Leucine and branched-chain amino acid metabolism contribute to the growth of bone sarcomas by regulating AMPK and mTORC1 signaling

Stemness related lncRNAs signature for the prognosis and tumor immune microenvironment of ccRCC patients

Long non-coding RNAs (lncRNAs) and cancer stem cells (CSCs) are crucial for the growth, migration, recurrence, and medication resistance of tumors. However, the impact of lncRNAs related to stemness on the outcome and tumor immune microenvironment (TIME) in clear cell renal cell carcinoma (ccRCC) is still unclear. In this study, we aimed to predict the outcome and TIME of ccRCC by constructing a stem related lncRNAs (SRlncRNAs) signature. We firstly downloaded ccRCC patients' clinical data and RNA sequencing data from UCSC and TCGA databases, and abtained the differentially expressed lncRNAs highly correlated with stem index in ccRCC through gene expression differential analysis and Pearson correlation analysis. Then, we selected suitable SRlncRNAs for constructing a prognostic signature of ccRCC patients by LASSO Cox regression. Further, we used nomogram and Kaplan Meier curves to evaluate the SRlncRNA signature for the prognose in ccRCC. At last, we used ssGSEA and GSVA to evaluate the correlation between the SRlncRNAs signature and TIME in ccRCC. Finally, We obtained a signtaure based on six SRlncRNAs, which are correlated with TIME and can effectively predict the ccRCC patients' prognosis. The SRlncRNAs signature may be a noval prognostic indicator in ccRCC.

Prognostic Signature in Osteosarcoma Based on Amino Acid Metabolism-Associated Genes

Background: Osteosarcoma (OS) is undeniably a formidable bone malignancy characterized by a scarcity of effective treatment options. Reprogramming of amino acid (AA) metabolism has been associated with OS development. The present study was designed to identify metabolism-associated genes (MAGs) that are differentially expressed in OS and to construct a MAG-based prognostic risk signature for this disease. Methods: Expression profiles and clinicopathological data were downloaded from Gene Expression Omnibus (GEO) and UCSC Xena databases. A set of AA MAGs was obtained from the MSigDB database. Differentially expressed genes (DEGs) in GEO dataset were identified using "limma." Prognostic MAGs from UCSC Xena database were determined through univariate Cox regression and used in the prognostic signature development. This signature was validated using another dataset from GEO database. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, single sample gene set enrichment analysis, and GDSC2 analyses were performed to explore the biological functions of the MAGs. A MAG-based nomogram was established to predict 1-, 3-, and 5-year survival. Real-time quantitative polymerase chain reaction, Western blot, and immunohistochemical staining confirmed the expression of MAGs in primary OS and paired adjacent normal tissues. Results: A total of 790 DEGs and 62 prognostic MAGs were identified. A MAG-based signature was constructed based on four MAGs: PIPOX, PSMC2, SMOX, and PSAT1. The prognostic value of this signature was successfully validated, with areas under the receiver operating characteristic curves for 1-, 3-, and 5-year survival of 0.714, 0.719, and 0.715, respectively. This MAG-based signature was correlated with the infiltration of CD56dim natural killer cells and resistance to several antiangiogenic agents. The nomogram was accurate in predictions, with a C-index of 0.77. The expression of MAGs verified by experiment was consistent with the trends observed in GEO database. Conclusion: Four AA MAGs were prognostic of survival in OS patients. This MAG-based signature has the potential to offer valuable insights into the development of treatments for OS.

Versatile function of AMPK signaling in osteosarcoma: An old player with new emerging carcinogenic functions

AMP-activated protein kinase (AMPK) signaling has a versatile role in Osteosarcoma (OS), an aggressive bone malignancy with a poor prognosis, particularly in cases that have metastasized or recurred. This review explores the regulatory mechanisms, functional roles, and therapeutic applications of AMPK signaling in OS. It focuses on the molecular activation of AMPK and its interactions with cellular processes like proliferation, apoptosis, and metabolism. The uncertain role of AMPK in cancer is also discussed, highlighting its potential as both a tumor suppressor and a contributor to carcinogenesis. The therapeutic potential of targeting AMPK signaling in OS treatment is examined, including direct and indirect activators like metformin, A-769662, resveratrol, and salicylate. Further research is needed to determine dosing, toxicities, and molecular mechanisms responsible for the anti-osteosarcoma effects of these compounds. This review underscores the complex involvement of AMPK signaling in OS and emphasizes the need for a comprehensive understanding of its molecular mechanisms. By elucidating the role of AMPK in OS, the aim is to pave the way for innovative therapeutic approaches that target this pathway, ultimately improving the prognosis and quality of life for OS patients.

