Differential expression and prognostic role of ACACA, ACLY, and FASN in schistosomiasis-associated versus hepatitis B virus-related liver cancer.

Introduction
Liver cancer ranks as the fourth leading cause of cancer-related deaths worldwide [1], with its incidence and mortality rates continuing to rise [2], making it a major global public health challenge and social burden. The main histological subtypes of primary liver cancer include hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC). Among these, HCC accounts for approximately 90% of all cases [3], while the proportion of CCA is about 15% [4, 5].
Liver cancer has diverse etiological factors. Common causes include chronic hepatitis B virus (HBV) infection, chronic hepatitis C virus (HCV) infection, metabolic-associated steatotic liver disease (MASLD), and alcohol-related liver disease (ALD) [6]. Additionally, schistosomiasis is a regionally prominent yet underrecognized etiological factor for liver cancer. Furthermore, aflatoxin exposure is an important risk factor for HCC [1], whereas chronic biliary inflammation is closely associated with the development of CCA [5].
Chronic hepatitis B virus (HBV) infection affects approximately 296 million people worldwide and is the primary etiological factor for liver cirrhosis and liver cancer [7]. Schistosomiasis is a complex tropical disease caused by schistosome infestation, with Schistosoma mansoni and Schistosoma japonicum being the most common pathogenic species​.
Existing evidence indicates that Schistosoma japonicum infection is closely associated with the development of liver cancer and bladder cancer; meanwhile, case reports have shown that Schistosoma mansoni infection may be related to liver cancer, prostate cancer, colorectal cancer, and ovarian tumors [8, 9]. Notably, Clonorchis sinensis and Opisthorchis viverrini, which also belong to the class Trematoda, have been classified as Group 1 carcinogens by the World Health Organization (WHO) [10–13].
Metabolic reprogramming is one of the core hallmarks of cancer [14–16]. As the metabolic hub of the human body, the liver exhibits particularly prominent metabolic disorders during the development and progression of liver cancer [17]. Among the numerous abnormal metabolic pathways, dysregulated lipid metabolism is considered a key driver of liver cancer initiation, and the abnormally activated de novo lipogenesis (DNL) pathway plays a crucial role in both the initiation and progression stages of liver cancer [18].
As biomacromolecules with diverse structures and complex functions, lipids are widely involved in key biological processes such as energy storage [19], metabolic regulation [20], epigenetic modification [21], signal transduction [22], immune regulation [23], inflammatory response [24], and cell recognition [25]. In the lipid synthesis pathway, ATP citrate lyase (ACLY), acetyl-CoA carboxylase α (ACACA), and fatty acid synthase (FASN) are three key rate-limiting enzymes [26]. Currently, it has been confirmed that these three enzymes are highly expressed in various malignant tumors, including liver cancer.
Notably, HBV infection and schistosome infection share similar geographical distribution characteristics; in terms of population distribution, the two also show consistency, with a higher prevalence in males than in females, and in adults than in children [27, 28]. From the perspective of pathological damage sites, HBV mainly targets the liver, while schistosome infection can also cause diseases of the liver and biliary system.
Despite differences in their pathogenic mechanisms, the similarity in clinical manifestations may lead to misdiagnosis in clinical practice: both can present with non-specific symptoms or signs such as fatigue, anorexia, fever, nausea, abdominal pain, jaundice, and hepatomegaly [29, 30]. More importantly, both have been confirmed as etiological factors for liver cancer [11]—HBV is a well-established carcinogen for HCC, while chronic schistosomiasis is an independent risk factor for liver cancer [31].
Existing studies have shown that schistosome infection can affect the lipid levels of the host [32]: after infection, a large number of macrophages infiltrate the liver, which not only exacerbates the local inflammatory response but also promotes abnormal lipid deposition [33]. Although it has been clearly established that liver cancer development is closely associated with lipid metabolism disorders, the mechanism by which schistosomiasis enhances the malignancy of liver cancer by regulating lipid metabolism pathways remains unclear.
On the other hand, as one of the main etiological factors for liver cancer, HBV infection can also induce lipogenic responses [34], and existing studies have confirmed that HBV can upregulate the expression of genes related to cholesterol biosynthesis [35]. It should be emphasized that schistosomiasis-related liver cancer (Sj-LC), as a regionally prominent subtype of liver cancer, is often characterized by unique clinical features in patients, including an older age at onset (data from this study: 66.38 ± 8.364 years vs. 60.75 ± 11.682 years in HBV-LC), a relatively lower male proportion (68.2% vs. 86.1% in HBV-LC), more advanced stage at diagnosis (72.0% at stage ⅣB), and a higher metastasis risk (nerve metastasis, P = 0.001; lymph node metastasis, P < 0.001). These features pose significant challenges to clinical diagnosis and treatment. However, current research on liver cancer lipid metabolism has mostly focused on common etiologies such as HBV infection, HCV infection, or metabolic dysfunction-associated steatotic liver disease (MASLD). Studies exploring the regulatory mechanisms of lipid metabolism in Sj-LC are extremely scarce, and systematic comparative studies on key lipid metabolism pathways and core molecules between Sj-LC and HBV-LC are even more lacking. This gap has hindered the development of targeted metabolic diagnosis and treatment strategies for Sj-LC, which urgently needs to be addressed.
Based on the aforementioned background, this study aimed to systematically compare the discrepancies in clinicopathological characteristics between schistosomiasis-related liver cancer and HBV-related liver cancer. It further sought to explore the differential expression patterns of key lipid metabolism enzymes (ACACA, ACLY, FASN) in these two subtypes, as well as investigate the potential prognostic relevance of these enzymes with due consideration of etiological specificity. The findings are expected to provide a theoretical basis for the subsequent development of targeted diagnostic and therapeutic strategies.

