MYC-driven accumulation of 2-hydroxyglutarate is associated with breast cancer prognosis

IFI16 inhibits DNA repair that potentiates type-I interferon-induced antitumor effects in triple negative breast cancer

Tumor DNA-damage response (DDR) has an important role in driving type-I interferon (IFN)-mediated host antitumor immunity, but it is not clear how tumor DNA damage is interconnected with the immune response. Here, we report the role of IFN-γ-inducible protein 16 (IFI16) in DNA repair, which amplifies the stimulator of IFN genes (STING)-type-I IFN signaling, particularly in triple-negative breast cancer (TNBC). IFI16 is rapidly induced and accumulated to the histone-evicted DNA at double-stranded breakage (DSB) sites, where it inhibits recruitment of DDR factors. Subsequently, IFI16 increases the release of DNA fragments to the cytoplasm and induces STING-mediated type-I IFN production. Synergistic cytotoxic and immunomodulatory effects of doxorubicin and type-I IFNs are decreased upon IFI16 depletion in vivo. Furthermore, IFI16 expression correlates with improved clinical outcome in patients with TNBC treated with chemotherapy. Together, our findings suggest that type-I IFNs and IFI16 could offer potential therapeutic strategies for TNBC.

Butyrate and Metformin Affect Energy Metabolism Independently of the Metabolic Phenotype in the Tumor Therapy Model

The BALB/c cell transformation assay (BALB-CTA) considers inter- and intra-tumor heterogeneities and affords the possibility of a direct comparison between untransformed and malignant cells. In the present study, we established monoclonal cell lines that originate from the BALB-CTA and mimic heterogeneous tumor cell populations, in order to investigate phenotype-specific effects of the anti-diabetic drug metformin and the short-chain fatty acid butyrate. Growth inhibitory effects were measured with a ViCell XR cell counter. The BALB/c tumor therapy model (BALB-TTM) was performed, and the extracellular glucose level was measured in the medium supernatant. Using a Seahorse Analyzer, the metabolic phenotypes of four selected clones were characterized, and effects on energy metabolism were investigated. Anti-carcinogenic effects and reduced glucose uptake after butyrate application were observed in the BALB-TTM. Metabolic characterization of the cell clones revealed three different phenotypes. Surprisingly, treatment with metformin or butyrate induced opposite metabolic shifts with similar patterns in all cell clones tested. In conclusion, the BALB-TTM is a relevant model for mechanistic cancer research, and the generation of monoclonal cell lines offers a novel possibility to investigate specific drug effects in a heterogeneous tumor cell population. The results indicate that induced alterations in energy metabolism seem to be independent of the original metabolic phenotype.

Association Between RSK2 and Clinical Indexes of Primary Breast Cancer: A Meta-Analysis Based on mRNA Microarray Data

Background: Although ribosomal protein S6 kinases, 90 kDa, polypeptide 3 (RSK2, RPS6KA3) has been reported to play an important role in cancer cell proliferation, invasion, and migration, including breast cancer, its clinical implication in primary breast cancer patients is not well understood, and there were not many studies to explore the relationship between RSK2 and breast cancer on a clinical level.

Methods: A systematic series matrix file search uploaded from January 1, 2008 to November 31, 2017 was undertaken using ArrayExpress and Gene Expression Omnibus (GEO) databases. Search filters were breast cancer, RNA assay, and array assay. Files eligible for inclusion met the following criteria: a) sample capacity is over 100, b) tumor sample comes from unselected patient’s primary breast tumor tissue, and c) expression of RSK2 and any clinical parameters of patients were available from the files. We use median as the cutoff value to assess the association between the expression of RSK2 and the clinical indexes of breast cancer patients.

Finding: The meta-analysis identified 13 series matrix files from GEO database involving 3,122 samples that come from patients’ primary breast cancer tissue or normal tissue. The expression of RSK2 in tumor tissues is lower than that in normal tissues [odds ratio (OR), 0.54; 95% credible interval (CI), 0.44–0.67; Cochran’s Q test p = 0.14; I² = 41.7%]. Patients with a high expression of RSK2 showed more favorable overall survival [hazard ratio (HR), 0.71; 95% CI, 0.49–0.94; Cochran’s Q test p = 0.95; I² = 0.0%] and less potential of distant metastasis (OR, 0.59; 95% CI, 0.41–0.87; Cochran’s Q test p = 0.88; I² = 0.0%) and lymph node infiltration (OR, 0.81; 95% CI, 0.65–0.998; Cochran’s Q test p = 0.09; I² = 42.8%). Besides, the expression of RSK2 in luminal breast cancer is lower than Cochran’s Q test p = 0.06; I² = 63.5%). RSK2 overexpression corresponded with higher histological grade (OR, 1.329; 95% CI, 1.03–1.721; Cochran’s Q test p = 0.69; I² = 0.0%). RSK2 expression is also associated with estrogen receptor (ER) and age.

Conclusion: The meta-analysis provides evidence that RSK2 is a potential biomarker in breast cancer patients. The expression of RSK2 is distinctive in different intrinsic subtypes of breast cancer, indicating that it may play an important role in specific breast cancer. Further study is needed to uncover the mechanism of RSK2 in breast cancer.

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The Significance of SIX1 as a Prognostic Biomarker for Survival Outcome in Various Cancer Patients: A Systematic Review and Meta-Analysis

Sine Oculis Homeobox Homolog 1 (SIX1) is reported to promote cancer initiation and progression in many preclinical models and is demonstrated in human cancer tissues. However, the correlation between SIX1 and cancer patients’ prognosis has not yet been systematically evaluated. Therefore, we performed a systematic review and meta-analysis in various human cancer types and extracted some data from TCGA datasets for further verification and perfection. We constructed 27 studies and estimated the association between SIX1 expression in various cancer patients’ overall survival and verified with TCGA datasets. Twenty-seven studies with 4899 patients are include in the analysis of overall, and disease-free survival, most of them were retrospective. The pooled hazard ratios (HRs) for overall and disease-free survival in high SIX1 expression patients were 1.54 (95% CI: 1.32-1.80, P<0.00001) and 1.83 (95% CI: 1.31-2.55, P=0.0004) respectively. On subgroup analysis classified in cancer type, high SIX1 expression was associated with poor overall survival in patients with hepatocellular carcinoma (HR 1.50; 95% CI: 1.17-1.93, P =0.001), breast cancer (HR 1.31; 95% CI: 1.10-1.55, P =0.002) and esophageal squamous cell carcinoma (HR 1.89; 95% CI: 1.42-2.52, P<0.0001). Next, we utilized TCGA online datasets, and the consistent results were verified in various cancer types. SIX1 expression indicated its potential to serve as a cancer biomarker and deliver prognostic information in various cancer patients. More works still need to improve the understandings of SIX1 expression and prognosis in different cancer types.

Transcriptomics and Metabolomics Integration Reveals Redox-Dependent Metabolic Rewiring in Breast Cancer Cells

Rewiring glucose metabolism toward aerobic glycolysis provides cancer cells with a rapid generation of pyruvate, ATP, and NADH, while pyruvate oxidation to lactate guarantees refueling of oxidized NAD⁺ to sustain glycolysis. CtPB2, an NADH-dependent transcriptional co-regulator, has been proposed to work as an NADH sensor, linking metabolism to epigenetic transcriptional reprogramming. By integrating metabolomics and transcriptomics in a triple-negative human breast cancer cell line, we show that genetic and pharmacological down-regulation of CtBP2 strongly reduces cell proliferation by modulating the redox balance, nucleotide synthesis, ROS generation, and scavenging. Our data highlight the critical role of NADH in controlling the oncogene-dependent crosstalk between metabolism and the epigenetically mediated transcriptional program that sustains energetic and anabolic demands in cancer cells.

The Expression and Prognostic Value of SUMO1-Activating Enzyme Subunit 1 and Its Potential Mechanism in Triple-Negative Breast Cancer

Background: Triple-negative breast cancer (TNBC) is the most invasive and metastatic subtype of breast cancer. SUMO1-activating enzyme subunit 1 (SAE1), an E1-activating enzyme, is indispensable for protein SUMOylation. SAE1 has been found to be a relevant biomarker for progression and prognosis in several tumor types. However, the role of SAE1 in TNBC remains to be elucidated.

