Characterization of 3D Organotypic Culture of Mouse Adipose-Derived Stem Cells.

Although stem cells are a promising avenue for harnessing the potential of adipose tissue, conventional two-dimensional (2D) culture methods have limitations. This study explored the use of three-dimensional (3D) cultures to preserve the regenerative potential of adipose-derived stem cells (ADSCs) and investigated their cellular properties. Flow cytometric analysis revealed significant variations in surface marker expressions between the two culture conditions. While 2D cultures showed robust surface marker expressions, 3D cultures exhibited reduced levels of CD44, CD90.2, and CD105. Adipogenic differentiation in 3D organotypic ADSCs faced challenges, with decreased organoid size and limited activation of adipogenesis-related genes. Key adipocyte markers, such as lipoprotein lipase (LPL) and adipoQ, were undetectable in 3D-cultured ADSCs, unlike positive controls in 2D-cultured mesenchymal stem cells (MSCs). Surprisingly, 3D-cultured ADSCs underwent mesenchymal-epithelial transition (MET), evidenced by increased E-cadherin and EpCAM expression and decreased mesenchymal markers. This study highlights successful ADSC organoid formation, notable MSC phenotype changes in 3D culture, adipogenic differentiation challenges, and a distinctive shift toward an epithelial-like state. These findings offer insights into the potential applications of 3D-cultured ADSCs in regenerative medicine, emphasizing the need for further exploration of underlying molecular mechanisms.

COL6A1 expression as a potential prognostic biomarker for risk stratification of T1 high grade bladder cancer: Unveiling the aggressive nature of a distinct non-muscle invasive subtype.

PURPOSE: T1 high grade (T1HG) bladder cancer (BC) is a type of non-muscle invasive BC (NMIBC) that is recognized as an aggressive subtype with a heightened propensity for progression. Current risk stratification methods for NMIBC rely on clinicopathological indicators; however, these approaches do not adequately capture the aggressive nature of T1HG BC. Thus, new, more accurate biomarkers for T1HG risk stratification are needed. Here, we enrolled three different patient cohorts and investigated expression of collagen type VI alpha 1 (COL6A1), a key component of the extracellular matrix, at different stages and grades of BC, with a specific focus on T1HG BC. MATERIALS AND METHODS: Samples from 298 BC patients were subjected to RNA sequencing and real-time polymerase chain reaction. RESULTS: We found that T1HG BC and muscle invasive BC (MIBC) exhibited comparable expression of COL6A1, which was significantly higher than that by other NMIBC subtypes. In particular, T1HG patients who later progressed to MIBC had considerably higher expression of COL6A1 than Ta, T1 low grade patients, and patients that did not progress, highlighting the aggressive nature and higher risk of progression associated with T1HG BC. Moreover, Cox and Kaplan-Meier survival analyses revealed a significant association between elevated expression of COL6A1 and poor progression-free survival of T1HG BC patients (multivariate Cox hazard ratio, 16.812; 95% confidence interval, 3.283-86.095; p=0.001 and p=0.0002 [log-rank test]). CONCLUSIONS: These findings suggest that COL6A1 may be a promising biomarker for risk stratification of T1HG BC, offering valuable insight into disease prognosis and guidance of personalized treatment decisions.

Multitask Learning-Based Deep Signal Identification for Advanced Spectrum Sensing.

The explosive demand for wireless communications has intensified the complexity of spectrum dynamics, particularly within unlicensed bands. To promote efficient spectrum utilization and minimize interference during communication, spectrum sensing needs to evolve to a stage capable of detecting multidimensional spectrum states. Signal identification, which identifies each device's signal source, is a potent method for deriving the spectrum usage characteristics of wireless devices. However, most existing signal identification methods mainly focus on signal classification or modulation classification, thus offering limited spectrum information. In this paper, we propose DSINet, a multitask learning-based deep signal identification network for advanced spectrum sensing systems. DSINet addresses the deep signal identification problem, which involves not only classifying signals but also deriving the spectrum usage characteristics of signals across various spectrum dimensions, including time, frequency, power, and code. Comparative analyses reveal that DSINet outperforms existing shallow signal identification models, with performance improvements of 3.3% for signal classification, 3.3% for hall detection, and 5.7% for modulation classification. In addition, DSINet solves four different tasks with a 65.5% smaller model size and 230% improved computational performance compared to single-task learning model sets, providing meaningful results in terms of practical use.

