Sage Journals: Discover world-class research

Abstract

Introduction

S100 calcium-binding protein A2 (S100A2) is associated with various tumors. However, its expression profile, clinical relevance, and prognostic value in hepatocellular carcinoma (HCC) remain unclear; therefore, this study assessed S100A2 expression levels in HCC and adjacent normal tissues.

Methods

To investigate the role of S100A2 in HCC, RNA sequencing and DNA methylation data were obtained from The Cancer Genome Atlas (TCGA)-Liver Hepatocellular Carcinoma (LIHC) cohort comprising 374 tumor and 50 normal liver tissues. A retrospective cohort of 216 HCC patients was also evaluated for correlations between S100A2 expression and clinicopathological characteristics. In a subset of 62 paired tumor and adjacent normal tissues, S100A2 protein and mRNA levels were assessed by immunohistochemistry (IHC) and quantitative RT-PCR. Finally, the relationship between S100A2 overexpression and clinicopathological variables was examined using the Cox proportional hazards regression model.

Results

Analysis of the TCGA-LIHC dataset revealed a marked elevation in S100A2 expression in tumor tissues compared to normal liver tissues. Consistently, DNA methylation analysis showed hypomethylation of several S100A2-associated CpG sites in liver hepatocellular carcinoma, suggesting a potential epigenetic mechanism for its upregulation. Correlation analysis demonstrated that increased S100A2 expression was associated with advanced histological grade, lymph node metastasis, serum alpha-fetoprotein level, microvascular invasion, tyrosine kinase inhibitor level, concurrent treatment, and higher Tumor, Node, Metastasis stage. Univariate analysis showed that elevated S100A2 levels were associated with significantly poorer recurrence-free survival (RFS) and overall survival (OS). Moreover, multivariate analysis identified S100A2 as an independent prognostic indicator for both RFS and OS. Kaplan–Meier survival curves also confirmed that patients with high S100A2 protein levels had significantly worse 5-year OS and RFS rates.

Conclusion

These findings indicate that S100A2 overexpression is associated with poor prognosis in patients with HCC, highlighting its potential utility as a diagnostic biomarker.

Plain Language Summary

Background: Recent studies have reported that the S100 calcium-binding protein A2 (S100A2) is associated with various tumours. Nonetheless, the prognostic role of S100A2 in hepatocellular carcinoma (HCC) is still unclear. Methods: Immunohistochemistry was employed to assess the S100A2 expression levels, and the relationship between S100A2 overexpression and clinical-pathological variables in HCC patients was explored. Results: A significant increase in S100A2 expression within HCC tissues compared to adjacent normal tissues was observed. Increased S100A2 expression correlated with histologic grade, lymph node metastasis, and TNM stage. In the univariate analysis, elevated S100A2 levels were strongly linked to lower recurrence-free survival (RFS) and overall survival (OS) in HCC patients. Multivariate analysis revealed that S100A2 is identified as an independent prognosis indicator of RFS and OS in HCC patients. Based on Kaplan-Meier analysis, high S100A2 protein levels are linked to worse 5-year OS and RFS in patients with HCC. Conclusion: According to the current findings, S100A2 overexpression serves as a poor prognosis indicator for HCC patients, underscoring its potential utility as a diagnostic biomarker for patients with HCC.

Keywords

S100 calcium-binding protein A2 hepatocellular carcinoma recurrence-free survival overall survival prognosis

1. Introduction

Hepatocellular carcinoma (HCC) is a common malignant solid tumor worldwide, accounting for 80–90% of all primary liver cancer cases.¹ Treatment modalities for HCC include liver transplantation, hepatic resection, radiotherapy, percutaneous ablation, and intra-arterial and systemic therapies.² However, owing to its insidious onset, less than 30% of patients are eligible for curative treatment at initial diagnosis.³ Although new systemic therapies have emerged, survival rates for advanced HCC remain low.⁴ Therefore, identifying novel therapeutic targets and reliable prognostic biomarkers for HCC is essential.

S100A2, a calcium-binding protein member of the S100 family encoded on chromosome 1q21,^5,6 significantly influences multiple oncogenic processes in HCC.⁷ It functions as a key regulator of intracellular calcium homeostasis and is involved in cell proliferation,⁸ migration,⁶ invasion,⁹ and apoptosis.¹⁰ S100 proteins, including S100A2, have been implicated in key aspects of HCC progression, including tumor cell proliferation,¹¹ metastasis,¹² and apoptosis.¹³ For instance, S100A2 silencing abrogates the suppressive effect of NFIC1 on cancer cell invasion and migration, thereby promoting metastasis by activating the MEK/ERK signaling pathway.¹⁴ The role of S100A2 in tumorigenesis is context-dependent, exhibiting both tumor-promoting and -suppressive functions in different cancer types. For instance, S100A2 is upregulated in endometrial¹⁵ and nasopharyngeal carcinomas,¹⁶ where it facilitates tumor progression and correlates with poor prognosis, whereas in gastric cancer, its loss is associated with lymph node metastasis and unfavorable outcomes.¹⁷ In HCC, S100A2 upregulation in HCC is driven by the hypoxia/hypoxia-inducible factor-1 alpha pathway and epigenetic modulation,¹⁸ and high S100A2 expression is linked to shorter overall survival (OS) in patients with HCC.¹⁹ Nevertheless, compared to well-characterized S100 family members, such as S100A4²⁰ and S100A6,²¹ the expression profile, clinical relevance, and prognostic significance of S100A2 in HCC remain unclear.

