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

The tRNA Gm18 methyltransferase TARBP1 promotes hepatocellular carcinoma progression via metabolic reprogramming of glutamine

Cancer cells rely on metabolic reprogramming to sustain the prodigious energetic requirements for rapid growth and proliferation. Glutamine metabolism is frequently dysregulated in cancers and is being exploited as a potential therapeutic target. Using CRISPR/Cas9 interference (CRISPRi) screening, we identified TARBP1 (TAR (HIV-1) RNA Binding Protein 1) as a critical regulator involved in glutamine reliance of cancer cell. Consistent with this discovery, TARBP1 amplification and overexpression are frequently observed in various cancers. Knockout of TARBP1 significantly suppresses cell proliferation, colony formation and xenograft tumor growth. Mechanistically, TARBP1 selectively methylates and stabilizes a small subset of tRNAs, which promotes efficient protein synthesis of glutamine transporter-ASCT2 (also known as SLC1A5) and glutamine import to fuel the growth of cancer cell. Moreover, we found that the gene expression of TARBP1 and ASCT2 are upregulated in combination in clinical cohorts and their upregulation is associated with unfavorable prognosis of HCC (hepatocellular carcinoma). Taken together, this study reveals the unexpected role of TARBP1 in coordinating the tRNA availability and glutamine uptake during HCC progression and provides a potential target for tumor therapy.

The bioenergetic landscape of cancer

Bioenergetic remodeling of core energy metabolism is essential to the initiation, survival, and progression of cancer cells through exergonic supply of adenosine triphosphate (ATP) and metabolic intermediates, as well as control of redox homeostasis. Mitochondria are evolutionarily conserved organelles that mediate cell survival by conferring energetic plasticity and adaptive potential. Mitochondrial ATP synthesis is coupled to the oxidation of a variety of substrates generated through diverse metabolic pathways. As such, inhibition of the mitochondrial bioenergetic system by restricting metabolite availability, direct inhibition of the respiratory Complexes, altering organelle structure, or coupling efficiency may restrict carcinogenic potential and cancer progression. Here, we review the role of bioenergetics as the principal conductor of energetic functions and carcinogenesis while highlighting the therapeutic potential of targeting mitochondrial functions.

Cancer-associated fibroblast-derived gene signature discriminates distinct prognoses by integrated single-cell and bulk RNA-seq analyses in breast cancer

BACKGROUND

Cancer-associated fibroblasts (CAFs) are one of the most predominant cellular subpopulations in the tumor stroma and play an integral role in cancer occurrence and progression. However, the prognostic role of CAFs in breast cancer remains poorly understood.

METHODS

We identified a number of CAF-related biomarkers in breast cancer by combining single-cell and bulk RNA-seq analyses. Based on univariate Cox regression as well as Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis, a novel CAF-associated prognostic model was developed. Breast cancer patients were grouped according to the median risk score and further analyzed for outcome, clinical characteristic, pathway activity, genomic feature, immune landscape, and drug sensitivity.

RESULTS

A total of 341 CAF-related biomarkers were identified from single-cell and bulk RNA-seq analyses. We eventually screened eight candidate prognostic genes, including CERCAM, EMP1, SDC1, PRKG1, XG, TNN, WLS, and PDLIM4, and constructed the novel CAF-related prognostic model. Grouped by the median risk score, high-risk patients showed a significantly worse prognosis and exhibited distinct pathway activities such as uncontrolled cell cycle progression, angiogenesis, and activation of glycolysis. In addition, the combined risk score and tumor mutation burden significantly improved the ability to predict patient prognosis. Importantly, patients in the high-risk group had a higher infiltration of M2 macrophages and a lower infiltration of CD8+ T cells and activated NK cells. Finally, we calculated the IC50 for a range of anticancer drugs and personalized the treatment regimen for each patient.

CONCLUSION

Integrating single-cell and bulk RNA-seq analyses, we identified a list of compositive CAF-associated biomarkers and developed a novel CAF-related prognostic model for breast cancer. This robust CAF-derived gene signature acts as an excellent predictor of patient outcomes and treatment responses in breast cancer.

Abnormal changes in metabolites caused by m6A methylation modification: The leading factors that induce the formation of immunosuppressive tumor microenvironment and their promising potential for clinical application

BACKGROUND

N6-methyladenosine (m6A) RNA methylation modifications have been widely implicated in the metabolic reprogramming of various cell types within the tumor microenvironment (TME) and are essential for meeting the demands of cellular growth and maintaining tissue homeostasis, enabling cells to adapt to the specific conditions of the TME. An increasing number of research studies have focused on the role of m6A modifications in glucose, amino acid and lipid metabolism, revealing their capacity to induce aberrant changes in metabolite levels. These changes may in turn trigger oncogenic signaling pathways, leading to substantial alterations within the TME. Notably, certain metabolites, including lactate, succinate, fumarate, 2-hydroxyglutarate (2-HG), glutamate, glutamine, methionine, S-adenosylmethionine, fatty acids and cholesterol, exhibit pronounced deviations from normal levels. These deviations not only foster tumorigenesis, proliferation and angiogenesis but also give rise to an immunosuppressive TME, thereby facilitating immune evasion by the tumor.

AIM OF REVIEW

The primary objective of this review is to comprehensively discuss the regulatory role of m6A modifications in the aforementioned metabolites and their potential impact on the development of an immunosuppressive TME through metabolic alterations.

KEY SCIENTIFIC CONCEPTS OF REVIEW

This review aims to elaborate on the intricate networks governed by the m6A-metabolite-TME axis and underscores its pivotal role in tumor progression. Furthermore, we delve into the potential implications of the m6A-metabolite-TME axis for the development of novel and targeted therapeutic strategies in cancer research.

Integrated multiomic profiling of breast cancer in the Chinese population reveals patient stratification and therapeutic vulnerabilities

Molecular profiling guides precision treatment of breast cancer; however, Asian patients are underrepresented in publicly available large-scale studies. We established a comprehensive multiomics cohort of 773 Chinese patients with breast cancer and systematically analyzed their genomic, transcriptomic, proteomic, metabolomic, radiomic and digital pathology characteristics. Here we show that compared to breast cancers in white individuals, Asian individuals had more targetable AKT1 mutations. Integrated analysis revealed a higher proportion of HER2-enriched subtype and correspondingly more frequent ERBB2 amplification and higher HER2 protein abundance in the Chinese HR+HER2+ cohort, stressing anti-HER2 therapy for these individuals. Furthermore, comprehensive metabolomic and proteomic analyses revealed ferroptosis as a potential therapeutic target for basal-like tumors. The integration of clinical, transcriptomic, metabolomic, radiomic and pathological features allowed for efficient stratification of patients into groups with varying recurrence risks. Our study provides a public resource and new insights into the biology and ancestry specificity of breast cancer in the Asian population, offering potential for further precision treatment approaches.

Prediction of metabolites associated with somatic mutations in cancers by using genome-scale metabolic models and mutation data

BACKGROUND

Oncometabolites, often generated as a result of a gene mutation, show pro-oncogenic function when abnormally accumulated in cancer cells. Identification of such mutation-associated metabolites will facilitate developing treatment strategies for cancers, but is challenging due to the large number of metabolites in a cell and the presence of multiple genes associated with cancer development.

RESULTS

Here we report the development of a computational workflow that predicts metabolite-gene-pathway sets. Metabolite-gene-pathway sets present metabolites and metabolic pathways significantly associated with specific somatic mutations in cancers. The computational workflow uses both cancer patient-specific genome-scale metabolic models (GEMs) and mutation data to generate metabolite-gene-pathway sets. A GEM is a computational model that predicts reaction fluxes at a genome scale and can be constructed in a cell-specific manner by using omics data. The computational workflow is first validated by comparing the resulting metabolite-gene pairs with multi-omics data (i.e., mutation data, RNA-seq data, and metabolome data) from acute myeloid leukemia and renal cell carcinoma samples collected in this study. The computational workflow is further validated by evaluating the metabolite-gene-pathway sets predicted for 18 cancer types, by using RNA-seq data publicly available, in comparison with the reported studies. Therapeutic potential of the resulting metabolite-gene-pathway sets is also discussed.

