ABSTRACT
Background
The gingiva and floor of the mouth are distinct subsites, and oral squamous cell carcinoma (OSCC) originating in these locations warrants further indepth understanding.
Methods
This study enrolled patients with OSCC from 2000 to 2020, and analyzed the clinicopathological characteristics. Kaplan–Meier analysis compared overall survival (OS) and recurrence‐free survival (RFS). Univariate analysis and multivariate Cox proportional hazards model examined the risk factors on survival outcomes.
Results
A total of 885 OSCC patients were included, with the most common tumor subsites: oral tongue (41.9%), gingiva (31.8%), and floor of mouth (16.0%). Gingival and floor of mouth showed a higher proportion of advanced stage (65.8%, 66.9%) and significantly poorer OS (3‐year: 63.0%, 57.0%; 5‐year: 49.8%, 37.3%) and RFS (3‐year: 59.1%, 61.3%; 5‐year: 55.5%, 57.0%). Neoadjuvant chemotherapy was associated with significantly reduced mortality in gingival cancer (HR = 0.598), while tobacco exposure (HR = 1.952) was associated with a significant increase in mortality in floor of mouth cancer.
Conclusion
Gingival cancer and floor of mouth cancer have a worse prognosis, and thus require greater attention throughout the entire management process.
Keywords: floor‐of‐mouth, gingival, oral squamous cell carcinoma, prognosis, risk factor
1. Introduction
Oral cancer ranks as the 16th most prevalent cancer worldwide [1], and oral squamous cell carcinoma (OSCC) is the most common pathological type [2]. In China, the incidence of oral cancer ranks 19th among malignant tumors [3], and the incidence is increasing year by year. From 1990 to 2021, the number of male oral cancer patients in China increased by 341.20%, and that of female patients increased by 180.33%. It is estimated that by 2036, the number of male oral cancer patients will continue to increase by 52.25%, and that of female patients will increase by 85.27% [4]. As the burden of oral cancer on China gradually increases, there is a growing focus on its precise management of OSCC. Oral cancer can be classified into six subsite origins based on anatomical locations: buccal mucosa, floor of mouth, oral tongue, gingival, retromolar trigone, and hard palate [5]. However, the gingiva and floor of mouth differ from other oral subsites in terms of anatomy, histological structure, and microenvironment, and thus these two subsites exhibit distinct disease characteristics. For example, the mandibular gingiva is a mere 2 mm or so in thickness, rendering it highly susceptible to early bone invasion and progression to advanced disease stages [6]. The floor of mouth comprises loose connective tissue with interconnected anatomical spaces, along with a dense network of lymph nodes and nerves, features that facilitate the spread of tumors along these spaces [7, 8]. Thus, enhancing focus on these highly invasive subsites, analyzing their disease characteristics and prognostic factors, can provide a theoretical basis for the individualized management of patients with OSCC.
This study compared the clinicopathological features and prognosis of OSCC at our center, and analyzed the risk factors affecting the long‐term survival of patients with gingival cancer and floor of mouth cancer, thereby providing management recommendations for patients with OSCC in these subsites.
2. Methods
2.1. Design of the Study and Populations
This retrospective study enrolled patients initially diagnosed with primary OSCC at our institution who underwent surgical intervention between 2000 and 2020. Exclusion criteria included, unclear primary tumor site, involvement of multiple primary tumor sites, absence of surgical intervention, unclear treatment strategy, lack of intraoperative pathological data, or having other malignant tumors. The analysis considered patient demographics (age, sex, tobacco and alcohol consumption), tumor characteristics (primary subsite, TNM stage, depth of invasion, lymph node metastasis and grade of differentiation), and treatment details (neck dissection, neoadjuvant chemotherapy), and the patients were followed up at 3 and 5 years after surgery to compare the incidence of endpoint events (death and disease recurrence) and to identify associated risk factors.
2.2. Statistical Analyses
Univariate analysis: analysis of variance (ANOVA) is used. For cases involving theoretical frequencies < 5, Fisher's exact test is applied. For ordinal data, the Kruskal–Wallis H test is adopted. Kaplan–Meier method to assess differences in OS and RFS across various subsites. The log‐rank test determined statistical significance, with a p value < 0.05. Clinical pathological characteristics with p < 0.05 in univariate analysis (tobacco, T stage, N stage, differentiation grade, and neoadjuvant chemotherapy) were prioritized for inclusion in multivariate analysis. Additionally, factor (alcohol) potentially associated with the development of OSCC were also included into the analysis. Multivariate Cox proportional hazards model was used to identify clinicopathological factors influencing survival, calculating hazard ratios and 95% confidence intervals (95% CI). Analyses were conducted using SPSS R26.0.0.0 software.
