Exploring novel lead scaffolds for SGLT2 inhibitors: Insights from machine learning and molecular dynamics simulations.

Sodium-glucose cotransporter 2 (SGLT2) plays a pivotal role in mediating glucose reabsorption within the renal filtrate, representing a well-known target in type 2 diabetes and heart failure. Recent emphasis has been directed toward designing SGLT2 inhibitors, with C-glycoside inhibitors emerging as front-runners. The architecture of SGLT2 has been successfully resolved using cryo-electron microscopy. However, comprehension of the pharmacophores within the binding site of SGLT2 remains unclear. Here, we use machine learning and molecular dynamics simulations on SGLT2 bound with its inhibitors in preclinical or clinical development to shed light on this issue. Our dataset comprises 1240 SGLT2 inhibitors amalgamated from diverse sources, forming the basis for constructing machine learning models. SHapley Additive exPlanation (SHAP) elucidates the crucial fragments that contribute to inhibitor activity, specifically Morgan_3, 162, 310, 325, 366, 470, 597, 714, 926, and 975. Furthermore, the computed binding free energies and per-residue contributions for SGLT2-inhibitor complexes unveil crucial fragments of inhibitors that interact with residues Asn-75, His-80, Val-95, Phe-98, Val-157, Leu-274, and Phe-453 in the binding site of SGLT2. This comprehensive investigation enhances understanding of the binding mechanism for SGLT2 inhibitors, providing a robust framework for evaluating and discovering novel lead scaffolds within this domain.

Insight into the Interaction Mechanism of Vitamin D against Metabolic Syndrome: A Meta-Analysis and In Silico Study.

As a dietary supplement or functional food additive, vitamin D (VD) deficiency may impact extra-skeletal functions associated with metabolic syndrome (MetS) risk factors. However, the precise effects and mechanisms of VD supplementation on dyslipidemia and insulin resistance in MetS subjects remain controversial. Here, we investigate potential therapeutic targets, pathways and mechanisms of VD against MetS through a comprehensive strategy including meta-analysis, network pharmacology analysis, molecular docking, dynamics simulations, and quantum chemical calculations. Our results reveal that VD supplementation significantly reduces triglyceride levels, fasting glucose, and insulin concentrations in subjects, thereby improving insulin homeostasis to some extent. We theoretically identify 14 core MetS-associated targets. Notably, VD exhibits substantial interactions with three targets (PPARγ, FABP4, and HMGCR) in the PPAR signaling pathway, indicating that VD can modulate this pathway. Van der Waals forces predominantly stabilize the complexes formed between VD and the three targets. Nonetheless, to provide valuable insights for personalized MetS management, further research is necessary to confirm our findings, emphasizing the importance of exploring genetic variability in VD response. In conclusion, our study contributes insights into the mechanisms of VD in preventing and treating MetS through dietary supplementation, promoting the development of VD-based functional foods or nutritious diets.

Depiction of neuroendocrine features associated with immunotherapy response using a novel one-class predictor in lung adenocarcinoma.

BACKGROUND: Tumours with no evidence of neuroendocrine transformation histologically but harbouring neuroendocrine features are collectively referred to as non-small cell lung cancer (NSCLC) with neuroendocrine differentiation (NED). Investigating the mechanisms underlying NED is conducive to designing appropriate treatment options for NSCLC patients. METHODS: In the present study, we integrated multiple lung cancer datasets to identify neuroendocrine features using a one-class logistic regression (OCLR) machine learning algorithm trained on small cell lung cancer (SCLC) cells, a pulmonary neuroendocrine cell type, based on the transcriptome of NSCLC and named the NED index (NEDI). Single-sample gene set enrichment analysis, pathway enrichment analysis, ESTIMATE algorithm analysis, and unsupervised subclass mapping (SubMap) were performed to assess the altered pathways and immune characteristics of lung cancer samples with different NEDI values. RESULTS: We developed and validated a novel one-class predictor based on the expression values of 13,279 mRNAs to quantitatively evaluate neuroendocrine features in NSCLC. We observed that a higher NEDI correlated with better prognosis in patients with LUAD. In addition, we observed that a higher NEDI was significantly associated with reduced immune cell infiltration and immune effector molecule expression. Furthermore, we found that etoposide-based chemotherapy might be more effective in the treatment of LUAD with high NEDI values. Moreover, we noted that tumours with low NEDI values had better responses to immunotherapy than those with high NEDI values. CONCLUSIONS: Our findings improve the understanding of NED and provide a useful strategy for applying NEDI-based risk stratification to guide decision-making in the treatment of LUAD.

