Clear Cell Research Articles

Antiangiogenic Tyrosine Kinase Inhibitors have Differential Efficacy in Clear Cell Renal Cell Carcinoma in Bone.

TKIs showed different efficacy in synchronous bone and lung metastases and did not eradicate tumors as single agents but induced extensive reprogramming of the BM microenvironment. This resulted in a significant decrease in neoangiogenic blood vessels, bone remodeling, and immune cell infiltration (including CD8 T cells) with altered spatial distribution.

4 Oral: Casdatifan in patients (pts) with previously treated clear cell renal cell cancer (ccRCC) and other solid tumors; preliminary results from ARC- 20: A phase 1, open-label dose-escalation and expansion study

4 Oral: Casdatifan in patients (pts) with previously treated clear cell renal cell cancer (ccRCC) and other solid tumors; preliminary results from ARC- 20: A phase 1, open-label dose-escalation and expansion study

Development and validation of a clinic-radiomics model based on intratumoral habitat imaging for progression-free survival prediction of patients with clear cell renal cell carcinoma: A multicenter study

PurposeTo develop and validate a clinicoradiomics model based on intratumoral habitat imaging for preoperatively predicting of progression-free survival (PFS) of clear cell renal cell carcinoma (ccRCC) and analyzing progression-associated genes expression. MethodsThis retrospective study included 691 ccRCC patients from multicenter databases. Entire tumor segmentation was performed with handcrafted process to generate habitat subregions based on a pixel-wise gray-level co-occurrence matrix analysis. Cox regression models for PFS prediction were constructed using conventional volumetric radiomics features (Radiomics), habitat subregions-derived radiomics (Rad-Habitat), and an integration of habitat radiomics and clinical characteristics (Hybrid Cox). Training (n = 393) and internal validation (n = 118) was performed in a Nanjing cohort, external validation was performed in a Wuhan and Zhejiang cohort (n = 227) and in a TCGA-KIRC (n =71) with imaging-genomic correlation. Statistical analysis included the area-under-ROC curve analysis, C-index, decision curve analysis (DCA) and Kaplan-Meier survival analysis. ResultsHybrid Cox model resulted in a C-index of 0.83 (95% CI, 0.73–0.93) in internal validation and 0.79 (95% CI, 0.74–0.84) in external validation for PFS prediction, higher than Radiomics and Rad-Habitat model. Patients stratified by Hybrid Cox model presented with significant difference survivals between high-risk and low-risk group in 3 data sets (all P < 0.001 at Log-rank test). TCGA-KIRC data analysis revealed 37 upregulated and 81 downregulated genes associated with habitat imaging features of ccRCC. Differentially expressed genes likely play critical roles in protein and mineral metabolism, immune defense, and cellular polarity maintenance.

Spatial Profiling of Ovarian Clear Cell Carcinoma Reveals Immune-Hot Features

Ovarian clear cell carcinoma (OCCC) has a high incidence in Asia, with a frequent occurrence at an early stage, but without sufficient data on molecular stratification for high-risk patients. Recently, immune-hot features have been proposed as indicators of poor prognosis in early stage OCCC. Specific patterns of intratumoral heterogeneity associated with immune-hot features must be defined. NanoString Digital Spatial Profiling technology was used to decipher the spatial distribution of the 18-plex protein panel. Regions of interest (ROIs) were collected based on the reference hematoxylin and eosin–stained morphology. Areas of illumination (AOIs) were defined according to the ROI segmentation using the fluorescence signals of the visualization markers pan-cytokeratin (PanCK), CD45, or DNA. Unsupervised hierarchical clustering of 595 AOIs from 407 ROIs showed that the PanCK segments expressed different combinations of immune markers, suggestive of immune mimicry. The following 3 immune-hot clusters were identified: granzyme B–high, immune signal-high , and immune-like cells; the following 2 immune-cold clusters were identified: fibronectin-high and immune checkpoint–high cells. In tumor samples at the International Federation of Gynecology and Obstetrics stage IC1/2 experiencing recurrence, there was an increased occurrence of PanCK+ AOIs with immune signal-high and immune-like cell groups in the papillary morphology surrounded by macrophage lineage tumor-infiltrating immune cells (TIIs). In contrast, for tumor samples at the International Federation of Gynecology and Obstetrics stage IC3/II with recurrence, PanCK+ AOIs were prevalent in the fibronectin-high group, particularly in those with a tubulocystic morphology surrounded by lymphoid lineage non-TIIs. Our study on the spatial profiling of early stage OCCC tumors revealed that the immune mimicry of tumor cells, presence of TIIs, and morphologic patterns were associated with recurrence, which switched during tumor progression.