Methods: In the research, the mRNA expression of SAE1 was analyzed via the cancer genome atlas (TCGA) and gene expression omnibus (GEO) database. Cistrome DB Toolkit was used to predict which transcription factors (TFs) are most likely to increase SAE1 expression in TNBC. The correlation between the expression of SAE1 and the methylation of SAE1 or quantity of tumor-infiltrating immune cells was further invested. Single-cell analysis, using CancerSEA, was performed to query which functional states are associated with SAE1 in different cancers in breast cancer at the single-cell level. Next, weighted gene coexpression network (WGCNA) was applied to reveal the highly correlated genes and coexpression networks of SAE1 in TNBC patients, and a prognostic model containing SAE1 and correlated genes was constructed. Finally, we also examined SAE1 protein expression of 207 TNBC tissues using immunohistochemical (IHC) staining.

Results: The mRNA and protein expression of SAE1 were increased in TNBC tissues compared with adjacent normal tissues, and the protein expression of SAE1 was significantly associated with overall survival (OS) and disease-free survival (DFS). Correlation analyses revealed that SAE1 expression was positively correlated with forkhead box M1 (FOXM1) TFs and negatively correlated with SAE1 methylation site (cg14042711) level. WGCNA indicated that the genes coexpressed with SAE1 belonged to the green module containing 1,176 genes. Through pathway enrichment analysis of the module, 1,176 genes were found enriched in cell cycle and DNA repair. Single-cell analysis indicated that SAE1 and its coexpression genes were associated with cell cycle, DNA damage, DNA repair, and cell proliferation. Using the LASSO COX regression, a prognostic model including SAE1 and polo-like kinase 1 (PLK1) was built to accurately predict the likelihood of DFS in TNBC patients.

Conclusion: In conclusion, we comprehensively analyzed the mRNA and protein expression, prognosis, and interaction genes of SAE1 in TNBC and constructed a prognostic model including SAE1 and PLK1. These results might be important for better understanding of the role of SAE1 in TNBC. In addition, DNA methyltransferase and TFs inhibitor treatments targeting SAE1 might improve the survival of TNBC patients.

Metabolic remodelling during early mouse embryo development

During early mammalian embryogenesis, changes in cell growth and proliferation depend on strict genetic and metabolic instructions. However, our understanding of metabolic reprogramming and its influence on epigenetic regulation in early embryo development remains elusive. Here we show a comprehensive metabolomics profiling of key stages in mouse early development and the two-cell and blastocyst embryos, and we reconstructed the metabolic landscape through the transition from totipotency to pluripotency. Our integrated metabolomics and transcriptomics analysis shows that while two-cell embryos favour methionine, polyamine and glutathione metabolism and stay in a more reductive state, blastocyst embryos have higher metabolites related to the mitochondrial tricarboxylic acid cycle, and present a more oxidative state. Moreover, we identify a reciprocal relationship between α-ketoglutarate (α-KG) and the competitive inhibitor of α-KG-dependent dioxygenases, L-2-hydroxyglutarate (L-2-HG), where two-cell embryos inherited from oocytes and one-cell zygotes display higher L-2-HG, whereas blastocysts show higher α-KG. Lastly, increasing 2-HG availability impedes erasure of global histone methylation markers after fertilization. Together, our data demonstrate dynamic and interconnected metabolic, transcriptional and epigenetic network remodelling during early mouse embryo development.

Metabolic Flexibility Is a Determinant of Breast Cancer Heterogeneity and Progression

Breast cancer progression is characterized by changes in cellular metabolism that contribute to enhanced tumour growth and adaptation to microenvironmental stresses. Metabolic changes within breast tumours are still poorly understood and are not as yet exploited for therapeutic intervention, in part due to a high level of metabolic heterogeneity within tumours. The metabolic profiles of breast cancer cells are flexible, providing dynamic switches in metabolic states to accommodate nutrient and energy demands and further aggravating the challenges of targeting metabolic dependencies in cancer. In this review, we discuss the intrinsic and extrinsic factors that contribute to metabolic heterogeneity of breast tumours. Next, we examine how metabolic flexibility, which contributes to the metabolic heterogeneity of breast tumours, can alter epigenetic landscapes and increase a variety of pro-tumorigenic functions. Finally, we highlight the difficulties in pharmacologically targeting the metabolic adaptations of breast tumours and provide an overview of possible strategies to sensitize heterogeneous breast tumours to the targeting of metabolic vulnerabilities.

LncRNA OIP5-AS1 Regulates the Warburg Effect Through miR-124-5p/IDH2/HIF-1α Pathway in Cervical Cancer

Hypoxia reprogrammed glucose metabolism affects the Warburg effect of tumor cells, but the mechanism is still unclear. Long-chain non-coding RNA (lncRNA) has been found by many studies to be involved in the Warburg effect of tumor cells under hypoxic condition. Herein, we find that lncRNA OIP5-AS1 is up-regulated in cervical cancer tissues and predicts poor 5-years overall survival in cervical cancer patients, and it promotes cell proliferation of cervical cancer cells in vitro and in vivo. Moreover, OIP5-AS1 is a hypoxia-responsive lncRNA and is essential for hypoxia-enhanced glycolysis which is IDH2 or hypoxia inducible factor-1α (HIF-1α) dependent. In cervical cancer cells, OIP5-AS1 promotes IDH2 expression by inhibiting miR-124-5p, and IDH2 promotes the Warburg effect of cervical under hypoxic condition through regulating HIF-1α expression. In conclusion, hypoxia induced OIP5-AS1 promotes the Warburg effect through miR-124-5p/IDH2/HIF-1α pathway in cervical cancer.

Multi-Omic Approaches to Breast Cancer Metabolic Phenotyping: Applications in Diagnosis, Prognosis, and the Development of Novel Treatments

Breast cancer (BC) is characterized by high disease heterogeneity and represents the most frequently diagnosed cancer among women worldwide. Complex and subtype-specific gene expression alterations participate in disease development and progression, with BC cells known to rewire their cellular metabolism to survive, proliferate, and invade. Hence, as an emerging cancer hallmark, metabolic reprogramming holds great promise for cancer diagnosis, prognosis, and treatment. Multi-omics approaches (the combined analysis of various types of omics data) offer opportunities to advance our understanding of the molecular changes underlying metabolic rewiring in complex diseases such as BC. Recent studies focusing on the combined analysis of genomics, epigenomics, transcriptomics, proteomics, and/or metabolomics in different BC subtypes have provided novel insights into the specificities of metabolic rewiring and the vulnerabilities that may guide therapeutic development and improve patient outcomes. This review summarizes the findings of multi-omics studies focused on the characterization of the specific metabolic phenotypes of BC and discusses how they may improve clinical BC diagnosis, subtyping, and treatment.

HIF-1-Independent Mechanisms Regulating Metabolic Adaptation in Hypoxic Cancer Cells

In solid tumours, cancer cells exist within hypoxic microenvironments, and their metabolic adaptation to this hypoxia is driven by HIF-1 transcription factor, which is overexpressed in a broad range of human cancers. HIF inhibitors are under pre-clinical investigation and clinical trials, but there is evidence that hypoxic cancer cells can adapt metabolically to HIF-1 inhibition, which would provide a potential route for drug resistance. Here, we review accumulating evidence of such adaptions in carbohydrate and creatine metabolism and other HIF-1-independent mechanisms that might allow cancers to survive hypoxia despite anti-HIF-1 therapy. These include pathways in glucose, glutamine, and lipid metabolism; epigenetic mechanisms; post-translational protein modifications; spatial reorganization of enzymes; signalling pathways such as Myc, PI3K-Akt, 2-hyxdroxyglutarate and AMP-activated protein kinase (AMPK); and activation of the HIF-2 pathway. All of these should be investigated in future work on hypoxia bypass mechanisms in anti-HIF-1 cancer therapy. In principle, agents targeted toward HIF-1β rather than HIF-1α might be advantageous, as both HIF-1 and HIF-2 require HIF-1β for activation. However, HIF-1β is also the aryl hydrocarbon nuclear transporter (ARNT), which has functions in many tissues, so off-target effects should be expected. In general, cancer therapy by HIF inhibition will need careful attention to potential resistance mechanisms.

