Down-regulation of ACACA suppresses the malignant progression of Prostate Cancer through inhibiting mitochondrial potential

Advancing functional foods: a systematic analysis of plant-derived exosome-like nanoparticles and their health-promoting properties

Plant-derived exosome-like nanoparticles (PDENs), emerging as novel bioactive agents, exhibit significant potential in food science and nutritional health. These nanoparticles, enriched with plant-specific biomolecules such as proteins, lipids, nucleic acids, and secondary metabolites, demonstrate unique cross-species regulatory capabilities, enabling interactions with mammalian cells and gut microbiota. PDENs enhance nutrient bioavailability by protecting sensitive compounds during digestion, modulate metabolic pathways through miRNA-mediated gene regulation, and exhibit anti-inflammatory and antioxidant properties. For instance, grape-derived PDENs reduce plasma triglycerides in high-fat diets, while ginger-derived nanoparticles alleviate colitis by downregulating pro-inflammatory cytokines. Additionally, PDENs serve as natural drug carriers, with applications in delivering therapeutic agents like doxorubicin and paclitaxel. Despite these advancements, challenges remain in standardizing extraction methods (ultracentrifugation, immunoaffinity), ensuring stability during food processing and storage, and evaluating long-term safety. Current research highlights the need for optimizing lyophilization techniques and understanding interactions between PDENs and food matrices. Furthermore, while PDENs show promise in functional food development-such as fortified beverages and probiotic formulations-their clinical translation requires rigorous pharmacokinetic studies and regulatory clarity. This review synthesizes existing knowledge on PDENs' composition, biological activities, and applications, while identifying gaps in scalability, stability, and safety assessments. Future directions emphasize interdisciplinary collaboration to harness PDENs' potential in combating metabolic disorders, enhancing food functionality, and advancing personalized nutrition strategies.

Identification and validation of biomarkers related to mitochondria during ex vivo lung perfusion for lung transplants based on machine learning algorithm

BACKGROUND

Ex vivo lung perfusion (EVLP) is a critical strategy to rehabilitate marginal donor lungs, thereby increasing lung transplantation (LTx) rates. Ischemia-reperfusion (I/R) injury inevitably occurs during LTx. Exploring the common mechanisms between EVLP and I/R may unveil new treatment targets to enhance LTx outcomes.

METHODS

We obtained datasets from the public Gene Expression Omnibus (GEO) for EVLP (GSE127055 and GSE127057) and I/R (GSE145989) processes. We performed analysis of differentially expressed genes (DEGs) and Gene Set Enrichment Analysis (GSEA). Mitochondrial genes were sourced from the MitoCarta 3.0 database. Hub mitochondrial-related DEGs (MitoDEGs) were identified using a combination of protein-protein interaction networks and machine learning methods, which were further validated in cell and mice models of EVLP.

RESULTS

GSEA analysis of DEGs following EVLP and I/R revealed significant inhibition of mitochondrial function pathways, encompassing mitochondrial central dogma, mtRNA metabolism, OXPHOS assembly factors, metals and cofactors, and heme synthesis and processing processes. Machine learning algorithms including Random Forest, LASSO, and XGBoost identified five downregulated genes (MTERF1, ACACA, COX15, OSGEPL1, and COQ9) as hub MitoDEGs for both EVLP and I/R processes. We confirmed the reduced expression of these hub MitoDEGs in endothelial cells during EVLP and observed mitochondrial damage in endothelial cells characterized by swollen morphology and cristae disappearance.

CONCLUSIONS

Imbalance in mitochondrial homeostasis is a shared pathological process during EVLP and I/R-induced lung injury. The identified hub mitochondrial-related genes (MTERF1, ACACA, COX15, OSGEPL1, and COQ9) suggest promising therapeutic targets for lung injury during LTx. The downregulation of these genes indicates a significant disruption in mitochondrial function. This study provides potential mitochondrial-related therapeutic targets for I/R-induced lung injury and for donor lung repair during EVLP procedure in LTx.

