Epidemiological Characteristics, Antifungal Susceptibility, Risk Factors, and Outcomes of Candida Bloodstream Infection: A Ten-Year Surveillance in a Teaching Hospital in China.

Background: Candida is one of the most important pathogens of hospital-acquired bloodstream infections. Its morbidity and mortality are still high, which is a serious global public problem. Purpose: To investigate the strain distribution, drug susceptibility, clinical characteristics of patients, and risk factors affecting the prognosis of Candida bloodstream infection (BSI). Materials and Methods: We retrospectively collected the clinical data, infection-related indicators, prognosis, strain prevalence and drug susceptibility of 163 patients with Candida BSI in a teaching hospital from January 2012 to December 2022. Univariate and multivariate logistic regression were used to analyze the risk factors affecting the prognosis. Results: In 163 cases of Candida BSI, Candida albicans accounted for 48.47%, and Candida non-albicans accounted for 51.53%. A total of 163 patients with Candida BSI were mainly distributed in intensive care unit (ICU) and emergency department, accounting for 40.49% and 14.72%, respectively. The resistance rate of Candida albicans to fluconazole, itraconazole and voriconazole was less than 10%, and the sensitivity rate of Candida tropicalis to fluconazole, itraconazole and voriconazole was less than 80%. The mortality rate of 163 patients with Candida BSI was 33.13%, with Candida non-albicans higher than that of Candida albicans (p = 0.04). Multivariate analysis showed that hemodialysis (OR = 0.199, 95% CI: 0.059-0.673, P = 0.009), arteriovenous catheters (OR = 0.344, 95% CI: 0.130-0.913, P = 0.032), elevated neutrophil count (OR = 0.409, 95% CI: 0.194-0.862, P = 0.019) and APACHE II score (OR = 0.848, 95% CI: 0.789~0.911, P < 0.001) were independent risk factors for death in patients with candidemia. Conclusion: The blood flow infection rate of Candida non-albicans is increasing, and the mortality rate and resistance to antifungal drugs are higher than that of Candida albicans. Hemodialysis, arteriovenous catheters, elevated neutrophil count and APACHE II score were associated with death in patients with Candida BSI.

Research Progress of Tumor Microenvironment Targeted Therapy for Clear Cell Renal Cell Carcinoma.

Renal clear cell carcinoma (ccRCC) and the tumor microenvironment (TME) influence each other, leading to the tumor microenvironment that can guide the corresponding treatment. With the deepening of research, some treatment options have achieved good results, such as tyrosine kinase inhibitors, immune checkpoint inhibitors, and so on. As the link between TME and malignancy is constantly discovered, more targeted studies on different components of TME are increasing, and this targeted therapy is a new method for treating ccRCC, and also a current research hotspot. This review summarizes the characteristics of the ccRCC tumor microenvironment, the outcomes of different treatments, and some potential targets.

M3NAS: Multi-Scale and Multi-Level Memory-Efficient Neural Architecture Search for Low-Dose CT Denoising.

Lowering the radiation dose in computed tomography (CT) can greatly reduce the potential risk to public health. However, the reconstructed images from dose-reduced CT or low-dose CT (LDCT) suffer from severe noise which compromises the subsequent diagnosis and analysis. Recently, convolutional neural networks have achieved promising results in removing noise from LDCT images. The network architectures that are used are either handcrafted or built on top of conventional networks such as ResNet and U-Net. Recent advances in neural network architecture search (NAS) have shown that the network architecture has a dramatic effect on the model performance. This indicates that current network architectures for LDCT may be suboptimal. Therefore, in this paper, we make the first attempt to apply NAS to LDCT and propose a multi-scale and multi-level memory-efficient NAS for LDCT denoising, termed M3NAS. On the one hand, the proposed M3NAS fuses features extracted by different scale cells to capture multi-scale image structural details. On the other hand, the proposed M3NAS can search a hybrid cell- and network-level structure for better performance. In addition, M3NAS can effectively reduce the number of model parameters and increase the speed of inference. Extensive experimental results on two different datasets demonstrate that the proposed M3NAS can achieve better performance and fewer parameters than several state-of-the-art methods. In addition, we also validate the effectiveness of the multi-scale and multi-level architecture for LDCT denoising, and present further analysis for different configurations of super-net.

