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ORIGINAL RESEARCH article

Front. Mol. Biosci., 01 August 2025

Sec. Molecular Diagnostics and Therapeutics

Volume 12 - 2025 | https://doi.org/10.3389/fmolb.2025.1617787

Prognostic value of positive lymph node ratio, tumor deposit, and perineural invasion in advanced colorectal signet-ring cell carcinoma

  • 1. Department of Surgery, The Affiliated Yixing Hospital of Jiangsu University, Yixing, Jiangsu, China

  • 2. Clinical Laboratory, Hainan Medical University, Haikou, Hainan, China

  • 3. Department of Gastroenterology, Jinhua Central Hospital Affiliated to Zhejiang University School of Medicine, Jinhua, China

  • 4. Department of Gastroenterology, The Affiliated Yixing Hospital of Jiangsu University, Yixing, Jiangsu, China

  • 5. Inpatient Management Center, Nanjing Drum Tower Hospital Affiliated to Nanjing University Medical School, Nanjing, China

  • 6. Department of Oncology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi People’s Hospital, Wuxi Medical Center, Nanjing Medical University, Wuxi, China

  • 7. Department of Gastroenterology, XuZhou Central Hospital Affiliated to Medical School of Southeast University, XuZhou, China

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Abstract

Background:

The aim of this study was to assess the prognostic significance of positive lymph node ratio (LNR), tumor deposits (TD), and perineural invasion (PNI) in advanced colorectal signet-ring cell carcinoma (SRCC).

Methods:

A multicenter retrospective cohort analysis was conducted involving 677 patients with advanced colorectal SRCC. The associations of variables with CSS and OS were analyzed using the Kaplan-Meier method and multivariable Cox proportional hazards models. A nomogram model was developed to predict outcomes.

Results:

High-LNR, TD-positive, and PNI-positive were associated with poorer CSS and OS in both the training and validation cohorts. Multivariate Cox analysis identified T stage, M stage, TD, CEA, chemotherapy, and LNR as independent prognostic factors. A prognostic nomogram model incorporating these variables demonstrated excellent calibration and satisfactory predictive accuracy. Survival curves generated from individualized nomogram scores effectively discriminated prognostic outcomes (P < 0.001). The combined variable of LNR, TD, and PNI significantly enhanced the predictive performance. Specifically, the combined variable exhibited the highest relative contribution to OS at 23.4%, surpassing that of T and M stages. For CSS, its relative contribution was 21.4%, ranking second only to T and M stages.

Conclusion:

LNR, TD, and PNI served as prognostic factors for advanced colorectal SRCC. The combined analysis demonstrated a higher prognostic predictive value.

Introduction

Signet ring cell carcinoma (SRCC) was a distinct subtype of adenocarcinoma, showing remarkable differences from adenocarcinoma in pathological features, clinical behavior and prognosis (Allart et al., 2022). It was characterized by abundant intracytoplasmic mucin that pushes the nucleus to one side, giving the cells a signet-ring-like appearance (Anthony et al., 1996). The diagnostic criterion for SRCC was the presence of more than 50% signet ring cells in the tumor tissue (Nagtegaal et al., 2020). Compared to colorectal conventional adenocarcinoma, colorectal SRCC tended to occur in younger individuals, was often diagnosed at an advanced stage, and had a lower survival rate (Weng et al., 2022; Korphaisarn et al., 2019). Notably, in a study involving 173,460 CRC patients, 1,932 (1.11%) were diagnosed with colorectal SRCC, and 76.04% of these cases were at stage III - IV (Shi et al., 2019). Studies have shown that SRCC was characterized by a high frequency of mutations in epithelial-mesenchymal transition (EMT)- and stemness-related genes (such as RNF43, CDH1, and SMAD4), accompanied by excessive activation of the transforming growth factor-β (TGF-β) pathway (An et al., 2021). Meanwhile, upregulation of the autophagic pathway and enrichment of immune-related proteins further promoted tumor progression (Chaudhary et al., 2025). These altered molecular features, combined with tumor stemness regulation and changes in the immune microenvironment (Ye et al., 2024a; Ye et al., 2024b; Ye et al., 2024c; Ye et al., 2025), collectively lead to poor response to conventional therapeutic regimens (Pande et al., 2008).

In current clinical practice, prognosis of CRC was primarily assessed using the TNM staging system (Weiser, 2018). However, this system did not account for the number of lymph nodes retrieved during surgery, potentially resulting in an underestimation of the actual number of metastatic lymph nodes and subsequent downstaging (Berger et al., 2005). The lymph node ratio (LNR) was defined as the ratio of positive lymph nodes to the total number of lymph nodes retrieved and may exhibit superior performance in predicting prognosis (Gartagani et al., 2022). Tumor deposits (TD) served as a supplement to TNM staging in CRC. When tumor deposits were present but there was no lymph node metastasis, they were considered as N1c stage (Brierley et al., 2017). Perineural invasion (PNI) refers to cancer cells invading nerves, around nerves, or directly through them, involving at least 33% of the nerve’s circumference or any layer of the nerve sheath structure (Zhang B. et al., 2023).

Research on advanced colorectal SRCC remains limited. Previous studies predominantly relied on case reports or small sample analyses. By leveraging multicenter data, this study systematically evaluated the prognostic value of LNR, TD, and PNI in advanced colorectal SRCC. Furthermore, a combined analysis was performed to develop a clinically applicable prognostic model.

