Defining a metabolic landscape of tumours: genome meets metabolism

Metabolic heterogeneity in tumor microenvironment - A novel landmark for immunotherapy

The surrounding non-cancer cells and tumor cells that make up the tumor microenvironment (TME) have various metabolic rhythms. TME metabolic heterogeneity is influenced by the intricate network of metabolic control within and between cells. DNA, protein, transport, and microbial levels are important regulators of TME metabolic homeostasis. The effectiveness of immunotherapy is also closely correlated with alterations in TME metabolism. The response of a tumor patient to immunotherapy is influenced by a variety of variables, including intracellular metabolic reprogramming, metabolic interaction between cells, ecological changes within and between tumors, and general dietary preferences. Although immunotherapy and targeted therapy have made great strides, their use in the accurate identification and treatment of tumors still has several limitations. The function of TME metabolic heterogeneity in tumor immunotherapy is summarized in this article. It focuses on how metabolic heterogeneity develops and is regulated as a tumor progresses, the precise molecular mechanisms and potential clinical significance of imbalances in intracellular metabolic homeostasis and intercellular metabolic coupling and interaction, as well as the benefits and drawbacks of targeted metabolism used in conjunction with immunotherapy. This offers insightful knowledge and important implications for individualized tumor patient diagnosis and treatment plans in the future.

Metabolic vulnerabilities in cancer: A new therapeutic strategy

Cancer metabolism is now a key area for therapeutic intervention, targeting unique metabolic reprogramming crucial for tumor growth and survival. This article reviews the therapeutic potential of addressing metabolic vulnerabilities through glycolysis and glutaminase inhibitors, which disrupt cancer cell metabolism. Challenges such as tumor heterogeneity and adaptive resistance are discussed, with strategies including personalized medicine and predictive biomarkers to enhance treatment efficacy. Additionally, integrating diet and lifestyle changes with metabolic targeting underscores a holistic approach to improving therapy outcomes. The article also examines the benefits of incorporating these strategies into standard care, highlighting the potential for more tailored, safer treatments. In conclusion, exploiting metabolic vulnerabilities promises a new era in oncology, positioning metabolic targeting at the forefront of personalized cancer therapy and transforming patient care.

Tumor initiation and early tumorigenesis: molecular mechanisms and interventional targets

Tumorigenesis is a multistep process, with oncogenic mutations in a normal cell conferring clonal advantage as the initial event. However, despite pervasive somatic mutations and clonal expansion in normal tissues, their transformation into cancer remains a rare event, indicating the presence of additional driver events for progression to an irreversible, highly heterogeneous, and invasive lesion. Recently, researchers are emphasizing the mechanisms of environmental tumor risk factors and epigenetic alterations that are profoundly influencing early clonal expansion and malignant evolution, independently of inducing mutations. Additionally, clonal evolution in tumorigenesis reflects a multifaceted interplay between cell-intrinsic identities and various cell-extrinsic factors that exert selective pressures to either restrain uncontrolled proliferation or allow specific clones to progress into tumors. However, the mechanisms by which driver events induce both intrinsic cellular competency and remodel environmental stress to facilitate malignant transformation are not fully understood. In this review, we summarize the genetic, epigenetic, and external driver events, and their effects on the co-evolution of the transformed cells and their ecosystem during tumor initiation and early malignant evolution. A deeper understanding of the earliest molecular events holds promise for translational applications, predicting individuals at high-risk of tumor and developing strategies to intercept malignant transformation.

Metabolic Insight into Glioma Heterogeneity: Mapping Whole Exome Sequencing to In Vivo Imaging with Stereotactic Localization and Deep Learning

Intratumoral heterogeneity (ITH) complicates the diagnosis and treatment of glioma, partly due to the diverse metabolic profiles driven by underlying genomic alterations. While multiparametric imaging enhances the characterization of ITH by capturing both spatial and functional variations, it falls short in directly assessing the metabolic activities that underpin these phenotypic differences. This gap stems from the challenge of integrating easily accessible, colocated pathology and detailed genomic data with metabolic insights. This study presents a multifaceted approach combining stereotactic biopsy with standard clinical open-craniotomy for sample collection, voxel-wise analysis of MR images, regression-based GAM, and whole-exome sequencing. This work aims to demonstrate the potential of machine learning algorithms to predict variations in cellular and molecular tumor characteristics. This retrospective study enrolled ten treatment-naïve patients with radiologically confirmed glioma. Each patient underwent a multiparametric MR scan (T1W, T1W-CE, T2W, T2W-FLAIR, DWI) prior to surgery. During standard craniotomy, at least 1 stereotactic biopsy was collected from each patient, with screenshots of the sample locations saved for spatial registration to pre-surgical MR data. Whole-exome sequencing was performed on flash-frozen tumor samples, prioritizing the signatures of five glioma-related genes: IDH1, TP53, EGFR, PIK3CA, and NF1. Regression was implemented with a GAM using a univariate shape function for each predictor. Standard receiver operating characteristic (ROC) analyses were used to evaluate detection, with AUC (area under curve) calculated for each gene target and MR contrast combination. Mean AUC for five gene targets and 31 MR contrast combinations was 0.75 ± 0.11; individual AUCs were as high as 0.96 for both IDH1 and TP53 with T2W-FLAIR and ADC, and 0.99 for EGFR with T2W and ADC. These results suggest the possibility of predicting exome-wide mutation events from noninvasive, in vivo imaging by combining stereotactic localization of glioma samples and a semi-parametric deep learning method. The genomic alterations identified, particularly in IDH1, TP53, EGFR, PIK3CA, and NF1, are known to play pivotal roles in metabolic pathways driving glioma heterogeneity. Our methodology, therefore, indirectly sheds light on the metabolic landscape of glioma through the lens of these critical genomic markers, suggesting a complex interplay between tumor genomics and metabolism. This approach holds potential for refining targeted therapy by better addressing the genomic heterogeneity of glioma tumors.

Cellular and clinical impact of protein phosphatase enzyme epigenetic silencing in multiple cancer tissues

BACKGROUND

Protein Phosphatase Enzymes (PPE) and protein kinases simultaneously control phosphorylation mechanisms that tightly regulate intracellular signalling pathways and stimulate cellular responses. In human malignancies, PPE and protein kinases are frequently mutated resulting in uncontrolled kinase activity and PPE suppression, leading to cell proliferation, migration and resistance to anti-cancer therapies. Cancer associated DNA hypermethylation at PPE promoters gives rise to transcriptional silencing (epimutations) and is a hallmark of cancer. Despite recent advances in sequencing technologies, data availability and computational capabilities, only a fraction of PPE have been reported as transcriptionally inactive as a consequence of epimutations.