CONCLUSIONS

Validation of the metabolite-gene-pathway set-predicting computational workflow indicates that a decent number of metabolites and metabolic pathways appear to be significantly associated with specific somatic mutations. The computational workflow and the resulting metabolite-gene-pathway sets will help identify novel oncometabolites and also suggest cancer treatment strategies.

Structure and biochemical characterization of l-2-hydroxyglutarate dehydrogenase and its role in the pathogenesis of l-2-hydroxyglutaric aciduria

l-2-hydroxyglutarate dehydrogenase (L2HGDH) is a mitochondrial membrane-associated metabolic enzyme, which catalyzes the oxidation of l-2-hydroxyglutarate (l-2-HG) to 2-oxoglutarate (2-OG). Mutations in human L2HGDH lead to abnormal accumulation of l-2-HG, which causes a neurometabolic disorder named l-2-hydroxyglutaric aciduria (l-2-HGA). Here, we report the crystal structures of Drosophila melanogaster L2HGDH (dmL2HGDH) in FAD-bound form and in complex with FAD and 2-OG and show that dmL2HGDH exhibits high activity and substrate specificity for l-2-HG. dmL2HGDH consists of an FAD-binding domain and a substrate-binding domain, and the active site is located at the interface of the two domains with 2-OG binding to the re-face of the isoalloxazine moiety of FAD. Mutagenesis and activity assay confirmed the functional roles of key residues involved in the substrate binding and catalytic reaction and showed that most of the mutations of dmL2HGDH equivalent to l-2-HGA-associated mutations of human L2HGDH led to complete loss of the activity. The structural and biochemical data together reveal the molecular basis for the substrate specificity and catalytic mechanism of L2HGDH and provide insights into the functional roles of human L2HGDH mutations in the pathogeneses of l-2-HGA.

SLC38A5 promotes glutamine metabolism and inhibits cisplatin chemosensitivity in breast cancer

BACKGROUND

Solute carrier family 38 member 5 (SLC38A5), as an amino acid transporter, play a vital role in cellular biological processes. In this study, we analyzed the function of SLC38A5 and its potential mechanism in breast cancer (BC) progression.

METHODS

The expression of SLC38A5 in cancer and adjacent-normal tissues was analyzed by qRT-PCR and Western blot, and its correlation with patient prognosis was analyzed. The immunohistochemical staining of cancer tissues and adjacent-normal tissues was performed on SLC38A5-positive specimens. BC mice were successfully applied to examine the role of SLC38A5 on tumor proliferation using the CCK-8 assay. In BC cells and mouse tumor tissues, SLC38A5 and PCNA expression were determined by Western blotting.

RESULTS

The study found that SLC38A5 was highly expressed in BC patients and associated with a poor survival. SLC38A5 silencing inhibited BC cell viability and glutamine uptake. In addition, SLC38A5 overexpression promoted BC cell viability via the glutamine metabolism. SLC38A5 inhibited cisplatin chemosensitivity in BC cells. Importantly, SLC38A5 silencing inhibited tumor growth in vivo.

CONCLUSION

Our findings suggest that SLC38A5 enhances BC cell viability by glutamine metabolism, inhibits the chemical sensitivity of cisplatin in BC cells, and promotes tumor growth, emphasizing the clinical relevance of SLC38A5 in BC management as a novel potential therapeutic target.

SERPINB3-MYC axis induces the basal-like/squamous subtype and enhances disease progression in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) exhibits distinct molecular subtypes: classical/progenitor and basal-like/squamous. Our study aimed to identify genes contributing to the development of the basal-like/squamous subtype, known for its aggressiveness. Transcriptome analyses revealed consistent upregulation of SERPINB3 in basal-like/squamous PDAC, correlating with reduced patient survival. SERPINB3 transgene expression in PDAC cells enhanced in vitro invasion and promoted lung metastasis in a mouse PDAC xenograft model. Metabolome analyses unveiled a metabolic signature linked to both SERPINB3 and the basal-like/squamous subtype, characterized by heightened carnitine/acylcarnitine and amino acid metabolism, associated with poor prognosis in patients with PDAC and elevated cellular invasiveness. Further analysis uncovered that SERPINB3 inhibited the cysteine protease calpain, a key enzyme in the MYC degradation pathway, and drove basal-like/squamous subtype and associated metabolic reprogramming through MYC activation. Our findings indicate that the SERPINB3-MYC axis induces the basal-like/squamous subtype, proposing SERPINB3 as a potential diagnostic and therapeutic target for this variant.

Diabetes-associated breast cancer is molecularly distinct and shows a DNA damage repair deficiency

Diabetes commonly affects patients with cancer. We investigated the influence of diabetes on breast cancer biology using a 3-pronged approach that included analysis of orthotopic human tumor xenografts, patient tumors, and breast cancer cells exposed to diabetes/hyperglycemia-like conditions. We aimed to identify shared phenotypes and molecular signatures by investigating the metabolome, transcriptome, and tumor mutational burden. Diabetes and hyperglycemia did not enhance cell proliferation but induced mesenchymal and stem cell-like phenotypes linked to increased mobility and odds of metastasis. They also promoted oxyradical formation and both a transcriptome and mutational signatures of DNA repair deficiency. Moreover, food- and microbiome-derived metabolites tended to accumulate in breast tumors in the presence of diabetes, potentially affecting tumor biology. Breast cancer cells cultured under hyperglycemia-like conditions acquired increased DNA damage and sensitivity to DNA repair inhibitors. Based on these observations, we conclude that diabetes-associated breast tumors may show an increased drug response to DNA damage repair inhibitors.

Population-specific Mutation Patterns in Breast Tumors from African American, European American, and Kenyan Patients

Women of African descent have the highest breast cancer mortality in the United States and are more likely than women from other population groups to develop an aggressive disease. It remains uncertain to what extent breast cancer in Africa is reminiscent of breast cancer in African American or European American patients. Here, we performed whole-exome sequencing of genomic DNA from 191 breast tumor and non-cancerous adjacent tissue pairs obtained from 97 African American, 69 European American, 2 Asian American, and 23 Kenyan patients. Our analysis of the sequencing data revealed an elevated tumor mutational burden in both Kenyan and African American patients, when compared with European American patients. TP53 mutations were most prevalent, particularly in African American patients, followed by PIK3CA mutations, which showed similar frequencies in European American, African American, and the Kenyan patients. Mutations targeting TBX3 were confined to European Americans and those targeting the FBXW7 tumor suppressor to African American patients whereas mutations in the ARID1A gene that are known to confer resistance to endocrine therapy were distinctively enriched among Kenyan patients. A Kyoto Encyclopedia of Genes and Genomes pathway analysis could link FBXW7 mutations to an increased mitochondrial oxidative phosphorylation capacity in tumors carrying these mutations. Finally, Catalogue of Somatic Mutations in Cancer (COSMIC) mutational signatures in tumors correlated with the occurrence of driver mutations, immune cell profiles, and neighborhood deprivation with associations ranging from being mostly modest to occasionally robust. To conclude, we found mutational profiles that were different between these patient groups. The differences concentrated among genes with low mutation frequencies in breast cancer.

SIGNIFICANCE

The study describes differences in tumor mutational profiles between African American, European American, and Kenyan breast cancer patients. It also investigates how these profiles may relate to the tumor immune environment and the neighborhood environment in which the patients had residence. Finally, it describes an overrepresentation of ARID1A gene mutations in breast tumors of the Kenyan patients.

Metabolic stratification of human breast tumors reveal subtypes of clinical and therapeutic relevance

Extensive metabolic heterogeneity in breast cancers has limited the deployment of metabolic therapies. To enable patient stratification, we studied the metabolic landscape in breast cancers (∼3000 patients combined) and identified three subtypes with increasing degrees of metabolic deregulation. Subtype M1 was found to be dependent on bile-acid biosynthesis, whereas M2 showed reliance on methionine pathway, and M3 engaged fatty-acid, nucleotide, and glucose metabolism. The extent of metabolic alterations correlated strongly with tumor aggressiveness and patient outcome. This pattern was reproducible in independent datasets and using in vivo tumor metabolite data. Using machine-learning, we identified robust and generalizable signatures of metabolic subtypes in tumors and cell lines. Experimental inhibition of metabolic pathways in cell lines representing metabolic subtypes revealed subtype-specific sensitivity, therapeutically relevant drugs, and promising combination therapies. Taken together, metabolic stratification of breast cancers can thus aid in predicting patient outcome and designing precision therapies.