Patients and methods

Patients

The study included colorectal SRCC patients from the SEER database between 2011 and 2018 as the training cohort. Concurrently, colorectal SRCC patients from four tertiary hospitals (the Second Affiliated Hospital of Nanjing Medical University, Yixing People’s Hospital, Drum Tower Hospital Affiliated to Nanjing University School of Medicine, and Xuzhou Central Hospital) in China were included as the external validation cohort. The inclusion criteria were as follows: (1) Patients with stage III or stage IV; (2) Individuals who underwent surgical treatment. Exclusion criteria included: (1) Non-primary tumors or surgeries performed at non-primary sites; (2) Concurrent presence of other tumors; (3) Perioperative death (≤1 month post-surgery); (4) Incomplete clinical or pathological data.

Study variables

Baseline data including demographic characteristics, tumor size, tumor site, grade, TNM staging, TD, LNR, PNI, carcinoembryonic antigen (CEA) levels, and chemotherapy status were collected. Survival outcomes for patients in the SEER dataset were obtained through systematic queries, while survival outcomes in Chinese hospitals were obtained through telephone follow-ups and death registry queries.

The primary outcome of the study was cancer-specific survival (CSS), defined as the time from diagnosis to death due to colorectal SRCC. The secondary outcome was overall survival (OS), defined as the time from diagnosis to death from any cause. This study adhered to the Helsinki Declaration. Ethical approval was obtained from the institutional review boards of the four tertiary Chinese hospitals with approval numbers: IRB Approval No. 2020-092, IRB Approval No. 2022-158, IRB Approval No. 2022-469-02, and IRB Approval No. XZXY-LK-20240116-007.

Statistical methods

Categorical variables were presented as counts (%) and compared using Pearson’s chi-square test or Fisher’s exact test. LNR was categorized into tertiles using X-tile software, which was identified by scoring the maximum X-squared value in the Kaplan-Meier test based on survival time and outcomes (Tang et al., 2018). Survival curves were constructed using the Kaplan-Meier method, and both univariate and multivariate prognostic analyses were carried out by Cox proportional hazards model. Variables that exhibited statistical significance in the training cohort were subsequently incorporated into the nomogram model. Internal validation was carried out through bootstrapping, and external validation was performed in four Chinese cohort. Model accuracy was assessed using receiver operating characteristic curves (ROC), while calibration curves were employed to evaluate the consistency between the predicted probabilities and the observed probabilities. Relative variable contributions to prognosis were calculated in R. All statistical tests were two-sided, with p < 0.05 considered significant. Statistical analyses were performed using SPSS 22.0, GraphPad Prism 9.4.1, and R 4.3.1 software.

Results

Clinical and pathological characteristics of patients

A total of 677 patients were included in the study, with 556 in the training cohort and 121 in the validation cohort, as illustrated in the flowchart (Figure 1). X-tile software categorized LNR into three groups: low-LNR (LNR <0.3), moderate-LNR (0.3 ≤ LNR ≤0.7), and high-LNR (LNR >0.7) (Supplementary Figure S1). In the training cohort, high-LNR, TD-positive, and PNI-positive patients were associated with T4 stage and >4 metastatic lymph nodes (Table 1). In the validation cohort, high-LNR and PNI-positive patients frequently had more than four metastatic lymph nodes, while TD-positive patients tended to exhibit PNI and distant metastasis (Table 2).

FIGURE 1

Flowchart illustrating the patient selection process for colorectal SRCC studies. From 2,998 SEER database patients, stepwise exclusions for non-primary tumors (647), non-primary surgical sites (608), incomplete pathology data (1,027), unknown survival timing or perioperative mortality (19), and stage 0, 1, 2 cases (141) result in a training set of 556 patients. From 135 patients in Chinese hospitals, exclusions include concurrent tumors (6) and incomplete data (8), resulting in a validation set of 121 patients.

Flowchart of the study.

