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Two-Dimensional MFI Zeolite Nanosheets Exfoliated through Surfactant Aided Solution Procedure.
NEK2 bounds to PKM2 and regulates PKM2 abundance via phosphorylation, which increases PKM2 stability. The xenograft tumor model checks the influence of NEK2 on tumor growth in vivo. Thus, NEK2 could be the novel biomarker and target of DLBCL, which remarkably ameliorates the diagnosis and treatment of DLBCL.
Tobacco smoking is a carcinogen for many cancers including bladder cancer. The microbiota is involved in the occurrence, development, and treatment of tumors. We explored the composition of male urinary microbiome and the correlation between tobacco smoking and microbiome in this study.

Alpha diversity, principal component analysis (PCA) and Adonis analysis, linear discriminant analysis (LDA) coupled with effect size measurement, and PICRUSt function predictive analysis were used to compare different microbiome between smokers and non-smokers in men.

There were 26 qualified samples included in the study. Eleven of them are healthy controls, and the others are from men with bladder cancer. 3-MA Simpson index and the result of PCA analysis between smokers and non-smokers were not different (P > 0.05) in healthy men. However, the abundance of Bacteroidaceae, Erysipelotrichales, Lachnospiraceae, Bacteroides, and so on in the urinary tract of smokers is much higher than that of non-smokers. Compared to non-smokers, the alpha diversity in smokers was elevated in patients with bladder cancer (P < 0.05). PCA analysis showed a significant difference between smokers and non-smokers (P < 0.001), indicating that tobacco smoking plays a vital role in urinary tract microbial composition.

The composition of microbiome in the urinary tract is closely related to tobacco smoking. link2 This phenomenon is more significant in patients with bladder cancer. This indicates tobacco smoking may promote the occurrence and development of bladder cancer by changing urinary tract microbiome.
The composition of microbiome in the urinary tract is closely related to tobacco smoking. This phenomenon is more significant in patients with bladder cancer. This indicates tobacco smoking may promote the occurrence and development of bladder cancer by changing urinary tract microbiome.
To evaluate whether texture features derived from semiquantitative kinetic parameter maps based on breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can determine human epidermal growth factor receptor 2 (HER2) status of patients with breast cancer.

This study included 102 patients with histologically confirmed breast cancer, all of whom underwent preoperative breast DCE-MRI and were enrolled retrospectively. This cohort included 48 HER2-positive cases and 54 HER2-negative cases. Seven semiquantitative kinetic parameter maps were calculated on the lesion area. A total of 55 texture features were extracted from each kinetic parameter map. Patients were randomly divided into training (n = 72) and test (n = 30) sets. The least absolute shrinkage and selection operator (LASSO) was used to select features in the training set, and then, multivariate logistic regression analysis was conducted to establish the prediction models. The classification performance was evaluated by receiver operatine the potential to be used as imaging biomarkers to distinguish HER2-positive and HER2-negative breast cancer.Next-generation sequencing (NGS) has drastically enhanced human cancer research, but diverse sequencing strategies, complicated open-source software, and the identification of massive numbers of mutations have limited the clinical application of NGS. Here, we first presented GPyFlow, a lightweight tool that flexibly customizes, executes, and shares workflows. We then introduced DIVIS, a customizable pipeline based on GPyFlow that integrates read preprocessing, alignment, variant detection, and annotation of whole-genome sequencing, whole-exome sequencing, and gene-panel sequencing. By default, DIVIS screens variants from multiple callers and generates a standard variant-detection format list containing caller evidence for each sample, which is compatible with advanced analyses. Lastly, DIVIS generates a statistical report, including command lines, parameters, quality-control indicators, and mutation summary. DIVIS substantially facilitates complex cancer genome sequencing analyses by means of a single powerful and easy-to-use command. The DIVIS code is freely available at https//github.com/niu-lab/DIVIS, and the docker image can be downloaded from https//hub.docker.com/repository/docker/sunshinerain/divis.The aim was to build a predictive model based on ultrasonography (US)-based deep learning model (US-DLM) and clinical features (Clin) for differentiating hepatocellular carcinoma (HCC) from other malignancy (OM) in cirrhotic patients. 112 patients with 120 HCCs and 60 patients with 61 OMs were included. They were randomly divided into training and test cohorts with a 41 ratio for developing and evaluating US-DLM model, respectively. Significant Clin predictors of OM in the training cohort were combined with US-DLM to build a nomogram predictive model (US-DLM+Clin). The diagnostic performance of US-DLM and US-DLM+Clin were compared with that of contrast enhanced magnetic resonance imaging (MRI) liver imaging and reporting system category M (MRI LR-M). US-DLM was the best independent predictor for evaluating OMs, followed by clinical information, including high cancer antigen 199 (CA199) level and female. The US-DLM achieved an AUC of 0.74 in the test cohort, which was comparable with that of MRI LR-M (AUC=0.84, p=0.232). The US-DLM+Clin for predicting OMs also had similar AUC value (0.81) compared with that of LR-M+Clin (0.83, p>0.05). US-DLM+Clin obtained a higher specificity, but a lower sensitivity, compared to that of LR-M +Clin (Specificity 82.6% vs. 73.9%, p=0.007; Sensitivity 78.6% vs. 92.9%, p=0.006) for evaluating OMs in the test set. The US-DLM+Clin model is valuable in differentiating HCC from OM in the setting of cirrhosis.
The aim of the present study was to construct and test a liquid-liquid phaseseparation (LLPS)-related gene signature as a prognostic tool for epithelial ovarian cancer (EOC).

