Targeting cancer-specific metabolic pathways for developing novel cancer therapeutics

Brucine Suppresses Malignant Progression of Prostate Cancer by Decreasing Sarcosine Accumulation via Downregulation of GNMT in the Glycine/sarcosine Metabolic Pathway

Prostate cancer (PCa) remains a leading cause of cancer-related incidence and mortality in men. Disruptions in amino acid (AA) metabolism contribute to the disease progression, with brucine, a glycine antagonist, exhibiting antitumor effects. This study explores the antitumor impact of brucine on PCa and investigates its mechanisms in regulating AA metabolic pathways. The study employed the PCa cell line DU-145, characterized by high sarcosine (Sar) levels, for various assays including Cell Counting Kit-8 (CCK8), wound healing, Transwell, 5-Ethynyl-2'-deoxyuridine (EDU), TdT mediated dUTP Nick End Labeling (TUNEL), flow cytometry, Western blot, and ultra-high-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Network pharmacological analysis determined the anticancer mechanisms of brucine. Sar levels in DU-145 cells were significantly higher than in normal prostatic epithelial cells RWPE-1. Treatment with brucine resulted in a marked decrease in cell viability, proliferation, invasion, and migration, while promoting apoptosis in a dose-dependent manner. Sar levels decreased with increasing brucine concentration. Network pharmacology analysis linked brucine's anticancer effect to the AA metabolism and glycine N-methyltransferase (GNMT) pathways. GNMT expression in prostate cancer tissues and The Cancer Genome Atlas database was significantly elevated compared to controls. Treatment with brucine led to downregulation of GNMT expression in DU-145 cells without significant effect on sarcosine dehydrogenase (SARDH). Addition of recombinant GNMT partially reversed the inhibitory effects of brucine on DU-145 cells. Treatment with brucine downregulates GNMT expression in DU-145 cells, reducing Sar accumulation and inhibiting tumor progression. These findings provide new insights into the antitumor mechanisms of brucine in PCa.

AKR1C3 silencing inhibits autophagy-dependent glycolysis in thyroid cancer cells by inactivating ERK signaling

Thyroid cancer is a highly differentiated and poorly malignant tumor. Interfering with glycolysis has become an effective means of controlling cancer progression and autophagy is negatively correlated with glycolysis. Aldo-keto reductase family 1 member C3 (AKR1C3) has been demonstrated to be highly expressed in thyroid cancer tissue and the higher AKR1C3 expression predicted the worse prognosis. We aimed to explore whether AKR1C3 could affect thyroid cancer progression by regulating autophagy-dependent glycolysis. AKR1C3 expression in thyroid cancer cells was detected by western blot. Then, AKR1C3 was knocked down by transfection with short hairpin RNA specific to AKR1C3 in the absence or presence of 3-methyladenine (3-MA) or PMA treatment. Cell cycle and apoptosis was detected by flow cytometry. Immunofluorescence staining was used to analyze LC3B expression. Extracellular acidification, glucose uptake and lactic acid secretion were detected. To evaluate the tumorigenicity of AKR1C3 insufficiency on thyroid cancer in vivo, TPC-1 cells with AKR1C3 knockdown were injected subcutaneously into nude mice. Then, cyclinD1 and Ki67 expression in tumorous tissues was measured by immunohistochemical analysis. Apoptosis was assessed by terminal-deoxynucleoitidyl transferase mediated nick end labeling staining. Additionally, the expression of proteins related to cell cycle, apoptosis, glycolysis, autophagy, and extracellular signal-regulated kinase (ERK) signaling in cells and tumor tissues was assessed by western blot. Highly expressed AKR1C3 was observed in thyroid cancer cells. AKR1C3 knockdown induced cell cycle arrest and apoptosis of TPC-1 cells. Besides, autophagy was activated and glycolysis was inhibited following AKR1C3 silencing, and 3-MA treatment restored the impacts of AKR1C3 silencing on glycolysis. The further experiments revealed that AKR1C3 insufficiency inhibited ERK signaling and PMA application reversed AKR1C3 silencing-induced autophagy in TPC-1 cells. The in vivo results suggested that AKR1C3 knockdown inhibited the development of subcutaneous TPC-1 tumors in nude mice and inactivated the ERK signaling. Collectively, AKR1C3 silencing inhibited autophagy-dependent glycolysis in thyroid cancer by inactivating ERK signaling.

