No abstract

PurposeThe aim of this study was to perform a systematic review and meta-analysis to evaluate the value of the Glasgow prognostic score (GPS) or modified Glasgow prognostic score (mGPS) in patients with colorectal cancer (CRC).MethodsA comprehensive medical literature search was performed using the online databases PubMed, Embase, Web of Science, and the Cochrane Library. After extracting basic characteristics and prognostic data from the included studies, overall survival (OS) and cancer-specific survival (CSS) were pooled as primary outcomes. Subgroup analyses were performed according to therapeutic strategies, models, cutoff values, regions, tumor, node, metastasis stages, sample size, and ages.ResultsForty-three independent cohorts from 41 studies with 9,839 CRC patients were included in the present study. Correlation between GPS or mGPS and OS was analyzed in 32 cohorts of 7,714 patients, and 23 independent cohorts of 5,375 patients focused on the correlation between GPS or mGPS and CSS. The overall outcomes showed that patients with elevated GPS or mGPS were associated with poor OS (HR: 2.20, 95% CI: 1.88–2.57, P<0.001). Elevated GPS or mGPS also resulted in worse CSS (HR: 1.86, 95% CI: 1.59–2.17, P<0.001). The results of the subgroup analyses confirmed the overall outcomes.ConclusionGPS or mGPS is an accurate prognostic predictor in patients with CRC. Patients with elevated pretreatment GPS or mGPS have a poor prognosis. Subgroup analyses confirmed the overall outcomes. Pretreatment GPS is a useful biomarker in the management of CRC.

Image textures, as a kind of local variations, provide important information for human visual system. Many image textures, especially the small-scale or stochastic textures are rich in high-frequency variations, and are difficult to be preserved. Current state-ofthe-art denoising algorithms typically adopt a nonlocal approach consisting of image patch grouping and group-wise denoising filtering. To achieve a better image denoising while preserving the variations in texture, we first adaptively group high correlated image patches with the same kinds of texture elements (texels) via an adaptive clustering method. This adaptive clustering method is applied in an over-clustering-and-iterative-merging approach, where its noise robustness is improved with a custom merging threshold relating to the noise level and cluster size. For texture-preserving denoising of each cluster, considering that the variations in texture are captured and wrapped in not only the between-dimension energy variations but also the within-dimension variations of PCA transform coefficients, we further propose a PCA-transform-domain variation adaptive filtering method to preserve the local variations in textures. Experiments on natural images show the superiority of the proposed transform-domain variation adaptive filtering to traditional PCA-based hard or soft threshold filtering. As a whole, the proposed denoising method achieves a favorable texture preserving performance both quantitatively and visually, especially for stochastic textures, which is further verified in camera raw image denoising.

Background Circular RNAs (circRNAs) have emerged as a special subset of endogenous RNAs that are implicated in tumorigenesis and cancer progression. Herein we aim to carry out a meta-analysis to evaluate the clinicopathologic, diagnostic and prognostic significance of circRNA expression in colorectal cancer (CRC). Methods A systematic search of online databases was performed for original articles published in English, which investigated the diagnostic accuracy, prognostic utility, and clinicopathologic association of circRNA(s) in CRC. Data were strictly extracted and study bias was judged using the Quality Assessment for Studies of Diagnostic Accuracy II (QUADAS II) and Newcastle-Ottawa Scale (NOS) checklists. Results A total of 13 studies, involving 1430 patients with CRC, were included in the meta-analysis. The clinicopathologic study showed that abnormally expressed circRNAs were correlated with tumor diameter (P = 0.0350), differentiation (P = 0.0038), lymphatic metastasis (P = 0.0119), distant metastasis (P < 0.0001), TNM stage (P = 0.0002), and depth of invasion (P = 0.001) in patients with CRC. The summary area under the curve (AUC) of circRNA for the discriminative efficacy between patients with and without CRC was estimated to be 0.79, corresponding to a weighted sensitivity of 0.77 [95% confidence interval (CI): 0.74–0.79], specificity of 0.67 (95%CI: 0.64–0.70), and diagnostic odds ratio (DOR) of 7.52 (95%CI: 4.66–12.12). Survival analysis showed that highly expressed circRNAs were correlated with significantly worse overall survival (OS) [hazard ratio (HR) = 2.66, 95%CI: 2.03–3.50, P = 0.000; X2 = 4.34, P = 0.740, I2 = 0.0%], whereas lower expression of circRNAs was associated with prolonged OS (weighted HR = 0.30, 95%CI: 0.17–0.53, P = 0.000; X2 = 1.34, P = 0.909, I2 = 0.0%). Stratified analysis in circRNA expression status, and test matrix also showed robust results. Conclusion Abnormally expressed circRNAs may be auxiliary biomarkers facilitating CRC diagnosis, and promising prognostic biomarkers in predicting the survival of CRC patients.

HtrA1, as serine protease lower expressed in various human solid tumors, can down-regulate cell growth and proliferation. In this study, we focus on whether overexpressed HtrA1 can inhibit the growth of gastric cancer in vitro. This study found the HtrA1 is lower expressed in gastric cancer tissue than in normal gastric tissue. When HtrA1 is highly expressing with recombinant plasmid in gastric cancer cell lines SGC-7901 and AGS, it weakened cell proliferation, invasion, and migration in vitro. These data suggested that HtrA1 as an inhibitor in gastric cancer cells resulted in anti-proliferation, reduced invasion, decreased migration, and suppressed growth and may be an effective molecular targets on gastric cancer treatment.