The RIG-I-NRF2 axis regulates the mesenchymal stromal niche for bone marrow transplantation.

Bone marrow-derived mesenchymal stem cells (BMSCs) support bone formation and constitute the stromal niche in regulating hematopoietic stem cells (HSCs). Stromal niche dysfunction affects HSC engraftment during transplantation; however, the underlying mechanisms remain elusive. In the present study, we found that all-trans retinoic acid (ATRA) and inflammation stress upregulated retinoic acid-inducible gene I (RIG-I) in BMSCs. Excess RIG-I expression damaged the clonogenicity, bone-forming ability of BMSCs and particularly their stromal niche function that supports HSC expansion in vitro and engraftment in vivo. Mechanistically, RIG-I elevation promoted the degradation of NRF2, a checkpoint for antioxidant cellular response, by altering the RIG-I-Trim25-Keap1-NRF2 complex, leading to reactive oxygen species (ROS) accumulation and BMSC damage. Genetic inhibition of RIG-I sustained NRF2 protein levels and reduced ROS levels in ATRA-treated BMSCs, thus preserving their clonogenicity, bone-forming ability, and stromal niche function in supporting HSC engraftment in mice. More importantly, RIG-I inhibition recovered the ATRA-treated stromal niche function to enhance HSC engraftment and emergency myelopoiesis for innate immunity against the bacterium Listeria monocytogenes during transplantation. Overall, we identified a noncanonical role of RIG-I in the regulation of the stromal niche for HSC transplantation.

Fatty acids metabolism affects the therapeutic effect of anti-PD-1/PD-L1 in tumor immune microenvironment in clear cell renal cell carcinoma.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is a highly invasive and metastatic subtype of kidney malignancy and is correlated with metabolic reprogramming for adaptation to the tumor microenvironment comprising infiltrated immune cells and immunomodulatory molecules. The role of immune cells in the tumor microenvironment (TME) and their association with abnormal fatty acids metabolism in ccRCC remains poorly understood. METHOD: RNA-seq and clinical data of KIRC from The Cancer Genome Atlas (TCGA) and E-MTAB-1980 from the ArrayExpress dataset. The Nivolumab group and Everolimus group of the CheckMate 025 study, the Atezolizumab arm of IMmotion150 and the Atezolizumab plus Bevacizumab group of IMmotion151 cohort were obtained for subsequent analysis. After differential expression genes identification, the signature was constructed through univariate Cox proportional hazard regression and simultaneously the least absolute shrinkage and selection operator (Lasso) analysis and the predictive performance of our signature was assessed by using receiver operating characteristic (ROC), Kaplan-Meier (KM) survival analysis, nomogram, drug sensitivity analysis, immunotherapeutic effect analysis and enrichment analysis. Immunohistochemistry (IHC), qPCR and western blot were performed to measure related mRNA or protein expression. Biological features were evaluated by wound healing, cell migration and invasion assays and colony formation test and analyzed using coculture assay and flow cytometry. RESULTS: Twenty fatty acids metabolism-related mRNA signatures were constructed in TCGA and possessed a strong predictive performance demonstrated through time-dependent ROC and KM survival analysis. Notably, the high-risk group exhibited an impaired response to anti-PD-1/PD-L1 (Programmed death-1 receptor/Programmed death-1 receptor-ligand) therapy compared to the low-risk group. The overall levels of the immune score were higher in the high-risk group. Additionally, drug sensitivity analysis observed that the model could effectively predict efficacy and sensitivity to chemotherapy. Enrichment analysis revealed that the IL6-JAK-STAT3 signaling pathway was a major pathway. IL4I1 could promote ccRCC cells' malignant features through JAK1/STAT3 signaling pathway and M2-like macrophage polarization. CONCLUSION: The study elucidates that targeting fatty acids metabolism can affect the therapeutic effect of PD-1/PD-L1 in TME and related signal pathways. The model can effectively predict the response to several treatment options, underscoring its potential clinical utility.

circCHST15 is a novel prognostic biomarker that promotes clear cell renal cell carcinoma cell proliferation and metastasis through the miR-125a-5p/EIF4EBP1 axis.

