Regulatory role of hexosamine biosynthetic pathway on hepatic cancer stem cell marker CD133 under low glucose conditions

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Modulation of LXR signaling altered the dynamic activity of human colon adenocarcinoma cancer stem cells in vitro

Background: The expansion and metastasis of colorectal cancers are closely associated with the dynamic growth of cancer stem cells (CSCs). This study aimed to explore the possible effect of LXR (a regulator of glycolysis and lipid hemostasis) in the tumorgenicity of human colorectal CD133 cells. Methods: Human HT-29 CD133+ cells were enriched by MACS and incubated with LXR agonist (T0901317) and antagonist (SR9243) for 72 h. Cell survival was evaluated using MTT assay and flow cytometric analysis of Annexin-V. The proliferation rate was measured by monitoring Ki-67 positive cells using IF imaging. The modulation of LXR was studied by monitoring the activity of all factors related to ABC transporters using real-time PCR assay and western blotting. Protein levels of metabolic enzymes such as PFKFB3, GSK3β, FASN, and SCD were also investigated upon treatment of CSCs with LXR modulators. The migration of CSCs was monitored after being exposed to LXR agonist using scratch and Transwell insert assays. The efflux capacity was measured using hypo-osmotic conditions. The intracellular content of reactive oxygen species was studied by DCFH-DA staining. Results: Data showed incubation of CSCs with T0901317 and SR9243 reduced the viability of CD133 cells in a dose-dependent manner compared to the control group. The activation of LXR up-regulated the expression and protein levels of ABC transporters (ABCA1, ABCG5, and ABCG8) compared to the non-treated cells (p < 0.05). Despite these effects, LXR activation suppressed the proliferation, clonogenicity, and migration of CD133 cells, and increased hypo-osmotic fragility (p < 0.05). We also showed that SR9243 inhibited the proliferation and clonogenicity of CD133 cells through down-regulating metabolic enzymes PFKFB3, GSK3β, FASN, and SCD as compared with the control cells (p < 0.05). Intracellular ROS levels were increased after the inhibition of LXR by SR9243 (p < 0.05). Calling attention, both T0901317 and SR9243 compounds induced apoptotic changes in cancer stem cells (p < 0.05). Conclusions: The regulation of LXR activity can be considered as a selective targeting of survival, metabolism, and migration in CSCs to control the tumorigenesis and metastasis in patients with advanced colorectal cancers

Postoperative serum metabolites of patients on a low carbohydrate ketogenic diet after pancreatectomy for pancreatobiliary cancer: a nontargeted metabolomics pilot study

A ketogenic diet is a potential adjuvant cancer therapy that limits glucose availability to tumours while fuelling normal tissues with ketone bodies. We examined the effect of a low carbohydrate ketogenic diet (LCKD) (80% kcal from fat, ketogenic ratio 1.75:1, w/w) compared to a general hospital diet (GD) on serum metabolic profiles in patients (n = 18, ≥ 19 years old) who underwent pancreatectomy for pancreatobiliary cancer. Serum samples collected preoperatively (week 0) and after the dietary intervention (week 2) were analysed with a nontargeted metabolomics approach using liquid chromatography-tandem mass spectrometry. Serum β-hydroxybutyrate and total ketone levels significantly increased after 2 weeks of LCKD compared to GD (p < 0.05). Principal component analysis score plots and orthogonal partial least squares discriminant analysis also showed significant differences between groups at week 2, with strong validation. In all, 240 metabolites differed between LCKD and GD. Pathways including glycerophospholipid and sphingolipid metabolisms were significantly enriched in the LCKD samples. LCKD decreased C22:1-ceramide levels, which are reported to be high in pancreatic cancer, while increasing lysophosphatidylcholine (18:2), uric acid, citrulline, and inosine levels, which are generally low in pancreatic cancer. Postoperative LCKD might beneficially modulate pancreatic cancer-related metabolites in patients with pancreatobiliary cancer.ope

Cancer stem cells (CSCs) : metabolic strategies for their identification and eradication

Phenotypic and functional heterogeneity is one of the most relevant features of cancer cells within different tumor types and is responsible for treatment failure. Cancer stem cells (CSCs) are a population of cells with stem cell-like properties that are considered to be the root cause of tumor heterogeneity, because of their ability to generate the full rep- ertoire of cancer cell types. Moreover, CSCs have been invoked as the main drivers of metastatic dissemination and therapeutic resistance. As such, targeting CSCs may be a useful strategy to improve the effectiveness of classical anticancer therapies. Recently, metabolism has been considered as a relevant player in CSC biology, and indeed, onco- genic alterations trigger the metabolite-driven dissemination of CSCs. More interestingly, the action of metabolic pathways in CSC maintenance might not be merely a conse- quence of genomic alterations. Indeed, certain metabotypic phenotypes may play a causative role in maintaining the stem traits, acting as an orchestrator of stemness. Here, we review the current studies on the metabolic features of CSCs, focusing on the bio- chemical energy pathways involved in CSC maintenance and propagation. We provide a detailed overview of the plastic metabolic behavior of CSCs in response to microenvironment changes, genetic aberrations, and pharmacological stressors. In addition, we describe the potential of comprehensive metabolic approaches to identify and selectively eradicate CSCs, together with the possibility to ‘force’ CSCs within certain metabolic dependences, in order to effectively target such metabolic biochemical inflexibilities. Finally, we focus on targeting mitochondria to halt CSC dissemination and effectively eradicate cancer