Leveraging mitochondrial-programmed cell death dynamics to enhance prognostic accuracy and immunotherapy efficacy in lung adenocarcinoma

BackgroundLung adenocarcinoma (LUAD) is a highly heterogeneous disease, posing significant challenges to accurate prognosis prediction. Mitochondria play a central role in the energy metabolism of eukaryotic cells and can influence...

Potential of quantitative T1 mapping to serve as a novel prognostic predictor of clear cell renal cell carcinoma after nephrectomy.

Accurate preoperative risk stratification methods are important for clear cell renal cell carcinoma (ccRCC) patients to enable personalized treatment. However, there are still no accurate and quantitative prognostic factors. This study aimed to investigate the effectiveness of T1 mapping in predicting the progression-free survival (PFS) of ccRCC after nephrectomy. A retrospective cohort study was performed in a China tertiary care hospital. This study reviewed the clinical and magnetic resonance imaging (MRI) data of consecutive inpatients with pathologically confirmed ccRCCs between September 2014 and September 2021. PFS was evaluated by following patients until the first adverse event. Radiological features including T1 relaxation time of tumors were assessed by 2 radiologists. Cox regression and visual nomogram, Kaplan-Meier survival, and log-rank test were utilized for survival analysis. A total of 195 patients with pathologically confirmed ccRCCs (mean age ± standard deviation, 56.0±12.0 years; 133 men) with eligible data were included in the study. The median follow-up was 27.6 months (range, 1-88 months), and 22 (11.3%) patients experienced metastasis or recurrence. Univariate and multivariate survival analysis showed the higher post-contrasted T1 relaxation time [P=0.001; hazard ratio (HR), 2.077; 95% confidence interval (CI): 1.350-3.196] and the incomplete tumor capsule (P<0.001; HR, 7.849; CI: 2.614-23.570) were independently associated with a shorter PFS of patients. Patients with ≥222.73 ms post-contrasted T1 relaxation time ccRCCs had worse PFS than the lower post-contrasted T1 relaxation time group. The T1 mapping quantitative parameters may be a new potential biomarker for predicting PFS in patients with ccRCCs.

Multi-instance learning for identifying high-risk subregions associated with synchronous distant metastasis in clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is one of the most common histological subtypes of renal tumors. To identify high-risk subregions associated with synchronous distant metastasis. This study enrolled a total of 277 patients with ccRCC. Voxel intensity and local entropy values were compiled within the region of interest for all patients. Unsupervised k-means clustering yielded three subregions per tumor. Radiomic features were extracted, and random forest-based feature selection was conducted. The selected features were used in a multi-instance support vector machine (mi-SVM) model for training, and predictions were made on the validation cohort. Model performance was evaluated using five-fold cross-validation. The subregion with the highest score for patients with synchronous distant metastasis was identified across all cohorts. The mi-SVM model yielded an average area under the curve (AUC) of 0.812 in the training cohort and 0.805 in the validation cohort. In the entire cohort of patients with synchronous distant metastasis, subregion 2, characterized by tumor periphery and intratumoral transitional components, accounted for the highest proportion (48.57%, 30.6/63) among all subregions. It represents a high-risk subregion for synchronous distant metastasis of clear cell renal cell carcinoma. The peripheral and intratumoral transition zones of clear cell renal cell carcinoma are high-risk subregions associated with synchronous distant metastasis.

