Endometrial cancer risk stratification using MRI radiomics: corroborating with choline metabolism.

BACKGROUND AND PURPOSE: Radiomics offers little explainability. This study aims to develop a radiomics model (Rad-Score) using diffusion-weighted imaging (DWI) to predict high-risk patients for nodal metastasis or recurrence in endometrial cancer (EC) and corroborate with choline metabolism. MATERIALS AND METHODS: From August 2015 to July 2018, 356 EC patients were enrolled. Rad-Score was developed using LASSO regression in a training cohort (n = 287) and validated in an independent test cohort (n = 69). MR spectroscopy (MRS) was also used in 230 patients. Nuclear MRS measured choline metabolites in 70 tissue samples. The performance was compared against European Society for Medical Oncology (ESMO) risk groups. A P < .05 denoted statistical significance. RESULTS: Rad-Score achieved 71.1% accuracy in the training and 71.0% in the testing cohorts. Incorporating clinical parameters of age, tumor type, size, and grade, Rad-Signature reached accuracies of 73.2% in training and 75.4% in testing cohorts, closely matching the performance to the post-operatively based ESMO's 70.7% and 78.3%. Rad-Score was significantly associated with increased total choline levels on MRS (P = .034) and tissue levels (P = .019). CONCLUSIONS: Development of a preoperative radiomics risk score, comparable to ESMO clinical standard and associated with altered choline metabolism, shows translational relevance for radiomics in high-risk EC patients. TRIAL REGISTRATION: This study was registered in ClinicalTrials.gov on 2015-08-01 with Identifier NCT02528864.

Do low skeletal muscle bulk and disturbed body fat mass impact tumor recurrence in stage I/II HCC undergoing surgery? An observational cohort study.

INTRODUCTION: The influence of deranged body composition on stage I/II HCC after surgery remains undetermined. The current study aimed to investigate the impact of low skeletal muscle bulk and disturbed body fat mass on the recurrence outcome of stage I/II HCC patients undergoing liver resection. The associated metabolomic alterations were also assessed. METHODS: From 2012 to 2021, stage I and II HCC patients who underwent liver resection at our institute were retrospectively reviewed. Their preoperative body composition including skeletal muscle mass and body fat volume was measured by computed tomography (CT). The recurrence outcome was recorded and analyzed. The preoperative serum was collected and subjected to metabolomic analysis. RESULTS: A total of 450 stage I and II HCC patients were included in the current study. Among them, 76% were male and around 60% had HBV infection. After stratified by normal cutoff values obtained from a healthy cohort, 6.4% of stage I/II HCC patients were found to have a low psoas muscle index (PMI), 17.8% a high subcutaneous adipose tissue (SAT) index, and 27.8% a high visceral adipose tissue (VAT) index. Cox regression multivariate analysis further demonstrated that low PMI and high SAT index were independent prognostic factors for time-to-recurrence (TTR) after surgery. Metabolomic analysis discovered that free fatty acid ß-oxidation was enhanced in with low PMI or high SAT index. CONCLUSION: The current study demonstrated that reduced psoas muscle mass may impair while elevated SAT may prolong the TTR of stage I/II HCC patients undergoing liver resections. VAT, on the other hand, was not associated with recurrence outcome after surgery. Further studies are warranted to validate our findings.

Antiviral therapy reduces hepatocellular carcinoma through suppressing hepatitis B virus replication may improve ER stress, mitochondrial and metabolic dysfunctions and decrease p62 in hybridized mice with single HBV transgene and miR-122.

