Sclerosing encapsulating peritonitis presenting with paroxysmal abdominal pain and strangulated mechanical bowel obstruction: A case report.

RATIONALE: Sclerosing encapsulated peritonitis (SEP) is a rare chronic peritoneal inflammation with unknown etiology, and is also known as abdominal cocoon. This occurs when the intestinal annulus is enveloped in the peritoneal cavity, resulting in intestinal obstruction. Its preoperative diagnosis and treatment strategy remains a challenge. PATIENT CONCERNS: The study reports a 53-year-old male, who presented with a 4-day history of paroxysmal abdominal pain, without the adverse reaction of nausea, vomiting, or diarrhea. DIAGNOSIS: The accurate diagnosis of SEP was made after the emergency diagnostic laparoscopy. INTERVENTIONS: The laparoscopic exploration revealed that the small intestine was wrapped by a layer of peritoneum. Then, the abdominal fibrous membrane was removed surgically, and adhesiolysis were performed. The patient recovered well, and gradually recovered by the 10th post-operative day. OUTCOMES: The patient was discharged uneventfully after 10 days, and the patient recovered well. After the 12-month follow-up, no symptoms of recurrence or complications were observed. LESSONS: The preoperative diagnosis of SEP remains difficult, and the onset of SEP has exhibited a younger trend. The diagnosis of SEP should remain on the list of differential diagnosis for paroxysmal abdominal pain. single-photon emission computed tomography/computed tomography and laparoscopic exploration have been proven to be helpful for establishing the diagnosis. In the early stage of intestinal obstruction caused by SEP, surgical intervention was immediately carried out in emergency department, and the patient recovered well after the operation. The present study also presents a review of the literature for other cases of SEP. The external evidence was helpful in making clinical decisions for patient care.

Prognostic value of a novel glycolysis-related gene expression signature for gastrointestinal cancer in the Asian population.

BACKGROUND: Globally, gastrointestinal (GI) cancer is one of the most prevalent malignant tumors. However, studies have not established glycolysis-related gene signatures that can be used to construct accurate prognostic models for GI cancers in the Asian population. Herein, we aimed at establishing a novel glycolysis-related gene expression signature to predict the prognosis of GI cancers. METHODS: First, we evaluated the mRNA expression profiles and the corresponding clinical data of 296 Asian GI cancer patients in The Cancer Genome Atlas (TCGA) database (TCGA-LIHC, TCGA-STAD, TCGA-ESCA, TCGA-PAAD, TCGA-COAD, TCGA-CHOL and TCGA-READ). Differentially expressed mRNAs between GI tumors and normal tissues were investigated. Gene Set Enrichment Analysis (GSEA) was performed to identify glycolysis-related genes. Then, univariate, LASSO regression and multivariate Cox regression analyses were performed to establish a key prognostic glycolysis-related gene expression signature. The Kaplan-Meier and receiver operating characteristic (ROC) curves were used to evaluate the efficiency and accuracy of survival prediction. Finally, a risk score to predict the prognosis of GI cancers was calculated and validated using the TCGA data sets. Furthermore, this risk score was verified in two Gene Expression Omnibus (GEO) data sets (GSE116174 and GSE84433) and in 28 pairs of tissue samples. RESULTS: Prognosis-related genes (NUP85, HAX1, GNPDA1, HDLBP and GPD1) among the differentially expressed glycolysis-related genes were screened and identified. The five-gene expression signature was used to assign patients into high- and low-risk groups (p < 0.05) and it showed a satisfactory prognostic value for overall survival (OS, p = 6.383 × 10-6). The ROC curve analysis revealed that this model has a high sensitivity and specificity (0.757 at 5 years). Besides, stratification analysis showed that the prognostic value of the five-gene signature was independent of other clinical characteristics, and it could markedly discriminate between GI tumor tissues and normal tissues. Finally, the expression levels of the five prognosis-related genes in the clinical tissue samples were consistent with the results from the TCGA data sets. CONCLUSIONS: Based on the five glycolysis-related genes (NUP85, HAX1, GNPDA1, HDLBP and GPD1), and in combination with clinical characteristics, this model can independently predict the OS of GI cancers in Asian patients.