Evaluating Stacked Methylation Markers for Blood-Based Multicancer Detection

The ability to detect several types of cancer using a non-invasive, blood-based test holds the potential to revolutionize oncology screening. We mined tumor methylation array data from the Cancer Genome Atlas (TCGA) covering 14 cancer types and identified two novel, broadly-occurring methylation markers at TLX1 and GALR1. To evaluate their performance as a generalized blood-based screening approach, along with our previously reported methylation biomarker, ZNF154, we rigorously assessed each marker individually or combined. Utilizing TCGA methylation data and applying logistic regression models within each individual cancer type, we found that the three-marker combination significantly increased the average area under the ROC curve (AUC) across the 14 tumor types compared to single markers (p = 1.158 × 10-10; Friedman test). Furthermore, we simulated dilutions of tumor DNA into healthy blood cell DNA and demonstrated increased AUC of combined markers across all dilution levels. Finally, we evaluated assay performance in bisulfite sequenced DNA from patient tumors and plasma, including early-stage samples. When combining all three markers, the assay correctly identified nine out of nine lung cancer plasma samples. In patient plasma from hepatocellular carcinoma, ZNF154 alone yielded the highest combined sensitivity and specificity values averaging 68% and 72%, whereas multiple markers could achieve higher sensitivity or specificity, but not both. Altogether, this study presents a comprehensive pipeline for the identification, testing, and validation of multi-cancer methylation biomarkers with a considerable potential for detecting a broad range of cancer types in patient blood samples.

NR1D1 Stimulates Antitumor Immune Responses in Breast Cancer by Activating cGAS-STING Signaling

Potentiating antitumor immunity is a promising therapeutic approach for treating a variety of cancers, including breast cancer. One potential strategy to promote antitumor immunity is targeting DNA damage response. Given that the nuclear receptor NR1D1 (also known as REV-ERBα) inhibits DNA repair in breast cancer cells, we explored the role of NR1D1 in antitumor CD8+ T-cell responses. First, deletion of Nr1d1 in MMTV-PyMT transgenic mice resulted in increased tumor growth and lung metastasis. Orthotopic allograft experiments suggested that loss of Nr1d1 in tumor cells rather than in stromal cells played a prominent role in increasing tumor progression. Comprehensive transcriptome analyses revealed that biological processes including type I IFN signaling and T cell-mediated immune responses were associated with NR1D1. Indeed, the expression of type I IFNs and infiltration of CD8+ T cells and natural killer cells in tumors were suppressed in Nr1d1-/-;MMTV-PyMT mice. Mechanistically, NR1D1 promoted DNA damage-induced accumulation of cytosolic DNA fragments and activated cGAS-STING signaling, which increased the production of type I IFNs and downstream chemokines CCL5 and CXCL10. Pharmacologic activation of NR1D1 by its ligand, SR9009, enhanced type I IFN-mediated antitumor immunity accompanied by the suppression of tumor progression and lung metastasis. Taken together, these findings reveal the critical role of NR1D1 in enhancing antitumor CD8+ T-cell responses, suggesting that NR1D1 may be a good therapeutic target for breast cancer.

SIGNIFICANCE

NR1D1 suppresses breast cancer progression and lung metastasis by enhancing antitumor immunity via cGAS-STING pathway activation, which provides potential immunotherapeutic strategies for breast cancer.

Identification of metabolic pathways contributing to ER+ breast cancer disparities using a machine-learning pipeline

African American (AA) women in the United States have a 40% higher breast cancer mortality rate than Non-Hispanic White (NHW) women. The survival disparity is particularly striking among (estrogen receptor positive) ER+ breast cancer cases. The purpose of this study is to examine whether there are racial differences in metabolic pathways typically activated in patients with ER+ breast cancer. We collected pretreatment plasma from AA and NHW ER+ breast cancer cases (AA n = 48, NHW n = 54) and cancer-free controls (AA n = 100, NHW n = 48) to conduct an untargeted metabolomics analysis using gas chromatography mass spectrometry (GC-MS) to identify metabolites that may be altered in the different racial groups. Unpaired t-test combined with multiple feature selection and prediction models were employed to identify race-specific altered metabolic signatures. This was followed by the identification of altered metabolic pathways with a focus in AA patients with breast cancer. The clinical relevance of the identified pathways was further examined in PanCancer Atlas breast cancer data set from The Cancer Genome Atlas Program (TCGA). We identified differential metabolic signatures between NHW and AA patients. In AA patients, we observed decreased circulating levels of amino acids compared to healthy controls, while fatty acids were significantly higher in NHW patients. By mapping these metabolites to potential epigenetic regulatory mechanisms, this study identified significant associations with regulators of metabolism such as methionine adenosyltransferase 1A (MAT1A), DNA Methyltransferases and Histone methyltransferases for AA individuals, and Fatty acid Synthase (FASN) and Monoacylglycerol lipase (MGL) for NHW individuals. Specific gene Negative Elongation Factor Complex E (NELFE) with histone methyltransferase activity, was associated with poor survival exclusively for AA individuals. We employed a comprehensive and novel approach that integrates multiple machine learning and statistical methods, coupled with human functional pathway analyses. The metabolic profile of plasma samples identified may help elucidate underlying molecular drivers of disproportionately aggressive ER+ tumor biology in AA women. It may ultimately lead to the identification of novel therapeutic targets. To our knowledge, this is a novel finding that describes a link between metabolic alterations and epigenetic regulation in AA breast cancer and underscores the need for detailed investigations into the biological underpinnings of breast cancer health disparities.

A bacterial enzyme may correct 2-HG accumulation in human cancers

A significant proportion of lower-grade glioma as well as many other types of human cancers are associated with neomorphic mutations in IDH1/2 genes (mIDH1/2). These mutations lead to an aberrant accumulation of 2-hydroxyglutarate (2-HG). Interestingly, even cancers without mIDH1/2 can exhibit increased levels of 2-HG due to factors like hypoxia and extracellular acidity. Mounting evidence demonstrates that 2-HG competitively inhibits α-ketoglutarate dependent enzymes, such as JmjC-domain-containing histone demethylases (JHDMs), ten-eleven translocation enzymes (TETs), and various dioxygenases (e.g., RNA m6A demethylases and prolyl hydroxylases). Consequently, the hypermethylation of DNA, RNA, and histones, and the abnormal activities of hypoxia-inducible factors (HIFs) have profound impacts on the establishment of cancer metabolism and microenvironment, which promote tumor progression. This connection between the oncometabolite 2-HG and glioma holds crucial implications for treatments targeting this disease. Here, I hypothesize that an ectopic introduction of a bacterial 2-hydroxyglutarate synthase (2-HG synthase) enzyme into cancer cells with 2-HG accumulation could serve as a promising enzyme therapy for glioma and other types of cancers. While absent in human metabolism, 2-HG synthase in bacterial species catalyzes the conversion of 2-HG into propionyl-CoA and glyoxylate, two metabolites that potentially possess anti-tumor effects. For a broad spectrum of human cancers with 2-HG accumulation, 2-HG synthase-based enzyme therapy holds the potential to not only correct 2-HG induced cancer metabolism but also transform an oncometabolite into metabolic challenges within cancer cells.

