Disitamab Vedotin Alone or in Combination With Immune Checkpoint Inhibitors in Bladder-Sparing Treatment of Muscle-Invasive Bladder Cancer: A Real-World Study.

PURPOSE: To evaluate the efficacy and safety of a novel humanized anti-HER2 antibody, RC48-ADC (Disitamab vedotin, DV), the combination of RC48-ADC with PD-1 inhibitors was used to treat muscle-invasive bladder cancer (MIBC). This combination therapy has potential applications in both bladder preservation and neoadjuvant therapy for MIBC. METHODS: Patients with MIBC underwent transurethral resection of bladder tumors followed by RC48-ADC alone or in combination with PD-1 inhibitors. Radiological and endoscopic evaluations were conducted 3 months later. The primary endpoint was objective response rate (ORR), with secondary endpoints including complete response rate (CR), partial response rate (PR), and bladder preservation rate. Treatment safety was assessed according to RECIST v1.1 criteria. RESULTS: Eleven patients were enrolled, with a median follow-up of 19.0 months. Nine patients achieved objective response, including 6 CR and 3 PR cases. The pathological ORR was 81.8%. Eight patients continued combined treatment after 3 months, maintaining a 72.7% bladder preservation rate at 16 months. One elderly patient progressed from ypT2N0M0 to ypT3N0M0 and underwent radical cystectomy but had no recurrence or metastasis 12 months postoperation. All patients reported varying degrees of treatment-related adverse reactions, which were largely manageable. CONCLUSION: The combination of RC48-ADC and PD-1 inhibitors proves to be a viable and safe option for bladder-sparing therapy, particularly for T2-stage MIBC patients who are ineligible for surgery and chemotherapy. This approach offers a promising new direction for bladder preservation or neoadjuvant therapy in MIBC patients.

MOICS, a novel classier deciphering immune heterogeneity and aid precise management of clear cell renal cell carcinoma at multiomics level.

Recent studies have indicated that the tumor immune microenvironment plays a pivotal role in the initiation and progression of clear cell renal cell carcinoma (ccRCC). However, the characteristics and heterogeneity of tumor immunity in ccRCC, particularly at the multiomics level, remain poorly understood. We analyzed immune multiomics datasets to perform a consensus cluster analysis and validate the clustering results across multiple internal and external ccRCC datasets; and identified two distinctive immune phenotypes of ccRCC, which we named multiomics immune-based cancer subtype 1 (MOICS1) and subtype 2 (MOICS2). The former, MOICS1, is characterized by an immune-hot phenotype with poor clinical outcomes, marked by significant proliferation of CD4+ and CD8+ T cells, fibroblasts, and high levels of immune inhibitory signatures; the latter, MOICS2, exhibits an immune-cold phenotype with favorable clinical characteristics, characterized by robust immune activity and high infiltration of endothelial cells and immune stimulatory signatures. Besides, a significant negative correlation between immune infiltration and angiogenesis were identified. We further explored the mechanisms underlying these differences, revealing that negatively regulated endopeptidase activity, activated cornification, and neutrophil degranulation may promote an immune-deficient phenotype, whereas enhanced monocyte recruitment could ameliorate this deficiency. Additionally, significant differences were observed in the genomic landscapes between the subtypes: MOICS1 exhibited mutations in TTN, BAP1, SETD2, MTOR, MUC16, CSMD3, and AKAP9, while MOICS2 was characterized by notable alterations in the TGF-ß pathway. Overall, our work demonstrates that multi-immune omics remodeling analysis enhances the understanding of the immune heterogeneity in ccRCC and supports precise patient management.

Multiomics-based classifier to decipher immune landscape of uveal melanoma and predict patient outcomes.

