Background and aims: Standardized quantitative criteria are lacking for the recommended circumferential thermal ablative margin in liver malignancies ≤3 cm. This study aimed to identify predictors of technical success in thermal ablation and develop a predictive model defining optimal ablation margins. Methods: This retrospective study analyzed 979 patients undergoing computed tomography-guided radiofrequency or microwave ablation for liver malignancies ≤3 cm. Using a radiotherapy treatment planning system, preoperative tumor dimensions [maximum tumor area, preoperative maximum tumor area (PreMTA); tumor volume, preoperative tumor volume (PreTV)] and postoperative ablation characteristics [maximum ablation area, postoperative maximum ablation area (Post-MAA); ablation volume, postoperative ablation volume (PostAV)] were volumetrically quantified. Volume ratio (PostAV/PreTV) and area ratio (PostMAA/PreMTA) were calculated. Univariate and multivariate logistic regression identified predictors of residual tumor. A nomogram was developed and validated using Harrell’s C-index, calibration curves, and receiver operating characteristic analysis. Size- and location-specific margin recommendations were derived mathematically. Results: Residual tumor occurred in 91 patients (9.3%). Multivariate analysis identified adjacent large vessel [odd ratio (OR) = 1.97; P = 0.015], larger PreMTA (OR = 1.44; P = 0.014), and lower volume ratio (OR = 0.77; P = 0.009) as independent predictors. For non-perivascular tumors, optimal volume ratios were 4.3, 6.0, and 8.8 (corresponding Δ R = 0.3 cm, 0.8 cm, 1.6 cm) for diameters 1.0 cm, 2.0 cm, and 3.0 cm, respectively. A web-based calculator was implemented (https://fbzl.org/monitor/ablation_model.html). Conclusions: This study establishes and validates a computational model defining tumor size- and vessel proximity-specific optimal ablation margins for liver malignancies ≤3 cm. The web-accessible model provides evidence-based individualized ablation targets that optimize oncological efficacy while preserving parenchyma, replacing conventional fixed margins.

Background: RNA alternative splicing represents a pivotal regulatory mechanism of eukaryotic gene expression, wherein splicing factors (SFs) serve as key regulators. Aberrant SF expression drives oncogenic splice variant production, thereby promoting tumorigenesis and malignant progression. However, the biological functions and potential targets of SFs remain largely underexplored. Methods: Through multi-omics analysis, we identified survival-related splicing factors (SFs) in esophageal cancer and elucidated their biological regulatory networks. To further investigate their downstream splicing targets, we combined alternative splicing events resulting from SF knockdown with those specific to esophageal cancer. Finally, these splicing events were validated through full-length RNA sequencing and confirmed in cancer cells and clinical specimens. Result: We identified six SFs that are highly expressed in esophageal cancer and correlate with poor prognosis. Further analysis revealed that these factors are significantly associated with immune infiltration, cancer stemness, tumor heterogeneity, and drug resistance. CRNKL1 was identified as a hub SFs. The target genes and pathways regulated by these SFs showed substantial overlap, suggesting their coordinated roles in promoting cancer stemness and metastasis. Specifically, alternative splicing of key markers, such as CD44 and CTTN, was regulated by most of these SFs and correlated with poor prognosis. Conclusions: Our study unveils six survival-related SFs that contribute to the aggressiveness of esophageal cancer and CTTN and CD44 alternative splicing may act as common downstream effectors of survival-related SFs. This study provides mechanistic insights into SF-mediated tumorigenesis and highlight novel therapeutic vulnerabilities in esophageal cancer.