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Background: Platelet proteins may be associated with Alzheimer’s disease (AD) pathology. Objective: To investigate the relationship between platelet proteins and cerebrospinal fluid (CSF) biomarkers of AD and cognition in individuals with memory decline to identify effective screening methods for detecting the early stages of the disease. Methods: We classified 68 participants with subjective memory decline according to the ATN framework determined by CSF amyloid-β (A), CSF p-tau (T), and t-tau (N). All participants underwent Mini-Mental State Examination (MMSE) and platelet-related protein content testing. Results: Eighteen participants had normal AD biomarkers (NCs), 24 subjects had non-AD pathologic changes (non-AD), and 26 subjects fell within the Alzheimer’s continuum (AD). The platelet amyloid-β protein precursor (AβPP) ratio in the AD group was significantly lower than in the non-AD and NCs groups, and positively correlated with MMSE scores and CSF amyloid-β42 level, which could affect MMSE scores through CSF amyloid-β42. Levels of platelet phosphorylated-tau 231 and ser396/404 phosphorylated tau were elevated in both AD and non-AD compared to NCs. Additionally, the receiver operating characteristic analysis demonstrated that the platelet AβPP ratio was a sensitive identifier for differentiating the AD from NCs (AUC = 0.846) and non-AD (AUC = 0.768). And ser396/404 phosphorylated tau could distinguish AD from NCs. Conclusion: Our study was the first to find an association between platelet AβPP ratio and CSF biomarkers of AD, which contribute to the understanding of the peripheral changes in AD. These findings may help to discover potential feasible and effective screening tools for AD.

Background. Lung squamous cell carcinoma (LUSC) is a subtype of highly malignant lung cancer with poor prognosis, for which smoking is the main risk factor. However, the underlying genetic and molecular mechanisms of smoking-related LUSC remain largely unknown. Methods. We mined existing LUSC-related mRNA, miRNA, and lncRNA transcriptome data and corresponding clinical data from The Cancer Genome Atlas (TCGA) database and divided them into smoking and nonsmoking groups, followed by differential expression analysis. Functional enrichment analysis of the unique differentially expressed mRNAs of the two groups was performed using the DAVID database. Subsequently, the lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) network of LUSC in smoking and nonsmoking groups was constructed. Finally, survival analyses were performed to determine the effects of differentially expressed lncRNAs/mRNAs/miRNAs that were involved in the ceRNA network on overall survival and to discover the hub genes. Results. A total of 1696 lncRNAs, 125 miRNAs, and 3246 mRNAs and 1784 lncRNAs, 96 miRNAs, and 3229 mRNAs with differentially expressed profiles were identified in the smoking and nonsmoking groups, respectively. The ceRNA network and survival analysis revealed four lncRNAs (LINC00466, DLX6-AS1, LINC00261, and AGBL1), one miRNA (hsa-mir-210), and two mRNAs (CITED2 and ENPP4), with the potential as biomarkers for smoking-related LUSC diagnosis and prognosis. Conclusion. Taken together, our research has identified the differences in the ceRNA regulatory networks between smoking and nonsmoking LUSC, which could lay the foundation for future clinical research.

Background With the development in research, the importance of microRNAs (miRNAs) in the occurrence and metastasis, and prognosis of lung squamous cell carcinoma (LUSC) have received extensive attention. This study aims to identify new biomarkers and pivotal genes associated with LUSC prognosis through bioinformatics. Materials and methods We downloaded miRNA and messenger RNA samples related to LUSC from The Cancer Genome Atlas (TCGA) database. Following initial data screening and preprocessing, we utilized the R platform and a range of analysis tools (miRDB, TargetScanHuman7.2, DAVID, and Cytoscape_v3.5.1) to analyze the TCGA data and identify highly specific and sensitive biomarkers. Results We finally identified 12 miRNAs and six central genes closely related to the overall survival of patients with LUSC. We found that high expression of 7 miRNAs (miR-301b, miR-383, miR-512, miR-515, miR-525, miR-577, and miR-5682) and low expression of five miRNAs (miR-448, miR-486, miR-4732,miR-4732, miR-516, and miR-1911) can significantly improve the overall survival rate of patients with LUSC. The six central genes DLGAP5, CENPA, CHEK1, LRRK2, CALB1, and TOP2A are directly or indirectly involved in the formation and metastasis of LUSC and could, therefore, be considered as target genes for drug therapy. Conclusion With the development in research, the importance of miRNAs in the occurrence and metastasis and prognosis of LUSC have received extensive attention. This study aims to identify new biomarkers and pivotal genes associated with LUSC prognosis through bioinformatics.