BACKGROUND: Circular RNAs (circRNAs) have been indicated as potentially critical mediators in various types of tumor progression, generally acting as microRNA (miRNA) sponges to regulate downstream gene expression. However, the aberrant expression profile and dysfunction of circRNAs in human clear cell renal cell carcinoma (ccRCC) need to be further investigated. This study mined key prognostic circRNAs and elucidates the potential role and molecular mechanism of circRNAs in regulating the proliferation and metastasis of ccRCC. METHODS: circCHST15 (hsa_circ_0020303) was identified by mining two circRNA microarrays from the Gene Expression Omnibus database and comparing matched tumor versus adjacent normal epithelial tissue pairs or matched primary versus metastatic tumor tissue pairs. These results were validated by quantitative real-time polymerase chain reaction and agarose gel electrophoresis. We demonstrated the biological effect of circCHST15 in ccRCC both in vitro and in vivo. To test the interaction between circCHST15 and miRNAs, we conducted a number of experiments, including RNA pull down assay, dual-luciferase reporter assay and fluorescence in situ hybridization. RESULTS: The expression of circCHST15 was higher in ccRCC tissues compared to healthy adjacent kidney tissue and higher in RCC cell lines compared to normal kidney cell lines. The level of circCHST15 was positively correlated with aggressive clinicopathological characteristics, and circCHST15 served as an independent prognostic indicator for overall survival and progression-free survival in patients with ccRCC after surgical resection. Our in vivo and in vitro data indicate that circCHST15 promotes the proliferation, migration, and invasion of ccRCC cells. Mechanistically, we found that circCHST15 directly interacts with miR-125a-5p and acts as a microRNA sponge to regulate EIF4EBP1 expression. CONCLUSIONS: We found that sponging of miR-125a-5p to promote EIF4EBP1 expression is the underlying mechanism of hsa_circ_0020303-induced ccRCC progression. This prompts further investigation of circCHST15 as a potential prognostic biomarker and therapeutic target for ccRCC.

A nomogram based on TFE3 IHC results and clinical factors as a preliminary screening scheme for TFE3-rearranged renal cell carcinoma.

BACKGROUND: TFE3 immunohistochemistry (TFE3-IHC) is controversial in the diagnosis of TFE3-rearranged renal cell carcinoma (TFE3-rearranged RCC). This study is to investigate the accuracy and sensitivity of IHC and establish a predictive model to diagnose TFE3-rearranged RCC. METHODS: Retrospective analysis was performed by collecting IHC and fluorescence in situ hybridization (FISH) results from 228 patients. IHC results were evaluated using three scoring systems. Scoring system 1 is graded based on nuclear staining intensity, scoring system 2 is graded based on the percentage of stained tumor cell nuclei, and scoring system 3 is graded based on both the nuclear staining intensity and the percentage. We collected patients' IHC results and clinical information. Important variables were screened based on univariate logistic regression analysis. Then, independent risk factors were established through multivariate logistic regression, and a nomogram model was constructed. The model was validated in internal test set and external validation set. The receiver operating characteristic curve (ROC curve), calibration curve, and decision curve analysis (DCA) were generated to assess discriminative ability of the model. RESULTS: The accuracy of IHC based on three scoring systems were 0.829, 0.772, and 0.807, respectively. The model included four factors including age, gender, lymph node metastasis and IHC results. Area under the curve (AUC) values were 0.935 for the training set, 0.934 for the internal test set, 0.933 for all 228 patients, and 0.916 for the external validation set. CONCLUSIONS: TFE3 IHC has high accuracy in the diagnosis of TFE3-rearranged RCC. Clinical information such as age and lymph node metastasis are independent risk factors, which can be used as a supplement to the results of TFE3 IHC. This study confirms the value of IHC in the diagnosis of TFE3-rearranged RCC. The accuracy of the diagnosis can be improved by incorporating IHC with other clinical risk factors.

ZNF397 Deficiency Triggers TET2-driven Lineage Plasticity and AR-Targeted Therapy Resistance in Prostate Cancer.