3. Results
3.1. Demographics
This study retrospectively collected 1132 patients who were first admitted to our center and underwent surgical treatment from 2000 to 2020, and finally included 885 patients with complete medical record data and follow‐up data (median follow‐up time of 52.0 months [IQR: 17.0–96.0 months]) (Table 1). The patient population in this study was predominantly males over 50 years old, with 695 patients (78.5%) aged above 50 and 570 male patients (64.4%). Most patients had a history of tobacco exposure (n = 445, 50.3%), with the highest proportion observed in patients with floor of mouth cancer (n = 93, 65.5%). In contrast, the proportion of patients with a history of alcohol consumption was relatively low (n = 321, 36.3%). According to the seventh edition AJCC staging guidelines, 497 patients (56.2%) were diagnosed with Stages III–IV at initial diagnosis. Among these, the proportions of Stages III–IV in gingival cancer (n = 185, 65.8%) and floor of mouth cancer (n = 95, 66.9%) were significantly higher than those in other oral subsites. Consistent with their moderate to advanced stage distribution characteristics, these two subsites also had higher proportions of T3 + T4 stage tumors (gingival cancer: n = 148, 52.6%; floor of mouth cancer: n = 65, 45.7%) and lymph node metastasis rates (gingival cancer: n = 114, 40.6%; floor of mouth cancer: n = 74, 52.1%). Clinical observations showed that cervical lymph node metastases in patients with OSCC were mainly concentrated in Level I (n = 168, 47.3%) and Level II (n = 187, 52.7%). Among common oral cancer sites, floor of mouth cancer had the highest metastasis rate to Level I (n = 39, 52.7%), while gingival cancer exhibited relatively high metastasis rates to both Level I (n = 50, 43.9%) and Level II (n = 55, 48.2%). Notably, gingival cancer also had low‐probability metastases to Level IV (n = 6, 4.2%) and Level V (n = 5, 3.5%).
TABLE 1.
Clinicopathological characteristics of patients with OSCC included in the study at our center from 2000 to 2020.
| Overal n = 885 | Tumor subsite | p | ||||||
|---|---|---|---|---|---|---|---|---|
| Oral tongue n = 371, 41.9% | Gingiva n = 281, 31.8% | Floor of mouth n = 142, 16.0% | Buccal mucosa n = 53, 6.0% | Retromolar trigone n = 20, 2.3% | Hard palate n = 18, 2.0% | |||
| Age, n (%) | 0.001 | |||||||
| ≤ 50 | 190 (21.5) | 101 (27.2) | 50 (17.8) | 28 (19.7) | 3 (5.6) | 6 (30.0) | 2 (11.1) | |
| > 50 | 695 (78.5) | 270 (72.8) | 231 (82.2) | 114 (80.3) | 50 (94.3) | 14 (70.0) | 16 (88.8) | |
| Gender, n (%) | < 0.001 | |||||||
| Male | 570 (64.4) | 233 (62.8) | 164 (58.4) | 129 (90.8) | 20 (37.7) | 13 (65.0) | 11 (61.1) | |
| Female | 315 (35.6) | 138 (37.2) | 117 (41.6) | 13 (9.2) | 33 (62.3) | 7 (35.0) | 7 (38.9) | |
| Tobacco, n (%) | < 0.001 | |||||||
| No | 440 (49.7) | 190 (51.2) | 146 (52.0) | 49 (34.5) | 35 (66.0) | 13 (65.0) | 7 (38.9) | |
