PHF8-GLUL axis in lipid deposition and tumor growth of clear cell renal cell carcinoma

Advanced N-glycoproteomics and proteomics approach revealed sexually dimorphic molecular signatures in primary mouse hepatocyte

Sexual dimorphism plays a critical role in disease pathophysiology, but the subtlety and complexity of these differences, along with a lack of precise comparative methods, hinder the advancement of precision medicine and drug development. This limitation is particularly evident in metabolic dysfunction-associated steatotic liver disease (MASLD), where sex-specific molecular mechanisms remain insufficiently understood. To address this gap, we employed an advanced integrative N-glycoproteomics and proteomics approach to systematically analyze sex-biased molecular signatures in primary mouse hepatocytes (PMHs) under healthy and MASLD conditions. Our analysis identified 280 sex-biased proteins and 39 sex-biased N-glycosites, and KEGG enrichment revealed that female-biased molecules were primarily involved in lipid metabolism, while male-biased molecules were associated with inflammation and cytoskeletal remodeling. A combined dataset of 302 sex-biased molecules was further analyzed using protein-protein interaction (PPI) analysis and Rc value calculations, resulting in the identification of 21 hub proteins and 2 hub N-glycosites as MASLD-associated sex-biased signatures. Notably, MASLD amplified proteomic sex differences while attenuating them in N-glycosylation. Western blot validation of key signatures, including female-biased MVK and male-biased LGALS3, highlighted distinct molecular adaptations between the sexes in MASLD progression. Our study introduced an advanced analytical framework for high-resolution comparative molecular profiling by integrating N-glycoproteomics with proteomics, providing valuable insights into sex-biased molecular signatures, enhancing preclinical model development, and advancing sex-specific therapeutic strategies in MASLD research and broader biological systems.

Circulating bile acid profiles characteristics and the potential predictive role in clear cell renal cell carcinoma progression

BACKGROUND

The incidence of clear cell renal cell carcinoma (ccRCC) has steadily increased over the past decade, and recent studies have linked bile acid (BA) metabolism to its development. However, the metabolic profile of BAs and their potential as biomarkers in ccRCC pathogenesis remain poorly characterized, making their evaluation crucial for advancing disease understanding and management.

METHODS

A total of 68 newly diagnosed ccRCC patients and 63 healthy controls were enrolled. Serum bile acid (BA) profiles were measured using Ultra Performance Liquid Chromatography-Tandem Mass Spectrometry (UPLC-MS/MS). The Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) model analyzed differences in serum BA profiles between ccRCC patients and controls. Additionally, the relationship between BA profiles and tumor heterogeneity parameters was investigated. Receiver Operating Characteristic (ROC) analysis identified potential biomarkers for ccRCC pathogenesis.

RESULTS

The BA profile was altered in ccRCC patients and was not influenced by sex or age. Specifically, primary and secondary unconjugated BA fractions were significantly higher in the ccRCC population. Five BA metabolite candidates exhibited the most significant differences between ccRCC patients and controls. Deoxycholic acid (DCA) was associated with pathological pTNM stage classification and grade. Chenodeoxycholic acid (CDCA) and lithocholic acid (LCA), combined with testosterone, showed potential as biomarkers for the pathogenesis of ccRCC.

CONCLUSION

Alterations in the serum BA profile are observed in ccRCC. Deoxycholic acid (DCA) correlates with pathological pTNM stage classification and tumor grade. Additionally, CDCA combined with LCA show potential as biomarkers for ccRCC pathogenesis.

CLINICAL TRIAL NUMBER

Not applicable.

The perspective of targeting cancer cell metabolism: combination therapy approaches

Cancer cells are considered the most adaptable for their metabolic status, which supports growth, survival, rapid proliferation, invasiveness, and metastasis in a nutrient-deficient microenvironment. Since the discovery of altered glucose metabolism (aerobic glycolysis), which is generally known as a part of metabolic reprogramming and an innate trait of cancer cells, in 1930 via Dr. Otto Warburg, numerous studies have endeavored to recognize various aspects of cancer cell metabolism and find new methods for efficiently eradicating described cells by targeting their energy metabolism. In this way, the outcomes have mainly been promising. Accordingly, outlining the related results will indeed assist us in making a definitive path for developing targeted therapy strategies based on cancer cell-altered metabolism. The present study reviews the key features of cancer cell metabolism and treatment strategies based on them. It emphasizes the importance of targeting cancer cell dysregulated metabolic pathways that influence the cell energy supply and manage cancer cell growth and survival. This trial also introduces a multimodal therapeutic strategy hypothesis, a potential next-generation combination therapy approach, and suggests interdisciplinary research to recognize the complexities of cancer metabolism and exploit them for designing more efficacious cancer therapeutic strategies.