Shutting off the fuel supply to target metabolic vulnerabilities in multiple myeloma

Pathways that govern cellular bioenergetics are deregulated in tumor cells and represent a hallmark of cancer. Tumor cells have the capacity to reprogram pathways that control nutrient acquisition, anabolism and catabolism to enhance their growth and survival. Tumorigenesis requires the autonomous reprogramming of key metabolic pathways that obtain, generate and produce metabolites from a nutrient-deprived tumor microenvironment to meet the increased bioenergetic demands of cancer cells. Intra- and extracellular factors also have a profound effect on gene expression to drive metabolic pathway reprogramming in not only cancer cells but also surrounding cell types that contribute to anti-tumor immunity. Despite a vast amount of genetic and histologic heterogeneity within and between cancer types, a finite set of pathways are commonly deregulated to support anabolism, catabolism and redox balance. Multiple myeloma (MM) is the second most common hematologic malignancy in adults and remains incurable in the vast majority of patients. Genetic events and the hypoxic bone marrow milieu deregulate glycolysis, glutaminolysis and fatty acid synthesis in MM cells to promote their proliferation, survival, metastasis, drug resistance and evasion of immunosurveillance. Here, we discuss mechanisms that disrupt metabolic pathways in MM cells to support the development of therapeutic resistance and thwart the effects of anti-myeloma immunity. A better understanding of the events that reprogram metabolism in myeloma and immune cells may reveal unforeseen vulnerabilities and advance the rational design of drug cocktails that improve patient survival.

The Interplay between Dysregulated Metabolism and Epigenetics in Cancer

Cellular metabolism (or energetics) and epigenetics are tightly coupled cellular processes. It is arguable that of all the described cancer hallmarks, dysregulated cellular energetics and epigenetics are the most tightly coregulated. Cellular metabolic states regulate and drive epigenetic changes while also being capable of influencing, if not driving, epigenetic reprogramming. Conversely, epigenetic changes can drive altered and compensatory metabolic states. Cancer cells meticulously modify and control each of these two linked cellular processes in order to maintain their tumorigenic potential and capacity. This review aims to explore the interplay between these two processes and discuss how each affects the other, driving and enhancing tumorigenic states in certain contexts.

MultiNEP: a multi-omics network enhancement framework for prioritizing disease genes and metabolites simultaneously

MOTIVATION

Many studies have successfully used network information to prioritize candidate omics profiles associated with diseases. The metabolome, as the link between genotypes and phenotypes, has accumulated growing attention. Using a "multi-omics" network constructed with a gene-gene network, a metabolite-metabolite network, and a gene-metabolite network to simultaneously prioritize candidate disease-associated metabolites and gene expressions could further utilize gene-metabolite interactions that are not used when prioritizing them separately. However, the number of metabolites is usually 100 times fewer than that of genes. Without accounting for this imbalance issue, we cannot effectively use gene-metabolite interactions when simultaneously prioritizing disease-associated metabolites and genes.

RESULTS

Here, we developed a Multi-omics Network Enhancement Prioritization (MultiNEP) framework with a weighting scheme to reweight contributions of different sub-networks in a multi-omics network to effectively prioritize candidate disease-associated metabolites and genes simultaneously. In simulation studies, MultiNEP outperforms competing methods that do not address network imbalances and identifies more true signal genes and metabolites simultaneously when we down-weight relative contributions of the gene-gene network and up-weight that of the metabolite-metabolite network to the gene-metabolite network. Applications to two human cancer cohorts show that MultiNEP prioritizes more cancer-related genes by effectively using both within- and between-omics interactions after handling network imbalance.

AVAILABILITY AND IMPLEMENTATION

The developed MultiNEP framework is implemented in an R package and available at: https://github.com/Karenxzr/MultiNep.

Lactate from glycolysis regulates inflammatory macrophage polarization in breast cancer

Globally, breast cancer is one of the leading causes of cancer death in women. Metabolic reprogramming and immune escape are two important mechanisms supporting the progression of breast cancer. Lactate in tumors mainly comes from glycolysis and glutaminolysis. Using multiomics data analysis, we found that lactate is mainly derived from glycolysis in breast cancer. Single-cell transcriptome analysis found that breast cancer cells with higher malignancy, especially those in the cell cycle, have higher expression levels of glycolytic metabolic enzymes. Combined with clinical data analysis, it was found that the expression of the lactate transporter SLC16A3 is correlated with breast cancer molecular subtypes and immune infiltration. Among 22 immune cells, macrophages are the most abundant immune cells in breast cancer tissues, and the proportion of M1 macrophages is lower in the high SLC16A3 expression group. Finally, in vitro experiments confirmed that lactate could inhibit the expression of M1 macrophage markers at both RNA and protein levels. In conclusion, we found that lactate produced by glycolysis regulates the polarization of inflammatory macrophages in breast cancer.

A multimodal atlas of tumour metabolism reveals the architecture of gene-metabolite covariation

Tumour metabolism is controlled by coordinated changes in metabolite abundance and gene expression, but simultaneous quantification of metabolites and transcripts in primary tissue is rare. To overcome this limitation and to study gene-metabolite covariation in cancer, we assemble the Cancer Atlas of Metabolic Profiles of metabolomic and transcriptomic data from 988 tumour and control specimens spanning 11 cancer types in published and newly generated datasets. Meta-analysis of the Cancer Atlas of Metabolic Profiles reveals two classes of gene-metabolite covariation that transcend cancer types. The first corresponds to gene-metabolite pairs engaged in direct enzyme-substrate interactions, identifying putative genes controlling metabolite pool sizes. A second class of gene-metabolite covariation represents a small number of hub metabolites, including quinolinate and nicotinamide adenine dinucleotide, which correlate to many genes specifically expressed in immune cell populations. These results provide evidence that gene-metabolite covariation in cellularly heterogeneous tissue arises, in part, from both mechanistic interactions between genes and metabolites, and from remodelling of the bulk metabolome in specific immune microenvironments.

Crosstalk between Metabolite Production and Signaling Activity in Breast Cancer

The reprogramming of metabolism is a recognized cancer hallmark. It is well known that different signaling pathways regulate and orchestrate this reprogramming that contributes to cancer initiation and development. However, recent evidence is accumulating, suggesting that several metabolites could play a relevant role in regulating signaling pathways. To assess the potential role of metabolites in the regulation of signaling pathways, both metabolic and signaling pathway activities of Breast invasive Carcinoma (BRCA) have been modeled using mechanistic models. Gaussian Processes, powerful machine learning methods, were used in combination with SHapley Additive exPlanations (SHAP), a recent methodology that conveys causality, to obtain potential causal relationships between the production of metabolites and the regulation of signaling pathways. A total of 317 metabolites were found to have a strong impact on signaling circuits. The results presented here point to the existence of a complex crosstalk between signaling and metabolic pathways more complex than previously was thought.

Glutamine metabolism in breast cancer and possible therapeutic targets

Cancer is characterized by metabolic reprogramming, which is a hot topic in tumor treatment research. Cancer cells alter metabolic pathways to promote their growth, and the common purpose of these altered metabolic pathways is to adapt the metabolic state to the uncontrolled proliferation of cancer cells. Most cancer cells in a state of nonhypoxia will increase the uptake of glucose and produce lactate, called the Warburg effect. Increased glucose consumption is used as a carbon source to support cell proliferation, including nucleotide, lipid and protein synthesis. In the Warburg effect, pyruvate dehydrogenase activity decreases, thereby disrupting the TCA cycle. In addition to glucose, glutamine is also an important nutrient for the growth and proliferation of cancer cells, an important carbon bank and nitrogen bank for the growth and proliferation of cancer cells, providing ribose, nonessential amino acids, citrate, and glycerin necessary for cancer cell growth and proliferation and compensating for the reduction in oxidative phosphorylation pathways in cancer cells caused by the Warburg effect. In human plasma, glutamine is the most abundant amino acid. Normal cells produce glutamine via glutamine synthase (GLS), but the glutamine synthesized by tumor cells is insufficient to meet their high growth needs, resulting in a "glutamine-dependent phenomenon." Most cancers have an increased glutamine demand, including breast cancer. Metabolic reprogramming not only enables tumor cells to maintain the reduction-oxidation (redox) balance and commit resources to biosynthesis but also establishes heterogeneous metabolic phenotypes of tumor cells that are distinct from those of nontumor cells. Thus, targeting the metabolic differences between tumor and nontumor cells may be a promising and novel anticancer strategy. Glutamine metabolic compartments have emerged as promising candidates, especially in TNBC and drug-resistant breast cancer. In this review, the latest discoveries of breast cancer and glutamine metabolism are discussed, novel treatment methods based on amino acid transporters and glutaminase are discussed, and the relationship between glutamine metabolism and breast cancer metastasis, drug resistance, tumor immunity and ferroptosis are explained, which provides new ideas for the clinical treatment of breast cancer.