Purpose Breast cancer (BC) remains a serious health threat for women due to its high incidence and the trend of rejuvenation. Accumulating evidence has highlighted that microRNAs (miRNAs) and messenger RNAs (mRNAs) could play important roles in various biological processes involved in the pathogenesis of BC. The present study aimed to identify potential prognostic biomarkers associated with BC. Methods Here, original gene expression profiles of patients with BC was downloaded from The Cancer Genome Atlas (TCGA) database. TargetScan, miRDB, and miRTarBase databases were used to predict the target genes of prognostic-related differentially expressed miRNAs (DEMs). Subsequently, functional enrichment analysis and topological analysis were performed on the overlaps of target genes and differentially expressed mRNAs (DEGs), and Kaplan-Meier analysis was used to predict prognosis-related target genes to identify prognostic biomarkers. Results A total of 218 DEMs and 2222 DEGs were extracted in which eight miRNAs were associated with prognosis, and 278 target DEGs were screened out incorporated into functional enrichment analysis and protein-protein interaction network visualization studies. Additionally, five hub genes (CXCL12, IGF1, LEF1, MMP1, and RACGAP1) were observed as potential biomarkers for BC prognosis through survival analysis. Conclusion We performed a distinctive correlation analysis of miRNA-mRNA in BC patients, and identified eight miRNAs and five hub genes may be effective biomarkers for the prognosis of BC patients.

Previous studies on long noncoding RNA (lncRNA) have made breakthroughs in the treatment of several tumors, and these findings have brought attention to the lncRNA signature of breast cancer. Increased understanding of genomic architecture and achievement of innovative therapeutic strategies has prompted creation of a novel oncological model for the treatment of solid cancers. In this study, we systematically analyzed the transcriptome of breast cancer tissues to gain more in-depth knowledge of tumor biology. Gene coexpression relationships were studied in 206 samples from The Cancer Genome Atlas database, and nine coexpression modules were identified. After screening and analysis, we identified four important prognosis-related lncRNAs (HOTAIR, SNHG16, HCP5, and TINCR), and constructed a prognostic model, one (HCP5) of which has not previously been identified in the context of breast cancer. Importantly, an understanding of prognosis facilitates precise disease risk assessment and advances the selection of strategies for risk-adaptive management. These findings broaden the landscape of carcinogenic lncRNAs in breast cancer, providing insights into the biological significance and clinical application of lncRNAs in breast cancer.

Objective To explore whether the whole brain resting-state functional connectivity (rs-FC) could predict episodic memory performance in individuals with subjective cognitive decline and amnestic mild cognitive impairment . Method This study included 33 cognitive normal (CN), 26 subjective cognitive decline (SCD) and 27 amnestic mild cognitive impairment (aMCI) patients, and all the participants completed resting-state fMRI (rs-fMRI) scan and neuropsychological scale test data. Connectome-based predictive modeling (CPM) based on the rs-FC data was used to predict the auditory verbal learning test-delayed recall (AVLT-DR) scores, which measured episodic memory in individuals. Pearson correlation between each brain connection in the connectivity matrices and AVLT-DR scores was computed across the patients in predementia stages of Alzheimer’s disease (AD). The Pearson correlation coefficient values separated into a positive network and a negative network. Predictive networks were then defined and employed by calculating positive and negative network strengths. CPM with leave-one-out cross-validation (LOOCV) was conducted to train linear models to respectively relate positive and negative network strengths to AVLT-DR scores in the training set. During the testing procedure, each left-out testing subject's strengths of positive and negative network was normalized using the parameters acquired during training procedure, and then the trained models were used to predict the testing participant’s AVLT-DR score. Results The negative network predictive model tested LOOCV significantly predicted individual differences in episodic memory from rs-FC. Key nodes that brain regions contributed to the prediction model were mainly located in the prefrontal cortex, frontal cortex, parietal cortex and temporal lobe. Conclusion Our findings demonstrated that rs-FC among multiple neural systems could predict episodic memory at the individual level.

