In vivo detection of dysregulated choline metabolism in paclitaxel-resistant ovarian cancers with proton magnetic resonance spectroscopy

MAFF Mediates PEITC-induced Enhancement of Sensitivity to Carboplatin in Ovarian Cancer Cell Lines via Activating ZNF711 Transcription in vivo and in vitro

Enhanced drug resistance poses a significant challenge in treating ovarian cancer (OC). Phenylethyl isothiocyanate (PEITC) is involved in drug resistance in OC, but the mechanism remains unclear. In this study, we investigated the molecular regulatory mechanism of carboplatin sensitivity in OC associated with PEITC, MAF BZIP Transcription Factor F (MAFF), and Zinc finger proteins (ZNF) 711. The carboplatin sensitivity was significantly increased in OC cells after PEITC treatment. Knockdown of MAFF significantly enhanced the carboplatin sensitivity of OC cells, promoted apoptosis, inhibited colony-forming efficiency in vitro, and suppressed tumor growth in vivo. The binding site of MAFF to the ZNF711 promoter was predicted, and the knockdown of MAFF significantly increased the ZNF711 expression. Results of the dual luciferase assay and ChIP-PCR confirmed the binding of MAFF to the ZNF711 promoter. Immunofluorescence and CoIP results demonstrated the colocalization and the binding of MAFF and its interacting protein, BZIP Transcription Factor ATF-like 3 (BATF3). Similarly, we confirmed the binding of BATF3 to the ZNF711 promoter. Knockdown of BATF3 alone and simultaneous knockdown of BATF3 and MAFF showed similar regulatory effects on ZNF711 transcription and apoptosis. These suggested that the binding of MAFF to BATF3 inhibited ZNF711 transcription and reduced carboplatin sensitivity in OC.

EDI3 knockdown in ER-HER2+ breast cancer cells reduces tumor burden and improves survival in two mouse models of experimental metastasis

BACKGROUND

Despite progress understanding the mechanisms underlying tumor spread, metastasis remains a clinical challenge. We identified the choline-producing glycerophosphodiesterase, EDI3 and reported its association with metastasis-free survival in endometrial cancer. We also observed that silencing EDI3 slowed cell migration and other cancer-relevant phenotypes in vitro. Recent work demonstrated high EDI3 expression in ER-HER2+ breast cancer compared to the other molecular subtypes. Silencing EDI3 in ER-HER2+ cells significantly reduced cell survival in vitro and decreased tumor growth in vivo. However, a role for EDI3 in tumor metastasis in this breast cancer subtype was not explored. Therefore, in the present work we investigate whether silencing EDI3 in ER-HER2+ breast cancer cell lines alters phenotypes linked to metastasis in vitro, and metastasis formation in vivo using mouse models of experimental metastasis.

METHODS

To inducibly silence EDI3, luciferase-expressing HCC1954 cells were transduced with lentiviral particles containing shRNA oligos targeting EDI3 under the control of doxycycline. The effect on cell migration, adhesion, colony formation and anoikis was determined in vitro, and significant findings were confirmed in a second ER-HER2+ cell line, SUM190PT. Doxycycline-induced HCC1954-luc shEDI3 cells were injected into the tail vein or peritoneum of immunodeficient mice to generate lung and peritoneal metastases, respectively and monitored using non-invasive bioluminescence imaging. Metabolite levels in cells and tumor tissue were analyzed using targeted mass spectrometry and MALDI mass spectrometry imaging (MALDI-MSI), respectively.

RESULTS

Inducibly silencing EDI3 reduced cell adhesion and colony formation, as well as increased susceptibility to anoikis in HCC1954-luc cells, which was confirmed in SUM190PT cells. No influence on cell migration was observed. Reduced luminescence was seen in lungs and peritoneum of mice injected with cells expressing less EDI3 after tail vein and intraperitoneal injection, respectively, indicative of reduced metastasis. Importantly, mice injected with EDI3-silenced cells survived longer. Closer analysis of the peritoneal organs revealed that silencing EDI3 had no effect on metastatic organotropism but instead reduced metastatic burden. Finally, metabolic analyses revealed significant changes in choline and glycerophospholipid metabolites in cells and in pancreatic metastases in vivo.