Cancer cells exhibit phenotypical plasticity and epigenetic reprogramming, which allows them to evade lineage-dependent targeted treatments by adopting lineage plasticity. The underlying mechanisms by which cancer cells exploit the epigenetic regulatory machinery to acquire lineage plasticity and therapy resistance remain poorly understood. We identified Zinc Finger Protein 397 (ZNF397) as a bona fide coactivator of the androgen receptor (AR), essential for the transcriptional program governing AR-driven luminal lineage. ZNF397 deficiency facilitates the transition of cancer cell from an AR-driven luminal lineage to a Ten-Eleven Translocation 2 (TET2)-driven lineage plastic state, ultimately promoting resistance to therapies inhibiting AR signaling. Intriguingly, our findings indicate that a TET2 inhibitor can eliminate the resistance to AR targeted therapies in ZNF397-deficient tumors. These insights uncover a novel mechanism through which prostate cancer acquires lineage plasticity via epigenetic rewiring and offer promising implications for clinical interventions designed to overcome therapy resistance dictated by lineage plasticity.

Development and external validation of the multichannel deep learning model based on unenhanced CT for differentiating fat-poor angiomyolipoma from renal cell carcinoma: a two-center retrospective study.

PURPOSE: There are undetectable levels of fat in fat-poor angiomyolipoma. Thus, it is often misdiagnosed as renal cell carcinoma. We aimed to develop and evaluate a multichannel deep learning model for differentiating fat-poor angiomyolipoma (fp-AML) from renal cell carcinoma (RCC). METHODS: This two-center retrospective study included 320 patients from the First Affiliated Hospital of Sun Yat-Sen University (FAHSYSU) and 132 patients from the Sun Yat-Sen University Cancer Center (SYSUCC). Data from patients at FAHSYSU were divided into a development dataset (n = 267) and a hold-out dataset (n = 53). The development dataset was used to obtain the optimal combination of CT modality and input channel. The hold-out dataset and SYSUCC dataset were used for independent internal and external validation, respectively. RESULTS: In the development phase, models trained on unenhanced CT images performed significantly better than those trained on enhanced CT images based on the fivefold cross-validation. The best patient-level performance, with an average area under the receiver operating characteristic curve (AUC) of 0.951 ± 0.026 (mean ± SD), was achieved using the "unenhanced CT and 7-channel" model, which was finally selected as the optimal model. In the independent internal and external validation, AUCs of 0.966 (95% CI 0.919-1.000) and 0.898 (95% CI 0.824-0.972), respectively, were obtained using the optimal model. In addition, the performance of this model was better on large tumors (≥ 40 mm) in both internal and external validation. CONCLUSION: The promising results suggest that our multichannel deep learning classifier based on unenhanced whole-tumor CT images is a highly useful tool for differentiating fp-AML from RCC.

Hsa_circ_0057105 modulates a balance of epithelial-mesenchymal transition and ferroptosis vulnerability in renal cell carcinoma.

BACKGROUND: The incidence of renal cell carcinoma (RCC) has increased in recent years. Metastatic RCC is common and remains a major cause of mortality. A regulatory role for circular RNAs (circRNAs) in the occurrence and progression of RCC has been identified, but their function, molecular mechanisms, and potential clinical applications remain poorly understood. METHODS: High-throughput RNA sequencing was used to explore the differential expression of circRNAs and their related pathways in RCC patients. Transwell and CCK-8 assays were used to assess the function of hsa_circ_0057105 in RCC cells. The clinical relevance of hsa_circ_0057105 was evaluated in a cohort of RCC patients. The hsa_circ_0057105 regulatory axis was defined using RNA pull-down, luciferase reporter assays, and fluorescence in situ hybridization assays, and the in vivo effect of hsa_circ_0057105 was validated using animal experiments. RESULTS: Single-sample gene set enrichment analysis and correlation analysis of RNA-seq data showed that hsa_circ_0057105 was potentially oncogenic and may serve to regulate epithelial-mesenchymal transition (EMT) activation in RCC. Hsa_circ_0057105 expression was associated with advanced TNM stages and was an independent prognostic factor for poor RCC patient survival. Phenotypic studies show that hsa_circ_0057105 can enhance the migration and invasion abilities of RCC cells. Further, hsa_circ_0057105 was shown to inhibit the expression of miR-577, a miRNA that regulated the expression of both COL1A1, which induced EMT activation, and VDAC2, which modulated ferroptosis sensitivity. The dual regulatory roles of hsa_circ_0057105 on EMT and ferroptosis sensitivity were verified using rescue experiments. Animal studies confirmed that hsa_circ_0057105 increased the metastatic ability and ferroptosis sensitivity of RCC cells in vivo. CONCLUSIONS: In RCC, hsa_circ_0057105 regulates COL1A1 and VDAC2 expression through its sponge effect on miR-577, acting like a 'double-edged sword'. These findings provide new insight into the relationship between EMT and ferroptosis in RCC and provide potential biomarkers for RCC surveillance and treatment.

