Overexpression and clinicopathological significance of zinc finger protein 71 in hepatocellular carcinoma

Abstract

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most prevalent and aggressive forms of liver cancer, with high morbidity and poor prognosis due to late diagnosis and limited treatment options. Despite advances in understanding its molecular mechanisms, effective biomarkers for early detection and targeted therapy remain scarce. Zinc finger protein 71 (ZNF71), a zinc-finger protein, has been implicated in various cancers, yet its role in HCC remains largely unexplored. This gap in knowledge underscores the need for further investigation into the ZNF71 of potential as a diagnostic or therapeutic target in HCC.

AIM

To explore the expression levels, clinical relevance, and molecular mechanisms of ZNF71 in the progression of HCC.

METHODS

The study evaluated ZNF71 expression in 235 HCC specimens and 13 noncancerous liver tissue samples using immunohistochemistry. High-throughput datasets were employed to assess the differential expression of ZNF71 in HCC and its association with clinical and pathological features. The impact of ZNF71 on HCC cell line growth was examined through clustered regularly interspaced short palindromic repeat knockout screens. Co-expressed genes were identified and analyzed for enrichment using LinkedOmics and Sangerbox 3.0, focusing on significant correlations (P < 0.01, correlation coefficient ≥ 0.3). Furthermore, the relationship between ZNF71 expression and immune cell infiltration was quantified using TIMER2.0.

RESULTS

ZNF71 showed higher expression in HCC tissues vs non-tumorous tissues, with a significant statistical difference (P < 0.05). Data from the UALCAN platform indicated increased ZNF71 levels across early to mid-stage HCC, correlating with disease severity (P < 0.05). High-throughput analysis presented a standardized mean difference in ZNF71 expression of 0.55 (95% confidence interval [CI]: 0.34-0.75). The efficiency of ZNF71 mRNA was evaluated, yielding an area under the curve of 0.78 (95%CI: 0.75-0.82), a sensitivity of 0.63 (95%CI: 0.53-0.72), and a specificity of 0.82 (95%CI: 0.73-0.89). Diagnostic likelihood ratios were positive at 3.61 (95%CI: 2.41-5.41) and negative at 0.45 (95%CI: 0.36-0.56). LinkedOmics analysis identified strong positive correlations of ZNF71 with genes such as ZNF470, ZNF256, and ZNF285. Pathway enrichment analyses highlighted associations with herpes simplex virus type 1 infection, the cell cycle, and DNA replication. Negative correlations involved metabolic pathways, peroxisomes, and fatty acid degradation. TIMER2.0 analysis demonstrated positive correlations of high ZNF71 expression with various immune cell types, including CD4⁺ T cells, B cells, regulatory T cells, monocytes, macrophages, and myeloid dendritic cells.

CONCLUSION

ZNF71 is significantly upregulated in HCC, correlating with the disease’s clinical and pathological stages. It appears to promote HCC progression through mechanisms involving the cell cycle and metabolism and is associated with immune cell infiltration. These findings suggest that ZNF71 could be a novel target for diagnosing and treating HCC.

Key Words: Hepatocellular carcinoma; Zinc finger protein 71; Immunohistochemistry; Enrichment analysis; Immune infiltration

Core Tip: This study identified zinc finger protein 71 (ZNF71) as a key marker significantly upregulated in hepatocellular carcinoma (HCC), linking its elevated levels to increased disease severity. Employing a comprehensive methodology, including immunohistochemistry, high-throughput analysis, and single-cell sequencing, we demonstrated the involvement of ZNF71 in promoting HCC progression through cell cycle and metabolic pathways. Our findings underscore the potential of ZNF71 as a therapeutic target, especially given its association with immune cell infiltration, highlighting its role in the tumor microenvironment.

