Loss of HSulf-1 promotes altered lipid metabolism in ovarian cancer

Urine metabolomics for assessing fertility-sparing treatment efficacy in endometrial cancer: a non-invasive approach using ultra-performance liquid chromatography mass spectrometry

OBJECTIVE

This study aimed to reveal the urine metabolic change of endometrial cancer (EC) patients during fertility-sparing treatment and establish non-invasive predictive models to identify patients with complete remission (CR).

METHOD

This study enrolled 20 EC patients prior to treatment (PT) and 22 patients with CR, aged 25-40 years. Eligibility criteria consisted of stage IA high-grade EC, lesions confined to endometrium, normal hepatic and renal function, normal urine test, no contraindication for fertility-sparing treatment and no prior therapy. Urine samples were analyzed using ultraperformance liquid chromatography mass spectrometry (UPLC-MS), a technique chosen for its high sensitivity and resolution, allows for rapid, accurate identification and quantification of metabolites, providing a comprehensive metabolic profile and facilitating the discovery of potential biomarkers. Analytical techniques were employed to determine distinct metabolites and altered metabolic pathways. The statistical analyses were performed using univariate and multivariate analyses, logistic regression and receiver operating characteristic (ROC) curves to discover and validate the potential biomarker models.

RESULTS

A total of 108 different urine metabolomes were identified between CR and PT groups. These metabolites were enriched in ascorbate and aldarate metabolism, one carbon pool by folate, and some amino acid metabolisms pathways. A panel consisting of Baicalin, 5beta-1,3,7 (11)-Eudesmatrien-8-one, Indolylacryloylglycine, Edulitine, and Physapubenolide were selected as biomarkers, which demonstrated the best predictive ability with the AUC values of 0.982/0.851 in training/10-fold-cross-validation group, achieving a sensitivity of 0.975 and specificity of 0.967, respectively.

CONCLUSION

The urine metabolic analysis revealed the metabolic changes in EC patients during the fertility-sparing treatment. The predictive biomarkers present great potential diagnostic value in fertility-sparing treatments for EC patients, offering a less invasive means of monitoring treatment efficacy. Further research should explore the mechanistic underpinnings of these metabolic changes and validate the biomarker panel in larger, diverse populations due to the small sample size and single-institution nature of our study.

Group III phospholipase A2 downregulation attenuated survival and metastasis in ovarian cancer and promotes chemo-sensitization

Background

Aberrant lipogenicity and deregulated autophagy are common in most advanced human cancer and therapeutic strategies to exploit these pathways are currently under consideration. Group III Phospholipase A2 (sPLA2-III/PLA2G3), an atypical secretory PLA2, is recognized as a regulator of lipid metabolism associated with oncogenesis. Though recent studies reveal that high PLA2G3 expression significantly correlates with poor prognosis in several cancers, however, role of PLA2G3 in ovarian cancer (OC) pathogenesis is still undetermined.

Methods

CRISPR-Cas9 and shRNA mediated knockout and knockdown of PLA2G3 in OC cells were used to evaluate lipid droplet (LD) biogenesis by confocal and Transmission electron microscopy analysis, and the cell viability and sensitization of the cells to platinum-mediated cytotoxicity by MTT assay. Regulation of primary ciliation by PLA2G3 downregulation both genetically and by metabolic inhibitor PFK-158 induced autophagy was assessed by immunofluorescence-based confocal analysis and immunoblot. Transient transfection with GFP-RFP-LC3B and confocal analysis was used to assess the autophagic flux in OC cells. PLA2G3 knockout OVCAR5 xenograft in combination with carboplatin on tumor growth and metastasis was assessed in vivo. Efficacy of PFK158 alone and with platinum drugs was determined in patient-derived primary ascites cultures expressing PLA2G3 by MTT assay and immunoblot analysis.

Results

Downregulation of PLA2G3 in OVCAR8 and 5 cells inhibited LD biogenesis, decreased growth and sensitized cells to platinum drug mediated cytotoxicity in vitro and in in vivo OVCAR5 xenograft. PLA2G3 knockdown in HeyA8MDR-resistant cells showed sensitivity to carboplatin treatment. We found that both PFK158 inhibitor-mediated and genetic downregulation of PLA2G3 resulted in increased number of percent ciliated cells and inhibited cancer progression. Mechanistically, we found that PFK158-induced autophagy targeted PLA2G3 to restore primary cilia in OC cells. Of clinical relevance, PFK158 also induces percent ciliated cells in human-derived primary ascites cells and reduces cell viability with sensitization to chemotherapy.