20 years of histone lysine demethylases: From discovery to the clinic and beyond

Twenty years ago, histone lysine demethylases (KDMs) were discovered. Since their discovery, they have been increasingly studied and shown to be important across species, development, and diseases. Considerable advances have been made toward understanding their (1) enzymology, (2) role as critical components of biological complexes, (3) role in normal cellular processes and functions, (4) implications in pathological conditions, and (5) therapeutic potential. This Review covers these key relationships related to the KDM field with the awareness that numerous laboratories have contributed to this field. The current knowledge coupled with future insights will shape our understanding about cell function, development, and disease onset and progression, which will allow for novel biomarkers to be identified and for optimal therapeutic options to be developed for KDM-related diseases in the years ahead.

Clear Cell Renal Cell Carcinoma: Characterizing the Phenotype of Von Hippel-Lindau Mutation Using MRI

BACKGROUND

The von Hippel-Lindau (VHL) mutation is an important alteration in clear cell renal cell carcinoma (ccRCC); however, its imaging phenotype remains unclear.

PURPOSE

To investigate whether MRI features can reflect the VHL mutation status.

STUDY TYPE

Retrospective.

FIELD STRENGTH/SEQUENCE

3 T/fast spin echo T2-weighted, spin-echo echo planar diffusion-weighted, gradient recalled echo T1-weighted, gradient recalled echo chemical-shift T1-weighted, and contrast-enhanced gradient recalled echo T1-weighted sequences.

POPULATION

One hundred five patients with ccRCC who underwent preoperative contrast-enhanced MRI and subsequent genomic sequencing: 59 consecutive patients from our institution (38 [64.41%] with VHL mutations) formed a training cohort, and 46 from The Cancer Genome Atlas (TCGA) database (24 [52.17%] with VHL mutations) formed an independent test cohort.

ASSESSMENT

Two radiologists, with 23 and 33 years of experience respectively, jointly evaluated the semantic MRI features of the primary lesion in ccRCCs to propose potential features related to VHL mutations in both cohorts. Three additional readers, with 5, 7, and 10 years of experience respectively, independently reviewed all lesions to assess the interobserver agreement of MRI features. A VHL mutational likelihood score (VHL-MULIS) system was constructed using the training cohort and validated using the independent test cohort.

STATISTICAL TESTS

Fisher's test or chi-square test, t-test or Mann-Whitney U test, logistic regression, Cohen's kappa (κ), area under the receiver operating characteristic curve (AUC). A two-sided P value <0.05 was considered statistically significant.

RESULTS

In both the local and public cohorts, T2-weighted signal intensity and presence of microscopic fat from primary lesions were significantly associated with VHL mutation status. The VHL-MULIS incorporated maximum diameter, T2-weighted signal intensity, and presence of microscopic fat in the training cohort and demonstrated promising diagnostic ability (AUC, 0.82; sensitivity, 0.79; specificity, 0.82) and substantial interobserver agreement (κ, 0.787) in the test cohort.

DATA CONCLUSION

The VHL mutation exhibited a distinct MRI phenotype. Integrating multiple semantic MRI features has potential to reflect the mutation status in patients with ccRCC.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 2.

PHF8/KDM7B: A Versatile Histone Demethylase and Epigenetic Modifier in Nervous System Disease and Cancers

Many human diseases, such as malignant tumors and neurological diseases, have a complex pathophysiological etiology, often accompanied by aberrant epigenetic changes including various histone modifications. Plant homologous domain finger protein 8 (PHF8), also known as lysine-specific demethylase 7B (KDM7B), is a critical histone lysine demethylase (KDM) playing an important role in epigenetic modification. Characterized by the zinc finger plant homology domain (PHD) and the Jumonji C (JmjC) domain, PHF8 preferentially binds to H3K4me3 and erases repressive methyl marks, including H3K9me1/2, H3K27me1, and H4K20me1. PHF8 is indispensable for developmental processes and the loss of PHF8 enzyme activity is linked to neurodevelopmental disorders. Moreover, increasing evidence shows that PHF8 is highly expressed in multiple tumors as an oncogenic factor. These findings indicate that studying the role of PHF8 will facilitate the development of novel therapeutic agents by the manipulation of PHF8 demethylation activity. Herein, we summarize the current knowledge of PHF8 about its structure and demethylation activity and its involvement in development and human diseases, with an emphasis on nervous system disorders and cancer. This review will update our understanding of PHF8 and promote the clinical transformation of its predictive and therapeutic value.