Yan Yao,1 Tingting Zhang,2 Lingyu Qi,2 Ruijuan Liu,3 Gongxi Liu,3 Jie Li,2 Changgang Sun3,4 1Clinical Medical Colleges, Weifang Medical University, Weifang, Shandong Province, People’s Republic of China; 2College of First Clinical Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong Province, People’s Republic of China; 3Department of Oncology, Weifang Traditional Chinese Hospital, Weifang, Shandong Province, People’s Republic of China; 4Innovative Institute of Chinese Medicine and Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, People’s Republic of ChinaCorrespondence: Changgang SunInnovative Institute of Chinese Medicine and Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, People’s Republic of ChinaTel +86 13583690699Email zhongliuyike@163.comBackground: Tumor microenvironment (TME) cells constitute a vital element of tumor tissues. Increasing evidence has shown that immune response in the microenvironment plays an active role in tumor invasion, metastasis, and recurrence, and is an important factor affecting tumor prognosis. Our study aimed to identify the gene signatures in lung adenocarcinoma (LUAD) microenvironment for prognosis and immunotherapy.Methods: In this study, we evaluated, for the first time, the stromal and immune scores of 594 patients from The Cancer Genome Atlas (TCGA) database with LUAD using the ESTIMATE algorithm. Three hundred and sixty-seven dysregulated immune-related genes were identified. Then, we performed functional enrichment analysis of these genes, and found the best gene model and construct the signature through univariate, Lasso and multivariate COX regression analysis. To assess the independently prognostic ability of the signature, the Kaplan–Meier survival analysis and Cox’s proportional hazards model were performed.Results: Functional enrichment analysis and protein–protein interaction networks showed that the immune-related genes mainly played a role in immune response, activation/proliferation of immune-related cells, and chemokine activity. A prognostic model involving 6 genes was constructed and the signature was identified as an independent prognostic factor and significantly associated with the overall survival (OS) of LUAD. The area under curve (AUC) of the receiver operating characteristic curve (ROC curve) for the 6 genes signature in predicting the 3-year survival rate was 0.708. Finally, four genes (FOXN4, KLHL4, FAM83F and CCR2) can be used as candidate prognostic biomarkers for LUAD.Conclusion: Our findings will help evaluate the prognosis of LUAD and provide new ideas for exploring the potential relationship between TME and LUAD treatment and prognosis.Keywords: lung adenocarcinoma, tumor microenvironment, ESTIMATE algorithm, immune-related gene, prognosis signatures

To determine the value of gadobenate dimeglumine (Gd-BOPTA)–enhanced biliary imaging from the hepatobiliary phase in predicting hepatic decompensation and insufficiency for patients with cirrhosis. This single-center retrospective study included 270 patients who underwent Gd-BOPTA-enhanced magnetic resonance imaging. The relative enhancement ratios of the biliary system (REB) and liver parenchyma (REL) in patients with normal liver function without underlying chronic liver disease and three groups of patients with Child-Pugh A, Child-Pugh B, and Child-Pugh C disease were measured. After a mean follow-up of 38.5 ± 22.5 months, prognostic factors were evaluated using the Cox proportional hazards regression model. Receiver operating characteristic (ROC) curve analyses were performed to assess the capacity of the REB and REL to predict the development of hepatic decompensation and insufficiency. During the follow-up period, nine of 79 patients with Child-Pugh A disease developed hepatic decompensation. The REB was a significant predictive factor (hazard ratio (HR) = 0.40 (0.19–0.84); p = 0.016), but the REL showed no association with hepatic decompensation. Moreover, the areas under the ROC curves (AUCs) were 0.83 and 0.52 for the REB and REL, respectively. Thirty-eight of 207 patients with cirrhosis developed hepatic insufficiency. The REB was a significant predictive factor (HR = 0.24 (0.13–0.46); p < 0.0001), but the REL did not show statistically significant association with hepatic insufficiency. The AUCs were 0.82 and 0.57 for the REB and REL, respectively. Gd-BOPTA-enhanced biliary imaging from the hepatobiliary phase was valuable in predicting hepatic decompensation and insufficiency for cirrhotic patients. • Gd-BOPTA-enhanced biliary imaging was a significant predictive factor for hepatic decompensation in patients with cirrhosis. • Gd-BOPTA-enhanced biliary imaging was a significant predictive factor for hepatic insufficiency in patients with cirrhosis. • Gd-BOPTA-enhanced biliary imaging showed superior predictive values for adverse clinical outcomes compared to liver parenchymal imaging at the hepatobiliary phase.

