Background: Although the recommended minimal examined lymph node (ELN) number in rectal cancer (RC) is 12, this standard remains controversial because of insufficient evidence. We aimed to refine this definition by quantifying the relationship between ELN number, stage migration and long-term survival in RC. Methods: Data from a Chinese multi-institutional registry (2009-2018) and the Surveillance, Epidemiology, and End Results (SEER) database (2008-2017) on stages I–III resected RC were analysed to determine the relationship between ELN count, stage migration, and overall survival (OS) using multivariable models. The series of odds ratios (ORs) for negative-to-positive node stage migration and hazard ratios (HRs) for survival with more ELNs were fitted using a Locally Weighted Scatterplot Smoothing (LOWESS) smoother, and structural breakpoints were determined using the Chow test. The relationship between ELN and survival was evaluated on a continuous scale using restricted cubic splines (RCS). Results: The distribution of ELN count between the Chinese registry (n=7694) and SEER database (n=21 332) was similar. With increasing ELN count, both cohorts exhibited significant proportional increases from node-negative to node-positive disease (SEER, OR, 1.012, P<0.001; Chinese registry, OR, 1.016, P=0.014) and serial improvements in OS (SEER: HR, 0.982; Chinese registry: HR, 0.975; both P<0.001) after controlling for confounders. Cut-point analysis showed an optimal threshold ELN count of 15, which was validated in the two cohorts, with the ability to properly discriminate probabilities of survival. Conclusions: A higher ELN count is associated with more precise nodal staging and better survival. Our results robustly conclude that 15 ELNs are the optimal cut-off point for evaluating the quality of lymph node examination and stratification of prognosis.

Background: The National Quality Forum has endorsed at least 12 lymph node yield (LNY) as a surgical quality indicator in colorectal cancer (CRC), but the prognostic value of adequate lymphadenectomy has rarely been investigated for CRC patients with distant metastatic disease. Methods: 4575 CRC patients with synchronous liver metastasis who underwent primary tumor resection were identified from a Chinese registry and the Surveillance, Epidemiology, and End Results (SEER) database between 2010 to 2017. Kaplan-Meier methods and Cox regression models were performed to assess the correlations between LNY and 3-year cancer specific survival (CSS). Propensity score matching (PSM) were used to confirmed the survival comparison between patients with <12 and ≥12 LNY. Results: The retrieval of at least 12 LNY was identified in most CRC patients (SEER database, 3380/3899, 86.7%; Chinese cohort, 565/676, 83.6%). In both SEER database and Chinese cohort, the patients with LNY ≥12 was significantly associated with better CSS compared to patients with LNY <12 before and after PSM, with all P<0.05. After controlling for the confounders, multivariate analysis demonstrated that LNY was also an independent prognostic factor for patients with distant metastasis in both cohorts. In subgroup analysis, the CSS benefit for patients with LNY ≥12 was observed across most of subgroups. Conclusions: Clinical feasibility of the 12–node threshold as a guideline quality metric of cancer care for CRC patients is necessary, and an oncologically adequate lymphadenectomy is still a critical component of high-quality surgical standard in CRC patients with distant metastases.

Background: This study aimed to investigate the prognostic impact of lymph node metastasis (LNM) on patients with colorectal cancer liver metastasis (CRLM) and elucidate the underlying immune mechanisms using multiomics profiling. Methods: We enrolled patients with CRLM from the US Surveillance, Epidemiology, and End Results (SEER) cohort and a multicenter Chinese cohort, integrating bulk RNA sequencing, single-cell RNA sequencing and proteomics data. The cancer-specific survival (CSS) and immune profiles of the tumor-draining lymph nodes (TDLNs), primary tumors and liver metastasis were compared between patients with and without LNM. Pathological evaluations were used to assess immune cell infiltration and histological features. Results: The CRLM patients with LNM had significantly shorter CSS than patients without LNM in two large cohorts. Our results showed that nonmetastatic TDLNs exhibited a greater abundance of immune cells, including CD4+ T cells, CD8+ T cells, and CD19+ B cells, whereas metastatic TDLNs were enriched with fibroblasts, endothelial cells, and macrophages. Immunohistochemical analysis confirmed elevated levels of CD3+ T cells, CD8+ T cells, and CD19+ B cells in nonmetastatic TDLNs. The presence of nonmetastatic TDLNs was associated with enhanced antitumor immune responses in primary tumors, characterized by a higher Klintrup–Makinen (KM) grade and the presence of tertiary lymphoid structures. Furthermore, liver metastasis in patients with nonmetastatic TDLNs were predominantly of the desmoplastic growth pattern (dHGP), while those with metastatic TDLNs were predominantly of the replacement growth pattern (rHGP). Conclusions: This research highlights the adverse prognostic impact of LNM on patients with CRLM and reveals potential related mechanisms through multiomics analysis. Our research paves the way for further refinement of the AJCC TNM staging system for CRLM in clinical practice.

Background: Although the surgical treatment strategy for rectal cancer (RC) is usually based on the preoperative diagnosis of lymph node metastasis (LNM), the accurate diagnosis of LNM has been a clinical challenge. In this study, we developed machine learning (ML) models to predict the LNM status before surgery based on a privacy-preserving computing platform (PPCP) and created a web tool to help clinicians with treatment-based decision-making in RC patients. Patients and methods: A total of 6578 RC patients were enrolled in this study. ML models, including logistic regression, support vector machine, extreme gradient boosting (XGB), and random forest, were used to establish the prediction models. The areas under the receiver operating characteristic curves (AUCs) were calculated to compare the accuracy of the ML models with the US guidelines and clinical diagnosis of LNM. Last, model establishment and validation were performed in the PPCP without the exchange of raw data among different institutions. Results: LNM was detected in 1006 (35.3%), 252 (35.3%), 581 (32.9%), and 342 (27.4%) RC patients in the training, test, and external validation sets 1 and 2, respectively. The XGB model identified the optimal model with an AUC of 0.84 [95% confidence interval (CI), 0.83–0.86] compared with the logistic regression model (AUC, 0.76; 95% CI, 0.74–0.78), random forest model (AUC, 0.82; 95% CI, 0.81–0.84), and support vector machine model (AUC, 0.79; 95% CI, 0.78–0.81). Furthermore, the XGB model showed higher accuracy than the predictive factors of the US guidelines and clinical diagnosis. The predictive XGB model was embedded in a web tool (named LN-MASTER) to predict the LNM status for RC. Conclusion: The proposed easy-to-use model showed good performance for LNM prediction, and the web tool can help clinicians make treatment-based decisions for patients with RC. Furthermore, PPCP enables state-of-the-art model development despite the limited local data availability.

While local immune responses within the tumour microenvironment are well studied and linked to colorectal cancer progression and patient survival, circulating immune cell subsets are less explored¹. Research comparing circulating immune cell subsets between healthy individuals and those with colorectal cancer involve limited sample sizes and focus only on the relationship between immune cells and prognosis^2,3. The impact of clinical variables on circulating immune cell subsets has not been well documented. Peripheral blood immune function testing offers data on proportions of cells as a non-invasive, economical screening tool, yet its implications remain superficial. Large-scale observational studies are needed to uncover its utility in clinical practice.