Weight maintenance and gain were significantly associated with lower risk of all-cause and cancer-related mortality in Korean adults who were newly diagnosed with cancer based on the Korean NHIS-HEALS cohort.

The burden of malignant neoplasms is increasing worldwide. Healthy lifestyles such as maintaining a healthy body weight are important to improve survival rate in cancer patients. This study was aimed to test the hypothesis that weight change affects mortality in patients newly diagnosed with cancer. This study was retrospectively designed based on the National Health Insurance Service-National Health Screening Cohort. A total of 1856 subjects aged at least 40 years who received a national health checkup within 6 months before cancer diagnosis was included. Study subjects were classified into 3 categories based on weight change before and after cancer diagnosis: weight loss, maintenance, and gain. Cox proportional hazards regression models were adopted to examine the association between weight change and mortality after adjusting for confounders. Compared to those experiencing weight loss, the adjusted hazards ratios (HRs) (95% confidence intervals [CIs]) for those experiencing weight maintenance were 0.327 (0.189-0.568) for all-cause mortality and 0.431 (0.215-0.867) for cancer-related mortality. The adjusted HRs (95% CIs) for those experiencing weight gain were 0.149 (0.044-0.505) for all-cause mortality and 0.289 (0.080-1.045) for cancer-related mortality. After stratifying according to baseline body mass index (BMI), weight maintenance and gain were negatively associated with all-cause mortality (0.286 [0.138-0.592] for weight maintenance and 0.119 [0.027-0.533] for weight gain) among those with a BMI < 25 kg/m2. Weight maintenance and gain reduced the risk of all-cause mortality in patients newly diagnosed with any cancer. In addition, weight maintenance was significantly related to cancer-related mortality.

Developmental delay and non-phenylketonuria (PKU) hyperphenylalaninemia in DNAJC12 deficiency: Case and approach.

BACKGROUND: Hyperphenylalaninemia is a biomarker for several monogenic neurotransmitter disorders where the body cannot metabolise phenylalanine to tyrosine. Biallelic pathogenic variants in DNAJC12, co-chaperone of phenylalanine, tyrosine, and tryptophan hydroxylases, leads to hyperphenylalaninemia and biogenic amines deficiency. METHODS AND RESULTS: A male firstborn to non-consanguineous Sudanese parents had hyperphenylalaninemia 247 µmol/L [reference interval (RI) < 200 µmol/L] at newborn screening. Dried blood spot dihydropteridine reductase (DHPR) assay and urine pterins were normal. He had severe developmental delay and autism spectrum disorder without a notable movement disorder. A low phenylalanine diet was introduced at two years without any clinical improvements. Cerebrospinal fluid (CSF) neurotransmitters at five years demonstrated low homovanillic acid (HVA) 0.259 µmol/L (reference interval (RI) 0.345-0.716) and 5-hydroxyindoleaetic acid (5HIAA) levels 0.024 µmol/L (reference interval (RI) 0.100-0.245). Targeted neurotransmitter gene panel analysis identified a homozygous c.78 + 1del variant in DNAJC12. At six years, he was commenced on 5-hydroxytryptophan 20 mg daily, and his protein-restricted diet was liberalised, with continued good control of phenylalanine levels. Sapropterin dihydrochloride 7.2 mg/kg/day was added the following year with no observable clinical benefits. He remains globally delayed with severe autistic traits. CONCLUSIONS: Urine, CSF neurotransmitter studies, and genetic testing will differentiate between phenylketonuria, tetrahydrobiopterin or DNAJC12 deficiency, with the latter characterised by a clinical spectrum ranging from mild autistic features or hyperactivity to severe intellectual disability, dystonia, and movement disorder, normal DHPR, reduced CSF HIAA and HVA. DNAJC12 deficiency should be considered early in the differential workup of hyperphenylalaninemia identified from newborn screening, with its genotyping performed once deficiencies of phenylalanine hydroxylase (PAH) and tetrahydrobiopterin (BH4) have been biochemically or genetically excluded.

Evaluation of Radiation Sensitivity Differences in Mouse Liver Tumor Organoids Using CRISPR/Cas9-Mediated Gene Mutation.