Uveal melanoma (UVM) prognosis and the possibilities for targeted therapy depend on a thorough understanding of immune infiltration features and the analysis of genomic and immune signatures. Leveraging multi-omics data from The Cancer Genome Atlas and GEO datasets, we employed an unsupervised clustering algorithm to categorize UVM into immune-related subgroups. Subsequent multi-omics analysis revealed two distinct UVM subtypes, each characterized by unique genomic mutations and immune microenvironment disparities. The aggressive UMCS2 subtype exhibited higher TNM stage and poorer survival, marked by elevated metabolism and increased immune infiltration. However, UMCS2 displayed heightened tumor mutational burden and immune dysfunction, leading to reduced responsiveness to immunotherapy. Importantly, these subtypes demonstrated differential sensitivity to targeted drugs due to significant variances in metabolic and immune environments, with UMCS2 displaying lower sensitivity. We developed a robust, subtype-specific marker-based risk scoring system. This system's diagnostic accuracy was validated through ROC curves, decision curve analysis, and calibration curves, all yielding satisfactory results. Additionally, cell experiments identified the pivotal function of HTR2B, the most crucial factor in this risk model. Knocking down HTR2B significantly reduced the activity, proliferation, and invasion ability of the UVM cell line. These findings underscored the impact of gene and immune microenvironment alterations in driving distinct molecular subtypes, emphasizing the need for precise treatment strategies. The molecular subtyping-based risk assessment system not only aids in predicting patient prognosis but also guides the identification of populations suitable for combined treatment. Molecules represented by HTR2B in the model may serve as effective therapeutic targets for UVM.Communicated by Ramaswamy H. Sarma.

Comprehensive analysis of the prognosis and immune infiltration of TMC family members in renal clear cell carcinoma.

Renal cancer is a common malignancy of the urinary system, and renal clear cell carcinoma (RCCC) is the most common pathological type. Transmembrane channel-like (TMC) protein is an evolutionarily conserved gene family containing 8 members, however there is still a lack of comprehensive analysis about TMC family members in RCCC. In this study, we analyzed the expression of TMC family members in RCCC from TCGA and investigated the prognosis values and immune infiltration of TMC family members in RCCC. We found that TMC2, TMC3, TMC5, TMC7 and TMC8 were significantly related with overall survival (OS) of RCCC patients. TMC3, TMC6, and TMC8 was positively correlated with the degree of immune infiltration in RCCC. TMC2, TMC6, TMC7, and TMC8 were positively correlated with immune checkpoint genes, whereas TMC4 was negative. According to KEGG and GO analysis, almost all TMCs except TMC4 were involved in the immune response. Thus, we may regard the TMC family members as novel biomarkers to predict potential prognosis and immunotherapeutic response in RCCC patients.

Deciphering the Role of Melatonin-Related Signatures in Tumor Immunity and the Prognosis of Clear Cell Renal Cell Carcinoma.

Methods: Adopting multiomics data from TCGA and other public datasets, we analysed the expression, mutation, and prognostic evaluation in multiple cancers. ccRCC patients were categorized into two subgroups by an unsupervised cluster algorithm: melatonin-pattern cancer subtype 1 (MPCS1) and subtype 2 (MPCS2). We then explored the immune microenvironment, immune therapy response, and tumor metabolic pathways between the two subtypes. The clinical characteristics, genomic mutation landscape, and molecular inhibitor response were further investigated. Finally, a melatonin regulator-related prognostic model was constructed to predict patient prognosis in ccRCC. Results: We found that melatonin regulators were dysregulated depending on distinct cancer types, which were associated with genomic variation. The two subtypes indicated different clinical characteristics and biological processes in ccRCC. MPCS2, an aggressive subtype, led an advanced clinical stage and poorer survival of ccRCC patients. The activated oncogenic signaling pathway and metabolic signatures were responsible for cancer progression in the MPCS2 subtype. The MPCS2 subgroup suggested a higher tumor mutational burden and immune dysfunction state, resulting in a lower response to immunotherapy. The copy number variations of MPCS2 were significantly more frequent than those of MPCS1. In addition, the two subgroups exhibited distinct drug responsiveness, with MPCS2 being less responsive to multiple drugs. Finally, we established a subtype biomarker-based prognostic risk model that exhibited satisfactory performance in ccRCC patients. Conclusion: Melatonin regulator-related features could remodel functional pathways and the tumor immune microenvironment through genomic mutations and pathway regulation. Melatonin regulator-associated molecular subtypes enhance the understanding of the molecular characteristics of renal cancer and can guide clinical treatment. Activating the melatonergic system axis may improve the effect of immunotherapy for ccRCC.