An NF-&amp;kappa;B-related signature associated with prognosis and drug sensitivity in clear cell renal cell carcinoma

An NF-&amp;kappa;B-related signature associated with prognosis and drug sensitivity in clear cell renal cell carcinoma

Multicenter evaluation of CT deep radiomics model in predicting Leibovich score risk groups for non-metastatic clear cell renal cell carcinoma

BackgroundNon-metastatic clear cell renal cell carcinoma (nccRCC) poses a significant risk of postoperative recurrence and metastasis, underscoring the importance of accurate preoperative risk assessment. While the Leibovich score is effective, it relies on postoperative histopathological data. This study aims to evaluate the efficacy of CT radiomics and deep learning models in predicting Leibovich score risk groups in nccRCC, and to explore the interrelationship between CT and pathological features. Patients and MethodsThis research analyzed 600 nccRCC patients from four datasets, dividing them into low (Leibovich scores of 0–2) and intermediate to high risk (Leibovichscores exceeding 3) groups. Radiological models were developed from CT subjective features, and radiomics and deep learning models were constructed from CT images. Additionally, a deep radiomics model and a fusion model integrating radiological, radiomics, and deep learning features were introduced. Model performance was assessed by AUC values, while survival differences across predicted groups were analyzed using survival curves and the DeLong test. Moreover, the research investigated the connection between CT and pathological features derived from whole-slide pathological images in the second validation dataset. ResultsWithin the training dataset, four radiological, three radiomics, and thirteen deep learning features were selected to develop models predicting nccRCC Leibovich score risk groups. The deep radiomics model demonstrated superior predictive accuracy, evidenced by AUC values of 0.881, 0.829, and 0.819 in external validation datasets. Notably, significant differences in overall survival were observed among patients classified by this model (DeLong test p < 0.05 across all datasets). Furthermore, a correlation and complementarity were observed between deep radiomics features and pathological deep learning features. ConclusionsThe CT deep radiomics model precisely predicts nccRCC Leibovich score risk groups preoperatively and highlights the synergistic effect between CT and pathological data.

PIEZO1 mediates matrix stiffness-induced tumor progression in kidney renal clear cell carcinoma by activating the Ca2+/Calpain/YAP pathway

ObjectiveThe significance of physical factors in the onset and progression of tumors has been increasingly substantiated by a multitude of studies. The extracellular matrix, a pivotal component of the tumor microenvironment, has been the subject of extensive investigation in connection with the advancement of KIRC (Kidney Renal Clear Cell Carcinoma) in recent years. PIEZO1, a mechanosensitive ion channel, has been recognized as a modulator of diverse physiological processes. Nonetheless, the precise function of PIEZO1 as a transducer of mechanical stimuli in KIRC remains poorly elucidated. MethodsA bioinformatics analysis was conducted using data from The Cancer Genome Atlas (TCGA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC) to explore the correlation between matrix stiffness indicators, such as COL1A1 and LOX mRNA levels, and KIRC prognosis. Expression patterns of mechanosensitive ion channels, particularly PIEZO1, were examined. Collagen-coated polyacrylamide hydrogel models were utilized to simulate varying stiffness environments and study their effects on KIRC cell behavior in vitro. Functional experiments, including PIEZO1 knockdown and overexpression, were performed to investigate the molecular mechanisms underlying matrix stiffness-induced cellular changes. Interventions in the Ca2+/Calpain/YAP Pathway were conducted to evaluate their effects on cell growth, EMT, and stemness characteristics. ResultsOur findings indicate a significant correlation between matrix stiffness and the prognosis of KIRC patients. It is observed that higher mechanical stiffness can facilitate the growth and metastasis of KIRC cells. Notably, we have also observed that the deficiency of PIEZO1 hinders the proliferation, EMT, and stemness characteristics of KIRC cells induced by a stiff matrix. Our study suggests that PIEZO1 plays a crucial role in mediating KIRC growth and metastasis through the activation of the Ca2+/Calpain/YAP Pathway. ConclusionThis study elucidates a novel mechanism through which the activation of PIEZO1 leads to calcium influx, subsequent calpain activation, and YAP nuclear translocation, thereby contributing to the progression of KIRC driven by matrix stiffness.

Mitochondrial respiratory complex II is altered in renal carcinoma.