INTRODUCTION

Hepatocellular carcinoma (HCC), derived from either epithelial or mesenchymal cells within the liver, have seen an upward trend in prevalence in recent periods. Data from 2020 indicate that globally, there were about 900000 new instances of this malignancy, culminating in approximately 830000 fatalities[1], positioning it as the fifth leading cause of cancer-related death worldwide and the fourth most prevalent in China[2]. The origins of HCC are not completely elucidated but are strongly associated with risk factors such as infections by hepatitis B and C viruses, chronic alcohol abuse, and exposure to aflatoxins[3]. Usually, due to the absence of obvious symptoms in the early stage of HCC development, the diagnosis of patients with HCC is delayed, which makes the disease enter a very serious invasive stage and greatly reduces the quality of life. The medical field is continuously evaluating and researching various novel and advanced treatment methods[4]. In the treatment of HCC, it can be found from the exploration of second-line treatment that there has been significant progress in recent years. New targeted therapeutic drugs and regimens have been continuously proposed, which provides more treatment options for patients with HCC. It also shows us the performance of different targeted therapies in efficacy and safety, and also highlights the importance of in-depth understanding of the disease mechanism[5,6]. In terms of mechanism, the study of programmed cell death mechanisms in HCC, such as apoptosis, necrosis, autophagy and ferroptosis, provides a theoretical basis for the treatment based on cell death regulation, and provides novel molecular therapeutic targets and strategies for the treatment of HCC[7]. These findings further indicate that it is of great potential to explore the mechanism of HCC development from the perspective of molecular targeting. For example, relevant studies have confirmed that related signaling molecules such as alpha fetoprotein, fibroblast growth factor receptor 4, and orosomucoid 1 are predictive biomarkers for the efficacy of HCC targeted therapy. These markers provide a key entry point for the targeted therapy of HCC[3]. However, due to difficulties in early diagnosis, distant metastasis, and drug resistance, the overall prognosis for patients with HCC remains poor. The complexity of HCC determines that we still need to continuously explore new potential targets. Therefore, developing new diagnostic biomarkers and therapeutic targets for HCC is crucial for improving patient prognosis.

Zinc finger proteins (ZNFs) represent the most extensive group of transcription factors within the human genome. In structure, the core of ZNF is that zinc ions coordinate with specific amino acid residues to form a stable domain similar to “finger.” In terms of biological function, it can act as a transcription factor to bind to specific DNA sequences to regulate gene transcription, bind to RNA to affect post-transcriptional gene expression, and participate in protein-protein interaction to regulate the activity, localization and stability of proteins in signal transduction pathway[8]. As part of the ZNF family, ZNF71 is closely related to a variety of tumors, including esophageal cancer[9], pancreatic cancer[10], and colon cancer[11]. Furthermore, Some ZNF71 members are overexpressed in HCC and promote its progression, making ZNFs promising as new biomarkers and therapeutic targets for HCC[8]. Despite this, investigations into the role of ZNF71 in HCC remain limited.

This study employed high-throughput sequencing and immunohistochemistry (IHC) to evaluate the expression and clinical significance of ZNF71 in HCC, thereby investigating its underlying molecular mechanisms with the goal of identifying novel biomarkers for the diagnosis and prognosis of HCC.

MATERIALS AND METHODS

Assessment of ZNF71 protein level in HCC tissues via IHC

For this analysis, 228 liver tissue microarrays were acquired, specifically 194 HCC and 34 non-HCC (including normal liver parenchyma as well as tissues from conditions such as cirrhosis, benign hepatic lesions, and other non-malignant liver disorders). Moreover, 7 HCC and 12 non-HCC tissue samples were procured from the First Affiliated Hospital of Guangxi Medical University (Guangxi, China). The inclusion criteria for this study were patients who had not received preoperative radiotherapy, chemotherapy, or immunotherapy. The exclusion criteria were patients with missing clinical or pathological data. Ethical approval for this study was granted by Pantomics, Inc. (Guilin Fanpu Biotechnology, Guilin, China) and the Ethics Committee of the First Affiliated Hospital of Guangxi Medical University (Ethics No. Fanpu [2018] 23; Guangxi, China). Clinical and pathological parameters, including age, sex, pathological grade, and tumor-node-metastasis stage, were collected. Informed consent was obtained from all participants and their families. To determine the subcellular localization of ZNF71, data were sourced from the Uniprot protein database (https://www.uniprot.org/). The correlation between ZNF71 protein expression and clinical-pathological features was analyzed using the UALCAN database (https://ualcan.path.uab.edu/index.html). IHC staining was performed using the EnVision two-step procedure. Tissue samples from both HCC and non-HCC were embedded in paraffin, sectioned, and underwent antigen retrieval processes. Following retrieval, the sections were incubated first with the primary ZNF71 antibody and then with an EnVision secondary antibody. Next, sections were washed and developed with diaminobenzidine chromogen. ZNF71-stained slides were utilized as positive controls, whereas sections treated with phosphate-buffered saline in lieu of the primary antibody served as a negative control. Slide evaluation was independently conducted by two pathologists employing a double-blind review method. Final IHC sections were scored based on both staining intensity and the percentage of ZNF71-positive cells observed. Staining intensities were classified as follows: No staining (0), weak staining/light yellow (1), moderate staining/brown (2), and strong staining/dark brown (3). Scores for the percentage of expressing cells were: No expression (0), ≤ 25% expression (1), 26%-50% expression (2), 51%-75% expression (3), and > 75% expression[12-14].