Identification of Novel 58-5p and SREBF1 Interaction and Effects on Apoptosis of Ovine Ovarian Granulosa Cell

High concentrations of prolactin (PRL)-induced ovine ovarian granulosa cell (GCs) apoptosis and MAPK12 could aggravate the induced effect. However, the molecular mechanisms that MAPK12-induced GC apoptosis and repressed steroid hormone secretion remain unclear. In this study, GCs in the P group (GCs with high PRL concentration: 500 ng/mL PRL) and P-10 group (GCs with 500 ng/mL PRL infected by lentiviruses carrying overexpressed sequences of MAPK12) were collected for whole-transcriptome analysis. Then, we applied the miRNA mimics combined with a dual-luciferase reporter gene assay to explore the molecular mechanisms through which MAPK12 affected GC apoptosis and steroid hormones secretion. The whole-transcriptome analysis indicated that MAPK12 regulated high PRL concentration GC apoptosis and steroid hormone secretion mainly through novel 58. The expression of pro-apoptotic proteins Caspase 3 and Bax was increased, while the expression of anti-apoptotic protein BCL-2 declined by novel 58-5p in high PRL concentration GCs (p < 0.05); The secretion of steroid hormones and genes associated with steroid secretion (CYP11A1, 3β-HSD and CYP19A1) decreased (p < 0.05), while the protein expression of the target gene, SREBF1 of novel 58, was repressed by novel 58-5p in high PRL concentration GCs (p < 0.05). Dual-luciferase reporter gene analysis showed that SREBF1 was confirmed as a target gene of novel 58-5p and the negative feedback interaction was established between novel 58-5p and SREBF1. The ggccggctgggggattgccg sequence may be the target site of SREBF1, targeted by novel 58-5p. In addition, steroid hormone secretion was reduced and GC apoptosis was suppressed after the interference of SREBF1 in ovine ovarian GCs with high PRL concentration. In conclusion, novel 58-5p regulated ovine ovarian GC apoptosis and steroid hormone secretion by targeting SREBF1.

Exploring glioma heterogeneity through omics networks: from gene network discovery to causal insights and patient stratification

Gliomas are primary malignant brain tumors with a typically poor prognosis, exhibiting significant heterogeneity across different cancer types. Each glioma type possesses distinct molecular characteristics determining patient prognosis and therapeutic options. This study aims to explore the molecular complexity of gliomas at the transcriptome level, employing a comprehensive approach grounded in network discovery. The graphical lasso method was used to estimate a gene co-expression network for each glioma type from a transcriptomics dataset. Causality was subsequently inferred from correlation networks by estimating the Jacobian matrix. The networks were then analyzed for gene importance using centrality measures and modularity detection, leading to the selection of genes that might play an important role in the disease. To explore the pathways and biological functions these genes are involved in, KEGG and Gene Ontology (GO) enrichment analyses on the disclosed gene sets were performed, highlighting the significance of the genes selected across several relevent pathways and GO terms. Spectral clustering based on patient similarity networks was applied to stratify patients into groups with similar molecular characteristics and to assess whether the resulting clusters align with the diagnosed glioma type. The results presented highlight the ability of the proposed methodology to uncover relevant genes associated with glioma intertumoral heterogeneity. Further investigation might encompass biological validation of the putative biomarkers disclosed.

Aberrant Energy Metabolism in Tumors and Potential Therapeutic Targets

Energy metabolic reprogramming is frequently observed during tumor progression as tumor cells necessitate adequate energy production for rapid proliferation. Although current medical research shows promising prospects in studying the characteristics of tumor energy metabolism and developing anti-tumor drugs targeting energy metabolism, there is a lack of systematic compendiums and comprehensive reviews in this field. The objective of this study is to conduct a systematic review on the characteristics of tumor cells' energy metabolism, with a specific focus on comparing abnormalities between tumor and normal cells, as well as summarizing potential targets for tumor therapy. Additionally, this review also elucidates the aberrant mechanisms underlying four major energy metabolic pathways (glucose, lipid, glutamine, and mitochondria-dependent) during carcinogenesis and tumor progression. Through the utilization of graphical representations, we have identified anomalies in crucial energy metabolism pathways, encompassing transporter proteins (glucose transporter, CD36, and ASCT2), signaling molecules (Ras, AMPK, and PTEN), as well as transcription factors (Myc, HIF-1α, CREB-1, and p53). The key molecules responsible for aberrant energy metabolism in tumors may serve as potential targets for cancer therapy. Therefore, this review provides an overview of the distinct energy-generating pathways within tumor cells, laying the groundwork for developing innovative strategies for precise cancer treatment.