Hepatitis B virus (HBV) hijacks autophagy for its replication. Nucleos(t)ide analogs (NUCs) treatment suppressed HBV replication and reduced hepatocellular carcinoma (HCC) incidence. However, the use of NUCs in chronic hepatitis B (CHB) patients with normal or minimally elevated serum alanine aminotransferase (ALT) levels is still debated. Animal models are crucial for studying the unanswered issue and evaluating new therapies. MicroRNA-122 (miR-122), which regulates fatty acid and cholesterol metabolism, is downregulated during hepatitis and HCC progression. The reciprocal inhibition of miR-122 with HBV highlights its role in HCC development as a tumor suppressor. By crossbreeding HBV-transgenic mice with miR-122 knockout mice, we generated a hybrid mouse model with a high incidence of HCC up to 89% and normal ALT levels before HCC. The model exhibited early-onset hepatic steatosis, progressive liver fibrosis, and impaired late-phase autophagy. Metabolomics and microarray analysis identified metabolic signatures, including dysregulation of lipid metabolism, inflammation, genomic instability, the Warburg effect, reduced TCA cycle flux, energy deficiency, and impaired free radical scavenging. Antiviral treatment reduced HCC incidence in hybrid mice by approximately 30-35% compared to untreated mice. This effect was linked to the activation of ER stress-responsive transcription factor ATF4, clearance of autophagosome cargo p62, and suppression of the CHOP-mediated apoptosis pathway. In summary, this study suggests that despite minimal ALT elevation, HBV replication can lead to liver injury. Endoplasmic reticulum stress, reduced miR-122 levels, mitochondrial and metabolic dysfunctions, blocking protective autophagy resulting in p62 accumulation, apoptosis, fibrosis, and HCC. Antiviral may improve the above-mentioned pathogenesis through HBV suppression.

Lack of incremental value of three-dimensional measurement in assessing invasiveness for lung cancer.

OBJECTIVES: The aim of this study was to evaluate the performance of consolidation-to-tumour ratio (CTR) and the radiomic models in two- and three-dimensional modalities for assessing radiological invasiveness in early-stage lung adenocarcinoma. METHODS: A retrospective analysis was conducted on patients with early-stage lung adenocarcinoma from Guangdong Provincial People's Hospital and Shenzhen People's Hospital. Manual delineation of pulmonary nodules along the boundary was performed on cross-sectional images to extract radiomic features. Clinicopathological characteristics and radiomic signatures were identified in both cohorts. CTR and radiomic score for every patient were calculated. The performance of CTR and radiomic models were tested and validated in the respective cohorts. RESULTS: A total of 818 patients from Guangdong Provincial People's Hospital were included in the primary cohort, while 474 patients from Shenzhen People's Hospital constituted an independent validation cohort. Both CTR and radiomic score were identified as independent factors for predicting pathological invasiveness. CTR in two- and three-dimensional modalities exhibited comparable results with areas under the receiver operating characteristic curves and were demonstrated in the validation cohort (area under the curve: 0.807 vs 0.826, P = 0.059) Furthermore, both CTR in two- and three-dimensional modalities was able to stratify patients with significant relapse-free survival (P < 0.000 vs P < 0.000) and overall survival (P = 0.003 vs P = 0.001). The radiomic models in two- and three-dimensional modalities demonstrated favourable discrimination and calibration in independent cohorts (P = 0.189). CONCLUSIONS: Three-dimensional measurement provides no additional clinical benefit compared to two-dimensional.

PAICS ubiquitination recruits UBAP2 to trigger phase separation for purinosome assembly.

Purinosomes serve as metabolons to enhance de novo purine synthesis (DNPS) efficiency through compartmentalizing DNPS enzymes during stressed conditions. However, the mechanism underpinning purinosome assembly and its pathophysiological functions remains elusive. Here, we show that K6-polyubiquitination of the DNPS enzyme phosphoribosylaminoimidazole carboxylase and phosphoribosylaminoimidazolesuccinocarboxamide synthetase (PAICS) by cullin-5/ankyrin repeat and SOCS box containing 11 (Cul5/ASB11)-based ubiquitin ligase plays a driving role in purinosome assembly. Upon several purinosome-inducing cues, ASB11 is upregulated by relieving the H3K9me3/HP1α-mediated transcriptional silencing, thus stimulating PAICS polyubiquitination. The polyubiquitinated PAICS recruits ubiquitin-associated protein 2 (UBAP2), a ubiquitin-binding protein with multiple stretches of intrinsically disordered regions, thereby inducing phase separation to trigger purinosome assembly for enhancing DNPS pathway flux. In human melanoma, ASB11 is highly expressed to facilitate a constitutive purinosome formation to which melanoma cells are addicted for supporting their proliferation, viability, and tumorigenesis in a xenograft model. Our study identifies a driving mechanism for purinosome assembly in response to cellular stresses and uncovers the impact of purinosome formation on human malignancies.