Renal cell carcinoma (RCC) is a disease typified by anomalies in cell metabolism. The function of mitochondria, including subunits of mitochondrial respiratory complex II (CII), in particular SDHB, are often affected. Here we investigated the state and function of CII in RCC patients. We evaluated tumour tissue as well as the adjacent healthy kidney tissue of 78 patients with RCC of different histotypes, focusing on their mitochondrial function. As clear cell RCC (ccRCC) is by far the most frequent histotype of RCC, we focused on these patients, which were grouped based on the pathological WHO/ISUP grading system to low- and high-grade patients, indicative of prognosis. We also evaluated mitochondrial function in organoids derived from tumour tissue of 7 patients. ccRCC tumours were characterized by mutated von Hippel-Lindau gene and high expression of carbonic anhydrase IX. We found low levels of mitochondrial DNA, protein and function, together with CII function in ccRCC tumour tissue, but not in other RCC types and non-tumour tissues. Mitochondrial content increased in high-grade tumours, while the function of CII remained low. Tumour organoids from ccRCC patients recapitulated molecular characteristics of RCC tissue. Our findings suggest that the state of CII, epitomized by its assembly and SDHB levels, deteriorates with the progressive severity of ccRCC. These observations hold the potential for stratification of patients with worse prognosis and may guide the exploration of targeted therapeutic interventions.

SNX4 Is Correlated With Immune Infiltration and Prognosis in Clear Cell Renal Cell Carcinoma.

Clear cell renal cell carcinoma (ccRCC) is known as the most common and malignant histologic subtype of renal carcinoma. Sorting nexin 4 (SNX4) plays a regulatory role in recycling from endosomes to the plasma membrane and promotes autophagosome assembly and transport, which may exert the cancerous growth and progression. This study aimed to assess the biological role of SNX4 in ccRCC and their clinical association via public biological data platforms combined with experimental verification. In our study, we analyzed the mRNA and protein expression of SNX4 in ccRCC under different clinicopathological characteristics through The Cancer Genome Atlas (TCGA), Human Protein Atlas (HPA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC) databases. We used the Gene Expression Profiling Interactive Analysis (GEPIA) platform to conduct the survival analysis and figure out the immune cell infiltration level under different expression levels of SNX4 combined with Tumor Immune Estimation Resource (TIMER) database. Furthermore, we predicted competing endogenous RNA (ceRNA) regulatory network using TargetScan, miRDB, starBase and miRTarBase online databases. We totally collected six paired ccRCC tissues and adjacent tissues and applied quantitative real-time polymerase chain reaction (qRT-PCR) and western blot (WB) to detect the expression of SNX4 in the collected clinical specimens. The mRNA and protein expression level of SNX4 was significantly lower in ccRCC than those in normal tissues. The results proposed that lower SNX4 was expressed in patients with higher histologic grade and in male patients. Kaplan-Meier analysis demonstrated that lower mRNA expression level of SNX4 was correlated with poorer prognosis. SNX4 had positive correlation with immune cell infiltrating levels and programmed cell death-ligand 1 (PD-L1) expression. Furthermore, we constructed the SNX4/miR-221-3p/miR-222-3p/DHRS4-AS1 axis, which may be the underlying ceRNA interaction network. Finally, we verified the reduced expression of SNX4 in ccRCC by qRT-PCR and WB. The expression of SNX4 in ccRCC was lower than adjacent tissues and its downregulated expression was associated with poor prognosis of ccRCC patients. SNX4 may exert critical roles in the tumorigenesis, development and migration of ccRCC via various mechanisms.

Application of Surface Plasmon Resonance Imaging Biosensors for Determination of Fibronectin, Laminin-5, and Type IV Collagen in Plasma, Urine, and Tissue of Renal Cell Carcinoma.

