Background: Melanoma is a cancer of the skin with potential to spread to other organs and is responsible for most deaths due to skin cancer. It is imperative to identify immune biomarkers for early melanoma diagnosis and treatment. Results: 63 immune-related genes of the total 1039 unique IRGs retrieved were associated with overall survival of melanoma. A multi-IRGs classifier constructed using eight IRGs showed a powerful predictive ability. The classifier had better predictive power compared with the current clinical data. GSEA analysis showed multiple signaling differences between high and low risk score group. Furthermore, biomarker was associated with multiple immune cells and immune infiltration in tumor microenvironment. Conclusions: The immune-related genes prognosis biomarker is an effective potential prognostic classifier in the immunotherapies and surveillance of melanoma. Methods: Melanoma samples of genes were retrieved from TCGA and GEO databases while the immunerelated genes (IRGs) were retrieved from the ImmPort database. WGCNA, Cox regression analysis and LASSO analysis were used to classify melanoma prognosis. ESTIMATE and CIBERSORT algorithms were used to explore the relationship between risk score and tumor immune microenvironment. GSEA analysis was performed to explore the biological signaling pathway.

Background Gastric cancer remains one of the major causes for tumor‐related deaths worldwide. Our study aimed to provide an understanding of primary gastric cancer and prompt its clinical diagnosis and treatment. Methods We integrated the expression profiles and overall survival information of primary gastric cancer in TCGA and GEO database and estimated the stromal score of each sample by the estimate R package. Stromal score and clinicopathologic characteristics associated with overall survival were analyzed by using Cox regression and the Kaplan‐Meier method. Gene set enrichment analysis (GSEA) and KEGG analysis were performed to explore the potential molecular mechanism in TCGA dataset. The relationship between immunotherapy‐associated markers or immune cell types and stromal score was explored by using Pearson correlation analysis. Results A total of 796 samples were collected for the analysis. Patients with stromal score‐high showed poor overall survival ( P < .01, HR: 1.407, 95% CI: 1.144‐1.731) and identified as an independent prognostic factor. KEGG analysis revealed that stromal score actively involved in diverse tumor‐associated pathways. GSEA analysis also revealed stromal score associated with diverse immune‐related biological processes. Furthermore, stromal score was related with immunotherapy‐associated markers and multiple immune cells. Conclusion Our results showed that stromal score could serve as a potential prognostic biomarker in primary gastric cancer and play an important role in the recognition, surveillance, and prognosis of gastric cancer.

Background and aim:The increased mortality rate and other poor prognosis make malnutrition a serious issue for adult critically ill patients in intensive care unit care. This study was to compare outcomes between combined parenteral and enteral nutrition and enteral nutrition alone for adult critically ill patients.Materials and methods:The PubMed (June 30st, 2018), EMBASE (June 30st, 2018), and Cochrane library databases (June 30st, 2018) were searched systematically. Randomized controlled trials (RCTs) of comparing combined PN and EN with EN alone were eligible. Relative risks (RRs), mean differences (MDs), and 95% confidence intervals (CIs) were calculated for dichotomous and continuous outcomes.Results:Eight RCTs involving 5360 patients met the inclusion criteria. Compared with combined PN and EN, fewer respiratory infections (RR, 1.13 [95% CI 1.01–1.25]) and shorter length of days at hospital (MD, 1.83 [95% CI 1.05–2.62]) were observed in EN alone group. And no significant differences were found on hospital mortality (RR, 0.91 [95% CI 0.74–1.12]), length of days in ICU (MD, −0.23 [95% CI −1.79 to 1.32]), duration of ventilatory support (MD, −1.10 [95% CI −3.15 to 0.94]), albumin (MD, −0.04 [95% CI, −0.12 to 0.21]), or prealbumin (MD, −0.77 [95% CI −0.22 to 1.75]) between theses 2 groups.Conclusion:Receiving EN alone decreased the respiratory infections and length of days at hospital for critically ill patients. Combined PN and EN did not add up the potential risk from PN and EN on hospital mortality, length of days in ICU, duration of ventilatory support, albumin, and prealbumin.

BackgroundPeriprosthetic bone loss following total hip arthroplasty (THA) was a well-known phenomenon. This systematic review was to assess the effectiveness of bisphosphonates (BPs) for decreasing periprosthetic bone resorption.MethodsThe MEDLINE, EMBASE, and Cochrane Library databases were searched up to March 2018. Randomized controlled trials compared the effects between administrating BPs and placebo or no medication were eligible; the target participants were patients who underwent THA. Mean differences (MD) and 95% confidence interval (95% CI) were calculated by using the random-effects models. Statistical analyses were performed by RevMan 5.3 software.ResultsFourteen trials involving 620 patients underwent THA were retrieved. BPs significantly prevented the loss of periprosthetic bone mineral density at 1 year (MD, 0.06 [95% CI, 0.03 to 0.08], p < 0.001), between 2 and 4 years (MD, 0.04 [95% CI, 0.01 to 0.07], p = 0.02), and more than 5 years after THA (MD, 0.08 [95% CI, 0.06 to 0.11], p < 0.001). Both serum bone alkaline phosphatase (MD, − 7.28 [95% CI, − 9.81 to − 4.75], p < 0.001) and urinary N-telopeptide of type I collagen (MD, − 24.37 [95% CI, − 36.37 to − 12.37], p < 0.001) in BP group were significantly lower. Subgroup analyses showed that the third-generation BPs were more effective in decreasing periprosthetic bone loss than the first and second generation within 1 year after THA (p = 0.001).ConclusionBPs were beneficial to decreasing periprosthetic bone loss. The third-generation BPs showed significantly efficacy for patients in short-term observation.

