Up-regulation of DGAT1 in cancer tissues and tumor-infiltrating macrophages influenced survival of patients with gastric cancer

A new strategy for screening novel functional genes involved in reduction of lipid droplet accumulation

Lipid droplets (LDs) are organelles that store excess lipids and provide fatty acids for energy production during starvation. LDs are also essential for cellular maintenance, but excessive accumulation of LDs triggers various cancers in addition to metabolic diseases such as diabetes. In this study, we aimed to develop a strategy to identify new genes that reduces accumulation of LDs in cancer cells using an RNA interference (RNAi) screening system employing artificial sequence-enriched shRNA libraries. Monitoring LDs by fluorescent activated cell sorting, the subsequently collected cumulative LDs cells, and shRNA sequence analysis identified a clone that potentially functioned to accumulate LDs. The clone showed no identical sequence to human Refseq. It showed very similar sequence to seven genes by allowing three mismatches. Among these genes, we identified the mediator complex subunit 6 (MED6) gene as a target of this shRNA. Silencing of MED6 led to an increase in LD accumulation and expression of the marker genes, PLIN2 and DGAT1, in fatty cells. MED6 is a member of the mediator complex that regulates RNA polymerase II transcription through transcription factor II. Some mediator complexes play important roles in both normal and pathophysiological transcription processes. These results suggest that MED6 transcriptionally regulates the genes involved in lipid metabolism and suppresses LD accumulation.

Lipid droplets provide metabolic flexibility for cancer progression

A hallmark of cancer cells is their remarkable ability to efficiently adapt to favorable and hostile environments. Due to a unique metabolic flexibility, tumor cells can grow even in the absence of extracellular nutrients or in stressful scenarios. To achieve this, cancer cells need large amounts of lipids to build membranes, synthesize lipid-derived molecules, and generate metabolic energy in the absence of other nutrients. Tumor cells potentiate strategies to obtain lipids from other cells, metabolic pathways to synthesize new lipids, and mechanisms for efficient storage, mobilization, and utilization of these lipids. Lipid droplets (LDs) are the organelles that collect and supply lipids in eukaryotes and it is increasingly recognized that the accumulation of LDs is a new hallmark of cancer cells. Furthermore, an active role of LD proteins in processes underlying tumorigenesis has been proposed. Here, by focusing on three major classes of LD-resident proteins (perilipins, lipases, and acyl-CoA synthetases), we provide an overview of the contribution of LDs to cancer progression and discuss the role of LD proteins during the proliferation, invasion, metastasis, apoptosis, and stemness of cancer cells.

Identification of hub genes and potential molecular mechanisms related to drug sensitivity in acute myeloid leukemia based on machine learning

Background: Acute myeloid leukemia (AML) is the most common form of leukemia among adults and is characterized by uncontrolled proliferation and clonal expansion of hematopoietic cells. There has been a significant improvement in the treatment of younger patients, however, prognosis in the elderly AML patients remains poor. Methods: We used computational methods and machine learning (ML) techniques to identify and explore the differential high-risk genes (DHRGs) in AML. The DHRGs were explored through multiple in silico approaches including genomic and functional analysis, survival analysis, immune infiltration, miRNA co-expression and stemness features analyses to reveal their prognostic importance in AML. Furthermore, using different ML algorithms, prognostic models were constructed and validated using the DHRGs. At the end molecular docking studies were performed to identify potential drug candidates targeting the selected DHRGs. Results: We identified a total of 80 DHRGs by comparing the differentially expressed genes derived between AML patients and normal controls and high-risk AML genes identified by Cox regression. Genetic and epigenetic alteration analyses of the DHRGs revealed a significant association of their copy number variations and methylation status with overall survival (OS) of AML patients. Out of the 137 models constructed using different ML algorithms, the combination of Ridge and plsRcox maintained the highest mean C-index and was used to build the final model. When AML patients were classified into low- and high-risk groups based on DHRGs, the low-risk group had significantly longer OS in the AML training and validation cohorts. Furthermore, immune infiltration, miRNA coexpression, stemness feature and hallmark pathway analyses revealed significant differences in the prognosis of the low- and high-risk AML groups. Drug sensitivity and molecular docking studies revealed top 5 drugs, including carboplatin and austocystin-D that may significantly affect the DHRGs in AML. Conclusion: The findings from the current study identified a set of high-risk genes that may be used as prognostic and therapeutic markers for AML patients. In addition, significant use of the ML algorithms in constructing and validating the prognostic models in AML was demonstrated. Although our study used extensive bioinformatics and machine learning methods to identify the hub genes in AML, their experimental validations using knock-out/-in methods would strengthen our findings.

