| Literature DB >> 36186777 |
Lei Chen1, Funing Yang2, Zhaoyan Qi1, Jiandong Tai1.
Abstract
Tumor budding (TB), a powerful, independent predictor of colorectal cancer (CRC), is important for making appropriate treatment decisions. Currently, TB is assessed only using the tumor bud count (TBC). In this study, we aimed to develop a novel prediction model, which includes different TB features, for lymph node metastasis (LNM) and local recurrence in patients with pT1 CRC. Enrolled patients (n = 354) were stratified into training and validation cohorts. Independent predictors of LNM and recurrence were identified to generate predictive nomograms that were assessed using the area under the receiver operating characteristic (AUROC) and decision curve analysis (DCA). Seven LNM predictors [gross type, histological grade, lymphovascular invasion (LVI), stroma type, TBC, TB mitosis, and TB CDX2 expression] were identified in the training cohort. LNM, histology grade, LVI, TBC, stroma type, and TB mitosis were independent predictors of recurrence. We constructed an LNM predictive nomogram with a high clinical application value using the DCA. Additionally, a nomogram predicting recurrence-free survival (RFS) was constructed. It presented an AUROC value of 0.944 for the training cohort. These models may assist surgeons in making treatment decisions. In the high-risk group, radical surgery with a postoperative adjuvant chemotherapy was associated with RFS. Postoperative chemotherapy can be better for high-risk patients with pT1 CRC. We showed that TB features besides TBC play important roles in CRC pathogenesis, and our study provides prognostic information to guide the clinical management of patients with early stage CRC.Entities:
Keywords: CDX2; colorectal cancer; lymph node metastasis; predictive nomogram; recurrence-free survival; risk stratification; tumor budding
Year: 2022 PMID: 36186777 PMCID: PMC9520336 DOI: 10.3389/fmed.2022.991785
Source DB: PubMed Journal: Front Med (Lausanne) ISSN: 2296-858X
Demographics of surgery of 354 patients with pT1 CRC who underwent surgical resection.
| Variable | All patients | |
| Age (years) | 65.2 ± 10.3 [30–91] | |
| Sex | Female | 131 (37.0%) |
| Male | 223 (63.0%) | |
| LNM | Absent | 305 (86.2%) |
| Present | 49 (13.8%) | |
| Gross tumor type | Non-pedunculated | 161 (45.5%) |
| Pedunculated | 193 (54.5%) | |
|
| Wild-type | 27 (7.6%) |
| Mutant-type | 156 (44.1%) | |
| - | 171 (48.3%) | |
|
| MSI-high | 11 (3.1%) |
| MSI-low | 172 (48.6%) | |
| - | 171 (48.3%) | |
|
| Absent | 182 (51.4%) |
| Present | 1 (0.3%) | |
| - | 171 (48.3%) | |
| Ki67 (%) | 78.7 ± 13.2 [5.0–95.0] | |
| Histology grade | Low-grade | 339 (95.8%) |
| High-grade | 15 (4.2%) | |
| Lymph-vascular invasion | Absent | 315 (89.0%) |
| Present | 39 (11.0%) | |
| TB construction | Cluster | 201 (56.8%) |
| Single | 153 (43.2%) | |
| TB location | ITB | 118 (33.4%) |
| PTB | 236 (66.7%) | |
| TB atypia | Non-specific | 311 (87.9%) |
| Anaplasia-like | 43 (12.1%) | |
| TB stroma | Inflammation | 100 (28.3%) |
| Fibrosis | 192 (54.2%) | |
| Myxoid | 62 (17.5%) | |
| TB mitosis | Absent | 298 (84.2%) |
| Present | 56 (15.8%) | |
| TB quantity | 10.7 ± 3.7 [0.0–18.0] | |
| TB CDX2 status | Negative | 87 (24.6%) |
| Positive | 267 (75.4%) | |
| TB EGFR status | Negative | 50 (14.1%) |
| Positive | 304 (85.9%) | |
| Recurrence | Absent | 316 (89.3%) |
| Present | 38 (10.7%) |
*Data are mean ± standard deviation. MSI, microsatellite instability; TB, tumor budding.
FIGURE 1Histological and immunohistochemical features of pT1 colorectal cancer (CRC). (A) High histology grade; (B) lymph-vascular invasion observed in a biopsy specimen; (C) inflammatory stroma surrounding tumor budding (TB); (D) myxoid stroma surrounding TB; (E) mitosis present in TB; (F) CDX2 expression in tumor cells, while loss of expression in TB.