Exploring the aging process of cognitively healthy adults by analyzing cerebrospinal fluid metabolomics using liquid chromatography-tandem mass spectrometry.

BACKGROUND: During biological aging, significant metabolic dysregulation in the central nervous system may lead to cognitive decline and neurodegeneration. However, the metabolomics of the aging process in cerebrospinal fluid (CSF) has not been thoroughly explored. METHODS: In this cohort study of CSF metabolomics using liquid chromatography-mass spectrometry (LC-MS), fasting CSF samples collected from 92 cognitively unimpaired adults aged 20-87 years without obesity or diabetes were analyzed. RESULTS: We identified 37 metabolites in these CSF samples with significant positive correlations with aging, including cysteine, pantothenic acid, 5-hydroxyindoleacetic acid (5-HIAA), aspartic acid, and glutamate; and two metabolites with negative correlations, asparagine and glycerophosphocholine. The combined alterations of asparagine, cysteine, glycerophosphocholine, pantothenic acid, sucrose, and 5-HIAA showed a superior correlation with aging (AUC = 0.982). These age-correlated changes in CSF metabolites might reflect blood-brain barrier breakdown, neuroinflammation, and mitochondrial dysfunction in the aging brain. We also found sex differences in CSF metabolites with higher levels of taurine and 5-HIAA in women using propensity-matched comparison. CONCLUSIONS: Our LC-MS metabolomics of the aging process in a Taiwanese population revealed several significantly altered CSF metabolites during aging and between the sexes. These metabolic alterations in CSF might provide clues for healthy brain aging and deserve further exploration.

Laparoscopic liver resection is associated with less significant muscle loss than the conventional open approach.

BACKGROUND: Laparoscopic liver resections (LLR) have been shown a treatment approach comparable to open liver resections (OLR) in hepatocellular carcinoma (HCC). However, the influence of procedural type on body composition has not been investigated. The aim of the current study was to compare the degree of skeletal muscle loss between LLR and OLR for HCC. METHODS: By using propensity score matching (PSM) analysis, 64 pairs of patients were enrolled. The change of psoas muscle index (PMI) after the operation was compared between the matched patients in the LLR and OLR. Risk factors for significant muscle loss (defined as change in PMI > mean change minus one standard deviation) were further investigated by multivariate analysis. RESULTS: Among patients enrolled, there was no significant difference in baseline characteristics between the two groups. The PMI was significantly decreased in the OLR group (P = 0.003). There were also more patients in the OLR group who developed significant muscle loss after the operations (P = 0.008). Multivariate analysis revealed OLR (P = 0.023), type 2 diabetes mellitus, indocyanine green retention rate at 15 min (ICG-15) > 10%, and cancer stage ≧ 3 were independent risk factors for significant muscle loss. In addition, significant muscle loss was associated with early HCC recurrence (P = 0.006). Metabolomic analysis demonstrated that the urea cycle may be decreased in patients with significant muscle loss. CONCLUSION: LLR for HCC was associated with less significant muscle loss than OLR. Since significant muscle loss was a predictive factor for early tumor recurrence and associated with impaired liver metabolism, LLR may subsequently result in a more favorable outcome.

Metabolomic Signature of Diabetic Kidney Disease in Cerebrospinal Fluid and Plasma of Patients with Type 2 Diabetes Using Liquid Chromatography-Mass Spectrometry.