This study aimed to assess S100A2 expression levels in HCC and adjacent normal tissues using data from The Cancer Genome Atlas (TCGA), immunohistochemistry (IHC), and quantitative reverse transcription polymerase chain reaction (RT-qPCR), and to further analyze its associations with clinicopathological features and patient prognosis. The primary objective of this study was to determine its prognostic significance and potential as a therapeutic target for HCC.

2. Materials and Methods

2.1. Patients

This retrospective study included 216 patients with HCC treated at Longyan Second People’s Hospital between January 2012 and December 2019. All the participants signed a written informed consent form allowing the use of their clinical data and tissue samples for research purposes. The medical data of all patients were carefully evaluated and approved for use by the Longyan Second People’s Hospital Medical Ethics Committee (IRB approval number: LYEYEC 2023-026, IRB approval date: May 21, 2023). The inclusion criteria were as follows: (i) histopathologically confirmed HCC; (ii) primary liver resection; (iii) no concurrent malignancies; and (iv) complete clinical data. Clinicopathological parameters, including sex, age, cirrhosis, HBsAg status, tumor size, pathological stage, histological grade, serum alpha-fetoprotein (AFP) level, microvascular invasion, tyrosine kinase inhibitor (TKI) level, concurrent treatment, and lymph node metastasis (LNM) status, were extracted from the medical records. All cases were pathologically confirmed and staged according to the Union for International Cancer Control (UICC) TNM, 8th edition. All patient information was de-identified, and individual identities could not be recognized. This study adhered to REMARK guidelines.²²

Postoperative follow-up was conducted via telephone interviews and clinical visits. The median follow-up duration was 66 months (range: 5–95 months), spanning from the date of surgery to the last follow-up (October 26, 2024) or death. OS is defined as the time elapsed from the commencement of treatment or surgery until death, the patient’s final follow-up (October 26, 2024), or death for any reason. According to this definition, the recurrence-free survival (RFS) period is the interval from the start of treatment or surgery to the recurrence or reappearance of the tumor.

2.2. TCGA Data Analysis

RNA sequencing datasets and DNA methylation profiles for liver hepatocellular carcinoma (LIHC), including 374 tumor and 50 normal liver tissues, were obtained from TCGA. Normalized S100A2 expression levels were analyzed for differential expression between tumor and normal groups. For DNA methylation, CpG sites associated with S100A2 were identified, and their beta values were visualized using a heatmap.

2.3. Immunohistochemistry

Following dewaxing and rehydration, IHC for S100A2 was performed on 62 paired 4-μm paraffin-embedded HCC and adjacent normal tissue sections according to the manufacturer’s instructions. Subsequently, sections were subjected to antigen retrieval and peroxidase blocking. They were then incubated for 1 h with rabbit monoclonal anti-S100A2 antibody (dilution 1:200, ab109494; Abcam, Cambridge, UK). Positive staining, characterized by brown chromogenic deposition in the nucleus and cytoplasm of the target cells, was confirmed by counterstaining with Mayer’s hematoxylin. Finally, all slides were examined under an optical microscope (Olympus BX53; Olympus Corporation, Tokyo, Japan) at 200× magnification, and staining specificity was verified using positive and negative controls.

2.4. Evaluation of the IHC Results

IHC results were evaluated by recording the percentage of S100A2-stained cells, followed by an assessment of intracellular staining intensity as described previously.²³ Two independent observers evaluated the fraction of immunopositive cells within the tumor matrix using the following criteria: 0 (0–10%), 1 (>10–30%), 2 (>30–50%), 3 (>50–70%), and 4 (>70–100%). Subsequently, staining intensity was scored semi-quantitatively as 0 (negative), 1 (mild), 2 (moderate), or 3 (intense). The overall score (range, 0–7) was calculated by summing the scores for positive cell percentage and staining intensity. The final score for each section was established by consensus among the observers. To assess the interrater reliability of the IHC scoring system, 30 cases were randomly selected for double-blind evaluation by two independent pathologists. Interobserver agreement was assessed using Cohen’s kappa (κ) coefficient.