Conclusions

Taken together, our study for the first time emphasizes the role of PLA2G3 in regulating the OC metastasis. This study further suggests the therapeutic potential of targeting phospholipases and/or restoration of PC for future OC treatment and the critical role of PLA2G3 in regulating ciliary function by coordinating interface between lipogenesis and metastasis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13046-021-01985-9.

Expression and prognostic significance of fatty acid synthase in clear cell renal cell carcinoma

Fatty acid synthase (FASN), a key enzyme essential for fatty acid (FA) synthesis, was reportedly implicated in the initiation and progression of various cancers. However, the clinical significance of FASN in renal cell carcinoma (RCC) has not been fully elucidated yet. Here we compare the expression profile and evaluate the prognostic significance of FASN in clear cell RCC (ccRCC) patients. FASN expression was examined in 3 pairs ccRCC and their adjacent nontumor tissues by western blotting (WB) analysis, and its expression was assessed in 145 ccRCC and 13 nontumor tissues by immunohistochemistry (IHC) analysis with tissue microarrays (TMAs). The prognosis of FASN was further investigated in large-scale database using LinkedOmics (n = 537) and The Cancer Protein Atlas (TCPA, n = 445), respectively. WB detected higher FASN expression in ccRCC than normal tissues, then IHC analysis revealed that FASN expression was positively associated with histological grade, pathological stage, tumor size and metastasis status, and negatively associated with cancer-specific survival (CSS). Univariate survival analysis demonstrated that high grade, advanced stage, large tumor, metastasis, and high FASN expression were significantly associated with a shorter CSS, and multivariate analysis revealed tumor grade, stage, metastasis and FASN were identified as independent predictors for CSS in patients with ccRCC. Further LinkedOmics and TCPA analyses confirmed that high FASN expression was correlated with a poorer overall survival (OS) of ccRCC. Collectively, these findings demonstrated FASN could be a poor prognostic factor in ccRCC patients, which indicated that FA synthesis might be implicated in the tumorigenesis and progression of ccRCC.

Lipolytic gene DAGLA is targeted by miR-223 in chicken hepatocytes

miR-223 is an important miRNA. It plays important roles in lipid metabolism by targeting related genes in mammals. It may be related to fatty liver in laying hens and its functions and target genes need further study. Through bioinformatics, we found that 349 genes were predicted as target genes of miR-223. Lipid-related gene DAGLA was among the predicted target genes. Dual-luciferase reporter assays showed that DAGLA was the target gene of miR-223 and the site mutation assays validated the target site of miR-223 in DAGLA. Overexpression of miR-223 in chicken hepatocytes LMH decreased the mRNA and protein expression of DAGLA, while knockdown of miR-223 increased expression of DAGLA in LMH cells, further indicating that miR-223 targets DAGLA and downregulates its expression. Since the target site of miR-223 in chicken DAGLA is not conserved, these findings suggest that miR-223 plays a specific role in chicken liver by regulating expression of target gene DAGLA.

HSulf‑1 and palbociclib exert synergistic antitumor effects on RB‑positive triple‑negative breast cancer

Human sulfatase-1 (HSulf-1) is emerging as a novel prognostic biomarker in breast cancer. Previous studies demonstrated HSulf-1 to function as a negative regulator of cyclin D1 in breast cancer. Accumulating preclinical evidence is supporting the efficacy of cyclin-dependent kinase (CDK) 4/6 inhibitors against the luminal androgen receptor sub-type of triple-negative breast cancer (TNBC). It was therefore hypothesized that HSulf-1 may cooperate with CDK4/6 inhibitors to control cell cycle progression in breast cancer cells. HSulf-1 expression was found to be downregulated in TNBC tissues and cell lines compared with that in healthy tissues and non-breast cancer cell lines, respectively. High levels of HSulf-1 expression was also found to be associated with increased progression-free survival and overall survival in patients with TNBC. Functionally, it was demonstrated that HSulf-1 served as tumor suppressor in TNBC by inducing cell cycle arrest and apoptosis whilst inhibiting proliferation, epithelial-mesenchymal transition, migration and invasion. Subsequent overexpression of HSulf-1 coupled with treatment with the CDK4/6 inhibitor palbociclib exhibited a synergistic antitumor effect on retinoblastoma (RB)-positive TNBC. Further studies revealed the mechanism underlying this cooperative antiproliferative effect involved to be due to the prohibitive effects of HSulf-1 on the palbociclib-induced accumulation of cyclin D1 through AKT/STAT3 and ERK1/2/STAT3 signaling. Taken together, findings from the present study not only suggest that HSulf-1 may be a potential therapeutic target for TNBC, but also indicate that combinatorial treatment could be an alternative therapeutic option for RB-positive TNBC, which may open novel perspectives.