TABLE 1

Low-LNR (N = 210) Moderate-LNR (N = 193) High-LNR (N = 153) p value TD-negative (N = 274) TD-positive (N = 282) p value PNI-negative (N = 330) PNI-positive (N = 226) p value
Gender 0.08 0.13 0.66
Female 102 (48.57) 92 (47.67) 90 (58.82) 131 (47.8) 153 (54.3) 166 (50.3) 118 (52.2)
Male 108 (51.43) 101 (52.33) 63 (41.18) 143 (52.2) 12,945.7 () 164 (49.7) 108 (47.8)
Age 0.17 <0.01 <0.01 0.02 0.09
Media (Q1-Q3) 67.50 (54.00–78.25) 63.00 (52.00–75.00) 64.00 (53.00–74.00) 68 (55.0–80.0) 63 (51.0–73.25) 67 (55.0–77.0) 62 (50.0–74.0)
Tumor size 0.02 0.02 0.42
≤5 cm 100 (47.62) 90 (46.63) 52 (33.99) 133 (48.5) 109 (38.7) 139 (42.1) 103 (45.6)
>5 cm 110 (52.38) 103 (53.37) 101 (66.01) 141 (51.5) 173 (61.3) 191 (57.9) 123 (54.4)
Tumor site <0.01 0.02 0.23
Right 152 (72.38) 126 (65.29) 79 (51.63) 192 (70.1) 165 (58.5) 220 (66.7) 137 (60.6)
Left 43 (20.48) 52 (26.94) 58 (37.91) 63 (23.0) 90 (31.9) 82 (24.8) 71 (31.4)
Rectum 15 (7.14) 15 (7.77) 16 (10.46) 19 (6.9) 27 (9.6) 28 (8.5) 18 (8.0)
Grade 0.01 0.04 0.08
Moderate 18 (8.57) 7 (3.63) 3 (1.96) 19 (6.9) 9 (3.2) 21 (6.4) 7 (3.1)
Poor 192 (91.43) 186 (96.37) 150 (98.04) 255 (93.1) 273 (96.8) 309 (93.6) 219 (96.9)
T stage <0.01 <0.01 <0.01
T1-3 115 (54.76) 89 (46.11) 47 (30.72) 161 (58.8) 90 (31.9) 179 (54.2) 72 (31.9)
T4 95 (45.24) 104 (53.89) 106 (69.28) 113 (41.2) 192 (68.1) 151 (45.8) 154 (68.1)
N stage <0.01 <0.01 <0.01
<4 nodes 132 (62.86) 9 (4.66) 3 (1.96) 98 (35.8) 46 (16.3) 105 (31.8) 39 (17.3)
≥4 nodes 78 (37.14) 184 (95.34) 150 (98.04) 176 (64.2) 236 (83.7) 225 (68.2) 187 (82.7)
M stage <0.01 <0.01 <0.01
M0 169 (80.48) 123 (63.73) 76 (49.67) 217 (79.2) 151 (53.5) 240 (72.7) 128 (56.6)
M1 41 (19.52) 70 (36.27) 77 (50.33) 57 (20.8) 131 (46.5) 90 (27.3) 98 (43.4)
TD <0.01 <0.01
Absent 139 (66.19) 90 (46.63) 45 (29.41) NA NA 198 (60.0) 76 (33.6)
Present 71 (33.81) 103 (53.37) 108 (70.59) NA NA 132 (40.0) 150 (66.4)
PNI <0.01 <0.01
Absent 149 (70.95) 106 (54.92) 75 (49.02) 198 (72.3) 132 (46.8) NA NA
Present 61 (29.05) 87 (45.08) 78 (50.98) 76 (27.7) 150 (53.2) NA NA
CEA 0.02 0.10 0.85
Negative 99 (47.14) 87 (45.08) 50 (32.68) 126 (46.0) 110 (39.0) 139 (42.1) 97 (42.9)
Positive 111 (52.86) 106 (54.92) 103 (67.32) 148 (54.0) 172 (61.0) 191 (57.9) 129 (57.1)
Neoadjuvant therapy 0.95 0.14 0.13
No 197 (93.81) 180 (93.26) 144 (94.11) 261 (95.3) 260 (92.2) 305 (92.4) 216 (95.6)
Yes 13 (6.19) 13 (6.74) 9 (5.88) 13 (4.7) 22 (7.8) 25 (7.6) 10 (4.4)
Chemotherapy 0.66 0.11 0.98
No 69 (32.86) 56 (29.02) 50 (32.68) 95 (34.7) 80 (28.4) 104 (31.5) 71 (31.4)
Yes 141 (67.14) 137 (70.98) 103 (67.32) 179 (65.3) 202 (71.6) 226 (68.5) 155 (68.6)
LNR <0.01 <0.01
Low NA NA NA 139 (50.7) 71 (25.2) 149 (45.2) 61 (27.0)
Moderate NA NA NA 90 (32.8) 103 (36.5) 106 (32.1) 87 (38.5)
High NA NA NA 45 (16.4) 108 (38.3) 75 (22.7) 78 (34.5)

Patient characteristics by LNR, TD and PNI in the training cohort.

TD, tumor deposit; PNI, perineural invasion; CEA, carcinoembryonic antigen; LNR, positive lymph node ratio.