A new thinking: deciphering the aberrance and clinical implication of copper-death signatures in clear cell renal cell carcinoma.

RATIONALE: Recent research has indicated that cuprotosis, or copper induced cell death, is a novel type of cell death that could be utilized as a new weapon for cancer management. However, the characteristics and implications of such signatures in cancers, especially in clear cell renal cell cancer (ccRCC), remain elusive. METHODS: Expression, methylation, mutation, clinical information, copy number variation, functional implication, and drug sensitivity data at the pan-cancer level were collected from The Cancer Genome Atlas. An unsupervised clustering algorithm was applied to decipher ccRCC heterogeneity. Immune microenvironment construction, immune therapy response, metabolic pattern, and cancer progression signature between subgroups were also investigated. RESULTS: Cuprotosis related genes were specifically downregulated in various cancer tissues compared with normal tissues and were correlated with hypermethylation and copy number variation. Cuprotosis scores were also dysregulated in tumor tissues, and we found that such a signature could positively regulate oxidative phosphorylation and Myc and negatively regulate epithelial mesenchymal translation and myogenesis pathways. CPCS1 (cuprotosis scores high) and CPCS2 (cuprotosis scores low) in ccRCC displayed distinctive clinical profiles and biological characteristics; the CPCS2 subtype had a higher clinical stage and a worse prognosis and might positively regulate cornification and epidermal cell differentiation to fuel cancer progression. CPCS2 also displayed a higher tumor mutation burden and low tumor stemness index, while it led to a low ICI therapy response and dysfunctional tumor immunity state. The genome-copy numbers of CPCS2, including arm- gain and arm- loss, were higher than those of CPCS1. The prognostic model constructed based on subgroup biomarkers exerted satisfactory performance in both the training and validation cohorts. In addition, overexpression of the copper death activator DLAT suppressed the malignant ability, including cell migration and proliferation, of renal cell lines in vitro and in vivo. Finally, activation of cuprotosis in tumors could enhance antitumor immunity through dsDNA-cGAS-STING signaling in ccRCC. CONCLUSION: The activation of cuprotosis might function as a promising approach among multiple cancers. The cuprotosis related signatures could reshape tumor immunity in the ccRCC microenvironment via cGAS-STING signal, thus activating tumor antigen-presenting process. Upregulation of DLAT expression in ccRCC cell lines could reactivate the copper death pattern and be treated as a suitable target for ccRCC.

A New Thinking: Deciphering the Aberrance and Clinical Implication of IGF Axis Regulation Pattern in Clear Cell Renal Cell Carcinoma.

Rationale: The recent research found that IGF regulator genes played a pivotal role in multiple biological processes, which may be developed for cancer treatment. However, the characteristics and implication of IGF regulators in cancers, especially in clear cell renal cell carcinoma (ccRCC), remain elusive. Methods: We systematically analyzed the expression, prognostic valuation, genome variation, and functional implication at pan-cancer level from The Cancer Genome Atlas. According to expression levels of IGF regulator genes, ccRCC could be divided into three different subtypes via unsupervised cluster algorithm: IGF pattern cancer type1 (IPCS1), type2 (IPCS2), and type3 (IPCS3). The immune microenvironment, immunotherapy response, metabolic pattern, and tumor progression signature among the three subgroups were investigated. The clinical characteristics, genomic mutations, and potential drug sensitivity were further analyzed. IGF pattern-related risk model was constructed to predict RCC patients' outcome. Finally, SHC1, a potential IGF axis target, was comprehensively investigated in ccRCC. Results: We found that IGF regulator genes were specifically upregulated in various cancer tissues, which were correlated with copy number variations and dysregulated pathways. IPCS1, IPCS2, and IPCS3 exhibited different clinical profiles and biological characteristics in ccRCC. IPCS3 subtype indicated a higher clinical stage and a worse survival. IPSC3 ccRCC displayed activated metabolic signatures to fuel the cancer progression. IPCS3 subgroup holds a higher tumor mutation burden and lower immune activities, which resulted in a low ICI therapy response and tumor immunity dysfunction state. The genome copy numbers of IPCS2/3, including arm gain and arm loss, were significantly higher than IPCS1. Besides, the drug sensitivity profiles were different among the three subgroups. The prognostic risk model based on subtype's biomarker exerted a promising performance both in training and validation cohorts. Finally, upregulated expression of SHC1 partly induced poorer immunotherapy response and shorter survival of ccRCC patients. Conclusion: Targeting IGF regulators may be functioned as a treatment approach among multi-cancers. IGF regulator-related signature could reshape the tumor immune microenvironment via activating multi-step immune programs. The inhibition of SHC1 may enhance the efficacy of immunotherapy, and SHC1 could be a suitable target for ccRCC therapy.