Chromatographic methods coupled to mass spectrometry for the determination of oncometabolites in biological samples-A review

It is now well-established that dysregulation of the tricarboxylic acid (TCA) cycle enzymes succinate dehydrogenase, fumarate hydratase, and isocitrate dehydrogenase leads to the abnormal cellular accumulation of succinate, fumarate, and 2-hydroxyglutarate, respectively, which contribute to the formation and malignant progression of numerous types of cancers. Thus, these metabolites, called oncometabolites, could potentially be useful as tumour-specific biomarkers and as therapeutic targets. For this reason, the development of analytical methodologies for the accurate identification and determination of their levels in biological matrices is an important task in the field of cancer research. Currently, hyphenated gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS) techniques are the most powerful analytical tools in what concerns high sensitivity and selectivity to achieve such difficult task. In this review, we first provide a brief description of the biological formation of oncometabolites and their oncogenic properties, and then we present an overview and critical assessment of the GC-MS and LC-MS based analytical approaches that are reported in the literature for the determination of oncometabolites in biological samples, such as biofluids, cells, and tissues. Advantages and drawbacks of these approaches will be comparatively discussed. We believe that the present review represents the first attempt to summarize the applications of these hyphenated techniques in the context of oncometabolite analysis, which may be useful to new and existing researchers in this field.

Essential amino acid metabolism-related molecular classification in triple-negative breast cancer

Aim: To develop an approach to characterize and classify triple-negative breast cancer (TNBC) tumors based upon their essential amino acid (EAA) metabolic activity. Methods: We performed bioinformatic analyses of genomic, transcriptomic and clinical data in an integrated cohort of 740 TNBC patients from public databases. Results: Based on EAA metabolism-related gene expression patterns, two TNBC subtypes were identified with distinct prognoses and genomic alterations. Patients exhibiting an upregulated EAA metabolism phenotype were more prone to chemoresistance but also expressed higher levels of immune checkpoint genes and may be better candidates for immune checkpoint inhibitor therapy. Conclusion: Metabolic classification based upon EAA profiles offers a novel biological insight into previously established TNBC subtypes and advances current understanding of TNBC's metabolic heterogeneity.

Metabostemness in cancer: Linking metaboloepigenetics and mitophagy in remodeling cancer stem cells

Cancer stem cells (CSCs) are rare populations of malignant cells with stem cell-like features of self-renewal, uninterrupted differentiation, tumorigenicity, and resistance to conventional therapeutic agents, and these cells have a decisive role in treatment failure and tumor relapse. The self-renewal potential of CSCs with atypical activation of developmental signaling pathways involves the maintenance of stemness to support cancer progression. The acquisition of stemness in CSCs has been accomplished through genetic and epigenetic rewiring following the metabolic switch. In this context, "metabostemness" denotes the metabolic parameters that essentially govern the epitranscriptional gene reprogramming mechanism to dedifferentiate tumor cells into CSCs. Several metabolites often referred to as oncometabolites can directly remodel chromatin structure and thereby influence the operation of epitranscriptional circuits. This integrated metaboloepigenetic dimension of CSCs favors the differentiated cells to move in dedifferentiated macrostates. Some metabolic events might perform as early drivers of epitranscriptional reprogramming; however, subsequent metabolic hits may govern the retention of stemness properties in the tumor mass. Interestingly, selective removal of mitochondria through autophagy can promote metabolic plasticity and alter metabolic states during differentiation and dedifferentiation. In this connection, novel metabostemness-specific drugs can be generated as potential cancer therapeutics to target the metaboloepigenetic circuitry to eliminate CSCs.

Metabolic reprograming confers tamoxifen resistance in breast cancer

Breast cancer is the most common cancer among females and the leading cause of cancer-related deaths. Approximately 70 % of breast cancers are estrogen receptor (ER) positive. An ER antagonist such as tamoxifen is used as adjuvant therapy in ER-positive patients. The major problem with endocrine therapy is the emergence of acquired resistance in approximately 40 % of patients receiving tamoxifen. Metabolic alteration is one of the hallmarks of cancer cells. Rapidly proliferating cancer cells require increased nutritional support to fuel various functions such as proliferation, cell migration, and metastasis. Recent studies have established that the metabolic state of cancer cells influences their susceptibility to chemotherapeutic drugs and that cancer cells reprogram their metabolism to develop into resistant phenotypes. In this review, we discuss the major findings on metabolic pathway alterations in tamoxifen-resistant (TAMR) breast cancer and the molecular mechanisms known to regulate the expression and function of metabolic enzymes and the respective metabolite levels upon tamoxifen treatment. It is anticipated that this in-depth analysis of specific metabolic pathways in TAMR cancer might be exploited therapeutically.

Metformin Decreases 2-HG Production through the MYC-PHGDH Pathway in Suppressing Breast Cancer Cell Proliferation

The biguanide drug metformin has been widely used for the treatment of type 2 diabetes, and there is evidence supporting the anticancer effect of metformin despite some controversy. Here, we report the growth inhibitory activity of metformin in the breast cancer (MCF-7) cells, both in vitro and in vivo, and the associated metabolic changes. In particular, a decrease in a well-known oncometabolite 2-hydroxyglutarate (2-HG) was discovered by a metabolomics approach. The decrease in 2-HG by metformin was accompanied by the reduction in histone methylation, consistent with the known tumorigenic mechanism of 2-HG. The relevance of 2-HG inhibition in breast cancer was also supported by a higher level of 2-HG in human breast cancer tissues. Genetic knockdown of PHGDH identified the PHGDH pathway as the producer of 2-HG in the MCF-7 cells that do not carry isocitrate dehydrogenase 1 and 2 (IDH1/IDH2) mutations, the conventional producer of 2-HG. We also showed that metformin’s inhibitory effect on the PHGDH-2HG axis may occur through the regulation of the AMPK-MYC pathway. Overall, our results provide an explanation for the coherent pathway from complex I inhibition to epigenetic changes for metformin’s anticancer effect.

MicroRNA-192-5p inhibits migration of triple negative breast cancer cells and directly regulates Rho GTPase activating protein 19

Among the different breast cancer subtypes, triple-negative breast cancer (TNBC) is associated with a poor prognosis, low survival rates, and high expression of histone deacetylases. Treatment with histone deacetylase inhibitor trichostatin A (TSA) leads to an increased expression of potential tumor-suppressive miRNAs. Characterization of these miRNAs can help to find new molecular targets for treatment of TNBC. We identified differentially expressed miRNAs by microarray analyses after treatment with TSA in the TNBC cell lines HCC38, HCC1395, and HCC1935. The gene locus of hsa-miRNA-192-5p (miR-192) and hsa-miR-194-2 (miR-194-2) with its host gene, long noncoding RNA miR-194-2HG, has been linked to inhibition of migration in different tumor types. Therefore, we examined tumor-relevant functional effects using WST-1-based proliferation, capsase-3/7-based apoptosis, and trans-well migration assays after transfection with miRNA mimics or specific siRNAs. We demonstrated the tumor-suppressive capacity of miR-192 in TNBC cells, which was exerted through inhibition of proliferation, induction of apoptosis, and reduction of migration. Gene expression and bioinformatics analyses of TNBC cell lines transfected with miR-192 mimics, identified a number of genes involved in migration including the Rho GTPase Activating Protein ARHGAP19. Through RNA immunoprecipitation we demonstrated the direct binding of miR-192 and ARHGAP19. Downregulation of ARHGAP19 expression by either miR-192 or siRNA inhibited migration of TNBC cells significantly. Our findings demonstrate that overexpression of epigenetically deregulated miR-192 decreases proliferation, promotes apoptosis, and inhibits migration of TNBC cell lines.

A pan-cancer transcriptomic study showing tumor specific alterations in central metabolism

Recently, there has been a resurgence of interest in metabolic rewiring of tumors to identify clinically relevant genes. However, most of these studies have had either focused on individual tumors, or are too general, providing a broad outlook on overall changes. In this study, we have first curated an extensive list of genes encoding metabolic enzymes and metabolite transporters relevant to carbohydrate, fatty acid and amino acid oxidation and biosynthesis. Next, we have used publicly available transcriptomic data for 20 different tumor types from The Cancer Genome Atlas Network (TCGA) and focused on differential expression of these genes between tumor and adjacent normal tissue. Our study revealed major transcriptional alterations in genes that are involved in central metabolism. Most tumors exhibit upregulation in carbohydrate and amino acid transporters, increased glycolysis and pentose phosphate pathway, and decreased fatty acid and amino acid oxidation. On the other hand, the expression of genes of the tricarboxylic acid cycle, anaplerotic reactions and electron transport chain differed between tumors. Although most transcriptomic alterations were conserved across many tumor types suggesting the initiation of common regulatory programs, expression changes unique to specific tumors were also identified, which can provide gene expression fingerprints as potential biomarkers or drug targets. Our study also emphasizes the value of transcriptomic data in the deeper understanding of metabolic changes in diseases.