Laminin, fibronectin, and collagen IV are pivotal extracellular matrix (ECM) components. The ECM environment governs the fundamental properties of tumors, including proliferation, vascularization, and invasion. Given the critical role of cell-matrix adhesion in malignant tumor progression, we hypothesize that the concentrations of these proteins may be altered in the plasma of patients with clear cell renal cell carcinoma (ccRCC). This study aimed to evaluate the serum, urine, and tissue levels of laminin-5, collagen IV, and fibronectin among a control group and ccRCC patients, with the latter divided into stages T1-T2 and T3-T4 according to the TNM classification. We included 60 patients with histopathologically confirmed ccRCC and 26 patients diagnosed with chronic cystitis or benign prostatic hyperplasia (BPH). Collagen IV, laminin-5, and fibronectin were detected using Surface Plasmon Resonance Imaging biosensors. Significant differences were observed between the control group and ccRCC patients, as well as between the T1-T2 and T3-T4 subgroups. Levels were generally higher in plasma and tissue for fibronectin and collagen IV in ccRCC patients and lower for laminin. The ROC (Receiver operating characteristic) analysis yielded satisfactory results for differentiating between ccRCC patients and controls (AUC 0.84-0.93), with statistical significance for both fibronectin and laminin in plasma and urine. Analysis between the T1-T2 and T3-T4 groups revealed interesting findings for all examined substances in plasma (AUC 0.8-0.95). The results suggest a positive correlation between fibronectin and collagen levels and ccRCC staging, while laminin shows a negative correlation, implying a potential protective role. The relationship between plasma and urine concentrations of these biomarkers may be instrumental for tumor detection and staging, thereby streamlining therapeutic decision-making.

Expanding the clinicopathologic spectrum and genomic landscape of tumors with SMARCA2/4::CREM fusions.

CREB gene family (ATF1, CREB1, CREM) fusions with either EWSR1 or FUS gene partners drive the pathogenesis of a wide range of neoplasms, including various soft tissue tumors, intracranial myxoid mesenchymal tumors (IMMTs), hyalinizing clear cell carcinoma (HCCC), and rare mesotheliomas. Recently, a SMARCA2::CREM fusion was reported in one case each of IMMT and HCCC. In this study, we expand the clinicopathologic and molecular spectrum of these neoplasms by describing three additional cases with SMARCA2::CREM and one with a novel SMARCA4::CREM fusion, highlighting the recurrent potential of additional CREB gene fusion partners beyond FET family members. To evaluate if these fusions define a new pathologic entity, we performed a comprehensive genomic and methylation analysis and compared the results to other related tumors. Tumors occurred in children and young adults (median age 20 years) and spanned a broad anatomic distribution, including soft tissue, intracranial, head and neck, and prostatic urethra. Microscopically, the tumors shared an undifferentiated round to epithelioid cell phenotype and a hyalinized fibrous stroma. Immunohistochemically, a polyphenotypic profile was observed, with variable expression of SOX10, desmin, and/or epithelial markers. No targetable genomic alterations were found using panel-based DNA sequencing. By DNA methylation and transcriptomic analyses, tumors grouped closely to FET::CREB entities, but not with SMARCA4/SMARCB1-deficient tumors. High expression of CREM by immunohistochemistry was also documented in these tumors. Patients experienced local recurrence (n = 2), locoregional lymph node metastases (n = 2), and an isolated visceral metastasis (n = 1). Overall, our study suggests that SMARCA2/4::CREM fusions define a distinct group of neoplasms with round cell to epithelioid histology, a variable immunoprofile, and a definite risk of malignancy. Larger studies are needed to further explore the pathogenetic relationship with the FET::CREB family of tumors. © 2024 The Pathological Society of Great Britain and Ireland.

A Rapidly Growing Nodule on the Eyebrow of a Pediatric Patient

A 11-year-old Caucasian girl presented to our Dermatology Unit with a 2-month history of an erythematous nodule, localized to the medial portion of her left eyebrow, rapidly growing in the two weeks before presentation. The histopathological examination revealed a dermal multi-nodular epithelial neoplasm composed of clear cells, squamous cells, and glandular cells, characterized by cytologic atypia, high mitotic activity, and an infiltrative deep growth pattern. The immunohistochemical profile of the lesion was as follows: CKAE1/AE3+, EMA+, CK8/18+, CK7+, CK19+, AR negative, p63 focally +, Ki67 25%, rare cells GCDFP15+, p53+.