Materials and methods​

Clinical data analysis​

Data collection​
This study enrolled 309 patients with hepatitis B virus-related liver cancer and 44 patients with schistosomiasis-related liver cancer who were hospitalized and treated at the First Affiliated Hospital of Wannan Medical College between June 2016 and December 2024. The study protocol was approved by the Medical Ethics Committee of Wannan Medical College (Ethics Approval No.: [2022] No. 33). All patients underwent pathological examination, and two or more experienced pathologists confirmed the diagnostic results in a double-masked manner. A retrospective study design was adopted to collect and organize the clinical baseline data, general demographic data, and pathological examination results of all patients.
For the cases between June 2016 and June 2021, stratified analysis of tumor staging was performed on 183 hepatitis B virus-related liver cancer patients and 25 schistosomiasis-related liver cancer patients in accordance with the 8th edition of the AJCC Cancer Staging System [36].

Inclusion and exclusion criteria​
Inclusion criteria: ① Patients who underwent liver pathological examination and were diagnosed with liver cancer at the First Affiliated Hospital of Wannan Medical College between June 2016 and December 2024; ② Patients in the schistosomiasis-related liver cancer group must have definite detection of schistosome eggs in liver tissue pathological sections; ③ Patients in the hepatitis B virus related liver cancer group must have laboratory etiological examination indicating a history of chronic HBV infection, with persistent positivity for hepatitis B surface antigen (HBsAg).
Exclusion criteria: ① Patients with concurrent hepatitis C virus (HCV) infection, metabolic-associated steatotic liver disease (MASLD), alcohol-related liver disease (ALD), or autoimmune hepatitis; ② Patients diagnosed with liver metastasis from other malignant tumors or liver cancer of unknown etiology; ③ Cases of schistosomiasis-related liver cancer complicated with HBV infection.
Finally, a total of 44 schistosomiasis-related liver cancer patients and 309 hepatitis B virus-related liver cancer patients were included in this study.

Grouping criteria​
Patients were grouped based on etiological and pathological examination results: ① Schistosomiasis-related liver cancer group (Sj group): Cases with definite detection of schistosome eggs in liver cancer tissue pathological sections; ② hepatitis B virus related liver cancer group (HBV group): Liver cancer cases with laboratory examination confirming a history of chronic HBV infection and positive HBsAg (see Fig. 1 for the grouping flowchart).

Statistical analysis​
IBM SPSS Statistics 26.0, GraphPad Prism 9.0, and R software (Version 4.2.2) were used for data processing and statistical analysis. The method of data description was selected according to the type of variables: categorical variables were presented as frequency (n) and percentage (%), while continuous variables were presented as “mean ± standard deviation (SD)” or interquartile range (IQR).
The following statistical methods were used for inter-group comparisons: ① The chi-square test (χ² test) was applied for categorical variables; ② For continuous variables, the Kolmogorov-Smirnov (K-S) test was first used to verify normality. Independent samples t-test was adopted for continuous variables conforming to normal distribution, and Mann-Whitney U test was used for continuous variables not conforming to normal distribution; ③ For the comparison of continuous variables among multiple groups, parametric test (one-way analysis of variance, ANOVA) was used for data conforming to normal distribution, and Kruskal-Wallis H test was used for data not conforming to normal distribution.
Differentially expressed genes (DEGs) analysis was performed using the limma package in R software, and survival analysis was conducted using the survival package. Data visualization was implemented with the ggplot2 package (for drawing trend graphs and survival curves) and the pheatmap package (for drawing heatmaps). All statistical tests were two-tailed, and a P-value < 0.05 was considered statistically significant.