Diabetic kidney disease (DKD) is the major cause of end stage renal disease in patients with type 2 diabetes mellitus (T2DM). The subtle metabolic changes in plasma and cerebrospinal fluid (CSF) might precede the development of DKD by years. In this longitudinal study, CSF and plasma samples were collected from 28 patients with T2DM and 25 controls, during spinal anesthesia for elective surgery in 2017. These samples were analyzed using liquid chromatography-mass spectrometry (LC-MS) in 2017, and the results were correlated with current DKD in 2017, and the development of new-onset DKD, in 2021. Comparing patients with T2DM having new-onset DKD with those without DKD, revealed significantly increased CSF tryptophan and plasma uric acid levels, whereas phosphatidylcholine 36:4 was lower. The altered metabolites in the current DKD cases were uric acid and paraxanthine in the CSF and uric acid, L-acetylcarnitine, bilirubin, and phosphatidylethanolamine 38:4 in the plasma. These metabolic alterations suggest the defective mitochondrial fatty acid oxidation and purine and phospholipid metabolism in patients with DKD. A correlation analysis found CSF uric acid had an independent positive association with the urine albumin-to-creatinine ratio. In conclusion, these identified CSF and plasma biomarkers of DKD in diabetic patients, might be valuable for monitoring the DKD progression.

Derangements and Reversibility of Energy Metabolism in Failing Hearts Resulting from Volume Overload: Transcriptomics and Metabolomics Analyses.

Derangements in cardiac energy metabolism have been shown to contribute to the development of heart failure (HF). This study combined transcriptomics and metabolomics analyses to characterize the changes and reversibility of cardiac energetics in a rat model of cardiac volume overload (VO) with the creation and subsequent closure of aortocaval fistula. Male Sprague-Dawley rats subjected to an aortocaval fistula surgery for 8 and 16 weeks exhibited characteristics of compensated hypertrophy (CH) and HF, respectively, in echocardiographic and hemodynamic studies. Glycolysis was downregulated and directed to the hexosamine biosynthetic pathway (HBP) and O-linked-N-acetylglucosaminylation in the CH phase and was further suppressed during progression to HF. Derangements in fatty acid oxidation were not prominent until the development of HF, as indicated by the accumulation of acylcarnitines. The gene expression and intermediates of the tricarboxylic acid cycle were not significantly altered in this model. Correction of VO largely reversed the differential expression of genes involved in glycolysis, HBP, and fatty acid oxidation in CH but not in HF. Delayed correction of VO in HF resulted in incomplete recovery of defective glycolysis and fatty acid oxidation. These findings may provide insight into the development of innovative strategies to prevent or reverse metabolic derangements in VO-induced HF.

Probing Folate-Responsive and Stage-Sensitive Metabolomics and Transcriptional Co-Expression Network Markers to Predict Prognosis of Non-Small Cell Lung Cancer Patients.

Tumour metabolomics and transcriptomics co-expression network as related to biological folate alteration and cancer malignancy remains unexplored in human non-small cell lung cancers (NSCLC). To probe the diagnostic biomarkers, tumour and pair lung tissue samples (n = 56) from 97 NSCLC patients were profiled for ultra-performance liquid chromatography tandem mass spectrometry (UPLC/MS/MS)-analysed metabolomics, targeted transcriptionomics, and clinical folate traits. Weighted Gene Co-expression Network Analysis (WGCNA) was performed. Tumour lactate was identified as the top VIP marker to predict advance NSCLC (AUC = 0.765, Sig = 0.017, CI 0.58-0.95). Low folate (LF)-tumours vs. adjacent lungs displayed higher glycolytic index of lactate and glutamine-associated amino acids in enriched biological pathways of amino sugar and glutathione metabolism specific to advance NSCLCs. WGCNA classified the green module for hub serine-navigated glutamine metabolites inversely associated with tumour and RBC folate, which module metabolites co-expressed with a predominant up-regulation of LF-responsive metabolic genes in glucose transport (GLUT1), de no serine synthesis (PHGDH, PSPH, and PSAT1), folate cycle (SHMT1/2 and PCFR), and down-regulation in glutaminolysis (SLC1A5, SLC7A5, GLS, and GLUD1). The LF-responsive WGCNA markers predicted poor survival rates in lung cancer patients, which could aid in optimizing folate intervention for better prognosis of NSCLCs susceptible to folate malnutrition.