High-throughput quantitation of amino acids and acylcarnitine in cerebrospinal fluid: identification of PCNSL biomarkers and potential metabolic messengers

Background: Due to the poor prognosis and rising occurrence, there is a crucial need to improve the diagnosis of Primary Central Nervous System Lymphoma (PCNSL), which is a rare type of non-Hodgkin's lymphoma. This study utilized targeted metabolomics of cerebrospinal fluid (CSF) to identify biomarker panels for the improved diagnosis or differential diagnosis of primary central nervous system lymphoma (PCNSL). Methods: In this study, a cohort of 68 individuals, including patients with primary central nervous system lymphoma (PCNSL), non-malignant disease controls, and patients with other brain tumors, was recruited. Their cerebrospinal fluid samples were analyzed using the Ultra-high performance liquid chromatography - tandem mass spectrometer (UHPLC-MS/MS) technique for targeted metabolomics analysis. Multivariate statistical analysis and logistic regression modeling were employed to identify biomarkers for both diagnosis (Dx) and differential diagnosis (Diff) purposes. The Dx and Diff models were further validated using a separate cohort of 34 subjects through logistic regression modeling. Results: A targeted analysis of 45 metabolites was conducted using UHPLC-MS/MS on cerebrospinal fluid (CSF) samples from a cohort of 68 individuals, including PCNSL patients, non-malignant disease controls, and patients with other brain tumors. Five metabolic features were identified as biomarkers for PCNSL diagnosis, while nine metabolic features were found to be biomarkers for differential diagnosis. Logistic regression modeling was employed to validate the Dx and Diff models using an independent cohort of 34 subjects. The logistic model demonstrated excellent performance, with an AUC of 0.83 for PCNSL vs. non-malignant disease controls and 0.86 for PCNSL vs. other brain tumor patients. Conclusion: Our study has successfully developed two logistic regression models utilizing metabolic markers in cerebrospinal fluid (CSF) for the diagnosis and differential diagnosis of PCNSL. These models provide valuable insights and hold promise for the future development of a non-invasive and reliable diagnostic tool for PCNSL.

High WFDC3 gene expression is associated with poor prognosis and reduced immune cells infiltration in pancreatic adenocarcinoma: A study using the TCGA database and bioinformatics analysis

Whey-acidic-protein (WAP) four-disulfide core domain protein 3 (WFDC3) is one of the WAP family proteins. This protein family is associated with the development of solid tumors and affects the tumor immunological microenvironment. However, the prognostic value of WFDC3 in pancreatic adenocarcinoma (PAAD) and its effect on the tumor immune microenvironment is yet to be clarified. The Cancer Genome Atlas database and Genotype-Tissue Expression database were used to analyze the differential expression of WFDC3 between the tumor and adjacent tissues. The clinical significance of WFDC3 was analyzed in The Cancer Genome Atlas and International Cancer Genome Consortium database using WFDC3 transcripts and clinical information. In order to elucidate the underlying mechanisms, gene set enrichment analysis was conducted to determine potential activated pathways. Immune score evaluation and publicly available pharmacogenomics database [the Genomics of Drug Sensitivity in Cancer] were utilized to quantify immune cell infiltration and the effect on chemotherapeutic drug sensitivity. WFDC3 levels were higher in PAAD tissues than in normal pancreatic tissues. High levels of WFDC3 expression progressively increased as PAAD tumor stages progressed. Patients with elevated WFDC3 expression showed a poor prognosis. The gene set enrichment analysis analysis revealed that glutamate, arginine, and proline, and histidine metabolism levels were elevated in patients with a high WFDC3 expression phenotype. B, CD4+ T, and CD8+ T cell infiltration was diminished in PAAD tissues with elevated WFDC3 expression. According to pharmacogenomics, PAAD tissues with high WFDC3 expression are susceptible to gemcitabine. WFDC3 is highly expressed in PAAD, and patients with a high level of WFDC3 expression have a shorter overall survival time, indicating a poorer prognosis. High expression of WFDC3 may lead to the development of PAAD by affecting the amino acid metabolism and the tumor immunological microenvironment. WFDC3 may serve as a potential diagnostic and prognostic biomarker for PAAD patients.