2.5. RT-qPCR Assay

After RNA extraction with TRIzol reagent (Invitrogen, Waltham, MA, USA) and cDNA synthesis using RevertAid™ reverse transcriptase (Takara, Shiga, Japan), qPCR was conducted on an ABI PRISM 7500 system (Applied Biosystems, Waltham, MA, USA). The thermal cycling profile consisted of a 2-min hold at 50°C, a 10-min denaturation at 95°C, and 50 cycles of 95°C for 15 s and 60°C for 1 min. S100A2 was amplified using the primers 5′-GAAGGAACTTCTGCACAAGG-3′ (forward) and 5′-GTGCCAGGAAAACAGCATAC-3′ (reverse). Experiments were performed in triplicate, and relative mRNA expression was quantified using the 2^−ΔΔCt method, with data presented as the mean of three independent replicates. A standard curve was generated using 10-fold serial dilutions of the cDNA. Ct values were plotted against log10 of template concentration, and the slope was used to calculate primer efficiency using formula E = (10⁻¹/slope⁻¹) × 100%E = (10^{-1/slope}-1)\times 100\%E = (10⁻¹/slope⁻¹) × 100%. The efficiency was XX% and R² = 0.99.

2.6. Statistical Analyses

SPSS (version 26.0) was used for all data analyses, and P < 0.05 was considered statistically significant. The relationship between S100A2 IHC staining in adjacent normal (paired adjacent non-cancerous liver tissues) and tumor tissue was determined by conducting either a chi-square test or a t-test. The association between S100A2 expression and clinicopathological variables was explored using Fisher’s exact test. OS was defined as tumor-related mortality, whereas the onset of any local or distant recurrence defined RFS, whichever occurred initially. The discrepancies in RFS and OS between the low and high S100A2 groups were assessed using univariate and multivariate analyses.

3. Results

3.1. S100A2 Protein Expression is Upregulated in Patients with HCC

Analysis of TCGA-LIHC dataset revealed that S100A2 mRNA expression was significantly higher in tumor tissues than in normal liver tissues (374 vs. 50, P < 0.001; Figure 1A). DNA methylation analysis revealed distinct patterns at the CpG sites of S100A2 in tumor and normal tissues, with multiple sites exhibiting differential methylation levels (Figure 1B). Representative IHC images of S100A2 are shown in Figure 1C. The average IHC staining intensity of S100A2 was significantly elevated in HCC tissues compared with normal tissues (4.113 ± 0.24 vs. 2.806 ± 0.22; Figure 1D). Furthermore, S100A2 protein expression was significantly higher in patients with HCC than in normal tissues (34/62 vs. 22/62, P < 0.001). Specifically, 34 cases showed higher S100A2 expression in tumor tissue, 22 cases showed lower expression, and six pairs showed no significant difference. The inter-rater agreement analysis demonstrated substantial consistency, with κ values of 0.800 for normal tissues and 0.726 for tumor tissues (Supplementary Material). S100A2 mRNA expression was markedly increased in tumor tissues compared to that in normal tissues (P < 0.001; Figure 1E).

Figure 1.

Transcriptional expression and methylation analysis of S100 calcium-binding protein A2 (S100A2) in liver hepatocellular carcinoma (LIHC). (A) S100A2 mRNA expression in tumor and normal liver tissues from The Cancer Genome Atlas (TCGA)-Liver Hepatocellular Carcinoma (LIHC) cohort (n = 374 tumors, n = 50 normal samples). S100A2 was significantly upregulated in tumor tissues (**P < 0.01). (B) DNA methylation patterns of CpG sites within S100A2 in tumor and normal tissues. Multiple sites showed differential methylation levels. (C) Representative immunohistochemical staining of S100A2 in 62 paired tumor and adjacent normal tissues. Positive staining was primarily cytoplasmic. (D) Scatter plot comparing S100A2 protein staining scores (mean ± standard error of the mean) between normal and tumor tissues. Statistical significance was evaluated using a paired t-test (***P < 0.001). (E) Quantitative RT-PCR analysis of S100A2 mRNA expression level in paired liver hepatocellular carcinoma (LIHC) and normal tissues. Tumor tissues exhibited significantly higher S100A2 levels (***P < 0.001)

3.2. S100A2 Expression and Clinical Criteria Correlation in HCC

Elevated S100A2 expression was significantly associated with several adverse clinical outcomes, including lymph node metastasis (LNM; P = 0.010), higher histological grade (P = 0.008), serum AFP levels (P = 0.003), microvascular invasion (P = 0.022), TKI levels (P = 0.039), concurrent treatment (P = 0.005), and advanced TNM stage (P = 0.004) (Table 1).

Table 1.