Bioinformatics analysis​
A total of 424 cases of transcriptome data (RNA-seq) from the liver hepatocellular carcinoma (LIHC) dataset were downloaded from The Cancer Genome Atlas (TCGA) database (https://portal.gdc.cancer.gov/). According to the clinical annotation information, liver cancer cases only associated with HBV infection (i.e., hepatitis B virus-related liver cancer group) were screened out. After further excluding duplicate samples, samples with missing clinical information, and liver cancer samples complicated with other etiologies, 111 valid transcriptome data were finally obtained, including 104 hepatitis B virus-related liver cancer tissue samples and 7 adjacent normal liver tissue samples. Among them, 102 hepatitis B virus-related liver cancer samples contained complete survival follow-up records, which were used for differentially expressed genes (DEGs) screening and correlation analysis between gene expression and survival prognosis.
The dataset of lipid metabolism-related genes (LMRGs) was derived from a published literature (PMID: 38357546), and was used to screen lipid metabolism-related genes with differential expression in hepatitis B virus-related liver cancer.

Collection and grouping of experimental specimens​
Gender- and age-stratified sampling was adopted to select schistosomiasis-related liver cancer (Schisto-LC) tissues, hepatitis B virus-related liver cancer (HBV-LC) tissues, and normal liver tissues resected during surgery due to accidental injuries (pathologically confirmed to be free of liver diseases) in the same period. The specific criteria were as follows: (1) Meeting the definite diagnostic criteria for Schisto-LC and HBV-LC (for Schisto-LC, schistosome eggs must be clearly detected in liver tissue pathological sections; for HBV-LC, laboratory tests must confirm a history of chronic HBV infection and persistent positivity for hepatitis B surface antigen [HBsAg]); (2) Excluding cases complicated with other liver diseases, other malignant tumors, or liver metastases; (3) Complete clinical data of cases, including definite pathological diagnosis results and relevant laboratory test data; (4) Normal liver tissues resected during surgery due to accidental injuries in the same period (pathologically confirmed to be free of liver diseases) were selected as normal controls to ensure the comparability of control samples and thereby minimize sampling bias as much as possible.
The samples were designated as the Sj group, HBV group, and normal control group, respectively. The protein expression levels of acetyl-CoA carboxylase α (ACACA), ATP citrate lyase (ACLY), and fatty acid synthase (FASN) in the three groups of tissues were detected by immunohistochemistry (IHC), and the mRNA expression levels of the above genes were detected by quantitative real-time polymerase chain reaction (RT-qPCR).

Immunohistochemical staining
Liver tissue samples were fixed in 4% paraformaldehyde for 2 h, then embedded in paraffin and sectioned at 4 μm thickness. Sections were baked at 60 °C for 30 min to enhance adhesion, followed by deparaffinization in xylene for 10 min. Gradient ethanol (100%, 95%, 85%, 75%) was used for rehydration (1 min per concentration), and samples were rinsed with distilled water.
For antigen retrieval, sections were immersed in a 1:50 diluted EDTA solution, heated to 120 °C in a pressure cooker for 2 min, cooled to room temperature (RT), and rinsed with phosphate-buffered saline (PBS). Endogenous peroxidase activity was blocked using a peroxidase blocker (10-minute incubation at RT), followed by PBS rinsing. Non-specific binding was inhibited with a blocking reagent (10-minute incubation at RT), and sections were rinsed again with PBS.
Primary antibodies against human ACACA (clone EP687Y, ab45174; Abcam), ACLY (clone EP704Y, ab40793; Abcam), and FASN (clone EPR7466, ab128870; Abcam) were applied to the sections, which were then incubated overnight at 4°C. After rewarming to RT, sections were rinsed with PBS and incubated with a universal secondary antibody (mouse/rabbit, KIT-9720; MXB Biotechnology, China) for 10 minutes at RT. Streptavidin-biotin-peroxidase complex was then reacted with the immune complexes, and color development was performed using 3,3’-diaminobenzidine (DAB; DAB-1031; MXB Biotechnology, China).
Finally, sections were counterstained with hematoxylin for nuclear visualization, mounted with neutral balsam, and analyzed via Fiji software to quantify staining intensity and positive area.