Application of Molecular Simulation Methods in Food Science: Status and Prospects.

Molecular simulation methods, such as molecular docking, molecular dynamic (MD) simulation, and quantum chemical (QC) calculation, have become popular as characterization and/or virtual screening tools because they can visually display interaction details that in vitro experiments can not capture and quickly screen bioactive compounds from large databases with millions of molecules. Currently, interdisciplinary research has expanded molecular simulation technology from computer aided drug design (CADD) to food science. More food scientists are supporting their hypotheses/results with this technology. To understand better the use of molecular simulation methods, it is necessary to systematically summarize the latest applications and usage trends of molecular simulation methods in the research field of food science. However, this type of review article is rare. To bridge this gap, we have comprehensively summarized the principle, combination usage, and application of molecular simulation methods in food science. We also analyzed the limitations and future trends and offered valuable strategies with the latest technologies to help food scientists use molecular simulation methods.

Elevated Preoperative NMPR Predicts an Unfavorable Chance of Survival in Resectable Esophageal Squamous Cell Carcinoma.

Background and objectives: Combined peripheral neutrophil−platelet indexes reflecting the systemic inflammatory status have been reported to predict the clinical outcome in patients with various types of cancer. However, the prognostic value of combined neutrophil−platelet indexes in operable esophageal squamous cell carcinoma (ESCC) remains unclear. The study introduced a novel combined neutrophil−meanplateletvolume−platelet ratio (NMPR) index and investigated its clinical and prognostic value in patients with operable ESCC receiving curative surgery. Materials and Methods: A retrospective analysis of the clinicopathologic data of 277 consecutive ESCC patients who received curative resection at Zhejiang Cancer Hospital in China between January 2007 and December 2010 was conducted (the training cohort). In addition, the clinicopathologic data of 101 resectable ESCC patients at Renmin Hospital of Hubei University of Medicine between December 2018 and June 2021 were collected (the external validation cohort). The optimal cutoff value of NMPR concerning overall survival (OS) in the training cohort was determined by X-tile software. Univariate and multivariate Cox regression analyses were used to evaluate the prognostic value of NMPR along with other variables in the training cohort, which was further validated with the same cutoff value in the external validation cohort. Significant predictors of OS were used to construct the nomogram, of which the discrimination and calibration was evaluated by concordance index (C-index) and calibration plots. Results: With a cutoff value of 16.62, the results from both the training and external validation cohorts supported the association of high NMPR (>16.62) with increased tumor length and advanced T stage but not with other variables. In the training cohort, a significant association between shorter OS and high NMPR (p = 0.04) as well as high CRP (p < 0.001), poor tumor differentiation (p = 0.008), advanced T stage (p = 0.006), advanced N stage (p < 0.001) and high CEA (p = 0.007) was revealed. Additionally, the high NMPR was verified to independently predict unfavorable OS (p = 0.049) in the external validation cohort. The C-index of the OS nomogram cooperating significant predictors in the training cohort was 0.71 and the calibration plots of the OS nomogram fitted well. Conclusions: The present study demonstrates that high NMPR is an independent predictor of unfavorable OS in resectable ESCC patients without neoadjuvant therapy.

Interaction mechanism of flavonoids and Tartary buckwheat bran protein: A fluorescence spectroscopic and 3D-QSAR study.