Leveraging macrophage metabolism for anticancer therapy: opportunities and pitfalls

Tumor-associated macrophages (TAMs) constitute an important part of the tumor microenvironment (TME) that regulates tumor progression. Tumor-derived signals, hypoxia, and competition for nutrients influence TAMs to reprogram their cellular metabolism. This altered metabolic profile creates a symbiotic communication between tumor and other immune cells to support tumor growth. In addition, the metabolic profile of TAMs regulates the expression of immune checkpoint molecules. The dynamic plasticity also allows TAMs to reshape their metabolism in response to modern therapeutic strategies. Therefore, over the years, a significant number of approaches have been implicated to reprogram cancer-promoting metabolism in TAMs. In this review, we discuss the current strategies and pitfalls, along with upcoming promising opportunities in leveraging TAM metabolism for developing better therapeutic approaches against cancer.

The role of DGAT1 and DGAT2 in regulating tumor cell growth and their potential clinical implications

Lipid metabolism is widely reprogrammed in tumor cells. Lipid droplet is a common organelle existing in most mammal cells, and its complex and dynamic functions in maintaining redox and metabolic balance, regulating endoplasmic reticulum stress, modulating chemoresistance, and providing essential biomolecules and ATP have been well established in tumor cells. The balance between lipid droplet formation and catabolism is critical to maintaining energy metabolism in tumor cells, while the process of energy metabolism affects various functions essential for tumor growth. The imbalance of synthesis and catabolism of fatty acids in tumor cells leads to the alteration of lipid droplet content in tumor cells. Diacylglycerol acyltransferase 1 and diacylglycerol acyltransferase 2, the enzymes that catalyze the final step of triglyceride synthesis, participate in the formation of lipid droplets in tumor cells and in the regulation of cell proliferation, migration and invasion, chemoresistance, and prognosis in tumor. Several diacylglycerol acyltransferase 1 and diacylglycerol acyltransferase 2 inhibitors have been developed over the past decade and have shown anti-tumor effects in preclinical tumor models and improvement of metabolism in clinical trials. In this review, we highlight key features of fatty acid metabolism and different paradigms of diacylglycerol acyltransferase 1 and diacylglycerol acyltransferase 2 activities on cell proliferation, migration, chemoresistance, and prognosis in tumor, with the hope that these scientific findings will have potential clinical implications.

Targeting DGAT1 inhibits prostate cancer cells growth by inducing autophagy flux blockage via oxidative stress

Impaired macroautophagy/autophagy flux has been implicated in the treatment of prostate cancer (PCa). However, the mechanism underlying autophagy dysregulation in PCa remains unknown. In the current study, we investigated the role of diacylglycerol acyltransferases 1 (DGAT1) and its potential effects on cellular energy homeostasis and autophagy flux in PCa. The results of immunohistochemical staining suggested that DGAT1 expression was positively corrected with tumor stage and node metastasis, indicating DGAT1 is an important factor involved in the development and progression of PCa. Furthermore, targeting DGAT1 remarkably inhibited cell proliferation in vitro and suppressed PCa growth in xenograft models by triggering severe oxidative stress and subsequently autophagy flux blockage. Mechanically, DGAT1 promoted PCa progression by maintaining cellular energy homeostasis, preserving mitochondrial function, protecting against reactive oxygen species, and subsequently promoting autophagy flux via regulating lipid droplet formation. Moreover, we found that fenofibrate exhibits as an upstream regulator of DGAT1. Fenofibrate performed its anti-PCa effect involved the aforementioned mechanisms, and partially dependent on the regulation of DGAT1. Collectively. These findings indicate that DGAT1 regulates PCa lipid droplets formation and is essential for PCa progression. Targeting DGAT1 might be a promising method to control the development and progression of PCa. Schematic representation of DGAT1 affects autophagy flux by regulating lipid homeostasis and maintaining mitochondrial function in prostate cancer (PCa). PCa is characterized up-regulation of DGAT1, leading to the translocation of free fatty acids into lipid droplets, thereby preventing PCa cell from lipotoxicity. Inhibition of DGAT1 suppresses growth of PCa by inducing oxidative stress and subsequently autophagy flux blockage. Further, the current results revealed that fenofibrate exhibits as an upstream regulator of DGAT1, and fenofibrate plays an anti-PCa role partially dependent on the regulation of DGAT1, suggesting a potential therapeutic approach to ameliorate this refractory tumor.