Quantitative real-time polymerase chain reaction (RT-qPCR)​
Total RNA was extracted from paraffin-embedded tissue sections using the Rnaprep Pure Total RNA Extraction Kit (DP439; Tiangen Biotech) supplemented with carrier RNA (4003101; Simgen). First-strand cDNA was synthesized following the manufacturer’s protocol using the Entilink™ First-Strand cDNA Synthesis Kit (Eq. 003; ELK Biotechnology).
RT-qPCR reactions were prepared with the Enturbo™ SYBR Green PCR Supermix Kit (Eq. 001; ELK Biotechnology) per the kit instructions. The thermal cycling conditions were: initial pre-denaturation at 95 °C for 3 min, followed by 40 cycles of denaturation (95 °C, 10 s), annealing (58 °C, 30 s), and extension (72 °C, 30 s). β-actin served as the internal reference gene, and relative gene expression levels were calculated using the 2^(-ΔΔCT) method. Primer sequences are provided in Table 1.

Results​

Comparison of general conditions and clinicopathological features between the two groups​
A total of 353 liver cancer patients were included in this study, and they were divided into the schistosomiasis-related liver cancer group (Sj group, n = 44) and the HBV-associated hepatocellular carcinoma group (HBV group, n = 309) based on etiology. The comparison results of clinicopathological features between the two groups are as follows (Table 2):​

Demographic features: Both groups were dominated by male patients, but the proportion of males in the Sj group (30 cases, 68.2%) was significantly lower than that in the HBV group (266 cases, 86.1%), with a statistically significant difference (P = 0.003). The average age of patients in the Sj group was (66.38 ± 8.364) years, which was significantly higher than that in the HBV group [(60.75 ± 11.682) years, P < 0.001].

Complications: The incidence of liver cirrhosis in the HBV group was significantly higher than that in the Sj group (P = 0.035); while the incidences of gastrointestinal bleeding (P < 0.001) and hepatic encephalopathy (P = 0.041) in the Sj group were significantly higher than those in the HBV group. There were no statistically significant differences in the incidences of ascites and splenomegaly between the two groups (P > 0.05).

Tumor pathological features: The pathological types of liver cancer in both groups included hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICCA). The proportion of HCC in the Sj group was significantly lower than that in the HBV group (P < 0.001). Regarding tumor metastasis features, the incidences of neural metastasis (P = 0.001), lymph node metastasis (P < 0.001), and extrahepatic spread (P < 0.001) in the Sj group were all significantly higher than those in the HBV group.

Comparison of laboratory test indicators between the two groups​
Laboratory indicators, including routine blood tests, liver and kidney function, coagulation function, and blood lipids, were collected from patients in both groups. The results of inter-group difference analysis are as follows (Table 3):​

Routine blood indicators: Statistically significant differences were observed between the two groups in hemoglobin (P = 0.009), platelet count (P = 0.006), and basophil proportion (P = 0.002). In addition, the eosinophil count in the Sj group was at the upper limit of the normal reference range and significantly higher than that in the HBV group (P < 0.001).

Blood lipid indicators: Regarding blood lipid indicators, the levels of cholesterol (P = 0.007) and triglycerides (P < 0.001) in the Sj group were significantly higher than those in the HBV group.

Liver and kidney function indicators: Both groups showed abnormal liver function, manifested by significantly increased levels of total bilirubin (P < 0.001), alanine aminotransferase (P < 0.001), aspartate aminotransferase (P = 0.001), and γ-glutamyl transpeptidase (P = 0.048). Among kidney function indicators, there were statistically significant differences in urea (P < 0.001) and serum uric acid (P = 0.032) between the two groups, but both were within the normal reference range.

Coagulation indicators: The D-dimer levels of patients in both groups exceeded the normal reference range, and the level in the Sj group was significantly higher than that in the HBV group (P = 0.001).