Relationship Between High and Low S100A2 Expression and Different Clinical Indicators in 216 Patients With Hepatocellular Carcinoma (HCC)

Parameter	Overall	High expression of S100A2	Low expression of S100A2	P Value
n	216	119	97
Age, n (%)
< 65	100	54	46	0.764
≥ 65	116	65	51
Gender
Male	126	64	62	0.133
Female	90	55	35
TNM stage(AJCC)
0–II	114	52	62	0.004
III–IV	102	67	35
Histologic grade
G1–G2	142	69	73	0.008
G3	74	50	24
HBsAg
Negative	30	16	14	0.453
Positive	186	103	83
Cirrhosis
No	69	39	30	0.772
Yes	147	80	67
Tumor size
< 4cm	108	57	51	0.494
≥ 4cm	108	62	46
Serum AFP, ng/mL
≤400	83	38	45	0.003
>400	133	81	52
Microvascular invasion
Absent	167	85	82	0.022
Present	49	34	15
TKI
Sorafenib	154	78	76	0.039
lenvatinib	62	41	21
Concurrent treatment
TACE	105	68	37	0.005
radiotherapy	111	51	60
Recurrence
No	148	84	64	0.468
Yes	68	35	33
LNM
No	131	63	68	0.010
Yes	85	56	29

S100A2, S100 calcium-binding protein A2; HBsAg, hepatitis B surface antigen; AFP, alpha-fetoprotein; TKI, tyrosine kinase Inhibitor; LNM, lymph node metastasis. Bold values indicate P < 0.05.

3.3. Survival Analysis

The effects of S100A2 expression on OS and RFS were evaluated using Cox proportional hazard regression models (Tables 2 and 3). A univariate analysis was performed to assess mortality risk. S100A2 (P = 0.001; P < 0.001), TNM stage (P < 0.001; P < 0.001), histologic grade (P = 0.010; P = 0.008), serum AFP levels (P = 0.023; P = 0.024), microvascular invasion (P = 0.001; P = 0.001), TKI levels (P = 0.036; P = 0.040), concurrent treatment (P = 0.032; P = 0.030), and LNM (P = 0.031; P = 0.039) were significantly associated with OS and RFS. After adjusting for confounding factors, S100A2 (P = 0.005; P = 0.003), TNM stage (P = 0.003; P = 0.002), serum AFP levels (P = 0.003; P = 0.004), microvascular invasion (P = 0.002; P = 0.002), TKI levels (P = 0.007; P = 0.007), concurrent treatment (P = 0.015; P = 0.016), and LNM (P < 0.001; P = 0.001) were significantly associated with OS and RFS. Univariate and multivariate analyses indicated that age, sex, histologic grade, and tumor size were not significantly associated with OS or RFS.

Table 2.

Univariate and Multivariable Analysis of Factors Potentially Predictive of Overall Survival in 216 Patients With HCC

Characteristics	Hazard Ratio	Univariate	P-value	Hazard Ratio	Multivariate	P-value
Characteristics	Hazard Ratio	95%CI	P-value	Hazard Ratio	95%CI	P-value
Age, years
≥ 65 vs < 65	0.854	0.638-1.143	0.290	0.897	0.661-1.216	0.483
Gender
Male vs Female	0.941	0.702-1.262	0.685	1.091	0.792-1.505	0.594
TNM stage(AJCC)
III-IV vs 0-II	1.888	1.404-2.539	< 0.001	1.595	1.176-2.162	0.003
Histologic grade
G3 vs G1–G2	1.517	1.106-2.081	0.010	1.223	0.881-1.697	0.229
HBsAg
Negative vs Positive	1.228	0.810-1.862	0.333	1.414	0.925-2.163	0.110
Cirrhosis
Yes vs No	0.852	0.625-1.161	0.310	0.923	0.662-1.286	0.635
Tumor size
≥ 4 vs < 4cm	1.068	0.800-1.427	0.655	1.117	0.830-1.503	0.446
Serum AFP, ng/mL
≥ 400 vs < 400	1.414	1.049-1.905	0.023	1.598	1.170-2.183	0.003
Microvascular invasion
Absent vs Present	1.861	1.280-2.705	0.001	1.836	1.252-2.690	0.002
TKI
Sorafenib vs lenvatinib	0.713	0.519-0.978	0.036	0.641	0.464-0.886	0.007
Concurrent treatment
TACE vs radiotherapy	1.376	1.028-1.840	0.032	1.444	1.073-1.944	0.015
Recurrence
Positive vs Negative	0.767	0.559-1.053	0.101	0.904	0.628-1.303	0.589
LNM
Yes vs No	0.722	0.538-0.970	0.031	0.597	0.441-0.809	< 0.001
S100A2 expression
High vs Low	1.616	1.202-2.174	0.001	1.552	1.143-2.109	0.005

HCC, hepatocellular carcinoma; S100A2, S100 calcium-binding protein A2; HBsAg: hepatitis B surface antigen; AFP, alpha-fetoprotein; TKI, tyrosine kinase inhibitor; LNM, lymph node metastasis. Bold values indicate P < 0.05.

Table 3.