TABLE 2

Low-LNR (N = 36) Moderate-LNR (N = 48) High-LNR (N = 37) p value TD-negative (N = 72) TD-positive (N = 49) p value PNI-negative (N = 65) PNI-positive (N = 56) p value
Gender 0.83 0.48 0.37
Female 24 (66.67) 29 (60.42) 24 (64.86) 44 (61.1) 33 (67.3) 39 (60.0) 38 (67.9)
Male 12 (33.33) 19 (39.58) 13 (35.14) 28 (38.9) 16 (32.7) 26 (40.0) 18 (32.1)
Age 0.94 0.71 0.76
Media (Q1-Q3) 58.50 (41.00–68.00) 59.00 (47.25–66.00) 57.00 (44.50–69.00) 57.5 (44.25–67.75) 60.0 (44.0–68.0) 59 (48.5–67.5) 59 (42.5–68.0)
Tumor size 0.83 0.97 0.02
≤5 cm 17 (47.22 25 (52.01) 20 (54.05) 37 (51.4) 25 (51.0) 27 (41.5) 35 (62.5)
>5 cm 19 (52.78) 23 (47.92) 17 (45.95) 35 (48.6) 24 (49.0) 38 (58.5) 21 (37.5)
Tumor site 0.23 0.13 0.40
Right 6 (16.67) 16 (33.33) 11 (29.73) 20 (27.8) 13 (26.5) 21 (32.3) 12 (21.4)
Left 9 (25.0) 11 (22.92) 13 (35.14) 15 (20.8) 18 (36.7) 16 (24.6) 17 (30.4)
Rectum 21 (58.33) 21 (43.75) 13 (35.14) 37 (51.4) 18 (36.7) 28 (43.1) 27 (48.2)
Grade 0.82 0.15 0.12
Moderate 1 (2.78) 1 (2.08) 2 (5.41) 4 (5.6) 0 (0.0) 4 (6.2) 0 (0.0)
Poor 35 (97.22) 47 (97.92) 35 (94.59) 68 (94.4) 49 (100.0) 61 (93.8) 56 (100.0)
T stage 0.86 0.15 0.14
T1-3 17 (47.22) 20 (41.67) 17 (45.95) 36 (50.0) 18 (36.7) 33 (50.8) 21 (37.5)
T4 19 (52.78) 28 (58.33) 20 (54.05) 36 (50.0) 31 (63.3) 32 (49.2) 35 (62.5)
N stage <0.01 0.77 0.03
<4 nodes 19 (52.78) 6 (12.50) 3 (8.11) 16 (22.2) 12 (24.5) 20 (30.8) 8 (14.3)
≥4 nodes 17 (47.22) 42 (87.50) 34 (91.89) 56 (77.8) 37 (75.5) 45 (69.2) 48 (85.7)
M stage 0.64 0.02 0.40
M0 27 (75.00) 33 (68.75) 24 (64.86) 56 (77.8) 28 (57.1) 43 (66.2) 41 (73.2)
M1 9 (25.00) 15 (31.25) 13 (35.14) 16 (22.2) 21 (42.9) 22 (33.8) 15 (26.8)
TD 0.28 0.02
Absent 25 (69.44) 28 (58.33) 19 (51.35) NA NA 45 (69.2) 27 (48.2)
Present 11 (30.56) 20 (41.67) 18 (48.65) NA NA 20 (30.8) 29 (51.8)
PNI 0.34 0.02
Absent 23 (63.89) 24 (50.0) 18 (48.65) 45 (62.5) 20 (40.8) NA NA
Present 13 (36.11) 24 (50.0) 19 (51.35) 27 (37.5) 29 (59.2) NA NA
CEA 0.79 0.48 0.33
Negative 16 (44.44) 25 (52.08) 18 (48.65) 37 (51.4) 22 (44.9) 29 (44.6) 30 (53.6)
Positive 20 (55.56) 23 (47.92) 19 (51.35) 35 (48.6) 27 (55.1) 36 (55.4) 26 (46.4)
Neoadjuvant therapy 0.18 0.399 0.22 0.685 0.51
No 35 (97.22) 47 (97.92) 33 (89.19) 67 (93.1) 48 (98.0) 61 (93.8) 54 (96.4)
Yes 1 (2.78) 1 (2.08) 4 (10.81) 5 (6.9) 1 (2.0) 4 (6.2) 2 (3.6)
Chemotherapy 0.47 0.63 0.23
No 13 (36.11) 17 (35.42) 9 (24.32) 22 (30.6) 17 (34.7) 24 (36.9) 15 (26.8)
Yes 23 (63.89) 31 (64.58) 28 (75.68) 50 (69.4) 32 (65.3) 41 (63.1) 41 (73.2)
LNR 0.28 0.34
Low NA NA NA 25 (34.7) 11 (22.4) 23 (35.4) 13 (23.2)
Moderate NA NA NA 28 (38.9) 20 (40.8) 24 (36.9) 24 (42.9)
High NA NA NA 19 (26.4) 18 (36.7) 18 (27.7) 19 (33.9)

Patient characteristics by LNR, TD and PNI in validation cohort.

TD, tumor deposit; PNI, perineural invasion; CEA, carcinoembryonic antigen; LNR, positive lymph node ratio.

Survival curves associated with the prognosis of LNR, TD, and PNI

Kaplan-Meier survival curves demonstrated that high-LNR, TD-positive, and PNI-positive were each associated with poorer CSS and OS in advanced colorectal SRCC in both cohorts (Figure 2; Supplementary Figure S2). This disparity was more pronounced in stage III tumors (Supplementary Figure S3). In stage IV tumors, only LNR remained significantly associated with survival, while TD and PNI showed no significance (Supplementary Figure S4). Similar trends were observed for OS. Interestingly, we conducted a combined analysis of TD, LNR, and PNI to construct a new combined variable, and patients were further classified into the triple-positive group (high LNR, TD-positive, PNI-positive), triple-negative group (low LNR, TD-negative, PNI-negative), or intermediate group. In the training cohort, 58 patients (10.4%) were triple-positive and 63 patients (11.3%) were triple-negative. The triple-positive group exhibited a higher cancer-related mortality risk compared to the triple-negative group, and this finding was validated in the validation cohort (Supplementary Figure S5).

FIGURE 2

Six graphs showing survival analysis in different contexts. Graphs A and B depict cancer-specific and overall survival based on lymph node ratio (LNR). Graphs C and D show cancer-specific and overall survival based on tumor deposit (TD) status. Graphs E and F illustrate cancer-specific and overall survival based on perineural invasion (PNI) status. Each graph includes survival probability over time in months, with significant differences in survival indicated (log-rank test p<0.0001).