| Yes | 445 (50.3) | 181 (48.8) | 135 (48.0) | 93 (65.5) | 18 (34.0) | 7 (35.0) | 11 (61.1) | |
| Alcohol, n (%) | 0.008 | |||||||
| No | 564 (63.7) | 234 (63.1) | 192 (68.3) | 73 (51.4) | 40 (75.5) | 14 (70.0) | 11 (61.1) | |
| Yes | 321 (36.3) | 137 (36.9) | 89 (31.7) | 69 (48.6) | 13 (24.5) | 6 (30.0) | 7 (38.9) | |
| T stage, n (%) | < 0.001 | |||||||
| T0 | 4 (0.5) | 2 (0.5) | — | — | 2 (3.8) | — | — | |
| T1 | 304 (34.4) | 139 (37.5) | 93 (33.1) | 45 (31.7) | 14 (26.4) | 5 (25.0) | 8 (44.4) | |
| T2 | 235 (26.6) | 138 (37.2) | 40 (14.2) | 32 (22.5) | 16 (30.2) | 5 (25.0) | 4 (22.2) | |
| T3 | 134 (15.1) | 56 (15.1) | 33 (11.7) | 32 (22.5) | 11 (20.8) | 2 (10.0) | 0 (0.0) | |
| T4 | 208 (23.5) | 36 (9.7) | 115 (40.9) | 33 (23.2) | 10 (18.9) | 8 (40.0) | 6 (33.3) | |
| N stage, n (%) | 0.060 | |||||||
| N0 | 530 (59.9) | 247 (66.6) | 167 (59.4) | 68 (47.9) | 27 (50.9) | 10 (50.0) | 11 (61.1) | |
| N+ | 355 (40.1) | 124 (33.4) | 114 (40.6) | 74 (52.1) | 26 (49.1) | 10 (50.0) | 7 (38.9) | |
| AJCC stage, n (%) | < 0.001 | |||||||
| Stage I–II | 388 (43.8) | 208 (56.1) | 96 (34.1) | 47 (33.1) | 19 (35.8) | 8 (40.0) | 10 (55.6) | |
| Stage III–IV | 497 (56.2) | 163 (43.9) | 185 (65.8) | 95 (66.9) | 34 (64.2) | 12 (60.0) | 8 (44.4) | |
| Lymph distribution, n (%) | ||||||||
| Level I | 168 (47.3) | 52 (41.9) | 50 (43.9) | 39 (52.7) | 14 (53.8) | 8 (80.0) | 5 (71.4) | 0.001 |
| Level II | 187 (52.7) | 82 (66.1) | 55 (48.2) | 24 (32.4) | 17 (65.4) | 4 (40.0) | 5 (71.4) | 0.265 |
| Level III | 83 (23.4) | 39 (31.5) | 19 (16.7) | 19 (25.7) | 6 (23.1) | — | — | 0.085 |
| Level IV | 18 (5.1) | 10 (8.1) | 6 (4.2) | 2 (2.7) | — | — | — | 0.700 |
| Level V | 8 (2.3) | 3 (2.4) | 5 (3.5) | — | — | — | — | 0.471 |
| Depth of invasion, n (%) | < 0.001 | |||||||
| ≤ 5 mm | 415 (46.9) | 190 (51.2) | 122 (43.4) | 62 (43.7) | 22 (41.5) | 8 (40.0) | 11 (61.1) | |
| > 5 mm, ≤ 10 mm | 216 (24.4) | 108 (29.1) | 52 (18.5) | 33 (23.2) | 14 (26.4) | 7 (35.0) | 2 (11.1) | |
| > 10 mm | 254 (28.7) | 73 (19.7) | 107 (38.1) | 47 (33.1) | 17 (32.1) | 5 (25.0) | 5 (27.8) | |
| Differentiation, n (%) | 0.469 | |||||||
| Well | 322 (36.4) | 148 (39.9) | 96 (34.2) | 40 (28.2) | 24 (45.3) | 7 (35.0) | 7 (38.9) | |
| Moderate | 420 (47.5) | 168 (45.3) | 137 (48.8) | 74 (52.1) | 22 (41.5) | 11 (55.0) | 8 (44.4) | |
| Poor | 143 (16.2) | 55 (14.8) | 48 (17.1) | 28 (19.7) | 7 (13.2) | 2 (10.0) | 3 (16.7) | |
| Lymph node dissection, n (%) | 0.075 | |||||||
| No | 191 (21.6) | 93 (25.1) | 58 (20.6) | 28 (19.7) | 10 (18.9) | — | 2 (11.1) | |
| Yes | 694 (78.4) | 278 (74.9) | 223 (79.4) | 114 (80.3) | 43 (81.1) | 20 (100.0) | 16 (88.9) | |
| Neoadjuvant chemotherapy, n (%) | < 0.001 | |||||||
| No | 517 (58.4) | 266 (71.7) | 121 (43.1) | 80 (56.3) | 29 (54.7) | 11 (55.0) | 10 (55.6) | |
| Yes | 368 (41.6) | 105 (28.3) | 160 (56.9) | 62 (43.7) | 24 (45.3) | 9 (45.0) | 8 (44.4) | |
Note: Bold values emphasize the values with a p‐value < 0.05.
