Glutamine and amino acid metabolism as a prognostic signature and therapeutic target in endometrial cancer

PHGDH: a novel therapeutic target in cancer

Serine is a key contributor to the generation of one-carbon units for DNA synthesis during cellular proliferation. In addition, it plays a crucial role in the production of antioxidants that prevent abnormal proliferation and stress in cancer cells. In recent studies, the relationship between cancer metabolism and the serine biosynthesis pathway has been highlighted. In this context, 3-phosphoglycerate dehydrogenase (PHGDH) is notable as a key enzyme that functions as the primary rate-limiting enzyme in the serine biosynthesis pathway, facilitating the conversion of 3-phosphoglycerate to 3-phosphohydroxypyruvate. Elevated PHGDH activity in diverse cancer cells is mediated through genetic amplification, posttranslational modification, increased transcription, and allosteric regulation. Ultimately, these characteristics allow PHGDH to not only influence the growth and progression of cancer but also play an important role in metastasis and drug resistance. Consequently, PHGDH has emerged as a crucial focal point in cancer research. In this review, the structural aspects of PHGDH and its involvement in one-carbon metabolism are investigated, and PHGDH is proposed as a potential therapeutic target in diverse cancers. By elucidating how PHGDH expression promotes cancer growth, the goal of this review is to provide insight into innovative treatment strategies. This paper aims to reveal how PHGDH inhibitors can overcome resistance mechanisms, contributing to the development of effective cancer treatments.

Signature identification based on immunogenic cell death-related lncRNAs to predict the prognosis and immune activity of patients with endometrial carcinoma

Background

Endometrial carcinoma (EC) is one of the most prevalent gynecologic malignancies and requires further classification for treatment and prognosis. Long non-coding RNAs (lncRNAs) and immunogenic cell death (ICD) play a critical role in tumor progression. Nevertheless, the role of lncRNAs in ICD in EC remains unclear. This study aimed to explore the role of ICD related-lncRNAs in EC via bioinformatics and establish a prognostic risk model based on the ICD-related lncRNAs. We also explored immune infiltration and immune cell function across prognostic groups and made treatment recommendations.

Methods

A total of 552 EC samples and clinical data of 548 EC patients were extracted from The Cancer Genome Atlas (TCGA) database and University of California Santa Cruz (UCSC) Xena, respectively. A prognostic-related feature and risk model was developed using the least absolute shrinkage and selection operator (LASSO). Subtypes were classified with consensus cluster analysis and validated with t-Distributed Stochastic Neighbor Embedding (tSNE). Kaplan-Meier analysis was conducted to assess differences in survival. Infiltration by immune cells was estimated by single sample gene set enrichment analysis (ssGSEA), Tumor IMmune Estimation Resource (TIMER) algorithm. Quantitative polymerase chain reaction (qPCR) was used to detect lncRNAs expression in clinical samples and cell lines. A series of studies was conducted in vitro and in vivo to examine the effects of knockdown or overexpression of lncRNAs on ICD.

Results

In total, 16 ICD-related lncRNAs with prognostic values were identified. Using SCARNA9, FAM198B-AS1, FKBP14-AS1, FBXO30-DT, LINC01943, and AL161431.1 as risk model, their predictive accuracy and discrimination were assessed. We divided EC patients into high-risk and low-risk groups. The analysis showed that the risk model was an independent prognostic factor. The prognosis of the high- and low-risk groups was different, and the overall survival (OS) of the high-risk group was lower. The low-risk group had higher immune cell infiltration and immune scores. Consensus clustering analysis divided the samples into four subtypes, of which cluster 4 had higher immune cell infiltration and immune scores.

Conclusions

A prognostic signature composed of six ICD related-lncRNAs in EC was established, and a risk model based on this signature can be used to predict the prognosis of patients with EC.