Lung adenocarcinoma (LUAD) is the leading cause of cancer-related death worldwide, and its underlying mechanism remains unclear. Accumulating evidence has highlighted that long non-coding RNA (lncRNA) acts as competitive endogenous RNA (ceRNA) and plays an important role in the occurrence and development of LUAD. Here, we comprehensively analyzed and provided an overview of the lncRNAs, miRNAs, and mRNAs associated with LUAD from The Cancer Genome Atlas (TCGA) database. Then, differentially expressed lncRNAs (DElncRNA), miRNAs (DEmiRNA), and mRNAs (DEmRNA) were used to construct a lncRNA–miRNA–mRNA regulatory network according to interaction information from miRcode, TargetScan, miRTarBase, and miRDB. Finally, the RNAs of the network were analyzed for survival and submitted for Cox regression analysis to construct prognostic indicators. A total of 1123 DElncRNAs, 95 DEmiRNAs, and 2296 DEmRNAs were identified (|log2FoldChange| (FC) > 2 and false discovery rate (FDR) or adjusted P value < 0.01). The ceRNA network was established based on this and included 102 lncRNAs, 19 miRNAs, and 33 mRNAs. The DEmRNAs in the ceRNA network were found to be enriched in various cancer-related biological processes and pathways. We detected 22 lncRNAs, 12 mRNAs, and 1 miRNA in the ceRNA network that were significantly associated with the overall survival of patients with LUAD (P < 0.05). We established three prognostic prediction models and calculated the area under the 1,3,5-year curve (AUC) values of lncRNA, mRNA, and miRNA, respectively. Among them, the prognostic index (PI) of lncRNA showed good predictive ability which was 0.737, 0.702 and 0.671 respectively, and eight lncRNAs can be used as candidate prognostic biomarkers for LUAD. In conclusion, our study provides a new perspective on the prognosis and diagnosis of LUAD on a genome-wide basis, and develops independent prognostic biomarkers for LUAD.

Recent studies have shown that long noncoding RNAs (lncRNA) HOX transcript antisense intergenic RNA (HOTAIR) polymorphisms are associated with cancer susceptibility. The greatest threat to women's health among a variety of cancers is breast cancer (BC), cervical cancer (CC), and ovarian cancer (OC), and the incidence of it is increasing. We performed a meta-analysis to clarify the relationship between lncRNA HOTAIR expression and BC, CC, and OC susceptibility. We thoroughly searched PubMed, Embase, and the Cochrane Library to obtain the relevant literature. We extracted data from case groups and control groups for each single-nucleotide polymorphism (SNP) (rs4759314, rs920778, rs189663, rs12826786, rs7958904, and rs874945) and compared the relationship between alleles, codominance models, dominant and invisible models and BC, CC, and OC susceptibility. Our study included 11 studies with a total of 5322 patients. There was a significant association between the rs4759314 polymorphism of HOTAIR and susceptibility to BC, CC, and OC (codominant model: AG/AA odds ratio [OR] = 1.13 [95% confidence intervals [CI], 1.00-1.29], GG/AA OR = 1.54 [95% CI, 1.06-2.23]; dominant model: GG + AG/AA OR = 1.16 [95% CI, 1.02-1.32]; and recessive model: GG/AA + AG OR = 1.51 [95% CI, 1.05-2.19]). The association between the expression of rs920778 and BC, CC, and OC susceptibility was not clear (alleles T/C: OR = 1.28 [95% CI, 0.87-1.89]; in codominant model: CT/CC OR = 1.10, [95% CI, 0.71-1.71], TT/CC OR = 1.29 [95% CI, 0.59-2.80]; dominant model: TC + TT/CC OR = 1.16, [95% CI, 0.73-1.86]; and recessive model: TT/TC + CC OR = 1.43, [95% CI, 0.83-2.47]). HOTAIR polymorphism rs1899663 was associated with BC, CC, and OC susceptibility to a certain extent, (alleles T/G OR = 0.90 [95% CI, 0.69-1.16]; in the codominant model: GT/GG OR = 0.81 [95% CI, 0.50-1.30], TT/GG OR = 1.04 [95% CI, 0.63-1.72]; dominant model: GT + TT/GG OR = 0.82 [95% CI, 0.52-1.29]; and recessive model: TT/GT + GG OR = 1.21 [95% CI, 0.76-1.94]). The rs12826786, rs7958904, and rs874945 polymorphisms were associated with a certain degree of BC, CC, and OC susceptibility, but they were not statistically significant. HOTAIR rs4759314 increased susceptibility to BC, CC, and OC in some patients; rs029778 and rs1899663 also increased susceptibility to some extent. SNPs rs12826786, rs7958904, and rs874945 did not correlate with an effect on patient susceptibility to BC, CC, and OC.

Based on the data analysis platform provided by Traditional Chinese Medicine inheritance Assistance system (V2.5), this paper analyzes the rule of prescribing drugs used by Professor Yongyan Wang for the treatment of apoplexy and deepens the understanding of his academic research on syndrome differentiation and treatment. Professor Wang’s medical records were summarized and sorted into the "Chinese Medicine inheritance Assistance system". Through the functions of "frequency statistics", "drug use mode", "rule analysis" and so on, the characteristics of professor Yongyan Wang's prescription for treating apoplexy were statistically analyzed. It is helpful to understand and inherit Professor Wang's academic thoughts by analyzing the data of professor Wang's medical records of apoplexy.