Tartary buckwheat bran protein (TBBP) is a valuable by-product of Tartary buckwheat processing. Current studies have indicated that TBBP is a desirable carrier and protector of flavonoids. However, the quantitative structure-affinity relationship of flavonoids with TBBP still remains to be elucidated. Here, by using the fluorescence spectroscopy method to measure the binding constants of 16 flavonoids with TBBP, we employ a combination of the atom-based three dimensional-quantitative structure-affinity relationships (3D-QSAR) and quantum-chemical calculation to explore the underlying binding mechanisms. We show that flavonoids can cause the intrinsic fluorescence quenching and form non-covalent complexes with TBBP driven by hydrogen bonding and van der Waal forces. The atom-based 3D-QSAR model reveals that the rutoside group at the C-7 position of flavones is favorable to enhance the binding constants of flavonoids with TBBP. Quantum-chemical calculations consistently disclose that the rutoside group can intensify interaction forces of flavonoids, thereby strengthening the binding. This work provides theoretical evidence that TBBP has the potential application to be raw materials for develop functional food, and be the delivery carriers of flavonoids.

Insight into the Structure-Odor Relationship of Molecules: A Computational Study Based on Deep Learning.

Molecules with pleasant odors, unacceptable odors, and even serious toxicity are closely related to human social life. It is impractical to identify the odors of molecules in large quantities (particularly hazardous odors) using experimental methods. Computer-aided methods have currently attracted increasing attention for the prediction of molecular odors. Here, through models based on multilayer perceptron (MLP) and physicochemical descriptors (MLP-Des), MLP and molecular fingerprint, and convolutional neural network (CNN), we conduct the two-class prediction of odor/no odor, fruity/no odor, floral/no odor, and woody/no odor, and the multi-class prediction of fruity/flowery/woody/no odor on our newly refined molecular odor datasets. We show that three kinds of predictors can robustly predict molecular odors. The MLP-Des model not only exhibits the best prediction results (the AUC values are 0.99 and 0.86 for the two- and multi-classification models, respectively) but can also well reflect the characteristics of the structure-odor relationship of molecules. The CNN model takes 2D molecular images as input and can automatically extract the structural features related to molecular odors. The proposed models are of great help for the prediction of molecular odorants, understanding the underlying relationship between chemical structure and odor perception, and the discovery of new odorous and/or hazardous molecules.

Heparanase is a prognostic biomarker independent of tumor purity and hypoxia based on bioinformatics and immunohistochemistry analysis of esophageal squamous cell carcinoma.

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is a common malignant tumor of the digestive tract with a poor prognosis. The tumor microenvironment (TME) is mainly composed of tumor cells, stromal cells, and immune cells and plays an important role in ESCC development. There are substantial differences in tumor purity among different parts of ESCC tissues, consisting of distinct immune and stromal cells and variations in the status of hypoxia. Thus, prognostic models of ESCC based on bioinformatic analysis of tumor tissues are unreliable. METHOD: Differentially expressed genes (DEGs) independent of tumor purity and hypoxia were screened by Spearman correlation analysis of public ESCC cohorts. Subsequently, the DEGs were subjected to Cox regression analysis. Then, we constructed a protein-protein interaction (PPI) network of the DEGs using Cytoscape. Intersection analysis of the univariate Cox and PPI results indicated that heparanase (HPSE), an endo-ß-D-glucuronidase capable of cleaving heparan sulfate side chains, was a predictive factor. Gene set enrichment analysis (GSEA) was used to reveal the potential function of HPSE, and single-cell sequencing data were analyzed to evaluate the distribution of HPSE in immune cells. Furthermore, a human ESCC tissue microarray was used to validate the expression and prognostic value of HPSE. RESULT: We found that HPSE was downregulated in ESCC tissues and was not correlated with tumor purity or hypoxia status. HPSE is involved in multiple biological processes. ESCC patients with low HPSE expression in cancerous tissues exhibited poor prognosis. CONCLUSIONS: These results indicate that low HPSE expression in cancerous tissues correlates with poor prognosis in patients with ESCC. HPSE is a novel prognostic biomarker independent of tumor purity and hypoxia status in ESCC.

Computational Methods for the Interaction between Cyclodextrins and Natural Compounds: Technology, Benefits, Limitations, and Trends.