The data set GSE26712 was used to screen the differentially expressed LLPS-related genes. Functional enrichment analysis was performed to reveal the potential biological functions. GSE17260 and GSE32062 were combined as the discovery to construct an LLPS-related gene signature through a three-step analysis (univariate Cox, least absolute shrinkage and selection operator, and multivariate Cox analyses). The EOC data set from The Cancer Genome Atlas as the test set was used to test the LLPS-related gene signature.

The differentially expressed LLPS-related genes involved in several cancer-related pathways, such as MAPK signaling pathway, cell cycle, and DNA replication. Eleven genes were selected to construct the LLPS-related gene signature risk index as prognostic biomarker for EOC. The risk index could successfully divide patients with EOC into high- and low-risk groups. The patients in high-risk group had significantly shorter overall survival than those with in low-risk group. The LLPS-related gene signature was validated in the test set and may be an independent prognostic factor compared to routine clinical features.

We constructed and validated an LLPS-related gene signature as a prognosis tool in EOC through integrated analysis of multiple data sets.
We constructed and validated an LLPS-related gene signature as a prognosis tool in EOC through integrated analysis of multiple data sets.Anaplastic lymphoma kinase (ALK) rearrangements account for approximately 5-6% of non-small-cell lung cancer (NSCLC) patients. In this study, a case of lung adenocarcinoma harboring a novel MRPS9-ALK fusion is reported. The patient responded well to the first and second generation of ALK-tyrosine kinase inhibitors (ALK-TKIs) (crizotinib then alectinib), as her imaging findings and clinical symptoms significantly improved. At last follow-up, over 21 months of overall survival (OS) has been achieved since ALK-TKI treatment. The progression-free survival (PFS) is already ten months since alectinib. The adverse effects were manageable. The case presented here provides first clinical evidence of the efficacy of ALK-TKIs in NSCLC patients with MRPS9-ALK fusion.Immune checkpoint blockade (ICB) shows remarkable clinical effects in patients with metastatic microsatellite-unstable (MSI) cancer. However, markers identifying potential non-responders are missing. We examined the prevalence of Beta-2-microglobulin (B2M) mutations, a common immune evasion mechanism, in stage IV MSI gastrointestinal cancer and its influence on metastatic pattern and patients' survival under ICB. Twenty-five patients with metastatic, MSI gastrointestinal adenocarcinoma were included. Eighteen patients received ICB with pembrolizumab and one patient with nivolumab/ipilimumab. Sequencing was performed to determine B2M mutation status. B2M mutations and loss of B2M expression were detected in 6 out of 25 stage IV MSI cancers. B2M mutations were strongly associated with exclusively peritoneal/peritoneal and lymph node metastases (p=0.0055). However, no significant differences in therapy response (25% vs. 46.6%, p>0.99) and survival (median PFS 19.5 vs 33.0 months, p=0.74; median OS 39 months vs. not reached, p>0.99) were observed between B2M-mutant and B2M-wild type tumor patients. Among metastatic MSI GI cancers, B2M-mutant tumors represent a biologically distinct disease with distinct metastatic patterns. To assess ICB response in B2M-mutant MSI cancer patients, future studies need to account for the fact that baseline survival of patients with B2M-mutant MSI cancer may be longer than of patients with B2M-wild type MSI cancer.
Epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) are effective in advanced EGFR-mutation non-small cell lung cancer (NSCLC) but the magnitude of tumor regression varies, and drug resistance is unavoidable. The pleckstrin homology domain leucine-rich repeat protein phosphatase (PHLPP) levels are reduced or lost and acts as a tumor suppressor in many cancers. Here, we hypothesized that PHLPP is a key regulator of EGFR-TKI sensitivity and a potential treatment target for overcoming resistance to EGFR-TKI in lung cancer.

Cell proliferation and growth inhibition were measured by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) and colony formation assay. PHLPP- knockdown stable cell lines were generated by lentivirus-mediated delivery of PHLPP shRNAs. The expression of PHLPP mRNA and protein levels was detected by real-time quantitative polymerase chain reaction (qPCR) and Western blotting. link3 Immunohistochemical (IHC) staining was performed to detect the PHLPP expression re, PHLPP expression level was not only a potential biomarker to predict EGFR-TKIs sensitivity but also as a therapeutic target in EGFR-TKIs therapy, enhancing PHLPP expression may be a valuable strategy for delaying or overcoming EGFR-TKIs drug resistance.
Treatment of recurrent primary pediatric brain tumors remains a major challenge, with most children succumbing to their disease. We conducted a prospective phase 2 study investigating the safety and efficacy of pomalidomide (POM) in children and young adults with recurrent and progressive primary brain tumors.

Patients with recurrent and progressive high-grade glioma (HGG), diffuse intrinsic pontine glioma (DIPG), ependymoma, or medulloblastoma received POM 2.6 mg/m
/day (the recommended phase 2 dose [RP2D]) on days 1-21 of a 28-day cycle. A Simon's Optimal 2-stage design was used to determine efficacy. Primary endpoints included objective response (OR) and long-term stable disease (LTSD) rates. Secondary endpoints included duration of response, progression-free survival (PFS), overall survival (OS), and safety.

46 patients were evaluable for response (HGG, n = 19; DIPG, ependymoma, and medulloblastoma, n = 9 each). Two patients with HGG achieved OR or LTSD (10.5% [95% CI, 1.3%-33.1%]; 1 partial response and 1 LTSD) and 1 patient with ependymoma had LTSD (11.
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