Univariate and Multivariate Analysis of Factors Potentially Predictive of Recurrence-free Survival in 216 Patients With HCC

Characteristics	Hazard Ratio	Univariate	P-value	Hazard Ratio	Multivariate	P-value
Characteristics	Hazard Ratio	95%CI	P-value	Hazard Ratio	95%CI	P-value
Age, years
≥ 65 vs < 65	0.852	0.637-1.141	0.336	0.887	0.655-1.202	0.441
Gender
Male vs Female	0.950	0.709-1.274	0.733	1.114	0.808-1.535	0.510
TNM stage(AJCC)
III-IV vs 0-II	1.925	1.430-2.590	< 0.001	1.631	1.203-2.213	0.002
Histologic grade
G3 vs G1–G2	1.532	1.117-2.103	0.008	1.238	0.892-1.720	0.202
HBsAg
Negative vs Positive	1.255	0.828-1.902	0.284	1.430	0.936-2.185	0.098
Cirrhosis
Yes vs No	0.862	0.633-1.173	0.346	0.942	0.677-1.310	0.722
Tumor size
≥ 4 vs < 4cm	1.065	0.798-1.423	0.974	1.126	0.836-1.517	0.434
Serum AFP, ng/mL
≥ 400 vs < 400	1.410	1.046-1.900	0.024	1.573	1.152-2.148	0.004
Microvascular invasion
Absent vs Present	1.857	1.277-2.700	0.001	1.821	1.243-2.667	0.002
TKI
Sorafenib vs lenvatinib	0.719	0.524-0.986	0.040	0.642	0.465-0.887	0.007
Concurrent treatment
TACE vs radiotherapy	1.379	1.031-1.844	0.030	1.442	1.072-1.940	0.016
Recurrence
Positive vs Negative	0.759	0.553-1.042	0.088	0.892	0.619-1.287	0.541
LNM
Yes vs No	0.733	0.546-0.985	0.039	0.612	0.453-0.828	0.001
S100A2 expression
High vs Low	1.650	1.226-2.221	< 0.001	1.591	1.169-2.164	0.003

HCC, hepatocellular carcinoma; S100A2, S100 calcium-binding protein A2; HBsAg: Hepatitis B surface antigen; AFP, alpha-fetoprotein; TKI, tyrosine kinase inhibitor; LNM, lymph node metastasis. Bold values indicate P < 0.05.

Kaplan–Meier analysis indicated that increased S100A2 expression was associated with unfavorable outcomes in patients with HCC (all P < 0.05) (Figure 2). In TCGA-LIHC cohort (n = 374), Kaplan–Meier survival analysis showed that patients with high S100A2 expression had significantly poorer OS than those with low S100A2 expression (P = 0.009, Figure 2A). Spearman’s correlation analysis showed that S100A2 expression was negatively correlated with OS (r = –0.16; Figure 2B). Moreover, the estimated 5-year OS and RFS rates in patients with HCC with different S100A2 expression levels (OS: 48.4% for low vs. 33.6% for high; RFS: 45.4% for low vs. 26.8% for high) corroborate this observation (Figure 2C–D).

Figure 2.

Correlation and survival analysis of S100A2 expression in hepatocellular carcinoma (HCC). (A) Kaplan–Meier overall survival curve of S100A2 expression in The Cancer Genome Atlas (TCGA)-Liver Hepatocellular Carcinoma (LIHC) cohort. (B) Spearman’s correlation heatmap between S100A2 expression and overall survival (OS) in TCGA-LIHC. Survival analysis based on S100A2 expression in patients with HCC. (C) Kaplan–Meier curves showing 5-year OS in patients with HCC, as well as OS according to S100A2 levels in 216 patients with HCC. (D) Kaplan–Meier curves showing the 5-year recurrence-free survival (RFS) rate in patients with HCC, as well as RFS according to S100A2 levels in 216 patients with HCC

4. Discussion

In this study, S100A2 expression was notably increased in HCC tissues compared with adjacent normal tissues. Increased S100A2 expression was significantly associated with TNM stage, histological grade, serum AFP levels, microvascular invasion, TKI levels, concurrent treatment, and LNM status, but not with age, sex, tumor size, HBsAg, cirrhosis, or recurrence. Furthermore, high S100A2 expression was associated with shorter OS and RFS. These findings suggest that S100A2 is a potential prognostic biomarker for HCC, highlighting its value in facilitating adjuvant therapy, particularly in high-risk subpopulations. Although previous in vitro studies (Jia et al¹⁸) have suggested potential regulatory mechanisms, to the best of our knowledge, this study is the first to demonstrate a direct correlation between hypomethylation of the S100A2 promoter and its protein overexpression in a clinical HCC cohort, offering novel mechanistic insight into its epigenetic regulation in human tumor tissues.