The expression and prognostic value of transporter 1, ATP binding cassette subfamily B member in clear cell renal cell cancer with experimental validation.

Transporter associated with antigen processing 1(TAP1) serves as a protein to transport antigenic peptides from the surface of the endoplasmic reticulum to the lumen of the endoplasmic reticulum when the antigens are presented by major histocompatibility complex type I (MHC-I), which has been identified to play a critical role in antigen presentation in innate immunity. In tumors, the role of TAP1 seems to remain controversial. On the one hand, given the role of TAP1 in antigen presentation, it is indicated that high TAP1 expression corresponds to the emergence of more neoantigens epitopes that facilitate the recognition for phagocytes, T cells and other cells. On the other hand, the genetic ablation of transporter associated with antigen processing (TAP) results in the presentation of new class I-restricted epitopes encoded in house-keeping products. Opposite result has been revealed by studies in other tumors suggest, which implies a more complex function of TAP1. Therefore, it's significant to clarify the role of TAP1 in clear cell renal cell carcinoma (ccRCC). In this study, we found the elevated expression levels in mRNA and protein of TAP1 in ccRCC tissues, which indicated a relatively worse prognosis. Transwell assay and Scratch assay in vitro demonstrated the promotive role of TAP1 in ccRCC migration as well as a significant role in metastasis. And the increased expression of TAP1 resulted in more immune cells infiltrated in cancer tissues. TAP1 was also demonstrated to be related to immune regulator genes, as gene set enrichment analysis (GSEA) indicated its significant role in immune regulation. The results of CancerSEA indicated the positive association of the high-level TAP1 expression with epithelial-mesenchymal transition (EMT) and the inverse association with Cell Cycle. The effective drugs were also predicted based on TAP1 expression, of which the high level was indeed associated with resistance to multiple drugs, but some effective drugs still identified based on high TAP1 expression. According to the analysis of various databases, the role of TAP1 in ccRCC was explored, especially in relationship of TAP1 with tumor microenvironment. These results indicate that TAP1 can serve as a potential target for treatment of ccRCC.

Targeting HIC1/TGF-ß axis-shaped prostate cancer microenvironment restrains its progression.

Prostate cancer (PCa) is a malignant tumor that seriously threatens men's health worldwide. Recently, stromal cells in the tumor microenvironment (TME) have been reported to contribute to the progression of PCa. However, the role and mechanism of how PCa cells interact with stromal cells to reshape the TME remain largely unknown. Here, using a spontaneous prostate adenocarcinoma (PRAD) model driven by the loss of Pten and Hic1, we found that M2 macrophages markedly infiltrated the stroma of Pten and Hic1 double conditional knockout (dCKO) mice compared with those in control (Ctrl) mice due to higher TGF-ß levels secreted by HIC1-deleted PCa cells. Mechanistically, TGF-ß in TME promoted the polarization of macrophages into "M2" status by activating the STAT3 pathway and modulating c-Myc to upregulate CXCR4 expression. Meanwhile, TGF-ß activated the fibroblasts to form cancer-associated fibroblasts (CAFs) that secrete higher CXCL12 levels, which bound to its cognate receptor CXCR4 on M2 macrophages. Upon interaction with CAFs, M2 macrophages secreted more CXCL5, which promoted the epithelial-mesenchymal transition (EMT) of PCa via CXCR2. Moreover, using the TGF-ß receptor I antagonist, galunisertib, significantly inhibited the tumor growth and progression of the TRAMP-C1 cell line-derived subcutaneous tumor model. Finally, we confirmed that the stromal microenvironment was shaped by TGF-ß in HIC1-deficient PCa and was associated with the progression of PCa.

Targeted inhibition of ACLY expression to reverse the resistance of sorafenib in hepatocellular carcinoma.