Discovery of Nanomolar Inhibitors for Human Dihydroorotate Dehydrogenase Using Structure-Based Drug Discovery Methods

We used a structure-based drug discovery approach to identify novel inhibitors of human dihydroorotate dehydrogenase (DHODH), which is a therapeutic target for treating cancer and autoimmune and inflammatory diseases. In the case of acute myeloid leukemia, no previously discovered DHODH inhibitors have yet succeeded in this clinical application. Thus, there remains a strong need for new inhibitors that could be used as alternatives to the current standard-of-care. Our goal was to identify novel inhibitors of DHODH. We implemented prefiltering steps to omit PAINS and Lipinski violators at the earliest stages of this project. This enriched compounds in the data set that had a higher potential of favorable oral druggability. Guided by Glide SP docking scores, we found 20 structurally unique compounds from the ChemBridge EXPRESS-pick library that inhibited DHODH with IC50, DHODH values between 91 nM and 2.7 μM. Ten of these compounds reduced MOLM-13 cell viability with IC50, MOLM-13 values between 2.3 and 50.6 μM. Compound 16 (IC50, DHODH = 91 nM) inhibited DHODH more potently than the known DHODH inhibitor, teriflunomide (IC50, DHODH = 130 nM), during biochemical characterizations and presented a promising scaffold for future hit-to-lead optimization efforts. Compound 17 (IC50, MOLM-13 = 2.3 μM) was most successful at reducing survival in MOLM-13 cell lines compared with our other hits. The discovered compounds represent excellent starting points for the development and optimization of novel DHODH inhibitors.

PLA2G2D fosters angiogenesis in non-small cell lung cancer through aerobic glycolysis

Non-small cell lung cancer (NSCLC) stands prominent among the prevailing and formidable oncological entities. The immune and metabolic-related molecule Phospholipase A2, group IID (PLA2G2D) exerts promotional effects on tumor progression. However, its involvement in cancer angiogenesis remains elusive. Therefore, this investigation delved into the functional significance of PLA2G2D concerning angiogenesis in NSCLC. This study analyzed the expression and enriched pathways of PLA2G2D in NSCLC tissues through bioinformatics analysis, and measured the expression of PLA2G2D in NSCLC cells using qRT-PCR and western blot (WB). Subsequently, the viability and angiogenic potential of NSCLC cells were assessed employing CCK-8 and angiogenesis assays, respectively. The expression profile of angiogenic factors was analyzed through WB. Finally, the expression of glycolysis pathway-related genes, extracellular acidification rate and oxygen consumption rate, and the levels of pyruvate, lactate, citrate, and malate were analyzed in NSCLC cells using qRT-PCR, Seahorse XF 96, and related kits. Bioinformatics analysis revealed the upregulation of PLA2G2D in NSCLC tissues and its association with VEGF and glycolysis signaling pathways. Molecular and cellular experiments demonstrated that upregulated PLA2G2D promoted the viability, angiogenic ability, and glycolysis pathway of NSCLC cells. Rescue assays revealed that the effects of high expression of PLA2G2D on the viability, angiogenic ability, and glycolysis of NSCLC cells were weakened after the addition of the glycolysis inhibitor 2-DG. In summary, PLA2G2D plays a key role in NSCLC angiogenesis through aerobic glycolysis, displaying great potential as a target for anti-angiogenesis therapy.

Lipid metabolism, amino acid metabolism, and prostate cancer: a crucial metabolic journey

Prostate cancer (PCa) is one of the most common malignancies in males worldwide, and its development and progression involve the regulation of multiple metabolic pathways. Alterations in lipid metabolism affect the proliferation and metastatic capabilities of PCa cells. Cancer cells increase lipid synthesis and regulate fatty acid oxidation to meet their growth and energy demands. Similarly, changes occur in amino acid metabolism in PCa. Cancer cells exhibit an increased demand for specific amino acids, and they regulate amino acid transport and metabolic pathways to fulfill their proliferation and survival requirements. These changes are closely associated with disease progression and treatment response in PCa cells. Therefore, a comprehensive investigation of the metabolic characteristics of PCa is expected to offer novel insights and approaches for the early diagnosis and treatment of this disease.