Background: Trastuzumab remains the standard protocol recommended for human epidermal growth factor receptor 2 (HER2)-positive metastatic breast cancer (MBC). After disease progression, the decision to continue trastuzumab treatment in combination with another type of chemotherapy, or to replace it with another HER2-targeted therapy, has not been conclusive. Methods: We systematically searched databases and extracted data from randomized controlled trials (RCTs) on patients who experienced disease progression after receiving trastuzumab-based therapies. Paired meta-analyses were performed to provide a comparison between patients continuously received trastuzumab-based therapy and those receiving other targeted therapies. Bayesian network meta-analysis was used to synthesize available evidence of direct or indirect comparison. Results: The 10 selected articles that included 3,158 patients were analyzed. The paired meta-analysis showed a 29% (hazard ratio (HR): 0.71; 95% confidence interval (CI): 0.60–0.85) reduction in mortality risk for patients continued receiving trastuzumab-based therapy than those receiving other targeted regimen. Bayesian network meta-analysis suggested that pertuzumab and trastuzumab plus capecitabine (PHC) showed an improvement in the overall survival (OS), with the highest surface under the cumulative ranking (SUCRA) (0.962 (82.3%)). In terms of progression-free survival (PFS) and objective response rate (ORR), trastuzumab emtansine (T-DM1) showed the highest SUCRA (0.949 (73.2%) and 0.997 (98.5%), respectively). Conclusions：Continuing trastuzumab with another type of chemotherapy is a better option for patients who experience disease progression after receiving trastuzumab-based therapy. Patients treated with PHC had the highest OS. Meanwhile, patients treated with T-DM1 showed better PFS and ORR than those treated with other regimens.

Background/purpose Cancer immunotherapy has revolutionized the clinical treatment of several tumors. Immune infiltration has been found to be closely related to clinical prognosis, but it shows limited activity in breast cancer (BC). Therefore, this study aimed to explore the infiltration pattern of immune cells in BC, and to find potential prognostic markers and new therapeutic targets.Patients and methods We downloaded the immune genome data of BC from the Cancer Genome Atlas (TCGA), and analyzed the tumor- infiltrating immune cells (TIICs) in BC for the first time using the CIBERSORT algorithm. The aim of this study was to assess the proportions of 22 immune cell subsets in BC and examine the correlation between each TIIC and overall survival (OS) as well as clinical characteristics.Results The results indicated that: (1) there was a significant difference between the immune infiltration spectrum of cancerous and adjacent tissues, with M2 macrophages, M0 macrophages, and CD4 + T cells being highly expressed in BC; (2) CD8 + T cells were positively correlated with activated CD4 + memory T cells and negatively correlated with M0 macrophages, and M2 macrophages was inversely correlated with M1 macrophages, T cells regulatory, T cells CD8; (3) T cells, macrophages and BC TNM stage, age, clinical stage were correlated (P < 0.05); and (4) high expression of M2 macrophage markers could be an independent biomarker of poor prognosis and a potential therapeutic target for BC.Conclusion This study provides a new research method for the systematic study of immune cells in the BC tumor microenvironment, and provides theoretical guidance for further experiments to verify M2 macrophages and T cell subsets as a potential target for immunotherapy and prognosis.

Background Long noncoding RNAs (lncRNAs) play a role in the formation, development, and prognosis of various cancers. Our study aimed to identify prognostic-related lncRNAs in lung squamous cell carcinoma (LUSC), which may provide new perspectives for individualized treatment of patients. Materials and Methods The RNA sequencing (lncRNA, microRNA (miRNA), mRNA) data and clinical information related to LUSC were obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed RNA sequences were used to construct the competitive endogenous RNA (ceRNA) network. In present study, we mainly used two prognostic verification methods, Cox analysis and survival analysis, to identify the prognostic relevance of specific lncRNAs and construct prognostic model of lncRNA. Results Datasets on 551 samples of lncRNA and mRNA and 523 miRNA samples were retrieved from the TCGA database. Analysis of the normal and LUSC samples identified 170 DElncRNAs, 331 DEmiRNAs, and 417 DEmRNAs differentially expressed RNAs. The ceRNA network contained 27 lncRNAs, 43 miRNAs, and 11 mRNAs. Furthermore, we identified seven specific lncRNAs (ERVH48-1, HCG9, SEC62-AS1, AC022148.1, LINC00460, C5orf17, LINC00261) as potential prognostic factors after correlation analysis, and five of the seven lncRNAs (AC022148.1, HCG9, LINC00460, C5orf17, LINC00261) constructed a prognostic model of LUSC. Conclusion In present study, we identified seven lncRNAs in the ceRNA network that are associated with potential prognosis in LUSC patients, and constructed a prognostic model of LUSC which can be used to assess the prognosis risk of clinical patients. Further biological experiments are needed to elucidate the specific molecular mechanisms underlying them.