Resistance to sorafenib has been documented in hepatocellular carcinoma (HCC) patients. We investigated: (i) the correlation between adenosine triphosphate citrate lyase (ACLY) expression and sorafenib resistance in HCC; and (ii) if targeted inhibition could reverse sorafenib resistance. Samples of HCC tissue were obtained from patients and ACLY expression was measured. PET/CT was employed to measure maximum standard unit value (SUVmax) in HCC patients before and after sorafenib treatment. Using HepG2 cells, we created a sorafenib-resistant cell line. Glucose metabolism and lipid synthesis in HCC cells were tested using 14C-glucose. Disulfide-crosslinked polyethylenimine (SS-PEI)-mediated plasmid transfection was carried out, followed by creation of an HCC model in mice. SUVmax of HCC lesions was closely related to ACLY expression. Patients with high ACLY expression were not sensitive to sorafenib therapy. Lipid metabolism was more active in sorafenib-resistant HCC cells. ACLY expression was higher in sorafenib-resistant cells and HCC-cell sensitivity to sorafenib increased after ACLY-knockout. The latter reversed sorafenib resistance in HCC cells more significantly under hypoxic conditions. SS-PEI/proline-modified short hairpin-(psh)RNA-ACLY plus sorafenib inhibited the growth of drug-resistant cells significantly. These data suggest that ACLY downregulation can reverse sorafenib resistance, and that SS-PEI can be used to mediate shRNA-ACLY transfection in HCC treatment.

Prostate Cancer Screening Using Prostate-Specific Antigen Tests in a High-Risk Population in China: A Cost-Utility Analysis.

BACKGROUND: Both National Comprehensive Cancer Network and Chinese guidelines recommend beginning prostate-specific antigen (PSA) screening for men aged 50 years or 45 years with a family history because they were at a higher risk of developing prostate cancer. Several model-based economic evaluations of PSA screening studies have been conducted, but with little evidence from China. OBJECTIVE: The aim of this study was to conduct an economic evaluation of the cost-utility of PSA-based prostate cancer screening in Chinese men. METHODS: We developed a decision-tree and Markov model in Excel (Microsoft Corp, Redmond, Washington) to compare 2 strategies that can be used to detect prostate cancer: PSA-based screening followed by a biopsy, and non-PSA screening. We assumed that the patients would repeat screening in subsequent years if their first-year PSA value was higher than 4.0 ng/mL. The model adopted health care system perspective and lifetime horizon. Screening efficacy, cost, utility, and long-term survival of prostate cancer were retrieved from published literature and physician surveys. Both quality-adjusted life year and costs were discounted at an annual rate of 3.5%. Uncertainty was assessed by 1-way and probabilistic sensitivity analyses. Our model also calculated the risk-to-benefit ratio as the ratio of overdiagnosis (biopsy without diagnosed) to prostate cancer-related deaths prevented in different age groups. RESULTS: The results suggested that PSA-based screening was cost-effective compared with no PSA screening, with an incremental cost-utility ratio of ¥11,381 ($1821/€1480) per quality-adjusted life year. This value was less than the threshold of 1-time gross domestic product per capita in China (ie, ¥70,892 [$11,343/€9216]). Sensitivity analyses confirmed the robustness of the results. The risk-to-benefit ratios of the 50 to 65 years and the 65 to 80 years age groups were 1.3 and 2.8, respectively. CONCLUSIONS: PSA-based prostate cancer screening appears to be cost-effective in some high-risk Chinese men. PSA screening (PSA testing followed by magnetic resonance imaging and biopsy if positive) can be recommended for Chinese men aged 50 to 65 years because this approach had the lowest risk-to-benefit ratio. The approach should be further adapted based on future updated data. (Curr Ther Res Clin Exp. 2022; 83:XXX-XXX)© 2022 Elsevier HS Journals, Inc.

Measurement of echo reduction for passive-material samples using sparse Bayesian learning and least squares estimation.

Echo reduction (ER) for passive materials is important for the evaluation of sound absorption performance. In a limited space, due to the strong interference of multipath signals, it is difficult to separate and extract the directed and reflected signals of the sample from the measured signal to accurately calculate the ER, especially at low frequencies. A method combining sparse Bayesian learning (SBL) and the least squares estimation (LSE) is proposed to extract the directed and normal reflected signals of the sample from the received signal. First, owing to the high resolution of SBL in time delays estimation, the set of multipath time delays is estimated. Then, the LSE is utilized to evaluate the amplitudes of multipath signals with estimated time delays as a priori information. With combination processing, the resolution of time delay estimation is enhanced, the dimension of the LSE is reduced, and the accuracy of the amplitude estimation for the directed and normal reflected signals, as well as the ER evaluation, is improved. The proposed method is validated through simulations and experiments in a cylindrical tank.