A compendium of mitochondrial molecular characteristics provides novel perspectives on the treatment of rheumatoid arthritis patients

Rheumatoid arthritis (RA) is an autoimmune disease that exhibits a high degree of heterogeneity, marked by unpredictable disease flares and significant variations in the response to available treatments. The lack of optimal stratification for RA patients may be a contributing factor to the poor efficacy of current treatment options. The objective of this study is to elucidate the molecular characteristics of RA through the utilization of mitochondrial genes and subsequently construct and authenticate a diagnostic framework for RA. Mitochondrial proteins were obtained from the MitoCarta database, and the R package limma was employed to filter for differentially expressed mitochondrial genes (MDEGs). Metascape was utilized to perform enrichment analysis, followed by an unsupervised clustering algorithm using the ConsensuClusterPlus package to identify distinct subtypes based on MDEGs. The immune microenvironment, biological pathways, and drug response were further explored in these subtypes. Finally, a multi-biomarker-based diagnostic model was constructed using machine learning algorithms. Utilizing 88 MDEGs present in transcript profiles, it was possible to classify RA patients into three distinct subtypes, each characterized by unique molecular and cellular signatures. Subtype A exhibited a marked activation of inflammatory cells and pathways, while subtype C was characterized by the presence of specific innate lymphocytes. Inflammatory and immune cells in subtype B displayed a more modest level of activation (Wilcoxon test P < 0.05). Notably, subtype C demonstrated a stronger correlation with a superior response to biologics such as infliximab, anti-TNF, rituximab, and methotrexate/abatacept (P = 0.001) using the fisher test. Furthermore, the mitochondrial diagnosis SVM model demonstrated a high degree of discriminatory ability in distinguishing RA in both training (AUC = 100%) and validation sets (AUC = 80.1%). This study presents a pioneering analysis of mitochondrial modifications in RA, offering a novel framework for patient stratification and potentially enhancing therapeutic decision-making.

A Splicing Transcriptome-Wide Association Study Identifies Candidate Altered Splicing for Prostate Cancer Risk

Prostate cancer (PCa) represents a huge public health burden among men. Many susceptibility genetic factors for PCa still remain unknown. In this study, we performed a large splicing transcriptome-wide association study (spTWAS) using three modeling strategies to develop alternative splicing genetic prediction models for identifying novel susceptibility loci and splicing introns for PCa risk by assessing 79,194 cases and 61,112 controls of European ancestry in the PRACTICAL, CRUK, CAPS, BPC3, and PEGASUS consortia. We identified 120 splicing introns of 97 genes showing an association with PCa risk at false discovery rate (FDR)-corrected threshold (FDR <0.05). Of them, 33 genes were enriched in PCa-related diseases and function categories. Fine-mapping analysis suggested that 21 splicing introns of 19 genes were likely causally associated with PCa risk. Thirty-five splicing introns of 34 novel genes were identified to be related to PCa susceptibility for the first time, and 11 of the genes were enriched in a cancer-related network. Our study identified novel loci and splicing introns associated with PCa risk, which can improve our understanding of the etiology of this common malignancy.

Identification of acetyl-CoA carboxylase alpha as a prognostic and targeted candidate for hepatocellular carcinoma

PURPOSE

The de novo lipogenesis has been a longstanding observation in hepatocellular carcinoma (HCC). However, the prognostic value and carcinogenic roles of the enzyme Acetyl-CoA carboxylase alpha (ACACA) in HCC remains unknown.

METHODS

The proteins with remarkable prognostic significance were screened out from The Cancer Proteome Atlas Portal (TCPA) database. Furthermore, the expression characteristics and prognostic value of ACACA were evaluated in multiple databases and the local HCC cohort. The loss-of-function assays were performed to uncover the potential roles of ACACA in steering malignant behaviors of HCC cells. The underlying mechanisms were conjectured by bioinformatics and validated in HCC cell lines.