In the training cohort, Kaplan-Meier survival curves for CSS and OS based on LNR (A, B), TD (C, D), and PNI (E, F). OS, Overall Survival; CSS, Cancer-Specific; LNR, positive lymph node ratio; TD, tumor deposit; PNI, perineural invasion.

Univariate and multivariate analyses

Univariate analysis in the training cohort identified that tumor size, T stage, N stage, M stage, TD, PNI, CEA, chemotherapy, and LNR had prognostic value. Multivariate Cox model revealed T stage, M stage, TD, CEA, chemotherapy, and LNR as independent prognostic factors for CSS (Table 3). In the validation cohort, T stage, M stage, PNI, CEA, and LNR independently predicted CSS (Table 3). Similar results were observed for OS (Table 4). Notably, we integrated the combined analysis of TD, LNR, and PNI into a multivariate model that included tumor size, T stage, N stage, M stage, CEA, and chemotherapy. The results showed that the combined variable independently predicted both CSS and OS in the two cohorts (Table 5).

TABLE 3

The training cohort The validation cohort
Univariate Multivariate Univariate Multivariate
HR (95% CI) p value HR (95% CI) p value HR (95% CI) p value HR (95% CI) p value
Gender
Female
Male 0.90 (0.73–1.12) 0.35 0.78 (0.47–1.27) 0.32
Age 1.00 (1.00–1.01) 0.34 1.01 (0.99–1.02) 0.42
Tumor size
≤5 cm
>5 cm 1.47 (1.18–1.83) <0.01 1.13 (0.91–1.42) 0.27 1.06 (0.67–1.69) 0.86
Tumor site 0.36
Right
Left 0.99 (0.78–1.26) 0.96 1.04 (0.56–1.95) 0.90
Rectum 0.74 (0.48–1.16) 0.16 0.96 (0.55–1.70) 0.90
Grade
Moderate
Poor 1.17 (0.72–1.91) 0.52 1.84 (0.45–7.54) 0.39
T stage
T1-3
T4 2.12 (1.69–2.65) <0.01 1.57 (1.25–2.01) <0.01 2.31 (1.40–3.82) <0.01 1.69 (1.01–2.83) 0.05
N stage
<4 nodes
≥4 nodes 2.65 (1.98–3.54) <0.01 1.26 (0.85–1.86) 0.26 1.55 (0.85–2.82) 0.16
M stage
M0
M1 2.55 (2.06–3.17) <0.01 1.65 (1.30–2.09) <0.01 2.35 (1.47–3.76) <0.01 2.32 (1.37–3.93) <0.01
TD
Absent
Present 1.85 (1.49–2.29) <0.01 1.30 (1.02–1.64) 0.03 2.46 (1.55–3.97) <0.01 1.62 (0.96–2.72) 0.07
PNI
Absent
Present 1.57 (1.27–1.94) <0.01 1.09 (0.87–1.36) 0.47 2.15 (1.33–3.46) <0.01 2.06 (1.22–3.47) 0.01
CEA
Negative
Positive 1.73 (1.39–2.16) <0.01 1.47 (1.16–1.85) <0.01 1.89 (1.17–3.04) 0.01 2.25 (1.35–3.75) <0.01
Neoadjuvant therapy
No
Yes 0.87 (0.56–1.34) 0.53 0.95 (0.35–2.60) 0.92
Chemotherapy
No
Yes 0.57 (0.46–0.72) <0.01 0.49 (0.39–0.62) <0.01 1.11 (0.67–1.85) 0.69
LNR <0.01 <0.01 0.01 0.01
Low
Moderate 2.22 (1.71–2.95) <0.01 1.96 (1.37–2.79) <0.01 1.72 (0.91–3.25) 0.10 1.77 (0.92–3.41) 0.09
High 3.96 (2.99–5.25) <0.01 2.57 (1.78–3.72) <0.01 2.79 (1.47–5.28) <0.01 3.02 (1.54–5.92) <0.01

Univariate and multivariate analyses of cancer-specific survival in the two cohorts.

HR, hazard ratios; CI, confidence intervals; TD, tumor deposit; PNI, perineural invasion; CEA, carcinoembryonic antigen; LNR, positive lymph node ratio.