Tumor microenvironment-induced tumor cell plasticity: relationship with hypoxic stress and impact on tumor resistance

The role of tumor interaction with stromal components during carcinogenesis is crucial for the design of efficient cancer treatment approaches. It is widely admitted that tumor hypoxic stress is associated with tumor aggressiveness and thus impacts susceptibility and resistance to different types of treatments. Notable biological processes that hypoxia functions in include its regulation of tumor heterogeneity and plasticity. While hypoxia has been reported as a major player in tumor survival and dissemination regulation, the significance of hypoxia inducible factors in cancer stem cell development remains poorly understood. Several reports indicate that the emergence of cancer stem cells in addition to their phenotype and function within a hypoxic tumor microenvironment impacts cancer progression. In this respect, evidence showed that cancer stem cells are key elements of intratumoral heterogeneity and more importantly are responsible for tumor relapse and escape to treatments. This paper briefly reviews our current knowledge of the interaction between tumor hypoxic stress and its role in stemness acquisition and maintenance. Our review extensively covers the influence of hypoxia on the formation and maintenance of cancer stem cells and discusses the potential of targeting hypoxia-induced alterations in the expression and function of the so far known stem cell markers in cancer therapy approaches. We believe that a better and integrated understanding of the effect of hypoxia on stemness during carcinogenesis might lead to new strategies for exploiting hypoxia-associated pathways and their targeting in the clinical setting in order to overcome resistance mechanisms. More importantly, at the present time, efforts are oriented towards the design of innovative therapeutical approaches that specifically target cancer stem cells.

The Illustration of Altered Glucose Dependency in Drug-Resistant Cancer Cells

A chemotherapeutic approach is crucial in malignancy management, which is often challenging due to the development of chemoresistance. Over time, chemo-resistant cancer cells rapidly repopulate and metastasize, increasing the recurrence rate in cancer patients. Targeting these destined cancer cells is more troublesome for clinicians, as they share biology and molecular cross-talks with normal cells. However, the recent insights into the metabolic profiles of chemo-resistant cancer cells surprisingly illustrated the activation of distinct pathways compared with chemo-sensitive or primary cancer cells. These distinct metabolic dynamics are vital and contribute to the shift from chemo-sensitivity to chemo-resistance in cancer. This review will discuss the important metabolic alterations in cancer cells that lead to drug resistance.

Integrating glycolysis, citric acid cycle, pentose phosphate pathway, and fatty acid beta-oxidation into a single computational model

The metabolic network of a living cell is highly intricate and involves complex interactions between various pathways. In this study, we propose a computational model that integrates glycolysis, the pentose phosphate pathway (PPP), the fatty acids beta-oxidation, and the tricarboxylic acid cycle (TCA cycle) using queueing theory. The model utilizes literature data on metabolite concentrations and enzyme kinetic constants to calculate the probabilities of individual reactions occurring on a microscopic scale, which can be viewed as the reaction rates on a macroscopic scale. However, it should be noted that the model has some limitations, including not accounting for all the reactions in which the metabolites are involved. Therefore, a genetic algorithm (GA) was used to estimate the impact of these external processes. Despite these limitations, our model achieved high accuracy and stability, providing real-time observation of changes in metabolite concentrations. This type of model can help in better understanding the mechanisms of biochemical reactions in cells, which can ultimately contribute to the prevention and treatment of aging, cancer, metabolic diseases, and neurodegenerative disorders.

Insights on the Role of Polyphenols in Combating Cancer Drug Resistance

Chemotherapy resistance is still a serious problem in the treatment of most cancers. Many cellular and molecular mechanisms contribute to both inherent and acquired drug resistance. They include the use of unaffected growth-signaling pathways, changes in the tumor microenvironment, and the active transport of medicines out of the cell. The antioxidant capacity of polyphenols and their potential to inhibit the activation of procarcinogens, cancer cell proliferation, metastasis, and angiogenesis, as well as to promote the inhibition or downregulation of active drug efflux transporters, have been linked to a reduced risk of cancer in epidemiological studies. Polyphenols also have the ability to alter immunological responses and inflammatory cascades, as well as trigger apoptosis in cancer cells. The discovery of the relationship between abnormal growth signaling and metabolic dysfunction in cancer cells highlights the importance of further investigating the effects of dietary polyphenols, including their ability to boost the efficacy of chemotherapy and avoid multidrug resistance (MDR). Here, it is summarized what is known regarding the effectiveness of natural polyphenolic compounds in counteracting the resistance that might develop to cancer drugs as a result of a variety of different mechanisms.