PRAME Expression: A Target for Cancer Immunotherapy and a Prognostic Factor in Uveal Melanoma

Purpose

Uveal melanoma (UM) is a rare disease with a high mortality, and new therapeutic options are being investigated. Preferentially Expressed Antigen in Melanoma (PRAME) is a cancer testis antigen, expressed in the testis, but also in cancers, including uveal melanoma. PRAME is considered a target for immune therapy in several cancers, and PRAME-specific T cell clones have been shown to kill UM cells.

Methods

We studied the literature on PRAME expression in hematological and solid malignancies, including UM, and its role as a target for immunotherapy. The distribution of tumor features was compared between PRAME-high and PRAME-low UM in a 64-patient cohort from the Leiden University Medical Center (LUMC) and in the Cancer Genome Atlas (TCGA) cohort of 80 cases and differential gene expression analysis was performed in the LUMC cohort.

Results

PRAME is expressed in many malignancies, it is frequently associated with a negative prognosis, and can be the target of T cell receptor (TCR)-transduced T cells, a promising treatment option with high avidity and safety. In UM, PRAME is expressed in 26% to 45% of cases and is correlated with a worse prognosis. In the LUMC and the TCGA cohorts, high PRAME expression was associated with larger diameter, higher Tumor-Node-Metastasis (TNM) stage, more frequent gain of chromosome 8q, and an inflammatory phenotype.

Conclusions

We confirm that PRAME is associated with poor prognosis in UM and has a strong connection with extra copies of 8q. We show that PRAME-specific immunotherapy in an adjuvant setting is promising in treatment of malignancies, including UM.

Characterization of Lipid Alterations by Oncogenic PIK3CA Mutations Using Untargeted Lipidomics in Breast Cancer

Lipids play crucial biological roles in health and disease, including in cancers. The phosphatidylinositol 3-kinase (PI3K) signaling pathway is a pivotal promoter of cell growth and proliferation in various types of cancer. The somatic mutations in PIK3CA, the gene coding for the catalytic subunit p110α of PI3K, are frequently present in cancer cells, including breast cancer. Although the most prominent mutants, represented by single amino acid substitutions in the helical domain in exon 9 (E545K) and the kinase domain in exon 20 (H1047R) are known to cause a gain of PI3K function, activate AKT signaling and induce oncogenic transformation, the effect of these mutations on cellular lipid profiles has not been studied. We carried out untargeted lipidomics using liquid chromatography-tandem mass spectrometry to detect the lipid alterations in mammary gland epithelial MCF10A cells with isogenic knockin of these mutations. A total of 536 species of lipids were analyzed. We found that the levels of monosialogangliosides, signaling molecules known to enhance cell motility through PI3K/AKT pathway, were significantly higher in both mutants. In addition, triglycerides and ceramides, lipid molecules known to be involved in promoting lipid droplet production, cancer cell migration and invasion, were increased, whereas lysophosphatidylcholines and phosphatidylcholines that are known to inhibit cancer cell motility were decreased in both mutants. Our results provide novel insights into a potential link between altered lipid profile and carcinogenesis caused by the PIK3CA hotspot mutations. In addition, we suggest untargeted lipidomics offers prospects for precision/personalized medicine by unpacking new molecular substrates of cancer biology.

Alteration of gastric microbiota and transcriptome in a rat with gastric intestinal metaplasia induced by deoxycholic acid

Objective

Bile reflux plays a key role in the development of gastric intestinal metaplasia (GIM), an independent risk factor of gastric cancer. Here, we aimed to explore the biological mechanism of GIM induced by bile reflux in a rat model.

Methods

Rats were treated with 2% sodium salicylate and allowed to freely drink 20 mmol/L sodium deoxycholate for 12 weeks, and GIM was confirmed by histopathological analysis. Gastric microbiota was profiled according to the 16S rDNA V3-V4 region, gastric transcriptome was sequenced, and serum bile acids (BAs) were analyzed by targeted metabolomics. Spearman's correlation analysis was used in constructing the network among gastric microbiota, serum BAs, and gene profiles. Real-time polymerase chain reaction (RT-PCR) measured the expression levels of nine genes in the gastric transcriptome.