High-throughput RNA sequencing and gene array detection of ZNF71 levels in HCC

HCC datasets were collected from The Cancer Genome Atlas, Genotype-Tissue Expression project, Gene Expression Omnibus, and ArrayExpress databases. The inclusion criteria were as follows: (1) The study subjects were humans; (2) The dataset included information on ZNF71 expression; (3) Data covered both HCC and non-HCC tissues; (4) The sample size met specific requirements; and (5) Data could be processed under current study conditions. StataV12.0 software was used to calculate the standard mean difference using a random effects model, and the Egger and Begg tests were used to assess publication bias, with P ≥ 0.05 indicating no publication bias. StataV12.0 software was used to plot the summary receiver operating characteristic curve and calculate the specificity, sensitivity, and likelihood ratios of ZNF71.

Investigating the regulatory impact of ZNF71 on HCC cell proliferation

This study examined the regulatory role of ZNF71 in HCC cell proliferation using clustered regularly interspaced short palindromic repeats (CRISPR) knockout screen. We evaluated the significance of ZNF71 by assessing dependency scores derived from the Clouds and the Earth's Radiant Energy System (CERES) algorithm in various HCC cell lines. Observations of negative dependency scores indicate a critical dependency on ZNF71 for cell growth, as its deletion leads to reduced proliferation. By contrast, positive dependency scores suggest that silencing ZNF71 could inhibit cell growth, pointing to its potential role as a growth suppressor in these cells[15].

Expression of ZNF71 mRNA in HCC cell lines

The expression levels of ZNF71 in HCC cell lines were examined using the RNA expression matrix from the Cancer Cell Line Encyclopedia dataset. Analysis of mRNA expression was performed with R software version 4.0.3 and visualized through horizontal bar charts employing ggplot2 version 3.3.3[16].

Co-expression gene enrichment analysis of ZNF71

Using the LinkedOmics database (http://www.linkedomics.org), Pearson correlation analysis was performed to identify genes co-expressed with ZNF71. Genes were selected based on P < 0.01 and an absolute correlation coefficient ≥ 0.3, indicating both positive and negative correlations. Kyoto Encyclopedia of genes and genomes enrichment analysis of the selected genes was conducted using Sangerbox 3.0 (http://vip.sangerbox.com/home.html). Significant enrichment was defined by P < 0.05 and a false discovery rate < 0.1. The top 10 most significant enriched pathways were visualized.

Relationship between ZNF71 expression and immune cell presence in HCC

The relationship between ZNF71 protein levels and the infiltration of various immune cells, such as CD4⁺ T cells, B cells, regulatory T cells, monocytes, macrophages, and myeloid dendritic cells in HCC was assessed using the TIMER2.0 portal (http://timer.comp-genomics.org/timer/). Associations were considered significant with a correlation coefficient (ρ) > 0.3 and P < 0.05.

Statistical analyses

The statistical evaluations and graphical representations were performed utilizing platforms such as UALCAN, LinkedOmics, Sangerbox 3.0, StataV12.0, and TIMER2.0. Quantitative outcomes were expressed as mean ± SD and assessed using the t-test. Categorical variables are presented as percentages and analyzed using the χ²-tests or Fisher’s exact test, as appropriate. A confidence interval (CI) of 95% was employed, and findings with P < 0.05 were deemed statistically significant.

RESULTS

High protein expression level of ZNF71 in HCC tissues based on IHC

IHC experiments were performed on 201 HCC tissue samples and 46 non-HCC tissue samples. The results showed that non-cancer tissues were negative, whereas cancer tissues were positive (Figure 1). Compared to normal tissues, ZNF71 expression was upregulated in HCC tissues (P < 0.05) (Figure 2A) and was elevated across stages I, II, and III (Figure 2B), showing an upward trend in HCC grading (Figure 2C), with all differences being statistically significant. However, there was no significant difference in ZNF71 expression related to distant lymph node metastasis (Figure 2D). To clarify the clinical and pathological significance of ZNF71 protein in patients with HCC, this study assessed the correlation between ZNF71 protein expression and various clinical and pathological factors using univariate analysis. The findings revealed no significant association between ZNF71 protein expression and patient age, sex, pathological grade, or tumor-node-metastasis stage (P > 0.05) (Table 1).