BACKGROUND: To assess the radiosensitivity of liver tumors harboring different genetic mutations, mouse liver tumors were generated in vivo through the hydrodynamic injection of clustered regularly interspaced short palindromic repeat/caspase 9 (CRISPR/Cas9) constructs encoding single-guide RNAs (sgRNAs) targeting Tp53, Pten, Nf1, Nf2, Tsc2, Cdkn2a, or Rb1. METHODS: The plasmid vectors were delivered to the liver of adult C57BL/6 mice via hydrodynamic tail vein injection. The vectors were injected into 10 mice in each group. Organoids were generated from mouse liver tumors. The radiation response of the organoids was assessed using an ATP cell viability assay. RESULTS: The mean survival period of mice injected with vectors targeting Nf2 (4.8 months) was lower than that of other mice. Hematoxylin and eosin staining, immunohistochemical (IHC) staining, and target sequencing analyses revealed that mouse liver tumors harbored the expected mutations. Tumor organoids were established from mouse liver tumors. Histological evaluation revealed marked morphological similarities between the mouse liver tumors and the generated tumor organoids. Moreover, IHC staining indicated that the parental tumor protein expression pattern was maintained in the organoids. The results of the ATP cell viability assay revealed that the tumor organoids with mutated Nf2 were more resistant to high-dose radiation than those with other gene mutations. CONCLUSIONS: This study developed a radiation response assessment system for mouse tumors with mutant target genes using CRISPR/Cas9 and organoids. The Tp53 and Pten double mutation in combination with the Nf2 mutation increased the radiation resistance of tumors. The system used in this study can aid in elucidating the mechanism underlying differential intrinsic radiation sensitivity of individual tumors.

Current treatment patterns within 1 year after prostate cancer diagnosis in Korean patients over 75 years old: a retrospective multicenter study.

Background: We aimed to evaluate the current status of first-line treatment options for prostate cancer in patients aged ≥75 years in Korea. Materials and methods: The study included 873 patients diagnosed with biopsy-proven prostate cancer at 5 institutions in Korea from January 2009 to December 2018. Inclusion criteria were aged ≥75 years at diagnosis, prostate biopsy with ≥12 cores, and follow-up period ≥1 year. Clinical data were retrospectively collected from electronic medical records. Results: Primary treatment for prostate cancer in patients aged ≥75 years included androgen deprivation therapy (ADT) (n = 614), radical prostatectomy (RP) (n = 114), and radiation therapy (n = 62). Among patients with RP, nine patients received ADT before RP. The RP group was younger with better Eastern Cooperative Oncology Group Performance Status (ECOG PS), lower initial prostate-specific antigen (PSA), Gleason score (GS), max percent positive cores, less positive cores, and less advanced clinical Tumor Node Metastasis (TNM) stage compared with the ADT group. Multivariate analysis showed that age, ECOG PS, and PSA were independent prognostic factors for RP. When the ADT group was classified by therapeutic regimens, the most common therapeutic regimen was maximal androgen blockade (MAB) (n = 571), and leuprolide + bicalutamide (n = 330) was the most common MAB regimen. Multivariate analysis for secondary treatment showed that age, ECOG PS, GS, and clinical N1 or M1 stage were independent predictive factors. Enzalutamide was the most preferred treatment for tertiary treatment. Conclusion: In patients with prostate cancer aged ≥75 years, the most common treatment option was MAB, and the leuprolide + bicalutamide was the most common MAB regimen. Age, ECOG PS, and PSA are the useful indicators of surgical treatment, which increased during the study period. Younger patients with high GS and advanced clinical stage were more likely to undergo secondary treatment.

A New Treatment Landscape for RCC: Association of the Human Microbiome with Improved Outcomes in RCC.

Microbes play different roles in metabolism, local or systemic inflammation, and immunity, and the human microbiome in tumor microenvironment (TME) is important for modulating the response to immunotherapy in cancer patients. Renal cell carcinoma (RCC) is an immunogenic tumor, and immunotherapy is the backbone of its treatment. Correlations between the microbiome and responsiveness to immune checkpoint inhibitors have been reported. This review summarizes the recent therapeutic strategies for RCC and the effects of TME on the systemic therapy of RCC. The current understanding and advances in microbiome research and the relationship between the microbiome and the response to immunotherapy for RCC are also discussed. Improving our understanding of the role of the microbiome in RCC treatment will facilitate the development of microbiome targeting therapies to modify the tumor microbiome and improve treatment outcomes.

DRL-OS: A Deep Reinforcement Learning-Based Offloading Scheduler in Mobile Edge Computing.