Long non‐coding RNAs (lncRNAs), which competitively bind miRNAs to regulate target mRNA expression in the competing endogenous RNAs (ceRNAs) network, have attracted increasing attention in breast cancer research. We aim to find more effective therapeutic targets and prognostic markers for breast cancer. LncRNA, mRNA and miRNA expression profiles of breast cancer were downloaded from TCGA database. We screened the top 5000 lncRNAs, top 5000 mRNAs and all miRNAs to perform weighted gene co‐expression network analysis. The correlation between modules and clinical information of breast cancer was identified by Pearson's correlation coefficient. Based on the most relevant modules, we constructed a ceRNA network of breast cancer. Additionally, the standard Kaplan‐Meier univariate curve analysis was adopted to identify the prognosis of lncRNAs. Ultimately, a total of 23 and 5 modules were generated in the lncRNAs/mRNAs and miRNAs co‐expression network, respectively. According to the Green module of lncRNAs/mRNAs and Blue module of miRNAs, our constructed ceRNA network consisted of 52 lncRNAs, 17miRNAs and 79 mRNAs. Through survival analysis, 5 lncRNAs (AL117190.1, COL4A2‐AS1, LINC00184, MEG3 and MIR22HG) were identified as crucial prognostic factors for patients with breast cancer. Taken together, we have identified five novel lncRNAs related to prognosis of breast cancer. Our study has contributed to the deeper understanding of the molecular mechanism of breast cancer and provided novel insights into the use of breast cancer drugs and prognosis.

Fubin Feng,1 Tingting Zhang,2 Fang Yin,3 Cun Liu,2 Jing Zhuang,1 Lingyu Qi,2 Xue Wang,4 Jia Li,5 Lu Wang,1 Jinhui Tian,6 Changgang Sun1,7 1Department of Oncology, Weifang Traditional Chinese Hospital, Weifang, Shandong Province, China; 2College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong Province, China; 3Department of Pediatrics, Weifang People’s Hospital, Weifang, Shandong Province, China; 4Department of Medicine, Qingdao University, Qingdao, Shandong Province, China; 5Department of Oncology, Weifang Medical University, Weifang, Shandong Province, China; 6Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, Gansu Province, China; 7Department of Oncology, Affiliated Hospital of Weifang Medical University, Weifang, Shandong Province, China Purpose: Numerous HER2-targeted therapy clinical trials have demonstrated efficacy and safety in the first-line treatment of metastatic breast cancer (MBC). However, the direct or indirect comparison of these drugs is unclear. This network meta-analysis can solve this issue to some extent. Materials and methods: PubMed, Embase, and the Cochrane Library were searched for Phase II/III randomized controlled trials (RCTs) on metastatic HER2-positive breast cancer for first-line treatment up to December 16, 2017. Paired meta-analyses were performed to compare the regimens directly with the TP (trastuzumab plus taxane) regimen. Bayesian network meta-analysis was used to synthesize available evidence of direct or indirect comparison. Results: The database search identified 1,935 articles, among which 13 articles (10 RCTs) were eligible for the analysis involving 5,177 patients treated with 11 different regimens. The progression-free survival (PFS) in the Bayesian network meta-analysis suggested that the PTP (pertuzumab and trastuzumab plus taxane) regimen had the highest probability to be the preferred treatment (surface under the cumulative ranking [SUCRA]: 0.967) followed by the TPC (carboplatin and trastuzumab plus taxane) regimen (SUCRA: 0.923). The PTP regimen (SUCRA: 0.926) was similarly preferred for overall survival (OS). For objective response rate (ORR), the PTC regimen might be the optimal treatment (SUCRA: 0.935), followed by the PTP regimen. Conclusion: Overall, PTP might be the optimal first-line treatment for HER-2-positive MBC to improve the PFS and OS. Meanwhile, TPC might be most effective treatment in terms of the ORR. Regarding safety, the two regimens showed acceptable grade 3 or greater hematologic toxicity and heart failure. Keywords: breast cancer, metastasis, HER2-positive, HER2-targeted agents, network meta-analysis, randomized controlled trial