Figure 1 Expression of zinc finger protein 71 protein is elevated in hepatocellular carcinoma tissues compared to non-hepatocellular carcinoma tissues. A-F: Immunohistochemistry images; G: Receiver operating characteristic curve; H: Violin plot. AUC: Area under the curve; CI: Confidence interval; FPR: False positive rate; HCC: Hepatocellular carcinoma; TPR: True positive rate.

Figure 2 Clinicopathological features of zinc finger protein 71 in hepatocellular carcinoma tissues. A: Expression of zinc finger protein 71 (ZNF71) in hepatocellular carcinoma (HCC) and non-HCC (P < 0.05); B: Expression of ZNF71 in HCC was based on cancer stage (stage 1/2/3 vs normal, P < 0.05; stage 4 vs normal, P > 0.05); C: Expression of ZNF71 in HCC was based on the tumor grade (P < 0.05); D: Expression of ZNF71 in HCC was based on lymph node metastasis (N0 vs normal, P < 0.05; N1 vs normal, P > 0.05). LIHC: Liver hepatocellular carcinoma; TCGA: The Cancer Genome Atlas.

Table 1 Clinicopathological parameters associated with zinc finger protein 71 expression in patients with hepatocellular carcinoma.

Clinicopathological characteristics	n	mean ± SD	t/F	P value
Age			0.001	0.978
≥ 55	64	10.25 ± 2.30
< 55	113	10.23 ± 2.36
Sex			0.542	0.298
Male	157	10.37 ± 2.24
Female	20	9.20 ± 2.78
Pathological grade			1.582	0.812
I	11	10.00 ± 2.37
I-II	10	9.80 ± 3.05
II	122	10.23 ± 2.33
II-III	12	11.00 ± 1.81
III	22	10.18 ± 2.30
TNM_T			0.616	0.735
T1	1	12 ± 0
T2	144	10.22 ± 2.35
T3	32	10.25 ± 2.26
TNM_N			-1.11	0.27
N0	175	10.22 ± 2.33
N1	2	12 ± 0

SD: Standard deviation; TNM: Tumor-node-metastasis.

High ZNF71 mRNA expression levels in HCC based on multiple datasets

Comprehensive data analysis was conducted by extracting records from The Cancer Genome Atlas, Genotype-Tissue Expression project, Gene Expression Omnibus, and ArrayExpress, initially involving 5232 datasets. Non-relevant datasets such as duplicates, non-transcriptomic, and non-human entries were discarded. A total of 904 datasets were further eliminated based on irrelevance in abstracts or titles, resulting in 81 datasets eligible for scrutiny. From these, 30 datasets were excluded due to lack of data availability and 19 for containing data from interventional studies, leaving 32 datasets for in-depth analysis (Figure 3). Findings revealed that ZNF71 mRNA levels were significantly higher in HCC tissues compared to normal counterparts (standard mean difference = 0.55, 95%CI: 0.34-0.75) (Figure 4A). Given the considerable heterogeneity observed (I² = 88.9%, P < 0.001), analysis was conducted using a random effects model. Publication bias was evaluated using the Begg and Egger tests, resulting in P values of 0.733 and 0.837, respectively (Figure 4B and C), indicating no substantial bias and confirming the reliability of the findings. The efficiency measured by the area under the curve of the summary receiver operating characteristic stood at 0.78 (95%CI: 0.75-0.82) (Figure 4D), with sensitivity and specificity demonstrated in Figure 4E at 0.63 (95%CI: 0.53-0.72) and 0.82 (95%CI: 0.73-0.89), respectively. The diagnostic likelihood ratios for positive and negative outcomes (Figure 4F) were 3.61 (95%CI: 2.41-5.41) and 0.45 (95%CI: 0.36-0.56), respectively, supporting the potential clinical utility of ZNF71 in HCC.

Figure 3 Flowchart of the inclusion analysis process. GEO: Gene Expression Omnibus; GTEx: Genotype-Tissue Expression project; TCGA: The Cancer Genome Atlas.