Hardware bottlenecks can throttle smart device (SD) performance when executing computation-intensive and delay-sensitive applications. Hence, task offloading can be used to transfer computation-intensive tasks to an external server or processor in Mobile Edge Computing. However, in this approach, the offloaded task can be useless when a process is significantly delayed or a deadline has expired. Due to the uncertain task processing via offloading, it is challenging for each SD to determine its offloading decision (whether to local or remote and drop). This study proposes a deep-reinforcement-learning-based offloading scheduler (DRL-OS) that considers the energy balance in selecting the method for performing a task, such as local computing, offloading, or dropping. The proposed DRL-OS is based on the double dueling deep Q-network (D3QN) and selects an appropriate action by learning the task size, deadline, queue, and residual battery charge. The average battery level, drop rate, and average latency of the DRL-OS were measured in simulations to analyze the scheduler performance. The DRL-OS exhibits a lower average battery level (up to 54%) and lower drop rate (up to 42.5%) than existing schemes. The scheduler also achieves a lower average latency of 0.01 to >0.25 s, despite subtle case-wise differences in the average latency.

Utility of a Molecular Signature for Predicting Recurrence and Progression in Non-Muscle-Invasive Bladder Cancer Patients: Comparison with the EORTC, CUETO and 2021 EAU Risk Groups.

To evaluate the utility of different risk assessments in non-muscle-invasive bladder cancer (NMIBC) patients, a total of 178 NMIBC patients from Chungbuk National University Hospital (CBNUH) were enrolled, and the predictive value of the molecular signature-based subtype predictor (MSP888) and risk calculators based on clinicopathological factors (EORTC, CUETO and 2021 EAU risk scores) was compared. Of the 178 patients, 49 were newly analyzed by the RNA-sequencing, and their MSP888 subtype was evaluated. The ability of the EORTC, MSP888 and two molecular subtyping systems of bladder cancer (Lund and UROMOL subtypes) to predict progression of 460 NMIBC patients from the UROMOL project was assessed. Cox regression analyses showed that the MSP888 was an independent predictor of NMIBC progression in the CBNUH cohort (p = 0.043). Particularly in patients without an intravesical BCG immunotherapy, MSP888 significantly linked with risk of disease recurrence and progression (both p < 0.05). However, the EORTC, CUETO and 2021 EAU risk scores showed disappointing results with respect to estimating the NMIBC prognosis. In the UROMOL cohort, the MSP888, Lund and UROMOL subtypes demonstrated a similar capacity to predict NMIBC progression (all p < 0.05). Conclusively, the MSP888 is favorable for stratifying patients to facilitate optimal treatment.

Study on the use of Nanostring nCounter to analyze RNA extracted from formalin-fixed-paraffin-embedded and fresh frozen bladder cancer tissues.

Formalin-fixed paraffin-embedded (FFPE) tissue is the most common source of archived material for genomic medicine. However, FFPE tissue is suboptimal for high-throughput analyses, such as RNA sequencing, because the quality of nucleic acids in FFPE tissues is low. We compared RNA-seq with the nCounter system to evaluate use of FFPE tissue for genomic medicine. Twelve fresh frozen bladder cancer samples were analyzed by both RNA sequencing and nCounter, and matched FFPE samples, by nCounter. Gene-expression values obtained by these two platforms were compared by calculating Pearson correlation coefficients for each sample (across the set of matched genes) and for each matched gene (across the set of samples). For each sample, gene-expression levels measured by RNA sequencing highly correlated with those measured by nCounter (all Pearson's R > 0.8, P < 0.0001), as seen by hierarchical clustering. RNA sequencing results for fresh frozen tissues positively correlated with nCounter results for FFPE tissues (R ranged from 0.675 to 0.873, all P < 0.0001). Correlation and hierarchical-clustering analyses of nCounter data from the two specimens demonstrated a strong positive correlation between each group (R ranged from 0.779 to 0.977, all P < 0.0001). Our findings suggest that the nCounter system is useful for assaying archived-FFPE samples and that the gene-expression signatures obtained from FFPE samples represent those from fresh frozen tissues.

3-Methylglutaconyl-CoA hydratase deficiency: When ascertainment bias confounds a biochemical diagnosis.

