Propose The purpose of this study was to compare the accuracy of visceral fat area (VFA) and body mass index (BMI) in predicting the risk of laparoscopic-assisted gastrectomy. Methods Clinicopathological and imaging data of 133 patients who underwent laparoscopy-assisted gastrectomy were recorded, including 17 cases of conversion to open surgery. The remaining 116 patients were retrospectively analyzed after we excluded 17 patients who had been transferred to laparotomy. The patients were divided into two groups according to BMI (≤25 kg/m2: BMI-L group; >25 kg/m2: BMI-H group) and VFA (≤100 cm2: VFA-L group; >100 cm2: VFA-H group). Clinical outcomes were compared between the BMI and VFA subgroups. Results There were no differences in intraoperative blood loss and the number of harvested lymph nodes between low and high patients defined by BMI and VFA (p > 0.050). However, in the comparison of patients who underwent laparoscopic resection only, it was found that the operation time and intraoperative blood loss of the VFA-H group were more than those of the VFA-L group (p < 0.050). Compared to the VFA-L group, the VFA-H group had later first exhaust time (p = 0.018), more complications (p < 0.001), and longer hospital stays (p = 0.049). However, no similar conclusion was obtained in the BMI group (p > 0.050). Conclusion This study demonstrates that VFA better evaluates the difficulty of laparoscopy-assisted gastrectomy and the risk of postoperative complications than BMI.
Colon adenocarcinoma (COAD) is one of the most common malignant tumors. Tumor mutation burden (TMB) has become an independent biomarker for predicting the response to immune checkpoint inhibitors (ICIs). miRNAs play an important role in cancer-related immune regulation. However, the relationship between miRNA expression and TMB in COAD remains unclear. Therefore, the transcriptome profiling data, clinical data, mutation annotation data, and miRNA expression profiles for cases of COAD were downloaded from the TCGA database. Subsequently, 323 COAD cases were randomly divided into training and test sets. The differential expression of miRNAs in the high and low TMB groups in the training set was obtained as a signature using the least absolute shrinkage and selection operator (LASSO) logistic regression and verified in the test set. Based on the LASSO method, principal component analysis (PCA), and ROC, we found that the signature was credible because it can discriminate between high and low TMB levels. In addition, the correlation between the 18-miRNA-based signature and immune checkpoints was performed, followed by qRT-PCR, to measure the relative expression of 18 miRNAs in COAD patients. The miRNA-based model had a strong positive correlation with TMB and a weak positive correlation with CTLA4 and CD274 (PD-L1). However, no correlation was observed between the model and SNCA (PD-1). Finally, enrichment analysis of the 18 miRNAs was performed to explore their biological functions. The results demonstrated that 18 miRNAs were involved in the process of immunity and cancer pathways. In conclusion, the 18-miRNA-based signature can effectively predict and discriminate between the different TMB levels of COAD and provide a guide for its treatment with ICIs.
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