The Association of Circulating L-Carnitine, γ-Butyrobetaine and Trimethylamine N-Oxide Levels with Gastric Cancer

Our study aimed to evaluate the association between gastric cancer (GC) and higher concentrations of the metabolites L-carnitine, γ-butyrobetaine (GBB) and gut microbiota-mediated trimethylamine N-oxide (TMAO) in the circulation. There is evidence suggesting that higher levels of TMAO and its precursors in blood can be indicative of either a higher risk of malignancy or indeed its presence; however, GC has not been studied in this regard until now. Our study included 83 controls without high-risk stomach lesions and 105 GC cases. Blood serum L-carnitine, GBB and TMAO levels were measured by ultra-high-performance liquid chromatography–mass spectrometry (UPLC/MS/MS). Although there were no significant differences between female control and GC groups, we found a significant difference in circulating levels of metabolites between the male control group and the male GC group, with median levels of L-carnitine reaching 30.22 (25.78–37.57) nmol/mL vs. 37.38 (32.73–42.61) nmol/mL (p < 0.001), GBB–0.79 (0.73–0.97) nmol/mL vs. 0.97 (0.78–1.16) nmol/mL (p < 0.05) and TMAO–2.49 (2.00–2.97) nmol/mL vs. 3.12 (2.08–5.83) nmol/mL (p < 0.05). Thus, our study demonstrated the association between higher blood levels of L-carnitine, GBB, TMAO and GC in males, but not in females. Furthermore, correlations of any two investigated metabolites were stronger in the GC groups of both genders in comparison to the control groups. Our findings reveal the potential role of L-carnitine, GBB and TMAO in GC and suggest metabolic differences between genders. In addition, the logistic regression analysis revealed that the only significant factor in terms of predicting whether the patient belonged to the control or to the GC group was the blood level of L-carnitine in males only. Hence, carnitine might be important as a biomarker or a risk factor for GC, especially in males.

Retrospective Analysis of the Predictive Value of 18F-FDG PET/CT Metabolic Parameters for PD-L1 Expression in Cervical Cancer

BACKGROUND

Immunotherapy targeting PD-1/PD-L1 has been proven to be effective for cervical cancer treatment. To explore non-invasive examinations for assessing the PD-L1 status in cervical cancer, we performed a retrospective study to investigate the predictive value of ¹⁸F-FDG PET/CT.

METHODS

The correlations between PD-L1 expression, clinicopathological characteristics and ¹⁸F-FDG PET/CT metabolic parameters were evaluated in 74 cervical cancer patients. The clinicopathological characteristics included age, histologic type, tumor differentiation, FIGO stage and tumor size. The metabolic parameters included maximum standard uptake (SUVmax), mean standard uptake (SUVmean), total lesion glycolysis (TLG) and tumor metabolic volume (MTV).

RESULTS

In univariate analysis, SUVmax, SUVmean, TLG, tumor size and tumor differentiation were obviously associated with PD-L1 status. SUVmax (rs = 0.42) and SUVmean (rs = 0.40) were moderately positively correlated with the combined positive score (CPS) for PD-L1 in Spearman correlation analysis. The results of multivariable analysis showed that the higher SUVmax (odds ratio = 2.849) and the lower degree of differentiation (Odds Ratio = 0.168), the greater probability of being PD-L1 positive. The ROC curve analysis demonstrated that when the cut-off values of SUVmax, SUVmean and TLG were 10.45, 6.75 and 143.4, respectively, the highest accuracy for predicting PD-L1 expression was 77.0%, 71.6% and 62.2%, respectively. The comprehensive predictive ability of PD-L1 expression, assessed by combining SUVmax with tumor differentiation, showed that the PD-L1-negative rate was 100% in the low probability group, whereas the PD-L1-positive rate was 84.6% in the high probability group. In addition, we also found that the H-score of HIF-1α was moderately positively correlated with PD-L1 CPS (rs = 0.51).

CONCLUSIONS

The SUVmax and differentiation of the primary lesion were the optimum predictors for PD-L1 expression in cervical cancer. There was a great potential for ¹⁸F-FDG PET/CT in predicting PD-L1 status and selecting cervical cancer candidates for PD1/PD-L1 immune checkpoint therapy.