3-Methylglutaconyl-CoA hydratase deficiency (MGA1) is a defect in leucine catabolism, which causes the accumulation of urinary 3-methylglutaconate, with or without 3-hydroxyisovalerate and 3-methylglutarate. It is an ultra-rare condition, with <30 cases published in the literature. It is unclear whether the clinical features seen in reported patients are caused by the biochemical abnormalities, or whether they simply represent an ascertainment bias in patients that come to clinical attention. We reviewed the collective Australian experience of patients with confirmed MGA1, four of whom were diagnosed when asymptomatic through newborn screening (NBS). When our cohort is considered alongside the broader literature, there is no clear evidence of a specific childhood-onset clinical phenotype associated with this disorder. Some patients have non-specific clinical features (such as autism spectrum disorder [ASD]); however, there are also other family members with ASD in the absence of MGA1, suggesting a multifactorial aetiology. Importantly, all four patients diagnosed through NBS (including three with over 18 years of clinical follow-up) remain asymptomatic in the absence of treatment. Based on the available literature, we suggest that MGA1 represents a biochemical phenotype, with an absence of a childhood clinical phenotype. The burdens of sustained treatment (particularly with intensive dietary leucine restriction) in asymptomatic individuals may be of little benefit, and likely to result in poor compliance. Longer-term follow-up of patients detected via NBS (or biochemical screening of large cohorts of asymptomatic adult individuals) will be required to conclusively prove or disprove the association with adult-onset leukoencephalopathy.

How can we best manage biochemical failure after radical prostatectomy?

Biochemical recurrence (BCR) is common after radical prostatectomy, but effective treatment options for men with BCR after curative treatment remain controversial. Although prostate-specific antigen is widely used as a surrogate marker for prostate cancer survival, it cannot fully differentiate between prostate-cancer-specific survival and overall survival. Thus, it is challenging for physicians to determine the timing of treatment to halt or slow the clinical progression of disease in patients with BCR while avoiding overtreatment for patients whose disease may not progress beyond BCR. Adjuvant therapy for radical prostatectomy or radiotherapy in intermediate- or high-risk localized prostate cancer has a benefit in terms of disease progression and survival but is not recommended in low-risk prostate cancer because of the significant adverse effects related to radiotherapy and androgen-deprivation therapy (ADT). Salvage radiotherapy (SRT) is also recommended for patients with BCR after radical prostatectomy. Several options for management of BCR after radical prostatectomy include SRT to the prostatic bed and/or pelvis, continuous or intermittent ADT, or observation. Patients' comorbidity, preferences, and cancer-related factors must be considered when deciding the best management strategy. Modern imaging technology such as positron emission tomography imaging of prostate-specific membrane antigen-positive regions enables earlier detection of disease progression, thus enhancing decision making for future disease management.

Secretory SERPINE1 Expression Is Increased by Antiplatelet Therapy, Inducing MMP1 Expression and Increasing Colon Cancer Metastasis.

Contrary to many reports that antiplatelet agents inhibit cancer growth and metastasis, new solid tumors have been reported in patients receiving long-term antiplatelet therapy. We investigated the effects of these agents directly on cancer cells in the absence of platelets to mimic the effects of long-term therapy. When four antiplatelet agents (aspirin, clopidogrel, prasugrel, and ticagrelor) were administered to colon cancer cells, cancer cell proliferation was inhibited similarly to a previous study. However, surprisingly, when cells were treated with a purinergic P2Y12 inhibitor (purinergic antiplatelet agent), the motility of the cancer cells was significantly increased. Therefore, gene expression profiles were identified to investigate the effect of P2Y12 inhibitors on cell mobility, and Serpin family 1 (SERPINE1) was identified as a common gene associated with cell migration and cell death in three groups. Antiplatelet treatment increased the level of SERPINE1 in cancer cells and also promoted the secretion of SERPINE1 into the medium. Increased SERPINE1 was found to induce MMP1 and, thus, increase cell motility. In addition, an increase in SERPINE1 was confirmed using the serum of patients who received these antiplatelet drugs. With these results, we propose that SERPINE1 could be used as a new target gene to prevent the onset and metastasis of cancer in patients with long-term antiplatelet therapy.

Observation of spin-glass-like characteristics in ferrimagnetic TbCo through energy-level-selective approach.