Analysis of the Outcome of Treatment of Brain Metastases from Malignant Trophoblastic Tumours and Risk Factors for Prognosis during Pregnancy.

Temozolomide combined with whole-brain radiotherapy has good near-term efficacy and safety in the treatment of brain metastases from nonsmall cell lung cancer. In this study, we analyzed the risk factors for treatment and prognosis of brain metastases in gestational trophoblastic neoplasm (GTN) during pregnancy. Thirty-one patients with brain metastases were included in the study. All patients had a pathological diagnosis of primary lesions, including 23 adenocarcinomas, 7 squamous carcinomas, and 1 adenosquamous carcinoma, and had ≥3 intracranial metastases, controlled primary lesions (including resected primary lesions or unresectable primary lesions in partial remission (PR)/complete remission (CR) for ≥2 months) by cranial enhancement MRI and no extracranial metastases. Presence or control of extracranial metastases was for ≥2 months. The common adverse toxic effects were nausea, vomiting, neutropenia, and thrombocytopenia, but most patients tolerated them with symptomatic management.

Programmed Topographic Substrates for Studying Roughness Gradient-Dependent Cell Migration Using Two-Photon Polymerization.

The mediation of the extracellular matrix is one of the major environmental cues to direct cell migration, such as stiffness-dependent durotaxis and adhesiveness-dependent haptotaxis. In this study, we explore another possible contact guidance: roughness dependent topotaxis. Different from previously reported studies on topotaxis that use standard photolithography to create micron or submicron structures that have identical height and different spatial densities, we develop a new method to programmatically fabricate substrates with different patterns of surface roughness using two-photon polymerization. Surface roughness ranging from 0.29 to 1.11 µm can be created by controlling the voxel distance between adjacently cured ellipsoid voxels. Patterned Ormocomp® masters are transferred to polypropylene films using the nanoimprinting method for cell migration study. Our experimental results suggest that MG63 cells can sense the spatial distribution of their underlying extracellar roughness and modulate their migration velocity and direction. Three characteristic behaviors were identified. First, cells have a higher migration velocity on substrates with higher roughness. Second, cells preferred to migrate from regions of higher roughness to lower roughness, and their migration velocity also decreased with descending roughness. Third, the migration velocity remained unchanged on the lower roughness range on a graded substrate with a steeper roughness. The last cell migration characteristic suggests the steepness of the roughness gradient can be another environmental cue in addition to surface roughness. Finally, the combination of two-photon polymerization and nanoimprint methods could become a new fabrication methodology to create better 3D intricate structures for exploring topotactic cell migrations.

Establishment of a Prognostic Prediction and Drug Selection Model for Patients with Clear Cell Renal Cell Carcinoma by Multiomics Data Analysis.

METHODS: This study was based on the multiomics data (including mRNA, lncRNA, miRNA, methylation, and WES) of 258 ccRCC patients from TCGA database. Firstly, we screened the feature values that had impact on the prognosis and obtained two subtypes. Then, we used 10 algorithms to achieve multiomics clustering and conducted pseudotiming analysis to further validate the robustness of our clustering method, based on which the two subtypes of ccRCC patients were further subtyped. Meanwhile, the immune infiltration was compared between the two subtypes, and drug sensitivity and potential drugs were analyzed. Furthermore, to analyze the heterogeneity of patients at the multiomics level, biological functions between two subtypes were compared. Finally, Boruta and PCA methods were used for dimensionality reduction and cluster analysis to construct a renal cancer risk model based on mRNA expression. RESULTS: A prognosis predicting model of ccRCC was established by dividing patients into the high- and low-risk groups. It was found that overall survival (OS) and progression-free interval (PFI) were significantly different between the two groups (p < 0.01). The area under the OS time-dependent ROC curve for 1, 3, 5, and 10 years in the training set was 0.75, 0.72, 0.71, and 0.68, respectively. CONCLUSION: The model could precisely predict the prognosis of ccRCC patients and may have implications for drug selection for ccRCC patients.