RESULTS

ACACA was identified as a crucial factor of HCC prognosis. Bioinformatics analyses showed that HCC patients with higher expression of ACACA protein or mRNA levels had poor prognosis. Knockdown of ACACA remarkably crippled the proliferation, colony formation, migration, invasion, epithelial-mesenchymal transition (EMT) process of HCC cells and induced the cell cycle arrest. Mechanistically, ACACA might facilitate the malignant phenotypes of HCC through aberrant activation of Wnt/β-catenin signaling pathway. In addition, ACACA expression was associated with the dilute infiltration of immune cells including plasmacytoid DC (pDC) and cytotoxic cells by utilization of relevant database analysis.

CONCLUSION

ACACA could be a potential biomarker and molecular target for HCC.

High Expression of COA6 Is Related to Unfavorable Prognosis and Enhanced Oxidative Phosphorylation in Lung Adenocarcinoma

Mitochondrial metabolism plays an important role in the occurrence and development of cancers. Cytochrome C oxidase assembly factor six (COA6) is essential in mitochondrial metabolism. However, the role of COA6 in lung adenocarcinoma (LUAD) remains unknown. Here we report that the expression of COA6 mRNA and protein were upregulated in LUAD tissues compared with lung normal tissues. We found that COA6 had high sensitivity and specificity to distinguish LUAD tissues from normal lung tissues shown by a receiver operating characteristic (ROC) curve. In addition, our univariate and multivariate Cox regression analysis indicated that COA6 was an independent unfavorable prognostic factor for LUAD patients. Furthermore, our survival analysis and nomogram showed that a high expression of COA6 mRNA was related to the short overall survival (OS) of LUAD patients. Notably, our weighted correlation network analysis (WGCNA) and functional enrichment analysis revealed that COA6 may participate in the development of LUAD by affecting mitochondrial oxidative phosphorylation (OXPHOS). Importantly, we demonstrated that depletion of COA6 could decrease the mitochondrial membrane potential (MMP), nicotinamide adenine dinucleotide (NAD) + hydrogen (H) (NADH), and adenosine triphosphate (ATP) production in LUAD cells (A549 and H1975), hence inhibiting the proliferation of these cells in vitro. Together, our study strongly suggests that COA6 is significantly associated with the prognosis and OXPHOS in LUAD. Hence, COA6 is highly likely a novel prognostic biomarker and therapeutic target of LUAD.

Peripubertal Nutritional Prevention of Cancer-Associated Gene Expression and Phenotypes

Breast cancer (BC) is a nearly ubiquitous malignancy that effects the lives of millions worldwide. Recently, nutritional prevention of BC has received increased attention due to its efficacy and ease of application. Chief among chemopreventive compounds are plant-based substances known as dietary phytochemicals. Sulforaphane (SFN), an epigenetically active phytochemical found in cruciferous vegetables, has shown promise in BC prevention. In addition, observational studies suggest that the life stage of phytochemical consumption may influence its anticancer properties. These life stages, called critical periods (CPs), are associated with rapid development and increased susceptibility to cellular damage. Puberty, a CP in which female breast tissue undergoes proliferation and differentiation, is of particular interest for later-life BC development. However, little is known about the importance of nutritional chemoprevention to CPs. We sought to address this by utilizing two estrogen receptor-negative [ER(-)] transgenic mouse models fed SFN-containing broccoli sprout extract during the critical period of puberty. We found that this treatment resulted in a significant decrease in tumor incidence and weight, as well as an increase in tumor latency. Further, we found significant alterations in the long-term expression of cancer-associated genes, including p21, p53, and BRCA2. Additionally, our transcriptomic analyses identified expressional changes in many cancer-associated genes, and bisulfite sequencing revealed that the antiproliferation-associated gene Erich4 was both hypomethylated and overexpressed in our experimental group. Our study indicates that dietary interventions during the CP of puberty may be important for later-life ER(-) BC prevention and highlights potential important genetic and epigenetic targets for treatment and study of the more deadly variants of BC.