TABLE 4

The training cohort The validation cohort
Univariate Multivariate Univariate Multivariate
HR (95% CI) p value HR (95% CI) p value HR (95% CI) p value HR (95% CI) p value
Gender
Female
Male 0.93 (0.76–1.14) 0.49 0.85 (0.54–1.34) 0.48
Age 1.00 (1.00–1.02) 0.01 1.01 (1.00–1.02) <0.01 1.01 (1.00–1.03) 0.10
Tumor size
≤5 cm
>5 cm 1.44 (1.18–1.77) <0.01 1.13 (0.92–1.40) 0.26 1.16 (0.75–1.79) 0.52
Tumor site 0.24 0.99
Right
Left 0.93 (0.74–1.16) 0.93 0.99 (0.55–1.80) 0.98
Rectum 0.72 (0.48–1.07) 0.10 1.01 (0.59–1.71) 0.98
Grade
Moderate
Poor 1.20 (0.76–1.91) 0.43 2.11 (0.52–8.58) 0.30
T stage
T1-3
T4 1.99 (1.61–2.45) <0.01 1.49 (1.20–1.86) <0.01 1.93 (1.22–3.04) 0.01 1.42 (0.89–2.27) 0.14
N stage
<4 nodes
≥4 nodes 2.31 (1.78–3.00) <0.01 1.26 (0.88–1.80) 0.21 1.10 (0.66–1.84) 0.72
M stage
M0
M1 2.29 (1.86–2.81) <0.01 1.59 (1.27–2.00) <0.01 2.11 (1.35–3.30) <0.01 1.89 (1.15–3.09) 0.01
TD
Absent
Present 1.78 (1.46–2.19) <0.01 1.35 (1.08–1.70) 0.01 2.57 (1.65–4.00) <0.01 1.85 (1.14–3.00) 0.01
PNI
Absent
Present 1.53 (1.26–1.87) <0.01 1.13 (0.91–1.40) 0.28 1.94 (1.23–3.04) <0.01 1.81 (1.11–2.94) 0.02
CEA
Negative
Positive 1.69 (1.38–2.08) <0.01 1.32 (1.05–1.65) 0.02 1.80 (1.15–2.81) 0.01 2.00 (1.26–3.20) <0.01
Neoadjuvant therapy
No
Yes 0.80 (0.53–1.22) 0.30 0.81 (0.30–2.22) 0.69
Chemotherapy
No
Yes 0.50 (0.41–0.62) <0.01 0.48 (0.38–0.60) <0.01 0.89 (0.56–1.40) 0.60
LNR <0.01 <0.01 0.02 0.02
Low
Moderate 1.97 (1.54–2.53) <0.01 1.81 (1.31–2.52) <0.01 1.52 (0.85–2.70) 0.16 1.57 (0.87–2.84) 0.13
High 3.49 (2.69–4.52) <0.01 2.51 (1.77–3.54) <0.01 2.31 (1.29–4.14) <0.01 2.42 (1.31–4.46) 0.01

Univariate and multivariate analyses of overall survival in the two cohorts.

HR, hazard ratios; CI, confidence intervals; TD, tumor deposit; PNI, perineural invasion; CEA, carcinoembryonic antigen; LNR, positive lymph node ratio.

TABLE 5

The training cohort The validation cohort
Cancer-specific survival Overall survival Cancer-specific survival Overall survival
HR (95% CI) p value HR (95% CI) p value HR (95% CI) p value HR (95% CI) p value
Tumor size
≤5 cm
>5 cm 1.18 (0.94–1.48) 0.16 1.13 (0.91–1.4) 0.26 1.03 (0.64–1.66) 0.91 1.12 (0.71–1.77) 0.62
T stage
T1-3
T4 1.63 (1.29–2.05) <0.01 1.56 (1.25–1.94) <0.01 1.86 (1.10–3.14) 0.02 1.54 (0.96–2.48) 0.07
N stage
<4 nodes
≥4 nodes 1.86 (1.36–2.53) <0.01 1.72 (1.30–2.27) 0.26 1.47 (0.78–2.78) 0.24 1.02 (0.59–1.76) 0.95
M stage
M0
M1 1.86 (1.48–2.35) <0.01 1.73 (1.38–2.15) <0.01 2.17 (1.34–3.53) 0.002 1.87 (1.18–2.97) 0.01
CEA
Negative
Positive 1.45 (1.15–1.83) 0.002 1.42 (1.14–1.76) 0.002 1.83 (1.11–3.01) 0.02 1.65 (1.04–2.62) 0.03
Chemotherapy
No
Yes 0.50 (0.39–0.63) <0.01 0.44 (0.36–0.55) <0.01 1.18 (0.70–2.00) 0.54 0.92 (0.57–1.47) 0.73
Combined variable <0.01 <0.01 0.001 0.002
Triple-negative
Intermediate 2.52 (1.48–4.29) 0.001 2.17 (1.38–3.41) 0.001 1.59 (0.64–3.94) 0.32 1.74 (0.79–3.84) 0.17
Triple-positive 3.05 (1.65–5.63) 0.001 2.77 (1.62–4.74) 0.001 5.12 (1.78–14.73) 0.002 5.03 (1.90–13.3) 0.001

Multivariate analyses of cancer - specific and overall survival in two cohorts for the combined variable of TD, LNR, PNI.

HR, hazard ratios; CI, confidence intervals; TD, tumor deposit; PNI, perineural invasion; CEA, carcinoembryonic antigen; LNR, positive lymph node ratio; Triple-positive: high LNR, TD-positive, and PNI-positive, Triple-negative: low LNR, TD-negative, and PNI-negative, Intermediate: the remaining group.

Construction and validation of the nomogram

A nomogram predicting CSS in advanced colorectal SRCC was developed based on T stage, M stage, TD, CEA, chemotherapy, and LNR (Figure 3A). Internal validation using ROC curves showed AUC values of 0.79, 0.80, and 0.83 for 1-year, 3-year, and 5-year CSS, respectively (Figure 3B). In external validation, the corresponding AUCs were 0.75, 0.65, and 0.63 (Figure 3C). Calibration curves for 3-year and 5-year CSS closely aligned with the 45-degree diagonal line (Figures 3D,E). Patients stratified by nomogram scores into low-, moderate-, and high-risk groups exhibited significantly different survival outcomes on Kaplan-Meier analysis (Figure 4). A novel nomogram integrating the combined variable was constructed (Figure 5A). The model demonstrated favorable calibration and discriminatory ability, with internal validation AUCs of 0.78, 0.80, and 0.82, and external validation AUCs of 0.81, 0.70, and 0.74 for 1-, 3-, and 5-year CSS, respectively (Figures 5B–E). Relative contribution analysis revealed that the combined variable exhibited the highest relative contribution to OS at 23.4%, surpassing that of T and M stages. For CSS, its relative contribution was 21.4%, ranking second only to T and M stages (Figures 6A,B).

