RESUMO
@#Objective To investigate the predictive value of prognostic nutritional index (PNI) in complications after thoracoscopy-assisted radical resection of esophageal cancer. Methods We collected the clinical data of patients who underwent thoracoscopy-assisted esophagectomy in the First Affiliated Hospital of Xinjiang Medical University from January 2015 to June 2020. The predictive value of PNI for postoperative complications was evaluated by establishing receiver operating characteristic (ROC) curve and the optimal cut-off point was determined. The patients were divided into a high PNI group and a low PNI group according to the cut-off point. The differences of baseline data and perioperative complications-related indicators between the two groups were compared and analyzed. Univariate and multivariate analyses were used to investigate the influence of PNI and other related indexes on postoperative complications. Results A total of 116 patients were enrolled in this study, including 75 males and 41 females, aged 65 (58-69) years. The area under ROC curve was 0.647, and the optimal cut-off point was 51.9. According to the cut-off point, there were 45 patients in the high PNI group and 71 patients in the low PNI group. The overall complication rate (χ2=10.437, P=0.001) and the incidence of postoperative pulmonary infection (χ2=10.811, P=0.001) were statistically different between the two groups. The results of univariate analysis showed that the duration of ventilator use (Z=–3.136, P=0.002), serum albumin value (t=2.961, P=0.004), and PNI value (χ2=10.437, P=0.001) were the possible risk factors for postoperative complications after thoracoscopy-assisted esophagectomy. The results of multivariate analysis suggested that the duration of ventilator use (OR=1.015, P=0.002) and the history of drinking (OR=5.231, P=0.013) were independent risk factors for postoperative complications, and high PNI was the protective factor for postoperative complications (OR=0.243, P=0.047). Conclusion PNI index has a certain value in predicting postoperative complications, which can quantify the preoperative nutritional and immune status of patients. Drinking history and duration of ventilator use are independent risk factors for postoperative complications of thoracoscopy-assisted esophagectomy, and high PNI is a protective factor for postoperative complications.
RESUMO
Confirming histological patterns of lung carcinoma is important for determining the prognosis and the next steps of treatment for a patient. Confirming the histologic patterns (subtype) of lung adenocarcinoma is important for determining the prognosis and treatment options for a patient. The task is challenging, and often requires the input of experienced pathologists, who by themselves lack interobserver concordance. A computer-aided diagnosis holds the potential to accelerate the time to diagnosis. As many adenocarcinoma tissue samples contain multiple histologic patterns, accurate computer-aided diagnosis requires annotations manually labeled by pathologists. We propose a method that merges weak supervised learning and Integrated Learning using Transfer Learning using two datasets: The Cancer Genome Atlas (TCGA), and the Clinical Proteomic Tumor Analysis Consortium (CPTAC) to reduce the need for manual annotation by a pathologist while maintaining accuracy. Whole-slide images (WSI) are first determined to be either adenocarcinoma or squamous cell carcinoma, then further identify the subtypes by generating weak classifiers for each subtype, then using integrated learning to create a strong classifier. Our model was evaluated with independent datasets from the CPTAC dataset and a dataset from a private hospital. It can achieve AUC values of 0.86, 0.91, 0.82, 0.77, 0.96, 0.98 in Acinar, LPA, Micropapillary, Papillary, Solid, and Normal, respectively.
RESUMO
Background: Thrombospondin type 1 domain-containing 7A (THSD7A) was reported to play a procancer role in esophageal squamous cell carcinoma (ESCC). The aim of the study was to screen the downstream functional genes of THSD7A and explore their functions in ESCC, based on the reported research into THSD7A function and on gene microarrays. Methods: We adopted quantitative reverse-transcription polymerase chain reaction (qRT-PCR) and Celigo high-content screening (HCS) technology to screen the downstream genes of THSD7A. The expression level of target genes was examined by PCR, western blot, and immunohistochemistry (IHC). The effects of these target genes on ESCC malignant biological behavior were performed in vivo and in vitro. The Kaplan-Meier (K-M) survival analysis and Cox regression were used to analyze the prognostic significance of target genes in ESCC patients. Experiments in the literature on liver cancer (LC) were repeated to verify the functions of these genes in different tumors. We further explored the cancer-promoting mechanism of target genes in ESCC by sequencing of the genes' exons. Results: Scavenger receptor class A member 5 (SCARA5) was proved to be the downstream driving gene of THSD7A. SCARA5 promoted cell proliferation and migration but inhibited apoptosis in ESCC. IHC results confirmed that SCARA5 expression in ESCC exceeded that in normal tissues. The K-M survival analysis indicated that SCARA5 expression quantity was not related to prognosis, but tumor volume and T classification were both the independent prognostic factors. Repetition of experiments in LC in the literature confirmed that SCARA5 had exactly opposite functions in EC and LC. Conclusion: SCARA5 was related to the development and occurrence of ESCC. Our findings suggested that it was a potentially diagnostic individualized therapeutic target for ESCC in the future and that its application could possibly be combined with that of upstream THSD7A gene.