Tingting Zhang,1 Yan Yao,2 Fubin Feng,3 Wenge Zhao,2 Jinhui Tian,4 Chao Zhou,3 Xue Wang,5 Shengjie Dong,6 Jia Li,2 Lingyu Qi,7 Changgang Sun3,8 1College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong Province, People’s Republic of China; 2Clinical Medical College, Weifang Medical University, Weifang, Shandong Province, People’s Republic of China; 3Department of Oncology, Weifang Traditional Chinese Hospital, Weifang, Shandong Province, People’s Republic of China; 4Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, Gansu Province, People’s Republic of China; 5Clinical Medical Colleges, Qingdao University, Shinan District, Qingdao, Shandong Province, People’s Republic of China; 6Department of the Joint and Bone Surgery, Yantaishan Hospital, Yantai, Shandong Province, People’s Republic of China; 7College of First Clinical Medicine, Shandong University of Traditional Chinese Medicine, Ji’nan, People’s Republic of China; 8Department of Oncology, Affiliated Hospital of Weifang Medical University, Kuiwen District, Weifang, Shandong Province, People’s Republic of China Background: Combined chemotherapy is the cornerstone treatment for patients with advanced Hodgkin lymphoma (HL). The objective of our study was to perform a network meta-analysis of the efficacy of different chemotherapy regimens in adults with advanced-stage HL.Materials and methods: We searched for relevant randomized controlled trials (RCTs) in titles/abstracts in PubMed, Embase, and the Cochrane Library. The search was last updated on April 3, 2018. RCTs that assessed the effectiveness of one of the following treatments were included: doxorubicin, bleomycin, vinblastine, and dacarbazine (ABVD); four cycles of increased dose of bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine, and prednisone (BEACOPPescalated) followed by two or four cycles of standard dose of BEACOPP (4× BEACOPPescalated + 2 or 4× BEACOPPbaseline); brentuximab vedotin plus doxorubicin, vinblastine, and dacarbazine (A+AVD); doxorubicin, vinblastine, mechlorethamine, vincristine, bleomycin, etoposide, and prednisone combined with radiation therapy (Stanford V); mechlorethamine (cyclophosphamide), vincristine, procarbazine, and prednisone (M[C]OPP); sequential or alternating chemotherapy regimens with ABVD as the footstone (eg, COPP/ABVD or mechlorethamine, vincristine, procarbazine, and prednisone [MOPP]/ABVD); eight cycles of BEACOPPescalated; hybrid MOPP/ABV; and M[C]EC (M[C]OPP with epidoxorubicin, bleomycin, vinblastine [EBV], and lomustine, doxorubicin, and vindesine [CAD]).Results: Overall, we screened 3,564 citations and deemed 18 reports of 16 trials eligible and included them in our network meta-analysis. A total of 11,928 participants were randomly assigned to one of the 12 combinations of chemotherapy regimens, of which 11,476 participants were analyzed. For the overall survival (OS), no differences were observed within any interventions when the ABVD regimen was used as the reference treatment. Similarly, relative to A+AVD, 8× BEACOPPescalated and 6× BEACOPPescalated also showed no differences (HR =1.07, 95% credible interval (CrI): 0.58–1.95; HR =0.62, 95% CrI: 0.16–1.83; and HR =0.71, 95% CrI: 0.30–1.72, respectively). In terms of complete remission (CR), enough evidence exists to support a maximum clinical treatment effect for 6× BEACOPPescalated (OR =1.88, 95% CrI: 1.20–2.96; and OR =3.43, 95% CrI: 1.87–6.24).Conclusion: When compared across the 12 combined chemotherapy regimens, six cycles of BEACOPPescalated may be the optimal treatment for patients with advanced-stage HL. Keywords: advanced-stage Hodgkin lymphoma, combined chemotherapy, overall survival, network meta-analysis, randomized controlled trial