METHODS

In this study, we examined promoter-associated DNA methylation profiles in Protein Phosphatase Enzymes and their Interacting Proteins (PPEIP) in a cohort of 705 cancer patients in five tissues (Large intestine, Oesophagus, Lung, Pancreas and Stomach) in three cell models (primary tumours, cancer cell lines and 3D embedded cancer cell cultures). As a subset of PPEIP are known tumour suppressor genes, we analysed the impact of PPEIP promoter hypermethylation marks on gene expression, cellular networks and in a clinical setting.

RESULTS

Here, we report epimutations in PPEIP are a frequent occurrence in the cancer genome and manifest independent of transcriptional activity. We observed that different tumours have varying susceptibility to epimutations and identify specific cellular signalling networks that are primarily affected by epimutations. Additionally, RNA-seq analysis showed the negative impact of epimutations on most (not all) Protein Tyrosine Phosphatase transcription. Finally, we detected novel clinical biomarkers that inform on patient mortality and anti-cancer treatment sensitivity.

CONCLUSIONS

We propose that DNA hypermethylation marks at PPEIP frequently contribute to the pathogenesis of malignancies and within the precision medicine space, hold promise as biomarkers to inform on clinical features such as patient survival and therapeutic response.

Comprehensive analysis the prognostic and immune characteristics of mitochondrial transport-related gene SFXN1 in lung adenocarcinoma

BACKGROUND

Mitochondria, which serve as the fundamental organelle for cellular energy and metabolism, are closely linked to the growth and survival of cancer cells. This study aims to identify and assess Sideroflexin1 (SFXN1), an unprecedented mitochondrial gene, as a potential prognostic biomarker for lung adenocarcinoma (LUAD).

METHODS

The mRNA and protein levels of SFXN1 were investigated based on the Cancer Genome Atlas (TCGA) LUAD dataset, and then validated by real-time quantitative PCR, Western Blotting and immunohistochemistry from our clinical samples. The clinical correlation and prognostic value were evaluated by the TCGA cohort and verified via our clinical dataset (n = 90). The somatic mutation, drug sensitivity data, immune cell infiltration and single-cell RNA sequencing data of SFXN1 were analyzed through public databases.

RESULTS

SFXN1 was markedly upregulated at both mRNA and protein levels in LUAD, and high expression of SFXN1 were correlated with larger tumor size, positive lymph node metastasis, and advanced clinical stage. Furthermore, SFXN1 upregulation was significantly associated with poor clinical prognosis. SFXN1 co-expressed genes were also analyzed, which were mainly involved in the cell cycle, central carbon metabolism, DNA repair, and the HIF-1α signaling pathway. Additionally, SFXN1 expression correlated with the expression of multiple immunomodulators, which act to regulate the tumor immune microenvironment. Results also demonstrated an association between SFXN1 expression and increased immune cell infiltration, such as activated CD8 + T cells, natural killer cells (NKs), activated dendritic cells (DCs), and macrophages. LUAD patients with high SFXN1 expression exhibited heightened sensitivity to multiple chemotherapies and targeted drugs and predicted a poor response to immunotherapy. SFXN1 represented an independent prognostic marker for LUAD patients with an improved prognostic value for overall survival when combined with clinical stage information.

CONCLUSIONS

SFXN1 is frequently upregulated in LUAD and has a significant impact on the tumor immune environment. Our study uncovers the potential of SFXN1 as a prognostic biomarker and as a novel target for intervention in LUAD.

Uncovering novel therapeutic targets in glucose, nucleotides and lipids metabolism during cancer and neurological diseases

BACKGROUND

Cell metabolism functions without a stop in normal and pathological cells. Different metabolic changes occur in the disease. Cell metabolism influences biochemical and metabolic processes, signaling pathways, and gene regulation. Knowledge regarding disease metabolism is limited.

OBJECTIVE

The review examines the cell metabolism of glucose, nucleotides, and lipids during homeostatic and pathological conditions of neurotoxicity, neuroimmunological disease, Parkinson's disease, thymoma in myasthenia gravis, and colorectal cancer.

METHODS

Data collection includes electronic databases, the National Center for Biotechnology Information, and Google Scholar, with several inclusion criteria: cell metabolism, glucose metabolism, nucleotide metabolism, and lipid metabolism in health and disease patients suffering from neurotoxicity, neuroinflammation, Parkinson's disease, thymoma in myasthenia gravis. The initial number of collected and analyzed papers is 250. The final analysis included 150 studies out of 94 selected papers. After the selection process, 62.67% remains useful.

RESULTS AND CONCLUSION

A literature search shows that signaling molecules are involved in metabolic changes in cells. Differences between cancer and neuroimmunological diseases are present in the result section. Our finding enables insight into novel therapeutic targets and the development of scientific approaches for cancer and neurological disease onset, outcome, progression, and treatment, highlighting the importance of metabolic dysregulation. Current understanding, emerging research technologies and potential therapeutic interventions in metabolic programming is disucussed and highlighted.

Deep neural network for discovering metabolism-related biomarkers for lung adenocarcinoma

Introduction

Lung cancer is a major cause of illness and death worldwide. Lung adenocarcinoma (LUAD) is its most common subtype. Metabolite-mRNA interactions play a crucial role in cancer metabolism. Thus, metabolism-related mRNAs are potential targets for cancer therapy.

Methods

This study constructed a network of metabolite-mRNA interactions (MMIs) using four databases. We retrieved mRNAs from the Tumor Genome Atlas (TCGA)-LUAD cohort showing significant expressional changes between tumor and non-tumor tissues and identified metabolism-related differential expression (DE) mRNAs among the MMIs. Candidate mRNAs showing significant contributions to the deep neural network (DNN) model were mined. Using MMIs and the results of function analysis, we created a subnetwork comprising candidate mRNAs and metabolites.

Results

Finally, 10 biomarkers were obtained after survival analysis and validation. Their good prognostic value in LUAD was validated in independent datasets. Their effectiveness was confirmed in the TCGA and an independent Clinical Proteomic Tumor Analysis Consortium (CPTAC) dataset by comparison with traditional machine-learning models.

Conclusion

To summarize, 10 metabolism-related biomarkers were identified, and their prognostic value was confirmed successfully through the MMI network and the DNN model. Our strategy bears implications to pave the way for investigating metabolic biomarkers in other cancers.