Oridonin impedes breast cancer growth by blocking cells in S phase and inhibiting the PI3K/AKT/mTOR signaling pathway

Breast cancer is one of the most common cancers. Oridonin, a traditional Chinese medicine, is believed to inhibit tumor growth, but its particular effects on breast cancer remain unknown. In this study, we examined oridonin's effects on 4T1, MCF-7, and MDAMB-231 cellular activity using CCK8. Scratch assays were used to detect oridonin's effects on cellular migration. Oridonin's effects on the breast cancer cell cycle were studied using flow cytometry, and expression of cell cycle related proteins p53, CDK2, and p21 was detected using Western blot assays. Metabolomics assays were used to detect changes in small molecule metabolites and metabolic pathways in breast cancer cells after treatment with oridonin. Oridonin's effects on breast cancer growth were also studied using xenograft mice. Metabolomics assays were used to detect changes in metabolites and metabolic pathways in xenograft mouse plasma in a control group, model group, and drug administration group. Experimental results showed that oridonin could significantly inhibit breast cancer growth both in vivo and in vitro. Scratch experiments showed that oridonin could inhibit breast cancer cell migration. Oridonin was also able to arrest cells in S phase by affecting several cell cycle-related proteins, including p53, CDK2, and p21. Metabolomic analysis of 4T1 cells identified a total of 33 differential metabolites, including multiple amino acids (such as l-Glutamic acid, l-Asparagine, l-Histidine, l-Valine, and l-Isoleucine). KEGG pathway enrichment analysis showed significant changes in aminoacyl-tRNA biosynthesis, and in multiple amino acid metabolic pathways. Plasma metabolomic analyses of xenograft mice revealed 28 differentially-expressed metabolites between the different animal model groups, including multiple amino acids. KEGG pathway analysis showed significant alterations in multiple amino acid metabolic pathways in oridonin-treated mice. Additionally, changes in the expression of PI3K, AKT and mTOR proteins, as well as in branched amino acids, suggest that oridonin affects the PI3K/AKT/mTOR signaling pathway by inhibiting the biosynthesis of valine, leucine and isoleucine. Taken together, our results suggest that oridonin has strong anti-tumor activity in vitro and in vivo, and has potential as an adjuvant to breast cancer treatment regimens.

Amino acid metabolism in immune cells: essential regulators of the effector functions, and promising opportunities to enhance cancer immunotherapy

Amino acids are basic nutrients for immune cells during organ development, tissue homeostasis, and the immune response. Regarding metabolic reprogramming in the tumor microenvironment, dysregulation of amino acid consumption in immune cells is an important underlying mechanism leading to impaired anti-tumor immunity. Emerging studies have revealed that altered amino acid metabolism is tightly linked to tumor outgrowth, metastasis, and therapeutic resistance through governing the fate of various immune cells. During these processes, the concentration of free amino acids, their membrane bound transporters, key metabolic enzymes, and sensors such as mTOR and GCN2 play critical roles in controlling immune cell differentiation and function. As such, anti-cancer immune responses could be enhanced by supplement of specific essential amino acids, or targeting the metabolic enzymes or their sensors, thereby developing novel adjuvant immune therapeutic modalities. To further dissect metabolic regulation of anti-tumor immunity, this review summarizes the regulatory mechanisms governing reprogramming of amino acid metabolism and their effects on the phenotypes and functions of tumor-infiltrating immune cells to propose novel approaches that could be exploited to rewire amino acid metabolism and enhance cancer immunotherapy.

Branched-chain amino acids alter cellular redox to induce lipid oxidation and reduce de novo lipogenesis in the liver

Metabolic and molecular interactions between branched-chain amino acid (BCAA) and lipid metabolism are evident in insulin-resistant tissues. However, it remains unclear whether insulin resistance is a prerequisite for these relationships and whether BCAAs or their metabolic intermediates can modulate hepatic lipid oxidation and synthesis. We hypothesized that BCAAs can alter hepatic oxidative function and de novo lipogenesis, independent of them being anaplerotic substrates for the mitochondria. Mice (C57BL/6NJ) were reared on a low-fat (LF), LF diet plus 1.5X BCAAs (LB), high-fat (HF) or HF diet plus 1.5X BCAAs (HB) for 12 wk. Hepatic metabolism was profiled utilizing stable isotopes coupled to mass spectrometry and nuclear magnetic resonance, together with fed-to-fasted changes in gene and protein expression. A greater induction of lipid oxidation and ketogenesis on fasting was evident in the BCAA-supplemented, insulin-sensitive livers from LB mice, whereas their rates of hepatic de novo lipogenesis remained lower than their LF counterparts. Onset of insulin resistance in HF and HB mice livers blunted these responses. Whole body turnover of BCAAs and their ketoacids, their serum concentrations, and the ketogenic flux from BCAA catabolism, all remained similar between fasted LF and LB mice. This suggested that the impact of BCAAs on lipid metabolism can occur independent of them or their degradation products fueling anaplerosis through the liver mitochondria. Furthermore, the greater induction of lipid oxidation in the LB livers accompanied higher mitochondrial NADH/NAD+ ratio and higher fed-to-fasting phosphorylation of AMPKα and ACC. Taken together, our results provide evidence that BCAA supplementation, under conditions of insulin sensitivity, improved the feeding-to-fasting induction of hepatic lipid oxidation through changes in cellular redox, thus providing a favorable biochemical environment for flux through β-oxidation and lower de novo lipogenesis.NEW & NOTEWORTHY Branched-chain amino acids (BCAAs) have been shown to modulate lipid metabolic networks in various tissues, especially during insulin resistance. In this study we show that the dietary supplementation of BCAAs to normal, insulin-sensitive mice resulted in higher mitochondrial NADH:NAD+ ratios and AMPK activation in the liver. This change in the cellular redox status provided an optimal metabolic milieu to increase fatty acid oxidation while keeping the rates of de novo lipogenesis lower in the BCAA-supplemented mice livers.