CONCLUSIONS

Reduced metastasis upon silencing supports EDI3's potential as a treatment target in metastasizing ER-HER2+ breast cancer.

Screening by Q Exactive liquid chromatography/tandem mass spectrometry identified Choline, 25-hydroxyvitamin D2, and SM(d18:0/16:1(9Z) (OH)) as biomarkers for high-grade serous ovarian cancer

High-grade serous ovarian cancer (HGSOC) has a high death rate and poor prognosis. The main causes of poor prognosis are asymptomatic early disease, no effective screening method at present, and advanced disease. Changes in cellular metabolism are characteristic of cancer, and plasma metabolome analysis can be used to identify biomarkers. In this study, we used Q Exactive liquid chromatography tandem mass spectrometry (LC-MS/MS, QE) to compare the differentiation between plasma samples (22 HGSOC samples and 22 normal samples). In total, we detected 124 metabolites, and an orthogonal partial least-squares-discriminant analysis (OPLS-DA) model was useful to distinguish HGSOC patients from healthy controls. Choline, 25-hydroxyvitamin D2, and sphingomyelin (d18:0/16:1(9Z) (OH))/SM(d18:0/16:1(9Z) (OH)) showed significantly differential plasma levels in HGSOC patients under the conditions of variable importance in projection (VIP) > 1, p < 0.05 using Student's t-test, and fold change (FC)  ≥ 1.5 or ≤ 0.667. Metabolic pathway analysis can provide valuable information to enhance the understanding of the underlying pathophysiology of HGSOC. In conclusion, the Q Exactive LC/MS/MS method validation-based plasma metabolomics approach may have potential as a convenient screening method for HGSOC and may be a method to monitor tumor recurrence in patients with HGSOC after surgery SIGNIFICANCE: High-grade serous ovarian cancer (HGSOC) has a high death rate and poor prognosis. The main causes of poor prognosis are asymptomatic early disease, no effective screening method at present, and advanced disease. Changes in cellular metabolism are characteristic of cancer, and plasma metabolome analysis can be used to identify biomarkers. In this study, we used Q Exactive liquid chromatography tandem mass spectrometry (LC-MS/MS, QE) to compare the differentiation between plasma samples (20 HGSOC samples and 20 normal samples). In total, we detected 124 metabolites, and an orthogonal partial least-squares-discriminant analysis (OPLS-DA) model was useful to distinguish HGSOC patients from healthy controls. Choline, 25-hydroxyvitamin D2, and sphingomyelin (d18:0/16:1(9Z) (OH))/SM(d18:0/16:1(9Z) (OH)) showed significantly differential plasma levels in HGSOC patients under the conditions of variable importance in projection (VIP) > 1, p < 0.05 using Student's t-test, and fold change (FC) ≥ 1.5 or ≤ 0.667. Metabolic pathway analysis can provide valuable information to enhance the understanding of the underlying pathophysiology of HGSOC. In conclusion, the Q Exactive LC/MS/MS method validation-based plasma metabolomics approach may have potential as a convenient screening method for HGSOC and may be a method to monitor tumor recurrence in patients with HGSOC after surgery.

An update on Glycerophosphodiester Phosphodiesterases; From Bacteria to Human

The hydrolysis of deacylated glycerophospholipids into sn-glycerol 3-phosphate and alcohol is facilitated by evolutionarily conserved proteins known as glycerophosphodiester phosphodiesterases (GDPDs). These proteins are crucial for the pathogenicity of bacteria and for bioremediation processes aimed at degrading organophosphorus esters that pose a hazard to both humans and the environment. Additionally, GDPDs are enzymes that respond to multiple nutrients and could potentially serve as candidate genes for addressing deficiencies in zinc, iron, potassium, and especially phosphate in important plants like rice. In mammals, glycerophosphodiesterases (GDEs) play a role in regulating osmolytes, facilitating the biosynthesis of anandamine, contributing to the development of skeletal muscle, promoting the differentiation of neurons and osteoblasts, and influencing pathological states. Due to their capacity to enhance a plant's ability to tolerate various nutrient deficiencies and their potential as pharmaceutical targets in humans, GDPDs have received increased attention in recent times. This review provides an overview of the functions of GDPD families as vital and resilient enzymes that regulate various pathways in bacteria, plants, and humans.

