumor Tissue vs. Non-Tumor Liver Tissue (A) Forest plot showing the association between GSTP1 hypermethylation in HCC tumor tissue versus non-tumor liver tissue. The pooled odds ratio (OR = 2.56; 95% CI: 1.80–3.64) highlights a significant correlation with tumor presence, supporting its role in identifying malignant transformations in liver tissue (B) Funnel plot.

The meta-analysis results, as shown in Figure A, indicate a pooled odds ratio (OR) of 2.56 (95% CI: 1.80–3.64), suggesting a significantly higher risk in the experimental group compared to the control group (P < 0.00001). Moderate heterogeneity was observed across the included studies (I2 = 68%, P = 0.002), which implies some variability in the effect sizes that warrants further investigation. The funnel plot in Figure B shows a slight asymmetry, potentially indicating publication bias, although additional tests such as Egger’s test would be necessary to confirm this. Overall, the findings demonstrate a statistically significant association while acknowledging heterogeneity and potential bias (Figure 4).

Figure 4. Liver Tissue of HCC Patients vs. Non-Tumor Liver Disease (A) Forest plot depicting GSTP1 hypermethylation in liver tissue of HCC patients compared to patients with non-tumor liver disease. The pooled odds ratio (OR = 2.56; 95% CI: 1.80–3.64) suggests its potential utility in distinguishing HCC from non-malignant liver conditions (B) Funnel plot.

The results of the meta-analysis are presented in Figure A, which shows a forest plot of odds ratios (OR) from five studies. The pooled odds ratio was 2.12 (95% CI: 1.07, 4.20), indicating a statistically significant association favoring the experimental group over the control group (Z = 2.15, P = 0.03). The heterogeneity test indicated moderate variability among the studies (I2 = 52%, P = 0.03). The individual odds ratios across the studies ranged from 0.91 to 3.29, with most falling on the side that supports the experimental intervention. Figure B presents a funnel plot, which suggests a slight asymmetry, possibly indicating the presence of publication bias (Figure 5).

Figure 5. HCC Tumor Tissue vs. Cirrhotic Liver Tissue (A) Forest plot comparing GSTP1 hypermethylation between HCC tumor tissue and cirrhotic liver tissue. The pooled odds ratio (OR = 2.12; 95% CI: 1.07–4.20) demonstrates a significant association, indicating its diagnostic relevance in differentiating HCC from cirrhosis (B) Funnel plot.

Hepatocellular carcinoma (HCC) is one of the most prevalent and lethal forms of cancer, with a rising global incidence and poor prognosis due to late-stage diagnosis and the aggressive nature of the disease (Bernardini et al., 2004). In recent years, research has increasingly focused on identifying biomarkers that can aid in early detection, prognosis, and therapeutic decision-making for HCC. One promising candidate in this context is the hypermethylation of the glutathione S-transferase pi 1 (GSTP1) gene, which plays a critical role in cellular defense mechanisms against oxidative stress and carcinogenesis (Li et al., 2012). This systematic review and meta-analysis were conducted to synthesize the current body of evidence on the correlation between GSTP1 hypermethylation and HCC, and to assess its clinical significance in terms of diagnosis, prognosis, and therapeutic potential (Arai et al., 2006).

GSTP1 is a member of the glutathione S-transferase family, which is involved in the detoxification of various carcinogens, including reactive oxygen species (ROS) and electrophilic compounds. The silencing of GSTP1 via promoter hypermethylation is a well-documented epigenetic alteration in several cancers, such as prostate, breast, and lung cancer (Cui et al., 2006). In HCC, the GSTP1 promoter is frequently hypermethylated, leading to gene silencing and a loss of the protective detoxification function. This loss of function can result in the accumulation of carcinogens and oxidative stress, which promotes the onset and progression of liver cancer (Formeister et al., 2010b).

The current meta-analysis included 10 high-quality case-control studies that assessed the association between GSTP1 hypermethylation and HCC. The studies consistently reported a significant correlation between GSTP1 hypermethylation and the presence of HCC. This is in line with previous findings, which suggest that GSTP1 hypermethylation is a frequent event in the pathogenesis of HCC, and supports its potential utility as a biomarker for early detection and liver carcinogenesis. Our findings also confirm that the hypermethylation of GSTP1 is not restricted to tumor tissues but may also be observed in peripheral blood or other biological samples, highlighting its potential as a non-invasive diagnostic tool (Yamada et al., 2016).

The use of different detection methods for GSTP1 hypermethylation introduces potential biases due to variations in sensitivity, specificity, and technical accuracy. PCR-based techniques are highly sensitive but may be more prone to false positives due to contamination, whereas methylation arrays provide a broader methylation profile but may lack sensitivity for low-abundance methylation signals. However, standardization of detection techniques in future studies is recommended to reduce variability and enhance comparability.

Our meta-analysis revealed a pooled odds ratio of 6.64 (95% CI: 2.17–20.38) for the comparison of liver cancer tissue versus liver tissue from patients with other liver diseases, indicating that GSTP1 hypermethylation is significantly more prevalent in HCC tissues. This finding suggests that GSTP1 methylation may serve as a sensitive molecular marker for distinguishing HCC from other liver diseases, such as cirrhosis or hepatitis, which share overlapping clinical features. Furthermore, the ability to detect GSTP1 hypermethylation in non-invasive biological samples, such as blood or urine, offers the potential for developing non-invasive screening methods for early HCC detection (Zhang et al., 2022).