Figure 4 High zinc finger protein 71 mRNA expression levels in hepatocellular carcinoma. A: Forest plot of the association between zinc finger protein 71 expression and hepatocellular carcinoma; B: Begg’s test for publication bias; C: Egger’s test for publication bias; D: Summary receiver operating characteristic curve; E: Sensitivity and specificity analysis; F: Positive and negative likelihood ratios. AUC: Area under the curve; CI: Confidence interval; SMD: Standardized mean difference; SROC: Summary receiver operating characteristic.

Exploring the impact of ZNF71 on HCC cell proliferation

The influence of ZNF71 on the proliferation of HCC cell was assessed using CRISPR knockout screening (Figure 5A). Interference with ZNF71 significantly impeded the growth across 18 HCC cell lines, indicating a potential role in promoting cell proliferation within HCC.

Figure 5 Impact of zinc finger protein 71 on hepatocellular carcinoma cells. A: Impact of zinc finger protein 71 (ZNF71) gene disruption across 18 hepatocellular carcinoma (HCC) cell lines (effect score of ZNF71 plotted for each cell line, displayed on the horizontal axis, with cell lines enumerated vertically); B: ZNF71 mRNA expression in HCC cell lines (horizontal axis: ZNF71 mRNA levels in transcripts per million; vertical axis: HCC cell lines).

Assessment of ZNF71 mRNA expression in HCC cell lines

Figure 5B illustrates the variability in ZNF71 expression across 20 HCC cell lines derived from the Cancer Cell Line Encyclopedia database. The data revealed differential expression levels of ZNF71 among the cell lines, with HLF and SNU-398 cells exhibiting the highest expression.

Co-expressed genes and signaling pathways of ZNF71

Analysis of mRNA sequences of patients with HCC using LinkedOmics revealed a significantly higher number of positively co-expressed genes compared to negatively co-expressed ones (Figure 6A). ZNF71 showed strong positive correlations with genes such as ZNF470, ZNF256, and ZNF285 (Pearson correlation coefficients = 0.5968, 0.5498, and 0.5331 respectively, P < 0.05) (Figure 6B and C), suggesting that ZNF71 may promote tumor development by influencing transcriptional processes. Enrichment analysis of 959 positively and 432 negatively co-expressed genes identified key pathways, which were visualized (Figure 6D and E). Positively correlated genes were primarily enriched in pathways related to Herpes simplex virus type 1 infection, the cell cycle, and DNA replication, while negatively correlated genes played roles in metabolic pathways, peroxisomes, and fatty acid degradation.

Figure 6 Co-expressed genes and signaling pathways of zinc finger protein 71. A: Zinc finger protein 71 (ZNF71) co-expressed genes in patients with hepatocellular carcinoma (HCC); B: ZNF71 positively correlated co-expressed genes in HCC; C: ZNF71 negatively correlated co-expressed genes in HCC; D: Enrichment analysis of ZNF71 positively correlated co-expressed genes in HCC; E: Enrichment analysis of ZNF71 negatively correlated co-expressed genes in HCC. KEGG: Kyoto Encyclopedia of Genes and Genomes.

Association of ZNF71 expression with immune cell infiltration in tumors

Utilizing TIMER2.0 for our analyses, it was established that elevated ZNF71 expression was significantly associated with the presence of various immune cell types in HCC (Figure 7). This includes CD4⁺ T cells (ρ = 0.379, P < 0.05), B cells (ρ = 0.386, P < 0.05), regulatory T cells (ρ = 0.324, P < 0.05), monocytes (ρ = 0.304, P < 0.05), macrophages (ρ = 0.345, P < 0.05), and myeloid dendritic cells (ρ = 0.388, P < 0.05). The data suggest a significant link between ZNF71 expression and immune cell infiltration levels in HCC.

Figure 7 Correlation of zinc finger protein 71 with immune-infiltrating cells (P < 0.05). TPM: Transcripts per million; ZNF71: Zinc finger protein 71.