Studying nanoscale structural alterations in cancer cells to evaluate ovarian cancer drug treatment, using transmission electron microscopy imaging

Understanding nanoscale structural changes can provide information about the physical state of cells/tissues. It has now been shown that increases in nanoscale structural alterations are associated with the progress of carcinogenesis in most cancer cases, including early carcinogenesis. Anti-cancerous therapies are designed to inhibit the growth of cancer cells; however, it is challenging to detect the efficacy of such drugs in the early stages of treatment. A unique method of assessing the impact of anti-cancerous drugs on cancerous cells/tissues is to probe the nanoscale structural alterations. In this paper, we study the effect of different anti-cancerous drugs on ovarian tumorigenic cells, using their nanoscale structural alterations as a biomarker. Transmission electron microscopy (TEM) imaging on thin cell sections is performed to obtain their nanoscale structures. The degree of nanoscale structural alterations of tumorigenic cells and anti-cancerous drug treated tumorigenic cells are quantified by using the recently developed inverse participation ratio (IPR) technique. Results show an increase in the degree of nanoscale fluctuations in tumorigenic cells relative to non-tumorigenic cells; then a near-reversal of the degree of fluctuation in tumorigenic cells to that in non-tumorigenic cells, following anti-cancerous drug treatment. These results support that the effect of anti-cancerous drugs in cancer treatment can be quantified by using the degree of nanoscale fluctuations in the cells via TEM imaging. Potential applications of the technique for cancer treatment are also discussed.

Effect of monoacylglycerol lipase on the tumor growth in endometrial cancer

Aim

Abnormal lipid metabolism plays a dual role in tumorigenesis, specifically in the occurrence and development of cancers. Monoacylglycerol lipase (MAGL), a hydrolase that is important for lipid metabolism, plays a vital role in different aspects of tumorigenesis. Many studies have shown that MAGL is highly elevated in a variety of cancers and plays an active role. However, its potential role in supporting endometrial cancer (EC) growth and progression has not yet been explored in depth.

Methods

Immunohistochemistry and quantitative real‐time reverse transcription polymerase chain reaction were performed to estimate the protein and messenger RNA (mRNA) levels of MAGL in tumor tissues. Then, JZL184 and small interfering RNA (siRNA) were used to decrease the expression of MAGL in EC cells. The gene and protein expression levels of MAGL were measured using quantitative real‐time PCR and western blotting, respectively. Additionally, the effect of MAGL on tumor growth in EC was detected by 3‐(4,5‐dimethylthiazol‐2‐yl)‐2,5‐diphenyltetrazolium bromide , cell cycle and western blotting assay in vitro.

Results

We found that MAGL was overexpressed in EC and was significantly correlated with surgical‐pathological stage, myometrial invasion, number of pregnancies and body mass index. The growth and cell cycle progression of tumor cells were significantly impaired in vitro by the pharmacological and siRNA‐mediated MAGL inhibition. In addition, MAGL inhibition seemed to repress two target genes, Cyclin D1 and Bcl‐2.

Conclusion

In summary, we have demonstrated that MAGL is involved in EC growth and progression. Our results suggest that targeting MAGL may be a novel and valid treatment for EC.

Non-coding RNAs derailed: The many influences on the fatty acid reprogramming of cancer

Non-coding RNAs (NcRNAs), a family of functional RNA molecules that cannot translate into proteins but control specific gene expression programs, have been shown to be implicated in various biological processes, including fatty acid metabolism. Fast-growing tumor cells rewire their fatty acid metabolic circuitry in order to meet the needs of energy storage, membrane proliferation, and the generation of signaling molecules, which is achieved by regulating a variety of key enzymes along with related signaling pathways in fatty acid metabolism. This review presents an update of our knowledge about the regulatory network of ncRNAs-specifically, microRNAs (miRNAs), long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs)-in this metabolic shift and discusses the possibility of ncRNA-based therapeutics being applied to the restoration of cancer-related fatty acid metabolism.

Identification of a six-gene signature predicting overall survival for hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) remains a major challenge for public health worldwide. Considering the great heterogeneity of HCC, more accurate prognostic models are urgently needed. To identify a robust prognostic gene signature, we conduct this study.