3.2. Kaplan–Meier Survival Curves
The 3‐year OS of OSCC was 68.8%, the 5‐year OS was 53.4%, the 3‐year RFS was 66.0%, and the 5‐year RFS was 63.4% (Table 2).
TABLE 2.
The 3‐year and 5‐year OS and RFS of patients with OSCC in common subsites in our center.
| Overall | Tumor subsite | p | |||
|---|---|---|---|---|---|
| Oral tongue | Gingiva | Floor of mouth | |||
| Overall survival, OS | |||||
| 3 years | 68.8% | 77.6% | 63.0% | 57.0% | < 0.001 |
| 5 years | 53.4% | 62.3% | 49.8% | 37.3% | < 0.001 |
| Recurrence‐free survival, RFS | |||||
| 3 years | 66.0% | 73.0% | 59.1% | 61.3% | < 0.001 |
| 5 years | 63.4% | 71.7% | 55.5% | 57.0% | < 0.001 |
Note: Bold values emphasize the values with a p‐value < 0.05.
Regarding the common subsites, the oral tongue had the best 3‐year and 5‐year OS (3‐year OS 77.6%, 5‐year OS 62.3%), followed by that from the gingiva (3‐year OS 63.0%, 5‐year OS 49.8%), and the worst was from the floor of mouth (3‐year OS 57.0%, 5‐year OS 37.3%). The Log‐rank test showed that there were statistically significant differences in OS among different subsites (3‐year p < 0.001, 5‐year p < 0.001). For RFS, the oral tongue also had the best outcome (3‐year RFS 73.0%, 5‐year RFS 71.7%), conspicuously, unlike OS, gingival cancer had the worst RFS (3‐year RFS 59.1%, 5‐year RFS 55.5%), and the RFS of floor of mouth cancer was in the middle (3‐year RFS 61.3%, 5‐year RFS 57.0%). The Log‐rank test also indicated that there was a statistically significant difference among different subsites (3‐year p < 0.001, 5‐year p < 0.001).
Kaplan–Meier curve indicated that both the long‐term and short‐term OS of gingival cancer and floor of mouth cancer were significantly poorer than that of oral tongue cancer (Figure 1). Specifically, floor of mouth cancer began to exhibit poorer OS around 3 years postoperatively (3‐year OS: floor of mouth cancer 57.0%, gingival cancer 63.0%, oral tongue cancer 77.6%), and its 5‐year OS was significantly lower than those of the aforementioned two subsites (5‐year OS: floor of mouth cancer 37.3%, gingival cancer 49.8%, oral tongue cancer 62.3%). Notably, gingival cancer showed a high early postoperative recurrence rate, while floor of mouth cancer began to have a higher incidence of recurrence events around 2 years postoperatively.
FIGURE 1.
The Kaplan–Meier method was used to compare the prognoses among patients with OSCC in common subsites. The study revealed considerable variations in OS and RFS across different subsites of OSCC, such as the oral tongue, gingiva, and floor of the mouth. In terms of subsite‐specific prognosis, the oral tongue showed the most favorable outcomes, whereas the floor of mouth had the lowest OS, and the gingiva exhibited the poorest RFS. [Color figure can be viewed at wileyonlinelibrary.com]
3.3. Risk Factors Affecting the Prognosis of Gingival Cancer and Floor of Mouth Cancer
To further investigate the risk factors affecting the prognosis of these two subsites, the results of univariate analysis showed that T stage (gingival cancer: p < 0.001, floor of mouth cancer: p = 0.001), N stage (gingival cancer: p = 0.033, floor of mouth cancer: p = 0.001), depth of invasion (gingival cancer: p < 0.001, floor of mouth cancer: p = 0.028), and differentiation (gingival cancer: p < 0.001, floor of mouth cancer: p = 0.001) were significantly associated with patient survival. Notably, gender (p = 0.013), tobacco consumption (p = 0.005), and neoadjuvant chemotherapy (p = 0.032) were significantly associated with the survival of patients with floor of mouth cancer (Table 3). Subsequently, we performed a risk analysis using a multivariate Cox regression model on the independent factors that were significantly associated with patient survival in the univariate analysis. Considering that gender differences in the patient population might cause effect modification and confounding effects in the analysis of risk factors, gender stratification was conducted. The results showed that higher T stages (T3: hazard ratio [HR] = 2.826, 95% CI 1.542–5.180, p = 0.001; T4: HR = 3.002, 95% CI 1.830–4.925, p < 0.001), positive cervical lymph nodes (HR = 1.487, 95% CI 1.028–2.150, p = 0.035), and poorer differentiation grades (moderate differentiation: HR = 3.579, 95% CI 2.189–5.850, p < 0.001; poor differentiation: HR = 3.436, 95% CI 1.923–6.140, p < 0.001) were associated with the significantly increased risk of death in patients with gingival cancer. Notably, neoadjuvant chemotherapy (HR = 0.598, 95% CI 0.396–0.902, p = 0.014) were associated with the significantly reduced risk of death in patients with gingival cancer. In patients with floor of mouth cancer, tobacco consumption (HR = 1.952, 95% CI 1.141–3.337, p = 0.015) was an independent risk factor promoting patient death (Table 4).