Exploration of urological biomarkers by urine metabolome NMR-analysis in an Asian patient cohort of prostate cancer

1.Prostate Cancer (PC) 1.1.Epidemiology Prostate cancer (PC) is one of the major threats to men’s health worldwide (Siegel et al., 2016; Brawley, 2012; Jahn et al., 2015; Center et al., 2012). In the United States PC was estimated to make up roughly 20% of the new cancer cases in men in 2016. Deaths from PC are expected to account for 8% of cancer associated deaths (Siegel et al., 2016). Epidemiological data from China are still rare and incomplete but were recently supplemented by high-quality data provided by the National Central Cancer Registry of China (NCCR) (Chen et al., 2016). The incidence rate of prostate cancer in China increased from 1998 to 2008 by a factor of 3, from 35.2/100,000 to 110.0/100,000 and the average annual growth rate was as high as 12.07% reaching 60,300 cases in 2015 (Zhu et al., 2015; Coffey, 2001; Baade et al., 2013; Chen et al., 2016). While incidence rates in rural areas remained stable between 2006 and 2009, there was an increase in urban areas, especially documented in Hong Kong and Shanghai. The rapid rise of the incidence rate may be in part related to the aging of the population but there seems to be a strong link to Western-style diet (Lin et al., 2015). A comparison of the incidences of prostate cancer in 2015 showed that although the total number of patients in the United States has reached 3.66 times that of China, the estimated death tolls in the two countries are almost similar (Table 1) (Siegel et al., 2016; Ervik et al., 2016; Chen et al., 2016).Interestingly, the numbers in the European Union (EU, WHO region) are in between which might reflect more regional variations in living conditions and diet. However, further investigations are required to come to valid conclusions. Effectivity of PC treatment and cancer recurrence heavily depend on early detection and proper risk stratification (Moller et al., 2015; Schroder et al., 2012; Klotz et al., 2015; Moyer, 2012). In the US, the proportion of localized prostate cancer accounts for more than 80% of all cases, which is also one of the major reasons the mortality/morbidity rate in the US is much lower than that in Asian countries, and continues to decrease (Moller et al., 2015; Jemal et al., 2015; DeSantis et al., 2014). Therefore, early detection and diagnosis is the most effective way by which to improve the survival rate, and development of new biomarkers and/or reasonable combination of current diagnostic methods is a hot spot in the field of prostate cancer research (Felgueiras et al., 2014). Among countries that have implemented prostate cancer screening strategies, five-year survival rates have improved rapidly in Japan, with an average annual increase of about 11.7% and a 5-year survival rate of 93%, while in China, the annual increase was only 3.7% and the 5-year survival rate was 69.2%(Yao et al., 2021). In 2018, there were 1.3 million new cases of prostate cancer worldwide, and its morbidity and mortality ranked second and fifth among male malignancies, respectively.However, to date no serum or urine biomarker or biomarker panel meets the requirements for highly sensitive and specific detection of PC and differentiation between indolent and significant PC. We here explore the prospects of metabolomics to improve prostate cancer detection, patient stratification and treatment monitoring. 1.2. PC classification and grading The prostate gland is a walnut-sized gland located between the bladder neck and the external urethral sphincter. There are four main zones in the prostate gland: the peripheral zone (posteriorly), the fibromuscular zone (anteriorly), the central zone (centrally) and the transitional zone (surrounding the urethra). The anatomy of the prostate gland is shown in Fig. 1 (Adapted from: Bhavsar et al., 2014).Prostate cancer does not occur uniformly throughout the prostate. Although cancers of the prostate often are multifocal, from 80% to 85% arise from the peripheral zone, 10% to 15% arise from the transition zone, and 5% to 10% arise from the central zone (Buyyounouski et al., 2017). The biopsy Gleason grading system is the most important prognostic marker for prostate cancer. The higher the Gleason score, the higher the malignant degree of prostate cancer. The TNM staging system proposed by AJCC is a widely used independent index that can reflect the progression and prognosis of prostate cancer. Table 2 shows the definitions for clinical and pathological T, N, and M classifications (Buyyounouski et al., 2017). Radical prostatectomy (RP) has become the most effective method for the treatment of localized prostate cancer and some high-risk prostate cancer. RP is used when the cancer is believed to be confined to the prostate gland. During the procedure, the prostate gland and some tissue around the gland, including the seminal vesicles, are removed. Transurethral resection of the prostate, or TURP, which also involves removal of part of the prostate gland, is an approach performed through the penis with an endoscope (small, flexible