Materials and methods

Level 3 mRNA expression profiles and clinicopathological data were obtained in The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC). GSE14520 dataset from the gene expression omnibus (GEO) database was downloaded to further validate the results in TCGA. Differentially expressed mRNAs between HCC and normal tissue were investigated. Univariate Cox regression analysis and lasso Cox regression model were performed to identify and construct the prognostic gene signature. Time-dependent receiver operating characteristic (ROC), Kaplan–Meier curve, multivariate Cox regression analysis, nomogram, and decision curve analysis (DCA) were used to assess the prognostic capacity of the six-gene signature. The prognostic value of the gene signature was further validated in independent GSE14520 cohort. Gene Set Enrichment Analyses (GSEA) was performed to further understand the underlying molecular mechanisms. The performance of the prognostic signature in differentiating between normal liver tissues and HCC were also investigated.

Results

A novel six-gene signature (including CSE1L, CSTB, MTHFR, DAGLA, MMP10, and GYS2) was established for HCC prognosis prediction. The ROC curve showed good performance in survival prediction in both the TCGA HCC cohort and the GSE14520 validation cohort. The six-gene signature could stratify patients into a high- and low-risk group which had significantly different survival. Cox regression analysis showed that the six-gene signature could independently predict OS. Nomogram including the six-gene signature was established and shown some clinical net benefit. Furthermore, GSEA revealed several significantly enriched oncological signatures and various metabolic process, which might help explain the underlying molecular mechanisms. Besides, the prognostic signature showed a strong ability for differentiating HCC from normal tissues.

Conclusions

Our study established a novel six-gene signature and nomogram to predict overall survival of HCC, which may help in clinical decision making for individual treatment.

Electronic supplementary material

The online version of this article (10.1186/s12935-019-0858-2) contains supplementary material, which is available to authorized users.

Targeted metabolomic profiling of low and high grade serous epithelial ovarian cancer tissues: a pilot study

INTRODUCTION

Epithelial ovarian cancer (EOC) remains the leading cause of death from gynecologic malignancies and has an alarming global fatality rate. Besides the differences in underlying pathogenesis, distinguishing between high grade (HG) and low grade (LG) EOC is imperative for the prediction of disease progression and responsiveness to chemotherapy.

OBJECTIVES

The aim of this study was to investigate, the tissue metabolome associated with HG and LG serous epithelial ovarian cancer.

METHODS

A combination of one dimensional proton nuclear magnetic resonance (1D H NMR) spectroscopy and targeted mass spectrometry (MS) was employed to profile the tissue metabolome of HG, LG serous EOCs, and controls.

RESULTS

Using partial least squares-discriminant analysis, we observed significant separation between all groups (p < 0.05) following cross validation. We identified which metabolites were significantly perturbed in each EOC grade as compared with controls and report the biochemical pathways which were perturbed due to the disease. Among these metabolic pathways, ascorbate and aldarate metabolism was identified, for the first time, as being significantly altered in both LG and HG serous cancers. Further, we have identified potential biomarkers of EOC and generated predictive algorithms with AUC (CI) = 0.940 and 0.929 for HG and LG, respectively.

CONCLUSION

These previously unreported biochemical changes provide a framework for future metabolomic studies for the development of EOC biomarkers. Finally, pharmacologic targeting of the key metabolic pathways identified herein could lead to novel and effective treatments of EOC.

Therapeutic targeting of PFKFB3 with a novel glycolytic inhibitor PFK158 promotes lipophagy and chemosensitivity in gynecologic cancers

Metabolic alterations are increasingly recognized as important novel anti‐cancer targets. Among several regulators of metabolic alterations, fructose 2,6 bisphosphate (F2,6BP) is a critical glycolytic regulator. Inhibition of the active form of PFKFB3^ser461 using a novel inhibitor, PFK158 resulted in reduced glucose uptake, ATP production, lactate release as well as induction of apoptosis in gynecologic cancer cells. Moreover, we found that PFK158 synergizes with carboplatin (CBPt) and paclitaxel (PTX) in the chemoresistant cell lines, C13 and HeyA8MDR but not in their chemosensitive counterparts, OV2008 and HeyA8, respectively. We determined that PFK158‐induced autophagic flux leads to lipophagy resulting in the downregulation of cPLA2, a lipid droplet (LD) associated protein. Immunofluorescence and co‐immunoprecipitation revealed colocalization of p62/SQSTM1 with cPLA2 in HeyA8MDR cells uncovering a novel pathway for the breakdown of LDs promoted by PFK158. Interestingly, treating the cells with the autophagic inhibitor bafilomycin A reversed the PFK158‐mediated synergy and lipophagy in chemoresistant cells. Finally, in a highly metastatic PTX‐resistant in vivo ovarian mouse model, a combination of PFK158 with CBPt significantly reduced tumor weight and ascites and reduced LDs in tumor tissue as seen by immunofluorescence and transmission electron microscopy compared to untreated mice. Since the majority of cancer patients will eventually recur and develop chemoresistance, our results suggest that PFK158 in combination with standard chemotherapy may have a direct clinical role in the treatment of recurrent cancer.