Intratumoral metabolic heterogeneity of colorectal cancer

Although the metabolic phenotype within tumors is known to differ significantly from that of the surrounding normal tissue, the importance of this heterogeneity is just becoming widely recognized. Colorectal cancer (CRC) is often classified as the Warburg phenotype, a metabolic type in which the glycolytic system is predominant over oxidative phosphorylation (OXPHOS) in mitochondria for energy production. However, this dichotomy (glycolysis vs. OXPHOS) may be too simplistic and not accurately represent the metabolic characteristics of CRC. Therefore, in this review, we decompose metabolic phenomena into factors based on their source/origin and reclassify them into two categories: extrinsic and intrinsic. In the CRC context, extrinsic factors include those based on the environment, such as hypoxia, nutrient deprivation, and the tumor microenvironment, whereas intrinsic factors include those based on subpopulations, such as pathological subtypes and cancer stem cells. These factors form multiple layers inside and outside the tumor, affecting them additively, dominantly, or mutually exclusively. Consequently, the metabolic phenotype is a heterogeneous and fluid phenomenon reflecting the spatial distribution and temporal continuity of these factors. This allowed us to redefine the characteristics of specific metabolism-related factors in CRC and summarize and update our accumulated knowledge of their heterogeneity. Furthermore, we positioned tumor budding in CRC as an intrinsic factor and a novel form of metabolic heterogeneity, and predicted its metabolic dynamics, noting its similarity to circulating tumor cells and epithelial-mesenchymal transition. Finally, the possibilities and limitations of using human tumor tissue as research material to investigate and assess metabolic heterogeneity are discussed.

Omics Technologies Improving Breast Cancer Research and Diagnostics

Breast cancer (BC) has yielded approximately 2.26 million new cases and has caused nearly 685,000 deaths worldwide in the last two years, making it the most common diagnosed cancer type in the world. BC is an intricate ecosystem formed by both the tumor microenvironment and malignant cells, and its heterogeneity impacts the response to treatment. Biomedical research has entered the era of massive omics data thanks to the high-throughput sequencing revolution, quick progress and widespread adoption. These technologies-liquid biopsy, transcriptomics, epigenomics, proteomics, metabolomics, pharmaco-omics and artificial intelligence imaging-could help researchers and clinicians to better understand the formation and evolution of BC. This review focuses on the findings of recent multi-omics-based research that has been applied to BC research, with an introduction to every omics technique and their applications for the different BC phenotypes, biomarkers, target therapies, diagnosis, treatment and prognosis, to provide a comprehensive overview of the possibilities of BC research.

Metabolic profiling stratifies colorectal cancer and reveals adenosylhomocysteinase as a therapeutic target

The genomic landscape of colorectal cancer (CRC) is shaped by inactivating mutations in tumour suppressors such as APC, and oncogenic mutations such as mutant KRAS. Here we used genetically engineered mouse models, and multimodal mass spectrometry-based metabolomics to study the impact of common genetic drivers of CRC on the metabolic landscape of the intestine. We show that untargeted metabolic profiling can be applied to stratify intestinal tissues according to underlying genetic alterations, and use mass spectrometry imaging to identify tumour, stromal and normal adjacent tissues. By identifying ions that drive variation between normal and transformed tissues, we found dysregulation of the methionine cycle to be a hallmark of APC-deficient CRC. Loss of Apc in the mouse intestine was found to be sufficient to drive expression of one of its enzymes, adenosylhomocysteinase (AHCY), which was also found to be transcriptionally upregulated in human CRC. Targeting of AHCY function impaired growth of APC-deficient organoids in vitro, and prevented the characteristic hyperproliferative/crypt progenitor phenotype driven by acute deletion of Apc in vivo, even in the context of mutant Kras. Finally, pharmacological inhibition of AHCY reduced intestinal tumour burden in ApcMin/+ mice indicating its potential as a metabolic drug target in CRC.

Adjuvant Treatments for Surgically Resected Non-Small Cell Lung Cancer Harboring EGFR Mutations: A Review

Importance

The use of adjuvant chemotherapy for stage IB-IIIA resected non-small cell lung cancer (NSCLC) has limited benefit for improving cure rates. The proportion of epidermal growth factor receptor (EGFR) alterations among patients with resected NSCLC is comparable to that observed in patients with advanced disease, and the use of EGFR tyrosine kinase inhibitors (TKIs) has been demonstrated to prolong disease-free survival (DFS). With recent approval of osimertinib in this context, a focus on the rapidly evolving scenario and future perspective in clinical practice is needed and was the aim of the current review.

Observations

Randomized phase 3 clinical trials demonstrated DFS benefit with adjuvant EGFR TKI therapy in patients with resected EGFR mutation-positive NSCLC. The most recent trial (ADAURA) assessed 3-year adjuvant osimertinib and showed consistent DFS benefit and a significant role of the intervention in preventing the occurrence of brain metastasis. However, the role of adjuvant chemotherapy, the appropriate duration of treatment, the management of disease relapse, and the effective cure rate remain undetermined. A deeper investigation on molecular biomarkers, covariant patterns, and dynamic monitoring of postsurgical circulating DNA would be helpful for the implementation of future strategies to further improve survival rates after adjuvant therapy for EGFR mutation-positive NSCLC.

Conclusions and Relevance

Adjuvant osimertinib revolutionized the treatment algorithm for patients with stage IB-IIIA resected EGFR mutation-positive NSCLC. Further evidence driven by clinical issues will be key for further optimization of the goals of adjuvant treatment in these patients.

Rethinking our approach to cancer metabolism to deliver patient benefit

Altered cellular metabolism is a major mechanism by which tumours support nutrient consumption associated with increased cellular proliferation. Selective dependency on specific metabolic pathways provides a therapeutic vulnerability that can be targeted in cancer therapy. Anti-metabolites have been used clinically since the 1940s and several agents targeting nucleotide metabolism are now well established as standard of care treatment in a range of indications. However, despite great progress in our understanding of the metabolic requirements of cancer and non-cancer cells within the tumour microenvironment, there has been limited clinical success for novel agents targeting pathways outside of nucleotide metabolism. We believe that there is significant therapeutic potential in targeting metabolic processes within cancer that is yet to be fully realised. However, current approaches to identify novel targets, test novel therapies and select patient populations most likely to benefit are sub-optimal. We highlight recent advances in technologies and understanding that will support the identification and validation of novel targets, re-evaluation of existing targets and design of optimal clinical positioning strategies to deliver patient benefit.