Results

In the stomach, deoxycholic acid (DCA) decreased the microbial diversity but promoted the abundances of several bacterial genera, such as Limosilactobacillus, Burkholderia-Caballeronia-Paraburkholderia, and Rikenellaceae RC9 gut group. Gastric transcriptome showed that the genes enriched in gastric acid secretion were significantly downregulated, whereas the genes enriched in fat digestion and absorption were obviously upregulated in GIM rats. The GIM rats had four promoted serum BAs, namely cholic acid (CA), DCA, taurocholic acid, and taurodeoxycholic acid. Further correlation analysis showed that the Rikenellaceae RC9 gut group was significantly positively correlated with DCA and RGD1311575 (capping protein-inhibiting regulator of actin dynamics), and RGD1311575 was positively correlated with Fabp1 (fatty acid-binding protein, liver), a key gene involved in fat digestion and absorption. Finally, the upregulated expression of Dgat1 (diacylglycerol acyltransferase 1) and Fabp1 related to fat digestion and absorption was identified by RT-PCR and IHC.

Conclusion

DCA-induced GIM enhanced gastric fat digestion and absorption function and impaired gastric acid secretion function. The DCA-Rikenellaceae RC9 gut group-RGD1311575/Fabp1 axis might play a key role in the mechanism of bile reflux-related GIM.

Review of lignans from 2019 to 2021: Newly reported compounds, diverse activities, structure-activity relationships and clinical applications

Lignans, with various biological activities, such as antitumor, antioxidant, antibacterial, and antiviral activities, are widely distributed in nature and mainly exist in the xylem of plants. In this paper, we summarized the structures and bioactivities of lignans reported in recent years (2019-2021) from five parts, including (1) a summary and classification of newly reported compounds; (2) the pharmacological activities of lignans; (3) molecular resources and activity distribution; (4) the structure-activity relationships; and (5) the clinical application of lignans. This review covers all undescribed compounds that were reported within the covered period of time and all bioactivity data about previously isolated lignans. The distribution of lignans in different plants and families is visualized, which improves the efficiency of searching for specific molecules. The diverse activities of different types of lignans provide an important reference for the rapid screening of these compounds. Discussion about the structure-activity relationships of lignans provides a direction for the structural modification of skeleton molecules. Combined with the clinical application of such molecules, this work will provide a valuable reference for pharmaceutical chemists.

Lipid Metabolism in Glioblastoma: From De Novo Synthesis to Storage

Glioblastoma (GBM) is the most lethal primary brain tumor. With limited therapeutic options, novel therapies are desperately needed. Recent studies have shown that GBM acquires large amounts of lipids for rapid growth through activation of sterol regulatory element-binding protein 1 (SREBP-1), a master transcription factor that regulates fatty acid and cholesterol synthesis, and cholesterol uptake. Interestingly, GBM cells divert substantial quantities of lipids into lipid droplets (LDs), a specific storage organelle for neutral lipids, to prevent lipotoxicity by increasing the expression of diacylglycerol acyltransferase 1 (DGAT1) and sterol-O-acyltransferase 1 (SOAT1), which convert excess fatty acids and cholesterol to triacylglycerol and cholesteryl esters, respectively. In this review, we will summarize recent progress on our understanding of lipid metabolism regulation in GBM to promote tumor growth and discuss novel strategies to specifically induce lipotoxicity to tumor cells through disrupting lipid storage, a promising new avenue for treating GBM.

Acyl-CoA:diacylglycerol acyltransferase: Properties, physiological roles, metabolic engineering and intentional control

Acyl-CoA:diacylglycerol acyltransferase (DGAT, EC 2.3.1.20) catalyzes the last reaction in the acyl-CoA-dependent biosynthesis of triacylglycerol (TAG). DGAT activity resides mainly in membrane-bound DGAT1 and DGAT2 in eukaryotes and bifunctional wax ester synthase-diacylglycerol acyltransferase (WSD) in bacteria, which are all membrane-bound proteins but exhibit no sequence homology to each other. Recent studies also identified other DGAT enzymes such as the soluble DGAT3 and diacylglycerol acetyltransferase (EaDAcT), as well as enzymes with DGAT activities including defective in cuticular ridges (DCR) and steryl and phytyl ester synthases (PESs). This review comprehensively discusses research advances on DGATs in prokaryotes and eukaryotes with a focus on their biochemical properties, physiological roles, and biotechnological and therapeutic applications. The review begins with a discussion of DGAT assay methods, followed by a systematic discussion of TAG biosynthesis and the properties and physiological role of DGATs. Thereafter, the review discusses the three-dimensional structure and insights into mechanism of action of human DGAT1, and the modeled DGAT1 from Brassica napus. The review then examines metabolic engineering strategies involving manipulation of DGAT, followed by a discussion of its therapeutic applications. DGAT in relation to improvement of livestock traits is also discussed along with DGATs in various other eukaryotic organisms.