Histone demethylase PHF8 promotes prostate cancer metastasis via the E2F1-SNAI1 axis

Metastasis is the primary culprit behind cancer-related fatalities in multiple cancer types, including prostate cancer. Despite great advances, the precise mechanisms underlying prostate cancer metastasis are far from complete. By using a transgenic mouse prostate cancer model (TRAMP) with and without Phf8 knockout, we have identified a crucial role of PHF8 in prostate cancer metastasis. By complexing with E2F1, PHF8 transcriptionally upregulates SNAI1 in a demethylation-dependent manner. The upregulated SNAI1 subsequently enhances epithelial-to-mesenchymal transition (EMT) and metastasis. Given the role of the abnormally activated PHF8/E2F1-SNAI1 axis in prostate cancer metastasis and poor prognosis, the levels of PHF8 or the activity of this axis could serve as biomarkers for prostate cancer metastasis. Moreover, targeting this axis could become a potential therapeutic strategy for prostate cancer treatment. © 2024 The Pathological Society of Great Britain and Ireland.

Identification of PI3K-AKT Pathway-Related Genes and Construction of Prognostic Prediction Model for ccRCC

BACKGROUND

Clear cell renal cell carcinoma (ccRCC), the predominate histological type of renal cell carcinoma (RCC), has been extensively studied, with poor prognosis as the stage increases. Research findings consistently indicated that the PI3K-Akt pathway is commonly dysregulated across various cancer types, including ccRCC. Targeting the PI3K-Akt pathway held promise as a potential therapeutic approach for treating ccRCC. Development and validation of PI3K-Akt pathway-related genes related biomarkers can enhance healthcare management of patients with ccRCC.

PURPOSE

This study aimed to identify the key genes in the PI3K-Akt pathway associated with the diagnosis and prognosis of CCRCC using data mining from the Cancer Genome Atlas (TCGA) and Gene Expression Synthesis (GEO) datasets.

METHODS

The purpose of this study is to use bioinformatics methods to screen data sets and clinicopathological characteristics associated with ccRCC patients. The exhibited significantly differential expressed genes (DEGs) associated with the PI3K-Akt pathway were examined by KEGG. In addition, Kaplan-Meier (KM) analysis used to estimate the survival function of the differential genes by using the UALCAN database and graphPad Prism 9.0. And exploring the association between the expression levels of the selected genes and the survival status and time of patients with ccRCC based on SPSS22.0. Finally, a multigene prognostic model was constructed to assess the prognostic risk of ccRCC patients.

RESULTS

A total of 911 genes with common highly expressed were selected based on the GEO and TCGA databases. According to the KEGG pathway analysis, there were 42 genes enriched in PI3K-Akt signalling pathway. And seven of highly expressed genes were linked to a poor prognosis in ccRCC. And a multigene prognostic model was established based on IL2RG, EFNA3, and MTCP1 synergistic expression might be utilized to predict the survival of ccRCC patients.

CONCLUSIONS

Three PI3K-Akt pathway-related genes may be helpful to identify the prognosis and molecular characteristics of ccRCC patients and to improve therapeutic regimens, and these risk characteristics might be further applied in the clinic.

Glutamine Metabolism and Prostate Cancer

Glutamine (Gln) is a non-essential amino acid that is involved in the development and progression of several malignancies, including prostate cancer (PCa). While Gln is non-essential for non-malignant prostate epithelial cells, PCa cells become highly dependent on an exogenous source of Gln. The Gln metabolism in PCa is tightly controlled by well-described oncogenes such as MYC, AR, and mTOR. These oncogenes contribute to therapy resistance and progression to the aggressive castration-resistant PCa. Inhibition of Gln catabolism impedes PCa growth, survival, and tumor-initiating potential while sensitizing the cells to radiotherapy. Therefore, given its significant role in tumor growth, targeting Gln metabolism is a promising approach for developing new therapeutic strategies. Ongoing clinical trials evaluate the safety and efficacy of Gln catabolism inhibitors in combination with conventional and targeted therapies in patients with various solid tumors, including PCa. Further understanding of how PCa cells metabolically interact with their microenvironment will facilitate the clinical translation of Gln inhibitors and help improve therapeutic outcomes. This review focuses on the role of Gln in PCa progression and therapy resistance and provides insights into current clinical trials.