Definition and verification of novel metastasis and recurrence related signatures of ccRCC: A multicohort study.

Background: Cancer metastasis and recurrence remain major challenges in renal carcinoma patient management. There are limited biomarkers to predict the metastatic probability of renal cancer, especially in the early-stage subgroup. Here, our study applied robust machine-learning algorithms to identify metastatic and recurrence-related signatures across multiple renal cancer cohorts, which reached high accuracy in both training and testing cohorts. Methods: Clear cell renal cell carcinoma (ccRCC) patients with primary or metastatic site sequencing information from eight cohorts, including one out-house cohort, were enrolled in this study. Three robust machine-learning algorithms were applied to identify metastatic signatures. Then, two distinct metastatic-related subtypes were identified and verified; matrix remodeling associated 5 (MXRA5), as a promising diagnostic and therapeutic target, was investigated in vivo and in vitro. Results: We identified five stable metastasis-related signatures (renin, integrin subunit beta-like 1, MXRA5, mesenchyme homeobox 2, and anoctamin 3) from multicenter cohorts. Additionally, we verified the specificity and sensibility of these signatures in external and out-house cohorts, which displayed a satisfactory consistency. According to these metastatic signatures, patients were grouped into two distinct and heterogeneous ccRCC subtypes named metastatic cancer subtype 1 (MTCS1) and type 2 (MTCS2). MTCS2 exhibited poorer clinical outcomes and metastatic tendencies than MTCS1. In addition, MTCS2 showed higher immune cell infiltration and immune signature expression but a lower response rate to immune blockade therapy than MTCS1. The MTCS2 subgroup was more sensitive to saracatinib, sunitinib, and several molecular targeted drugs. In addition, MTCS2 displayed a higher genome mutation burden and instability. Furthermore, we constructed a prognosis model based on subtype biomarkers, which performed well in training and validation cohorts. Finally, MXRA5, as a promising biomarker, significantly suppressed malignant ability, including the cell migration and proliferation of ccRCC cell lines in vitro and in vivo. Conclusions: This study identified five robust metastatic signatures and proposed two metastatic probability clusters with stratified prognoses, multiomics landscapes, and treatment options. The current work not only provided new insight into the heterogeneity of renal cancer but also shed light on optimizing decision-making in immunotherapy and chemotherapy.

Methyltransferase-like 14 suppresses growth and metastasis of renal cell carcinoma by decreasing long noncoding RNA NEAT1.

Growing evidence supports that N6-methyladenosine (m6A) modification acts as a critical regulator involved in tumorigenesis at the mRNA level. However, the role of m6A modification at the noncoding RNA level remains largely unknown. We found that methyltransferase-like 14 (METTL14) was significantly downregulated in renal cell carcinoma (RCC) tissues (n = 580). Gain-of-function and loss-of-function experiments revealed that METTL14 attenuated the proliferation and migration ability of RCC cells in vivo and in vitro. The methylated RNA immunoprecipitation experiments identified that METTL14 decreased the expression of long noncoding RNA nuclear enriched abundant transcript 1_1 (NEAT1_1) in an m6A-dependent manner. Mechanistically, RNA pull-down assay and RNA immunoprecipitation identified NEAT1_1 directly bound to m6A reader YTH N6-methyladenosine RNA binding protein 2 (YTHDF2). Notably, YTHDF2 accelerated the degradation of NEAT1_1 by selectively recognizing METTL14-mediated m6A marks on NEAT1_1. Multivariate analysis suggested that METTL14 downregulation was associated with malignant characteristics and predicted poor prognosis in RCC patients. In conclusion, our results uncover a newly identified METTL14-YTHDF2-NEAT1_1 signaling axis, which facilitates RCC growth and metastasis and provides fresh insight into RCC therapy.