TABLE 3.
Univariate analysis of risk factors associated with death from gingival cancer and floor of mouth cancer.
| Gingiva | Floor of mouth | |||||||
|---|---|---|---|---|---|---|---|---|
| Total | Survival | Death | p | Total | Survival | Death | p | |
| Age | 0.222 | 0.811 | ||||||
| ≤ 50 | 50 | 21 | 29 | 28 | 11 | 17 | ||
| > 50 | 231 | 119 | 112 | 114 | 42 | 72 | ||
| Gender | 0.369 | 0.013 | ||||||
| Female | 117 | 62 | 55 | 13 | 9 | 4 | ||
| Male | 164 | 78 | 86 | 129 | 44 | 85 | ||
| Tobacco | 0.135 | 0.005 | ||||||
| No | 146 | 79 | 67 | 49 | 26 | 23 | ||
| Yes | 135 | 61 | 74 | 93 | 27 | 66 | ||
| Alcohol | 0.171 | 0.794 | ||||||
| No | 192 | 101 | 91 | 73 | 28 | 45 | ||
| Yes | 89 | 39 | 50 | 69 | 25 | 44 | ||
| T stage | < 0.001 | 0.001 | ||||||
| T1 | 93 | 65 | 28 | 45 | 26 | 19 | ||
| T2 | 40 | 21 | 19 | 32 | 13 | 19 | ||
| T3 | 33 | 12 | 21 | 32 | 8 | 24 | ||
| T4 | 115 | 42 | 73 | 33 | 6 | 27 | ||
| N stage | 0.033 | 0.001 | ||||||
| N0 | 167 | 92 | 75 | 68 | 35 | 33 | ||
| N+ | 114 | 48 | 66 | 74 | 18 | 56 | ||
| Depth of invasion | < 0.001 | 0.028 | ||||||
| ≤ 5 mm | 122 | 79 | 43 | 62 | 30 | 32 | ||
| > 5 mm, ≤ 10 mm | 52 | 26 | 26 | 33 | 12 | 21 | ||
| > 10 mm | 107 | 35 | 72 | 47 | 11 | 36 | ||
| Differentiation | < 0.001 | 0.001 | ||||||
| Well | 96 | 75 | 21 | 40 | 22 | 18 | ||
| Moderate | 137 | 45 | 92 | 74 | 28 | 46 | ||
| Poor | 48 | 20 | 28 | 28 | 3 | 25 | ||
| Lymph node dissection | 0.393 | 0.499 | ||||||
| No | 58 | 26 | 32 | 28 | 12 | 16 | ||
| Yes | 223 | 114 | 109 | 114 | 41 | 73 | ||
| Neoadjuvant chemotherapy | 0.371 | 0.032 | ||||||
| No | 121 | 64 | 57 | 80 | 36 | 44 | ||
| Yes | 160 | 76 | 84 | 62 | 17 | 45 | ||
Note: Bold values emphasize the values with a p‐value < 0.05.
TABLE 4.