Extracellular Vesicle-Mediated Transfer of LncRNA IGFL2-AS1 Confers Sunitinib Resistance in Renal Cell Carcinoma.

Sunitinib resistance remains a serious challenge to the treatment of advanced and metastatic renal cell carcinoma (RCC), yet the mechanisms underlying this resistance are not fully understood. Here, we report that the long noncoding RNA IGFL2-AS1 is a driver of therapy resistance in RCC. IGFL2-AS1 was highly upregulated in sunitinib-resistant RCC cells and was associated with poor prognosis in patients with clear cell RCC (ccRCC) who received sunitinib therapy. IGFL2-AS1 enhanced TP53INP2 expression by competitively binding to hnRNPC, a multifunctional RNA-binding protein that posttranscriptionally suppresses TP53INP2 expression through alternative splicing. Upregulated TP53INP2 enhanced autophagy and ultimately led to sunitinib resistance. Meanwhile, IGFL2-AS1 was packaged into extracellular vesicles through hnRNPC, thus transmitting sunitinib resistance to other cells. N6-methyladenosine modification of IGFL2-AS1 was critical for its interaction with hnRNPC. In a patient-derived xenograft model of sunitinib-resistant ccRCC, injection of chitosan-solid lipid nanoparticles containing antisense oligonucleotide-IGFL2-AS1 successfully reversed sunitinib resistance. These findings indicate a novel molecular mechanism of sunitinib resistance in RCC and suggest that IGFL2-AS1 may serve as a prognostic indicator and potential therapeutic target to overcome resistance. SIGNIFICANCE: Extracellular vesicle-packaged IGFL2-AS1 promotes sunitinib resistance by regulating TP53INP2-triggered autophagy, implicating this lncRNA as a potential therapeutic target in renal cell carcinoma.

Development and validation of a novel defined mutation classifier based on Lasso logistic regression for predicting the overall survival of immune checkpoint inhibitor therapy in renal cell carcinoma.

Background: Currently, immune checkpoint inhibitor (ICI)-based therapy has become the first-line treatment for advanced renal cell carcinoma (RCC). However, few biomarkers have been identified to predict the response to ICI therapy in RCC patients. Herein, our research aimed to build a gene mutation prognostic indicator for ICI therapy. Methods: This multi-cohort study explored the mutation patterns in 2 publicly available advanced RCC ICI therapy cohorts, the Memorial Sloan Kettering Cancer Center (MSKCC) advanced RCC ICI therapy cohort and the CheckMate ICI therapy cohort. A total of 261 patients in the CheckMate ICI therapy cohort were randomly assigned to either the training or validation set. Least absolute shrinkage and selection operator (Lasso) logistic regression analysis was subsequently used to develop a mutation classifier utilizing the training set. The classifier was then validated internally in the validation set and externally in 2 ICI therapy cohorts and 2 non-ICI therapy cohorts. Survival analysis, receiver operator characteristic curves and Harrell's concordance index were performed to assess the prognostic value of the classifier. Function and immune microenvironment analysis in each subgroup defined by the classifier were performed. Results: A 10-gene mutation classifier was constructed based on the CheckMate ICI therapy cohort to separate patients into 2 risk groups, with patients in the high-risk group showing significantly lower overall survival probability than those in the low-risk group [the training set (HR: 1.791; 95% CI: 1.207-2.657; P=0.003), the validation set (HR: 1.842; 95% CI: 1.133-2.996; P=0.012) and combination set (HR: 1.819; 95% CI: 1.339-2.470; P<0.001)]. Further validation confirmed that the mutation classifier only showed predictive value for patients receiving ICI therapy instead of non-ICI therapy. Combined with the clinical characteristics, the risk score was proven to be an independent prognostic factor for overall survival in ICI therapy by multivariate Cox regression analysis. Functional and immune infiltration analysis demonstrated that lower risk scores tended to associate with immunologically "hot" status in RCC. Conclusions: Our 10-gene mutation classifier was found to be a biomarker for predicting the overall survival of patients with advanced RCC to ICI therapy.