The implications of IDH mutations for cancer development and therapy

Mutations in the genes encoding the cytoplasmic and mitochondrial forms of isocitrate dehydrogenase (IDH1 and IDH2, respectively; collectively referred to as IDH) are frequently detected in cancers of various origins, including but not limited to acute myeloid leukaemia (20%), cholangiocarcinoma (20%), chondrosarcoma (80%) and glioma (80%). In all cases, neomorphic activity of the mutated enzyme leads to production of the oncometabolite D-2-hydroxyglutarate, which has profound cell-autonomous and non-cell-autonomous effects. The broad effects of IDH mutations on epigenetic, differentiation and metabolic programmes, together with their high prevalence across a variety of cancer types, early presence in tumorigenesis and uniform expression in tumour cells, make mutant IDH an ideal therapeutic target. Herein, we describe the current biological understanding of IDH mutations and the roles of mutant IDH in the various associated cancers. We also present the available preclinical and clinical data on various methods of targeting IDH-mutant cancers and discuss, based on the underlying pathogenesis of different IDH-mutated cancer types, whether the treatment approaches will converge or be context dependent.

From Metabolism to Genetics and Vice Versa: The Rising Role of Oncometabolites in Cancer Development and Therapy

Over the last decades, the study of cancer metabolism has returned to the forefront of cancer research and challenged the role of genetics in the understanding of cancer development. One of the major impulses of this new trend came from the discovery of oncometabolites, metabolic intermediates whose abnormal cellular accumulation triggers oncogenic signalling and tumorigenesis. These findings have led to reconsideration and support for the long-forgotten hypothesis of Warburg of altered metabolism as oncogenic driver of cancer and started a novel paradigm whereby mitochondrial metabolites play a pivotal role in malignant transformation. In this review, we describe the evolution of the cancer metabolism research from a historical perspective up to the oncometabolites discovery that spawned the new vision of cancer as a metabolic disease. The oncometabolites’ mechanisms of cellular transformation and their contribution to the development of new targeted cancer therapies together with their drawbacks are further reviewed and discussed.

Pan-cancer characterization of metabolism-related biomarkers identifies potential therapeutic targets

Background

Generally, cancer cells undergo metabolic reprogramming to adapt to energetic and biosynthetic requirements that support their uncontrolled proliferation. However, the mutual relationship between two critical metabolic pathways, glycolysis and oxidative phosphorylation (OXPHOS), remains poorly defined.

Methods

We developed a “double-score” system to quantify glycolysis and OXPHOS in 9668 patients across 33 tumor types from The Cancer Genome Atlas and classified them into four metabolic subtypes. Multi-omics bioinformatical analyses was conducted to detect metabolism-related molecular features.

Results

Compared with patients with low glycolysis and high OXPHOS (LGHO), those with high glycolysis and low OXPHOS (HGLO) were consistently associated with worse prognosis. We identified common dysregulated molecular features between different metabolic subgroups across multiple cancers, including gene, miRNA, transcription factor, methylation, and somatic alteration, as well as investigated their mutual interfering relationships.

Conclusion

Overall, this work provides a comprehensive atlas of metabolic heterogeneity on a pan-cancer scale and identified several potential drivers of metabolic rewiring, suggesting corresponding prognostic and therapeutic utility.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-02889-0.

Mammary epithelial cells have lineage-rooted metabolic identities

Cancer metabolism adapts the metabolic network of its tissue of origin. However, breast cancer is not a disease of a single origin. Multiple epithelial populations serve as the culprit cell of origin for specific breast cancer subtypes, yet our knowledge of the metabolic network of normal mammary epithelial cells is limited. Using a multi-omic approach, here we identify the diverse metabolic programmes operating in normal mammary populations. The proteomes of basal, luminal progenitor and mature luminal cell populations revealed enrichment of glycolysis in basal cells and of oxidative phosphorylation in luminal progenitors. Single-cell transcriptomes corroborated lineage-specific metabolic identities and additional intra-lineage heterogeneity. Mitochondrial form and function differed across lineages, with clonogenicity correlating with mitochondrial activity. Targeting oxidative phosphorylation and glycolysis with inhibitors exposed lineage-rooted metabolic vulnerabilities of mammary progenitors. Bioinformatics indicated breast cancer subtypes retain metabolic features of their putative cell of origin. Thus, lineage-rooted metabolic identities of normal mammary cells may underlie breast cancer metabolic heterogeneity and targeting these vulnerabilities could advance breast cancer therapy.

Restructuring the Gut Microbiota by Intermittent Fasting Lowers Blood Pressure

[Figure: see text].

In vitro and in vivo analysis of metabolites involved in the TCA cycle and glutamine metabolism associated with cisplatin resistance in human lung cancer

Elucidating the dysregulated metabolic pathways in cancer cells and their relevance to cisplatin resistance could yield new insights into cancer therapy. We previously reported that eight metabolites involved in the tricarboxylic acid (TCA) cycle and glutamine metabolism were associated with platinum-based chemotherapy efficacy in human lung cancer. Here, we investigated the metabolic differences upon cisplatin treatment in lung cancer in vitro and in vivo. A simple and partially validated standard addition method was applied for the quantification of five metabolites involved in the TCA cycle and glutamine metabolism using amide hydrophilic interaction liquid chromatography-tandem mass spectrometry (HILIC-MS/MS). The present study investigated the levels of these biomarkers in A549 cells and the cisplatin-resistant A549-DDP cells, as well as in the plasma before and after cisplatin treatment in A549 xenograft mice. Levels of five metabolites, including 2-hydroxyglutaric acid (2-HG), α-ketoglutarate (α-KG), succinate, glutamine, and glutamate, showed a decreasing trend in A549-DDP cells. In addition, 2-HG and glutamine were the most significantly altered metabolites in cisplatin-treated A549 xenograft mice. These data indicate that the TCA cycle and glutamine metabolism play important roles in cisplatin-based chemotherapy resistance in lung cancer. Our results provide a new angle for exploring the molecular mechanisms underlying cisplatin resistance.

Biochemical Background in Mitochondria Affects 2HG Production by IDH2 and ADHFE1 in Breast Carcinoma

Simple Summary

2-hydroxyglutarate (2HG) is a metabolite resembling normal cell metabolite 2-oxoglutarate (2OG), however, its accumulation in cells might lead to amplification of processes in cancer development. R-2HG is a product or bi-product of several metabolic enzymes, including mitochondrial ones. We investigated whether production of mitochondrial 2HG is elevated in breast cancer cell lines and identified active competition for initial substrate, 2OG, between enzymes isocitrate dehydrogenase IDH2 and alcohol dehydrogenase ADHFE1. We have also investigated possible substrate and cofactor NADPH channeling between the two IDH2 molecules within mitochondria. We characterized several situations when either IDH2 and ADHFE1 produce a non-negligible amount of 2HG, which is then actively exported from cells. This can serve as a clinical application of our findings. We have therefore quantified 2HG levels in the urine of breast carcinoma patients after resection of their tumors and showed a positive correlations between cancer stages and 2HG levels. Note that cancer stages I to IV differ by the existence and severity of metastases. Extension of these findings might help to improve diagnostic approaches of breast carcinoma.

Abstract

Mitochondrial production of 2-hydroxyglutarate (2HG) can be catalyzed by wild-type isocitrate dehydrogenase 2 (IDH2) and alcohol dehydrogenase, iron-containing 1 (ADHFE1). We investigated whether biochemical background and substrate concentration in breast cancer cells promote 2HG production. To estimate its role in 2HG production, we quantified 2HG levels and its enantiomers in breast cancer cells using analytical approaches for metabolomics. By manipulation of mitochondrial substrate fluxes using genetic and pharmacological approaches, we demonstrated the existence of active competition between 2HG producing enzymes, i.e., IDH2 and ADHFE1. Moreover, we showed that distinct fractions of IDH2 enzyme molecules operate in distinct oxido-reductive modes, providing NADPH and producing 2HG simultaneously. We have also detected 2HG release in the urine of breast cancer patients undergoing adjuvant therapy and detected a correlation with stages of breast carcinoma development. In summary, we provide a background for vital mitochondrial production of 2HG in breast cancer cells with outcomes towards cancer biology and possible future diagnosis of breast carcinoma.