LncRNA RP11-89 facilitates tumorigenesis and ferroptosis resistance through PROM2-activated iron export by sponging miR-129-5p in bladder cancer.

Long non-coding RNAs (lncRNAs) act as important regulators of tumorigenesis and development in bladder cancer. However, the underlying molecular mechanisms remain elusive. We previously identified a novel lncRNA signature related to immunity and progression in bladder cancer. Here we further explored the function of RP11-89, a lncRNA discovered in the previous signature. Loss- and gain-of function experiments were performed using CCK-8 assay, flow cytometry, Transwell assays, scratch tests and subcutaneous nude mouse models. High-throughput RNA sequencing was conducted to identify dysregulated genes in bladder cancer cells with RP11-89 knockdown or overexpression. Regulation of RP11-89 on miR-129-5p and PROM2 was explored through luciferase reporter assay, RIP assay and RNA pull-down assay. RP11-89 promoted cell proliferation, migration and tumorigenesis and inhibited cell cycle arrest via the miR-129-5p/PROM2 axis. We found that RP11-89 "sponges" miR-129-5p and upregulates PROM2. Elevated PROM2 in cells was associated with attenuated ferroptosis through iron export, formation of multivesicular bodies and less mitochondrial abnormalities. We demonstrated that RP11-89 is a novel tumorigenic regulator that inhibits ferroptosis via PROM2-activated iron export. RP11-89 may serve as a potential biomarker for targeted therapy in bladder cancer.

Comprehensive analysis of alternative splicing profiling reveals novel events associated with prognosis and the infiltration of immune cells in prostate cancer.

BACKGROUND: Alternative splicing (AS) is believed to play a vital role in tumor development. Therefore, comprehensive investigation of AS and its biological function in prostate cancer (PCa) is crucial. METHODS: The AS profiling of 489 patients with PCa was obtained from The Cancer Genome Atlas (TCGA) SpliceSeq database. Bioinformatics tools were used to describe splicing associations and build prognostic models. Unsupervised clustering of the determined prognostic AS events and the relationship with immune characteristics were also explored. RESULTS: In total, 20,723 AS events were detected and 2,805 were identified in PCa. In the regulatory networks, the data suggested a significant correlation between splicing factor (SF) expression and AS events. To stratify the progression risk of PCa patients, prognostic models were constructed using splicing patterns. Six AS events were screened out as independent prognostic factors for progression-free survival. Based on the gene features, we constructed the combined prognostic predictors model, and the receiver operating characteristic (ROC) curve for this model reached a high area under the ROC curve (AUC) of 0.729793, indicating a favorable ability to predict patient outcomes. Through unsupervised clustering analysis, the correlations between AS-based clusters and prognosis as well as immune characteristics were revealed. The correlation analysis on TIMER revealed the relationship between gene expression and immune cell infiltration. CONCLUSIONS: This in-depth genome-wide analysis of the AS profiling in PCa revealed unique AS events associated with cancer progression and the infiltration of immune cells, with potential for predicting outcomes and therapeutic responses.

DAN-Net: Dual-domain adaptive-scaling non-local network for CT metal artifact reduction.

Metallic implants can heavily attenuate x-rays in computed tomography (CT) scans, leading to severe artifacts in reconstructed images, which significantly jeopardize image quality and negatively impact subsequent diagnoses and treatment planning. With the rapid development of deep learning in the field of medical imaging, several network models have been proposed for metal artifact reduction (MAR) in CT. Despite the encouraging results achieved by these methods, there is still much room to further improve performance. In this paper, a novel dual-domain adaptive-scaling non-local network (DAN-Net) is proposed for MAR. We correct the corrupted sinogram using adaptive scaling first to preserve more tissue and bone details. Then, an end-to-end dual-domain network is adopted to successively process the sinogram and its corresponding reconstructed image is generated by the analytical reconstruction layer. In addition, to better suppress the existing artifacts and restrain the potential secondary artifacts caused by inaccurate results of the sinogram-domain network, a novel residual sinogram learning strategy and non-local module are leveraged in the proposed network model. Experiments demonstrate the performance of the proposed DAN-Net is competitive with several state-of-the-art MAR methods in both qualitative and quantitative aspects.