Comparison of AJCC tumor staging between the two groups​
AJCC staging analysis was performed on 208 liver cancer patients (25 cases in the Sj group and 183 cases in the HBV group) who were followed up and completed staging between June 2016 and December 2021. The results are shown in Table 4:​
Patients in the HBV group were mainly at Stage Ⅰ (99 cases, 54.1%) and Stage Ⅱ (46 cases, 25.1%); while patients in the Sj group were mainly at Stage ⅣB (18 cases, 72.0%). The comparison of the proportion of patients at Stage ⅣB between the two groups showed a statistically significant difference (P < 0.001), suggesting that the tumor progression of patients in the Sj group was more advanced at the time of diagnosis.

Bioinformatics analysis results of hepatitis B virus related liver cancer

Screening of differentially expressed genes (DEGs)
Between hepatitis B virus-related liver cancer Tissues and Adjacent Normal Tissues Based on the TCGA-LIHC dataset, with the screening criteria of “|log₂FC| > 1 and adjusted P-value < 0.05”, the differences in gene expression between hepatitis B virus-related liver cancer tissues and adjacent normal tissues were compared. A total of 3336 DEGs were screened out, including 2913 upregulated genes and 423 downregulated genes (Fig. 2, Volcano plot). The heatmap shows the expression distribution of the top 20 upregulated DEGs and top 20 downregulated DEGs (sorted by |log₂FC|) in the two groups of samples (Fig. 3). Notably, the key lipid metabolism enzyme genes ACACA, ACLY, and FASN all belong to the upregulated DEGs, and their expression levels were significantly increased in hepatitis B virus-related liver cancer tissues (Fig. 4).

Intersection analysis of DEGs and lipid metabolism-related genes (LMRGs)
A total of 3336 DEGs were subjected to intersection analysis with 895 LMRGs (derived from PMID: 38357546). A Venn diagram showed that 180 overlapping genes were obtained, including ACACA, ACLY, and FASN (Fig. 5). This suggests that the abnormal expression of these three key lipid metabolism enzyme genes may be involved in the occurrence and development of hepatitis B virus-related liver cancer.

Screening of lipid metabolism-related prognostic genes in hepatitis B virus-related liver cancer
Based on 102 hepatitis B virus-related liver cancer samples with complete survival follow-up records in the TCGA-LIHC dataset, univariate Cox regression analysis was used to screen DEGs related to patient survival (P < 0.05), and a total of 364 survival-related genes were obtained. After intersection analysis with 895 LMRGs, 18 lipid metabolism-related prognostic genes were finally obtained (Fig. 6). It should be noted that ACACA and ACLY were not included in this prognostic gene list.

Comparison of expression levels of ACACA, ACLY, and FASN in the two groups of liver cancer tissues​
Immunohistochemistry (IHC) staining results showed that ACACA, ACLY, and FASN were all localized in the cytoplasm. The staining results were quantitatively analyzed (positive staining area, optical density value) using Fiji software, and combined with the mRNA expression levels detected by quantitative real-time PCR (RT-qPCR), the results are as follows:​

IHC detection results​

ACLY expression: The positive staining area of ACLY in the Sj group was significantly larger than that in the normal control group (P < 0.001) and the HBV group (P < 0.05); although the positive staining area of ACLY in the HBV group was higher than that in the normal control group, the difference was not statistically significant (Fig. 7a).

FASN expression: The positive staining area of FASN in the Sj group was significantly higher than that in the normal control group (P < 0.05); although it was higher than that in the HBV group, the difference was not statistically significant (Fig. 7a).

ACACA expression: The positive staining area of ACACA in the Sj group was higher than that in the HBV group and the normal control group, but there was no statistically significant difference among the three groups (Figs. 7b and 8).

RT-qPCR detection results​
The mRNA expression levels of ACACA and ACLY in liver cancer tissues showed an upward trend (Fig. 7c):​

Compared with normal liver tissues, the mRNA expression levels of ACACA (P < 0.05) and ACLY (P < 0.05) in the Sj group were significantly increased.

Although the mRNA expression levels of ACACA, ACLY, and FASN in the HBV group were higher than those in the normal control group, the differences were not statistically significant (P > 0.05).

Although the mRNA expression levels of ACACA, ACLY, and FASN in the Sj group were higher than those in the HBV group, the differences between the groups were not statistically significant (P > 0.05).