The Role of 2-Oxoglutarate Dependent Dioxygenases in Gliomas and Glioblastomas: A Review of Epigenetic Reprogramming and Hypoxic Response

Gliomas are a heterogeneous group of cancers that predominantly arise from glial cells in the brain, but may also arise from neural stem cells, encompassing low-grade glioma and high-grade glioblastoma. Whereas better diagnosis and new treatments have improved patient survival for many cancers, glioblastomas remain challenging with a highly unfavorable prognosis. This review discusses a super-family of enzymes, the 2-oxoglutarate dependent dioxygenase enzymes (2-OGDD) that control numerous processes including epigenetic modifications and oxygen sensing, and considers their many roles in the pathology of gliomas. We specifically describe in more detail the DNA and histone demethylases, and the hypoxia-inducible factor hydroxylases in the context of glioma, and discuss the substrate and cofactor requirements of the 2-OGDD enzymes. Better understanding of how these enzymes contribute to gliomas could lead to the development of new treatment strategies.

Integrated multi-omics analysis of ovarian cancer using variational autoencoders

Cancer is a complex disease that deregulates cellular functions at various molecular levels (e.g., DNA, RNA, and proteins). Integrated multi-omics analysis of data from these levels is necessary to understand the aberrant cellular functions accountable for cancer and its development. In recent years, Deep Learning (DL) approaches have become a useful tool in integrated multi-omics analysis of cancer data. However, high dimensional multi-omics data are generally imbalanced with too many molecular features and relatively few patient samples. This imbalance makes a DL based integrated multi-omics analysis difficult. DL-based dimensionality reduction technique, including variational autoencoder (VAE), is a potential solution to balance high dimensional multi-omics data. However, there are few VAE-based integrated multi-omics analyses, and they are limited to pancancer. In this work, we did an integrated multi-omics analysis of ovarian cancer using the compressed features learned through VAE and an improved version of VAE, namely Maximum Mean Discrepancy VAE (MMD-VAE). First, we designed and developed a DL architecture for VAE and MMD-VAE. Then we used the architecture for mono-omics, integrated di-omics and tri-omics data analysis of ovarian cancer through cancer samples identification, molecular subtypes clustering and classification, and survival analysis. The results show that MMD-VAE and VAE-based compressed features can respectively classify the transcriptional subtypes of the TCGA datasets with an accuracy in the range of 93.2-95.5% and 87.1-95.7%. Also, survival analysis results show that VAE and MMD-VAE based compressed representation of omics data can be used in cancer prognosis. Based on the results, we can conclude that (i) VAE and MMD-VAE outperform existing dimensionality reduction techniques, (ii) integrated multi-omics analyses perform better or similar compared to their mono-omics counterparts, and (iii) MMD-VAE performs better than VAE in most omics dataset.

Multiomics integrative analysis reveals antagonistic roles of CBX2 and CBX7 in metabolic reprogramming of breast cancer

Striking similarity exists between metabolic changes associated with embryogenesis and tumorigenesis. Chromobox proteins‐CBX2/4/6/7/8, core components of canonical polycomb repressor complex 1, play essential roles in embryonic development and aberrantly expressed in breast cancer. Understanding how altered CBX expression relates to metabolic reprogramming in breast cancer may reveal vulnerabilities of therapeutic pertinence. Using transcriptomic and metabolomic data from breast cancer patients (N > 3000 combined), we performed pathway‐based analysis and identified outstanding roles of CBX2 and CBX7 in positive and negative regulation of glucose metabolism, respectively. Genetic ablation experiments validated the contrasting roles of two isoforms in cancer metabolism and cell growth. Furthermore, we provide evidence for the role of mammalian target of rapamycin complex 1 signaling in mediating contrary effects of CBX2 and CBX7 on breast cancer metabolism. Underpinning the biological significance of metabolic roles, CBX2 and CBX7 were found to be the most up‐ and downregulated isoforms, respectively, in breast tumors compared with normal tissues. Moreover, CBX2 and CBX7 expression (not other isoforms) correlated strongly, but oppositely, with breast tumor subtype aggressiveness and the proliferation markers. Consistently, genomic data also showed higher amplification frequency of CBX2, not CBX7, in breast tumors. Highlighting the clinical significance of findings, disease‐specific survival and drug sensitivity analysis revealed that CBX2 and CBX7 predicted patient outcome and sensitivity to FDA‐approved/investigational drugs. In summary, this work identifies novel cross talk between CBX2/7 and breast tumor metabolism, and the results presented may have implications in strategies targeting breast cancer.

Metabolomic-based clinical studies and murine models for acute pancreatitis disease: A review

Acute pancreatitis (AP) is one of the most common gastroenterological disorders requiring hospitalization and is associated with substantial morbidity and mortality. Metabolomics nowadays not only help us to understand cellular metabolism to a degree that was not previously obtainable, but also to reveal the importance of the metabolites in physiological control, disease onset and development. An in-depth understanding of metabolic phenotyping would be therefore crucial for accurate diagnosis, prognosis and precise treatment of AP. In this review, we summarized and addressed the metabolomics design and workflow in AP studies, as well as the results and analysis of the in-depth of research. Based on the metabolic profiling work in both clinical populations and experimental AP models, we described the metabolites with potential utility as biomarkers and the correlation between the altered metabolites and AP status. Moreover, the disturbed metabolic pathways correlated with biological function were discussed in the end. A practical understanding of current and emerging metabolomic approaches applicable to AP and use of the metabolite information presented will aid in designing robust metabolomics and biological experiments that result in identification of unique biomarkers and mechanisms, and ultimately enhanced clinical decision-making.

Isoform-specific Activities of Androgen Receptor and its Splice Variants in Prostate Cancer Cells

Androgen receptor (AR) signaling continues to drive castration-resistant prostate cancer (CRPC) in spite of androgen deprivation therapy (ADT). Constitutively active shorter variants of AR, lacking the ligand binding domain, are frequently expressed in CRPC and have emerged as a potential mechanism for prostate cancer to escape ADT. ARv7 and ARv567es are 2 of the most commonly detected variants of AR in clinical samples of advanced, metastatic prostate cancer. It is not clear if variants of AR merely act as weaker substitutes for AR or can mediate unique isoform-specific activities different from AR. In this study, we employed LNCaP prostate cancer cell lines with inducible expression of ARv7 or ARv567es to delineate similarities and differences in transcriptomics, metabolomics, and lipidomics resulting from the activation of AR, ARv7, or ARv567es. While the majority of target genes were similarly regulated by the action of all 3 isoforms, we found a clear difference in transcriptomic activities of AR versus the variants, and a few differences between ARv7 and ARv567es. Some of the target gene regulation by AR isoforms was similar in the VCaP background as well. Differences in downstream activities of AR isoforms were also evident from comparison of the metabolome and lipidome in an LNCaP model. Overall our study implies that shorter variants of AR are capable of mediating unique downstream activities different from AR and some of these are isoform specific.

Identification of Hub Genes and Pathways of Triple Negative Breast Cancer by Expression Profiles Analysis

Purpose

Triple negative breast cancer (TNBC) is an intrinsic subtype of breast cancer with a poor prognosis, characterized by a lack of ER and PR expression and the absence of HER2 amplification. The aim of this study is to characterize hub genes (key genes in the molecular interaction network) expression in TNBC, which may serve as prognostic predictors for TNBC treatment.

Methods

Four transcriptome microarray datasets GSE27447, GSE39004, GSE43358 and GSE45827 were obtained from the Gene Expression Omnibus (GEO) database, and R package limma and RobustRankAggreg were employed to identify common differentially expressed genes (DEGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted by DAVID and KOBAS database. Thereafter, protein–protein interaction (PPI) network was constructed according to STRING online database. Functional modules and hub genes were screened by MCODE and cytohubba plug-ins, and the Cancer Genome Atlas (TCGA) survival analysis and qRT-PCR were utilized to validate the expression of these hub genes on TNBC.