1H NMR metabolomic profiling of human cerebrospinal fluid in aging process.

The molecular process of biological aging might be accompanied by significant metabolic derangement, especially in the central nervous system (CNS), since the brain has an enormous energy demand. However, the metabolic signature of the aging process in cerebrospinal fluid (CSF) has not been thoroughly investigated, especially in the Asian population. In this prospective cohort study on CSF metabolomics using proton nuclear magnetic resonance (NMR) spectroscopy, fasting CSF samples from 75 cognitively unimpaired patients aged 20-92 years without diabetes or obesity, undergoing spinal anesthesia for elective surgery were analyzed. Several metabolites in CSF samples were identified as having a significant association with the aging process in cerebral circulation; among the metabolites, the levels of alanine, citrate, creatinine, lactate, leucine, tyrosine, and valine significantly increased in old patients compared to those in young patients. The combined CSF metabolite alterations in citrate, lactate, leucine, tyrosine, and valine had a superior correlation with the aging process in all age groups. In conclusion, our pilot study of aging CSF metabolomics in the Taiwanese population presents significantly altered CSF metabolites with potential relevance to the aging process. These metabolic alterations in CSF samples might imply increasing anaerobic glycolysis, mitochondrial dysfunction, and decreasing glucose utilization in cerebral circulation in aged patients.

Targeting KDM4B that coactivates c-Myc-regulated metabolism to suppress tumor growth in castration-resistant prostate cancer.

Rationale: The progression of prostate cancer (PCa) to castration-resistant PCa (CRPC) despite continuous androgen deprivation therapy is a major clinical challenge. Over 90% of patients with CRPC exhibit sustained androgen receptor (AR) signaling. KDM4B that removes the repressive mark H3K9me3/2 is a transcriptional activator of AR and has been implicated in the development of CRPC. However, the mechanisms of KDM4B involvement in CRPC remain largely unknown. Here, we sought to demonstrate the molecular pathway mediated by KDM4B in CRPC and to provide proof-of-concept evidence that KDM4B is a potential CRPC target. Methods: CRPC cells (C4-2B or CWR22Rv1) depleted with KDM4B followed by cell proliferation (in vitro and xenograft), microarray, qRT-PCR, Seahorse Flux, and metabolomic analyses were employed to identify the expression and metabolic profiles mediated by KDM4B. Immunoprecipitation was used to determine the KDM4B-c-Myc interaction region. Reporter activity assay and ChIP analysis were used to characterize the KDM4B-c-Myc complex-mediated mechanistic actions. The clinical relevance between KDM4B and c-Myc was determined using UCSC Xena analysis and immunohistochemistry. Results: We showed that KDM4B knockdown impaired CRPC proliferation, switched Warburg to OXPHOS metabolism, and suppressed gene expressions including those targeted by c-Myc. We further demonstrated that KDM4B physically interacted with c-Myc and they were co-recruited to the c-Myc-binding sequence on the promoters of metabolic genes (LDHA, ENO1, and PFK). Importantly, KDM4B and c-Myc synergistically promoted the transactivation of the LDHA promoter in a demethylase-dependent manner. We also provided evidence that KDM4B and c-Myc are co-expressed in PCa tissue and that high expression of both is associated with worse clinical outcome. Conclusions: KDM4B partners with c-Myc and serves as a coactivator of c-Myc to directly enhance c-Myc-mediated metabolism, hence promoting CRPC progression. Targeting KDM4B is thus an alternative therapeutic strategy for advanced prostate cancers driven by c-Myc and AR.

