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The applicability of the nomogram was internally and independently validated. Results The predictors included the Eastern Cooperative Oncology Group Performance Status (ECOG), presence of an active cancer (AC), central venous catheter (CVC), and D-dimer levels. These risk factors are shown on the nomogram and verified. The nomogram demonstrated good discrimination and fine calibration with an AUROC of 0.875 (0.832 in internal validation and 0.807 in independent validation). The DCA revealed that the nomogram had a high clinical application value. Conclusions We propose the nomogram for predicting TE in patients with GC receiving chemotherapy, which can help in making timely personalized clinical decisions for different risk populations.Pancreatic cancer (PC) is a highly malignant tumor in the digestive system. Both long noncoding RNAs (lncRNAs) and autophagy play vital roles in the development and progress of PC. Here, we constructed a prognostic risk score system based on the expression profile of autophagy-associated lncRNAs for prognostic prediction in PC patients. Firstly, we extracted the expression profile of lncRNA and clinical information from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. The autophagy-associated genes were from The Human Autophagy Database. Through Cox regression and survival analysis, we screened out seven autophagy-associated lncRNAs and built the risk score system in which the patients with PC were distinguished into high- and low-risk groups in both training and validation datasets. PCA plot displayed distinct discrimination, and risk score system displayed independently predictive value for PC patient survival time by multivariate Cox regression. Then, we built a lncRNA and mRNA co-expression network via Cytoscape and Sankey diagram. Finally, we analyzed the function of lncRNAs in high- and low-risk groups by gene set enrichment analysis (GSEA). The results showed that autophagy and metabolism might make significant effects on PC patients of low-risk groups. Taken together, our study provides a new insight to understand the role of autophagy-associated lncRNAs and finds novel therapeutic and prognostic targets in PC.Colorectal cancer (CRC) is the third leading cause of cancer-related death worldwide in both sexes. Current therapies include surgery, chemotherapy, and targeted therapy; however, prolonged exposure to chemical agents induces toxicity in patients and drug resistance. So, we implemented a therapeutic strategy based on the combination of doxorubicin, metformin, and sodium oxamate called triple therapy (Tt). We found that Tt significantly reduced proliferation by inhibiting the mTOR/AKT pathway and promoted apoptosis and autophagy in CRC derived cells compared with doxorubicin. Several autophagy genes were assessed by western blot; ULK1, ATG4, and LC3 II were overexpressed by Tt. Interestingly, ULK1 was the only one autophagy-related protein gradually overexpressed during Tt administration. Thus, we assumed that there was a post-transcriptional mechanism mediating by microRNAs that regulate UKL1 expression during autophagy activation. Through bioinformatics approaches, we ascertained that ULK1 could be targeted by mir-26a, which is overexpressed in advanced stages of CRC. In vitro experiments revealed that overexpression of mir-26a decreased significantly ULK1, mRNA, and protein expression. Contrariwise, the Tt recovered ULK1 expression by mir-26a decrease. Due to triple therapy repressed mir-26a expression, we hypothesized this drug combination could be involved in mir-26a transcription regulation. Consequently, we analyzed the mir-26a promoter sequence and found two HIF-1α transcription factor recognition sites. We developed two different HIF-1α stabilization models. Both showed mir-26a overexpression and ULK1 reduction in hypoxic conditions. Immunoprecipitation experiments were performed and HIF-1α enrichment was observed in mir-26a promoter. Surprisingly, Tt diminished HIF-1α detection and restored ULK1 mRNA expression. These results reveal an important regulation mechanism controlled by the signaling that activates HIF-1α and that in turn regulates mir-26a transcription.

This study aimed to compare the long-term outcomes of liver transplantation (LT) and liver resection (LR) among patients with stage I and II hepatocellular carcinoma (HCC).

SEER 18 registry from 2004 to 2015 was retrieved for this study. We included 1,765 and 1,746 cases with stage I-II (AJCC, 7

) HCC in the multivariable analyses and instrumental variable (IV) analyses, respectively. Propensity score matching (PSM) was further carried out to ensure comparability. Propensity score to receive LT was adjusted by stabilized inverse probability of treatment weighting (IPTW) and standardized mortality ratio weighting (SMRW) methods. In addition, IV analysis was performed to adjust both measured and unmeasured confounding factors.

We identified 1,000 (56.7%) and 765 (43.3%) patients treated with LR and LT, respectively. Halofuginone research buy In the multivariable adjusted cohort, after adjusting potential confounders, patients undergoing LT offered significant prognostic advantages over LR in overall survival (OS, P < 0.001) ante was to increase in the future, average long-term survival may also increase. However, for some special populations such as the elderly patients, owing to the similar outcomes between LT and LR, the selection of LT should be cautious.

LT provided a survival benefit for cases with stage I-II HCC. These results indicated that if LT rate was to increase in the future, average long-term survival may also increase. However, for some special populations such as the elderly patients, owing to the similar outcomes between LT and LR, the selection of LT should be cautious.

To evaluate fitting quality and repeatability of four mathematical models for diffusion weighted imaging (DWI) during tumor progression in mouse xenograft model of prostate cancer.

Human prostate cancer cells (PC-3) were implanted subcutaneously in right hind limbs of 11 immunodeficient mice. Tumor growth was followed by weekly DWI examinations using a 7T MR scanner. Additional DWI examination was performed after repositioning following the fourth DWI examination to evaluate short term repeatability. DWI was performed using 15 and 12 b-values in the ranges of 0-500 and 0-2000 s/mm

, respectively. Corrected Akaike information criteria and F-ratio were used to evaluate fitting quality of each model (mono-exponential, stretched exponential, kurtosis, and bi-exponential).

Significant changes were observed in DWI data during the tumor growth, indicated by ADC

, ADC

, and ADC

. Similar results were obtained using low as well as high b-values. No marked changes in model preference were present between the weeks 1-4.