Introduction

Gastric carcinoma (GC) is a major global public health issue, representing the fifth most common malignancy and the third leading cause of cancer-related death worldwide.1 Its incidence varies regionally: rates are higher in Eastern Asia, Central/Eastern Europe, and the Pacific regions of South America, while lower in North America and Africa.1,2 According to the 2019 World Health Organization’s (WHO) Classification of Tumors of the Digestive System, GC containing mucin is categorized into signet ring cell carcinoma (SRC) and mucinous gastric carcinoma (MGC), predicated upon whether mucin is intracellular or extracellular.3 Unlike SRC, MGC cells produce abundant mucus and secrete it through glandular ducts, forming a mucus lake that exceeds 50% of the tumor’s volume. Although rare (2.2–6.8% of GC), MGC often presents with advanced tumor stage, large volume, and high lymph node metastasis rates.4

MGC typically arises from the submucosa, maintaining an intact mucosal surface.5,6 This growth pattern poses diagnostic challenges during the gold standard gastroscopic biopsy, leading to inconsistent preoperative and postoperative diagnoses. With abundant fibrous tissue and mucin, MGC proliferates aggressively and is associated with poor outcomes.5,7 Although the WHO classifies GC with less than 50% tumor volume of extracellular mucin pool (LEMPC) as non-mucinous gastric carcinoma (NMGC), emerging evidence suggests that LEMPC may represent an intermediate phenotype with distinct clinicopathologic and imaging characteristics, and it may progress more rapidly than NMGC under similar treatment.8 Therefore, we included LEMPC as an independent comparison group in this study.

Recent research suggests characteristic MGC imaging findings, yet systematic analysis and robust pathological evidence remain insufficient.9–12 Further clarifying these features and exploring underlying mechanisms is crucial. MGC’s unique proliferative growth may alter stromal composition and angiogenesis compared to NMGC, potentially detectable via Enhanced Multi-slice Spiral CT (MSCT). Therefore, this study retrospectively analyzed the clinicopathological characteristics, CT features, and angiogenesis of MGC, LEMPC, and NMGC, aiming to delineate MGC’s distinct properties and investigate mechanisms associated with its angiogenic differences.

Patients and Methods Patients

A retrospective analysis was conducted on 40 pathologically confirmed MGC patients, 53 LEMPC patients, and 100 randomly selected NMGC patients (20 NMGC cases annually) between September 1, 2017, and August 31, 2022 at the First Affiliated Hospital of the University of South China. Inclusion criteria were curative surgery with histologically confirmed MGC, LEMPC, or NMGC; no prior treatments; and comprehensive clinical data. Exclusion criteria included distant metastasis or organ invasion precluding complete resection, prior malignancies, non-epithelial or specific carcinoma diagnosis, and mortality unrelated to gastric cancer. Ultimately, 29 MGC, 36 LEMPC, and 72 NMGC patients were included for clinicopathological evaluation.

Clinicopathological Analysis

Data on tumor location, maximum diameter, cell differentiation, depth of infiltration (T stage), lymph node metastasis (N stage), nerve invasion, and vascular invasion were collected from 138 GC patients. Pathological staging (pTNM) followed the 8th edition of the AJCC TNM system. Follow-up was conducted via telephone or outpatient reviews until November 2022, ranging from 4 to 62 months, (median, 30 months).

CT Technique

Preoperative imaging employed a 64-slice MSCT. After fasting for at least 6 hours, patients ingested 800–1000 mL of tepid water to distend the stomach. CT parameters included a 250 mA tube current, 120 kV tube voltage, 512×512 matrix, and 1 mm slice thickness. Scanning was performed in the supine position, followed by an enhanced scan with intravenous injection of 80 mL iohexol at 3–4 mL/s via the median cubital vein.