Integrated multiomics analyses unveil the implication of a costimulatory molecule score on tumor aggressiveness and immune evasion in breast cancer: A large-scale study through over 8,000 patients

BACKGROUND

Although immunotherapy has revolutionised cancer management, reliable genomic biomarkers for identifying eligible patient subpopulations are lacking. Costimulatory molecules play a crucial role in mounting anti-tumour responses, and clinical trials targeting these novel biomarkers are underway. However, whether these molecules can determine tumour aggressiveness and the risk of tumour evasion in breast cancer (BC) remains largely unknown.

METHODS

The whole-tissue transcriptomic data of 8236 patients with BC from 15 independent cohorts were extracted. An integrated scoring system named 'costimulatory molecule score' (CMS) was constructed and sufficient validated using least absolute shrinkage and selection operator regression (1000 iterations) and the random survival forest algorithm (1000 trees). The correlation among CMSs, cancer genotypes and clinicopathological characteristics was examined. Extensive multiomics and immunogenomic analyses were performed to investigate and verify the association among CMSs, enriched pathways, potential intrinsic and extrinsic immune escape mechanisms, immunotherapy response and therapeutic options.

RESULTS

The predictive role of CMS model that relies on expression pattern of merely 5 costimulatory genes for prognosis is almost universally applicable to BC patients in a platform-independent manner. Through internal and external in silico validation, high CMS was characterized by favorable genotypes but decreased tumor immunogenicity, activation of stroma, immune-suppressive states and potential immunotherapeutic resistance. Similar results were observed in a real-world immunotherapy cohort and Pan-Cancer analysis.

CONCLUSION

This comprehensive characterization indicates CMS model may be complemented for predicting tumor aggressiveness and immune evasion in BC patients, underlining the future clinical potential for further exploration of resistance mechanisms and optimization of immunotherapeutic strategies.

Targeting Mitochondria with ClpP Agonists as a Novel Therapeutic Opportunity in Breast Cancer

Breast cancer is the most frequently diagnosed malignancy worldwide and the leading cause of cancer mortality in women. Despite the recent development of new therapeutics including targeted therapies and immunotherapy, triple-negative breast cancer remains an aggressive form of breast cancer, and thus improved treatments are needed. In recent decades, it has become increasingly clear that breast cancers harbor metabolic plasticity that is controlled by mitochondria. A myriad of studies provide evidence that mitochondria are essential to breast cancer progression. Mitochondria in breast cancers are widely reprogrammed to enhance energy production and biosynthesis of macromolecules required for tumor growth. In this review, we will discuss the current understanding of mitochondrial roles in breast cancers and elucidate why mitochondria are a rational therapeutic target. We will then outline the status of the use of mitochondria-targeting drugs in breast cancers, and highlight ClpP agonists as emerging mitochondria-targeting drugs with a unique mechanism of action. We also illustrate possible drug combination strategies and challenges in the future breast cancer clinic.

L-2hydroxyglutaric acid rewires amino acid metabolism in colorectal cancer via the mTOR-ATF4 axis

Oncometabolites, such as D/L-2-hydroxyglutarate (2HG), have directly been implicated in carcinogenesis; however, the underlying molecular mechanisms remain poorly understood. Here, we showed that the levels of the L-enantiomer of 2HG (L2HG) were specifically increased in colorectal cancer (CRC) tissues and cell lines compared with the D-enantiomer of 2HG (D2HG). In addition, L2HG increased the expression of ATF4 and its target genes by activating the mTOR pathway, which subsequently provided amino acids and improved the survival of CRC cells under serum deprivation. Downregulating the expression of L-2-hydroxyglutarate dehydrogenase (L2HGDH) and oxoglutarate dehydrogenase (OGDH) increased L2HG levels in CRC, thereby activating mTOR-ATF4 signaling. Furthermore, L2HGDH overexpression reduced L2HG-mediated mTOR-ATF4 signaling under hypoxia, whereas L2HGDH knockdown promoted tumor growth and amino acid metabolism in vivo. Together, these results indicate that L2HG ameliorates nutritional stress by activating the mTOR-ATF4 axis and thus could be a potential therapeutic target for CRC.

Short term starvation potentiates the efficacy of chemotherapy in triple negative breast cancer via metabolic reprogramming

BACKGROUND

Chemotherapy (CT) is central to the treatment of triple negative breast cancer (TNBC), but drug toxicity and resistance place strong restrictions on treatment regimes. Fasting sensitizes cancer cells to a range of chemotherapeutic agents and also ameliorates CT-associated adverse effects. However, the molecular mechanism(s) by which fasting, or short-term starvation (STS), improves the efficacy of CT is poorly characterized.

METHODS

The differential responses of breast cancer or near normal cell lines to combined STS and CT were assessed by cellular viability and integrity assays (Hoechst and PI staining, MTT or H₂DCFDA staining, immunofluorescence), metabolic profiling (Seahorse analysis, metabolomics), gene expression (quantitative real-time PCR) and iRNA-mediated silencing. The clinical significance of the in vitro data was evaluated by bioinformatical integration of transcriptomic data from patient data bases: The Cancer Genome Atlas (TCGA), European Genome-phenome Archive (EGA), Gene Expression Omnibus (GEO) and a TNBC cohort. We further examined the translatability of our findings in vivo by establishing a murine syngeneic orthotopic mammary tumor-bearing model.

RESULTS

We provide mechanistic insights into how preconditioning with STS enhances the susceptibility of breast cancer cells to CT. We showed that combined STS and CT enhanced cell death and increased reactive oxygen species (ROS) levels, in association with higher levels of DNA damage and decreased mRNA levels for the NRF2 targets genes NQO1 and TXNRD1 in TNBC cells compared to near normal cells. ROS enhancement was associated with compromised mitochondrial respiration and changes in the metabolic profile, which have a significant clinical prognostic and predictive value. Furthermore, we validate the safety and efficacy of combined periodic hypocaloric diet and CT in a TNBC mouse model.

CONCLUSIONS

Our in vitro, in vivo and clinical findings provide a robust rationale for clinical trials on the therapeutic benefit of short-term caloric restriction as an adjuvant to CT in triple breast cancer treatment.

P2RX7 promotes osteosarcoma progression and glucose metabolism by enhancing c-Myc stabilization

BACKGROUND

Osteosarcoma is the most common malignant tumor in bone and its prognosis has reached a plateau in the past few decades. Recently, metabolic reprogramming has attracted increasing attention in the field of cancer research. In our previous study, P2RX7 has been identified as an oncogene in osteosarcoma. However, whether and how P2RX7 promotes osteosarcoma growth and metastasis through metabolic reprogramming remains unexplored.

METHODS

We used CRISPR/Cas9 genome editing technology to establish P2RX7 knockout cell lines. Transcriptomics and metabolomics were performed to explore metabolic reprogramming in osteosarcoma. RT-PCR, western blot and immunofluorescence analyses were used to determine gene expression related to glucose metabolism. Cell cycle and apoptosis were examined by flowcytometry. The capacity of glycolysis and oxidative phosphorylation were assessed by seahorse experiments. PET/CT was carried out to assess glucose uptake in vivo.

RESULTS

We demonstrated that P2RX7 significantly promotes glucose metabolism in osteosarcoma via upregulating the expression of genes related to glucose metabolism. Inhibition of glucose metabolism largely abolishes the ability of P2RX7 to promote osteosarcoma progression. Mechanistically, P2RX7 enhances c-Myc stabilization by facilitating nuclear retention and reducing ubiquitination-dependent degradation. Furthermore, P2RX7 promotes osteosarcoma growth and metastasis through metabolic reprogramming in a predominantly c-Myc-dependent manner.

CONCLUSIONS

P2RX7 plays a key role in metabolic reprogramming and osteosarcoma progression via increasing c-Myc stability. These findings provide new evidence that P2RX7 might be a potential diagnostic and/or therapeutic target for osteosarcoma. Novel therapeutic strategies targeting metabolic reprogramming appear to hold promise for a breakthrough in the treatment of osteosarcoma.