The prognostic significance of S100A2 in HCC is likely attributable to its involvement in multiple oncogenic signaling pathways. S100A2 acts as a potent activator of core oncogenic cascades, such as PI3K/AKT and TGF-β/Smad, which collectively drive key tumorigenic phenotypes, including sustained proliferation, enhanced migration, tissue invasion, and metastatic dissemination.^24,25 Furthermore, S100A2 has also been implicated in broader oncogenic mechanisms, such as metabolic reprogramming,²⁶ epithelial–mesenchymal transition,²⁷ and modulation of anti-tumor immune responses,²⁸ all of which are highly relevant to HCC pathogenesis and progression. In HCC specifically, PI3K/AKT and TGF-β/Smad pathway hyperactivation are major drivers of disease progression and directly promote proliferation and metastatic spread.^29,30 Given the characteristic glycolytic phenotype and high metabolic demand of HCC, S100A2 overexpression may further enhance tumor aggressiveness by reinforcing PI3K/AKT-mediated survival signaling and facilitating metabolic reprogramming, which supports rapid proliferation under nutrient stress.^31,32 Moreover, HCC develops within a unique microenvironment characterized by chronic inflammation, immune tolerance, and frequent exposure to viral hepatitis- or cirrhosis-related injuries.³³ In this liver-specific context, S100A2 may contribute to an immunosuppressive tumor microenvironment by altering immune cell infiltration, thereby promoting immune evasion and potentially diminishing the efficacy of both conventional therapies and immunotherapies.³⁴ Collectively, these mechanistic insights provide a biologically plausible foundation for the observed association between elevated S100A2 expression and poor prognosis in HCC.

This study confirmed that S100A2 is an independent prognostic marker in HCC, consistent with previous reports (Wan et al.¹⁹) linking its expression to poor survival outcomes. Unlike earlier studies that primarily emphasized correlations with survival, this study demonstrated that high S100A2 expression was systematically associated with multiple adverse clinicopathological features, providing direct tissue-level evidence of its role in tumor aggressiveness. These clinical observations are consistent with previous experimental findings indicating an oncogenic function of S100A2; its overexpression promotes tumor progression, and its silencing disrupts TGF-β–mediated invasion and migration, ultimately contributing to poor survival outcomes.³⁵ By integrating quantitative IHC scoring with survival analysis and methylation data, this study advances S100A2 from molecular observations to a clinically actionable biomarker framework by bridging mechanistic understanding with potential diagnostic and prognostic applications.

Numerous studies have demonstrated the roles of S100A2 in cancer therapy and drug resistance. For instance, targeting S100A2 during drug design may provide a novel therapeutic strategy for pancreatic cancer by disrupting its interaction with p53, thereby suppressing cancer cell proliferation and survival.³⁶ In head and neck squamous cell carcinoma, elevated S100A2 levels are a key factor in cisplatin-specific chemoresistance, where its overexpression sustains resistance even after cisplatin withdrawal.³⁷ Similarly, in colorectal cancer, the KRT6A/S100A2 axis promotes tumor progression, and inhibiting this pathway significantly enhances the anti-tumor efficacy of sinigrin, suggesting its potential as a therapeutic target.³⁸ Although these findings suggest a broader role of S100A2 in therapy resistance, direct evidence supporting the causal role of S100A2 in modulating chemotherapy sensitivity in HCC remains limited. Therefore, although S100A2 dysregulation may represent a biologically relevant feature of HCC, further mechanistic investigations and in vivo validation, including patient-derived xenograft models, are required to determine its therapeutic relevance.

This study has several limitations: First, its retrospective, single-center design may introduce potential confounding factors and biases owing to the lack of standardized follow-up protocols. Second, the limited sample size may compromise statistical power and limit the generalizability of the findings. Third, this study was primarily correlative, relying on clinical association and bioinformatics analyses without experimental validation of the mechanistic role of S100A2 in HCC.

5. Conclusion

This study identified S100A2 as an important biomarker for diagnosing and predicting HCC prognosis, and it may function as a gene that promotes tumor progression. Elucidating the molecular mechanisms underlying HCC progression could provide critical insights that guide the development of personalized targeted therapies for this disease. However, future multicenter studies with larger cohorts and more comprehensive experimental approaches are required to confirm the prognostic significance of S100A2 and further elucidate its molecular mechanisms in HCC.

Supplemental Material

Supplemental Material - Overexpression of S100 Calcium-Binding Protein A2 is Associated With Poor Prognosis in Hepatocellular Carcinoma

Supplemental Material for Overexpression of S100 Calcium-Binding Protein A2 is Associated With Poor Prognosis in Hepatocellular Carcinoma by Xiaopeng Chen, Ma Shaoqing, Zeng Wenlong, Huang Chuiguo, Jianyang Guo in Cancer Control.

Footnotes

ORCID iDs

Xiaopeng Chen

Shaoqing Ma

Wenlong Zeng

Jianyang Guo

Ethical Considerations

The medical data of all patients were carefully evaluated and sanctioned for use approved by the Longyan Second People’s Hospital’s medical ethics committee (IRB approval number: LYEYEC 2023-026, IRB approval date: May 21, 2023). This study was conducted in accordance with the Declaration of Helsinki.

Consent to Participate

Informed consent was obtained from all subjects involved in the study.

Authors’ Contributions

Conceptualization, Xiaopeng Chen and Shaoqing Ma; Methodology, Wenlong Zeng; Software, Jianyang Guo; Validation, Xiaopeng Chen, Chuiguo Huang and Shaoqing Ma; Formal analysis, Wenlong Zeng; Investigation, Shaoqing Ma; Resources, Jianyang Guo; Data curation, Chuiguo Huang; Writing—original draft preparation, Xiaopeng Chen; Writing—review and editing, Shaoqing Ma; Project administration, Xiaopeng Chen; All authors have read and agreed to the published version of the manuscript.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by Natural Science Foundation of Fujian Province (2022LYF17045).