Results

A total of 134 DEGs were identified by differential expression analysis, consisting of 88 up- and 46 down-regulated genes. GO and KEGG analyses showed that the terms and pathways enriched were mainly associated with cell adhesion, tumorigenesis and cellular immunity. From the PPI network, we identified six hub genes, including CD3D, CD3E, CD3G, FYN, GRAP2 and ITK. Survival analysis and the qRT-PCR results confirmed the robustness of the identified hub genes.

Conclusion

This study provides a new insight into the understanding of the molecular mechanisms associated with TNBC and suggested that the hub genes may serve as prognostic predictors.

Lilikoi V2.0: a deep learning-enabled, personalized pathway-based R package for diagnosis and prognosis predictions using metabolomics data

BACKGROUND

previously we developed Lilikoi, a personalized pathway-based method to classify diseases using metabolomics data. Given the new trends of computation in the metabolomics field, it is important to update Lilikoi software.

RESULTS

here we report the next version of Lilikoi as a significant upgrade. The new Lilikoi v2.0 R package has implemented a deep learning method for classification, in addition to popular machine learning methods. It also has several new modules, including the most significant addition of prognosis prediction, implemented by Cox-proportional hazards model and the deep learning-based Cox-nnet model. Additionally, Lilikoi v2.0 supports data preprocessing, exploratory analysis, pathway visualization, and metabolite pathway regression.

CONCULSION

Lilikoi v2.0 is a modern, comprehensive package to enable metabolomics analysis in R programming environment.

Multi-omics approaches in cancer research with applications in tumor subtyping, prognosis, and diagnosis

While cost-effective high-throughput technologies provide an increasing amount of data, the analyses of single layers of data seldom provide causal relations. Multi-omics data integration strategies across different cellular function levels, including genomes, epigenomes, transcriptomes, proteomes, metabolomes, and microbiomes offer unparalleled opportunities to understand the underlying biology of complex diseases, such as cancer. We review some of the most frequently used data integration methods and outline research areas where multi-omics significantly benefit our understanding of the process and outcome of the malignant transformation. We discuss algorithmic frameworks developed to reveal cancer subtypes, disease mechanisms, and methods for identifying driver genomic alterations and consider the significance of multi-omics in tumor classifications, diagnostics, and prognostications. We provide a comprehensive summary of each omics strategy's most recent advances within the clinical context and discuss the main challenges facing their clinical implementations. Despite its unparalleled advantages, multi-omics data integration is slow to enter everyday clinics. One major obstacle is the uneven maturity of different omics approaches and the growing gap between generating large volumes of data compared to data processing capacity. Progressive initiatives to enforce the standardization of sample processing and analytical pipelines, multidisciplinary training of experts for data analysis and interpretation are vital to facilitate the translatability of theoretical findings.

Structure, substrate specificity, and catalytic mechanism of human D-2-HGDH and insights into pathogenicity of disease-associated mutations

D-2-hydroxyglutarate dehydrogenase (D-2-HGDH) catalyzes the oxidation of D-2-hydroxyglutarate (D-2-HG) into 2-oxoglutarate, and genetic D-2-HGDH deficiency leads to abnormal accumulation of D-2-HG which causes type I D-2-hydroxyglutaric aciduria and is associated with diffuse large B-cell lymphoma. This work reports the crystal structures of human D-2-HGDH in apo form and in complexes with D-2-HG, D-malate, D-lactate, L-2-HG, and 2-oxoglutarate, respectively. D-2-HGDH comprises a FAD-binding domain, a substrate-binding domain, and a small C-terminal domain. The active site is located at the interface of the FAD-binding domain and the substrate-binding domain. The functional roles of the key residues involved in the substrate binding and catalytic reaction and the mutations identified in D-2-HGDH-deficient diseases are analyzed by biochemical studies. The structural and biochemical data together reveal the molecular mechanism of the substrate specificity and catalytic reaction of D-2-HGDH and provide insights into the pathogenicity of the disease-associated mutations.

The oncometabolite R-2-hydroxyglutarate dysregulates the differentiation of human mesenchymal stromal cells via inducing DNA hypermethylation

Background

Isocitrate dehydrogenase (IDH1/2) gene mutations are the most frequently observed mutations in cartilaginous tumors. The mutant IDH causes elevation in the levels of R-enantiomer of 2-hydroxylglutarate (R-2HG). Mesenchymal stromal cells (MSCs) are reasonable precursor cell candidates of cartilaginous tumors. This study aimed to investigate the effect of oncometabolite R-2HG on MSCs.

Methods

Human bone marrow MSCs treated with or without R-2HG at concentrations 0.1 to 1.5 mM were used for experiments. Cell Counting Kit-8 was used to detect the proliferation of MSCs. To determine the effects of R-2HG on MSC differentiation, cells were cultured in osteogenic, chondrogenic and adipogenic medium. Specific staining approaches were performed and differentiation-related genes were quantified. Furthermore, DNA methylation status was explored by Illumina array-based arrays. Real-time PCR was applied to examine the signaling component mRNAs involved in.

Results

R-2HG showed no influence on the proliferation of human MSCs. R-2HG blocked osteogenic differentiation, whereas promoted adipogenic differentiation of MSCs in a dose-dependent manner. R-2HG inhibited chondrogenic differentiation of MSCs, but increased the expression of genes related to chondrocyte hypertrophy in a lower concentration (1.0 mM). Moreover, R-2HG induced a pronounced DNA hypermethylation state of MSC. R-2HG also improved promotor methylation of lineage-specific genes during osteogenic and chondrogenic differentiation. In addition, R-2HG induced hypermethylation and decreased the mRNA levels of SHH, GLI1and GLI2, indicating Sonic Hedgehog (Shh) signaling inhibition.

Conclusions

The oncometabolite R-2HG dysregulated the chondrogenic and osteogenic differentiation of MSCs possibly via induction of DNA hypermethylation, improving the role of R-2HG in cartilaginous tumor development.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-020-07744-x.

Metabolic-Pathway-Based Subtyping of Triple-Negative Breast Cancer Reveals Potential Therapeutic Targets

Triple-negative breast cancer (TNBC) remains an unmet medical challenge. We investigated metabolic dysregulation in TNBCs by using our multi-omics database (n = 465, the largest to date). TNBC samples were classified into three heterogeneous metabolic-pathway-based subtypes (MPSs) with distinct metabolic features: MPS1, the lipogenic subtype with upregulated lipid metabolism; MPS2, the glycolytic subtype with upregulated carbohydrate and nucleotide metabolism; and MPS3, the mixed subtype with partial pathway dysregulation. These subtypes were validated by metabolomic profiling of 72 samples. These three subtypes had distinct prognoses, molecular subtype distributions, and genomic alterations. Moreover, MPS1 TNBCs were more sensitive to metabolic inhibitors targeting fatty acid synthesis, whereas MPS2 TNBCs showed higher sensitivity to inhibitors targeting glycolysis. Importantly, inhibition of lactate dehydrogenase could enhance tumor response to anti-PD-1 immunotherapy in MPS2 TNBCs. Collectively, our analysis demonstrated the metabolic heterogeneity of TNBCs and enabled the development of personalized therapies targeting unique tumor metabolic profiles.

Quantitative Analysis of Oncometabolite 2-Hydroxyglutarate

Gain-of-function mutations of isocitrate dehydrogenase 1 and 2 (IDH1/2) were demonstrated to induce the production and accumulation of oncometabolite 2-hydroxyglutarate (2HG). 2HG is a potent competitor of α-ketoglutarate (α-KG) and can inhibit multiple α-KG-dependent dioxygenases that are critical for regulating the metabolic and epigenetic state of cells. The accumulation of 2HG contributes to elevated risk of malignant tumors. 2HG carries an asymmetric carbon atom in its carbon backbone and therefore occurs in two enantiomers, D-2-hydroxyglutarate (D-2HG) and L-2-hydroxyglutarate (L-2HG). Each enantiomer is produced and metabolized in independent biochemical pathway and catalyzed by different enzymes. The accurate diagnosis of 2HG-related diseases relies on determining the configuration of the two enantiomers. Quantitative methods for analysis of D-2HG and L-2HG have been well developed. These analytical strategies mainly include the use of chiral chromatography medium to facilitate chromatographic separation of enantiomers prior to spectroscopy or mass spectrometry analysis and the use of chiral derivatization reagents to convert the enantiomers to diastereomers with differential physical and chemical properties that can improve their chromatographic separation. Here, we summarize and discuss these established methods for analysis of total 2HG as well as the determination of the enantiomers of D-2HG and L-2HG.