Establishment of a prognosis Prediction Model Based on Pyroptosis-Related Signatures Associated With the Immune Microenvironment and Molecular Heterogeneity in Clear Cell Renal Cell Carcinoma.

BACKGROUND: Pyroptosis is essential for tumorigenesis and progression of neoplasm. However, the heterogeneity of pyroptosis and its relationship with the tumor microenvironment (TME) in clear cell renal cell carcinoma (ccRCC) remain unclear. The purpose of the present study was to identify pyroptosis-related subtypes and construct a prognosis prediction model based on pyroptosis signatures. METHODS: First, heterogenous pyroptosis subgroups were explored based on 33 pyroptosis-related genes and ccRCC samples from TCGA, and the model established by LASSO regression was verified by the ICGC database. Then, the clinical significance, functional status, immune infiltration, cell-cell communication, genomic alteration, and drug sensitivity of different subgroups were further analyzed. Finally, the LASSO-Cox algorithm was applied to narrow down the candidate genes to develop a robust and concise prognostic model. RESULTS: Two heterogenous pyroptosis subgroups were identified: pyroptosis-low immunity-low C1 subtype and pyroptosis-high immunity-high C2 subtype. Compared with C1, C2 was associated with a higher clinical stage or grade and a worse prognosis. More immune cell infiltration was observed in C2 than that in C1, while the response rate in the C2 subgroup was lower than that in the C1 subgroup. Pyroptosis-related genes were mainly expressed in myeloid cells, and T cells and epithelial cells might influence other cell clusters via the pyroptosis-related pathway. In addition, C1 was characterized by MTOR and ATM mutation, while the characteristics of C2 were alterations in SPEN and ROS1 mutation. Finally, a robust and promising pyroptosis-related prediction model for ccRCC was constructed and validated. CONCLUSION: Two heterogeneous pyroptosis subtypes were identified and compared in multiple omics levels, and five pyroptosis-related signatures were applied to establish a prognosis prediction model. Our findings may help better understand the role of pyroptosis in ccRCC progression and provide a new perspective in the management of ccRCC patients.

BMP2 Modified by the m6A Demethylation Enzyme ALKBH5 in the Ossification of the Ligamentum Flavum Through the AKT Signaling Pathway.

Ossification of the ligamentum flavum (OLF) is characterized by a process of ectopic bone formation in the ligamentum flavum. The definitive pathophysiology of OLF still remains unclear, but the epigenetic m6A modification plays an important role in OLF. In addition, no studies have reported the function of ALKBH5 in OLF development. In this study, we investigated the function of the m6A demethylation enzyme ALKBH5 in OLF. To evaluate the function of ALKBH5, OLF tissues and normal ligamentum flavum tissues were collected. In vitro methods, including HE, IHC and western blotting assays, were used to evaluate the association of ALKBH5 with OLF. In addition, we verified the effects of ALKBH5 on osteogenesis using alizarin red and ALP staining. MeRIP q-PCR was performed to investigate the methylation level of BMP2. Moreover, the mechanism of ALKBH5-mediated regulation of the ossification of the ligamentum flavum cells through the AKT signaling pathway was also verified. The present study showed that the expression of ALKBH5 increased in OLF tissues. The overexpression of ALKBH5 increased the expression of osteogenic genes and promoted the ossification of ligamentum flavum cells. Furthermore, BMP2 was significantly enriched in the ligamentum flavum cells of the anti-m6A group compared with those of the IgG group. The overexpression of ALKBH5 led to the activation of p-AKT, and BMP2 was regulated by ALKBH5 through the AKT signaling pathway. ALKBH5 promoted the osteogenesis of the ligamentum flavum cells through BMP2 demethylation and AKT activation. ALKBH5 was shown to be an important demethylation enzyme in OLF development.

EGFR-AS1 Promotes Bladder Cancer Progression by Upregulating EGFR.