Discussion
Schistosomiasis is a tropical parasitic disease prevalent worldwide, and it still imposes a high disease burden, especially in developing countries. When humans come into contact with contaminated water containing schistosome cercariae, the cercariae can penetrate the skin and enter the human circulatory system, eventually colonizing the liver and the intestinal venous system to develop into adult worms and lay eggs [37].
In the liver microenvironment, schistosome eggs and their metabolites can induce a persistent chronic inflammatory response, promoting the massive release of pro-inflammatory cytokines such as interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), and interleukin-1β (IL-1β). These cytokines further activate key signaling pathways, including nuclear factor-κB (NF-κB) and signal transducer and activator of transcription 3 (STAT3). By regulating the balance between cell proliferation and apoptosis, and inducing the excessive production of reactive oxygen species (ROS), they eventually lead to the accumulation of DNA damage and gene mutations, providing a pathological basis for the occurrence of liver cancer [38, 39].
In this study, we systematically compared the clinicopathological features of schistosomiasis-related liver cancer (Sj-LC) and hepatitis B virus-related liver cancer (HBV-LC). Although both conform to the basic pathological rules of liver cancer [40], significant differences were observed in the complication spectrum, tumor invasiveness, and pathological subtype composition. Compared with the HBV group, patients in the Schistosoma japonicum (Sj) group had significantly higher incidences of gastrointestinal bleeding (P < 0.001) and hepatic encephalopathy (P = 0.041), along with notably increased proportions of neural metastasis (P = 0.001), lymph node metastasis (P < 0.001), and extrahepatic spread (P < 0.001). Meanwhile, the proportion of hepatocellular carcinoma (HCC) in the Sj group was significantly lower than that in the HBV group (P < 0.001), whereas the proportion of intrahepatic cholangiocarcinoma (ICC) was higher.
Notably, lymph node metastasis, a crucial poor prognostic indicator for liver cancer progression [41], was highly prevalent in the Sj group. This not only suggests that Schisto-LC may exhibit more aggressive malignant biological behavior but also provides clinical evidence for the poorer prognosis of patients with this subtype.
It should be clarified that the difference in tumor subtypes between the two groups is an inherent characteristic of the diseases: HBV primarily targets and damages hepatocytes, leading to a predominance of HCC in HBV-related liver cancer. In contrast, schistosome eggs deposit in the intrahepatic portal areas and mainly damage biliary epithelial cells, resulting in a higher proportion of ICC in Schisto-LC [42]. This difference is not artificially controllable. Furthermore, existing studies have confirmed that ICC itself is associated with higher malignancy and poorer prognosis (the median survival time of cholangiocarcinoma is less than 2 years [43]). The synergistic effect between ICC and schistosome infection may further enhance tumor invasiveness.
Analysis results of laboratory indicators further revealed the pathophysiological differences between the two groups of patients. Compared with the HBV group, the Sj group had significantly lower levels of hemoglobin (P = 0.009), platelet count (P = 0.006), and basophil proportion (P = 0.002), and the eosinophil count was at the upper limit of the normal range (P < 0.001). This characteristic may be related to chronic immune inflammation and myelosuppression induced by schistosome infection. Liver function indicators showed that both groups had elevated levels of total bilirubin, alanine aminotransferase, aspartate aminotransferase, and γ-glutamyl transpeptidase, but the Sj group had more significant coagulation dysfunction (higher D-dimer level, P = 0.001), indicating more severe impairment of liver synthetic function. In addition, the levels of cholesterol (P = 0.007) and triglycerides (P < 0.001) in the Sj group were significantly increased, which provides clinical clues for the hypothesis that “schistosome infection may promote liver cancer progression by regulating lipid metabolism”. Moreover, this characteristic of dyslipidemia is more prominent in Schisto-LC, suggesting that it may be a specific metabolic phenotype of this subtype.
Tumor stage is a core indicator for prognostic evaluation of liver cancer [44]. The present study found significant differences in tumor stage between the two groups: among 183 HBV-LC patients, the majority were at stage Ⅰ (54.1%) and stage Ⅱ (25.1%), whereas 72.0% (18 cases) of 25 Schisto-LC patients were at stage ⅣB (P < 0.001). This result indicates that most Schisto-LC patients are already at an advanced tumor stage at the time of diagnosis, which may be related to the insidious early symptoms and lack of specific screening methods for this subtype. It also confirms the feature of higher malignancy of Schisto-LC from a clinical perspective, providing a basis for the subsequent development of targeted early diagnosis strategies.