What's new?

Ovarian and cervical cancer patients experience high rates of chemoresistance and tumor recurrence. To improve patient outcome, greater understanding of mechanisms behind these phenomena is needed. Here, activity of PFKFB3, a glycolytic regulator overexpressed in cancer, was found to be positively correlated with chemoresistance and lipid droplet (LD) biogenesis in ovarian and cervical cancer cells. PFK‐158, a PFKFB3 inhibitor, sensitized chemoresistant cells to drug‐induced cytotoxicity by simultaneously targeting both glycolytic and lipogenic pathways to inhibit tumor growth and LDs in a drug‐resistant xenograft model. The findings warrant further investigation of PFK158 as a treatment for recurrent gynecological malignancy.

Integrated omics and gene expression analysis identifies the loss of metabolite-metabolite correlations in small cell lung cancer

BACKGROUND AND OBJECTIVE

Small cell lung cancer (SCLC) is the most aggressive type of lung carcinoma with high metastatic potential and chemoresistance upon relapse. Cancer cells remodel the existing metabolic pathways for their benefits and the perturbations in cellular metabolism are the hallmark of cancer. However, the extent of these changes remains largely unknown for SCLC.

MATERIALS AND METHODS

We characterized the metabolic perturbations in SCLC cells (SCLCC) by metabolomics. Large-scale correlation analysis was performed between metabolites. Targeted proteomics and gene expression analysis were employed to investigate the changes of key enzymes and genes in the disturbed pathways.

RESULTS

We found dramatic decrease of metabolite-metabolite correlations in SCLCC compared with normal control cells and non-small cell lung cancer cells. Pathway analysis revealed that the loss of correlations was associated with the alternations of fatty acid oxidation, urea cycle, and purine salvage pathway in SCLCC. Targeted proteomics and gene expression analysis confirmed significant changes of the expression for the key enzymes and genes in the pathways in SCLCC including the upregulation of carbamoyl phosphate synthase 1 (urea cycle) and carnitine palmitoyltransferase 1A (fatty acid oxidation), and the downregulation of hypoxanthine-guanine phosphoribosyltransferase and adenine phosphoribosyltransferase in purine salvage pathway.

CONCLUSION

We demonstrated the loss of metabolite-metabolite correlations in SCLCC associated with the upregulation of fatty acid oxidation and urea cycle and the downregulation of purine salvage pathways. Our findings provide insights into the metabolic reprogramming in SCLCC and highlight the potential therapeutic targets for the treatment of SCLC.

A distinctively expressed long noncoding RNA, RP11-466I1.1, may serve as a prognostic biomarker in hepatocellular carcinoma

It is urgent to explore effective diagnostic and prognostic biomarkers for hepatocellular carcinoma (HCC). Now, both lncRNAs and lipid metabolism are involved in tumor pathogenesis. Long noncoding RNA, RP11‐466I1.1, could likely be linked to lipid metabolism according to our bioinformatics analysis, yet studies about RP11‐466I1.1 expression in tumors and its potential functions are still lacking. We aimed to explore the expression and correlations with clinical features of a long noncoding RNA, RP11‐466I1.1, and further analyze its diagnostic and prognostic values in hepatocellular carcinoma. Expression levels of RP11‐466I1.1 were detected by quantitative real‐time PCR (qRT‐PCR) in tissue and serum level, and expression differences were analyzed by independent 2‐tailed t tests. Clinical features were obtained, and their correlations with RP11‐466I1.1 were analyzed by chi‐squared test. Receiver operating characteristic (ROC) curve was performed to assess the diagnostic value. Kaplan‐Meier method and log‐rank test were used to evaluate the prognostic value of RP11‐466I1.1. Results showed that RP11‐466I1.1 was upregulated in HCC tissues (P < .01) and serum (P < .05). Significant upregulation of RP11‐466I1.1 in HCC tissues with poor histological grade (P < .01) and incomplete tumor capsule (P < .01) was found compared to that with better histological grade and complete tumor capsule, respectively. The diagnostic value of RP11‐466I1.1 was not supported by ROC curve analysis (AUROC=0.665, P = .079). Yet, the significant correlation of RP11‐466I1.1 with poor prognosis indicated its potential prognostic value in HCC. This study suggested that RP11‐466I1.1 is distinctively expressed in HCC and may serve as a promising novel prognostic biomarker. The concrete mechanisms of RP11‐466I1.1 playing roles in HCC pathogenesis need further study.