Co-Targeting FASN and mTOR Suppresses Uveal Melanoma Growth

Uveal melanoma (UM) displays a high frequency of metastasis; however, effective therapies for metastatic UM are limited. Identifying unique metabolic features of UM may provide a potential targeting strategy. A lipid metabolism protein expression signature was induced in a normal choroidal melanocyte (NCM) line transduced with GNAQ (Q209L), a driver in UM growth and development. Consistently, UM cells expressed elevated levels of fatty acid synthase (FASN) compared to NCMs. FASN upregulation was associated with increased mammalian target of rapamycin (mTOR) activation and sterol regulatory element-binding protein 1 (SREBP1) levels. FASN and mTOR inhibitors alone significantly reduced UM cell growth. Concurrent inhibition of FASN and mTOR further reduced UM cell growth by promoting cell cycle arrest and inhibiting glucose utilization, TCA cycle metabolism, and de novo fatty acid biosynthesis. Our findings indicate that FASN is important for UM cell growth and co-inhibition of FASN and mTOR signaling may be considered for treatment of UM.

Spatial metabolic heterogeneity of oligodendrogliomas at single-cell resolution

Oligodendrogliomas are a type of rare and incurable gliomas whose metabolic profiles have yet to be fully examined. The present study examined the spatial differences in metabolic landscapes underlying oligodendrogliomas and should provide unique insights into the metabolic characteristics of these uncommon tumors. Single-cell RNA-sequencing expression profiles from 4044 oligodendroglioma cells derived from tumors resected from four locations frontal, temporal, parietal, and frontotemporoinsular) and in which 1p/19q co-deletion and IDH1 or IDH2 mutations were confirmed were computationally analyzed through a robust workflow to elucidate relative differences in metabolic pathway activities among the different locations. Dimensionality reduction using metabolic expression profiles exhibited clustering corresponding to each location subgroup. From the 80 metabolic pathways examined, over 70 pathways had significantly different activity scores between location subgroups. Further analysis of metabolic heterogeneity suggests that mitochondrial oxidative phosphorylation accounts for considerable metabolic variation within the same locations. Steroid and fatty acid metabolism pathways were also found to be major contributors to heterogeneity. Oligodendrogliomas display distinct spatial metabolic differences in addition to intra-location metabolic heterogeneity.

Lactic acid fermentation: A maladaptive mechanism and an evolutionary throwback boosting cancer drug resistance

After four decades of research primarily focused on tumour genetics, the importance of metabolism in tumour biology is receiving renewed attention. Cancer cells undergo energy, biosynthetic and metabolic rewiring, which involves several pathways with a prevalent change from oxidative phosphorylation (OXPHOS) to lactic acid fermentation, known as the Warburg effect. During carcinogenesis, microenvironmental changes can trigger the transition from OXPHOS to lactic acid fermentation, an ancient form of energy supply, mimicking the behaviour of certain anaerobic unicellular organisms according to "atavistic" models of cancer. However, the role of this transition as a mechanism of cancer drug resistance is unclear. Here, we hypothesise that the metabolic rewiring of cancer cells to fermentation can be triggered, enhanced, and sustained by exposure to chronic or high-dose chemotherapy, thereby conferring resistance to drug therapy. We try to expand on the idea that metabolic reprogramming from OXPHOS to lactate fermentation in drug-resistant tumour cells occurs as a general phenotypic mechanism in any type of cancer, regardless of tumour cell heterogeneity, biodiversity, and genetic characteristics. This metabolic response may therefore represent a common feature in cancer biology that could be exploited for therapeutic purposes to overcome chemotherapy resistance, which is currently a major challenge in cancer treatment.

Allopregnanolone: Metabolism, Mechanisms of Action, and Its Role in Cancer

Allopregnanolone (3α-THP) has been one of the most studied progesterone metabolites for decades. 3α-THP and its synthetic analogs have been evaluated as therapeutic agents for pathologies such as anxiety and depression. Enzymes involved in the metabolism of 3α-THP are expressed in classical and nonclassical steroidogenic tissues. Additionally, due to its chemical structure, 3α-THP presents high affinity and agonist activity for nuclear and membrane receptors of neuroactive steroids and neurotransmitters, such as the Pregnane X Receptor (PXR), membrane progesterone receptors (mPR) and the ionotropic GABA_A receptor, among others. 3α-THP has immunomodulator and antiapoptotic properties. It also induces cell proliferation and migration, all of which are critical processes involved in cancer progression. Recently the study of 3α-THP has indicated that low physiological concentrations of this metabolite induce the progression of several types of cancer, such as breast, ovarian, and glioblastoma, while high concentrations inhibit it. In this review, we explore current knowledge on the metabolism and mechanisms of action of 3α-THP in normal and tumor cells.

Single cell metabolism: current and future trends

Single cell metabolomics is an emerging and rapidly developing field that complements developments in single cell analysis by genomics and proteomics. Major goals include mapping and quantifying the metabolome in sufficient detail to provide useful information about cellular function in highly heterogeneous systems such as tissue, ultimately with spatial resolution at the individual cell level. The chemical diversity and dynamic range of metabolites poses particular challenges for detection, identification and quantification. In this review we discuss both significant technical issues of measurement and interpretation, and progress toward addressing them, with recent examples from diverse biological systems. We provide a framework for further directions aimed at improving workflow and robustness so that such analyses may become commonly applied, especially in combination with metabolic imaging and single cell transcriptomics and proteomics.

Nanomedicines Targeting Metabolism in the Tumor Microenvironment

Cancer cells reprogram their metabolism to meet their growing demand for bioenergy and biosynthesis. The metabolic profile of cancer cells usually includes dysregulation of main nutritional metabolic pathways and the production of metabolites, which leads to a tumor microenvironment (TME) having the characteristics of acidity, hypoxic, and/or nutrient depletion. Therapies targeting metabolism have become an active and revolutionary research topic for anti-cancer drug development. The differential metabolic vulnerabilities between tumor cells and other cells within TME provide nanotechnology a therapeutic window of anti-cancer. In this review, we present the metabolic characteristics of intrinsic cancer cells and TME and summarize representative strategies of nanoparticles in metabolism-regulating anti-cancer therapy. Then, we put forward the challenges and opportunities of using nanoparticles in this emerging field.