CT Reconstruction With PDF: Parameter-Dependent Framework for Data From Multiple Geometries and Dose Levels.

The current mainstream computed tomography (CT) reconstruction methods based on deep learning usually need to fix the scanning geometry and dose level, which significantly aggravates the training costs and requires more training data for real clinical applications. In this paper, we propose a parameter-dependent framework (PDF) that trains a reconstruction network with data originating from multiple alternative geometries and dose levels simultaneously. In the proposed PDF, the geometry and dose level are parameterized and fed into two multilayer perceptrons (MLPs). The outputs of the MLPs are used to modulate the feature maps of the CT reconstruction network, which condition the network outputs on different geometries and dose levels. The experiments show that our proposed method can obtain competitive performance compared to the original network trained with either specific or mixed geometry and dose level, which can efficiently save extra training costs for multiple geometries and dose levels.

MAGIC: Manifold and Graph Integrative Convolutional Network for Low-Dose CT Reconstruction.

Low-dose computed tomography (LDCT) scans, which can effectively alleviate the radiation problem, will degrade the imaging quality. In this paper, we propose a novel LDCT reconstruction network that unrolls the iterative scheme and performs in both image and manifold spaces. Because patch manifolds of medical images have low-dimensional structures, we can build graphs from the manifolds. Then, we simultaneously leverage the spatial convolution to extract the local pixel-level features from the images and incorporate the graph convolution to analyze the nonlocal topological features in manifold space. The experiments show that our proposed method outperforms both the quantitative and qualitative aspects of state-of-the-art methods. In addition, aided by a projection loss component, our proposed method also demonstrates superior performance for semi-supervised learning. The network can remove most noise while maintaining the details of only 10% (40 slices) of the training data labeled.

A 5-lncRNA Signature Associated with Smoking Predicts the Overall Survival of Patients with Muscle-Invasive Bladder Cancer.

Increasing evidence demonstrated that noncoding RNA is abnormally expressed in cancer tissues and serves a vital role in tumorigenesis, tumor development, and metastasis. The aim of the present study was to determine an lncRNA signature in order to predict the overall survival (OS) of patients with muscle-invasive bladder cancer (MIBC). A total of 246 patients with pathologically confirmed MIBC in The Cancer Genome Atlas (TCGA) dataset were recruited and included in the present study. We choose patients who have smoked less (including never smoking) or more than 15 years. A total of 44 differentially expressed lncRNAs were identified with a fold change larger than 1.5 and a P value < 0.05 through the limma package. Subsequently, a comparison between patients with no tobacco smoke exposure for <15 years and patients who had been exposed to tobacco smoke for >15 years was performed by using the matchIt package. Among the 44 differentially expressed lncRNAs, 5 lncRNAs were identified to be significantly associated with OS. Based on the characteristic risk scores of these 5 lncRNAs, patients were divided into low-risk and high-risk groups and exhibited significant differences in OS. Multivariate Cox regression analysis demonstrated that the 5-lncRNA signature was independent of age, tumor-node metastasis (TNM) staging, lymphatic node status, and adjuvant postoperative radiotherapy. In the present study, a novel 5-lncRNA signature was developed and was demonstrated to be useful in predicting the survival of patients with MIBC. If validated, this lncRNA signature may assist in the selection of a high-risk subpopulation that requires more aggressive therapeutic intervention. The risk scores involved in several associated pathways were identified using gene set enrichment analysis (GSEA). However, the clinical implications and mechanism of these 5 lncRNAs require further investigation.

Noise-Powered Disentangled Representation for Unsupervised Speckle Reduction of Optical Coherence Tomography Images.