Cyclodextrins (CDs) have a hollow structure with a hydrophobic interior and hydrophilic exterior. Forming inclusion complexes with CDs will maximize the bioavailability of natural compounds and enable active components to be processed into functional foods, medicines, additives, and so forth. However, experimental methods cannot explain CD-guest binding at the atomic level. Different models have been recently developed to simulate the interaction between CDs and guests to study the binding conformation and analyze noncovalent forces. This review paper summarizes modeling methods of CD-natural compound complexes. The methods include quantitative structure-activity relationships, molecular docking, molecular dynamics simulations, and quantum-chemical calculations. The applications of these methods to enhance the solubility and bioactivities of guest molecules, assist material transportation, and promote compound extraction are also discussed. The purpose of this review is to explore interaction mechanisms of CDs and guests and to help expand new applications of CDs.

HNRNPL Is Identified and Validated as a Prognostic Biomarker Associated with Microsatellite Instability in Human Gastric Cancer.

Microsatellite instability (MSI) is emerging as a promising subtype related to immunotherapy in gastric cancer (GC). However, the underlying mechanism between MSI and microsatellite stability (MSS) remains unclear. In this study, we conducted a weighted gene co-expression network analysis and found that the expression of heterogeneous nuclear ribonucleoprotein L (HNRNPL) was significantly increased in MSI GC compared with MSS GC. This finding was further validated in public GC cohorts and commercialized human GC tissue microarray. The significant negative correlation with the expression of mismatch repair protein mutL homolog 1 (MLH1) may be one of the potential mechanisms for the upregulation of HNRNPL expression in MSI GC (R = -0.689, p = 8.59e-11). In addition, HNRNPL expression was markedly upregulated in GC tissues compared with adjacent normal tissues. High HNRNPL expression also predicted a poor prognosis in GC patients. Finally, gene set enrichment analysis revealed that high HNRNPL MSI GC samples were highly positive associated with the biological functions of inflammation and cell proliferation, such as interferon gamma response, MYC targets, E2F targets, and G2/M checkpoints. In conclusion, HNRNPL could be a new MSI-associated prognostic biomarker in GC and could be a new target for the MSI GC treatment.

Emerging Benefits: Pathophysiological Functions and Target Drugs of the Sigma-1 Receptor in Neurodegenerative Diseases.

The sigma-1 receptor (Sig-1R) is encoded by the SIGMAR1 gene and is a nonopioid transmembrane receptor located in the mitochondrial-associated endoplasmic reticulum membrane (MAM). It helps to locate endoplasmic reticulum calcium channels, regulates calcium homeostasis, and acts as a molecular chaperone to control cell fate and participate in signal transduction. It plays an important role in protecting neurons through a variety of signaling pathways and participates in the regulation of cognition and motor behavior closely related to neurodegenerative diseases. Based on its neuroprotective effects, Sig-1R has now become a breakthrough target for alleviating Alzheimer's disease and other neurodegenerative diseases. This article reviews the most cutting-edge research on the function of Sig-1R under normal or pathologic conditions and target drugs of the sigma-1 receptor in neurodegenerative diseases.

Efficacy and Safety of Berberine Alone for Several Metabolic Disorders: A Systematic Review and Meta-Analysis of Randomized Clinical Trials.