Background The optimal sequence of endocrine therapy in a neoadjuvant setting for hormone receptor-positive (HR+) breast cancer is unclear. Our study evaluated the efficacy and acceptability of neoadjuvant endocrine therapy for HR+ breast cancer. Methods We identified studies based on titles and abstracts that were published before 22 June 2018 in the following databases: PubMed, EMBASE, and the Cochrane Library. Eligible studies were randomised controlled trials with at least one arm that evaluated the effectiveness of one or a combination of anastrozole, letrozole, palbociclib, tamoxifen, fulvestrant, abemaciclib, everolimus, gefitinib, ribociclib, taselisib, and exemestane. We pooled effect sizes using the odds ratio (OR) and corresponding 95% credibility interval (95% CrI). The primary outcomes were response rate and treatment completion. Results Our network meta-analysis included 3,306 participants and 16 eligible studies, which assessed 15 treatments. In terms of response rates, compared with letrozole combined therapy, tamoxifen was associated with a significant reduction in response rate (OR, 0.34; 95% CrI, 0.13-0.85; OR, 0.32; 95% CrI, 0.13-0.80; OR, 0.26; 95% CrI, 0.09-0.83; and OR, 0.30; 95% CrI, 0.09-0.96; for letrozole plus everolimus, letrozole plus taselisib, letrozole plus zoledronic acid, and letrozole plus lapatinib, respectively). Based on the surface under the cumulative ranking curves ranking, letrozole plus zoledronic acid was associated with the highest rate of response (87.6%), followed by letrozole plus lapatinib (85.2%), and letrozole plus taselisib (79.3%). Conclusions Ultimately, our study established that letrozole plus zoledronic acid may be an optimal treatment based on its current rank in a neoadjuvant setting for HR+ breast cancer.

Background Breast cancer (BRCA) is the most prevalent cancer that threatens female health. A growing body of evidence has demonstrated the non-negligible effects of messenger RNAs (mRNAs) on biological processes involved in cancers; however, there is no definite conclusion regarding the role of mRNAs in predicting the prognosis of BRCA patients. Materials and methods We systematically screened the mRNA expression landscape and clinical data of samples from the Cancer Genome Atlas (TCGA). Univariate Cox analysis and robust likelihood-based survival analysis were conducted to identify key mRNAs associated with BRCA. Furthermore, risk scores based on multivariate Cox analysis divided the training set into high-risk and low-risk groups. ROC analysis determined the optimal cut-off point for patient classification of risk levels. The prognostic model was additionally validated in the testing set and complete dataset. Finally, we plotted the survival curves for the mRNAs used in our model. Results We obtained the original expression data of 13,617 mRNAs from a total of 1088 samples. After comprehensive survival analysis, the four-mRNA (ACSL1, OTUD3, PKD1L2, and WISP1) prognosis risk assessment model was constructed. Furthermore, the area under cure (AUC) was 0.834, indicating that the model was meaningful and reasonable. In each dataset, analysis based on the four-mRNA signature risk score indicated that the survival status of the group with high risk score was worse than that of the group with low risk scores. Patients with strong mRNA expression of OTUD3, PKD1L2, and WISP1 tended to have good prognosis, whereas patients with high ACSL1 expression tended to have poor prognosis. Conclusion In summary, we constructed a four-mRNA prognosis risk assessment model for BRCA. The newly developed model offers more possibilities for assessing prognosis and guiding the selection of better treatment strategies for BRCA.

Nitrification inhibitors (NIs) 3,4-dimethylpyrazole phosphate (DMPP) and dicyandiamide (DCD) have been used extensively to improve nitrogen fertilizer utilization in farmland. However, their comparative effects on ammonia-oxidizing bacteria (AOB) and ammonia-oxidizing archaea (AOA) in agricultural soils are still unclear. Here, we compared the impacts of these two inhibitors on soil nitrification, AOA and AOB abundance as well as their community structure in a vegetable soil by using real-time PCR and terminal restriction fragment length polymorphism (T-RFLP). Our results showed that urea application significantly increased the net nitrification rates, but were significantly inhibited by both NIs, and the inhibitory effect of DMPP was significantly greater than that of DCD. AOB growth was more greatly inhibited by DMPP than by DCD, and the net nitrification rate was significantly related to AOB abundance, but not to AOA abundance. Application of urea and NIs to soil did not change the diversity of the AOA community, with the T-RFs remaining in proportions that were similar to control soils, while the community structure of AOB exhibited obvious shifts within all different treatments compared to the control. Phylogenetic analysis showed that all AOA sequences fell within group 1.1a and group 1.1b, and the AOB community consisted of Nitrosospira cluster 3, cluster 0, and unidentified species. These results suggest that DMPP exhibited a stronger inhibitory effect on nitrification than DCD by inhibiting AOB rather than AOA.

The aim of this study was to develop techniques to evaluate soil phosphorus (P) sorption capacity (PSC) and determine critical soil P levels to predict P loss potential for calcareous soils. Seventy-five soils mostly from Northern China were analyzed for soil P using four extraction methods (water, Pw; carbonate, POls; ammonium oxalate, Pox; and Mehlich 3, PM3) as well as PSC derived from single-point (PSC150) and multipoint sorption (S t) isotherms. Strong correlation was found between PSC150 and S t (r 2=0.89, p