Image Analysis

Poor-quality images were excluded, leaving 27 MGC, 35 LEMPC, and 65 NMGC cases (n = 127) for MSCT evaluation. Two senior radiologists independently reviewed the MSCT images blinded to pathological findings, and any discrepancies were resolved by discussion to reach consensus. The radiologists assessed mucosal integrity, calcification, tumor enhancement ratio (solid vs mucus/necrotic), enhancement patterns (homogeneous, heterogeneous, stratified), and maximum tumor thickness. Homogeneous enhancement indicated a CT value difference <10 HU, heterogeneous enhancement involved cystic or necrotic areas, and stratified enhancement featured a low-density submucosal layer between enhanced mucosal and muscular layers. A 10-mm region of interest was placed in the area of maximal enhancement during the arterial or venous phase, excluding necrotic, mucosal, and artifact regions. To reduce inter-patient variability, maximum enhancement value (HU) was calculated as the highest arterial or venous CT value minus the plain CT value, and the enhancement ratio as that value divided by the abdominal aorta CT value during arterial enhancement. GC staging using enhanced MSCT is detailed in previous studies.13,14

Immunohistochemistry (IHC) and Microvessel Density (MVD) Analysis

Seventeen patients were randomly selected from each group (MGC, LEMPC, and NMGC) for IHC/MVD analyses. Two cases were excluded prior to staining due to inadequate tissue preservation, yielding 17 MGC, 16 LEMPC, and 16 NMGC cases and 98 paired postoperative tumor and corresponding paracancerous normal tissue samples for the final analysis. Sections were stained for CD34 (1:2500, Abcam, ab81289), VEGF-A (1:800, Proteintech, 66828-1-IG), HIF-1α (1:200, Proteintech, 20960-1-AP), and EGF (1:200, Proteintech, 27141-1-AP). Two senior pathologists, blinded to group assignments, evaluated staining.

IHC scores for VEGF-A, HIF-1α, and EGF were calculated by multiplying an intensity score (0=no staining, 1=light yellow, 2=yellow-brown, 3=brown-black) by the percentage of positive cells (<5%=0, 6–20%=1, 21–50%=2, >50%=3). Scoring was performed at ×400 magnification, averaging five random fields. For each case, the mean value across the five fields was used as the patient-level measurement to avoid pseudoreplication. Scores were classified as 0 (negative), 1–4 (weakly positive, +), 5–8 (positive, ++), and >9 (strongly positive, ++++), with 0–4 indicating low and ≥5 high expression. MVD was determined using a CD34 antibody in two steps: First, at ×50 magnification, areas with abundant GC cell infiltration and small vessels were selected, explicitly avoiding necrotic areas and mucin pools; second, microvessels were counted at ×200 magnification in five fields. Only CD34-positive endothelial clusters and small, isolated vascular branches were included, excluding large vessels or those wider than 8 red blood cells.

Statistical Analysis

Data were analyzed with SPSS 26.0 (IBM, New York, NY, USA), considering P < 0.05 statistically significant. Variables were assessed for normal distribution using analytical tests (Kolmogorov–Smirnov or Shapiro–Wilk). Categorical variables were expressed as percentages and compared using the χ2 or Fisher’s exact test. Measurement data were presented as mean ± standard deviation and compared with paired t-tests or one-way ANOVA for three-group comparisons. The concordance between enhanced MSCT-based staging and pathological staging (T, N, and TNM) was assessed using weighted kappa coefficients (strength of agreement interpreted using conventional thresholds). Kaplan-Meier curves and Log rank tests were applied to overall survival (OS), defined from surgery to death or last follow-up. Non-gastric cancer deaths were considered lost to follow-up. Risk factors were identified by univariate analysis, followed by Cox’s proportional hazards model to determine independent prognostic factors.

For the IHC / MVD subset, standardized effect sizes (Hedges’ g) with 95% confidence intervals were estimated for key comparisons, and patient-level bootstrap resampling (10,000 iterations) was used to obtain bootstrap 95% confidence intervals for effect sizes and mean differences; nonparametric sensitivity analyses were performed when distributional assumptions were not met.

Results Clinicopathologic Features and Laboratory Tests Across Three GC Subtypes

Sex distribution differed among the three groups (P < 0.05). The MGC group had more pyloric tumors (P = 0.001) and predominantly low or undifferentiated cells (P = 0.005). However, tumor markers (CA125, CA19-9, AFP, and CEA) did not differ significantly among groups [Table 1]. Although the MGC group generally displayed larger tumor diameters, higher T stages, and more advanced pTNM stages compared with the LEMPC and NMGC groups, these differences were not statistically significant [Table S1].

