The tumor microenvironment (TME) within mucosal neoplastic tissue in oral cancer (ORCA) is greatly influenced by tumor-infiltrating lymphocytes (TILs). Here, a clustering method was performed using CIBERSORT profiles of ORCA data that were filtered from the publicly accessible data of patients with head and neck cancer in The Cancer Genome Atlas (TCGA) using hierarchical clustering where patients were regrouped into binary risk groups based on the clustering-measuring scores and survival patterns associated with individual groups. Based on this analysis, clinically reasonable differences were identified in 16 out of 22 TIL fractions between groups. A deep neural network classifier was trained using the TIL fraction patterns. This internally validated classifier was used on another individual ORCA dataset from the International Cancer Genome Consortium data portal, and patient survival patterns were precisely predicted. Seven common differentially expressed genes between the two risk groups were obtained. This new approach confirms the importance of TILs in the TME and provides a direction for the use of a novel deep-learning approach for cancer prognosis.

Cho SH, et al. Ann Hepatobiliary Pancreat Surg. 2018 Nov;22(4):305-309. https://doi.org/10.14701/ahbps.2018.22.4.305

Background: Although the prevention of extracorporeal membrane oxygenation (ECMO) catheter-related infection is crucial, scientific evidence regarding best practices are still lacking. Methods: We conducted an uncontrolled before-and-after study to test whether the introduction of disinfection with 2% chlorhexidine gluconate (CHG) and 70% isopropyl alcohol (IPA) of the exposed circuits and hub in patients treated with ECMO would affect the rate of blood stream infection (BSI) and microbial colonization of the ECMO catheter. We compared the microbiological and clinical data before and after the intervention. Results: A total of 1740 ECMO catheter days in 192 patients were studied. These were divided into 855 ECMO catheter days in 96 patients before and 885 ECMO catheter days in 96 patients during the intervention. The rates of BSI were significantly decreased during the intervention period at 11.7/1000 ECMO catheter days before vs. 2.3/1000 ECMO catheter days during (difference 9.4, 95% confidence interval (CI) 1.5–17.3, p = 0.019). Furthermore, the colonization of the ECMO catheter was similarly significantly reduced during the intervention period at 10.5/1000 ECMO catheter days before vs. 2.3/1000 ECMO catheter days during intervention (difference 8.3, 95% CI 0.7–15.8, p = 0.032). Hospital mortality (41.7% vs. 24%, p = 0.009) and sepsis-related death (17.7% vs. 6.3%, p = 0.014) were also significantly decreased during intervention. Conclusion: Extensive disinfection of exposed ECMO circuits and hub with 2% CHG/IPA was associated with a reduction in both BSI and microbial colonization of ECMO catheters. A further randomized controlled study is required to verify these results. Trial registration: KCT 0004431

Transmembrane p24 trafficking protein 3 (TMED3) is a metastatic suppressor in colon cancer and hepatocellular carcinoma. However, its function in the progression of clear cell renal cell carcinoma (ccRCC) is unknown. Here, we report that TMED3 could be a new prognostic marker for ccRCC. Patient data were extracted from cohorts in the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC). Differential expression of TMED3 was observed between the low stage (Stage I and II) and high stage (Stage III and IV) patients in the TCGA and ICGC cohorts and between the low grade (Grade I and II) and high grade (Grade III and IV) patients in the TCGA cohort. Further, we evaluated TMED3 expression as a prognostic gene using Kaplan-Meier survival analysis, multivariate analysis, the time-dependent area under the curve (AUC) of Uno’s C-index, and the AUC of the receiver operating characteristics at 5 years. The Kaplan-Meier analysis revealed that TMED3 overexpression was associated with poor prognosis for ccRCC patients. Analysis of the C-indices and area under the receiver operating characteristic curve further supported this. Multivariate analysis confirmed the prognostic significance of TMED3 expression levels (P = 0.005 and 0.006 for TCGA and ICGC, respectively). Taken together, these findings demonstrate that TMED3 is a potential prognostic factor for ccRCC.