Background: Metabolic activity is the basic life activity of organisms and the fundamental for maintaining body functions. With the improvement of living standards, the incidence of metabolic disorder is also increasing. At present, most of the clinical treatment strategies and meta-analysis for metabolic disorder uncover that combined medicines with berberine ameliorate several metabolic disorders. However, evidence to disclose the therapeutic effect of berberine treatment alone and the possible factors affecting the efficacy is limited. Therefore, we have formulated strict inclusion criteria and selected more reliable data for meta-analysis through more refined screening strategies to provide evidence and guidance for clinical decision-making and understand the effect of berberine treatment alone and the factors affecting its efficacy. Methods and results: Using meta-analysis of "Cochrane Handbook for Systematic Reviews of Interventions" as guidelines, we searched PubMed, GeenMedical, Cochrane library, and china national knowledge infrastructure (CNKI) for trials reporting clinical treatment data of berberine. Another 417 trials were included through other sources to increase confidence in results. Among the 1,660 related documents retrieved from the four databases, 18 eligible documents were selected for analysis. Given the differences in trial design and measurement units, we used the standardized mean difference (SMD) method to eliminate the differences and then summarize the data for analysis. The main factors are triglyceride (TG), total cholesterol (TC), low-density lipoprotein (LDL), high-density lipoprotein (HDL), homeostasis model assessment-insulin resistance (HOMA-IR), and fasting plasma glucose (FPG). Random-effect model analysis was performed: TG (SMD: 0.94; 95%CI: 0.49,1.38; p = 0.00), TC (SMD: 1.06; 95%CI: 0.64, 1.48; p = 0.00), LDL (SMD: 1.77; 95%CI: 1.11,2.44; p = 0.00), HDL (SMD: -1.59; 95%CI: -2.32, -0.85; p = 0.00), HOMA-IR (SMD: 1.25; 95%CI: 0.25,2.24; p = 0.01), and FPG (SMD: 0.65; 95%CI: 0.28,1.03; p = 0.00). This study aimed to conduct a systematic review and meta-analysis of the literature to evaluate the therapeutic effect of berberine singly on metabolic diseases. Conclusion: Berberine can improve obesity and hyperlipidemia by reducing TG, TC, and LDL and increasing HDL; reduce insulin resistance to improve type Ⅱ diabetes; and prevent diabetic encephalopathy.

Berberine ameliorates neuronal AD-like change via activating Pi3k/PGCε pathway.

IR (insulin resistance) in diabetic brain gave rise to the generation of toxic factor Aß42 and axon collapse which were the marker of AD (Alzheimer's disease)-like lesions in the circumstance of diabetes mellitus. But the underling molecular mechanism was not clear. Chronic HGHI (high glucose and high insulin) exposure accelerates IR has been reported in type II diabetes models. Berberine has been shown to promising effect for IR in vitro and in vivo. This study demonstrates the protective effect and the underlying mechanism of berberine on HGHI-induced IR. HGHI-induced cells were used to mimic the hyperinsulinemia resulting in IR. Berberine was used to uncover the mechanisms for the treatment of hyperinsulinemia in IR model. Morris water maze (MWM), PET imaging, CCK8 assay, ELISA assay, glucose kits, microscopy, and western blot analysis were performed to evaluate the protective effects of berberine. Berberine-improved HGHI-induced IR was correlated with the increase of glucose application in neurons. Meanwhile, the expressions of Pi3K, as well as GLUT3, PKCε, and APP were downregulated in the model, while p-IRS Ser307 was upregulated compared with Normal group. Fortunately, these scenes were reversed by berberine administration. Furthermore, berberine decreased GSK3ß Y216 expressions, inhibited the production of oligomer Aß42 and extended neuronal axon. The monomeric berberine treatment improves IR that may be involved in glucose effective application, rectifying the related proteins of the aberrant insulin pathway. Additionally, it suppressed the generation of Aß42 and ameliorated neuron axon damage. Finally, berberine improves DM (diabetes mellitus)-induced cognitive impairment.

[Clinical efficacy of acupuncture combined with modified Xiangfu Decoction in treatment of menopausal insomnia cause by liver Qi stagnation].

To evaluate the efficacy and safety of acupuncture combined with modified Xiangfu Decoction in the treatment of menopausal insomnia case by liver Qi stagnation. Totally 120 cases were randomly divided into the control group(60 cases) and the treatment group(60 cases). Estazolam and acupuncture combined with modified Xiangfu Decoction were given for 16 weeks. Before and after treatment, Epworth sleepiness scale(ESS), Pittsburgh sleep quality index(PSQI), Hamilton anxiety scale(HAMA) and traditional Chinese medicine(TCM) syndrome score were compared between the two groups. Polysomnography monitor was used to monitor sleep progress and sleep structure. Serum LH, FSH and E_2 were determined. The clinical efficacy and incidence of adverse reactions were observed. Four cases were lost during the study. The total effective rate in the treatment group was 91.5%, which was higher than that in the control group 75.4%(P<0.05). After treatment, the scores of clinical symptoms(ESS, PSQI, HAMA, TCM symptoms) in the treatment group were significantly reduced(P<0.05), and lower than that in the control group(P<0.05). TST, SE in the treatment group were increased(P<0.05), while AWT, SL, AT in the treatment group were decreased(P<0.05), and the improvement was more significant than that in the control group(P<0.05). S_1 in the treatment group was decreased(P<0.05), whereas S_2, S_(3+4), REM in the treatment group were increased(P<0.05), and the improvement was more significant than that in the control group(P<0.05). The contents of LH and FSH in the treatment group were significantly reduced(P<0.05), while the content of E_2 was significantly increased(P<0.05), and the changes were more significant than those in the control group(P<0.05). The incidence of adverse reactions in the control group was 8.8%, which was higher than 1.7% in the treatment group(P<0.05). Acupuncture combined with modified Xiangfu Decoction could significantly improve the sleep status of menopausal insomnia cases caused by liver Qi stagnation, with a lower incidence of adverse reactions, and so is worthy of clinical promotion and application.