Table 1 Comparison of Clinicopathological Characteristics in Patients with MGC, LEMPC, and NMGC

Survival Comparison Across MGC, LEMPC and NMGC

The OS rate was significantly lower in the MGC group than in the NMGC group (P = 0.021). However, the LEMPC group showed no significant survival difference compared with either MGC or NMGC [Figure 1]. Univariate analysis identified the pathological type of MGC, tumor diameter >5 cm, T3/T4 infiltration depth, positive lymph node metastasis, and pTNM stages III/IV as risk factors, whereas no variables remained independently associated with OS in the multivariable Cox model [Table 2]. MSCT-based staging showed substantial agreement with pathologic staging (weighted κ: T = 0.643, N = 0.820, and TNM = 0.739; all P < 0.001; Tables S3–S5). Agreement remained moderate to almost perfect across MGC, LEMPC, and NMGC (all P < 0.001; Table S6).

Table 2 Univariate and Multivariate Analysis of Prognostic Impact Factors in Patients with MGC, LEMPC, and NMGC

Figure 1 (A–C) Kaplan-Meier Overall survival (OS) curves for gastric cancer patients.

MSCT Features and Tumor Enhancement Across Three GC Subtypes

Representative enhanced MSCT images for the three groups are shown in Figure S1–S3. Tumor thickening was greatest in the MGC group (P = 0.017). This group also exhibited higher rates of intact mucosal lines and calcifications (55.6% and 40.7%, respectively; P < 0.001, P = 0.001). Given the mucinous component, tumor enhancement range ratios ≥1 were found in 6 (22.2%) MGC, 21 (60%) LEMPC, and 65 (100%) NMGC cases, indicating that overall enhancement was most common in NMGC (P < 0.001). Enhancement characteristics also differed (P < 0.001): MGC commonly displayed layered reinforcement, LEMPC exhibited heterogeneous or layered reinforcement, and NMGC favored overall reinforcement (homogeneous or heterogeneous). The MGC group showed the lowest maximum tumor enhancement ratio (P < 0.001) [Table 3].

Table 3 Comparison of Clinical Imaging Characteristics of MGC, LEMPC, and NMGC Patients

MVD in Cancerous Tissues Across Three GC Subtypes

In NMGC, the MVD in cancerous tissues exceeded that of paracancerous normal tissues (P < 0.001). By contrast, MGC and LEMPC had lower MVD in cancerous tissues than in paracancerous tissues (P < 0.001) [Table S2, Figure 2]. Pairwise comparisons among cancerous tissues showed statistically significant differences in MVD (P < 0.001), while corresponding normal tissues did not differ among the three groups [Figure 2]. The overall between-group separation in tumor MVD was large and remained stable in resampling-based analyses (eg, MGC vs NMGC: Hedges’ g = −5.43).

Figure 2 Microvessel density (MVD) in carcinomas and corresponding paracancerous normal tissues in MGC, LEMPC, and NMGC. (A–C) Differential comparison of MVD in carcinomas and normal tissues from MGC (A), LEMPC (B), and NMGC (C). (D and E) Comparison of MVD levels in paracancerous normal tissues (D) and cancerous tissues (E) among the three groups. (F) Representative micrographs showing MVD in carcinoma and paracancerous normal tissues detected by immunohistochemical staining (×200, bar = 100μm). Statistical significance is indicated as follows: P < 0.0001; ns, not significant.

VEGF-A, HIF-1α, and EGF Expression in Cancerous Tissues Across Three GC Subtypes

In MGC and LEMPC, VEGF-A and EGF expression did not differ between cancer and paracancerous normal tissues; however, NMGC showed elevated VEGF-A and EGF in cancerous tissues (P = 0.033, P < 0.001). Among cancerous tissues, VEGF-A and EGF levels were significantly higher in NMGC than in MGC or LEMPC (P = 0.002, P < 0.001). Additionally, VEGF-A IHC scores differed notably between MGC and NMGC, while EGF varied between NMGC and both LEMPC and MGC [Figure 3]. HIF-1α expression levels showed no significant differences among MGC, LEMPC, and NMGC, and no intergroup variation was found in HIF-1α IHC scores [Figure 3]. Effect-size estimates were consistent with higher VEGF-A and EGF expression in NMGC than in MGC/LEMPC.