Construction and Validation of Protein Expression-related Prognostic Models in Clear Cell Renal Cell Carcinoma

Objective: To construct a prognostic evaluation model for clear cell renal cell carcinoma (ccRCC) patients using bioinformatics method and to screen potential drugs for ccRCC. Methods: ccRCC RNA sequencing data, clinical data, and protein expression data were downloaded from the TCGA database. Univariate Cox and Lasso regression analyses were performed on the combined data to screen out the proteins related to the prognosis, and they were included in a multivariate Cox proportional hazard model. The patients were divided into high and low-risk groups for a survival difference analysis. The predictive power of the model was evaluated on the basis of overall survival, progression-free survival, independent prognostic, clinically relevant receiver operating characteristic (ROC) curve, C-index, principal component, and clinical data statistics analyses. GSEA enrichment and immune function correlation analyses were performed. The samples were divided into different subtypes based on the expression of the risk proteins, and survival analysis of the subtypes was performed. The risk-related protein and RNA sequencing data were analyzed to screen out sensitive drugs with significant differences between the high and low-risk groups. Results: A total of 469 ccRCC-related proteins were screened, of which 13 proteins with independent prognostic significance were screened by univariate Cox, Lasso, and multivariate Cox regression analyses to construct the prognostic model. The sensitivity and accuracy of the model in predicting the survival of patients with ccRCC were high (1 year: 0.811, 3 years: 0.783, 5 years: 0.777). The 13 proteins were closely related to immunity, and the model proteins were different between kidney and tumor tissues according to the HPA database. The samples were divided into three subtypes, and there were obvious clinical characteristics of the three subtypes in the grade and T, N and M stages. According to the IC50 values, CGP-60474, vinorelbine, doxorubicin, etoposide, FTI-277, JQ12, OSU-03012, pyrimethamine, and other drugs were more sensitive in the high-risk group. Conclusions: A prognostic model of protein expression in ccRCC was successfully constructed, which had good predictive ability for the prognosis of ccRCC patients. The ccRCC-related proteins in the model can be used as targets for studying the pathogenesis and targeted therapy.

Acetyl-CoA carboxylase 1 depletion suppresses de novo fatty acid synthesis and mitochondrial β-oxidation in castration-resistant prostate cancer cells

Cancer cells, including those of prostate cancer (PCa), often hijack intrinsic cell signaling to reprogram their metabolism. Part of this reprogramming includes the activation of de novo synthesis of fatty acids that not only serve as building blocks for membrane synthesis but also as energy sources for cell proliferation. However, how de novo fatty acid synthesis contributes to PCa progression is still poorly understood. Herein, by mining public datasets, we discovered that the expression of acetyl-CoA carboxylase alpha (ACACA), which encodes acetyl-CoA carboxylase 1 (ACC1), was highly expressed in human PCa. In addition, patients with high ACACA expression had a short disease-free survival time. We also reported that depletion of ACACA reduced de novo fatty acid synthesis and PI3K/AKT signaling in the human castration-resistant PCa (CRPC) cell lines DU145 and PC3. Furthermore, depletion of ACACA downregulates mitochondrial beta-oxidation, resulting in mitochondrial dysfunction, a reduction in ATP production, an imbalanced NADP⁺/NADPhydrogen(H) ratio, increased reactive oxygen species, and therefore apoptosis. Reduced exogenous fatty acids by depleting lipid or lowering serum supplementation exacerbated both shRNA depletion and pharmacological inhibition of ACACA-induced apoptosis in vitro. Collectively, our results suggest that inhibition of ectopic ACACA, together with suppression of exogenous fatty acid uptake, can be a novel strategy for treating currently incurable CRPC.