Long noncoding RNAs play an essential role in bladder cancer progression. The role of long noncoding RNA EGFR-AS1 in bladder cancer needs further study. We used clinical specimens to analyze the relationship between EGFR-AS1 and bladder cancer patients' characteristics. The functional experiments and mechanism studies were performed using qRT-PCR, transwell assay, survival analysis, and correlation analysis. We found that high expression of EGFR-AS1 was nearly related to aggressive bladder cancer and indicated poor prognosis for patients. The functional experiments in vivo and in vitro suggested that EGFR-AS1 promoted the proliferation and invasion of bladder cancer cells. Mechanically, EGFR-AS1 promoted the expression of EGFR by inhibiting the degradation of EGFR mRNA, thereby promoting the metastasis of bladder cancer. In addition, EGFR-AS1/EGFR may be involved in the immune-related pathways of bladder cancer. These studies indicate that the EGFR-AS1/EGFR pathway may be a potential diagnostic marker and therapeutic target for bladder cancer.

CircRNA cRAPGEF5 inhibits the growth and metastasis of renal cell carcinoma via the miR-27a-3p/TXNIP pathway.

Circular RNAs (circRNAs) are reported to act as important regulators in cancers. CircRNA RAPGEF5 (cRAPGEF5) is derived from exons 2-6 of the RAPGEF5 gene and may promote papillary thyroid cancer progression. However, the role of cRAPGEF5 in renal cell carcinoma (RCC) remains unclear. In this study, we found cRAPGEF5 to be significantly downregulated in RCC tissues. Among 245 RCC cases, cRAPGEF5 downregulation correlated positively with aggressive clinical characteristics and independently predicted poor overall survival and recurrence-free survival. Functional assays demonstrated that cRAPGEF5 suppresses RCC proliferation and migration in vitro and in vivo. Mechanistically, RNA Immunoprecipitation and circRNA in vivo precipitation assays showed that cRAPGEF5 functions as a sponge of oncogenic miR-27a-3p, which targets the suppressor gene TXNIP. Interactions between miR-27a-3p and cRAPGEF5 or TXNIP were confirmed by dual-luciferase reporter assays. In conclusion, cRAPGEF5 plays a role in suppressing RCC via the miR-27a-3p/TXNIP pathway and may serve as a promising prognostic biomarker and novel therapeutic target for RCC patients.

DNA methylation-regulated QPCT promotes sunitinib resistance by increasing HRAS stability in renal cell carcinoma.

Rationale: Although sunitinib has been shown to improve the survival rate of advanced renal cell carcinoma (RCC) patients, poor drug response is a major challenge that reduces patient benefit. It is important to elucidate the underlying mechanism so that the therapeutic response to sunitinib can be restored. Methods: We used an Illumina HumanMethylation 850K microarray to find methylation-differentiated CpG sites between sunitinib-nonresponsive and -responsive RCC tissues and Sequenom MassARRAY methylation analysis to verify the methylation chip results. We verified glutaminyl peptide cyclotransferase (QPCT) expression in sunitinib-nonresponsive and -responsive RCC tissues via qRT-PCR, western blot and immunohistochemical assays. Then, cell counting kit 8 (CCK-8), plate colony formation and flow cytometric assays were used to verify the function of QPCT in RCC sunitinib resistance after QPCT intervention or overexpression. Chromatin immunoprecipitation (ChIP) was performed to clarify the upstream regulatory mechanism of QPCT. A human proteome microarray assay was used to identify downstream proteins that interact with QPCT, and co-immunoprecipitation (co-IP) and confocal laser microscopy were used to verify the protein chip results. Results: We found that the degree of methylation in the QPCT promoter region was significantly different between sunitinib-nonresponsive and -responsive RCC tissues. In the sunitinib-nonresponsive tissues, the degree of methylation in the QPCT promoter region was significantly reduced, and the expression of QPCT was upregulated, which correlated with a clinically poor response to sunitinib. A knockdown of QPCT conferred sunitinib sensitivity traits to RCC cells, whereas an overexpression of QPCT restored sunitinib resistance in RCC cells. Mechanistically, reducing the methylation degree of the QPCT promoter region by 5-aza-2'-deoxycytidine (decitabine) in RCC cells could increase the expression of QPCT and NF-κB (p65) bound to the QPCT promoter region, positively regulating its expression, while the hypermethylation in the QPCT promoter region could inhibit the binding of NF-κB (p65). QPCT could bind to HRAS and attenuate the ubiquitination of HRAS, thus increasing its stability and leading to the activation of the ERK pathway in RCC cells. Conclusion: QPCT may be a novel predictor of the response to sunitinib therapy in RCC patients and a potential therapeutic target.