Figure 3 Immunohistochemistry (IHC) detection of vascular endothelial growth factor A (VEGF-A), hypoxia-inducible factor-1α (HIF-1α), and epidermal growth factor (EGF) in carcinomas and corresponding paracancerous normal tissues of MGC, LEMPC, and NMGC. (A–C) Representative immunohistochemical staining of VEGF-A (A), HIF-1α (B), EGF(C) in carcinomas and normal tissues (×400, bar = 50μm). (D–F) IHC score differences (cancer tissue score - normal tissue score) for VEGF-A (D) HIF-1α (E) EGF (F) among the three groups. Statistical significance is indicated as follows: P < 0.05; P < 0.001.

Abbreviation: ns, not significant.

Discussion

Research focusing exclusively on MGC as a distinct GC subtype remains relatively sparse, often limited to pathological studies.4,5,8 In MGC-related research, frequent comparisons with SRC—a GC subtype characterized by a different cellular localization of mucin—reveal distinct clinicopathological features.7,15,16 Bozkaya et al observed notable differences between SRC and MGC in vascular and neurological invasion, Borrmann staging, and tumor size.15 Building on these observations, our data further indicate that LEMPC, characterized by a lower proportion of extracellular mucin, also exhibits a relatively high risk of vascular invasion. This finding may be attributable to the higher prevalence of SRC components within LEMPC tissues, rendering these tumors more prone to vascular infiltration. Taken together, these results suggest that LEMPC represents a clinically relevant intermediate subtype rather than a simple variant of NMGC, particularly with respect to invasive behavior and vascular involvement. Beyond reinforcing known MGC traits, this study identified additional gender and tumor site distributions in MGC, while underscoring a lack of distinctive clinical test or tumor marker features for MGC and LEMPC.

MGC generally arises within the submucosa, leaving the superficial mucosa relatively intact, consistent with our imaging findings.5 Such a growth pattern hampers endoscopic biopsy, delaying diagnosis and contributing to advanced staging with unfavorable prognosis. Although extracellular mucin pools confer characteristic imaging appearances, many MGC-related studies employ simplistic designs, with conclusions limited to describing imaging features.17,18 Other studies have explored advanced imaging modalities in gastric cancer, including dynamic contrast-enhanced MRI, computed tomography perfusion, dual-energy CT imaging, and gallium-68-labeled fibroblast activation protein inhibitor PET/CT.9–12 In clinical practice, however, enhanced MSCT remains the primary imaging modality for abdominal tumor evaluation, warranting a more systematic MSCT-based investigation. By categorizing tumors into MGC, LEMPC, and NMGC according to extracellular mucin percentage, we demonstrated that MGC exhibits pronounced tumor thickening, layered enhancement patterns, and calcification—features discernible on enhanced MSCT. Rather than relying on perfusion parameters, we compared maximal tumor enhancement values and enhancement ratios across subtypes, revealing that MGC tends to display the lowest vascularization. These imaging characteristics, when interpreted alongside angiogenesis-related findings, may facilitate earlier recognition of MGC and improve subtype-specific clinical management.

Considering the impact of extracellular mucin pools on imaging phenotypes, elucidating angiogenesis-related mechanisms under varying vascular perfusion conditions is essential. This can be achieved by investigating MVD and the expression of key angiogenesis-related factors. Among these, VEGF-A is a potent driver of angiogenesis, promoting endothelial cell survival, proliferation, and migration.19,20 Likewise, EGF stimulates tumor growth via pathways such as RAS/RAF/MAPK and AKT/PI3K/mTOR, thereby promoting angiogenesis, invasion,and metastasis.21,22 Inhibiting EGF receptor signaling can suppress both vascularization and tumor growth.23,24 Our data demonstrated that MGC tissues exhibited the lowest MVD, accompanied by reduced VEGF-A and EGF expression, suggesting that diminished pro-angiogenic signaling may underlie MGC’s diminished vascularization.