Melanoma is a skin cancer with great metastatic potential, which is responsible for the major deaths in skin cancer. Although the prognosis of melanoma patients has been improved with the comprehensive treatment, for patients with metastasis, the complexity and heterogeneity of diffuse diseases make prognosis prediction and systematic treatment difficult and ineffective. Therefore, we established a novel personalized immune-related gene pairs index (IRGPI) to predict the prognosis of patients with metastatic melanoma, which was conducive to provide new insights into clinical decision-making and prognostic monitoring for metastatic melanoma. Through complex analysis and filtering, we identified 24 immune-related gene pairs to build the model and obtained the optimal cut-off value from receiver operating characteristic curves, which divided the patients into high and low immune-risk groups. Meantime, the Kaplan–Meier analysis, Cox regression analysis and subgroup analysis showed that IRGPI had excellent prognostic value. Furthermore, IRGPI was shown that was closely associated with immune system in the subsequent tumor microenvironment analysis and gene set enrichment analysis. In addition, we broken through the data processing limitations of traditional researches in different platforms through the application of gene pairs, which would provide great credibility for our model. We believe that our research would provide a new perspective for clinical decision-making and prognostic monitoring in metastatic melanoma.

Background Papillary thyroid cancer (PTC) is the most common type of thyroid cancer. However, due to the lack of reliable prognostic biomarkers for PTC, overtreatment has been on the rise. Therefore, our research aims to identify new and promising prognostic biomarkers and provide fresh perspectives for clinical decision making. Methods The RNA‐seq data and clinical data of PTC samples were obtained from The Cancer Genome Atlas data portal. GSE64912 and GSE83520 datasets were downloaded through the GEOquery R package. The difference in the expression of oxoglutarate dehydrogenase like ( OGDHL ) between PTC and normal tissues was explored by the Wilcoxon test. Kaplan–Meier (KM) and Cox regression analyses were used to further explore the prognostic value of OGDHL . The tumor microenvironments of PTC patients were explored based on ssGSEA and Tumor Immune Estimation Resource online database. Gene Set Enrichment Analysis (GSEA) was performed to explore the biological processes associated with OGDHL . Results The expression level of OGDHL in PTC was significantly altered compared to that in normal tissues ( p < 0.05). Various biological processes associated with OGDHL were also explored through GSEA. KM analysis suggested that the low‐ OGDHL group had a better overall survival [OS, p = 3.49e‐03, hazard ratio (HR) = 4.567]. The receiver operating characteristic curve also indicated the favorable prognostic potential of OGDHL . Moreover, OGDHL was proved to be an independent prognostic indicator in Cox analysis ( p = 1.33e‐02, HR = 0.152). In the analysis of the tumor microenvironment, the low‐ OGDHL group showed a lower immune score and stromal score, while tumor purity was higher. The expression of OGDHL was also closely correlated with the infiltration of immune cells. Conclusion Our study elucidated the influence of OGDHL on the prognosis of PTC and demonstrated its potential as a novel biomarker, which would provide new insights into the prognosis monitoring and clinical decision making in PTC patients.

Background: The epidermal growth factor receptor (EGFR) mutation status related to the treatment approach for advanced non-small cell lung cancer (NSCLC) patients. This study aimed to evaluate the diagnostic accuracy of peripheral blood circulating tumor DNA (ctDNA) in EGFR mutated advanced NSCLC patients. Method: The related database was systematically searched with keywords until January 19, 2020. Studies contained the histopathological and cytological advanced NSCLC samples were included, and the diagnostic data were recorded for calculating sensitivity and specificity. I 2 statistics were used for detecting heterogeneity across studies, and the meta-regression was performed to seek the source of heterogeneity. Result: A total of 32 studies with 4527 advanced NSCLC patients were included in our meta-analysis. Among them, 87% of the patients were diagnosed as stage IV. The pooled sensitivity of peripheral blood ctDNA was 0.70 (95% CI: 0.63–0.75, I 2 = 81.76) and the pooled specificity was 0.98 (95% CI: 0.96–0.99, I 2 = 88.33). The meta-regression showed that the prospective study design and the ARMS detection method were the main source of heterogeneity for sensitivity ( P < .05), and the publication country (Asia or non-Asia) was the main source of heterogeneity for specificity ( P < .01). Conclusion: ctDNA biopsy has high specificity and diagnostic accuracy in detection of EGFR mutation in advanced NSCLC patients. When the ctDNA gene test result is negative, we should fully consider the risk of missed diagnosis, and further tissue biopsy is still needed to undertake.

Nephroblastoma, also known as Wilms' tumor (WT), is the most common renal tumor that occurs in children. Although the efficacy of treatment has been significantly improved by a series of comprehensive treatments, some patients still have poor prognosis. Myelin and lymphocyte (MAL) protein, a highly hydrophobic integrated membrane‐bound protein, has been implicated in many tumors and is also closely linked to kidney development. However, the relationship between MAL and WT has not yet been elucidated. Therefore, we attempted to evaluate the feasibility of MAL as a promising prognosis factor for WT. The differential expression of MAL was investigated using TARGET database and was verified using the Gene Expression Omnibus database and real‐time quantitative PCR. The prognostic ability of MAL was determined using Kaplan–Meier and Cox regression analyses. Pearson correlation analysis was applied to explore the relationship between MAL expression and methylation sites. The ESTIMATE and CIBERSORT algorithms showed that MAL expression was associated with the WT tumor microenvironment. Gene Set Enrichment Analysis (GSEA) indicated that multiple signaling pathways closely associated with tumorigenesis were differentially enriched between the high‐ and low‐MAL groups. In conclusion, our study comprehensively explored the potential of MAL as a prognosis factor for WT. Meanwhile, we also demonstrated that MAL, as a prognostic factor for WT, may be closely related to the tumor microenvironment.