Neoadjuvant and adjuvant chemotherapy share equivalent efficacy in improving overall survival and cancer-specific survival among muscle invasive bladder cancer patients who undergo radical cystectomy: a retrospective cohort study based on SEER database.

Background: Although neoadjuvant chemotherapy (NAC) followed by radical cystectomy (RC) have been reported an 6% absolute improvement in 5-year overall survival (OS) for muscle invasive bladder cancer (MIBC), criticism still exists including the delay of surgery and the lack of accurate pathological evidence guidance. Trials have instead focused on adjuvant chemotherapy (AC) but encountered with many difficulties. Convincing data directly compared the treatment efficacy of these 2 strategies are lacking. Methods: We conducted a retrospective cohort study to compare the effectiveness of NAC versus AC among patients with T2-4N0-3M0 bladder cancer using the Surveillance, Epidemiology, and End Results (SEER) database. OS and cancer-specific survival (CSS) were compared using Kaplan-Meier (KM) survival estimators and univariate Cox proportional hazards regression models adjusted for inverse probability of treatment weighting (IPTW). The baseline between groups were compared using standardized mean differences (SMD) approach and kernel density plot. Sensitivity analysis was performed to test the robustness of our results. Results: In total, 1,620 (38.9%) of all eligible patients (4,169) received NAC and 2,549 (61.1%) received AC. After adjusted for propensity score, all baseline characteristics were balanced with SMD <10%. The IPTW-adjusted survival analyses revealed no significant difference in OS between the 2 groups [adjusted hazard ratio (AHR) 1.09, 95% confidence interval (CI): 0.99-1.20, P=0.1]. Exploratory subgroup analysis indicated longer OS among lymph node-negative patients treated with NAC (AHR 1.25, 95% CI: 1.1-1.4, P=0.001), whereas lymph node-positive patients were in favor of AC (AHR 0.85, 95% CI: 0.72-0.99, P=0.043). This treatment heterogeneity according to lymph node status is associated with better prognosis in Stage II (T2N0) patients receiving NAC (AHR 1.28, 95% CI: 1.1-1.6, P=0.014). Meanwhile, in stage III-IV (T3-T4 and/or N+) diseases, NAC shares similar treatment efficacy to AC (AHR 0.98, 95% CI: 0.87-1.1, P=0.762). The analyses of CSS yielded similar, robust results on the effect of potential unmeasured confounding variables. Conclusions: Our population-based study suggests that NAC and AC might be interchangeable in MIBC management, especially in patients with Stage III-IV (T3-T4 and/or N+) diseases. However, this conclusion needs further validation from powerful, robust randomized trials.

A novel 7-chemokine-genes predictive signature for prognosis and therapeutic response in renal clear cell carcinoma.

Background: Renal clear cell carcinoma (ccRCC) is one of the most prevailing type of malignancies, which is affected by chemokines. Chemokines can form a local network to regulate the movement of immune cells and are essential for tumor proliferation and metastasis as well as for the interaction between tumor cells and mesenchymal cells. Establishing a chemokine genes signature to assess prognosis and therapy responsiveness in ccRCC is the goal of this effort. Methods: mRNA sequencing data and clinicopathological data on 526 individuals with ccRCC were gathered from the The Cancer Genome Atlas database for this investigation (263 training group samples and 263 validation group samples). Utilizing the LASSO algorithm in conjunction with univariate Cox analysis, the gene signature was constructed. The Gene Expression Omnibus (GEO) database provided the single cell RNA sequencing (scRNA-seq) data, and the R package "Seurat" was applied to analyze the scRNA-seq data. In addition, the enrichment scores of 28 immune cells in the tumor microenvironment (TME) were calculated using the "ssGSEA" algorithm. In order to develop possible medications for patients with high-risk ccRCC, the "pRRophetic" package is employed. Results: High-risk patients had lower overall survival in this model for predicting prognosis, which was supported by the validation cohort. In both cohorts, it served as an independent prognostic factor. Annotation of the predicted signature's biological function revealed that it was correlated with immune-related pathways, and the riskscore was positively correlated with immune cell infiltration and several immune checkpoints (ICs), including CD47, PDCD1, TIGIT, and LAG-3, while it was negatively correlated with TNFRSF14. The CXCL2, CXCL12, and CX3CL1 genes of this signature were shown to be significantly expressed in monocytes and cancer cells, according to scRNA-seq analysis. Furthermore, the high expression of CD47 in cancer cells suggested us that this could be a promising immune checkpoint. For patients who had high riskscore, we predicted 12 potential medications. Conclusion: Overall, our findings show that a putative 7-chemokine-gene signature might predict a patient's prognosis for ccRCC and reflect the disease's complicated immunological environment. Additionally, it offers suggestions on how to treat ccRCC using precision treatment and focused risk assessment.