Impact of Cold Ischemia on the Stability of 1H-MRS-Detected Metabolic Profiles of Ovarian Cancer Specimens

Proton magnetic resonance spectroscopy (1H-MRS) of surgically collected tumor specimens may contribute to investigating cancer metabolism and the significance of the "total choline" (tCho) peak (3.2 ppm) as malignancy and therapy response biomarker. To ensure preservation of intrinsic metabolomic information, standardized handling procedures are needed. The effects of time to freeze (cold ischemia) were evaluated in (a) surgical epithelial ovarian cancer (EOC) specimens using high-resolution (HR) 1H-MRS (9.4 T) of aqueous extracts and (b) preclinical EOC samples (xenografts in SCID mice) investigated by in vivo MRI-guided 1H-MRS (4.7 T) and by HR-1H-MRS (9.4 T) of tumor extracts or intact fragments (using magic-angle-spinning (MAS) technology). No significant changes were found in the levels of 27 of 29 MRS-detected metabolites (including the tCho profile) in clinical specimens up to 2 h cold ischemia, besides an increase in lysine and a decrease in glutathione. EOC xenografts showed a 2-fold increase in free choline within 2 h cold ischemia, without further significant changes for any MRS-detected metabolite (including phosphocholine and tCho) up to 6 h. At shorter times (≤1 h), HR-MAS analyses showed unaltered tCho components, along with significant changes in lactate, glutamate, and glutamine. Our results support the view that a time to freeze of 1 h represents a safe threshold to ensure the maintenance of a reliable tCho profile in EOC specimens.

Habitat Radiomics Based on MRI for Predicting Platinum Resistance in Patients with High-Grade Serous Ovarian Carcinoma: A Multicenter Study

RATIONALE AND OBJECTIVES

This study aims to explore the feasibility of MRI-based habitat radiomics for predicting response of platinum-based chemotherapy in patients with high-grade serous ovarian carcinoma (HGSOC), and compared to conventional radiomics and deep learning models.

MATERIALS AND METHODS

A retrospective study was conducted on HGSOC patients from three hospitals. K-means algorithm was used to perform clustering on T2-weighted images (T2WI), contrast-enhanced T1-weighted images (CE-T1WI), and apparent diffusion coefficient (ADC) maps. After feature extraction and selection, the radiomics model, habitat model, and deep learning model were constructed respectively to identify platinum-resistant and platinum-sensitive patients. A nomogram was developed by integrating the optimal model and clinical independent predictors. The model performance and benefit was assessed using the area under the receiver operating characteristic curve (AUC), net reclassification index (NRI), and integrated discrimination improvement (IDI).

RESULTS

A total of 394 eligible patients were incorporated. Three habitats were clustered, a significant difference in habitat 2 (weak enhancement, high ADC values, and moderate T2WI signal) was found between the platinum-resistant and platinum-sensitive groups (P < 0.05). Compared to the radiomics model (0.640) and deep learning model (0.603), the habitat model had a higher AUC (0.710). The nomogram, combining habitat signatures with a clinical independent predictor (neoadjuvant chemotherapy), yielded a highest AUC (0.721) among four models, with positive NRI and IDI.

CONCLUSION

MRI-based habitat radiomics had the potential to predict response of platinum-based chemotherapy in patients with HGSOC. The nomogram combining with habitat signature had a best performance and good model gains for identifying platinum-resistant patients.

Detection, mechanisms, and therapeutic implications of oncometabolites

Metabolic abnormalities are a hallmark of cancer cells and are essential to tumor progression. Oncometabolites have pleiotropic effects on cancer biology and affect a plethora of processes, from oncogenesis and metabolism to therapeutic resistance. Targeting oncometabolites, therefore, could offer promising therapeutic avenues against tumor growth and resistance to treatments. Recent advances in characterizing the metabolic profiles of cancer cells are shedding light on the underlying mechanisms and associated metabolic networks. This review summarizes the diverse detection methods, molecular mechanisms, and therapeutic targets of oncometabolites, which may lead to targeting oncometabolism for cancer therapy.