Rare earth (RE)-transition metal (TM) ferrimagnetic alloys are gaining increasing attention because of their potential use in the field of antiferromagnetic spintronics. The moment from RE sub-lattice primarily originates from the 4f-electrons located far below the Fermi level (EF), and the moment from TM sub-lattice arises from the 3d-electrons across the EF. Therefore, the individual magnetic moment configurations at different energy levels must be explored to clarify the microscopic mechanism of antiferromagnetic spin dynamics. Considering these issues, here we investigate the energy-level-selective magnetic moment configuration in ferrimagnetic TbCo alloy. We reveal that magnetic moments at deeper energy levels are more easily altered by the external magnetic field than those near the EF. More importantly, we find that the magnetic moments at deeper energy levels exhibit a spin-glass-like characteristics such as slow dynamics and magnetic moment freezing whereas those at EF do not. These unique energy-level-dependent characteristics of RE-TM ferrimagnet may provide a better understanding of ferrimagnet, which could be useful in spintronic applications as well as in spin-glass studies.

A Semantic Data-Based Distributed Computing Framework to Accelerate Digital Twin Services for Large-Scale Disasters.

As natural disasters become extensive, due to various environmental problems, such as the global warming, it is difficult for the disaster management systems to rapidly provide disaster prediction services, due to complex natural phenomena. Digital twins can effectively provide the services using high-fidelity disaster models and real-time observational data with distributed computing schemes. However, the previous schemes take little account of the correlations between environmental data of disasters, such as landscapes and weather. This causes inaccurate computing load predictions resulting in unbalanced load partitioning, which increases the prediction service times of the disaster management agencies. In this paper, we propose a novel distributed computing framework to accelerate the prediction services through semantic analyses of correlations between the environmental data. The framework combines the data into disaster semantic data to represent the initial disaster states, such as the sizes of wildfire burn scars and fuel models. With the semantic data, the framework predicts computing loads using the convolutional neural network-based algorithm, partitions the simulation model into balanced sub-models, and allocates the sub-models into distributed computing nodes. As a result, the proposal shows up to 38.5% of the prediction time decreases, compared to the previous schemes.

A Novel Digital Twin Architecture with Similarity-Based Hybrid Modeling for Supporting Dependable Disaster Management Systems.

Disaster management systems require accurate disaster monitoring and prediction services to reduce damages caused by natural disasters. Digital twins of natural environments can provide the services for the systems with physics-based and data-driven disaster models. However, the digital twins might generate erroneous disaster prediction due to the impracticability of defining high-fidelity physics-based models for complex natural disaster behavior and the dependency of data-driven models on the training dataset. This causes disaster management systems to inappropriately use disaster response resources, including medical personnel, rescue equipment and relief supplies, to ensure that it may increase the damages from the natural disasters. This study proposes a digital twin architecture to provide accurate disaster prediction services with a similarity-based hybrid modeling scheme. The hybrid modeling scheme creates a hybrid disaster model that compensates for the errors of physics-based prediction results with a data-driven error correction model to enhance the prediction accuracy. The similarity-based hybrid modeling scheme reduces errors from the data dependency of the hybrid model by constructing a training dataset using similarity assessments between the target disaster and the historical disasters. Evaluations in wildfire scenarios show that the digital twin decreases prediction errors by approximately 50% compared with those of the existing schemes.

Expression of RPL9 predicts the recurrence of non-muscle invasive bladder cancer with BCG therapy.

Numerous biomarkers and risk tables can be used to predict recurrence or progression of patients with primary or recurrent non-muscle invasive bladder cancer (NMIBC) receiving Bacillus Calmette-Guerin (BCG). However, few are suitable for BCG-unresponsive disease (i.e., recurrence or progression after BCG treatment). Therefore, identification of a novel marker that allows accurate prediction of prognosis, particularly risk of recurrence, is critically important in clinical practice. In the current study, gene ontology and gene set enrichment analyses of microarray datasets (GSE13507, n = 47) revealed that differentially expressed genes in recurred NMIBC patients after BCG treatment were associated with virus and ribosomal pathways. Among the core-enrichment genes, the expression of RPL9, a putative tumor suppressor, was lower in recurred NMIBC patients after BCG therapy than in patients without recurrence (P = 0.033) from the E-MTAT-4321 European cohort (n = 84). Data from The Cancer Genome Atlas (n = 406) showed that bladder cancer patients with higher RPL9 expression had a longer overall survival probability than patients with lower RPL9 expression (P = 0.011). Moreover, we used the latest digital PCR platform to examine 59 NMIBC patients and identified downregulation of RPL9 in patients with recurrence after BCG therapy (P = 0.031). The Kaplan-Meier survival estimator showed that NMIBC patients with higher expression of RPL9 had longer recurrence-free survival (log-rank test, P = 0.015). Therefore, we conclude that RPL9 expression is a prospective predictor of recurrence after BCG therapy in NMIBC patients.