The Heterogeneity of Breast Cancer Metabolism

Despite advances in screening, therapy, and surveillance that have improved patient survival rates, breast cancer is still the most commonly diagnosed cancer and the second leading cause of cancer mortality among women [1]. Breast cancer is a highly heterogeneous disease rooted in a genetic basis, influenced by extrinsic stimuli, and reflected in clinical behavior. The diversity of breast cancer hormone receptor status and the expression of surface molecules have guided therapy decisions for decades; however, subtype-specific treatment often yields diverse responses due to varying tumor evolution and malignant potential. Although the mechanisms behind breast cancer heterogeneity is not well understood, available evidence suggests that studying breast cancer metabolism has the potential to provide valuable insights into the causes of these variations as well as viable targets for intervention.

In vivo assessment of glutamine anaplerosis into the TCA cycle in human pre-malignant and malignant clonal plasma cells

Background

Overexpression of c-Myc is required for the progression of pre-malignant plasma cells in monoclonal gammopathy of undetermined significance (MGUS) to malignant plasma cells in multiple myeloma (MM). c-Myc also increases glutamine anaplerosis into the tricarboxylic acid (TCA) cycle within cancer cells. Whether increased glutamine anaplerosis is associated with the progression of pre-malignant to malignant plasma cells is unknown.

Methods

Human volunteers (N = 7) and patients with MGUS (N = 11) and MM (N = 12) were prospectively recruited to undergo an intravenous infusion of ¹³C-labeled glutamine followed by a bone marrow aspiration to obtain bone marrow cells and plasma.

Results

Despite notable heterogeneity, stable isotope-resolved metabolomics (SIRM) revealed that the mean ¹³C-labeled glutamine anaplerosis into the TCA cycle was higher in malignant compared to pre-malignant bone marrow plasma cells relative to the remainder of their paired bone marrow mononuclear cells. RNA sequencing demonstrated a higher relative mRNA expression of c-Myc and glutamine transporters such as ASCT2 and SN2 in malignant compared to pre-malignant bone marrow plasma cells. Finally, higher quantitative levels of TCA cycle intermediates in the bone marrow plasma differentiated MM from MGUS patients.

Conclusion

Measurement of the in vivo activity of glutamine anaplerosis into the TCA cycle provides novel insight into the metabolic changes associated with the transformation of pre-malignant plasma cells in MGUS to malignant plasma cells in MM.

Trial registration

NCT03384108 and NCT03119883

Cancer stem cells: Culprits in endocrine resistance and racial disparities in breast cancer outcomes

Breast cancer stem cells (BCSCs) promote endocrine therapy (ET) resistance, also known as endocrine resistance in hormone receptor (HR) positive breast cancer. Endocrine resistance occurs via mechanisms that are not yet fully understood. In vitro, in vivo and clinical data suggest that signaling cascades such as Notch, hypoxia inducible factor (HIF), and integrin/Akt promote BCSC-mediated endocrine resistance. Once HR positive breast cancer patients relapse on ET, targeted therapy agents such as cyclin dependent kinase inhibitors are frequently implemented, though secondary resistance remains a threat. Here, we discuss Notch, HIF, and integrin/Akt pathway regulation of BCSC activity and potential strategies to target these pathways to counteract endocrine resistance. We also discuss a plausible link between elevated BCSC-regulatory gene levels and reduced survival observed among African American women with basal-like breast cancer which lacks HR expression. Should future studies reveal a similar link for patients with luminal breast cancer, then the use of agents that impede BCSC activity could prove highly effective in improving clinical outcomes among African American breast cancer patients.

TNFAIP8 drives metabolic reprogramming to promote prostate cancer cell proliferation

Tumor necrosis factor-α-induced protein 8 (TNFAIP8) is a member of TIPE/TNFAIP8 family, has been involved in the development and progression of various human cancers. We hypothesized that TNFAIP8 promotes prostate cancer (PCa) progression via regulation of oxidative phosphorylation (OXPHOS) and glycolysis. Ectopic expression of TNFAIP8 increased PCa cell proliferation/migration/spheroid formation by enhancing cell metabolic activities. Mechanistically, TNFAIP8 activated the PI3K-AKT pathway and up-regulated PCa cell survival. TNFAIP8 was also found to regulate the expression of glucose metabolizing enzymes, enhancing glucose consumption, and endogenous ATP production. Treatment with a glycolysis inhibitor, 2-deoxyglucose (2-DG), reduced TNFAIP8 mediated glucose consumption, ATP production, spheroid formation, and PCa cell migration. By maintaining mitochondrial membrane potential, TNFAIP8 increased OXPHOS and glycolysis. Moreover, TNFAIP8 modulates the production of glycolytic metabolites in PCa cells. Collectively, our data suggest that TNFAIP8 exerts its oncogenic effects by enhancing glucose metabolism and by facilitating metabolic reprogramming in PCa cells. Therefore, TNFAIP8 may be a biomarker associated with prostate cancer and indicate a potential therapeutic target.

Acetate Revisited: A Key Biomolecule at the Nexus of Metabolism, Epigenetics, and Oncogenesis - Part 2: Acetate and ACSS2 in Health and Disease

Acetate, the shortest chain fatty acid, has been implicated in providing health benefits whether it is derived from the diet or is generated from microbial fermentation of fiber in the gut. These health benefits range widely from improved cardiac function to enhanced red blood cell generation and memory formation. Understanding how acetate could influence so many disparate biological functions is now an area of intensive research. Protein acetylation is one of the most common post-translational modifications and increased systemic acetate strongly drives protein acetylation. By virtue of acetylation impacting the activity of virtually every class of protein, acetate driven alterations in signaling and gene transcription have been associated with several common human diseases, including cancer. In part 2 of this review, we will focus on some of the roles that acetate plays in health and human disease. The acetate-activating enzyme acyl-CoA short-chain synthetase family member 2 (ACSS2) will be a major part of that focus due to its role in targeted protein acetylation reactions that can regulate central metabolism and stress responses. ACSS2 is the only known enzyme that can recycle acetate derived from deacetylation reactions in the cytoplasm and nucleus of cells, including both protein and metabolite deacetylation reactions. As such, ACSS2 can recycle acetate derived from histone deacetylase reactions as well as protein deacetylation reactions mediated by sirtuins, among many others. Notably, ACSS2 can activate acetate released from acetylated metabolites including N-acetylaspartate (NAA), the most concentrated acetylated metabolite in the human brain. NAA has been associated with the metabolic reprograming of cancer cells, where ACSS2 also plays a role. Here, we discuss the context-specific roles that acetate can play in health and disease.

2-Hydroxyglutarate in Cancer Cells

Significance: Cancer cells are stabilized in an undifferentiated state similar to stem cells. This leads to profound modifications of their metabolism, which further modifies their genetics and epigenetics as malignancy progresses. Specific metabolites and enzymes may serve as clinical markers of cancer progression. Recent Advances: Both 2-hydroxyglutarate (2HG) enantiomers are associated with reprogrammed metabolism, in grade III/IV glioma, glioblastoma, and acute myeloid leukemia cells, and numerous other cancer types, while acting also in the cross talk of tumors with immune cells. 2HG contributes to specific alternations in cancer metabolism and developed oxidative stress, while also inducing decisions on the differentiation of naive T lymphocytes, and serves as a signal messenger in immune cells. Moreover, 2HG inhibits chromatin-modifying enzymes, namely 2-oxoglutarate-dependent dioxygenases, and interferes with hypoxia-inducible factor (HIF) transcriptome reprogramming and mammalian target of rapamycin (mTOR) pathway, thus dysregulating gene expression and further promoting cancerogenesis. Critical Issues: Typically, heterozygous mutations within the active sites of isocitrate dehydrogenase isoform 1 (IDH1)^R132H and mitochondrial isocitrate dehydrogenase isoform 2 (IDH2)^R140Q provide cells with millimolar r-2-hydroxyglutarate (r-2HG) concentrations, whereas side activities of lactate and malate dehydrogenase form submillimolar s-2-hydroxyglutarate (s-2HG). However, even wild-type IDH1 and IDH2, notably under shifts toward reductive carboxylation glutaminolysis or changes in other enzymes, lead to "intermediate" 0.01-0.1 mM 2HG levels, for example, in breast carcinoma compared with 10^-8M in noncancer cells. Future Directions: Uncovering further molecular metabolism details specific for given cancer cell types and sequence-specific epigenetic alternations will lead to the design of diagnostic approaches, not only for predicting patients' prognosis or uncovering metastases and tumor remissions but also for early diagnostics.