FIGURE 3

Diagram with five panels. A: Nomogram for predicting survival based on several factors like TD, CEA, M, T, chemotherapy, and LNR. B and C: ROC curves with AUC values showing predictive accuracy over one, three, and five years (AUC values ranging from 0.632 to 0.825). D and E: Calibration plots comparing actual survival against nomogram-predicted survival probability over the same time periods, illustrating model performance.

The nomogram model for CSS (A), as well as time-dependent ROC curves (B, C) and calibration curves (D, E) in internal and external validation. CSS, Cancer-Specific Survival; LNR, positive lymph node ratio; TD, tumor deposit; ROC, receiver operating characteristic.

FIGURE 4

Kaplan-Meier graph showing cancer-specific survival over 120 months. Three lines represent survival probabilities: blue for low risk, green for moderate risk, and red for high risk. The log-rank test significance is less than 0.0001. A table below lists patient numbers at risk for each category at different time points.

Survival curve analysis based on nomogram variable score groups (three risk groups).

FIGURE 5

Panel A shows a nomogram for predicting survival probabilities based on different variables like CEA, T, N, M stages, combined variables, and chemotherapy. Panels B and C depict receiver operating characteristic (ROC) curves indicating area under the curve (AUC) values for predicting survival at one, three, and five years, with higher AUCs representing better model performance. Panels D and E present calibration plots comparing actual survival with nomogram-predicted probabilities over the same periods, showing close alignment for predictive accuracy.

The nomogram model for CSS based on the combined variable of TD, LNR, and PNI (A), as well as time-dependent ROC curves (B, C) and calibration curves (D, E) in internal and external validation. CSS, Cancer-Specific Survival; LNR, positive lymph node ratio; TD, tumor deposit; PNI, perineural invasion; ROC, receiver operating characteristic.

FIGURE 6

Two pie charts labeled A and B compare variables. Chart A shows segments: M (22.9%), T (21.1%), CEA (19.4%), Combined variable (23.4%), Chemotherapy (5.6%), and N (7.6%). Chart B displays segments: M (24.2%), T (21.7%), CEA (19.6%), Combined variable (21.4%), Chemotherapy (6.2%), and N (6.9%).

Relative contribution analysis of the combined variable for OS (A) and CSS (B). CSS, Cancer-Specific; OS, Overall-Survival, Combined variable, the triple-positive group (high LNR, TD-positive, PNI-positive), triple-negative group (low LNR, TD-negative, PNI-negative), or intermediate group.

Discussion

Signet ring cell carcinoma (SRCC) is a distinct subtype of adenocarcinoma, with remarkable differences from adenocarcinoma in pathological features, clinical behavior, prognosis, and other aspects (Dekker et al., 2019). SRCC originated primarily from mucosal epithelial cells. Microscopically, tumor cells displayed abundant mucin-filled cytoplasm, with over 50% signet ring cells in the tumor (Nagtegaal et al., 2020; Benesch and Mathieson, 2020). A higher proportion of signet ring cell components was associated with a worse prognosis (An et al., 2021; Song et al., 2019). In SRCC, the expression of adhesion molecules such as E-cadherin and β-catenin is downregulated, while intestinal trefoil factor and mucin two are upregulated, making it more prone to lymph node metastasis (Börger et al., 2007). Studies generally indicate that this type of tumor is insensitive to drugs such as cetuximab, oxaliplatin, and 5-fluorouracil (Pande et al., 2008). Therefore, exploring prognostic biomarker models related to colorectal SRCC for personalized treatment remains crucial.

LNR had demonstrated predictive value in gastrointestinal tumors (Zhu et al., 2018; Zhang C. et al., 2023). In the eighth edition of the UICC TNM classification, TD was defined as discrete nodules of cancer in the lymph drainage area of pericolorectal adipose tissue. TD was associated with poor prognosis in advanced stage rectal cancer (Wang et al., 2019). Previous studies indicated that the combined variable of TD and LNR had superior prognostic value for stage III CRC (Liu et al., 2024). PNI referred to the invasion of tumor cells into the nerve sheath and/or encirclement of the nerve circumference, which was associated with tumor invasion, metastasis, cancer-related pain, and poor clinical outcomes (Wang et al., 2024). Past studies documented the incidence of PNI across CRC stages: approximately 10% in stage I–II, 30% in stage III, and up to 40% in stage IV (Knijn et al., 2016; Al-Sukhni et al., 2017). However, the combined role of LNR, TD, and PNI as pathological biomarkers in advanced colorectal SRCC remained understudied.