Metabolic reprogramming is one of the core characteristics of tumor cells. As the central hub of lipid metabolism, the liver’s metabolic disorders play a crucial role in the occurrence of liver cancer [14–17]. Lipids not only provide energy for the rapid proliferation of tumor cells [19] but also regulate tumor invasion and metastasis through processes such as participating in signal transduction [22] and epigenetic modification [21, 45]. Existing studies have confirmed that HBV infection can interfere with liver lipid metabolism by upregulating the expression of cholesterol synthesis-related genes [35] and inducing lipogenic responses [34]. Schistosome infection has also been reported to affect host blood lipid levels and promote hepatic lipid deposition [32, 33]. However, direct evidence is still lacking regarding whether the two pathogens regulate liver cancer progression through common or specific lipid metabolic pathways. Currently, most studies on lipid metabolism in liver cancer focus on common etiologies such as HBV and HCV infections, and there is an extreme scarcity of research exploring the regulatory mechanisms of lipid metabolism in Schisto-LC. The present study is conducted to address this research gap.
Aberrant activation of the de novo lipogenesis (DNL) pathway is a typical feature of lipid metabolic reprogramming in liver cancer [46, 47]. The key rate-limiting enzymes of this pathway—ATP citrate lyase (ACLY) [48], acetyl-CoA carboxylase α (ACACA) [48–50], and fatty acid synthase (FASN) [48, 51, 52]—are often highly expressed in liver cancer tissues and are associated with malignant tumor phenotypes [53]. It should be noted that due to the lack of specialized transcriptomic and survival datasets for Schisto-LC in current public databases, this study selected the TCGA-LIHC dataset (predominantly HBV-LC) for bioinformatics analysis. The aim was to provide a reference framework for lipid metabolism research in Schisto-LC rather than directly extrapolate conclusions, and this methodological choice has a certain degree of asymmetry.
Analysis based on this dataset revealed that ACACA, ACLY, and FASN are all upregulated differentially expressed genes (DEGs) in HBV-LC and are included in the 180 overlapping genes between HBV-LC DEGs and lipid metabolism-related genes (LMRGs), suggesting that these three enzymes may be involved in the lipid metabolic reprogramming process of HBV-LC. Further univariate Cox regression analysis showed that ACACA and ACLY were not included in the list of lipid metabolism-related prognostic genes for HBV-LC, indicating that even in HBV-LC, the abnormal expression of these two enzymes is only associated with tumorigenesis and not proven independent prognostic biomarkers. It is further emphasized that the above survival analysis results are only applicable to the HBV-LC subtype and cannot be extrapolated to Schisto-LC.
To further clarify the expression differences of key lipid metabolism enzymes between the two liver cancer subtypes, this study performed verification using immunohistochemistry (IHC) and quantitative real-time polymerase chain reaction (RT-qPCR). The results showed that the area and intensity of positive protein staining for ACACA, ACLY, and FASN in Schisto-LC tissues were higher than those in HBV-LC tissues. Specifically, ACLY protein expression was significantly higher in Schisto-LC tissues than in normal liver tissues and HBV-LC tissues (P < 0.05), and FASN protein expression was significantly higher in Schisto-LC tissues than in normal liver tissues (P < 0.05). RT-qPCR results demonstrated that the mRNA expression levels of ACACA and ACLY in the Sj group were significantly higher than those in normal liver tissues (P < 0.05), and the mRNA expression of all three genes showed a trend of “Sj group > HBV group > normal control group” (though the intergroup differences did not reach statistical significance).
Combined with the more advanced tumor stage, stronger invasiveness, and more significant dyslipidemia of Schisto-LC, these findings suggest that more prominent lipid metabolic reprogramming exists in Schisto-LC. This characteristic is not a universally enhanced pathway phenomenon in liver cancer but a specific molecular feature of this subtype. We hypothesize that schistosome infection may upregulate the expression of ACACA, ACLY, and FASN, thereby enhancing the activity of the DNL pathway and providing sufficient lipid raw materials for tumor cells. This process promotes tumor proliferation, migration, and metastasis, ultimately leading to the formation of a more malignant clinical phenotype.
This hypothesis is only a preliminary assumption based on expression correlation and has not been verified by survival data. The direct association between this molecular feature and the prognosis of Schisto-LC requires confirmation in subsequent studies. Meanwhile, this hypothesis is consistent with the conclusions of previous studies that “ACLY regulates liver cancer stemness and invasiveness by activating the Wnt/β-catenin pathway [54], high FASN expression is associated with an increased risk of tumor recurrence [55], and ACACA expression is positively correlated with tumor stage and poor prognosis [56–58]”. These findings provide a new direction for the research on the molecular mechanisms of Schisto-LC.