The use of multi-omics data and approaches in breast cancer immunotherapy: a review

Breast cancer is projected to be the most common cancer in women in 2020 in the USA. Despite high remission rates treatment side effects remain an issue, hence the interest in novel approaches such as immunotherapies which aim to utilize patients' immune systems to target cancer cells. This review summarizes the basics of breast cancer including staging and treatment options, followed by a discussion on immunotherapy, including immune checkpoint blockade. After this, examples of the role of omics-type data and computational biology/bioinformatics in breast cancer are explored. Ultimately, there are several promising areas to investigate such as the prediction of neoantigens and the use of multi-omics data to direct research, with noted appropriate in clinical trial design in terms of end points.

Biological Networks Regulating Cell Fate Choice Are Minimally Frustrated

Characterization of the differences between biological and random networks can reveal the design principles that enable the robust realization of crucial biological functions including the establishment of different cell types. Previous studies, focusing on identifying topological features that are present in biological networks but not in random networks, have, however, provided few functional insights. We use a Boolean modeling framework and ideas from the spin glass literature to identify functional differences between five real biological networks and random networks with similar topological features. We show that minimal frustration is a fundamental property that allows biological networks to robustly establish cell types and regulate cell fate choice, and that this property can emerge in complex networks via Darwinian evolution. The study also provides clues regarding how the regulation of cell fate choice can go awry in a disease like cancer and lead to the emergence of aberrant cell types.

Metabonomic study of the intervention effects of Parthenolide on anti-thyroid cancer activity

Thyroid cancer is the most common endocrine malignant tumor in the world, and its incidence is increasing. Although the mortality rate of thyroid cancer is low, its persistence/recurrence rate is high. In addition, some patients with thyroid cancer fail to respond to radiation. Therefore, it is urgent need to develop a novel treatment for thyroid cancer. Parthenolide (PTL), a traditional Chinese medicine Tanacetum parthenium extract, has shown encouraging effects in anti-tumor, anti-inflammatory and anti-malaria. However, it is unclear whether PTL has an anti-thyroid cancer effect and its possible mechanism of action. In the recent years, metabonomics has been widely used in tumors research to explore the pharmacological mechanism of drugs, but few studies used metabonomics to investigate the pharmacological effects of PTL in thyroid tumors. In order to comprehensively reveal the mechanism and effects of PTL on anti-thyroid tumors, metabonomics combined cell biological research methods were conducted. The results showed that PTL promote apoptosis of thyroid cancer cells (TPC-1) in a concentration-dependent manner. The metabolic differences between the PTL group and the control group were compared by metabonomics, and 31 potential metabolites were identified. These metabolites were mainly involved in the tricarboxylic acid cycle, amino acid metabolism, choline metabolism and lipid metabolism. These results implied that PTL may inhibit the proliferation and development of thyroid carcinoma by accelerating oxidation emergency response, inhibiting adenosine triphosphate (ATP) synthesis and metabolic imbalance. The results of this study revealed that PTL can be an effective and potential drug for the treatment of thyroid cancer.

Immune Cell Associations with Cancer Risk

Proper immune system function hinders cancer development, but little is known about whether genetic variants linked to cancer risk alter immune cells. Here, we report 57 cancer risk loci associated with differences in immune and/or stromal cell contents in the corresponding tissue. Predicted target genes show expression and regulatory associations with immune features. Polygenic risk scores also reveal associations with immune and/or stromal cell contents, and breast cancer scores show consistent results in normal and tumor tissue. SH2B3 links peripheral alterations of several immune cell types to the risk of this malignancy. Pleiotropic SH2B3 variants are associated with breast cancer risk in BRCA1/2 mutation carriers. A retrospective case-cohort study indicates a positive association between blood counts of basophils, leukocytes, and monocytes and age at breast cancer diagnosis. These findings broaden our knowledge of the role of the immune system in cancer and highlight promising prevention strategies for individuals at high risk.

Metabolite sensing and signaling in cancer

Metabolites are not only substrates in metabolic reactions, but also signaling molecules controlling a wide range of cellular processes. Discovery of the oncometabolite 2-hydroxyglutarate provides an important link between metabolic dysfunction and cancer, unveiling the signaling function of metabolites in regulating epigenetic and epitranscriptomic modifications, genome integrity, and signal transduction. It is now known that cancer cells remodel their metabolic network to support biogenesis, caused by or resulting in the dysregulation of various metabolites. Cancer cells can sense alterations in metabolic intermediates to better coordinate multiple biological processes and enhance cell metabolism. Recent studies have demonstrated that metabolite signaling is involved in the regulation of malignant transformation, cell proliferation, epithelial-to-mesenchymal transition, differentiation blockade, and cancer stemness. Additionally, intercellular metabolite signaling modulates inflammatory response and immunosurveillance in the tumor microenvironment. Here, we review recent advances in cancer-associated metabolite signaling. An in depth understanding of metabolite signaling will provide new opportunities for the development of therapeutic interventions that target cancer.

A DNA Methylation-Based Panel for the Prognosis and Dagnosis of Patients With Breast Cancer and Its Mechanisms

Objective

To identify DNA methylation related biomarkers in patients with breast cancer (BC).

Materials and Methods

A total of seven BC methylation studies including 1,438 BC patients or breast tissues were included in this study. An elastic net regularized Cox proportional hazards regression (CPH) model was used to build a multi-5′-C-phosphate-G-3′ methylation panel. The diagnosis and prognosis power of the panel was evaluated and validated using a Kaplan–Meier curve, univariate and multivariable CPH, subgroup analysis. A nomogram containing the panel was developed. The relationships between the panel-based methylation risk and the immune landscape and genomic metrics were investigated.

Results

Sixty-eight CpG sites were significantly correlated with the overall survival (OS) of BC patients, and based on the result of penalized CPH, a 28-CpG site based multi CpG methylation panel was found. The prognosis and diagnosis role of the panel was validated in the discovery set, validation set, and six independent cohorts, which indicated that higher methylation risk was associated with poor OS, and the panel outperformed currently available biomarkers and remained an independent factor after adjusting for other clinical features. The methylation risk was negatively correlated with innated and adaptive immune cells, and positively correlated with total mutation load, SCNA, and MATH.

Conclusions

We validated a multi CpG methylation panel that could independently predict the OS of BC patients. The Th2-mediated tumor promotion effect—suppression of innate and adaptive immunity—participated in the progression of high-risk BC. Patients with high methylation risk were associated with tumor heterogeneity and poor survival.

Tumor Cell-Intrinsic Immunometabolism and Precision Nutrition in Cancer Immunotherapy

One of the greatest challenges in the cancer immunotherapy field is the need to biologically rationalize and broaden the clinical utility of immune checkpoint inhibitors (ICIs). The balance between metabolism and immune response has critical implications for overcoming the major weaknesses of ICIs, including their lack of universality and durability. The last decade has seen tremendous advances in understanding how the immune system's ability to kill tumor cells requires the conspicuous metabolic specialization of T-cells. We have learned that cancer cell-associated metabolic activities trigger shifts in the abundance of some metabolites with immunosuppressory roles in the tumor microenvironment. Yet very little is known about the tumor cell-intrinsic metabolic traits that control the immune checkpoint contexture in cancer cells. Likewise, we lack a comprehensive understanding of how systemic metabolic perturbations in response to dietary interventions can reprogram the immune checkpoint landscape of tumor cells. We here review state-of-the-art molecular- and functional-level interrogation approaches to uncover how cell-autonomous metabolic traits and diet-mediated changes in nutrient availability and utilization might delineate new cancer cell-intrinsic metabolic dependencies of tumor immunogenicity. We propose that clinical monitoring and in-depth molecular evaluation of the cancer cell-intrinsic metabolic traits involved in primary, adaptive, and acquired resistance to cancer immunotherapy can provide the basis for improvements in therapeutic responses to ICIs. Overall, these approaches might guide the use of metabolic therapeutics and dietary approaches as novel strategies to broaden the spectrum of cancer patients and indications that can be effectively treated with ICI-based cancer immunotherapy.