Design and Synthesis of New Pyrimidine-Quinolone Hybrids as Novel hLDHA Inhibitors

A battery of novel pyrimidine-quinolone hybrids was designed by docking scaffold replacement as lactate dehydrogenase A (hLDHA) inhibitors. Structures with different linkers between the pyrimidine and quinolone scaffolds (10-21 and 24−31) were studied in silico, and those with the 2-aminophenylsulfide (U-shaped) and 4-aminophenylsulfide linkers (24−31) were finally selected. These new pyrimidine-quinolone hybrids (24−31)(a−c) were easily synthesized in good to excellent yields by a green catalyst-free microwave-assisted aromatic nucleophilic substitution reaction between 3-(((2/4-aminophenyl)thio)methyl)quinolin-2(1H)-ones 22/23(a−c) and 4-aryl-2-chloropyrimidines (1−4). The inhibitory activity against hLDHA of the synthesized hybrids was evaluated, resulting IC50 values of the U-shaped hybrids 24−27(a−c) much better than the ones of the 1,4-linked hybrids 28−31(a−c). From these results, a preliminary structure−activity relationship (SAR) was established, which enabled the design of novel 1,3-linked pyrimidine-quinolone hybrids (33−36)(a−c). Compounds 35(a−c), the most promising ones, were synthesized and evaluated, fitting the experimental results with the predictions from docking analysis. In this way, we obtained novel pyrimidine-quinolone hybrids (25a, 25b, and 35a) with good IC50 values (<20 μM) and developed a preliminary SAR.

A Resource to Infer Molecular Paths Linking Cancer Mutations to Perturbation of Cell Metabolism

Some inherited or somatically-acquired gene variants are observed significantly more frequently in the genome of cancer cells. Although many of these cannot be confidently classified as driver mutations, they may contribute to shaping a cell environment that favours cancer onset and development. Understanding how these gene variants causally affect cancer phenotypes may help developing strategies for reverting the disease phenotype. Here we focus on variants of genes whose products have the potential to modulate metabolism to support uncontrolled cell growth. Over recent months our team of expert curators has undertaken an effort to annotate in the database SIGNOR 1) metabolic pathways that are deregulated in cancer and 2) interactions connecting oncogenes and tumour suppressors to metabolic enzymes. In addition, we refined a recently developed graph analysis tool that permits users to infer causal paths leading from any human gene to modulation of metabolic pathways. The tool grounds on a human signed and directed network that connects ∼8400 biological entities such as proteins and protein complexes via causal relationships. The network, which is based on more than 30,000 published causal links, can be downloaded from the SIGNOR website. In addition, as SIGNOR stores information on drugs or other chemicals targeting the activity of many of the genes in the network, the identification of likely functional paths offers a rational framework for exploring new therapeutic strategies that revert the disease phenotype.

Combination strategies to target metabolic flexibility in cancer

Therapeutically interfering with metabolic pathways has great merit to curtail tumor growth because the demand for copious amounts of energy for growth-supporting biomass production is common to all cancer entities. A major impediment to a straight implementation of metabolic cancer therapy is the metabolic flexibility and plasticity of cancer cells (and their microenvironment) resulting in therapy resistance and evasion. Metabolic combination therapies, therefore, are promising as they are designed to target several energetic routes simultaneously and thereby diminish the availability of alternative substrates. Thus, dietary restrictions, specific nutrient limitations, and/or pharmacological interventions impinging on metabolic pathways can be combined to improve cancer treatment efficacy, to overcome therapy resistance, or even act as a preventive measure. Here, we review the most recent developments in metabolic combination therapies particularly highlighting in vivo reports of synergistic effects and available clinical data. We close with identifying the challenges of the field (metabolic tumor heterogeneity, immune cell interactions, inter-patient variabilities) and suggest a "metabo-typing" strategy to tailor evidence-based metabolic combination therapies to the energetic requirements of the tumors and the patient's nutritional habits and status.

Multi-Omics Approach Points to the Importance of Oxylipins Metabolism in Early-Stage Breast Cancer

The involvement of oxylipins, metabolites of polyunsaturated fatty acids, in cancer pathogenesis was known long ago, but only the development of the high-throughput methods get the opportunity to study oxylipins on a system level. The study aimed to elucidate alterations in oxylipin metabolism as characteristics of breast cancer patients. We compared the ultra-high-performance liquid chromatography-mass spectrometry (UPLC-MS/MS) oxylipin profile signatures in the blood plasma of 152 healthy volunteers (HC) and 169 patients with different stages of breast cancer (BC). To integrate lipidomics, transcriptomics, and genomics data, we analyzed a transcriptome of 10 open database datasets obtained from tissues and blood cells of BC patients and SNP data for 33 genes related to oxylipin metabolism. We identified 18 oxylipins, metabolites of omega-3 or omega-6 polyunsaturated fatty acids, that were differentially expressed between BCvsHC patients, including anandamide, prostaglandins and hydroxydocosahexaenoic acids. DEGs analysis of tissue and blood samples from BC patients revealed that 19 genes for oxylipin biosynthesis change their expression level, with CYP2C19, PTGS2, HPGD, and FAAH included in the list of DEGs in the analysis of transcriptomes and the list of SNPs associated with BC. Results allow us to suppose that oxylipin signatures reflect the organism's level of response to the disease. Our data regarding changes in oxylipins at the system level show that oxylipin profiles can be used to evaluate the early stages of breast cancer.

Combined impact of lipidomic and genetic aberrations on clinical outcomes in metastatic castration-resistant prostate cancer

BACKGROUND

Both changes in circulating lipids represented by a validated poor prognostic 3-lipid signature (3LS) and somatic tumour genetic aberrations are individually associated with worse clinical outcomes in men with metastatic castration-resistant prostate cancer (mCRPC). A key question is how the lipid environment and the cancer genome are interrelated in order to exploit this therapeutically. We assessed the association between the poor prognostic 3-lipid signature (3LS), somatic genetic aberrations and clinical outcomes in mCRPC.

METHODS

We performed plasma lipidomic analysis and cell-free DNA (cfDNA) sequencing on 106 men with mCRPC commencing docetaxel, cabazitaxel, abiraterone or enzalutamide (discovery cohort) and 94 men with mCRPC commencing docetaxel (validation cohort). Differences in lipid levels between men ± somatic genetic aberrations were assessed with t-tests. Associations between the 3LS and genetic aberrations with overall survival (OS) were examined using Kaplan-Meier methods and Cox proportional hazard models.

RESULTS

The 3LS was associated with shorter OS in the discovery (hazard ratio [HR] 2.15, 95% confidence interval [CI] 1.4-3.3, p < 0.001) and validation cohorts (HR 2.32, 95% CI 1.59-3.38, p < 0.001). Elevated plasma sphingolipids were associated with AR, TP53, RB1 and PI3K aberrations (p < 0.05). Men with both the 3LS and aberrations in AR, TP53, RB1 or PI3K had shorter OS than men with neither in both cohorts (p ≤ 0.001). The presence of 3LS and/or genetic aberration was independently associated with shorter OS for men with AR, TP53, RB1 and PI3K aberrations (p < 0.02). Furthermore, aggressive-variant prostate cancer (AVPC), defined as 2 or more aberrations in TP53, RB1 and/or PTEN, was associated with elevated sphingolipids. The combination of AVPC and 3LS predicted for a median survival of ~12 months. The relatively small sample size of the cohorts limits clinical applicability and warrants future studies.