Downregulation of RIG-I mediated by ITGB3/c-SRC/STAT3 signaling confers resistance to interferon-α-induced apoptosis in tumor-repopulating cells of melanoma.

BACKGROUND: Interferon-α (IFN-α) plays a pivotal role in host antitumor immunity, and the evasion of IFN-α signaling pathway can lead to IFN-α resistance during the treatment of cancer. Although the interplay between IFN-α and tumor cells has been extensively investigated in differentiated tumor cells, much less attention has been directed to tumor-repopulating cells (TRCs). METHODS: Three-dimentional soft fibrin matrix was used to select and grow highly malignant and tumorigenic melanoma TRCs. The regulation of integrin ß3 (ITGB3)-c-SRC-STAT signaling pathway in melanoma TRCs was investigated both in vitro and in vivo. The relevant mRNA and protein expression levels were analyzed by qRT-PCR and western blot analysis. Immunoprecipitation and chromatin immunoprecipitation (ChIP) followed by qPCR (ChIP-qPCR) assays were performed to detect protein-protein and protein-DNA interactions. The clinical impacts of retinoic acid inducible gene-I (RIG-I) were assessed in melanoma datasets obtained from The Cancer Genome Atlas and Gene Expression Omnibus profiles. RESULTS: IFN-α-induced apoptosis was decreased in melanoma TRCs. Compared with conventional flask-cultured cells, IFN-α-mediated STAT1 activation was diminished in melanoma TRCs. Decreased expression of RIG-I in melanoma TRCs led to diminished activation of STAT1 via enhancing the interaction between Src homology region 2 domain-containing phosphatase-1 and STAT1. In addition, low expression levels of RIG-I correlated with poor prognosis in patients with melanoma. STAT3 was highly phosphorylated in TRCs and knockdown of STAT3 reversed the downregulation of RIG-I in TRCs. Knockdown of STAT3 resulted in STAT1 activation and increased expression of the pro-apoptosis genes in IFN-α-treated TRCs. Combined treatment of STAT3 inhibitor and IFN-α increased the apoptosis rate of TRCs. Disruption of ITGB3/c-SRC/STAT3 signaling pathway significantly elevated the efficiency of IFN-α-induced apoptosis of TRCs. CONCLUSIONS: In melanoma TRCs, ITGB3-c-SRC-STAT3 pathway caused RIG-I repression and then affect STAT1 activation to cause resistance to IFN-α-induced apoptosis. RIG-I is a prognostic marker in patients with melanoma. Combination of STAT3 inhibitor and IFN-α could enhance the efficacy of melanoma treatment. Our findings may provide a new concept of combinatorial treatment for future immunotherapy.

Macrophages reprogrammed by lung cancer microparticles promote tumor development via release of IL-1ß.

Despite their mutual antagonism, inflammation and immunosuppression coexist in tumor microenvironments due to tumor and immune cell interactions, but the underlying mechanism remains unclear. Previously, we showed that tumor cell-derived microparticles induce an M2 phenotype characterized by immunosuppression in tumor-infiltrating macrophages. Here, we further showed that lung cancer microparticles (L-MPs) induce macrophages to release a key proinflammatory cytokine, IL-1ß, thus promoting lung cancer development. The underlying mechanism involves the activation of TLR3 and the NLRP3 inflammasome by L-MPs. More importantly, tyrosine kinase inhibitor treatment-induced L-MPs also induce human macrophages to release IL-1ß, leading to a tumor-promoting effect in a humanized mouse model. These findings demonstrated that in addition to their anti-inflammatory effect, L-MPs induce a proinflammatory phenotype in tumor-infiltrating macrophages, promoting the development of inflammatory and immunosuppressive tumor microenvironments.