DISCUSSION

HCC is recognized as a highly aggressive malignancy, presenting significant challenges to public health. Recent advances in high-throughput technologies have propelled the quest for diagnostic markers and therapeutic targets in oncology to the forefront. Traditional markers such as alpha fetoprotein, des-gamma-carboxy prothrombin, hepatocyte growth factor, alongside newer biomarkers such as splicing factor 3b subunit 4 and Kruppel-like transcription factor 2, illustrate this shift. Despite extensive research into various biomarkers for HCC, there remains a pressing need for breakthroughs that could revolutionize diagnosis and therapy in this field. Therefore, the discovery of novel biological markers is imperative for improving diagnosis, therapy, and prognostic evaluation in HCC. Interest in the ZNF gene family’s involvement in HCC has been increasing. For instance, ZNF143 has been noted to enhance HCC cell proliferation, suggesting its potential as a new biomarker and therapeutic target[17]. ZNF384 has been characterized as an oncogenic factor in HCC and might act as a prognostic indicator[18]. Yet, the clinical relevance and molecular mechanisms of ZNF71 within this family in HCC remain underexplored. In 2000, ZNF71 was reportedly induced in human umbilical vein endothelial cells by tumor necrosis factor α[19]. Research into the role of ZNF71 in cancer began emerging in 2018 when Guo et al[20] identified differential expression patterns between non-small cell lung cancer and healthy tissue, highlighting its potential as a biomarker to enhance treatment and prognosis in non-small cell lung cancer. By 2022, investigations into ZNF71 expanded slightly, with several studies verifying its role in promoting the development or progression of diseases such as osteosarcoma, oral squamous cell carcinoma, laryngeal squamous cell carcinoma, and non-small cell lung cancer, positioning it as a viable clinical marker[21-25].

Despite observations of ZNF71 overexpression in various cancers, its clinical implications in HCC have yet to be documented. This investigation utilizes IHC and online database assessments to examine ZNF71 expression levels in HCC and their correlation with clinical pathologic features. Techniques such as single-cell sequencing and CRISPR knockout screening have confirmed the elevated expression of ZNF71 in HCC tissues, indicating a significant disparity in expression between HCC and non-HCC tissues and positioning ZNF71 as a potential novel early diagnostic and prognostic marker for HCC.

To delve deeper into the role of ZNF71 in HCC, this research examined its co-expressed genes, revealing that genes with strong positive correlations predominantly function as transcription factors[25,26]. These genes play a significant role in cancer genesis and progression, pointing to the potential impact of ZNF71 on HCC via modulation of the cell cycle pathway. The ZNF gene family is notably linked to tumorigenesis. For example, as a ZNF transcription factor, zinc finger and SCAN domain containing 20 (ZSCAN20) is up-regulated in HCC and is closely related to the clinicopathological features and prognosis of patients with HCC. The effect of ZSCAN20 on HCC may be achieved through processes such as cell cycle, immune infiltration, and m6A modification, which is expected to be a biomarker for HCC diagnosis, treatment, and prognosis[25]. Elevated expression of ZNF of the cerebellum 2 correlates with adverse outcomes and shorter survival rates among patients with HCC, suggesting its pivotal role in the tumor’s immune infiltration microenvironment[27]. Moreover, the high expression of ZFP41 is associated with poor prognosis of patients with HCC, and plays a key role in cell viability, proliferation, migration, invasion and glycolysis. It may be a potential prognostic biomarker and therapeutic target for HCC[28]. Additionally, negatively correlated genes, like hydroxyacyl-coenzyme A dehydrogenase[29] and lactate dehydrogenase D[30], primarily intervene in the metabolic processes of HCC. Thus, ZNF71 may influence the transcriptional processes of HCC cells through its positively co-expressed genes, particularly the ZNF gene family, and regulate cellular metabolic pathways through negatively co-expressed genes, leading to the onset and progression of HCC.

Subsequent enrichment analyses of genes co-expressed with ZNF71 indicate that genes positively associated may influence HCC development through mechanisms involving viral infections, cell cycle control, DNA replication, and chromosomal stability. In contrast, genes that are negatively correlated seem to be integral in managing the metabolic functions within HCC cells. Thus, ZNF71 is posited to affect both cell cycle and metabolic pathways, which in turn could alter the progression and onset of HCC. While definitive evidence linking these processes to HCC is lacking, their potential influence remains significant. Concerning cell cycle regulation, ZNF643 appears to moderately alter cell cycle arrest[31]. Additionally, ZSCAN20, another ZNF essential for regulating gene expression, may play a role in cell cycle modification[32]. The outcomes of this enrichment analysis highlight the crucial role of ZNF71 in HCC progression, offering insights into novel therapeutic targets and providing a theoretical framework for further exploration of ZNF71 in HCC treatment.