CONCLUSIONS

Elevated circulating sphingolipids were associated with AR, TP53, RB1, PI3K and AVPC aberrations in mCRPC, and the combination of lipid and genetic abnormalities conferred a worse prognosis. These findings suggest that certain genotypes in mCRPC may benefit from metabolic therapies.

Drug Metabolism for the Identification of Clinical Biomarkers in Breast Cancer

Breast cancer is classified into four major molecular subtypes, and is considered a heterogenous disease. The risk profiles and treatment of breast cancer differ according to these subtypes. Early detection dramatically improves the prospects of successful treatment, resulting in a reduction in overall mortality rates. However, almost 30% of women primarily diagnosed with the early-stage disease will eventually develop metastasis or resistance to chemotherapies. Immunotherapies are among the most promising cancer treatment options; however, long-term clinical benefit has only been observed in a small subset of responding patients. The current strategies for diagnosis and treatment rely heavily on histopathological examination and molecular diagnosis, disregarding the tumor microenvironment and microbiome involving cancer cells. In this review, we aim to praise the use of pharmacogenomics and pharmacomicrobiomics as a strategy to identify potential biomarkers for guiding and monitoring therapy in real-time. The finding of these biomarkers can be performed by studying the metabolism of drugs, more specifically, immunometabolism, and its relationship with the microbiome, without neglecting the information provided by genetics. A larger understanding of cancer biology has the potential to improve patient care, enable clinical decisions, and deliver personalized medicine.

Natural product 1,2,3,4,6-penta-O-galloyl-β-D-glucopyranose is a reversible inhibitor of glyceraldehyde 3-phosphate dehydrogenase

Aerobic glycolysis, also known as the Warburg effect, is a hallmark of cancer cell glucose metabolism and plays a crucial role in the activation of various types of immune cells. Glyceraldehyde 3-phosphate dehydrogenase (GAPDH) catalyzes the conversion of D-glyceraldehyde 3-phosphate to D-glycerate 1,3-bisphosphate in the 6th critical step in glycolysis. GAPDH exerts metabolic flux control during aerobic glycolysis and therefore is an attractive therapeutic target for cancer and autoimmune diseases. Recently, GAPDH inhibitors were reported to function through common suicide inactivation by covalent binding to the cysteine catalytic residue of GAPDH. Herein, by developing a high-throughput enzymatic screening assay, we discovered that the natural product 1,2,3,4,6-penta-O-galloyl-β-D-glucopyranose (PGG) is an inhibitor of GAPDH with K_i = 0.5 μM. PGG blocks GAPDH activity by a reversible and NAD⁺ and Pi competitive mechanism, suggesting that it represents a novel class of GAPDH inhibitors. In-depth hydrogen deuterium exchange mass spectrometry (HDX-MS) analysis revealed that PGG binds to a region that disrupts NAD⁺ and inorganic phosphate binding, resulting in a distal conformational change at the GAPDH tetramer interface. In addition, structural modeling analysis indicated that PGG probably reversibly binds to the center pocket of GAPDH. Moreover, PGG inhibits LPS-stimulated macrophage activation by specific downregulation of GAPDH-dependent glucose consumption and lactate production. In summary, PGG represents a novel class of GAPDH inhibitors that probably reversibly binds to the center pocket of GAPDH. Our study sheds new light on factors for designing a more potent and specific inhibitor of GAPDH for future therapeutic applications.

The role of metabolic ecosystem in cancer progression — metabolic plasticity and mTOR hyperactivity in tumor tissues

Despite advancements in cancer management, tumor relapse and metastasis are associated with poor outcomes in many cancers. Over the past decade, oncogene-driven carcinogenesis, dysregulated cellular signaling networks, dynamic changes in the tissue microenvironment, epithelial-mesenchymal transitions, protein expression within regulatory pathways, and their part in tumor progression are described in several studies. However, the complexity of metabolic enzyme expression is considerably under evaluated. Alterations in cellular metabolism determine the individual phenotype and behavior of cells, which is a well-recognized hallmark of cancer progression, especially in the adaptation mechanisms underlying therapy resistance. In metabolic symbiosis, cells compete, communicate, and even feed each other, supervised by tumor cells. Metabolic reprogramming forms a unique fingerprint for each tumor tissue, depending on the cellular content and genetic, epigenetic, and microenvironmental alterations of the developing cancer. Based on its sensing and effector functions, the mechanistic target of rapamycin (mTOR) kinase is considered the master regulator of metabolic adaptation. Moreover, mTOR kinase hyperactivity is associated with poor prognosis in various tumor types. In situ metabolic phenotyping in recent studies highlights the importance of metabolic plasticity, mTOR hyperactivity, and their role in tumor progression. In this review, we update recent developments in metabolic phenotyping of the cancer ecosystem, metabolic symbiosis, and plasticity which could provide new research directions in tumor biology. In addition, we suggest pathomorphological and analytical studies relating to metabolic alterations, mTOR activity, and their associations which are necessary to improve understanding of tumor heterogeneity and expand the therapeutic management of cancer.

Regulation and functional role of the electron transport chain supercomplexes

Mitochondria are one of the most exhaustively investigated organelles in the cell and most attention has been paid to the components of the mitochondrial electron transport chain (ETC) in the last 100 years. The ETC collects electrons from NADH or FADH₂ and transfers them through a series of electron carriers within multiprotein respiratory complexes (complex I to IV) to oxygen, therefore generating an electrochemical gradient that can be used by the F₁-F₀-ATP synthase (also named complex V) in the mitochondrial inner membrane to synthesize ATP. The organization and function of the ETC is a continuous source of surprises. One of the latest is the discovery that the respiratory complexes can assemble to form a variety of larger structures called super-complexes (SCs). This opened an unexpected level of complexity in this well-known and fundamental biological process. This review will focus on the current evidence for the formation of different SCs and will explore how they modulate the ETC organization according to the metabolic state. Since the field is rapidly growing, we also comment on the experimental techniques used to describe these SC and hope that this overview may inspire new technologies that will help to advance the field.