Hypoxia-reprogrammed tricarboxylic acid cycle promotes the growth of human breast tumorigenic cells.

Clinical applications of antiangiogenic agents profoundly affect tumor cell behaviors via the resultant hypoxia. To date, how the hypoxia regulates tumor cells remains unclear. Here, we show that hypoxia promotes the growth of human breast tumorigenic cells that repopulate tumors [tumor-repopulating cells (TRCs)] in vitro and in vivo. This stimulating effect is ascribed to hypoxia-induced reactive oxygen species (ROS) that activates Akt and NF-κB, dependent on the attenuated tricarboxylic acid (TCA) cycle. We find that fumarate is accumulated in the TCA cycle of hypoxic TRCs, leading to glutathione succination, NADPH/NADP+ decrease, and an increase in ROS levels. Mechanistically, hypoxia-increased HIF-1α transcriptionally downregulates the expression of mitochondrial phosphoenolpyruvate carboxykinase (PCK2), leading to TCA cycle attenuation and fumarate accumulation. These findings reveal that hypoxia-reprogrammed TCA cycle promotes human breast TRCs growth via a HIF-1α-downregulated PCK2 pathway, implying a need for a combination of an antiangiogenic therapy with an antioxidant modulator.

Enhanced mitochondrial pyruvate transport elicits a robust ROS production to sensitize the antitumor efficacy of interferon-γ in colon cancer.

Metabolic reprogramming is a feature of cancer cells and crucial for tumor growth and metastasis. Interferon-γ (IFNγ) is a cytokine that plays a pivotal role in host antitumor immunity. However, little is known about the roles of metabolic reprogramming in immune responses. Here, we show that colon cancer cells reprogram metabolism to coordinate proper cellular responses to IFNγ by downregulating mitochondrial pyruvate carrier (MPC)1 and 2 via STAT3 signaling. Forced overexpression of MPC promote the production of reactive oxygen species and enhance the apoptosis induced by IFNγ in colon cancer cells. Moreover, inhibiting STAT3 sensitize the antitumor efficacy of IFN-γ against colon cancer cells. Our findings present a previously unrecognized mechanism that colon cancer manipulate to resist IFNγ mediated antitumor immunity that have implications for targeting a unique aspect of this disease.

Hydroxychloroquine induced lung cancer suppression by enhancing chemo-sensitization and promoting the transition of M2-TAMs to M1-like macrophages.

BACKGROUND: Lysosome-associated agents have been implicated as possible chemo-sensitizers and immune regulators for cancer chemotherapy. We investigated the potential roles and mechanisms of hydroxychloroquine (HCQ) in combination with chemotherapy in lung cancer treatment. METHODS: The effects of combined treatment on non-small cell lung cancer (NSCLC) were investigated using cell viability assays and animal models. The influence of HCQ on lysosomal pH was evaluated by lysosomal sensors and confocal microscopy. The effects of HCQ on the tumour immune microenvironment were analysed by flow cytometry. RESULTS: HCQ elevates the lysosomal pH of cancer cells to inactivate P-gp while increasing drug release from the lysosome into the nucleus. Furthermore, single HCQ therapy inhibits lung cancer by inducing macrophage-modulated anti-tumour CD8+ T cell immunity. Moreover, HCQ could promote the transition of M2 tumour-associated macrophages (TAMs) into M1-like macrophages, leading to CD8+ T cell infiltration into the tumour microenvironment. CONCLUSIONS: HCQ exerts anti-NSCLC cells effects by reversing the drug sequestration in lysosomes and enhancing the CD8+ T cell immune response. These findings suggest that HCQ could act as a promising chemo-sensitizer and immune regulator for lung cancer chemotherapy in the clinic.