Multivariate Cox regression analysis of independent risk factors associated with 5‐year OS from gingival cancer and floor of mouth cancer.
| Gingiva | Floor of mouth | |||
|---|---|---|---|---|
| HR (95% CI) | p | HR (95% CI) | p | |
| Tobacco | ||||
| No | 1 | 1 | ||
| Yes | 0.737 (0.450–1.209) | 0.227 | 1.952 (1.141–3.337) | 0.015 |
| Alcohol | ||||
| No | 1 | 1 | ||
| Yes | 1.528 (0.927–2.517) | 0.096 | 0.974 (0.604–1.570) | 0.914 |
| T stage | ||||
| T1 | 1 | 1 | ||
| T2 | 1.442 (0.798–2.604) | 0.225 | 1.174 (0.595–2.316) | 0.644 |
| T3 | 2.826 (1.542–5.180) | 0.001 | 1.436 (0.731–2.819) | 0.293 |
| T4 | 3.002 (1.830–4.925) | < 0.001 | 2.543 (1.321–4.897) | 0.005 |
| N stage | ||||
| N0 | 1 | 1 | ||
| N+ | 1.487 (1.028–2.150) | 0.035 | 1.576 (0.976–2.544) | 0.063 |
| Differentiation | ||||
| Well | 1 | 1 | ||
| Moderate | 3.579 (2.189–5.850) | < 0.001 | 1.412 (0.773–2.578) | 0.262 |
| Poor | 3.436 (1.923–6.140) | < 0.001 | 1.987 (0.979–4.032) | 0.057 |
| Neoadjuvant chemotherapy | ||||
| No | 1 | 1 | ||
| Yes | 0.598 (0.396–0.902) | 0.014 | 1.038 (0.644–1.672) | 0.879 |
Note: Bold values emphasize the values with a p‐value < 0.05.
4. Discussion
The anatomical specificity of oral subsites and geographic variation in carcinogenic factors shape the diversity of the global disease landscape of OSCC. At our center, OSCC predominantly originates from the oral tongue (41.9%) and gingiva (31.8%), followed by the floor of mouth (16.0%) and buccal mucosa (6.0%). The retromolar trigone (2.3%) and hard palate (2.0%) are the least common sites of occurrence. Notably, the incidence of gingival cancer surpasses that of floor of mouth and buccal mucosa cancers, diverging significantly from subsite distributions in Europe, America, and South Asia [9, 10, 11, 12]. Research shows that in high‐HDI regions such as Europe and America, the floor of mouth is a prevalent site for OSCC. These regions also have elevated rates of tobacco and alcohol use, the primary risk factors for OSCC [11, 13, 14, 15]. In South Asia, OSCC predominantly affects the buccal mucosa, with high betel nut consumption cited as a key factor contributing to the region's highest global incidence of oral cancer [12, 16]. This is also consistent with the high incidence rates of buccal cancer in areca nut‐endemic areas in China [17, 18]. In this study, the reason for the high incidence of gingival cancer at our center was not observed, but it should not be easily ignored because another study in an area adjacent to our center also pointed out the high incidence of gingival cancer [19]. This may hint at potential region‐specific etiological factors within certain ecological and sociodemographic contexts.
This study also found that the proportion of patients with gingival cancer and floor of mouth cancer who were diagnosed at advanced stages during initial diagnosis was significantly higher than that of patients with oral tongue cancer; additionally, their prognostic performance was significantly poorer. This suggests that gingival cancer and floor of mouth cancer may have poorer biological behavior or be underscreened for tumors at these two sites, which has sparked our research interest in these subsites. Notably, gingival cancer has been reported to have a lower incidence in previous studies, leading to lower attention and limited understanding of tumors at this site. This makes it urgent for us to analyze the high‐risk factors affecting its prognosis. Univariate analysis revealed that T stage, N stage, DOI, and differentiation grade were all significantly associated with mortality in patients with gingival cancer, and this result aligns with the conclusions of previous studies [20]. Furthermore, in the multivariate analysis, we also observed that preoperative neoadjuvant chemotherapy for gingival cancer significantly reduced death risk. This underscores the importance of early screening, early diagnosis, and early systematic treatment for patients with gingival cancer. Although there is insufficient basis for determining that gingival cancer is highly malignant solely based on its disease stage at initial diagnosis, as its deeper anatomical location makes early screening difficult; compared with lip lesions, the probability of precancerous lesions in the gingiva progressing to malignant tumors is 6–10 times higher [18], and early symptoms are subtle, making it easy to be confused with benign diseases [21]. However, studies have clearly shown that there is no significant difference in the delayed diagnosis time between gingival cancer and cancers in other subsites of the oral cavity. Nevertheless, the frequency of invading adjacent bony tissue is significantly higher than that of cancers in other sites, which is associated with the thinness of the gingival mucosal tissue and its proximity to bony tissue [22]. Therefore, it is certain that enhancing attention to and screening for gingival cancers, as well as detecting cancer foci at an early stage, are crucial for improving the prognosis of patients with gingival cancer. This is particularly significant for patients with lesions that may progress to oral cancer, such as oral lichen planus, oral leukoplakia, and Fanconi's anemia [23].