D-2-Hydroxyglutarate Inhibits Calcineurin Phosphatase Activity to Abolish NF-AT Activation and IL-2 Induction in Stimulated Lymphocytes

Gliomas expressing mutant isocitrate dehydrogenases excessively synthesize d-2-hydroxyglutarate (D2HG), suppressing immune surveillance. A portion of this D2HG is released from these tumor cells, but the way environmental D2HG inhibits lymphocyte function is undefined. We incubated human PBLs or Jurkat T cells with D2HG at concentrations present within and surrounding gliomas or its obverse l-2-hydroxyglutarate (L2HG) stereoisomer. We quantified each 2HG stereoisomer within washed cells by N-(p-toluenesulfonyl)-l-phenylalanyl chloride derivatization with stable isotope-labeled D2HG and L2HG internal standards, HPLC separation, and mass spectrometry. D2HG was present in quiescent cells and was twice as abundant as L2HG. Extracellular 2HG rapidly increased intracellular levels of the provided stereoisomer by a stereoselective, concentration-dependent process. IL-2 expression, even when elicited by A23187 and PMA, was abolished by D2HG in a concentration-dependent manner, with significant reduction at just twice its basal level. In contrast, L2HG was only moderately inhibitory. IL-2 expression is regulated by increased intracellular Ca2+ that stimulates calcineurin to dephosphorylate cytoplasmic phospho-NF-AT, enabling its nuclear translocation. D2HG abolished stimulated expression of a stably integrated NF-AT-driven luciferase reporter that precisely paralleled its concentration-dependent inhibition of IL-2. D2HG did not affect intracellular Ca2+. Rather, surface plasmon resonance showed D2HG, but not L2HG, bound calcineurin, and D2HG, but not L2HG, inhibited Ca2+-dependent calcineurin phosphatase activity in stimulated Jurkat extracts. Thus, D2HG is a stereoselective calcineurin phosphatase inhibitor that prevents NF-AT dephosphorylation and so abolishes IL-2 transcription in stimulated lymphocytes. This occurs at D2HG concentrations found within and adjacent to gliomas independent of its metabolic or epigenetic transcriptional regulation.

rox: A Statistical Model for Regression with Missing Values

High-dimensional omics datasets frequently contain missing data points, which typically occur due to concentrations below the limit of detection (LOD) of the profiling platform. The presence of such missing values significantly limits downstream statistical analysis and result interpretation. Two common techniques to deal with this issue include the removal of samples with missing values and imputation approaches that substitute the missing measurements with reasonable estimates. Both approaches, however, suffer from various shortcomings and pitfalls. In this paper, we present "rox", a novel statistical model for the analysis of omics data with missing values without the need for imputation. The model directly incorporates missing values as "low" concentrations into the calculation. We show the superiority of rox over common approaches on simulated data and on six metabolomics datasets. Fully leveraging the information contained in LOD-based missing values, rox provides a powerful tool for the statistical analysis of omics data.

Histopathologic and proteogenomic heterogeneity reveals features of clear cell renal cell carcinoma aggressiveness

Clear cell renal cell carcinomas (ccRCCs) represent ∼75% of RCC cases and account for most RCC-associated deaths. Inter- and intratumoral heterogeneity (ITH) results in varying prognosis and treatment outcomes. To obtain the most comprehensive profile of ccRCC, we perform integrative histopathologic, proteogenomic, and metabolomic analyses on 305 ccRCC tumor segments and 166 paired adjacent normal tissues from 213 cases. Combining histologic and molecular profiles reveals ITH in 90% of ccRCCs, with 50% demonstrating immune signature heterogeneity. High tumor grade, along with BAP1 mutation, genome instability, increased hypermethylation, and a specific protein glycosylation signature define a high-risk disease subset, where UCHL1 expression displays prognostic value. Single-nuclei RNA sequencing of the adverse sarcomatoid and rhabdoid phenotypes uncover gene signatures and potential insights into tumor evolution. In vitro cell line studies confirm the potential of inhibiting identified phosphoproteome targets. This study molecularly stratifies aggressive histopathologic subtypes that may inform more effective treatment strategies.

Minimal frustration underlies the usefulness of incomplete regulatory network models in biology

Regulatory networks as large and complex as those implicated in cell-fate choice are expected to exhibit intricate, very high-dimensional dynamics. Cell-fate choice, however, is a macroscopically simple process. Additionally, regulatory network models are almost always incomplete and/or inexact, and do not incorporate all the regulators and interactions that may be involved in cell-fate regulation. In spite of these issues, regulatory network models have proven to be incredibly effective tools for understanding cell-fate choice across contexts and for making useful predictions. Here, we show that minimal frustration-a feature of biological networks across contexts but not of random networks-can compel simple, low-dimensional steady-state behavior even in large and complex networks. Moreover, the steady-state behavior of minimally frustrated networks can be recapitulated by simpler networks such as those lacking many of the nodes and edges and those that treat multiple regulators as one. The present study provides a theoretical explanation for the success of network models in biology and for the challenges in network inference.

IntLIM 2.0: identifying multi-omic relationships dependent on discrete or continuous phenotypic measurements

Motivation

IntLIM uncovers phenotype-dependent linear associations between two types of analytes (e.g. genes and metabolites) in a multi-omic dataset, which may reflect chemically or biologically relevant relationships.

Results

The new IntLIM R package includes newly added support for generalized data types, covariate correction, continuous phenotypic measurements, model validation and unit testing. IntLIM analysis uncovered biologically relevant gene-metabolite associations in two separate datasets, and the run time is improved over baseline R functions by multiple orders of magnitude.

Availability and implementation

IntLIM is available as an R package with a detailed vignette (https://github.com/ncats/IntLIM) and as an R Shiny app (see Supplementary Figs S1-S6) (https://intlim.ncats.io/).

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

CD8+ T cell metabolic changes in breast cancer

Immunometabolism has advanced our understanding of how the cellular environment and nutrient availability regulates immune cell fate. Not only are metabolic pathways closely tied to cell signaling and differentiation, but can induce different subsets of immune cells to adopt unique metabolic programs, influencing disease progression. Dysregulation of immune cell metabolism plays an essential role in the progression of several diseases including breast cancer (BC). Metabolic reprogramming plays a critical role in regulating T cell functions. CD8⁺ T cells are an essential cell type within the tumor microenvironment (TME). To induce antitumor responses, CD8⁺ T cells need to adapt their metabolism to fulfill their energy requirement for effective function. However, different markers and immunologic techniques have made identifying specific CD8⁺ T cells subtypes in BC a challenge to the field. This review discusses the immunometabolic processes of CD8⁺ T cell in the TME in the context of BC and highlights the role of CD8⁺ T cell metabolic changes in tumor progression.

Acetyl-CoA regulates lipid metabolism and histone acetylation modification in cancer

Acetyl-CoA, as an important molecule, not only participates in multiple intracellular metabolic reactions, but also affects the post-translational modification of proteins, playing a key role in the metabolic activity and epigenetic inheritance of cells. Cancer cells require extensive lipid metabolism to fuel for their growth, while also require histone acetylation modifications to increase the expression of cancer-promoting genes. As a raw material for de novo lipid synthesis and histone acetylation, acetyl-CoA has a major impact on lipid metabolism and histone acetylation in cancer. More importantly, in cancer, acetyl-CoA connects lipid metabolism with histone acetylation, forming a more complex regulatory mechanism that influences cancer growth, proliferation, metastasis.