HIF is a master regulator of oxygen sensing, influencing genes involved in oxygen consumption, erythropoiesis, angiogenesis, and mitochondrial metabolism.25 Although HIF-1α specifically promotes GC progression by enhancing β-catenin/VEGF-driven angiogenesis, our analysis revealed no significant differences in HIF-1α among MGC, LEMPC, and NMGC.26 One plausible explanation is that extensive extracellular mucin pools in MGC exacerbate intratumoral hypoxia while simultaneously limiting effective vascular development, thereby attenuating the translation of hypoxic signaling into downstream angiogenic output. In this context, hypoxia-related signaling may be present without a corresponding increase in angiogenic effector molecules at the protein level. Consistent with this interpretation, Hashimoto et al demonstrated that HIF-1α triggers multiple pro-angiogenic factors, including VEGF-A, platelet-derived growth factor-β, EGF, and fibrinogen activator inhibitor-1.27 Accordingly, the absence of detectable differences in HIF-1α expression, together with marked downregulation of VEGF-A and EGF in MGC tissues, suggests that impaired angiogenesis in MGC is more likely attributable to insufficient downstream effector signaling rather than altered HIF-1α abundance itself.

Notably, reduced angiogenesis in MGC may compromise chemotherapeutic efficacy by limiting drug delivery to tumor cells. Since angiogenesis is central to tumor growth and metastasis, inhibiting pathological neovascularization can improve tumor perfusion and drug distribution, thereby enhancing chemotherapy efficacy in GC patients.28–30 This suggests that diminished vascularization in MGC could contribute to chemoresistance. Future studies should further investigate the molecular interplay between mucus production and angiogenic regulation in MGC, which may inform strategies to optimize therapeutic delivery and improve clinical outcomes.

Conclusion

Our study systematically analyzed MGC and LEMPC—two GC subtypes characterized by extracellular mucin pools—by integrating clinically relevant tests, pathological features, and imaging data. Enhanced MSCT proved especially valuable for early detection and aided in distinguishing these subtypes based on their distinct morphological and enhancement characteristics. Moreover, our findings highlight that MGC exhibits significantly reduced angiogenesis, which is associated with the downregulation of VEGF-A and EGF. LEMPC exhibited intermediate clinicopathological and vascular features between MGC and NMGC, supporting its relevance as a distinct clinical subtype.

Abbreviations

EGF, epidermal growth factor; GC, gastric carcinomas; HIF-1α, hypoxia-inducible factor-1 alpha; IHC, immunohistochemistry; LEMPC, gastric carcinoma with less than 50% tumor volume of extracellular mucin pool; MGC, mucinous gastric carcinoma; MSCT, multi-slice spiral CT; MVD, microvessel density; NMGC, non-mucinous gastric carcinoma; OS, overall survival; SRC, signet ring cell carcinoma; VEGF-A, vascular endothelial growth factor A; WHO, World Health Organization.

Data Sharing Statement

The datasets generated and/or analyzed during the current study are available from the corresponding author Qiulin Huang upon reasonable request. No additional data are publicly available beyond those presented in this article.

Ethics Approval Statement

This study was conducted in accordance with the Declaration of Helsinki and was approved by the Ethics Committee of the First Affiliated Hospital of the University of South China (Approval No. 2022ll0801001). It was a retrospective analysis of archival formalin-fixed, paraffin-embedded gastric tissue specimens and anonymized clinical and imaging data. Accordingly, the requirement for individual written informed consent was waived by the ethics committee.

Consent for Publication

The Ethics Committee of the First Affiliated Hospital of the University of South China waived the requirement for individual written informed consent for the publication of anonymized clinical data and imaging findings due to the retrospective nature of the study.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Funding

This work was supported by the Natural Science Foundation of Hunan Province, China (Grant No. 2025JJ81050 & 2023JJ60368), Scientific Research Fund Project of Hunan Provincial Health Commission (Grant No.20201919 & 202104010105), Major Scientific Research Project for High-level Health Talents of Hunan Province Health Commission (Grant No. 20230533 & 20231526), and the National Primary-level Science Popularization Initiative Program (Science Communication Research and Practice Project; Grant No. KCXBKT2025052).

Disclosure

The authors report no conflicts of interest in this work.

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