The tumor immune microenvironment, closely related to tumor tissues, has become a consensus in the academic community. Based on the varying levels of immune cell infiltration in different tumors, immunotherapies such as immune checkpoint inhibitors hold substantial potential in HCC. This study suggests that ZNF71 might influence the efficacy of immune treatments in patients with HCC by regulating immune cell infiltration. Dendritic cell play a key coordinating role in tumor immune responses[33,34], with their expression strongly correlated with ZNF71. In the tumor microenvironment, the process of immune rejection of cancer cells depends on T cell activation[35,36]. To function effectively, dendritic cells must capture, process, and present antigens on major histocompatibility complex II to T cells, thereby activating them and linking innate and adaptive immune responses[34,37]. Interestingly, in the HCC environment, postoperative plasmacytoid dendritic cells secrete interferon α. The secretion of this cytokine mainly affects the recruitment of myeloid-derived suppressor cells. Myeloid-derived suppressor cells can inhibit the function of T cells, such as affecting the activity and proliferation of T cells, thus creating an immune environment conducive to the recurrence of HCC, which indirectly reflects the immune-related relationship between dendritic cells and T cells by affecting other cells[38]. Furthermore, tumor-associated macrophages (TAMs) are pivotal in the immune evasion process. In HCC, an increased presence of TAMs correlates with enhanced tumor growth and aggressiveness, typically resulting in an unfavorable postoperative outcome, and inhibition of TAM activity appears to beneficially impact HCC treatment[39]. Recent investigations have also demonstrated that the presence of TAMs in HCC tissues, characterized by a specific gene signature, is strongly associated with decreased survival rates in patients with HCC, highlighting the potential of targeting this form of tumor infiltration in HCC therapeutic approaches[40]. Therefore, it can be speculated that the upregulation of ZNF71 might alter the level of immune infiltration in the HCC microenvironment, particularly regulating cells, macrophages, CD4⁺, B cells, monocytes, and myeloid dendritic cells, thereby affecting the development process of HCC, but further experimental verification is needed.

In summary, this investigation integrates immunohistochemical techniques with extensive data analysis to confirm the overexpression of ZNF71 in HCC. It also demonstrates that elevated levels of ZNF71 protein are strongly linked with the pathological grades and clinical stages of HCC, offering a new perspective between HCC and non-HCC cases. Enrichment analysis has revealed that ZNF71 might influence cell cycle and metabolic processes, thereby accelerating the progression of HCC and emerging as a promising target for new treatments. Additionally, this study examines the tumor immune microenvironment in HCC, finding a significant correlation between increased ZNF71 expression and immune cell infiltration within HCC. Future investigations aim to clarify the specific roles of ZNF71 in HCC, particularly its interactions with immune infiltration and other elements of the tumor microenvironment. Additionally, attention will be paid to the application value of ZNF71 in different liver cancer subtypes, different clinical stages, and different treatment methods, providing more robust support for clinical practice. By deeply studying the role of ZNF71 in HCC, it is hoped that more accurate diagnostics, more effective treatments, and better prognoses can be provided for patients. However, due to the limited number of non-HCC cases included in this study, there is a potential risk of bias in the results. Future research will aim to include a larger number of non-HCC cases to further validate the findings and reduce this bias. Additionally, in vivo experiments using animal models will be necessary to validate the therapeutic potential of ZNF71 and provide further mechanistic insights into its role in HCC progression.

CONCLUSION

In conclusion, our research highlights the notable upregulation of ZNF71 in HCC, which appears to be closely associated with disease progression and severity. The significant expression levels of ZNF71 observed across various stages of HCC suggest its potential as a diagnostic marker and therapeutic target. Our analyses indicate that ZNF71 may influence key biological processes, such as the cell cycle and metabolic pathways, offering insights into possible mechanisms by which ZNF71 could contribute to tumor development and progression. Additionally, the correlation between ZNF71 expression and enhanced immune cell infiltration suggests a potential role for ZNF71 in the tumor microenvironment. While these findings provide promising directions for further research, additional studies are necessary to fully elucidate ZNF71’s role and its clinical applicability as a therapeutic target in HCC.

ACKNOWLEDGEMENTS

We would like to thank Guangxi Zhuang Autonomous Region Clinical Medicine Research Center for Molecular Pathology and Intelligent Pathology Precision Diagnosis for providing technical support.