ANGPTL3 inhibits renal cell carcinoma metastasis by inhibiting VASP phosphorylation.

Angiopoietin-like proteins (ANGPTLs) comprise a group of proteins that are structurally similar to angiopoietins. In our previous studies, we found that ANGPTL3 can inhibit sorafenib resistance in renal cell carcinoma (RCC). According to bioinformatics analysis based on data in the Cancer Genome Atlas (TCGA), we found that expression of ANGPTL3 was significantly lower in RCC tissues than in adjacent tissues and that disease-free survival and overall survival were significantly shorter in patients with lower ANGPTL3 levels than in those with higher ANGPTL3 levels. Consistent with these results, we demonstrated that RCC tissues exhibited lower ANGPTL3 mRNA and protein expression levels than paired adjacent tissues. Moreover, we found that ANGPTL3 upregulation was associated with better clinical outcomes in RCC patients. ANGPTL3 overexpression inhibited the metastatic ability in RCC cells. Mechanistically, ANGPTL3 binds to vasodilator-stimulated phosphoprotein (VASP) and inhibits its phosphorylation at amino acid 157 in RCC cells. Finally, ANGPTL3 expression and VASP-157 phosphorylation may be combined to predict the prognosis of RCC patients. Overall, our findings describe the role of ANGPTL3 in inhibiting RCC metastasis and thus provide new molecular markers for RCC treatment and prognosis.

Physicochemical, functional and emulsion properties of edible protein from avocado (Persea americana Mill.) oil processing by-products.

Avocado (Persea americana) is a tropical fruit that has drawn great interest its oil for foods and cosmetic industries; however, avocado oil processing by-product is a potential source of edible protein. Herein, edible protein was prepared from defatted avocado meal, and it's physicochemical, functional and emulsion properties were investigated. The avocado protein showed U-shaped exhibiting strong effect of pH, and a minimum solubility being observed at pH 4.5, confirming the isoelectric point of avocado protein. Nutritionally, the avocado protein contains all the essential amino acids. Avocado protein provided higher water and oil absorption capacities, higher radical scavenging capacity but lower in-vitro digestibility compared with soy protein. Furthermore, the avocado protein as emulsifier afforded a stability oil-in-water emulsion system, resulting in a greater emulsifying stability than that of soy protein. The present results highlight the potential source of edible protein from avocado oil processing by-products for functional food ingredients.

Long noncoding RNA EGFR-AS1 promotes cell growth and metastasis via affecting HuR mediated mRNA stability of EGFR in renal cancer.

Long noncoding RNAs (lncRNAs) are implicated in renal cell carcinoma (RCC), but remain largely unclear. Using publicly available transcriptome sequencing data from renal cancer (n = 703) and integrating bioinformatics analyses, we screened and identified a valuable lncRNA, EGFR-AS1. In our validation cohort (n = 204), EGFR-AS1 was significantly upregulated in RCC tissues (P < 0.001). Gain-of-function and loss-of-function studies showed that EGFR-AS1 promoted cell proliferation and invasion in vitro and in vivo. Based on previous studies and sequence complementarity of EGFR with EGFR-AS1, we demonstrated that EGFR-AS1 directly bound to EGFR mRNA and inhibited its degradation. Furthermore, RNA pull-down and mass spectrometry analyses showed that EGFR-AS1 interacted with HuR, which was responsible for the mRNA stability of EGFR. Multivariate analysis suggested that higher EGFR-AS1 expression predicted a poor prognosis in RCC patients (high vs low: P = 0.018, HR = 2.204, 95% CI: 1.145-4.241). In conclusion, EGFR-AS1 enhances the malignant phenotype of RCC cells by enhancing HuR-mediated mRNA stability of EGFR. Our data also provide biological rationales for EGFR-AS1 as a prognostic biomarker and a potential therapeutic target for RCC.