BCAT1, as a prognostic factor for HCC, can promote the development of liver cancer through activation of the AKT signaling pathway and EMT

More and more studies have shown that Branched chain amino acid transaminase 1 (BCAT1) is involved in the occurrence and development of a variety of tumors. However, the mechanism of its occurrence and development in hepatocellular carcinoma (HCC) remains unclear. Here, we demonstrated the relationship between BCAT1 and AKT signaling pathway, as well as EMT, and the clinical significance of BCAT1 by using BCAT1 expression in 5 cell lines and 113 liver cancer and non-liver cancer tissue samples. The results showed that the expression of AKT was positively correlated with BCAT1 in HCC tissues, and BCAT1 could promote the progression of HCC cells through the AKT signaling pathway. Clinical analysis and Bioinformatics technology analysis revealed that BCAT1 was correlated with poor prognosis, and BCAT1 expression in the HCC tissues was evidently correlated with tumor number, vascular invasion, Edmondson grade and TNM stage (P < 0.05). In vitro studies showed that BCAT1 increased the invasion and migration of in MHCC-97H cells a d Huh7 cells. By inhibiting the expression of the BCAT1 gene, we detected the corresponding changes in the expression levels of Twist, E-cadherin and Vimentin, confirming that BCAT1 may promote the invasion and migration of HCC cells through epithelial-mesenchymal transformation (EMT). Overall, BCAT1 can activate AKT signaling pathway and EMT to promote the development and metastasis of HCC cells. this study may provide new ideas and directions for cancer diagnosis and treatment.

Selection of lncRNAs That Influence the Prognosis of Osteosarcoma Based on Copy Number Variation Data

Osteosarcoma is the most common primary malignancy in the musculoskeletal system. It is reported that copy number variation- (CNV-) derived lncRNAs contribute to the progression of osteosarcoma. However, whether CNV-derived lncRNAs affect the prognosis of osteosarcoma remains unclear. Here, we obtained osteosarcoma-related CNV data and gene expression profiles from The Cancer Genome Atlas (TCGA) database. CNV landscape analysis indicated that copy number amplification of lncRNAs was more frequent than deletion in osteosarcoma samples. Thirty-four CNV-lncRNAs with DNA-CNV frequencies greater than 30% and their corresponding 294 mRNAs were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway enrichment analyses revealed that these mRNAs were mainly enriched in olfaction, olfactory receptor activity, and olfactory transduction processes. Furthermore, we predicted that a total of 23 genes were cis-regulated by 16 CNV-lncRNAs, while 30 transcription factors (TFs) were trans-regulated by 5 CNV-lncRNAs. Through $t$ -tests, univariate Cox regression analysis, and the least absolute shrinkage and selection operator (LASSO), we constructed a CNV-related risk model including 3 lncRNAs (AC129492.1, PSMB1, and AC037459.4). The Kaplan-Meier (K-M) curves indicated that patients with high-risk scores showed poor prognoses. The areas under the receiver operating characteristic (ROC) curves (AUC) for predicting 3-, 5-, and 7-year overall survival (OS) were greater than 0.7, showing a satisfactory predictive efficiency. Gene set enrichment analysis (GSEA) revealed that the prognostic signature was intimately linked to skeletal system development, immune regulation, and inflammatory response. Collectively, our study developed a novel 3-CNV-lncRNA prognostic signature that would provide theoretical guidance for the clinical prognostic management of osteosarcoma.