Tobacco consumption has long been recognized as a high‐risk factor for oral cancer, but this association may be significantly correlated only with certain oral subsites [24]. A population‐based study in the United States over a 10‐year period showed that as smoking rates in the country declined, the incidence rates of only some oral cancer subsites decreased—including floor of mouth cancer and hard palate cancer [25]. The mechanisms by which tobacco induces oral cancer can be roughly categorized into two types: one involves physical damage (e.g., friction, thermal stimulation) from practices such as tobacco chewing, which triggers repeated inflammatory repair [26]; the other involves chemical‐induced base mutations caused by substances like reactive oxygen species (ROS) generated during tobacco use [27]. Additionally, studies have reported that oral dysbiosis (imbalance of oral microbiota) resulting from tobacco use is also one of the contributing factors to oral cancer [28]. Eloranta et al. [24] explicitly proposed that the carcinogenic effect of tobacco varies by oral subsite. Specifically, the floor of mouth, located at the lowest part of the oral cavity, is prone to the accumulation of carcinogens from tobacco. Moreover, it is covered by a thin layer of non‐keratinized epithelium, making it more sensitive to chemical and physical stimuli. Consequently, the association between carcinogenic effect of tobacco and floor of mouth cancer is the most pronounced. Consistent with these findings, our study also revealed that among patients with floor of mouth cancer, the proportion of those with a history of tobacco consumption was significantly higher than that in patients with OSCC at other subsites. Furthermore, we identified tobacco consumption as an independent risk factor affecting the prognosis of floor of mouth cancer. Therefore, for floor of mouth cancer, in addition to strengthening early screening, it is also essential to enhance smoking cessation education for high‐risk groups.
Beyond these anatomical and carcinogenic influences, genetic‐level differences may also underlie the high malignancy of gingival cancer and floor of mouth cancer. Eichberger et al. [29] observed that the expression of matrix metalloproteinase 27 (MMP‐27) was significantly lower in tumor tissues with mandibular bone invasion, compared with that in gingival and floor of mouth cancer tissues that grow along the mandible without invasion. This finding clarifies the key role of gene expression in tumor invasion; notably, it should be further compared with findings in oral tongue cancer tissues to highlight the unique role of MMP‐27 in driving the highly malignant progression of gingival and floor of mouth cancers. As a homologue of the tumor suppressor gene p53, p63 exerts a critical role in the pathogenesis of head and neck squamous cell carcinoma (HNSCC). A study investigating the baseline expression of p63 in normal tongue and gingival tissues revealed that the average p63 expression in normal tongue tissue was 2.5 times higher than that in normal gingival tissue. When normal tissues were compared with tumor tissues, p63 expression was significantly reduced in tongue cancer tissues, whereas no significant alterations were noted in gingival and floor of mouth cancer tissues. These changes in tumor suppressor genes may help account for the characteristic rapid progression of gingival and floor of mouth cancers [30].
Neoadjuvant chemotherapy has emerged as a pivotal downstaging strategy for locally advanced OSCC and demonstrated favorable therapeutic efficacy. In previous studies, 18%–43.2% of patients with unresectable advanced oral cancer have responded to the docetaxel–cisplatin two‐drug regimen or the three‐drug regimen combined with fluorouracil [31, 32, 33, 34], which provides an opportunity for surgical resection and improved long‐term prognosis in this subset of patients [35]. However, tumors at different subsites exhibit heterogeneous responses to this treatment [32]. Such variability is attributed to inherent differences in tissue architecture, epigenetic profiles, and other biological characteristics. Studies have shown that oral tumors deficient in functional p53 rarely attain a complete response to cisplatin/fluorouracil‐based chemotherapy, whereas 40% of patients whose tumors express functional p53 achieve complete response [36, 37]. Notably, the functional status of p53 has been proven to differ significantly across distinct oral cancer subsites [38]. Our study indicates that neoadjuvant chemotherapy is associated with improved prognosis in gingival cancer, but no such correlation has been found in floor of mouth cancer. This suggests the specificity of gingival cancer in the response to neoadjuvant chemotherapy. However, there is still limited research on the causes of this specificity. In the future, more cases should be included to comprehensively compare the neoadjuvant treatment response characteristics among different subsites. Additionally, multi‐omics data analysis should be performed to explore whether there are subsite‐specific factors that affect the bioavailable concentration of drugs in target tissues or drug resistance regulatory pathways.