Redox metabolism: ROS as specific molecular regulators of cell signaling and function

Redox reactions are intrinsically linked to energy metabolism. Therefore, redox processes are indispensable for organismal physiology and life itself. The term reactive oxygen species (ROS) describes a set of distinct molecular oxygen derivatives produced during normal aerobic metabolism. Multiple ROS-generating and ROS-eliminating systems actively maintain the intracellular redox state, which serves to mediate redox signaling and regulate cellular functions. ROS, in particular hydrogen peroxide (H₂O₂), are able to reversibly oxidize critical, redox-sensitive cysteine residues on target proteins. These oxidative post-translational modifications (PTMs) can control the biological activity of numerous enzymes and transcription factors (TFs), as well as their cellular localization or interactions with binding partners. In this review, we describe the diverse roles of redox regulation in the context of physiological cellular metabolism and provide insights into the pathophysiology of diseases when redox homeostasis is dysregulated.

A Transcriptomic Approach Reveals Selective Ribosomal Remodelling in the Tumour Versus the Stromal Compartment of Metastatic Colorectal Cancer

Simple Summary

In this study, we analyzed a cohort of six colorectal cancer patients harboring KRAS mutations and with wild-type BRAF from a transcriptional perspective, with the aim of elucidating the role of the stromal cells in tumor progression. Specifically, paraffin-embedded specimens were subjected to microdissection and hybridized on Agilent-026652 microarrays to compare the gene expression of tumor samples composed of neoplastic epithelial samples against the neighboring stromal tissue. A paired rank-product test led to the detection of 193 differentially expressed genes. Subsequent functional enrichment analysis pointed to extracellular matrix constituents, angiogenesis, and cell migration as the main biological processes enhanced in stromata, while the tumor compartment was characterized by an overexpression of many ribosomal protein genes. A further gene set enrichment analysis against a comprehensive ribosomal protein gene set finally revealed that only cytosolic ribosomes (80S) were affected by such upregulation, while mitochondrial ribosomes were virtually unaltered.

Abstract

Because of its high incidence and poor prognosis, colorectal cancer (CRC) represents an important health issue in several countries. As with other carcinomas, the so-called tumour microenvironment (TME) has been shown to play key roles in CRC progression and related therapeutical outcomes, even though a deeper understanding of the underlying molecular mechanisms is needed to devise new treatment strategies. For some years now, omics technologies and consolidated bioinformatics pipelines have allowed scientists to access large amounts of biologically relevant information, even when starting from small tissue samples; thus, in order to shed new light upon the role of the TME in CRC, we compared the gene expression profiles of 6 independent tumour tissues (all progressed towards metastatic disease) to the expression profile of the surrounding stromata. To do this, paraffin-embedded whole tissues were first microdissected to obtain samples enriched with tumour and stromal cells, respectively. Afterwards, RNA was extracted and analysed using a microarray-based approach. A thorough bioinformatics analysis was then carried out to identify transcripts differentially expressed between the two groups and possibly enriched functional terms. Overall, 193 genes were found to be significantly downregulated in tumours compared to the paired stromata. The functional analysis of the downregulated gene list revealed three principal macro areas of interest: the extracellular matrix, cell migration, and angiogenesis. Conversely, among the upregulated genes, the main alterations detected by the functional annotation were related to the ribosomal proteins (rProteins) of both the large (60S) and small (40S) subunits of the cytosolic ribosomes. Subsequent gene set enrichment analysis (GSEA) confirmed the massive overexpression of most cytosolic—but not mitochondrial—ribosome rProteins.

Tumor Microenvironment-Derived Metabolites: A Guide to Find New Metabolic Therapeutic Targets and Biomarkers

Metabolic reprogramming is a hallmark of cancer that enables cancer cells to grow, proliferate and survive. This metabolic rewiring is intrinsically regulated by mutations in oncogenes and tumor suppressors, but also extrinsically by tumor microenvironment factors (nutrient and oxygen availability, cell-to-cell interactions, cytokines, hormones, etc.). Intriguingly, only a few cancers are driven by mutations in metabolic genes, which lead metabolites with oncogenic properties (i.e., oncometabolites) to accumulate. In the last decade, there has been rekindled interest in understanding how dysregulated metabolism and its crosstalk with various cell types in the tumor microenvironment not only sustains biosynthesis and energy production for cancer cells, but also contributes to immune escape. An assessment of dysregulated intratumor metabolism has long since been exploited for cancer diagnosis, monitoring and therapy, as exemplified by 18F-2-deoxyglucose positron emission tomography imaging. However, the efficient delivery of precision medicine demands less invasive, cheaper and faster technologies to precisely predict and monitor therapy response. The metabolomic analysis of tumor and/or microenvironment-derived metabolites in readily accessible biological samples is likely to play an important role in this sense. Here, we review altered cancer metabolism and its crosstalk with the tumor microenvironment to focus on energy and biomass sources, oncometabolites and the production of immunosuppressive metabolites. We provide an overview of current pharmacological approaches targeting such dysregulated metabolic landscapes and noninvasive approaches to characterize cancer metabolism for diagnosis, therapy and efficacy assessment.

Metabolic Alterations and Therapeutic Opportunities in Rare Forms of Melanoma

Melanoma is derived from melanocytes located in multiple regions of the body. Cutaneous melanoma (CM) represents the major subgroup, but less-common subtypes including uveal melanoma (UM), mucosal melanoma (MM), and acral melanoma (AM) arise that have distinct genetic profiles. Treatments effective for CM are ineffective in UM, AM, and MM, and patient survival remains poor. As reprogrammed cancer metabolism is associated with tumorigenesis, the underlying mechanisms are well studied and provide therapeutic opportunities in many cancers; however, metabolism is less well studied in rarer melanoma subtypes. We summarize current knowledge of the metabolic alterations in rare melanoma and potential applications of targeting cancer metabolism to improve the therapeutic options available to UM, AM, and MM patients.

Succinate Pathway in Head and Neck Squamous Cell Carcinoma: Potential as a Diagnostic and Prognostic Marker

Simple Summary

Emerging evidence points to succinate as an important oncometabolite in cancer development; however, the contribution of the succinate-SUCNR1 axis to cancer progression remains unclear. Head and neck squamous cell carcinoma (HNSCC) is associated with disease and treatment-related morbidity so there is an urgent need for innovation in treatment and diagnosis practices. Our aim was to evaluate the potential of the succinate-related pathway as a diagnostic and prognostic biomarker in HNSCC. The circulating succinate levels are increased in HNSCC, being a potential noninvasive biomarker for HNSCC diagnosis. Moreover, the succinate receptor (SUCNR1) and genes related to succinate metabolism, which are predominantly expressed in the tumoral mucosa as compared with healthy tissue, are positively associated with plasma succinate. Remarkably, we found that SUCNR1 and SDHA expression levels predict prognosis.