Metabolic reprogramming of the tumor immune microenvironment in ovarian cancer: A novel orientation for immunotherapy

Ovarian cancer is the most lethal gynecologic tumor, with the highest mortality rate. Numerous studies have been conducted on the treatment of ovarian cancer in the hopes of improving therapeutic outcomes. Immune cells have been revealed to play a dual function in the development of ovarian cancer, acting as both tumor promoters and tumor suppressors. Increasingly, the tumor immune microenvironment (TIME) has been proposed and confirmed to play a unique role in tumor development and treatment by altering immunosuppressive and cytotoxic responses in the vicinity of tumor cells through metabolic reprogramming. Furthermore, studies of immunometabolism have provided new insights into the understanding of the TIME. Targeting or activating metabolic processes of the TIME has the potential to be an antitumor therapy modality. In this review, we summarize the composition of the TIME of ovarian cancer and its metabolic reprogramming, its relationship with drug resistance in ovarian cancer, and recent research advances in immunotherapy.

Single-Cell RNA Sequencing Reveals the Role of Epithelial Cell Marker Genes in Predicting the Prognosis of Colorectal Cancer Patients

Single-cell RNA sequencing (scRNA-seq) is increasingly used in studies on gastrointestinal cancers. This study investigated the prognostic value of epithelial cell-associated biomarkers in colorectal cancer (CRC) using scRNA-seq data. We downloaded and analysed scRNA-seq data from four CRC samples from the Gene Expression Omnibus (GEO), and we identified marker genes of malignant epithelial cells (MECs) using CRC transcriptome and clinical data downloaded from The Cancer Genome Atlas (TCGA) and GEO as training and validation cohorts, respectively. In the TCGA training cohort, weighted gene correlation network analysis, univariate Cox proportional hazard model (Cox) analysis, and least absolute shrinkage and selection operator regression analysis were performed on the marker genes of MEC subsets to identify a signature of nine prognostic MEC-related genes (MECRGs) and calculate a risk score based on the signature. CRC patients were divided into high- and low-risk groups according to the median risk score. We found that the MECRG risk score was significantly correlated with the clinical features and overall survival of CRC patients, and that CRC patients in the high-risk group showed a significantly shorter survival time. The univariate and multivariate Cox regression analyses showed that the MECRG risk score can serve as an independent prognostic factor for CRC patients. Gene set enrichment analysis revealed that the MECRG signature genes are involved in fatty acid metabolism, p53 signalling, and other pathways. To increase the clinical application value, we constructed a MECRG nomogram by combining the MECRG risk score with other independent prognostic factors. The validity of the nomogram is based on receiver operating characteristics and calibration curves. The MECRG signature and nomogram models were well validated in the GEO dataset. In conclusion, we established an epithelial cell marker gene-based risk assessment model based on scRNA-seq analysis of CRC samples for predicting the prognosis of CRC patients.

Wnt antagonist as therapeutic targets in ovarian cancer

Ovarian cancer is a fatal malignancy in women with a low survival rate that demands new therapeutic paradigms. Cancer cells acquire various exclusive alterations to proliferate, invade, metastasize, and escape cell death, acting independently of growth-inducing or growth-inhibiting signals. The nature of cellular signaling in tumorigenesis is interwoven. Wnt signaling is an evolutionarily conserved signaling cascade that has been shown to regulate ovarian cancer pathogenesis. The molecular mechanism of Wnt signaling underlying the development of ovarian cancer, drug resistance, and relapse is not completely understood. Extracellularly secreted Wnt signaling inhibitors are crucial regulators of ovarian cancer tumorigenesis and malignant properties of cancer stem cells. Wnt inhibitors arbitrated modifications affecting Wnt pathway proteins on the cell membranes, in the cytoplasm, and in the nucleus have been shown to span essential contributions in the initiation, progression, and chemoresistance of ovarian cancer. Although many extrinsic inhibitors developed targeting the downstream components of the Wnt signaling pathway, investigating the molecular mechanisms of endogenous secreted inhibitors might substantiate prognostic or therapeutic biomarkers development. Given the importance of Wnt signaling in ovarian cancer, more systematic studies combined with clinical studies are requisite to probe the precise mechanistic interactions of Wnt antagonists in ovarian cancer. This review outlines the latest progress on the Wnt antagonists and ovarian cancer-specific regulators such as micro-RNAs, small molecules, and drugs regulating these Wnt antagonists in ovarian tumourigenesis.