The study found that TD was present in 50.7% of advanced colorectal SRCC cases, while PNI in 40.6% of cases. These rates were notably higher than those reported in general CRC literature (Knijn et al., 2016; Jin et al., 2015), likely due to the unique malignant pathological nature of SRCC. Moreover, high-LNR, TD-positive, and PNI-positive were all associated with poor prognosis. Further analysis revealed that LNR served as a consistent prognostic indicator across all stages, while TD and PNI showed significant prognostic value only in stage III, with no predictive significance in stage IV. This discrepancy may be attributed to the prevalence of distant metastasis in stage IV patients, which predominantly influences survival outcomes.

In this study, a nomogram model for advanced colorectal SRCC was constructed. By using individualized nomogram scores for risk stratification, the model effectively distinguished the survival outcomes of different subgroups, verifying its reliability. The combined analysis of TD, LNR, and PNI enhanced the prognostic assessment tool. The relative contribution analysis revealed that the combined variable accounted for 23.4% of OS prediction, surpassing the contributions of T and M stages. For CSS prediction, their combined weight reached 21.4%, second only to T and M stages. These findings underscored that TD, LNR, and PNI were essential biomarkers that complement the traditional staging system.

Nevertheless, the study has several limitations. As a retrospective design, it is inherently susceptible to selection and information biases. The absence of specific chemotherapy regimens and detailed patient health status limits the establishment of causal relationships. Secondly, the predictive performance of the nomogram diminishes over extended follow-up due to unmeasured confounding factors (e.g., secondary diseases, treatment changes). Future multicenter studies with larger sample sizes are necessary to enhance the model’s stability and generalizability.

In conclusion, LNR, TD, and PNI can serve as valuable prognostic factors for advanced colorectal SRCC. Their combined analysis represents a significant addition to the traditional staging system, offering a novel perspective for precise clinical prognosis assessment.

Statements

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

The studies involving humans were approved by The ethics committees for the four hospitals are as follows: Nanjing Medical University Second Affiliated Hospital Medical Ethics Committee, No. 2020-092; Yixing People’s Hospital Medical Ethics Committee, No. 2022-158; Nanjing University School of Medicine Affiliated Gulou Hospital Medical Ethics Committee, No. 2022-469-02; Xuzhou Central Hospital Biomedical Research Ethics Review Committee, No. XZXY-LK-20240116-007. The studies were conducted in accordance with the local legislation and institutional requirements. The ethics committee/institutional review board waived the requirement of written informed consent for participation from the participants or the participants’ legal guardians/next of kin because this was a retrospective data analysis. Therefore, the requirement for obtaining informed consent from patients was waived by the ethics committee.

Author contributions

LC: Data curation, Writing – original draft, Conceptualization, Investigation, Formal Analysis, Methodology, Supervision, Writing – review and editing. HW: Formal Analysis, Project administration, Data curation, Validation, Writing – review and editing, Conceptualization, Writing – original draft. TL: Data curation, Methodology, Supervision, Investigation, Conceptualization, Writing – review and editing, Writing – original draft. SF: Writing – original draft, Methodology, Conceptualization, Software, Investigation, Data curation. YD: Writing – original draft, Conceptualization, Software, Investigation, Methodology, Data curation. YZ: Writing – original draft, Methodology, Conceptualization, Investigation, Software. YP: Supervision, Writing – original draft, Methodology, Software, Investigation. CW: Writing – original draft, Visualization, Resources, Formal Analysis, Funding acquisition, Validation, Writing – review and editing, Project administration. XW: Funding acquisition, Formal Analysis, Software, Writing – original draft, Writing – review and editing, Resources, Visualization, Conceptualization, Investigation. LL: Data curation, Validation, Resources, Conceptualization, Visualization, Project administration, Formal Analysis, Methodology, Writing – review and editing, Supervision, Funding acquisition, Investigation, Software, Writing – original draft.

Funding

The author(s) declare that financial support was received for the research and/or publication of this article. Major Project of the Hospital Management Institute of the National Health Commission of the People’s Republic of China (YM2024ZD026); General Program of Wuxi Medical Center of Nanjing Medical University (WMCG202354), Doctoral Talent Fund of the Affiliated Wuxi People’s Hospital of Nanjing Medical University (BSRC202303).

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declare that no Generative AI was used in the creation of this manuscript.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fmolb.2025.1617787/full#supplementary-material

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Summary

Keywords

colorectal signet ring cell carcinoma, lymph node ratio, tumor deposit, perineural invasion, prognosis

Citation

Chu L, Wang H, Ling T, Feng S, Ding Y, Zhang Y, Pan Y, Wang C, Wang X and Liu L (2025) Prognostic value of positive lymph node ratio, tumor deposit, and perineural invasion in advanced colorectal signet-ring cell carcinoma. Front. Mol. Biosci. 12:1617787. doi: 10.3389/fmolb.2025.1617787

Received

25 April 2025

Accepted

27 June 2025

Published

01 August 2025

Volume

12 - 2025

Edited by

Zhihuang Hu, Fudan University, China

Reviewed by

Jianwei Zhang, The Sixth Affiliated Hospital of Sun Yat-sen University, China

Xiagang Luo, The Second Affiliated Hospital of Nanjing Medical University Department of Gastroenterology, Jiangsu, China

Bicheng Ye, Southeast University, China

Updates

Copyright

*Correspondence: Cenzhu Wang, ; Xiaohong Wang, ; Lei Liu,

†These authors have contributed equally to this work

Disclaimer

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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