tube with a light and a lens on the end). This procedure doesn't cure prostate cancer but can remove the obstruction while the doctors plan for definitive treatment. Laparoscopic surgery, done manually or by robot, is another method of removal of the prostate gland. Shortcomings in comprehensive medical check-ups in low- and middle-income countries lead to delayed detection of PC and are causative of high numbers of advanced PC cases at first diagnosis. The performance of available biomarkers is still insufficient and limited applicability, including logistical and financial burdens, impedes comprehensive implementation into health care systems. There is broad agreement on the need of new biomarkers to improve (i) early detection of PC, (ii) risk stratification, (iii) prognosis, and (iv) treatment monitoring. 2. PC Biomarkers Serum prostate specific antigen (PSA) level and digital rectal examination (DRE) constitute the major screening tests for prostate cancer (PC) diagnosis, while the transrectal ultrasound-guided prostate biopsy provides the final confirmation of cancer presence (Velonas et al., 2013). PSA level has been extensively used as a biomarker to detect PC. Nevertheless, due to prostate physiology, PSA testing results in a large frequency of false positives leading to numerous men each year undergoing unnecessary prostate biopsy procedures (Vickers et al., 2008; Link et al., 2004; McDunn et al., 2013; Roberts et al., 2011; Djavan et al., 2000). Hence, a non-invasive, cost-effective, efficient, and reasonably accurate test for early identification of PC is urgently needed. Compared with serum, urine is easier to obtain and handle, needs less sample preparation, and has higher amounts of metabolites and lower protein content (Rigau et al., 2013; Wilkosz et al., 2011; Zhang et al., 2013). Therefore, in attempt to solve this diagnostic dilemma, many previous studies have focused on urinary metabolomic profile, to identify the predictive biomarkers for PC (Chistiakov et al., 2018). Yang and colleagues conducted a study searching for urine metabolite biomarkers for the detection of PC. They found twenty differentially expressed urine metabolites in a cohort of 50 prostate cancer patients compared to non-cancerous individuals (Yang et al., 2021; Gordetsky et al., 2016; Nam et al., 2018; Di Meo et al., 2017). The combination of solely three metabolites, representing alterations in Glycine, Serine, and Threonine metabolism (KEGG database pathway), was able to identify PC patients with 77% accuracy at 80% sensitivity and 64% specificity. Furthermore, those metabolites could separate significant PC (Gleason score ≥ 7) from indolent PC (GS 6), which confirms urine metabolomics as a promising diagnostic tool in PC. However, to date, no single urine biomarker/biomarker panel meets the requirements for highly sensitive, and specific detection of PC. Therefore, the search for PC-specific biomarkers still is an active area of research. 3. PC prevalence is not equal in different populations There is a racial difference in incidence rate and interpatient heterogeneity of prostate cancer. By contrast, Asian men have lower disease prevalence compared with Asian-American or American PC cohorts. Despite lower PC incidence, the Asian populations have a higher prevalence of advanced disease, probably due to the lack of availability of more sensitive diagnostic tools (Ateeq et al., 2016). Therefore, it’s necessary to define the urine metabolome in an Asian population. 4. Aims of the study − Exploration of novel biomarkers for the detection of PC in an Asian cohort. − Are urinary metabolomics suitable to develop new PC biomarkers? − What are the advantages of urine biomarkers? − How to identify novel biomarkers in the urine and to investigate the possible functions and roles of potential biomarkers in PC

Metabolism-Based Therapeutic Strategies Targeting Cancer Stem Cells

Cancer heterogeneity constitutes the major source of disease progression and therapy failure. Tumors comprise functionally diverse subpopulations, with cancer stem cells (CSCs) as the source of this heterogeneity. Since these cells bear in vivo tumorigenicity and metastatic potential, survive chemotherapy and drive relapse, its elimination may be the only way to achieve long-term survival in patients. Thanks to the great advances in the field over the last few years, we know now that cellular metabolism and stemness are highly intertwined in normal development and cancer. Indeed, CSCs show distinct metabolic features as compared with their more differentiated progenies, though their dominant metabolic phenotype varies across tumor entities, patients and even subclones within a tumor. Following initial works focused on glucose metabolism, current studies have unveiled particularities of CSC metabolism in terms of redox state, lipid metabolism and use of alternative fuels, such as amino acids or ketone bodies. In this review, we describe the different metabolic phenotypes attributed to CSCs with special focus on metabolism-based therapeutic strategies tested in preclinical and clinical settings