Screening of differential gene expression patterns through survival analysis for diagnosis, prognosis and therapies of clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is the most prevalent subtype of kidney cancer. Although there is increasing evidence linking ccRCC to genetic alterations, the exact molecular mechanism behind this relationship is not yet completely known to the researchers. Though drug therapies are the best choice after the metastasis, unfortunately, the majority of the patients progressively develop resistance against the therapeutic drugs after receiving it for almost 2 years. In this case, multi-targeted different variants of therapeutic drugs are essential for effective treatment against ccRCC. To understand molecular mechanisms of ccRCC development and progression, and explore multi-targeted different variants of therapeutic drugs, it is essential to identify ccRCC-causing key genes (KGs). In order to obtain ccRCC-causing KGs, at first, we detected 133 common differentially expressed genes (cDEGs) between ccRCC and control samples based on nine (9) microarray gene-expression datasets with NCBI accession IDs GSE16441, GSE53757, GSE66270, GSE66272, GSE16449, GSE76351, GSE66271, GSE71963, and GSE36895. Then, we filtered these cDEGs through survival analysis with the independent TCGA and GTEx database and obtained 54 scDEGs having significant prognostic power. Next, we used protein-protein interaction (PPI) network analysis with the reduced set of 54 scDEGs to identify ccRCC-causing top-ranked eight KGs (PLG, ENO2, ALDOB, UMOD, ALDH6A1, SLC12A3, SLC12A1, SERPINA5). The pan-cancer analysis with KGs based on TCGA database showed the significant association with different subtypes of kidney cancers including ccRCC. The gene regulatory network (GRN) analysis revealed some crucial transcriptional and post-transcriptional regulators of KGs. The scDEGs-set enrichment analysis significantly identified some crucial ccRCC-causing molecular functions, biological processes, cellular components, and pathways that are linked to the KGs. The results of DNA methylation study indicated the hypomethylation and hyper-methylation of KGs, which may lead the development of ccRCC. The immune infiltrating cell types (CD8+ T and CD4+ T cell, B cell, neutrophil, dendritic cell and macrophage) analysis with KGs indicated their significant association in ccRCC, where KGs are positively correlated with CD4+ T cells, but negatively correlated with the majority of other immune cells, which is supported by the literature review also. Then we detected 10 repurposable drug molecules (Irinotecan, Imatinib, Telaglenastat, Olaparib, RG-4733, Sorafenib, Sitravatinib, Cabozantinib, Abemaciclib, and Dovitinib.) by molecular docking with KGs-mediated receptor proteins. Their ADME/T analysis and cross-validation with the independent receptors, also supported their potent against ccRCC. Therefore, these outputs might be useful inputs/resources to the wet-lab researchers and clinicians for considering an effective treatment strategy against ccRCC.

Utilising an in silico model to predict outcomes in senescence-driven acute liver injury

Currently liver transplantation is the only treatment option for liver disease, but organ availability cannot meet patient demand. Alternative regenerative therapies, including cell transplantation, aim to modulate the injured microenvironment from inflammation and scarring towards regeneration. The complexity of the liver injury response makes it challenging to identify suitable therapeutic targets when relying on experimental approaches alone. Therefore, we adopted a combined in vivo-in silico approach and developed an ordinary differential equation model of acute liver disease able to predict the host response to injury and potential interventions. The Mdm2fl/fl mouse model of senescence-driven liver injury was used to generate a quantitative dynamic characterisation of the key cellular players (macrophages, endothelial cells, myofibroblasts) and extra cellular matrix involved in liver injury. This was qualitatively captured by the mathematical model. The mathematical model was then used to predict injury outcomes in response to milder and more severe levels of senescence-induced liver injury and validated with experimental in vivo data. In silico experiments using the validated model were then performed to interrogate potential approaches to enhance regeneration. These predicted that increasing the rate of macrophage phenotypic switch or increasing the number of pro-regenerative macrophages in the system will accelerate the rate of senescent cell clearance and resolution. These results showcase the potential benefits of mechanistic mathematical modelling for capturing the dynamics of complex biological systems and identifying therapeutic interventions that may enhance our understanding of injury-repair mechanisms and reduce translational bottlenecks.