SNP discovery and association study for growth, fatness and meat quality traits in Iberian crossbred pigs

Iberian pigs and its crosses are produced to obtain high-quality meat products. The objective of this work was to evaluate a wide panel of DNA markers, selected by biological and functional criteria, for association with traits related to muscle growth, fatness, meat quality and metabolism. We used 18 crossbred Iberian pigs with divergent postnatal growth patterns for whole genome sequencing and SNP discovery, with over 13 million variants being detected. We selected 1023 missense SNPs located on annotated genes and showing different allele frequencies between pigs with makerdly different growth patterns. We complemented this panel with 192 candidate SNPs obtained from literature mining and from muscle RNAseq data. The selected markers were genotyped in 480 Iberian × Duroc pigs from a commercial population, in which phenotypes were obtained, and an association study was performed for the 1005 successfully genotyped SNPs showing segregation. The results confirmed the effects of several known SNPs in candidate genes (such as LEPR, ACACA, FTO, LIPE or SCD on fatness, growth and fatty acid composition) and also disclosed interesting effects of new SNPs in less known genes such as LRIG3, DENND1B, SOWAHB, EPHX1 or NFE2L2 affecting body weight, average daily gain and adiposity at different ages, or KRT10, NLE1, KCNH2 or AHNAK affecting fatness and FA composition. The results provide a valuable basis for future implementation of marker-assisted selection strategies in swine and contribute to a better understanding of the genetic architecture of relevant traits.

MicroRNA Profile of MA-104 Cell Line Associated With the Pathogenesis of Bovine Rotavirus Strain Circulated in Chinese Calves

Bovine rotavirus (BRV) causes massive economic losses in the livestock industry worldwide. Elucidating the pathogenesis of BRV would help in the development of more effective measures to control BRV infection. The MA-104 cell line is sensitive to BRV and is thereby a convenient tool for determining BRV–host interactions. Thus far, the role of the microRNAs (miRNAs) of MA-104 cells during BRV infection is still ambiguous. We performed Illumina RNA sequencing analysis of the miRNA libraries of BRV-infected and mock-infected MA-104 cells at different time points: at 0 h post-infection (hpi) (just after 90 min of adsorption) and at 6, 12, 24, 36, and 48 hpi. The total clean reads obtained from BRV-infected and uninfected cells were 74,701,041 and 74,184,124, respectively. Based on these, 579 were categorized as known miRNAs and 144 as novel miRNAs. One hundred and sixty differentially expressed (DE) miRNAs in BRV-infected cells in comparison with uninfected MA-104 cells were successfully investigated, 95 of which were upregulated and 65 were downregulated. The target messenger RNAs (mRNAs) of the DE miRNAs were examined by bioinformatics analysis. Functional annotation of the target genes with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) suggested that these genes mainly contributed to biological pathways, endocytosis, apoptotic process, trans-Golgi membrane, and lysosome. Pathways such as the mammalian target of rapamycin (mTOR) (mml-miR-486-3p and mml-miR-197-3p), nuclear factor kappa B (NF-κB) (mml-miR-204-3p and novel_366), Rap1 (mml-miR-127-3p), cAMP (mml-miR-106b-3p), mitogen-activated protein kinase (MAPK) (mml-miR-342-5p), T-cell receptor signaling (mml-miR-369-5p), RIG-I-like receptor signaling (mml-miR-504-5p), AMP-activated protein kinase (AMPK) (mml-miR-365-1-5p), and phosphatidylinositol-3-kinase/protein kinase B (PI3K/Akt) signaling (mml-miR-299-3p) were enriched. Moreover, real-time quantitative PCR (qPCR) verified the expression profiles of 23 selected DE miRNAs, which were consistent with the results of deep sequencing, and the 28 corresponding target mRNAs were mainly of regulatory pathways of the cellular machinery and immune importance, according to the bioinformatics analysis. Our study is the first to report a novel approach that uncovers the impact of BRV infection on the miRNA expressions of MA-104 cells, and it offers clues for identifying potential candidates for antiviral or vaccine strategies.

Personalized Medicine for Prostate Cancer: Is Targeting Metabolism a Reality?