EHBP1L1 Drives Immune Evasion in Renal Cell Carcinoma through Binding and Stabilizing JAK1.

High lymphocyte infiltration and immunosuppression characterize the tumor microenvironment (TME) in renal cell carcinoma (RCC). There is an urgent need to elucidate how tumor cells escape the immune attack and to develop novel therapeutic targets to enhance the efficacy of immune checkpoint blockade (ICB) in RCC. Overactivated IFN-γ-induced JAK/STAT signaling involves in such TME, but the underlying mechanisms remain elusive. Here, EH domain-binding protein 1-like protein 1 (EHBP1L1) is identified as a crucial mediator of IFN-γ/JAK1/STAT1/PD-L1 signaling in RCC. EHBP1L1 is highly expressed in RCC, and high EHBP1L1 expression levels are correlated with poor prognosis and resistance to ICB. EHBP1L1 depletion significantly inhibits tumor growth, which is attributed to enhanced CD8+ T cell-mediated antitumor immunity. Mechanistically, EHBP1L1 interacts with and stabilizes JAK1. By competing with SOCS1, EHBP1L1 protects JAK1 from proteasomal degradation, which leads to elevated JAK1 protein levels and JAK1/STAT1/PD-L1 signaling activity, thereby forming an immunosuppressive TME. Furthermore, the combination of EHBP1L1 inhibition and ICB reprograms the immunosuppressive TME and prevents tumor immune evasion, thus significantly reinforcing the therapeutic efficacy of ICB in RCC patient-derived xenograft (PDX) models. These findings reveal the vital role of EHBP1L1 in immune evasion in RCC, which may be a potential complement for ICB therapy.

LZTFL1 inhibits kidney tumor cell growth by destabilizing AKT through ZNRF1-mediated ubiquitin proteosome pathway.

LZTFL1 is a tumor suppressor located in chromosomal region 3p21.3 that is deleted frequently and early in various cancer types including the kidney cancer. However, its role in kidney tumorigenesis remains unknown. Here we hypothesized a tumor suppressive function of LZTFL1 in clear cell renal cell carcinoma (ccRCC) and its mechanism of action based on extensive bioinformatics analysis of patients' tumor data and validated it using both gain- and loss-functional studies in kidney tumor cell lines and patient-derive xenograft (PDX) model systems. Our studies indicated that LZTFL1 inhibits kidney tumor cell proliferation by destabilizing AKT through ZNRF1-mediated ubiquitin proteosome pathway and inducing cell cycle arrest at G1. Clinically, we found that LZTFL1 is frequently deleted in ccRCC. Downregulation of LZTFL1 is associated with a poor ccRCC outcome and may be used as prognostic maker. Furthermore, we show that overexpression of LZTFL1 in PDX via lentiviral delivery suppressed PDX growth, suggesting that re-expression of LZTFL1 may be a therapeutic strategy against ccRCC.

Insight into the Catalytic Activity of Amorphous Multimetallic Catalysts under a Magnetic Field toward the Oxygen Evolution Reaction.