Pharmacometabolomics reveals urinary diacetylspermine as a biomarker of doxorubicin effectiveness in triple negative breast cancer

Triple-negative breast cancer (TNBC) patients receive chemotherapy treatment, including doxorubicin, due to the lack of targeted therapies. Drug resistance is a major cause of treatment failure in TNBC and therefore, there is a need to identify biomarkers that determine effective drug response. A pharmacometabolomics study was performed using doxorubicin sensitive and resistant TNBC patient-derived xenograft (PDX) models to detect urinary metabolic biomarkers of treatment effectiveness. Evaluation of metabolite production was assessed by directly studying tumor levels in TNBC-PDX mice and human subjects. Metabolic flux leading to biomarker production was determined using stable isotope-labeled tracers in TNBC-PDX ex vivo tissue slices. Findings were validated in 12-h urine samples from control (n = 200), ER+/PR+ (n = 200), ER+/PR+/HER2+ (n = 36), HER2+ (n = 81) and TNBC (n = 200) subjects. Diacetylspermine was identified as a urine metabolite that robustly changed in response to effective doxorubicin treatment, which persisted after the final dose. Urine diacetylspermine was produced by the tumor and correlated with tumor volume. Ex vivo tumor slices revealed that doxorubicin directly increases diacetylspermine production by increasing tumor spermidine/spermine N¹-acetyltransferase 1 expression and activity, which was corroborated by elevated polyamine flux. In breast cancer patients, tumor diacetylspermine was elevated compared to matched non-cancerous tissue and increased in HER2+ and TNBC compared to ER+ subtypes. Urine diacetylspermine was associated with breast cancer tumor volume and poor tumor grade. This study describes a pharmacometabolomics strategy for identifying cancer metabolic biomarkers that indicate drug response. Our findings characterize urine diacetylspermine as a non-invasive biomarker of doxorubicin effectiveness in TNBC.

Safeguarding DNA Replication: A Golden Touch of MiDAS and Other Mechanisms

DNA replication is a tightly regulated fundamental process allowing the correct duplication and transfer of the genetic information from the parental cell to the progeny. It involves the coordinated assembly of several proteins and protein complexes resulting in replication fork licensing, firing and progression. However, the DNA replication pathway is strewn with hurdles that affect replication fork progression during S phase. As a result, cells have adapted several mechanisms ensuring replication completion before entry into mitosis and segregating chromosomes with minimal, if any, abnormalities. In this review, we describe the possible obstacles that a replication fork might encounter and how the cell manages to protect DNA replication from S to the next G1.

DrDimont: explainable drug response prediction from differential analysis of multi-omics networks

MOTIVATION

While it has been well established that drugs affect and help patients differently, personalized drug response predictions remain challenging. Solutions based on single omics measurements have been proposed, and networks provide means to incorporate molecular interactions into reasoning. However, how to integrate the wealth of information contained in multiple omics layers still poses a complex problem.

RESULTS

We present DrDimont, Drug response prediction from Differential analysis of multi-omics networks. It allows for comparative conclusions between two conditions and translates them into differential drug response predictions. DrDimont focuses on molecular interactions. It establishes condition-specific networks from correlation within an omics layer that are then reduced and combined into heterogeneous, multi-omics molecular networks. A novel semi-local, path-based integration step ensures integrative conclusions. Differential predictions are derived from comparing the condition-specific integrated networks. DrDimont's predictions are explainable, i.e. molecular differences that are the source of high differential drug scores can be retrieved. We predict differential drug response in breast cancer using transcriptomics, proteomics, phosphosite and metabolomics measurements and contrast estrogen receptor positive and receptor negative patients. DrDimont performs better than drug prediction based on differential protein expression or PageRank when evaluating it on ground truth data from cancer cell lines. We find proteomic and phosphosite layers to carry most information for distinguishing drug response.

AVAILABILITY AND IMPLEMENTATION

DrDimont is available on CRAN: https://cran.r-project.org/package=DrDimont.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Cellular reprogramming, chemoresistance, and dietary interventions in breast cancer

Breast cancer (BC) diagnosis has been associated with significant risk factors, including family history, late menopause, obesity, poor eating habits, and alcoholism. Despite the advances in the last decades regarding cancer treatment, some obstacles still hinder the effectiveness of therapy. For example, chemotherapy resistance is common in locally advanced or metastatic cancer, reducing treatment options and contributing to mortality. In this review, we provide an overview of BC metabolic changes, including the impact of restrictive diets associated with chemoresistance, the therapeutic potential of the diet on tumor progression, pathways related to metabolic health in oncology, and perspectives on the future in the area of oncological nutrition.

The crosstalk of the human microbiome in breast and colon cancer: A metabolomics analysis

The human microbiome's role in colon and breast cancer is described in this review. Understanding how the human microbiome and metabolomics interact with breast and colon cancer is the chief area of this study. First, the role of the gut and distal microbiome in breast and colon cancer is investigated, and the direct relationship between microbial dysbiosis and breast and colon cancer is highlighted. This work also focuses on the many metabolomic techniques used to locate prospective biomarkers, make an accurate diagnosis, and research new therapeutic targets for cancer treatment. This review clarifies the influence of anti-tumor medications on the microbiota and the proactive measures that can be taken to treat cancer using a variety of therapies, including radiotherapy, chemotherapy, next-generation biotherapeutics, gene-based therapy, integrated omics technology, and machine learning.

Difluoromethylornithine (DFMO) Enhances the Cytotoxicity of PARP Inhibition in Ovarian Cancer Cells

Ovarian cancer accounts for 3% of the total cancers in women, yet it is the fifth leading cause of cancer deaths among women. The BRCA1/2 germline and somatic mutations confer a deficiency of the homologous recombination (HR) repair pathway. Inhibitors of poly (ADP-ribose) polymerase (PARP), another important component of DNA damage repair, are somewhat effective in BRCA1/2 mutant tumors. However, ovarian cancers often reacquire functional BRCA and develop resistance to PARP inhibitors. Polyamines have been reported to facilitate the DNA damage repair functions of PARP. Given the elevated levels of polyamines in tumors, we hypothesized that treatment with the polyamine synthesis inhibitor, α-difluoromethylornithine (DFMO), may enhance ovarian tumor sensitivity to the PARP inhibitor, rucaparib. In HR-competent ovarian cancer cell lines with varying sensitivities to rucaparib, we show that co-treatment with DFMO increases the sensitivity of ovarian cancer cells to rucaparib. Immunofluorescence assays demonstrated that, in the presence of hydrogen peroxide-induced DNA damage, DFMO strongly inhibits PARylation, increases DNA damage accumulation, and reduces cell viability in both HR-competent and deficient cell lines. In vitro viability assays show that DFMO and rucaparib cotreatment significantly enhances the cytotoxicity of the chemotherapeutic agent, cisplatin. These results suggest that DFMO may be a useful adjunct chemotherapeutic to improve the anti-tumor efficacy of PARP inhibitors in treating ovarian cancer.

NOS2 and S-nitrosothiol signaling induces DNA hypomethylation and LINE-1 retrotransposon expression

Inducible nitric oxide synthase (NOS2) produces high local concentrations of nitric oxide (NO), and its expression is associated with inflammation, cellular stress signals, and cellular transformation. Additionally, NOS2 expression results in aggressive cancer cell phenotypes and is correlated with poor outcomes in patients with breast cancer. DNA hypomethylation, especially of noncoding repeat elements, is an early event in carcinogenesis and is a common feature of cancer cells. In addition to altered gene expression, DNA hypomethylation results in genomic instability via retrotransposon activation. Here, we show that NOS2 expression and associated NO signaling results in substantial DNA hypomethylation in human cell lines by inducing the degradation of DNA (cytosine-5)–methyltransferase 1 (DNMT1) protein. Similarly, NOS2 expression levels were correlated with decreased DNA methylation in human breast tumors. NOS2 expression and NO signaling also resulted in long interspersed noncoding element 1 (LINE-1) retrotransposon hypomethylation, expression, and DNA damage. DNMT1 degradation was mediated by an NO/p38-MAPK/lysine acetyltransferase 5–dependent mechanism. Furthermore, we show that this mechanism is required for NO-mediated epithelial transformation. Therefore, we conclude that NOS2 and NO signaling results in DNA damage and malignant cellular transformation via an epigenetic mechanism.

