A genomic-clinicopathologic Nomogram for the preoperative prediction of lymph node metastasis in gastric cancer.

BACKGROUND: Preoperative evaluation of lymph node (LN) state is of pivotal significance for informing therapeutic decisions in gastric cancer (GC) patients. However, there are no non-invasive methods that can be used to preoperatively identify such status. We aimed at developing a genomic biosignature based model to predict the possibility of LN metastasis in GC patients. METHODS: We used the RNA profile retrieving strategy and performed RNA expression profiling in a large GC cohort (GSE62254, n = 300) from Gene Expression Ominus (GEO). In the exploratory stage, 300 GC patients from GSE62254 were involved and the differentially expressed RNAs (DERs) for LN-status were determined using the R software. GC samples in GSE62254 were randomly allocated into a learning set (n = 210) and a verification set (n = 90). By using the Least absolute shrinkage and selection operator (LASSO) regression approach, a set of 23-RNA signatures were established and the signature based nomogram was subsequently built for distinguishing LN condition. The diagnostic efficiency, as well as the clinical performance of this model were assessed using the decision curve analysis (DCA). Metascape was used for bioinformatic analysis of the DERs. RESULTS: Based on the genomic signature, we established a nomogram that robustly distinguished LN status in the learning (AUC = 0.916, 95% CI 0.833-0.999) and verification sets (AUC = 0.775, 95% CI 0.647-0.903). DCA demonstrated the clinical value of this nomogram. Functional enrichment analysis of the DERs was performed using bioinformatics methods which revealed that these DERs were involved in several lymphangiogenesis-correlated cascades. CONCLUSIONS: In this study, we present a genomic signature based nomogram that integrates the 23-RNA biosignature based scores and Lauren classification. This model can be utilized to estimate the probability of LN metastasis with good performance in GC. The functional analysis of the DERs reveals the prospective biogenesis of LN metastasis in GC.

Glasgow prognostic score is a predictive index for postoperative infectious complications after total proctocolectomy in ulcerative colitis patients.

BACKGROUND AND AIM: Glasgow prognostic score is a systemic inflammatory-based score. The aim of this study was to determine whether the Glasgow prognostic score was a useful predictor of short-term outcomes in patients who undergo total proctocolectomy for ulcerative colitis. METHODS: eighty ulcerative colitis patients who underwent a total proctocolectomy with ileal pouch-anal anastomosis or permanent end ileostomy from June 2014 to March 2020 were retrospectively analyzed. Patients were divided into a lower Glasgow prognostic score group and a higher Glasgow prognostic score group. RESULTS: postoperative infectious complication occurred more frequently in the higher Glasgow prognostic score group (8.3 % vs 29.5 %, p = 0.018). According to the univariate and multivariate analysis, only a higher Glasgow prognostic score was associated with an increased risk of postoperative infectious complication (OR: 5.478, 95 % CI: 1.236-24.279). CONCLUSION: Glasgow prognostic score is a simple and useful indicator of postoperative infectious complications.

Impact of three-dimensional reconstruction visualization technology on short-term and long-term outcomes after hepatectomy in patients with hepatocellular carcinoma: a propensity-score-matched and inverse probability of treatment-weighted multicenter study.

BACKGROUND: Three-dimensional reconstruction visualization technology (3D-RVT) is an important tool in the preoperative assessment of patients undergoing liver resection. However, it is not clear whether this technique can improve short-term and long-term outcomes in patients with hepatocellular carcinoma (HCC) compared with two-dimensional (2D) imaging. METHOD: A total of 3402 patients from five centers were consecutively enrolled from January 2016 to December 2020, and grouped based on the use of 3D-RVT or 2D imaging for preoperative assessment. Baseline characteristics were balanced using propensity score matching (PSM, 1:1) and stabilized inverse probability of treatment-weighting (IPTW) to reduce potential selection bias. The perioperative outcomes, long-term overall survival (OS), and recurrence-free survival (RFS) were compared between the two groups. Cox-regression analysis was used to identify the risk factors associated with RFS. RESULTS: A total of 1681 patients underwent 3D-RVT assessment before hepatectomy (3D group), while 1721 patients used 2D assessment (2D group). The PSM cohort included 892 patient pairs. In the IPTW cohort, there were 1608.3 patients in the 3D group and 1777.9 patients in the 2D group. In both cohorts, the 3D group had shorter operation times, lower morbidity and liver failure rates, as well as shorter postoperative hospital stays. The 3D group had more margins ≥10 mm and better RFS than the 2D group. The presence of tumors with a diameter ≥5 cm, intraoperative blood transfusion and multiple tumors were identified as independent risk factors for RFS, while 3D assessment and anatomical resection were independent protective factors. CONCLUSION: In this multicenter study, perioperative outcomes and RFS of HCC patients following 3D-RVT assessment were significantly different from those following 2D imaging assessment. Thus, 3D-RVT may be a feasible alternative assessment method before hepatectomy for these patients.

Targeting BMI-1-mediated epithelial-mesenchymal transition to inhibit colorectal cancer liver metastasis.

Liver is the most common metastatic site for colorectal cancer (CRC), there is no satisfied approach to treat CRC liver metastasis (CRCLM). Here, we investigated the role of a polycomb protein BMI-1 in CRCLM. Immunohistochemical analysis showed that BMI-1 expression in liver metastases was upregulated and associated with T4 stage, invasion depth and right-sided primary tumor. Knockdown BMI-1 in high metastatic HCT116 and LOVO cells repressed the migratory/invasive phenotype and reversed epithelial-mesenchymal transition (EMT), while BMI-1 overexpression in low metastatic Ls174T and DLD1 cells enhanced invasiveness and EMT. The effects of BMI-1 in CRC cells were related to upregulating snail via AKT/GSK-3ß pathway. Furthermore, knockdown BMI-1 in HCT116 and LOVO cells reduced CRCLM using experimental liver metastasis mice model. Meanwhile, BMI-1 overexpression in Ls174T and DLD1 significantly increased CRCLM. Moreover, sodium butyrate, a histone deacetylase and BMI-1 inhibitor, reduced HCT116 and LOVO liver metastasis in immunodeficient mice. Our results suggest that BMI-1 is a major regulator of CRCLM and provide a potent molecular target for CRCLM treatment.