Slow kinetics in the oxygen evolution reaction (OER) remains a Gordian knot to develop an efficient and cost-effective electrocatalyst in electrochemical water splitting. In recent studies, either a synergistic effect on multimetallic catalysts or spin polarization in ferromagnetic materials is considered as a desirable way to improve water electrolysis. Herein, the OER performance of amorphous FeNiCo-based multimetallic catalysts with adjustable composition was investigated from the perspective of atomic structure. Mössbauer spectra results demonstrate that the OER activities exhibit a significant dependence on the local structure of catalysts in which a catalyst with a high content of Fe clusters of low coordination numbers tends to obtain higher activity. Furthermore, benefiting from the spin polarization of these ferromagnetic catalysts, the OER activity is notably enhanced in the presence of a magnetic field. In particular, overpotential reduction exceeding 20 mV (above 100 mA cm-2) in alkaline OER performance is observed for strong ferromagnetic catalysts in comparison with the weak ferromagnetic ones. An increment of 65.2% in turnover frequency is achieved for the catalyst with the strongest ferromagnetism. This magnetic enhancement strategy affords an effective way of improving the water oxidation performance on amorphous ferromagnetic catalysts.

Development of a fully automatic separation system coupled with online ICP-MS for measuring rare earth elements in seawater.

Rare earth elements (REEs) are useful geological indicators of marine geochemistry. However, extremely low concentrations (sub-ng L-1) and high-salt matrices result in inefficient measurements. A fully automatic separation system (ELSPE-2 Precon) is used in the online determination of ultra-trace REEs in seawater using inductively coupled plasma mass spectrometry. This system mainly comprises three sections: (i) an auto-sampler (eas-2A) with 120 positions; (ii) a poly(styrene-divinylbenzene) resin column (Prin-Cen Col007) with iminodiacetic and ethylenediaminetriacetic acid functional groups to eliminate the high-salt matrix (e.g., Na, Ca, K, Mg, Al, Ba, Fe, Sr, P, and S) and preserve the target REEs; and (iii) a Trp002 cleanup column for the reduction of the reagent and procedural blank values. The detection limits (3σ) were in the range 0.002 (Dy)-0.097 ng L-1 (La), and the long-term reproducibility (8 h) was between 80% and 120% for all REEs in a 3.5% NaCl matrix solution. The accuracy of this method was verified using a seawater reference material (NASS-6), and the measured REE concentrations were consistent with those previously reported. The proposed online system was used to investigate coastal water samples with varying salinities from the Pearl River Estuary (Guangdong, China). Variations in the REE distribution patterns of different layers of seawater were observed, which could be due to the mixing of potentially light rare earth element-enriched bottom seawater. Moreover, a positive Gd anomaly in river water and seawater might be attributed to anthropogenic pollution from hospitals and the pharmaceutical industry.

An Aging and Senescence-Related Gene Signature for Prognosis Prediction in Clear Cell Renal Cell Carcinoma.

Background: Clear cell renal cell carcinoma (ccRCC) is the most common solid lesion in the kidney. This study aims to establish an aging and senescence-related mRNA model for risk assessment and prognosis prediction in ccRCC patients. Methods: ccRCC data were obtained from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) datasets. By applying univariate Cox regression, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression, a new prognostic model based on aging and senescence-related genes (ASRGs) was established. Depending on the prognostic model, high- and low-risk groups were identified for further study. The reliability of the prediction was evaluated in the validation cohort. Pan-cancer analysis was conducted to explore the role of GNRH1 in tumors. Results: A novel prognostic model was established based on eight ASRGs. This model was an independent risk factor and significantly correlated with the prognosis and clinicopathological features of ccRCC patients. The high- and low-risk groups exhibited distinct modes in the principal component analysis and different patterns in immune infiltration. Moreover, the nomogram combining risk score and other clinical factors showed excellent predictive ability, with AUC values for predicting 1-, 3-, and 5-year overall survival in the TCGA cohort equal to 0.88, 0.82, and 0.81, respectively. Conclusion: The model and nomogram based on the eight ASRGs had a significant value for survival prediction and risk assessment for ccRCC patients, providing new insights into the roles of aging and senescence in ccRCC.

Identification of ZDHHC1 as a Pyroptosis Inducer and Potential Target in the Establishment of Pyroptosis-Related Signature in Localized Prostate Cancer.