Given the potential role of lipid metabolic reprogramming in Schisto-LC, inhibitors targeting key enzymes of the DNL pathway may provide a new strategy for the treatment of this liver cancer subtype. For example, the ACACA inhibitor AICAR has been shown to inhibit tumor cell growth in in vitro experiments [59], and the FASN inhibitor orlistat has exhibited anti-hepatocellular carcinoma effects both in vitro and in animal models [60, 61]. As a key upstream enzyme of the DNL pathway, ACLY and its inhibitors (initially used for the treatment of metabolic diseases) have received widespread attention in cancer treatment research in recent years [62]. The high expression of ACLY in Schisto-LC tissues observed in this study suggests that it may serve as a potential therapeutic target for this subtype, providing a theoretical basis for subsequent targeted drug experiments.
This study has certain limitations. First, the lack of specialized transcriptomic and survival datasets for Schisto-LC in public databases led to the reliance on HBV-LC data for reference in the bioinformatics analysis part, making it impossible to directly verify the association between key lipid metabolism enzymes and the prognosis of Schisto-LC. This is also an important reason why this study did not conclude that these enzymes can be used as prognostic biomarkers. Second, there was a significant imbalance in the cohort sample size: the sample size of the Schisto-LC group (n = 44) was much smaller than that of the HBV-LC group (n = 309). This situation is mainly due to the regional epidemic characteristics of schistosomiasis, resulting in a limited number of eligible cases that could actually be included. The imbalance in sample size may not only reduce the statistical power of the subgroup analysis of the Sj group but also prevent us from conducting multivariate regression analysis to adjust for key confounding variables such as age, gender, tumor stage, and liver cirrhosis, which may further affect the robustness of some conclusions. Meanwhile, the sample sizes for IHC and RT-qPCR verification were relatively small, and the sample sizes of the HCC and ICC subgroups within the Sj-LC group were further reduced. This may lead to insufficient statistical power for stratified analysis, failing to fully reveal the regulatory differences of infection etiologies on lipid metabolism under different tumor subtypes. Finally, this study adopted a retrospective design, which cannot completely avoid selection bias, and no functional experiments were conducted to verify the specific mechanisms of action of key lipid metabolism enzymes.
To address the above limitations, subsequent studies will be carried out from five aspects: ① Construct cell models and animal models of Schisto-LC (establish Schisto-related ICC and HCC models respectively), and clarify the functions of ACACA, ACLY, and FASN in the formation of malignant phenotypes of Schisto-LC with different tumor subtypes through gene knockdown/overexpression experiments; ② Expand the sample size and conduct multi-center prospective studies, collaborate with multiple medical institutions in schistosomiasis-endemic areas to ensure sufficient sample sizes of HCC and ICC subgroups within each group, construct a cohort with balanced sample sizes, establish an exclusive dataset for Schisto-LC, perform multivariate regression analysis to adjust for key confounding variables, and verify the expression significance of key lipid metabolism enzymes and their association with prognosis; ③ Refine studies related to tumor classification, conduct in-depth analysis of the regulatory mechanisms of the interaction between different infection etiologies and different tumor subtypes on lipid metabolism pathways, and clarify the weight of infection etiologies and tumor classification on clinical outcomes respectively; ④ Carry out drug intervention experiments targeting ACLY, FASN, and ACACA to evaluate their therapeutic effects on Schisto-LC with different tumor subtypes; ⑤ Improve data collection and quality control, establish a standardized clinical data collection process, and reduce selection bias and information bias.
In conclusion, this study confirms that Schisto-LC is a subtype of liver cancer with unique clinicopathological characteristics and molecular expression profiles. Its more advanced tumor stage and stronger invasiveness are associated with higher expression levels of key lipid metabolism enzymes (ACACA, ACLY, FASN), suggesting that lipid metabolic reprogramming may be one of its core molecular mechanisms. Through an integrated research approach combining clinical data, bioinformatics analysis, and laboratory verification, this study focuses on Schisto-LC, which has not been sufficiently studied, and fills the gap in research on lipid metabolism mechanisms in this field. In the future, by in-depth analysis of the pathogenesis of Schisto-LC and establishing an exclusive research dataset, it is expected to develop highly specific diagnostic biomarkers and targeted therapeutic drugs, thereby providing new strategies for improving the prognosis of patients with this subtype of liver cancer.