CENPA promotes glutamine metabolism and tumor progression by up-regulating SLC38A1 in endometrial cancer

Glutamine addiction is a significant hallmark of metabolic reprogramming in tumors and is crucial to the progression of cancer. Nevertheless, the regulatory mechanisms of glutamine metabolism in endometrial cancer (EC) remains elusive. In this research, we found that elevated expression of CENPA and solute carrier family 38 member 1 (SLC38A1) were firmly associated with worse clinical stage and unfavorable outcomes in EC patients. In addition, ectopic overexpression or silencing of CENPA could either enhance or diminish glutamine metabolism and tumor progression in EC. Mechanistically, CENPA directly regulated the transcriptional activity of the target gene, SLC38A1, leading to enhanced glutamine uptake and metabolism, thereby promoting EC progression. Notably, a prognostic model utilizing the expression levels of CENPA and SLC38A1 genes independently emerged as a prognostic factor for EC. More importantly, CENPA and SLC38A1 were significantly elevated and positively correlated, as well as indicative of poor prognosis in multiple cancers. In brief, our study confirmed that CENPA is a critical transcription factor involved in glutamine metabolism and tumor progression through modulating SLC38A1. This revelation suggests that targeting CENPA could be an appealing therapeutic approach to address pan-cancer glutamine addiction.

A critical review of advances in tumor metabolism abnormalities induced by nitrosamine disinfection by-products in drinking water

Intensified sanitation practices amid the recent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak might result in the increased release of chloramine disinfectants into surface water, significantly promoting the formation of nitrosamine disinfection by-products (DBPs) in drinking water. Unfortunately, these nitrosamine DBPs exhibit significant genotoxic, carcinogenic, and mutagenic properties, whereas chlorinating disinfectants remain in global practice. The current review provides valuable insights into the occurrence, identification, contamination status, exposure limits, and toxicity of the new unregulated disinfection by-products (nitrosamine DBPs) in drinking water. As a result, concentrations of nitrosamine DBPs far exceed allowable limits in drinking water, and prolonged exposure has the potential to cause metabolic disorders, a critical step in tumor initiation and progression. Importantly, based on recent research, we have concluded the role of nitrosamines DBPs in different metabolic pathways. Remarkably, nitrosamine DBPs can induce chronic inflammation and initiate tumors by activating sphingolipid and polyunsaturated fatty acid metabolism. Regarding amino acid and nucleotide metabolism, nitrosamine DBPs can inhibit tryptophan metabolism and de novo nucleotide synthesis. Moreover, inhibition of de novo nucleotide synthesis fails to repair DNA damage induced by nitrosamines. Additionally, the accumulation of lactate induced by nitrosamine DBPs may act as a pivotal signaling molecule in communication within the tumor microenvironment. However, with the advancement of tumor metabolomics, understanding the role of nitrosamine DBPs in causing cancer by inducing metabolic abnormalities significantly lags behind, and specific mechanisms of toxic effects are not clearly defined. Urgently, further studies exploring this promising area are needed.

Dual targeting of glutamine and serine metabolism in acute myeloid leukemia

Acute myeloid leukemia (AML) is a heterogeneous hematological malignancy characterized by disrupted blood cell production and function. Recent investigations have highlighted the potential of targeting glutamine metabolism as a promising therapeutic approach for AML. Asparaginases, enzymes that deplete circulating glutamine and asparagine, are approved for the treatment of acute lymphoblastic leukemia, but are also under investigation in AML, with promising results. We previously reported an elevation in plasma serine levels following treatment with Erwinia-derived asparaginase (also called crisantaspase). This led us to hypothesize that AML cells initiate the de novo serine biosynthesis pathway in response to crisantaspase treatment and that inhibiting this pathway in combination with crisantaspase would enhance AML cell death. Here we report that in AML cell lines, treatment with the clinically available crisantaspase, Rylaze, upregulates the serine biosynthesis enzymes phosphoglycerate dehydrogenase (PHGDH) and phosphoserine aminotransferase (PSAT1) through activation of the Amino Acid Response (AAR) pathway, a cellular stress response mechanism that regulates amino acid metabolism and protein synthesis under conditions of nutrient limitation. Inhibition of serine biosynthesis through CRISPR-Cas9-mediated knockout of PHGDH resulted in a ~250-fold reduction in the half-maximal inhibitory concentration (IC50) for Rylaze, indicating heightened sensitivity to crisantaspase therapy. Treatment of AML cells with a combination of Rylaze and a small molecule inhibitor of PHGDH (BI4916) revealed synergistic anti-proliferative effects in both cell lines and primary AML patient samples. Rylaze-BI4916 treatment in AML cell lines led to the inhibition of cap-dependent mRNA translation and protein synthesis, as well as a marked decrease in intracellular glutathione levels, a critical cellular antioxidant. Collectively, our results highlight the clinical potential of targeting serine biosynthesis in combination with crisantaspase as a novel therapeutic strategy for AML.