Pyroptosis or cellular inflammatory necrosis is a programmed cell death kind. Accumulating evidence shows that pyroptosis plays a crucial role in the invasion, metastasis, and proliferation of tumor cells, thus affecting the prognosis of tumors and therapeutic effects. Prostate cancer (PCa), a common malignancy among men, is associated with inflammation. Pathophysiological effects of pyroptosis on tumor development and progression, as well as the mediation of PCa, are known, but its effects on the potential prognosis for PCa warrant in-depth investigation. Herein, we built a risk model of six pyroptosis-related genes and verified their predictive abilities for prognostic and therapeutic effects. Higher risk scores indicated a higher probability of biochemical recurrence (BCR), higher immune infiltration, and worsened clinicopathological features. To derive scientific and reliable predictions for BCR in patients having PCa, the findings of the current study were verified in the Gene Expression Omnibus (GEO) cohort following evaluation in The Cancer Genome Atlas (TCGA) dataset. Additionally, after evaluating the six genes in the model, ZDHHC1 was found to be an important component. Its antitumor role was further assessed through in vivo and in vitro experiments, and its promoting effect on pyroptosis was further evaluated and verified. The above results provided a new perspective for further studies on pyroptosis and its clinical utility for PCa.

CircME1 promotes aerobic glycolysis and sunitinib resistance of clear cell renal cell carcinoma through cis-regulation of ME1.

Circular RNAs (circRNAs) play critical roles in clear cell renal cell carcinoma (ccRCC). However, their involvement in sunitinib resistance remains largely unknown. Herein, we identified a novel circRNA, named circME1, which contributes to sunitinib resistance development in ccRCC. CircME1 also promoted proliferation, migration, and invasion of ccRCC cells. Further mechanism analysis showed that circME1 interacted with U1 snRNP at the promoter of its parental gene ME1, thereby upregulating the expression of ME1, enhancing aerobic glycolysis of ccRCC, and promoting its malignant phenotype. Furthermore, ME1 specific inhibitor could effectively repress the oncogenic functions of circME1. Taken together, our study demonstrates that the circME1/ME1 pathway is involved in ccRCC progression and sunitinib resistance development, which may be exploited for anticancer therapy.

Retinoic Acid Inhibits Tumor-Associated Mesenchymal Stromal Cell Transformation in Melanoma.

Bone marrow mesenchymal stem/stromal cells (BMSCs) can be transformed into tumor-associated MSCs (TA-MSCs) within the tumor microenvironment to facilitate tumor progression. However, the underline mechanism and potential therapeutic strategy remain unclear. Here, we explored that interleukin 17 (IL-17) cooperating with IFNγ transforms BMSCs into TA-MSCs, which promotes tumor progression by recruiting macrophages/monocytes and myeloid-derived suppressor cells (MDSCs) in murine melanoma. IL-17 and IFNγ transformed TA-MSCs have high expression levels of myelocyte-recruiting chemokines (CCL2, CCL5, CCL7, and CCL20) mediated by activated NF-κB signaling pathway. Furthermore, retinoic acid inhibits NF-κB signaling, decreases chemokine expression, and suppresses the tumor-promoting function of transformed TA-MSCs by prohibiting the recruitment of macrophages/monocytes and MDSCs in the tumor microenvironment. Overall, our findings demonstrate that IL-17 collaborating with IFNγ to induce TA-MSC transformation, which can be targeted by RA for melanoma treatment.

Single-Cell Atlas Reveals Fatty Acid Metabolites Regulate the Functional Heterogeneity of Mesenchymal Stem Cells.

Bone marrow mesenchymal stem cells (MSCs) are widely used clinically due to their versatile roles in multipotency, immunomodulation, and hematopoietic stem cell (HSC) niche function. However, cellular heterogeneity limits MSCs in the consistency and efficacy of their clinical applications. Metabolism regulates stem cell function and fate decision; however, how metabolites regulate the functional heterogeneity of MSCs remains elusive. Here, using single-cell RNA sequencing, we discovered that fatty acid pathways are involved in the regulation of lineage commitment and functional heterogeneity of MSCs. Functional assays showed that a fatty acid metabolite, butyrate, suppressed the self-renewal, adipogenesis, and osteogenesis differentiation potential of MSCs with increased apoptosis. Conversely, butyrate supplement significantly promoted HSC niche factor expression in MSCs, which suggests that butyrate supplement may provide a therapeutic approach to enhance their HSC niche function. Overall, our work demonstrates that metabolites are essential to regulate the functional heterogeneity of MSCs.