However, it is important to note that there is considerable variability in the reported frequencies of GSTP1 hypermethylation across studies. This variability may be attributed to differences in study design, sample size, methodological approaches (e.g., methylation-specific PCR vs. DNA methylation arrays), and population characteristics (Gupta et al., 2023). For instance, studies involving patients with chronic liver diseases may report higher frequencies of GSTP1 hypermethylation, potentially due to the increased exposure to carcinogenic factors. Thus, while GSTP1 hypermethylation holds promise as a diagnostic marker, further standardization of detection methods and large-scale clinical trials are needed to validate its utility in different patient populations (Tada et al., 2005).

This finding aligns with previous studies that have suggested GSTP1 hypermethylation is associated with more aggressive tumor behavior and poorer clinical outcomes in HCC. GSTP1 methylation may reflect underlying epigenetic changes that contribute to the malignant transformation of hepatocytes and the progression of liver cancer. Furthermore, as a molecular biomarker, GSTP1 methylation could be used in conjunction with other prognostic indicators, such as tumor stage, to improve the accuracy of predicting patient outcomes and guide therapeutic decisions (Bakker et al., 2002).

However, it is worth noting that while GSTP1 hypermethylation is significantly associated with poor prognosis, the exact mechanisms by which it influences HCC progression remain unclear (Zhang et al., 2005). Additional research is needed to explore the molecular pathways underlying GSTP1 methylation in HCC, as well as its potential interaction with other oncogenic pathways, such as those involving p53, NF-kB, and TGF-β signaling (Cui et al., 2006). Understanding these mechanisms could pave the way for the development of targeted therapies that reverse GSTP1 silencing and restore its protective function in liver cancer cells (Lee et al., 2003b).

Beyond its diagnostic and prognostic significance, GSTP1 hypermethylation may also offer therapeutic opportunities in HCC. Epigenetic therapies, such as DNA methyltransferase inhibitors (DNMTi) like azacitidine and decitabine, have been investigated as potential treatments for cancers characterized by promoter hypermethylation of tumor suppressor genes (Li et al., 2018). These agents work by inhibiting the DNA methyltransferases responsible for adding methyl groups to the promoter regions of genes, thus restoring the expression of silenced genes, including tumor suppressors like GSTP1 (Zhang et al., 2005).

In the context of HCC, epigenetic therapies aimed at reversing GSTP1 hypermethylation could enhance the cellular detoxification capacity and reduce tumor progression by reactivating the silenced GSTP1 gene (Jain et al., 2012b). Although early studies in other cancers have shown promise, the application of such therapies in HCC remains an area of active research (Zakir et al., 2022). Clinical trials are needed to assess the efficacy and safety of DNMTi in HCC patients, particularly in combination with other treatment modalities such as chemotherapy, immunotherapy, or targeted therapies (Lee et al., 2003b). Additionally, the identification of GSTP1 as a potential therapeutic target could lead to the development of novel agents that specifically target the hypermethylation of GSTP1 or the upstream regulators involved in its silencing (Lam et al., 2006). For example, small molecules or RNA-based therapies could be designed to specifically demethylate the GSTP1 promoter and restore its expression in liver cancer cells. This approach could complement existing treatment strategies and improve clinical outcomes for patients with advanced HCC (Anzola et al., 2004).

Despite the promising findings of this meta-analysis, several challenges and limitations should be considered when interpreting the results (Reibenwein et al., 2007). First, the studies included in this analysis were primarily observational in nature, and many involved small sample sizes. While the meta-analysis increased the statistical power of the analysis, further large-scale, multicenter studies are needed to confirm the clinical utility of GSTP1 hypermethylation as a biomarker for HCC (Anzola et al., 2004).

There is considerable heterogeneity in the methodologies used to assess GSTP1 hypermethylation, including differences in the biological samples analyzed (e.g., tumor tissue vs. blood) and the detection techniques (e.g., PCR-based methods vs. methylation arrays) (Su et al., 2007b). Standardization of detection methods will be critical for improving the reproducibility and reliability of GSTP1 methylation assessments across different studies and patient populations (Zhong et al., 2002a). The potential for publication bias cannot be ruled out, as studies with positive findings are more likely to be published than those with negative results. While the funnel plots and Egger’s test suggest a slight asymmetry, further research is needed to evaluate the impact of publication bias on the overall findings (Henrique and Jerónimo, 2004).

The variability in study designs, sample sizes, and GSTP1 hypermethylation detection methods across the included studies could introduce significant biases. Studies varied in terms of design (e.g., case-control versus cohort), which may influence the strength and direction of associations observed. Additionally, differences in sample sizes may impact the statistical power of individual studies and contribute to potential overestimation or underestimation of effects. Specifically, studies with smaller sample sizes may be more susceptible to Type I and Type II errors, thus influencing the overall conclusions. Furthermore, the methods used to detect GSTP1 hypermethylation varied across studies, with some employing PCR-based techniques while others utilized methylation arrays. These differences in detection methods may have affected the sensitivity and specificity of the results, potentially leading to discrepancies in findings. While we conducted a sensitivity analysis to address the influence of detection method variability, it is important to acknowledge that such differences may have contributed to heterogeneity in the pooled estimates.

The authors thank AiMi Academic Services (www.aimieditor.com) for English language editing and review services.

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