Monitoring Early Glycolytic Flux Alterations Following Radiotherapy in Cancer and Immune Cells: Hyperpolarized Carbon-13 Magnetic Resonance Imaging Study.

Alterations in metabolism following radiotherapy affect therapeutic efficacy, although the mechanism underlying such alterations is unclear. A new imaging technique-named dynamic nuclear polarization (DNP) carbon-13 magnetic resonance imaging (MRI)-probes the glycolytic flux in a real-time, dynamic manner. The [1-13C]pyruvate is transported by the monocarboxylate transporter (MCT) into cells and converted into [1-13C]lactate by lactate dehydrogenase (LDH). To capture the early glycolytic alterations in the irradiated cancer and immune cells, we designed a preliminary DNP 13C-MRI study by using hyperpolarized [1-13C]pyruvate to study human FaDu squamous carcinoma cells, HMC3 microglial cells, and THP-1 monocytes before and after irradiation. The pyruvate-to-lactate conversion rate (kPL [Pyr.]) calculated by kinetic modeling was used to evaluate the metabolic alterations. Western blotting was performed to assess the expressions of LDHA, LDHB, MCT1, and MCT4 proteins. Following irradiation, the pyruvate-to-lactate conversion rates on DNP 13C-MRI were significantly decreased in the FaDu and the HMC3 cells but increased in the THP-1 cells. Western blot analysis confirmed the similar trends in LDHA and LDHB expression levels. In conclusion, DNP 13C-MRI non-invasively captured the different glycolytic alterations among cancer and immune systems in response to irradiation, implying its potential for clinical use in the future.

Prognostic Significance of O-GlcNAc and PKM2 in Hormone Receptor-Positive and HER2-Nonenriched Breast Cancer.

Predictive metabolic biomarkers for the recurrent luminal breast cancer (BC) with hormone receptor (HR)-positive and human epidermal growth factor receptor type 2 (HER2)-negative are lacking. High levels of O-GlcNAcylation (O-GlcNAc) and pyruvate kinase isoenzyme M2 (PKM2) are associated with malignancy in BC; however, the association with the recurrence risk remains unclear. We first conduct survival analysis by using the METABRIC dataset to assess the correlation of PKM2 expression with BC clinical outcomes. Next, patients with HR+/HER2- luminal BC were recruited for PKM2/O-GlcNAc testing. Logistic regression and receiver operating characteristic curve analysis were performed to evaluate the 10-year DFS predicted outcome. Survival analysis of the METABRIC dataset revealed that high expression of PKM2 was significantly associated with worse overall survival in luminal BC. The high expression of O-GlcNAc or PKM2 was a significant independent marker for poor 10-year DFS using immunohistochemical analysis. The PKM2 or O-GlcNAc status was a significant predictor of DFS, with the combination of PKM2-O-GlcNAc status and T stage greatly enhancing the predictive outcome potential. In summary, O-GlcNAc, PKM2, and T stage serve as good prognostic discriminators in HR+/HER2- luminal BC.

Arginine starvation elicits chromatin leakage and cGAS-STING activation via epigenetic silencing of metabolic and DNA-repair genes.