Prostate cancer invokes major shifts in gene transcription and metabolic signaling to mediate alterations in nutrient acquisition and metabolic substrate selection when compared to normal tissues. Exploiting such metabolic reprogramming is proposed to enable the development of targeted therapies for prostate cancer, yet there are several challenges to overcome before this becomes a reality. Herein, we outline the role of several nutrients known to contribute to prostate tumorigenesis, including fatty acids, glucose, lactate and glutamine, and discuss the major factors contributing to variability in prostate cancer metabolism, including cellular heterogeneity, genetic drivers and mutations, as well as complexity in the tumor microenvironment. The review draws from original studies employing immortalized prostate cancer cells, as well as more complex experimental models, including animals and humans, that more accurately reflect the complexity of the in vivo tumor microenvironment. In synthesizing this information, we consider the feasibility and potential limitations of implementing metabolic therapies for prostate cancer management.

Targeting Mitochondrial OXPHOS and Their Regulatory Signals in Prostate Cancers

Increasing evidence suggests that tumor development requires not only oncogene/tumor suppressor mutations to drive the growth, survival, and metastasis but also metabolic adaptations to meet the increasing energy demand for rapid cellular expansion and to cope with the often nutritional and oxygen-deprived microenvironment. One well-recognized strategy is to shift the metabolic flow from oxidative phosphorylation (OXPHOS) or respiration in mitochondria to glycolysis or fermentation in cytosol, known as Warburg effects. However, not all cancer cells follow this paradigm. In the development of prostate cancer, OXPHOS actually increases as compared to normal prostate tissue. This is because normal prostate epithelial cells divert citrate in mitochondria for the TCA cycle to the cytosol for secretion into seminal fluid. The sustained level of OXPHOS in primary tumors persists in progression to an advanced stage. As such, targeting OXPHOS and mitochondrial activities in general present therapeutic opportunities. In this review, we summarize the recent findings of the key regulators of the OXPHOS pathway in prostate cancer, ranging from transcriptional regulation, metabolic regulation to genetic regulation. Moreover, we provided a comprehensive update of the current status of OXPHOS inhibitors for prostate cancer therapy. A challenge of developing OXPHOS inhibitors is to selectively target cancer mitochondria and spare normal counterparts, which is also discussed.

Multi-Omic Approaches to Breast Cancer Metabolic Phenotyping: Applications in Diagnosis, Prognosis, and the Development of Novel Treatments

Breast cancer (BC) is characterized by high disease heterogeneity and represents the most frequently diagnosed cancer among women worldwide. Complex and subtype-specific gene expression alterations participate in disease development and progression, with BC cells known to rewire their cellular metabolism to survive, proliferate, and invade. Hence, as an emerging cancer hallmark, metabolic reprogramming holds great promise for cancer diagnosis, prognosis, and treatment. Multi-omics approaches (the combined analysis of various types of omics data) offer opportunities to advance our understanding of the molecular changes underlying metabolic rewiring in complex diseases such as BC. Recent studies focusing on the combined analysis of genomics, epigenomics, transcriptomics, proteomics, and/or metabolomics in different BC subtypes have provided novel insights into the specificities of metabolic rewiring and the vulnerabilities that may guide therapeutic development and improve patient outcomes. This review summarizes the findings of multi-omics studies focused on the characterization of the specific metabolic phenotypes of BC and discusses how they may improve clinical BC diagnosis, subtyping, and treatment.

A New Prognostic Risk Signature of Eight Ferroptosis-Related Genes in the Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common renal cell carcinoma and has poor prognosis in the locally advanced stage. Ferroptosis, a relatively new type of cell death, has gained significant attention in recent years. This study aimed to explore the prognostic value of ferroptosis-related genes (FRGs) in ccRCC. In this study, 50 differentially expressed FRGs between ccRCC and adjacent normal kidney tissues were identified, 26 of them correlated with overall survival (OS) (P <0.05). Eight optimal FRGs were selected by Lasso regression and multivariate Cox regression analysis, and used to construct a new prognostic risk signature to predict the prognosis of ccRCC patients. In addition, the signature passed the validation of prognostic survival analyses by a significant margin, and the risk score was identified as an independent prognostic marker via Cox regression analyses. Further studies indicated that the signature was significantly correlated with immune cell infiltration. Moreover, the levels of eight FRGs were examined in ccRCC. Collectively, the 8-FRG prognostic risk signature helps the clinicians predict the prognosis and OS of the patients, and standardize prognostic assessments.