FIGURE 2Predicted model of lymph node metastasis (LNM). (A) Forest plots to decipher the risk factors associated with LNM identified in the univariate logistic regression analysis; (B) newly developed nomogram for predicting LNM in patients with pT1 CRC. The calibration curve for predicting LNM of pT1 CRCs in the (C) training and (D) validation cohorts. Decision curve analysis of the nomogram and TB quantity alone for predicting LNM in patients with pT1 CRC in the (E) training cohort and (F) validation cohort.
Multivariate logistic regression analysis of lymph node metastasis.
| Training cohort | Validation cohort | |||
| ( | ( | |||
| OR (95% CI) |
| OR (95% CI) |
| |
|
| ||||
| Non-pedunculated | 1.000 | 1.000 | ||
| Pedunculated | 0.641 (0.098–4.185) | 0.477 | 0.826 (0.124–4.079) | 0.772 |
|
| ||||
| Low-grade | 1.000 | 1.000 | ||
| High-grade | 5.561 (1.933–16.003) | 0.002 | 4.403 (1.046–18.520) | 0.043 |
|
| ||||
| Absent | 1.000 | 1.000 | ||
| Present | 34.194 (9.511–122.930) | 0.004 | 11.156 (2.186–56.912) | 0.003 |
|
| ||||
| Inflammation | 1.000 | 1.000 | ||
| Fibrosis | 1.667 (1.278–9.451) | 0.527 | 1.206 (1.1412–6.216) | 0.087 |
| Myxoid | 6.746 (1.831–24.851) | 0.032 | 4.303 (1.945–15.933) | 0.022 |
|
| ||||
| Absent | 1.000 | 1.000 | ||
| Present | 2.770 (0.643–11.925) | 0.171 | 1.013 (0.926–2.618) | 0.568 |
| TB quantity | 63.429 (14.623–275.130) | 0.001 | 28.952 (4.010–208.990) | 0.008 |
|
| ||||
| Negative | 15.919 (4.259–59.494) | 0.021 | 17.350 (7.689–25.778) | 0.003 |
| Positive | 1.000 | 1.000 |
CI, confidence interval; OR, odds ratio; MSI, microsatellite instability; LVI, lymphovascular invasion; TB, tumor budding.
FIGURE 3Prediction model for recurrence-free survival (RFS). (A) Forest plots to decipher the risk factors associated with RFS identified in univariate Cox regression analysis; (B) RFS predictive nomogram. The calibration curve of postoperative RFS in patients with pT1 CRC in the (C) training cohort and (D) validation cohort. Predictive accuracy of RFS-nomogram in the (E) training cohort and (F) validation cohort.
Multivariate COX regression analysis of recurrence.
| Training cohort | Validation cohort | |||
| ( | ( | |||
| HR (95% CI) |
| HR (95% CI) |
| |
|
| ||||
| Absent | 1.000 | 1.000 | ||
| Present | 32.292 (14.401–72.407) | < 0.0001 | 16.331 (6.007–58.260) | < 0.0001 |
|
| ||||
| Non-pedunculated | 1.000 | 1.000 | ||
| Pedunculated | 0.733 (0.171–2.153) | 0.337 | 0.891 (0.432–3.014) | 0.547 |
|
| ||||
| Low-grade | 1.000 | 1.000 | ||
| High-grade | 1.622 (1.002–2.627) | 0.049 | 1.548 (0.771–3.107) | 0.218 |
|
| ||||
| Absent | 1.000 | 1.000 | ||
| Present | 2.686 (1.162–6.208) | 0.021 | 2.958 (1.160–7.541) | 0.023 |
|
| ||||
| Inflammation | 1.000 | 1.000 | ||
| Fibrosis | 1.256 (0.449–1.632) | 0.551 | 1.192 (0.312–1.880) | 0.715 |
| Myxoid | 1.719 (0.264–1.955) | 0.001 | 1.280 (0.950–2.819) | 0.151 |
|
| ||||
| Absent | 1.000 | 1.000 | ||
| Present | 1.022 (0.540–1.933) | < 0.0001 | 1.567 (0.615–2.673) | 0.094 |
| TB quantity | 1.703 (1.055–2.750) | 0.029 | 1.563 (0.838–2.914) | 0.020 |
|
| ||||
| Negative | 0.935 (0.520–1.679) | 0.216 | 1.789 (0.711–4.502) | 0.799 |
| Positive | 1.000 | 1.000 |
Statistical analyses were conducted using log-rank tests and a Cox proportional hazards model. CI, confidence interval; LVI, lymphovascular invasion; RFS, recurrence-free survival; TB, tumor budding.
FIGURE 4Survival curves for subgroup analysis in patients with different risk of postsurgical recurrence stratified by nomogram score. (A) Kaplan–Meier survival curves for RFS according to the risk status in all patients; (B) RFS according to different therapy in high-risk cohort.