The innovation of this study lies in being the first to compare the clinical characteristics of OSCC across different subsites in the region where our center is located. Additionally, it conducts long‐term follow‐up in a large cohort to evaluate the prognosis of different subsites, and performs risk factor analysis for mortality in subsites with high incidence and mortality rates, providing guidance for the refined management of oral cancer patients in this region. Meanwhile, this study also has certain limitations and requires further improvement. First, it is a single‐center study and lacks validation with multi‐center data. In subsequent research, multi‐center data should be included, particularly from centers in northern China with similar living environments and habits, to further explore the pathogenic characteristics of each subsite, especially the reasons for the high incidence of gingival cancer. Second, this study used the seventh edition TNM staging system and lacked data on prognostic factors such as neurovascular invasion and extranodal extension of lymph nodes when analyzing disease characteristics. While it identified and discussed differences in disease characteristics among subsites when comparing their survival characteristics, it lacked complete information on these confounding factors, primarily due to limitations in the details provided by pathologists in their descriptions of intraoperative pathological findings. In the future, detailed analysis of intraoperative pathological findings should be conducted, and prognostic differences across subsites should be re‐evaluated after strictly controlling for confounding factors. As a retrospective study, we were unable to obtain detailed data on patients' social determinants of health, such as socioeconomic status, distance to medical facilities, and health literacy. These factors may contribute to the differences in diagnostic staging among oral subsites. Future studies should incorporate these key variables to more accurately clarify the independent relationship between primary tumor subsites and their staging.
In conclusion, there are differences in disease characteristics among OSCC at different subsites. Furthermore, gingival cancer and floor of mouth cancer account for a relatively high proportion among OSCC; compared with oral tongue cancer, both exhibits more severe tumor invasion and lymph node metastasis at initial diagnosis. In terms of prognosis, both have significantly poorer outcomes than oral tongue cancer: gingival cancer shows a higher early postoperative recurrence rate, while floor of mouth cancer presents poorer OS, particularly during long‐term follow‐up. Regarding the underlying reasons, we identified that neoadjuvant chemotherapy is an independent protective factor for reducing mortality in patients with gingival cancer. Therefore, in the clinical management of patients with gingival cancer, priority should be given to enhancing patient adherence to neoadjuvant therapy and ensuring the delivery of complete, standardized treatment regimens. Additionally, during the early postoperative period of gingival cancer, especially within 2 years after surgery, close imaging monitoring should be conducted to promptly intervene in cases of recurrent gingival cancer. For patients with floor of mouth cancer, smoking cessation education is of great importance. Early reduction in tobacco consumption may significantly improve their prognosis.
Author Contributions
Y.S.D., C.J., and X.D.W. conceived and designed the study. H.L., Y.S.W., A.L.Y., J.Z., and R.Y.S. did case collection and follow‐up. H.L., Y.S.D., Y.F., X.H.L., W.F.S., and S.S.C. contributed to data analysis. The manuscript was written by H.L. and Y.D. and revised by Y.S.W. and Y.S.D. Y.S.D, X.D.W. supervised the research. All authors read and approved the final manuscript.
Funding
Peak Discipline Support Program of the 14th Five‐Year Plan of Tianjin Medical University Cancer Institute & Hospital (7‐2‐8).
Ethics Statement
This study was approved by the Ethics Committee of Tianjin Medical University Cancer Institute & Hospital (approval number: bc20255237).
Conflicts of Interest
The authors declare no conflicts of interest.
Acknowledgments
The authors would like to thank all the experts and colleagues who have provided assistance with this research.
Contributor Information
Xudong Wang, Email: wxd.1133@163.com.
Yuansheng Duan, Email: duanyuansheng89@163.com.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.