Due to its noninvasive character, optical coherence tomography (OCT) has become a popular diagnostic method in clinical settings. However, the low-coherence interferometric imaging procedure is inevitably contaminated by heavy speckle noise, which impairs both visual quality and diagnosis of various ocular diseases. Although deep learning has been applied for image denoising and achieved promising results, the lack of well-registered clean and noisy image pairs makes it impractical for supervised learning-based approaches to achieve satisfactory OCT image denoising results. In this paper, we propose an unsupervised OCT image speckle reduction algorithm that does not rely on well-registered image pairs. Specifically, by employing the ideas of disentangled representation and generative adversarial network, the proposed method first disentangles the noisy image into content and noise spaces by corresponding encoders. Then, the generator is used to predict the denoised OCT image with the extracted content features. In addition, the noise patches cropped from the noisy image are utilized to facilitate more accurate disentanglement. Extensive experiments have been conducted, and the results suggest that our proposed method is superior to the classic methods and demonstrates competitive performance to several recently proposed learning-based approaches in both quantitative and qualitative aspects. Code is available at: https://github.com/tsmotlp/DRGAN-OCT.

Validation of a finite element model with six-year-old child anatomical characteristics as specified in Euro NCAP Pedestrian Human Model Certification (TB024).

Accident statistics show that more than 80% of car-to-pedestrian collisions (CPC) occur when pedestrians cross the road. It is very important to establish a finite element model with natural walking posture to study the kinematics and injury mechanism of pedestrians. In this study, a finite element model of six-year-old child pedestrian is developed with detailed anatomical characteristics and posture parameters as specified in Euro NCAP Pedestrian Human Model Certification (TB024). The numerical human body model is validated in total twelve simulations in which the pedestrian is impacted against four generic vehicle models at speeds 30, 40, 50 km/h prescribed in TB024. The Head Impact Time (HIT), Contact Force and the Trajectories of HC, T12 and AC of all twelve simulations are compared with the reference corridors provided by Technical Bulletin 024. The results indicate that the numerical human body model of a six-year-old child can be used to demonstrate the suitability of the sensing system for the range of pedestrian sizes; the timing of system deployment, and the bonnet deflection due to body loading. Furthermore, the model could be a good tool for further research on pedestrian injury mechanism and the development of pedestrian protection devices.

LINC00675 activates androgen receptor axis signaling pathway to promote castration-resistant prostate cancer progression.

The development of prostate cancer (PCa) from androgen-deprivation therapy (ADT) sensitive to castration resistant (CRPC) seriously impacts life quality and survival of PCa patients. Emerging evidence shows that long noncoding RNAs (lncRNAs) play vital roles in cancer initiation and progression. However, the inherited mechanisms of how lncRNAs participate in PCa progression and treatment resistance remain unclear. Here, we found that a long noncoding RNA LINC00675 was upregulated in androgen-insensitive PCa cell lines and CRPC patients, which promoted PCa progression both in vitro and in vivo. Knockdown of LINC00675 markedly suppressed tumor formation and attenuated enzalutamide resistance of PCa cells. Mechanistically, LINC00675 could directly modulate androgen receptor's (AR) interaction with mouse double minute-2 (MDM2) and block AR's ubiquitination by binding to it. Meanwhile, LINC00675 could bind to GATA2 mRNA and stabilize its expression level, in which GATA2 could act as a co-activator in the AR signaling pathway. Notably, we treated subcutaneous xenografts models with enzalutamide and antisense oligonucleotides (ASO) targeting LINC00675 in vivo and found that targeting LINC00675 would benefit androgen-deprivation-insensitive models. Our findings disclose that the LINC00675/MDM2/GATA2/AR signaling axis is a potential therapeutic target for CRPC patients.

Targeting CPT1B as a potential therapeutic strategy in castration-resistant and enzalutamide-resistant prostate cancer.