Sulfatase-1 knockdown promotes in vitro and in vivo aggressive behavior of murine hepatocarcinoma Hca-P cells through up-regulation of mesothelin

Our previous study (Oncotarget 2016; 7:46) demonstrated that the over-expression of sulfatase-1 in murine hepatocarcinoma Hca-F cell line (a murine HCC cell with lymph node metastatic [LNM] rate of >75%) downregulates mesothelin and leads to reduction in lymphatic metastasis, both in vitro and in vivo. In current work, we investigated the effects of Sulf-1 knockdown on mesothelin (Msln) and it's effects on the in vitro cell proliferation, migration, invasion, and in vivo tumor growth and LNM rate for Hca-P cells (a murine HCC cell with LNM rate of <25%). Western blotting and qRT-PCR assay indicated that both in vitro and in vivo Sulf-1 was down-regulated by 75% and 68% and led to up regulation of Msln by 55% in shRNA-transfected-Sulf-1-Hca-P cells compared with Hca-P and nonspecific sequence control plasmid transfected Hca-P cell (shRNA-Nc-Hca-P). The in vitro proliferation, migration and invasion potentials were significantly enhanced following Sulf-1 stable down-regulation. In addition, Sulf-1 knock-down significantly promoted tumor growth and increased LNM rates of shRNA-Sulf-1-Hca-P-transplanted mice by 78.6% (11 out of 14 lymph nodes were positive of cancer). Consistent with our previous work, we confirmed that Sulf-1 plays an important role in hepatocarcinoma cell proliferation, migration, invasion and metastasis. The interaction between Sulf-1 and Msln is a potential therapeutic target in the development of liver cancer therapy.

Proteomics analysis to reveal biological pathways and predictive proteins in the survival of high-grade serous ovarian cancer

High-grade serous ovarian cancer (HGSC) is an aggressive cancer with a worse clinical outcome. Therefore, studies about the prognosis of HGSC may provide therapeutic avenues to improve patient outcomes. Since genome alteration are manifested at the protein level, we integrated protein and mRNA data of ovarian cancer from The Cancer Genome Atlas (TCGA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC) and utilized the sparse overlapping group lasso (SOGL) method, a new mechanism-driven variable selection method, to select dysregulated pathways and crucial proteins related to the survival of HGSC. We found that biosynthesis of amino acids was the main biological pathway with the best predictive performance (AUC = 0.900). A panel of three proteins, namely EIF2B1, PRPS1L1 and MAPK13 were selected as potential predictive proteins and the risk score consisting of these three proteins has predictive performance for overall survival (OS) and progression free survival (PFS), with AUC of 0.976 and 0.932, respectively. Our study provides additional information for further mechanism and therapeutic avenues to improve patient outcomes in clinical practice.

Loss of HSulf-1: The Missing Link between Autophagy and Lipid Droplets in Ovarian Cancer

Defective autophagy and deranged metabolic pathways are common in cancer; pharmacologic targeting of these two pathways could provide a viable therapeutic option. However, how these pathways are regulated by limited availability of growth factors is still unknown. Our study shows that HSulf-1 (endosulfatase), a known tumor suppressor which attenuates heparin sulfate binding growth factor signaling, also regulates interplay between autophagy and lipogenesis. Silencing of HSulf-1 in OV202 and TOV2223 cells (ovarian cancer cell lines) resulted in increased lipid droplets (LDs), reduced autophagic vacuoles (AVs) and less LC3B puncta. In contrast, HSulf-1 proficient cells exhibit more AVs and reduced LDs. Increased LDs in HSulf-1 depleted cells was associated with increased ERK mediated cPLA2^S505 phosphorylation. Conversely, HSulf-1 expression in SKOV3 cells reduced the number of LDs and increased the number of AVs compared to vector controls. Furthermore, pharmacological (AACOCF3) and ShRNA mediated downregulation of cPLA2 resulted in reduced LDs, and increased autophagy. Finally, in vivo experiment using OV202 Sh1 derived xenograft show that AACOCF3 treatment effectively attenuated tumor growth and LD biogenesis. Collectively, these results show a reciprocal regulation of autophagy and lipid biogenesis by HSulf-1 in ovarian cancer.