Rationale: One of the most common metabolic defects in cancers is the deficiency in arginine synthesis, which has been exploited therapeutically. Yet, challenges remain, and the mechanisms of arginine-starvation induced killing are largely unclear. Here, we sought to demonstrate the underlying mechanisms by which arginine starvation-induced cell death and to develop a dietary arginine-restriction xenograft model to study the in vivo effects. Methods: Multiple castration-resistant prostate cancer cell lines were treated with arginine starvation followed by comprehensive analysis of microarray, RNA-seq and ChIP-seq were to identify the molecular and epigenetic pathways affected by arginine starvation. Metabolomics and Seahorse Flux analyses were used to determine the metabolic profiles. A dietary arginine-restriction xenograft mouse model was developed to assess the effects of arginine starvation on tumor growth and inflammatory responses. Results: We showed that arginine starvation coordinately and epigenetically suppressed gene expressions, including those involved in oxidative phosphorylation and DNA repair, resulting in DNA damage, chromatin-leakage and cGAS-STING activation, accompanied by the upregulation of type I interferon response. We further demonstrated that arginine starvation-caused depletion of α-ketoglutarate and inactivation of histone demethylases are the underlying causes of epigenetic silencing. Significantly, our dietary arginine-restriction model showed that arginine starvation suppressed prostate cancer growth in vivo, with evidence of enhanced interferon responses and recruitment of immune cells. Conclusions: Arginine-starvation induces tumor cell killing by metabolite depletion and epigenetic silencing of metabolic genes, leading to DNA damage and chromatin leakage. The resulting cGAS-STING activation may further enhance these killing effects.

c-Src facilitates tumorigenesis by phosphorylating and activating G6PD.

Glucose-6-phosphate dehydrogenase (G6PD) is the first and rate-limiting enzyme in pentose phosphate pathway (PPP), excessive activation of which has been considered to be involved in tumorigenesis. Here, we show that tyrosine kinase c-Src interacts with and phosphorylates G6PD at Tyr 112. This phosphorylation enhances catalytic activity of G6PD by dramatically decreasing its Km value and increasing its Kcat value for substrate glucose-6-phosphate. Activated G6PD therefore augments the PPP flux for NADPH and ribose-5-phosphate production which is required for detoxification of intracellular reactive oxygen species (ROS) and biosynthesis of cancer cells, and eventually contributes to tumorigenesis. Consistently, c-Src activation is closely correlated with tyrosine phosphorylation and activity of G6PD in clinical colorectal cancer samples. We thus uncover another aspect of c-Src in promoting cell proliferation and tumorigenesis, deepening our understanding of c-Src as a proto-oncogene.

Gene co-expression modules integrated with immunoscore predicts survival of non-small cell lung cancer.

BACKGROUND: This study aimed to deconvolve the levels of infiltrating immune cells in non-small cell lung cancer (NSCLC) and to identify specific gene co-expression modules associated with prognosis of NSCLC. MATERIALS AND METHODS: CIBERSORT algorithm was employed to infer the relative abundance of 22 immune cell subtypes in 1751 NSCLC subjects. The patterns of immune infiltration were identified for NSCLC with different clinical and genomic features and were used to construct an immunoscore by LASSO regression associated with NSCLC survival. Weighted gene co-expression network analysis (WGCNA) was employed to identify specific modules related to immunoscore and NSCLC survival. An integrated prognostic model was constructed with immunoscore combined with the available clinical variables and the selected gene modules to predict the prognosis of NSCLC. RESULTS: We found distinct immune infiltration patterns for NSCLC with different genotype. EGFR-mutant NSCLC was characterized by enriched resting memory CD4+ T cell. An immunoscore was established based on the infiltration abundance of 17 selected immune cell subtypes. Patients with a low immunoscore had a prolonged survival and higher abundance of CD4+ T cell, resting dendritic cells and resting mast cells. The WGCNA analysis identified the gene modules significantly associated with immunoscore and the prognosis of NSCLC. The immunoscore was further incorporated with clinical parameters and selected gene modules to fit a predictive model which stratified patients into subgroups with significantly different survival. CONCLUSION: The distinct immune profiles are associated with differential overall survival of NSCLC and the integrated model can robustly predict the prognosis of NSCLC.

Plasma phenylalanine and glutamine concentrations correlate with subsequent hepatocellular carcinoma occurrence in liver cirrhosis patients: an exploratory study.