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

The data used to support the findings of this study are included within the article and the supplementary information. The data and materials in the current study are available from the corresponding author on reasonable request.*

Supplemental Material

Supplemental material for this article is available online.

References

Coffin

. Hepatocellular Carcinoma: Past and Present Challenges and Progress in Molecular Classification and Precision Oncology. Int J Mol Sci. 2023;24(17):13274. doi:10.3390/ijms241713274.

Vogel

Meyer

Sapisochin

Salem

Saborowski

. Hepatocellular carcinoma. Lancet. 2022;400(10360):1345-1362. doi:10.1016/S0140-6736(22)01200-4.

Wang

Deng

. Hepatocellular carcinoma: molecular mechanism, targeted therapy, and biomarkers. Cancer Metastasis Rev. 2023;42(3):629-652. doi:10.1007/s10555-023-10084-4.

Altundag

. Recent Advances in Systemic Therapy for Hepatocellular Carcinoma. Exp Clin Transplant. 2024;22(1):3-8. doi:10.6002/ect.2021.0478.

Liang

Huang

Cai

, et al. The S100 family is a prognostic biomarker and correlated with immune cell infiltration in pan-cancer. Discov Oncol. 2024;15(1):137. doi:10.1007/s12672-024-00945-x.

Sugino

Sawada

. Influence of S100A2 in Human Diseases. Diagnostics (Basel). 2022;12(7):1756. doi:10.3390/diagnostics12071756.

Delangre

Oppliger

Berkcan

Gjorgjieva

Correia de Sousa

Foti

. S100 Proteins in Fatty Liver Disease and Hepatocellular Carcinoma. Int J Mol Sci. 2022;23(19):11030. doi:10.3390/ijms231911030.

Wang

. The S100 protein family in lung cancer. Clin Chim Acta. 2021;520:67-70. doi:10.1016/j.cca.2021.05.028.

Wolf

Haase-Kohn

Pietzsch

. S100A2 in cancerogenesis: a friend or a foe? Amino Acids. 2011;41(4):849-861. doi:10.1007/s00726-010-0623-2.

10.

Pan

Kuo

, et al. The p53-S100A2 Positive Feedback Loop Negatively Regulates Epithelialization in Cutaneous Wound Healing. Sci Rep. 2018;8(1):5458. doi:10.1038/s41598-018-23697-5.

11.

Cui

Dai

, et al. S100 protein family: Emerging role and mechanism in digestive tract cancer (Review). Int J Oncol. 2024;64(6):59. doi:10.3892/ijo.2024.5647.

12.

Liu

Cai

Zou

Meng

. Stanniocalcin 1 promotes lung metastasis of breast cancer by enhancing EGFR-ERK-S100A4 signaling. Cell Death Dis. 2023;14(7):395. doi:10.1038/s41419-023-05911-z.

13.

Zhang

Yang

Xing

Zhang

. Expression and gene regulatory network of S100A16 protein in cervical cancer cells based on data mining. BMC Cancer. 2023;23(1):1124. doi:10.1186/s12885-023-11574-y.

14.

Zhang

Wang

Liang

, et al. NFIC1 inhibits the migration and invasion of MDA-MB-231 cells through S100A2-mediated inactivation of MEK/ERK pathway. Arch Biochem Biophys. 2023;734:109497. doi:10.1016/j.abb.2022.109497.

15.

Zhang

Xia

. High expression of S100A2 predicts poor prognosis in patients with endometrial carcinoma. BMC Cancer. 2022;22(1):77. doi:10.1186/s12885-022-09180-5.

16.

Peng

Xia

Zhou

, et al. S100A2 upregulates GLUT1 expression to promote glycolysis in the progression of nasopharyngeal carcinoma. Histol Histopathol. 2024;39:18778. doi:10.14670/HH-18-778.

17.

Liu

Wang

Luo

. Clinical significance of S100A2 expression in gastric cancer. Tumour Biol. 2014;35(4):3731-3741. doi:10.1007/s13277-013-1495-3.

18.

Yan

Huang

Liu

Wang

. Transcriptional activation of S100A2 expression by HIF-1alpha via binding to the hypomethylated hypoxia response elements in HCC cells. Mol Carcinog. 2022;61(5):494-507. doi:10.1002/mc.23393.

19.

Wan

Tan

Qian

, et al. Prognostic Value of S100 Family mRNA Expression in Hepatocellular Carcinoma. Turk J Gastroenterol. 2024;35(4):316-334. doi:10.5152/tjg.2024.22658.

20.