Single Atom‐Engineered 2D Catalytic Nanosheets for Sonocatalytic Suppression of Orthotopic Clear Cell Renal Cell Carcinoma

AbstractClear cell renal cell carcinoma (ccRCC), a prevalent malignant tumor, exhibits resistance to chemotherapy, necessitating advanced therapeutic approaches. Sonocatalytic therapy has emerged as a promising non‐invasive treatment for solid tumors due to its ability to penetrate deep tissue. Herein, the development of single atomic Au‐doped 2D TiO2 nanosheets are presented with oxygen vacancies (Au‐SA/Def‐TiO2, ASDT) for sonocatalytic treatment of ccRCC. Surface defects on TiO2 nanosheets effectively stabilize Au single atomic sites via the Ti‐Au‐Ti structure, enhancing catalytic properties and facilitating reactive oxygen species (ROS) generation by reducing energy barriers and improving electron (e−) and hole (h+) separation. Additionally, ASDT exhibits peroxidase‐like activities, further augmenting ROS production, leading to significant inhibition of tumor growth in subcutaneous and orthotopic ccRCC models under ultrasound irradiation. This study underscores the efficacy of defect engineering for stabilizing single atoms to boost ROS production and achieve effective tumor eradication by the enhanced sonocatalytic effect.

Signaling Pathways in Clear Cell Renal Cell Carcinoma and Candidate Drugs Unveiled through Transcriptomic Network Analysis of Hub Genes

Clear cell renal cell carcinoma (ccRCC) is a type of kidney cancer. It advances quickly and often metastasizes, making the prognosis for patients challenging. This study used weighted gene co-expression network analysis (WGCNA) to study gene expression data of different stages of ccRCC obtained in the GEO database. The analysis identified three significant highly preserved gene modules across the datasets: GSE53757, GSE22541, GSE66272, and GSE73731. Functional annotation and pathway enrichment analysis using DAVID revealed inflammatory pathways (e.g., NF-kB, Hippo, and HIF-1 pathways) that may drive ccRCC development and progression. The study also introduced the involvement of viral infections associated with the disease in the metabolic reprogramming of ccRCC. A drug repurposing analysis was also conducted to identify potential drug candidates for ccRCC using the upregulated and downregulated hub genes. The top candidates are ziprasidone (dopamine and serotonin receptor antagonist) and fentiazac (cyclooxygenase inhibitor). Other drug candidates were also obtained, such as phosphodiesterase/DNA methyltransferase/ATM kinase inhibitors, acetylcholine antagonists, and NAD precursors. Overall, the study’s findings suggest that identifying several genes and signaling pathways related to ccRCC may uncover new targets, biomarkers, and even drugs that can be repurposed, which can help develop new and effective treatments for the disease.

Expression analysis, molecular docking and molecular dynamics simulations to identify potential BTK inhibitors: strategy for targeting pan-cancer

ABSTRACT Bruton's Tyrosine Kinase (BTK), a soluble tyrosine kinase plays an essential role in the growth, development, and signalling of B cells. It is a non-receptor kinase that is crucial for leukemic cell survival, proliferation, and oncogenic signalling in many B cell malignancies. The enhanced metastasis caused by BTK expression may be reduced by BTK inhibitors, which also have powerful therapeutic effects. The goal of the study is to identify potential inhibitors which have good binding affinity with BTK. The current study also aims to investigate the expression pattern and the prognostic significance of BTK across all cancer types. Interestingly, it was found that BTK was highly overexpressed in numerous cancer types including; clear cell renal carcinoma, glioblastoma, head and neck, liver and breast cancer. BTK was found to reduce the relapse-free and overall survival rate. Furthermore, using in silico approach two structural analogues of Pirtobrutinib namely; 163207918 and 129269825 that bind to BTK with higher affinity were identified. Using drug-likeness analysis the therapeutic possibility of screened Pirtobrutinib analogues were evaluated. The Molecular docking and dynamic analysis revealed that the new Pirtobrutinib analogues could be potent inhibitors with higher binding affinity and stability in comparison with the parent compound. In conclusion, after preclinical and clinical research, the identified analogues may open the door for their prospective use in cancer therapy.