BACKGROUND: Prostate cancer is characterized by aberrant lipid metabolism, including elevated fatty acid oxidation. Carnitine palmitoyltransferase 1B (CPT1B) catalyzes the rate-limiting step of fatty acid oxidation. This study aimed to determine if CPT1B has a critical role in prostate cancer progression and to identify its regulatory mechanism. METHODS: CPT1B expression data from The Cancer Genome Atlas and Gene Expression Omnibus databases was compared with patient survival data. A tissue microarray was constructed with 60 samples of prostate cancer and immunohistochemically stained for CPT1B. Castration-resistant prostate cancer (CRPC) cell lines 22RV1 and C4-2 in which CPT1B expression had been stably knocked down were established; and cell proliferation, cell cycle distribution, and invasion were investigated by Cell Counting Kit-8 (CCK-8) and colony formation assays, flow cytometry, and Transwell assays, respectively. To examine the impact of androgen receptor (AR) inhibition on CPT1B expression, JASPAR CORE was searched to identify AR-binding sites in CPT1B. Dual luciferase and ChIP assays were performed to confirm CPT1B activity and AR binding, respectively. Differentially expressed genes (DEGs) in prostate cancer underwent gene set enrichment analysis (GSEA). Enzalutamide-resistant C4-2 cells were generated and the mechanism of enzalutamide resistance and downstream signaling pathway changes of CPT1B to C4-2 was explored through CCK-8 test. RESULTS: CPT1B expression was upregulated in human prostate cancer compared with normal prostate tissue and was associated with poor disease-free survival and overall survival. Silencing of CPT1B resulted in downregulated cell proliferation, reduced S-phase distribution, and lower invasive ability, whereas the opposite was observed in CRPC cells overexpressing CPTB1. DEGS in prostate cancer were correlated with G-protein-coupled receptor signaling, molecular transducer activity, and calcium ion binding. AR may regulate CPT1B expression and activity via specific binding sites, as confirmed by dual luciferase and ChIP assays. The CCK-8 experiment demonstrated that CPT1B overexpression in C4-2 cells did not significantly increase the ability of enzalutamide resistance. However, overexpression of CPT1B in C4-2R cells significantly increased the enzalutamide resistance. Upregulation of CPT1B expression increased AKT expression and phosphorylation. CONCLUSIONS: CPT1B is upregulated in prostate cancer and is correlated with poor prognosis, indicating its potential as a biomarker. AR inhibits the transcription of CPT1B. In the CRPC cell line, overexpression of CPT1B alone cannot promote enzalutamide resistance, but in the drug-resistant line C4-2R, overexpression of CPT1B can promote the resistance of C4-2R to enzalutamide.

Development and validation of a robust multigene signature as an aid to predict early relapse in stage I-III clear cell and papillary renal cell cancer.

Background and objectives: Multi-gene signature can be used as prognostic indicator in many types of cancer, but the association with early-relapse in patients with stage I-III clear cell and papillary renal cell cancer (RCC) is unknown. We aim to establish a mRNAs signature for improving prediction of early-relapse in patients with stage I-III clear cell and papillary RCC. Methods: The data of 610 patients with stage I-III RCC from The Cancer Genome Atlas (TCGA) and 270 patients from Fudan University Shanghai Cancer Center (FUSCC) were extracted. Propensity score matching analysis, linear models for microarray data VOOM method, least absolute shrinkage and selection operation Cox regression modeling analysis was conducted in turn for selecting multi-mRNA signature. Survival differences were assessed by Kaplan-Meier estimate and compared using log-rank test. Multivariable Cox regression and time-dependent receiver operating characteristic curves were used to evaluate the association of mRNAs signature with relapse-free survival (RFS). Results: Seventeen mRNAs were identified to constitute the early-relapse signature. Among patients with stage I-III RCC, those with high-risk score calculated from 17 mRNAs signature showed shorter RFS than those with low-risk score, both in TCGA discovery and internal validation sets, and in FUSCC discovery and internal validation sets (all p < 0.05). In multivariable Cox regression analysis, the 17 mRNAs signature remained an independent prognostic factor both in TCGA discovery (HR 2.43, 95%CI 1.98-2.96) and internal validation sets (HR 1.66, 95%CI 1.19-2.30), and FUSCC discovery (HR 1.28, 95%CI 1.13-1.43) and internal validation sets (HR 1.65, 95%CI 1.11-2.48). Additionally, the 17 mRNAs signature achieved a higher accuracy for RFS estimation beyond clinical indicator. Conclusion: The 17 mRNAs signature could classify stage I-III RCC patients into low- or high-risk of early-relapse, and will help to guide interventions to optimize survival outcomes.