El-Bendary

Farid

Arafa

Elkashef

Abdullah

El-Mesery

. Prognostic value of S100A4 and Glypican-3 in hepatocellular carcinoma in cirrhotic HCV patients. J Egypt Natl Canc Inst. 2023;35(1):26. doi:10.1186/s43046-023-00184-1.

21.

Chen

Ruan

, et al. S100A6 drives lymphatic metastasis of liver cancer via activation of the RAGE/NF-kB/VEGF-D pathway. Cancer Lett. 2024;587:216709. doi:10.1016/j.canlet.2024.216709.

22.

McShane

Altman

Sauerbrei

, et al. REporting recommendations for tumour MARKer prognostic studies (REMARK). Br J Cancer. 2005;93(4):387-391. doi:10.1038/sj.bjc.6602678.

23.

Kumar

Srivastava

Kaur

, et al. Prognostic significance of cytoplasmic S100A2 overexpression in oral cancer patients. J Transl Med. 2015;13:8. doi:10.1186/s12967-014-0369-9.

24.

Zhu

Zhang

, et al. LncRNA RP11-93B14.5 promotes gastric cancer cell growth through PI3K/AKT signaling pathway. Mol Biotechnol. 2024;66(9):2332-2340. doi:10.1007/s12033-023-00844-6.

25.

Chen

Guo

Jiang

, et al. S100A2 induces epithelial-mesenchymal transition and metastasis in pancreatic cancer by coordinating transforming growth factor beta signaling in SMAD4-dependent manner. Cell Death Discov. 2023;9(1):356. doi:10.1038/s41420-023-01661-1.

26.

Chen

Zhou

, et al. S100A2 promotes glycolysis and proliferation via GLUT1 regulation in colorectal cancer. FASEB J. 2020;34(10):13333-13344. doi:10.1096/fj.202000555R.

27.

Wang

Yang

Xiao

. miR-325-3p Promotes the Proliferation, Invasion, and EMT of Breast Cancer Cells by Directly Targeting S100A2. Oncol Res. 2021;28(7):731-744. doi:10.3727/096504020X16100888208039.

28.

Hatthakarnkul

Ammar

Pennel

KAF

, et al. Protein expression of S100A2 reveals it association with patient prognosis and immune infiltration profile in colorectal cancer. J Cancer. 2023;14(10):1837-1847. doi:10.7150/jca.83910.

29.

Sun

Ding

Song

, et al. FDX1 downregulation activates mitophagy and the PI3K/AKT signaling pathway to promote hepatocellular carcinoma progression by inducing ROS production. Redox Biol. 2024;75:103302. doi:10.1016/j.redox.2024.103302.

30.

Sun

Zuo

Yan

Yin

. RRM2 Regulates Hepatocellular Carcinoma Progression Through Activation of TGF-beta/Smad Signaling and Hepatitis B Virus Transcription. Genes (Basel). 2024;15(12):1575. doi:10.3390/genes15121575.

31.

Aoki

Nishida

Kurebayashi

, et al. Molecular classification of hepatocellular carcinoma based on zoned metabolic feature and oncogenic signaling pathway. Clin Mol Hepatol. 2025;31(3):981-1002. doi:10.3350/cmh.2024.1088.

32.

Yang

Hilakivi-Clarke

Shaha

, et al. Metabolic reprogramming and its clinical implication for liver cancer. Hepatology. 2023;78(5):1602-1624. doi:10.1097/HEP.0000000000000005.

33.

Anwar

Arslan

Sarfraz

, et al. Immunotherapy Responses in Viral Hepatitis-Induced HCC: A Systematic Review and Meta-Analysis. Curr Oncol. 2024;31(11):7204-7225. doi:10.3390/curroncol31110532.

34.

Chen

Wang

Song

Ruze

Zhao

. S100A2 Is a Prognostic Biomarker Involved in Immune Infiltration and Predict Immunotherapy Response in Pancreatic Cancer. Front Immunol. 2021;12:758004. doi:10.3389/fimmu.2021.758004.

35.

Zhao

Luo

Lei

Zhang

. Knockdown of ferritin heavy chain (FTH) inhibits the migration of prostate cancer through reducing S100A4, S100A2, and S100P expression. Transl Cancer Res. 2020;9(9):5418-5429. doi:10.21037/tcr-19-2852.

36.

Sun

Baker

Russell

, et al. Novel piperazine-1,2,3-triazole leads for the potential treatment of pancreatic cancer. RSC Med Chem. 2023;14(11):2246-2267. doi:10.1039/d2md00289b.

37.

Inukai

Nishimura

Okamoto

, et al. Identification of cisplatin-resistant factor by integration of transcriptomic and proteomic data using head and neck carcinoma cell lines. Nagoya J Med Sci. 2020;82(3):519-531. doi:10.18999/nagjms.82.3.519.

38.

Yang

Zeng

, et al. Sinapine thiocyanate exhibited anti-colorectal cancer effects by inhibiting KRT6A/S100A2 axis. Cancer Biol Ther. 2023;24(1):2249170. doi:10.1080/15384047.2023.2249170.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

2.20 MB