The role of metabolic reprogramming in kidney cancer

Metabolic reprogramming is a cellular process in which cells modify their metabolic patterns to meet energy requirements, promote proliferation, and enhance resistance to external stressors. This process also introduces new functionalities to the cells. The 'Warburg effect' is a well-studied example of metabolic reprogramming observed during tumorigenesis. Recent studies have shown that kidney cells undergo various forms of metabolic reprogramming following injury. Moreover, metabolic reprogramming plays a crucial role in the progression, prognosis, and treatment of kidney cancer. This review offers a comprehensive examination of renal cancer, metabolic reprogramming, and its implications in kidney cancer. It also discusses recent advancements in the diagnosis and treatment of renal cancer.

Acetylation- and ubiquitination-regulated SFMBT2 acts as a tumor suppressor in clear cell renal cell carcinoma

BACKGROUND

Clear cell renal cell carcinoma (RCC) is the most common kidney tumor. The analysis from medical database showed that Scm-like with four MBT domains protein 2 (SFMBT2) was decreased in advanced clear cell RCC cases, and its downregulation was associated with the poor prognosis. This study aims to investigate the role of SFMBT2 in clear cell RCC.

METHODS

The expression of SFMBT2 in clear cell RCC specimens were determined by immunohistochemistry staining and western blot. The overexpression and knockdown of SFMBT2 was realized by infection of lentivirus loaded with SFMBT2 coding sequence or silencing fragment in 786-O and 769-P cells, and its effects on proliferation and metastasis were assessed by MTT, colony formation, flow cytometry, wound healing, transwell assay, xenograft and metastasis experiments in nude mice. The interaction of SFMBT2 with histone deacetylase 3 (HDAC3) and seven in absentia homolog 1 (SIAH1) was confirmed by co-immunoprecipitation.

RESULTS

In our study, SFMBT2 exhibited lower expression in clear cell RCC specimens with advanced stages than those with early stages. Overexpression of SFMBT2 inhibited the growth and metastasis of clear cell RCC cells, 786-O and 769-P, in vitro and in vivo, and its silencing displayed opposites effects. HDAC3 led to deacetylation of SFMBT2, and the HDAC3 inhibitor-induced acetylation prevented SFMBT2 from SIAH1-mediated ubiquitination modification and proteasome degradation. K687 in SFMBT2 protein molecule may be the key site for acetylation and ubiquitination.

CONCLUSIONS

SFMBT2 exerted an anti-tumor role in clear cell RCC cells, and HDAC3-mediated deacetylation promoted SIAH1-controlled ubiquitination of SFMBT2. SFMBT2 may be considered as a novel clinical diagnostic marker and/or therapeutic target of clear cell RCC, and crosstalk between its post-translational modifications may provide novel insights for agent development.

P2RY13 is a prognostic biomarker and associated with immune infiltrates in renal clear cell carcinoma: A comprehensive bioinformatic study

Background and Aims

Clear cell renal cell carcinoma (ccRCC) is a common and aggressive form of cancer with a high incidence globally. This study aimed to investigate the role of P2RY13 in the progression of ccRCC and elucidate its mechanism of action.

Methods

Gene Expression Omnibus and The Cancer Genome Atlas databases were used to extract gene expression profiles of ccRCC. These profiles were annotated and visualized by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses, as well as Gene Set Enrichment Analysis (GSEA). The STRING database was used to establish a protein-protein interaction network and to analyze the functional similarity. The GEPIA2 database was used to predict survival associated with hub genes. Meanwhile, the TIMER2.0 database was used to assess immune cell infiltration and its link with the hub genes. Immunohistochemistry (IHC) was used to determine the difference between ccRCC and adjacent normal tissue.

Results

We identified 272 differentially expressed genes (DEGs). GO and KEGG analyses suggested that DEGs were primarily involved in lymphocyte activation, inflammatory response, immunological effector mechanism pathways. By cytohubba, the 20 highest-scoring hub genes were screened to identify critical genes in the protein-protein interaction network linked with ccRCC. Resting dendritic cells, CD8 T cells, and activated mast cells all showed a significant positive correlation with these hub genes. Moreover, a higher immune score was associated with increased prognostic risk scores, which in turn correlated with a poorer prognosis. IHC revealed that P2RY13 was expressed at higher levels in ccRCC compared to para-cancer tissues.

Conclusion

Identifying the DEGs will aid in the understanding of the causes and molecular mechanisms involved in ccRCC. P2RY13 may play a pivotal role in the progression and prognosis of ccRCC, potentially driving carcinogenesis though immune system mechanisms.