HSulf-1 deficiency dictates a metabolic reprograming of glycolysis and TCA cycle in ovarian cancer

Warburg effect has emerged as a potential hallmark of many cancers. However, the molecular mechanisms that led to this metabolic state of aerobic glycolysis, particularly in ovarian cancer (OVCA) have not been completely elucidated. HSulf-1 predominantly functions by limiting the bioavailability of heparan binding growth factors and hence their downstream signaling. Here we report that HSulf-1, a known putative tumor suppressor, is a negative regulator of glycolysis. Silencing of HSulf-1 expression in OV202 cell line increased glucose uptake and lactate production by upregulating glycolytic genes such as Glut1, HKII, LDHA, as well as metabolites. Conversely, HSulf-1 overexpression in TOV21G cells resulted in the down regulation of glycolytic enzymes and reduced glycolytic phenotype, supporting the role of HSulf-1 loss in enhanced aerobic glycolysis. HSulf-1 deficiency mediated glycolytic enhancement also resulted in increased inhibitory phosphorylation of pyruvate dehydrogenase (PDH) thus blocking the entry of glucose flux into TCA cycle. Consistent with this, metabolomic and isotope tracer analysis showed reduced glucose flux into TCA cycle. Moreover, HSulf-1 loss is associated with lower oxygen consumption rate (OCR) and impaired mitochondrial function. Mechanistically, lack of HSulf-1 promotes c-Myc induction through HB-EGF-mediated p-ERK activation. Pharmacological inhibition of c-Myc reduced HB-EGF induced glycolytic enzymes implicating a major role of c-Myc in loss of HSulf-1 mediated altered glycolytic pathway in OVCA. Similarly, PG545 treatment, an agent that binds to heparan binding growth factors and sequesters growth factors away from their ligand also blocked HB-EGF signaling and reduced glucose uptake in vivo in HSulf-1 deficient cells.

Lipid Droplets: A Key Cellular Organelle Associated with Cancer Cell Survival under Normoxia and Hypoxia

The Warburg effect describes the phenomenon by which cancer cells obtain energy from glycolysis even under normoxic (O₂-sufficient) conditions. Tumor tissues are generally exposed to hypoxia owing to inefficient and aberrant vasculature. Cancer cells have multiple molecular mechanisms to adapt to such stress conditions by reprogramming the cellular metabolism. Hypoxia-inducible factors are major transcription factors induced in cancer cells in response to hypoxia that contribute to the metabolic changes. In addition, cancer cells within hypoxic tumor areas have reduced access to serum components such as nutrients and lipids. However, the effect of such serum factor deprivation on cancer cell biology in the context of tumor hypoxia is not fully understood. Cancer cells are lipid-rich under normoxia and hypoxia, leading to the increased generation of a cellular organelle, the lipid droplet (LD). In recent years, the LD-mediated stress response mechanisms of cancer cells have been revealed. This review focuses on the production and functions of LDs in various types of cancer cells in relation to the associated cellular environment factors including tissue oxygenation status and metabolic mechanisms. This information will contribute to the current understanding of how cancer cells adapt to diverse tumor environments to promote their survival.

Fatty acid oxidation and carnitine palmitoyltransferase I: emerging therapeutic targets in cancer

Tumor cells exhibit unique metabolic adaptations that are increasingly viewed as potential targets for novel and specific cancer therapies. Among these targets, the carnitine palmitoyltransferase system is responsible for delivering the long-chain fatty acid (FA) from cytoplasm into mitochondria for oxidation, where carnitine palmitoyltransferase I (CPTI) catalyzes the rate-limiting step of fatty acid oxidation (FAO). With increasing understanding of the crucial role had by fatty acid oxidation in cancer, CPTI has received renewed attention as a pivotal mediator in cancer metabolic mechanism. CPTI activates FAO and fuels cancer growth via ATP and NADPH production, constituting an essential part of cancer metabolism adaptation. Moreover, CPTI also functionally intertwines with other key pathways and factors to regulate gene expression and apoptosis of cancer cell. Here, we summarize recent findings and update the current understanding of FAO and CPTI in cancer and provide theoretical basis for this enzyme as an emerging potential molecular target in cancer therapeutic intervention.