MAPK-mediated PHGDH induction is essential for melanoma formation and represents an actionable vulnerability

Overexpression of PHGDH, the rate-limiting enzyme in the serine synthesis pathway, promotes melanomagenesis, melanoma cell proliferation, and survival of metastases in serine-low environments such as the brain. While PHGDH amplification explains PHGDH overexpression in a subset of melanomas, we find that PHGDH levels are universally increased in melanoma cells due to oncogenic BRAFV600E promoting PHGDH transcription through mTORC1-mediated translation of ATF4. Importantly, PHGDH expression was critical for melanomagenesis as depletion of PHGDH in genetic mouse models blocked melanoma formation. Despite BRAFV600E-mediated upregulation, PHGDH was further induced by exogenous serine restriction. Surprisingly, BRAFV600E inhibition diminished serine restriction-mediated PHGDH expression by preventing ATF4 induction, creating a potential vulnerability whereby melanoma cells could be specifically starved of serine by combining BRAFV600E inhibition with exogenous serine restriction. Indeed, we show that this combination promoted cell death in vitro and attenuated melanoma growth in vivo. This study identified a melanoma cell-specific PHGDH-dependent vulnerability.

MKRN1 regulates the expression profiles and transcription factor activity in HeLa cells inhibition suppresses cervical cancer cell progression

Cervical cancer is one of the most common gynecologic malignancies worldwide, necessitating the identification of novel biomarkers and therapeutic targets. This study aimed to investigate the significance of MKRN1 in cervical cancer and explore its potential as a diagnostic marker and therapeutic target. The results indicated that MKRN1 expression was up-regulated in cervical cancer tissues and correlated with advanced tumor stage, higher grade, and poor patient survival. Functional studies demonstrated that targeting MKRN1 effectively inhibited cell proliferation, migration, and invasion, highlighting its critical role in tumor progression and metastasis. Moreover, the knockdown of MKRN1 resulted in altered expression patterns of six transcription factor-encoding genes, revealing its involvement in gene regulation. Co-expression network analysis unveiled complex regulatory mechanisms underlying the effects of MKRN1 knockdown on gene expression. Furthermore, the results suggested that MKRN1 might serve as a diagnostic marker for personalized treatment strategies and a therapeutic target to inhibit tumor growth, metastasis, and overcome drug resistance. The development of MKRN1-targeted interventions might hold promise for advancing personalized medicine approaches in cervical cancer treatment. Further research is warranted to validate these findings, elucidate underlying mechanisms, and translate these insights into improved management and outcomes for cervical cancer patients.

Urine and serum metabolomic analysis of endometrial cancer diagnosis and classification based on ultra-performance liquid chromatography mass spectrometry

OBJECTIVE

This study aimed to reveal the urinary and serum metabolic pattern of endometrial cancer (EC) and establish diagnostic models to identify EC from controls, high-risk from low-risk EC, and type II from type I EC.

METHOD

This study included 146 EC patients (comprising 79 low-risk and 67 high-risk patients, including 124 type I and 22 type II) and 59 controls. The serum and urine samples were analyzed using ultraperformance liquid chromatography mass spectrometry. Analysis was used to elucidate the distinct metabolites and altered metabolic pathways. Receiver operating characteristic (ROC) analyses were employed to discover and validate the potential biomarker models.

RESULTS

Serum and urine metabolomes displayed significant differences between EC and controls, with metabolites related to amino acid and nicotinamide metabolisms. The serum and urine panels distinguished these two groups with Area Under the Curve (AUC) of 0.821 and 0.902, respectively. The panel consisting of serum and urine metabolites demonstrated the best predictive ability (AUC = 0.953 and 0.976 in discovering and validation group). In comparing high-risk and low risk EC, differential metabolites were enriched in purine and glutamine metabolism. The AUC values for serum and urine panels were 0.818, and 0.843, respectively. The combined panel exhibited better predictive accuracy (0.881 in discovering group and 0.936 in external validation). In the comparison between type I and type II group, altered folic acid metabolism was identified. The serum, urine and combined panels discriminated these two groups with the AUC of 0.829, 0.913 and 0.922, respectively.

CONCLUSION

The combined urine and serum metabolome effectively revealed the metabolic patterns in EC patients, offering valuable diagnostic models for EC diagnosis and classification.