GEO data mining and TCGA analysis reveal altered branched chain amino acid metabolism in pancreatic cancer patients

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive tumor of the digestive system which has a less than 1% 5-year survival rate. The pathogenesis of PDAC development is incompletely understood. Genetic predisposition, disease history of chronic pancreatitis and diabetes elevate the risk of PDAC while environmental and dietary factors including smoking, alcohol abuse, high fat/protein intake as well as air pollution exacerbate PDAC progression. BCAAs, consisting of leucine, isoleucine and valine are essential amino acids that are obtained from food and play versatile roles in carcinogenesis. Recent studies have demonstrated that BCAA metabolism affects PDAC development but the results are controversial. To explore the possible engagement of BCAA metabolism in PDAC, we took advantage of the GEO and TCGA database and discovered that BCAA uptake is closely related to PDAC development while BCAA catabolism is down-regulated in PDAC tissue. Besides, NOTCH and MYC are differentially involved in BCAA metabolism in tumor and muscle, and enhanced lipid synthesis is independent of BCAA catabolism. Altogether, we highlight BCAA uptake as a promising target for PDAC treatment.

BCAT1 affects mitochondrial metabolism independently of leucine transamination in activated human macrophages

In response to environmental stimuli, macrophages change their nutrient consumption and undergo an early metabolic adaptation that progressively shapes their polarization state. During the transient, early phase of pro-inflammatory macrophage activation, an increase in tricarboxylic acid (TCA) cycle activity has been reported, but the relative contribution of branched-chain amino acid (BCAA) leucine remains to be determined. Here, we show that glucose but not glutamine is a major contributor of the increase in TCA cycle metabolites during early macrophage activation in humans. We then show that, although uptake of BCAAs is not altered, their transamination by BCAT1 is increased following 8 h lipopolysaccharide (LPS) stimulation. Of note, leucine is not metabolized to integrate into the TCA cycle in basal or stimulated human macrophages. Surprisingly, the pharmacological inhibition of BCAT1 reduced glucose-derived itaconate, α-ketoglutarate and 2-hydroxyglutarate levels without affecting succinate and citrate levels, indicating a partial inhibition of the TCA cycle. This indirect effect is associated with NRF2 (also known as NFE2L2) activation and anti-oxidant responses. These results suggest a moonlighting role of BCAT1 through redox-mediated control of mitochondrial function during early macrophage activation.

Multifaceted role of branched-chain amino acid metabolism in cancer

Metabolic reprogramming fulfils increased nutrient demands and regulates numerous oncogenic processes in tumors, leading to tumor malignancy. Branched-chain amino acids (BCAAs, i.e., valine, leucine, and isoleucine) function as nitrogen donors to generate macromolecules such as nucleotides and are indispensable for human cancer cell growth. The cell-autonomous and non-autonomous roles of altered BCAA metabolism have been implicated in cancer progression and the key proteins in the BCAA metabolic pathway serve as possible prognostic and diagnostic biomarkers in human cancers. Here we summarize how BCAA metabolic reprogramming is regulated in cancer cells and how it influences cancer progression.

Identification of potential prognostic small nucleolar RNA biomarkers for predicting overall survival in patients with sarcoma

Objective

The main purpose of the present study is to screen prognostic small nucleolar RNA (snoRNA) markers using the RNA‐sequencing (RNA‐seq) dataset of The Cancer Genome Atlas (TCGA) sarcoma cohort.

Methods

The sarcoma RNA‐seq dataset comes from the TCGA cohort. A total of 257 sarcoma patients were included into the prognostic analysis. Multiple bioinformatics analysis methods for functional annotation of snoRNAs and screening of targeted drugs, including biological network gene ontology tool, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA), and connectivity map (CMap) are used.

Results

We had identified 15 snoRNAs that were significantly related to the prognosis of sarcoma and constructed a prognostic signature based on four prognostic snoRNA (U3, SNORA73B, SNORD46, and SNORA26) expression values. Functional annotation of these four snoRNAs by their co‐expression genes suggests that some of them were closely related to cell cycle‐related biological processes and tumor‐related signaling pathways, such as Wnt, mitogen‐activated protein kinase, target of rapamycin, and nuclear factor‐kappa B signaling pathway. GSEA of the risk score suggests that high risk score phenotype was significantly enriched in cell cycle‐related biological processes, protein SUMOylation, DNA replication, p53 binding, regulation of DNA repair, and DNA methylation, as well as Myc, Wnt, RB1, E2F, and TEL pathways. Then we also used the CMap online tool to screen five targeted drugs (rilmenidine, pizotifen, amiprilose, quipazine, and cinchonidine) for this risk score model in sarcoma.

Conclusion

Our study have identified 15 snoRNAs that may be serve as novel prognostic biomarkers for sarcoma, and constructed a prognostic signature based on four prognostic snoRNA expression values.