The Role of Lipid Metabolism in Gastric Cancer

Gastric cancer has been one of the most common cancers worldwide with extensive metastasis and high mortality. Chemotherapy has been found as a main treatment for metastatic gastric cancer, whereas drug resistance limits the effectiveness of chemotherapy and leads to treatment failure. Chemotherapy resistance in gastric cancer has a complex and multifactorial mechanism, among which lipid metabolism plays a vital role. Increased synthesis of new lipids or uptake of exogenous lipids can facilitate the rapid growth of cancer cells and tumor formation. Lipids form the structural basis of biofilms while serving as signal molecules and energy sources. It is noteworthy that lipid metabolism is capable of inducing drug resistance in gastric cancer cells by reshaping the tumor micro-environment. In this study, new mechanisms of lipid metabolism in gastric cancer and the metabolic pathways correlated with chemotherapy resistance are reviewed. In particular, we discuss the effects of lipid metabolism on autophagy, biomarkers treatment and drug resistance in gastric cancer from the perspective of lipid metabolism. In brief, new insights can be gained into the development of promising therapies through an in-depth investigation of the mechanism of lipid metabolism reprogramming and resensitization to chemotherapy in gastric cancer cells, and scientific treatment can be provided by applying lipid-key enzyme inhibitors as cancer chemical sensitizers in clinical settings.

An Aging-Related Gene Signature-Based Model for Risk Stratification and Prognosis Prediction in Breast Cancer

BACKGROUND

Aging, an inevitable process characterized by functional decline over time, is a significant risk factor for various tumors. However, little is known about aging-related genes (ARGs) in breast cancer (BC). We aimed to explore the potential prognostic role of ARGs and to develop an ARG-based prognosis signature for BC.

METHODS

RNA-sequencing expression profiles and corresponding clinicopathological data of female patients with BC were obtained from public databases in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). An ARG-based risk signature was constructed in the TCGA cohort based on results of least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis, and its prognostic value was further validated in the GSE20685 cohort.

RESULTS

A six ARG-based signature, including CLU, DGAT1, MXI1, NFKBI, PIK3CA and PLAU, was developed in the TCGA cohort and significantly stratified patients into low- and high-risk groups. Patients in the former group showed significantly better prognosis than those in the latter. Multivariate Cox regression analysis demonstrated that the ARG risk score was an independent prognostic factor for BC. A predictive nomogram integrating the ARG risk score and three identified factors (age, N- and M-classification) was established in the TCGA cohort and validated in the GSE20685 cohort. Calibration plots showed good consistency between predicted survival probabilities and actual observations.

CONCLUSION

A novel ARG-based risk signature was developed for patients with BC, which can be used for individual prognosis prediction and promoting personalized treatment.

Prognostic Score System Using Preoperative Inflammatory, Nutritional and Tumor Markers to Predict Prognosis for Gastric Cancer: A Two-Center Cohort Study

INTRODUCTION

Gastric cancer (GC) is the fourth leading cause of cancer-related death worldwide. Our study aimed to investigate the prognostic value of preoperative inflammatory, nutritional and tumor markers and develop an effective prognostic score system to predict the prognosis of GC patients.

METHODS

We retrospectively analyzed 1587 consecutive GC patients who received curative gastrectomy from two medical centers. A novel prognostic score system was proposed based on independently preoperative markers associated with overall survival (OS) of GC patients. A nomogram based on prognostic score system was further established and validated internally and externally.

RESULTS

Based on multivariate analysis in the training set, a novel BLC (body mass index-lymphocyte-carbohydrate antigen 19-9) score system was proposed, which showed an effective predictability of OS in GC patients (log-rank P < 0.001). Moreover, receiver-operating characteristic (ROC) analysis showed that BLC had better performance in predicting OS than the traditional prognostic markers. The C-index of the BLC based-nomogram was 0.710 (95% CI 0.686-0.734), and the areas under ROC curves for predicting 3- and 5-year OS were 0.781 (95% CI 0.750-0.813) and 0.755 (95% CI 0.723-0.786), respectively, which were higher than those of tumor node metastasis (TNM) staging system alone. The calibration curve for probability of 3- and 5-year OS rate showed a good fitting effect between prediction by nomogram and actual observation. Verification in the internal and external validation sets showed results consistent with those in the training set.

CONCLUSIONS

The BLC combining inflammatory, nutritional and tumor markers was an independent prognostic predictor for GC patients, and the nomogram based on BLC could accurately predict the personalized survival of patients with GC.