Aberrant metabolisms have been hypothesized to precede the occurrence of hepatocellular carcinoma (HCC), therefore, we investigated biomarkers associated with subsequent HCC in peripheral bloods using metabolomic technologies. A cohort of 475 HCC-naïve liver cirrhotic patients were recruited and prospectively followed. A total of 39 patients developed HCC in the follow-up period. Baseline plasma metabolites were explored using untargeted nuclear magnetic resonance. Candidates were then quantified by ultra-performance liquid chromatography. A series of univairiate and multivariate analysis showed that Phenylalanine (Phe) and Glutamine (Gln) levels are associated with time to HCC, independent of viological etiologies and age. A HCC risk score R was then constructed using the polynomial combination of age, Phe and Gln in the units of micromolar (µM):[Formula: see text] R correlates with the time to HCC significantly (Hazard ratio [HR] = 2.368, 95% confidence interval [CI] 1.760-3.187, P < 0.001). An additional cross-sectional analysis showed that Phe and Gln concentrations both correlates with HCC occurrence in the next 3 years (area under the receiver operating characteristic curve [AUC] = 0.607 and 0.629, P = 0.033 and 0.010 respectively). In conclusion, phenylalanine and glutamine concentrations in the peripheral blood correlate with subsequent HCC.

c-Src Promotes Tumorigenesis and Tumor Progression by Activating PFKFB3.

Reprogramming of glucose metabolism is a key event in tumorigenesis and progression. Here, we show that active c-Src stimulates glycolysis by phosphorylating (Tyr194) and activating PFKFB3, a key enzyme that boosts glycolysis by producing fructose-2,6-bisphosphate and activating PFK1. Increased glycolysis intermediates replenish non-oxidative pentose phosphate pathway (PPP) and serine pathway for biosynthesis of cancer cells. PFKFB3 knockout (KO) cells and their counterpart reconstituted with PFKFB3-Y194F show comparably impaired abilities for proliferation, migration, and xenograft formation. Furthermore, PFKFB3-Y194F knockin mice show impaired glycolysis and, mating of these mice with APCmin/+ mice attenuates spontaneous colon cancer formation in APCmin/+ mice. In summary, we identify a specific mechanism by which c-Src mediates glucose metabolism to meet cancer cells' requirements for maximal biosynthesis and proliferation. The PFKFB3-Tyr194 phosphorylation level highly correlates with c-Src activity in clinical tumor samples, indicating its potential as an evaluation for tumor prognosis.

Metabolomic biomarkers in cervicovaginal fluid for detecting endometrial cancer through nuclear magnetic resonance spectroscopy.

INTRODUCTION: Endometrial cancer (EC) is one of the most common gynecologic neoplasms in developed countries but lacks screening biomarkers. OBJECTIVES: We aim to identify and validate metabolomic biomarkers in cervicovaginal fluid (CVF) for detecting EC through nuclear magnetic resonance (NMR) spectroscopy. METHODS: We screened 100 women with suspicion of EC and benign gynecological conditions, and randomized them into the training and independent testing datasets using a 5:1 study design. CVF samples were analyzed using a 600-MHz NMR spectrometer equipped with a cryoprobe. Four machine learning algorithms-support vector machine (SVM), partial least squares discriminant analysis (PLS-DA), random forest (RF), and logistic regression (LR), were applied to develop the model for identifying metabolomic biomarkers in cervicovaginal fluid for EC detection. RESULTS: A total of 54 women were eligible for the final analysis, with 21 EC and 33 non-EC. From 29 identified metabolites in cervicovaginal fluid samples, the top-ranking metabolites chosen through SVM, RF and PLS-DA which existed in independent metabolic pathways, i.e. phosphocholine, malate, and asparagine, were selected to build the prediction model. The SVM, PLS-DA, RF, and LR methods all yielded area under the curve values between 0.88 and 0.92 in the training dataset. In the testing dataset, the SVM and RF methods yielded the highest accuracy of 0.78 and the specificity of 0.75 and 0.80, respectively. CONCLUSION: Phosphocholine, asparagine, and malate from cervicovaginal fluid, which were identified and independently validated through models built using machine learning algorithms, are promising metabolomic biomarkers for the detection of EC using NMR spectroscopy.