Mifepristone increases mRNA translation rate, triggers the unfolded protein response, increases autophagic flux, and kills ovarian cancer cells in combination with proteasome or lysosome inhibitors

The synthetic steroid mifepristone blocks the growth of ovarian cancer cells, yet the mechanism driving such effect is not entirely understood. Unbiased genomic and proteomic screenings using ovarian cancer cell lines of different genetic backgrounds and sensitivities to platinum led to the identification of two key genes upregulated by mifepristone and involved in the unfolded protein response (UPR): the master chaperone of the endoplasmic reticulum (ER), glucose regulated protein (GRP) of 78 kDa, and the CCAAT/enhancer binding protein homologous transcription factor (CHOP). GRP78 and CHOP were upregulated by mifepristone in ovarian cancer cells regardless of p53 status and platinum sensitivity. Further studies revealed that the three UPR-associated pathways, PERK, IRE1α, and ATF6, were activated by mifepristone. Also, the synthetic steroid acutely increased mRNA translation rate, which, if prevented, abrogated the splicing of XBP1 mRNA, a non-translatable readout of IRE1α activation. Moreover, mifepristone increased LC3-II levels due to increased autophagic flux. When the autophagic-lysosomal pathway was inhibited with chloroquine, mifepristone was lethal to the cells. Lastly, doses of proteasome inhibitors that are inadequate to block the activity of the proteasomes, caused cell death when combined with mifepristone; this phenotype was accompanied by accumulation of poly-ubiquitinated proteins denoting proteasome inhibition. The stimulation by mifepristone of ER stress and autophagic flux offers a therapeutic opportunity for utilizing this compound to sensitize ovarian cancer cells to proteasome or lysosome inhibitors.

Novel personalized pathway-based metabolomics models reveal key metabolic pathways for breast cancer diagnosis

Background

More accurate diagnostic methods are pressingly needed to diagnose breast cancer, the most common malignant cancer in women worldwide. Blood-based metabolomics is a promising diagnostic method for breast cancer. However, many metabolic biomarkers are difficult to replicate among studies.

Methods

We propose that higher-order functional representation of metabolomics data, such as pathway-based metabolomic features, can be used as robust biomarkers for breast cancer. Towards this, we have developed a new computational method that uses personalized pathway dysregulation scores for disease diagnosis. We applied this method to predict breast cancer occurrence, in combination with correlation feature selection (CFS) and classification methods.

Results

The resulting all-stage and early-stage diagnosis models are highly accurate in two sets of testing blood samples, with average AUCs (Area Under the Curve, a receiver operating characteristic curve) of 0.968 and 0.934, sensitivities of 0.946 and 0.954, and specificities of 0.934 and 0.918. These two metabolomics-based pathway models are further validated by RNA-Seq-based TCGA (The Cancer Genome Atlas) breast cancer data, with AUCs of 0.995 and 0.993. Moreover, important metabolic pathways, such as taurine and hypotaurine metabolism and the alanine, aspartate, and glutamate pathway, are revealed as critical biological pathways for early diagnosis of breast cancer.

Conclusions

We have successfully developed a new type of pathway-based model to study metabolomics data for disease diagnosis. Applying this method to blood-based breast cancer metabolomics data, we have discovered crucial metabolic pathway signatures for breast cancer diagnosis, especially early diagnosis. Further, this modeling approach may be generalized to other omics data types for disease diagnosis.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-016-0289-9) contains supplementary material, which is available to authorized users.

Correlation analysis of urine metabolites and clinical staging in patients with ovarian cancer

This study is to investigate the correlation between urine metabolites and clinical staging in patients with ovarian cancer. The urina sanguinis from 56 cases of primary epithelial ovarian cancer patients and 15 healthy volunteers was collected and the urine metabolites were extracted. Ultra high performance liquid chromatography/time-of-flight mass spectrometry (UPLC-Q-TOF-MS) analysis was performed. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were used to analyze the mass spectrometry data. Database retrieval and comparison of the screened metabolites were performed and one-way ANOVA and least significant difference (LSD) t test were carried out. PCA analysis of UPLC-Q-TOF-MS results showed that the score plots of samples from healthy people and patients with ovarian cancer at different clinical stages were separated. Further PLS-DA analysis significantly improved the classification results. The R(2)X was 0.757, the R(2)Y was 0.977 and the Q(2)Y was 0.87, indicating that the model stability and predictability were good. Eight metabolites, including N-acetylneuraminic acid-9-phosphate, 5'-methioadenosine, uric acid-3-nucleoside, pseudouridine, L-valine, succinic acid, L-proline and β-nicotinamide mononucleotide were identified. The contents of these metabolites increased with the development of the disease. There was correlation between urine metabolites and clinical staging in patients with ovarian cancer.

Erratum to: Loss of HSulf-1 promotes altered lipid metabolism in ovarian cancer

[This corrects the article DOI: 10.1186/2049-3002-2-13.].