Gene expression is a poor predictor of steady-state metabolite abundance in cancer cells

Metabolic reprogramming is a hallmark of cancer characterized by global changes in metabolite levels. However, compared with the study of gene expression, profiling of metabolites in cancer samples remains relatively understudied. We obtained metabolomic profiling and gene expression data from 454 human solid cancer cell lines across 24 cancer types from the Cancer Cell Line Encyclopedia (CCLE) database, to evaluate the feasibility of inferring metabolite levels from gene expression data. For each metabolite, we trained multivariable LASSO regression models to identify gene sets that are most predictive of the level of each metabolite profiled. Even when accounting for cell culture conditions or cell lineage in the model, few metabolites could be accurately predicted. In some cases, the inclusion of the upstream and downstream metabolites improved prediction accuracy, suggesting that gene expression is a poor predictor of steady-state metabolite levels. Our analysis uncovered a single robust relationship between the expression of nicotinamide N-methyltransferase (NNMT) and 1-methylnicotinamide (MNA), however, this relationship could only be validated in cancer samples with high purity, as NNMT is not expressed in immune cells. Together, we have trained models that use gene expression profiles to predict the level of individual metabolites. Our analysis suggests that inferring metabolite levels based on the expression of genes is generally challenging in cancer.

Estrogen Receptor and the Unfolded Protein Response: Double-Edged Swords in Therapy for Estrogen Receptor-Positive Breast Cancer

Estrogen receptor α (ERα) is a target for the treatment of ER-positive breast cancer patients. Paradoxically, it is also the initial site for estrogen (E₂) to induce apoptosis in endocrine-resistant breast cancer. How ERα exhibits distinct functions, in different contexts, is the focus of numerous investigations. Compelling evidence demonstrated that unfolded protein response (UPR) is closely correlated with ER-positive breast cancer. Treatment with antiestrogens initially induces mild UPR through ERα with activation of three sensors of UPR-PRK-like endoplasmic reticulum kinase (PERK), inositol-requiring enzyme 1α (IRE1α), and activating transcription factor 6 (ATF6)-in the endoplasmic reticulum. Subsequently, these sensors interact with stress-associated transcription factors such as c-MYC, nuclear factor-κB (NF-κB), and hypoxia-inducible factor 1α (HIF1α), leading to acquired endocrine resistance. Paradoxically, E₂ further activates sustained secondary UPR via ERα to induce apoptosis in endocrine-resistant breast cancer. Specifically, PERK plays a key role in inducing apoptosis, whereas IRE1α and ATF6 are involved in endoplasmic reticulum stress-associated degradation after E₂ treatment. Furthermore, persistent activation of PERK deteriorates stress responses in mitochondria and triggers of NF-κB/tumor necrosis factor α (TNFα) axis, ultimately determining cell fate to apoptosis. The discovery of E₂-induced apoptosis has clinical relevance for treatment of endocrine-resistant breast cancer. All of these findings demonstrate that ERα and associated UPR are double-edged swords in therapy for ER-positive breast cancer, depending on the duration and intensity of UPR stress. Herein, we address the mechanistic progress on how UPR leads to endocrine resistance and commits E₂ to inducing apoptosis in endocrine-resistant breast cancer.

Comprehensive metabolomics expands precision medicine for triple-negative breast cancer

Metabolic reprogramming is a hallmark of cancer. However, systematic characterizations of metabolites in triple-negative breast cancer (TNBC) are still lacking. Our study profiled the polar metabolome and lipidome in 330 TNBC samples and 149 paired normal breast tissues to construct a large metabolomic atlas of TNBC. Combining with previously established transcriptomic and genomic data of the same cohort, we conducted a comprehensive analysis linking TNBC metabolome to genomics. Our study classified TNBCs into three distinct metabolomic subgroups: C1, characterized by the enrichment of ceramides and fatty acids; C2, featured with the upregulation of metabolites related to oxidation reaction and glycosyl transfer; and C3, having the lowest level of metabolic dysregulation. Based on this newly developed metabolomic dataset, we refined previous TNBC transcriptomic subtypes and identified some crucial subtype-specific metabolites as potential therapeutic targets. The transcriptomic luminal androgen receptor (LAR) subtype overlapped with metabolomic C1 subtype. Experiments on patient-derived organoid and xenograft models indicate that targeting sphingosine-1-phosphate (S1P), an intermediate of the ceramide pathway, is a promising therapy for LAR tumors. Moreover, the transcriptomic basal-like immune-suppressed (BLIS) subtype contained two prognostic metabolomic subgroups (C2 and C3), which could be distinguished through machine-learning methods. We show that N-acetyl-aspartyl-glutamate is a crucial tumor-promoting metabolite and potential therapeutic target for high-risk BLIS tumors. Together, our study reveals the clinical significance of TNBC metabolomics, which can not only optimize the transcriptomic subtyping system, but also suggest novel therapeutic targets. This metabolomic dataset can serve as a useful public resource to promote precision treatment of TNBC.

2-Hydroxyglutarate destabilizes chromatin regulatory landscape and lineage fidelity to promote cellular heterogeneity

The epigenome delineates lineage-specific transcriptional programs and restricts cell plasticity to prevent non-physiological cell fate transitions. Although cell diversification fosters tumor evolution and therapy resistance, upstream mechanisms that regulate the stability and plasticity of the cancer epigenome remain elusive. Here we show that 2-hydroxyglutarate (2HG) not only suppresses DNA repair but also mediates the high-plasticity chromatin landscape. A combination of single-cell epigenomics and multi-omics approaches demonstrates that 2HG disarranges otherwise well-preserved stable nucleosome positioning and promotes cell-to-cell variability. 2HG induces loss of motif accessibility to the luminal-defining transcriptional factors FOXA1, FOXP1, and GATA3 and a shift from luminal to basal-like gene expression. Breast tumors with high 2HG exhibit enhanced heterogeneity with undifferentiated epigenomic signatures linked to adverse prognosis. Further, ascorbate-2-phosphate (A2P) eradicates heterogeneity and impairs growth of high 2HG-producing breast cancer cells. These findings suggest 2HG as a key determinant of cancer plasticity and provide a rational strategy to counteract tumor cell evolution.

Kusi et al. show that the oncometabolite 2-hydroxyglutarate (2HG) initiates cell-level epigenome fluctuations in the chromatin regulatory landscape, accompanied by loss of lineage fidelity. Breast tumors with high 2HG accumulation exhibit enhanced cellular heterogeneity with undifferentiated stem-like epigenomic signatures. The findings suggest metabolic derangement as a molecular origin of breast cancer heterogeneity.

Pathophysiological Integration of Metabolic Reprogramming in Breast Cancer

Simple Summary

Tumors exhibit metabolic changes that differentiate them from the normal tissues from which they derive. These metabolic changes favor tumor growth, are primarily induced by cancer cells, and produce metabolic and functional changes in the surrounding stromal cells. There is a close functional connection between the metabolic changes in tumor cells and those that appear in the surrounding stroma. A better understanding of intratumoral metabolic interactions may help identify new vulnerabilities that will facilitate new, more individualized treatment strategies against cancer. We review the metabolic changes described in tumor and stromal cells and their functional changes and then consider, in depth, the metabolic interactions between the cells of the two compartments. Although these changes are generic, we illustrate them mainly with reference to examples in breast cancer.

Abstract

Metabolic changes that facilitate tumor growth are one of the hallmarks of cancer. The triggers of these metabolic changes are located in the tumor parenchymal cells, where oncogenic mutations induce an imperative need to proliferate and cause tumor initiation and progression. Cancer cells undergo significant metabolic reorganization during disease progression that is tailored to their energy demands and fluctuating environmental conditions. Oxidative stress plays an essential role as a trigger under such conditions. These metabolic changes are the consequence of the interaction between tumor cells and stromal myofibroblasts. The metabolic changes in tumor cells include protein anabolism and the synthesis of cell membranes and nucleic acids, which all facilitate cell proliferation. They are linked to catabolism and autophagy in stromal myofibroblasts, causing the release of nutrients for the cells of the tumor parenchyma. Metabolic changes lead to an interstitium deficient in nutrients, such as glucose and amino acids, and acidification by lactic acid. Together with hypoxia, they produce functional changes in other cells of the tumor stroma, such as many immune subpopulations and endothelial cells, which lead to tumor growth. Thus, immune cells favor tissue growth through changes in immunosuppression. This review considers some of the metabolic changes described in breast cancer.

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.