Abstract

Head and neck squamous cell carcinoma (HNSCC) is characterized by high rates of mortality and treatment-related morbidity, underscoring the urgent need for innovative and safe treatment strategies and diagnosis practices. Mitochondrial dysfunction is a hallmark of cancer and can lead to the accumulation of tricarboxylic acid cycle intermediates, such as succinate, which function as oncometabolites. In addition to its role in cancer development through epigenetic events, succinate is an extracellular signal transducer that modulates immune response, angiogenesis and cell invasion by activating its cognate receptor SUCNR1. Here, we explored the potential value of the circulating succinate and related genes in HNSCC diagnosis and prognosis. We determined the succinate levels in the serum of 66 pathologically confirmed, untreated patients with HNSCC and 20 healthy controls. We also surveyed the expression of the genes related to succinate metabolism and signaling in tumoral and nontumoral adjacent tissue and in normal mucosa from 50 patients. Finally, we performed immunohistochemical analysis of SUCNR1 in mucosal samples. The results showed that the circulating levels of succinate were higher in patients with HNSCC than in the healthy controls. Additionally, the expression of SUCNR1, HIF-1α, succinate dehydrogenase (SDH) A, and SDHB was higher in the tumor tissue than in the matched normal mucosa. Consistent with this, immunohistochemical analysis revealed an increase in SUCNR1 protein expression in tumoral and nontumoral adjacent tissue. High SUCNR1 and SDHA expression levels were associated with poor locoregional control, and the locoregional recurrence-free survival rate was significantly lower in patients with high SUCNR1 and SDHA expression than in their peers with lower levels (77.1% [95% CI: 48.9–100.0] vs. 16.7% [95% CI: 0.0–44.4], p = 0.018). Thus, the circulating succinate levels are elevated in HNSCC and high SUCNR1/SDHA expression predicts poor locoregional disease-free survival, identifying this oncometabolite as a potentially valuable noninvasive biomarker for HNSCC diagnosis and prognosis.

Targeting the Metabolic Adaptation of Metastatic Cancer

Simple Summary

The search for new therapeutic opportunities to target cancer metastasis is crucial for the improvement of cancer treatment. One of the characteristics of tumoral and metastatic cells is the capacity to reorganize their metabolism, together with the ability to grow faster, migrate and form new tumours in distant sites. Therefore, the pharmaceutical inhibition of metabolic pathways represents a promising strategy to specifically target metastatic cells, especially in colorectal cancer metastasis.

Abstract

Metabolic adaptation is emerging as an important hallmark of cancer and metastasis. In the last decade, increasing evidence has shown the importance of metabolic alterations underlying the metastatic process, especially in breast cancer metastasis but also in colorectal cancer metastasis. Being the main cause of cancer-related deaths, it is of great importance to developing new therapeutic strategies that specifically target metastatic cells. In this regard, targeting metabolic pathways of metastatic cells is one of the more promising windows for new therapies of metastatic colorectal cancer, where still there are no approved inhibitors against metabolic targets. In this study, we review the recent advances in the field of metabolic adaptation of cancer metastasis, focusing our attention on colorectal cancer. In addition, we also review the current status of metabolic inhibitors for cancer treatment.

Architectural control of metabolic plasticity in epithelial cancer cells

Metabolic plasticity enables cancer cells to switch between glycolysis and oxidative phosphorylation to adapt to changing conditions during cancer progression, whereas metabolic dependencies limit plasticity. To understand a role for the architectural environment in these processes we examined metabolic dependencies of cancer cells cultured in flat (2D) and organotypic (3D) environments. Here we show that cancer cells in flat cultures exist in a high energy state (oxidative phosphorylation), are glycolytic, and depend on glucose and glutamine for growth. In contrast, cells in organotypic culture exhibit lower energy and glycolysis, with extensive metabolic plasticity to maintain growth during glucose or amino acid deprivation. Expression of KRAS^G12V in organotypic cells drives glucose dependence, however cells retain metabolic plasticity to glutamine deprivation. Finally, our data reveal that mechanical properties control metabolic plasticity, which correlates with canonical Wnt signaling. In summary, our work highlights that the architectural and mechanical properties influence cells to permit or restrict metabolic plasticity.

Aconitase 2 sensitizes MCF-7 cells to cisplatin eliciting p53-mediated apoptosis in a ROS-dependent manner

Aconitase 2 (ACO2) belongs to the tricarboxylic acid (TCA) cycle, which represents a key metabolic hub for cellular metabolism that is frequently altered in cancer for satisfying bioenergetic and biosynthetic requirements of proliferating cells. The promotion of ACO2 activity in breast cancer cell lines was shown to slow down proliferation imposing a switch from aerobic glycolysis to oxidative metabolism. The alteration of metabolic pathways in cancer also impinges on the sensitivity to chemotherapeutic interventions. In this work, we evidence that the presence of ACO2 sensitizes cells to the treatment with the genotoxic agents cisplatin (CDDP) and doxorubicin activating the apoptotic cell death mechanism. This response was driven by the accumulation of reactive oxygen species (ROS) following both ACO2 overexpression and CDDP exposure that permit the stabilization/activation of p53 in nuclear and mitochondrial compartments. Collectively, our results highlight that in ACO2 overexpressing cells the promotion of mitochondrial metabolism accounts for increased ROS production that was buffered by p53 mitochondrial recruitment and autophagy induction. However, these systems are not able to counteract the CDDP-mediated oxidative stress that becomes the Achilles heel for increasing susceptibility to apoptotic cell death.

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.

Resolving Metabolic Heterogeneity in Experimental Models of the Tumor Microenvironment from a Stable Isotope Resolved Metabolomics Perspective

The tumor microenvironment (TME) comprises complex interactions of multiple cell types that determines cell behavior and metabolism such as nutrient competition and immune suppression. We discuss the various types of heterogeneity that exist in solid tumors, and the complications this invokes for studies of TME. As human subjects and in vivo model systems are complex and difficult to manipulate, simpler 3D model systems that are compatible with flexible experimental control are necessary for studying metabolic regulation in TME. Stable Isotope Resolved Metabolomics (SIRM) is a valuable tool for tracing metabolic networks in complex systems, but at present does not directly address heterogeneous metabolism at the individual cell level. We compare the advantages and disadvantages of different model systems for SIRM experiments, with a focus on lung cancer cells, their interactions with macrophages and T cells, and their response to modulators in the immune microenvironment. We describe the experimental set up, illustrate results from 3D cultures and co-cultures of lung cancer cells with human macrophages, and outline strategies to address the heterogeneous TME.

Metabolic alterations in the tumor microenvironment and their role in oncogenesis

Metabolic reprogramming is a characteristic feature of both cancer cells and their neighbouring cells in the tumor microenvironment (TME). The latter include stroma fibroblasts and adipocytes, that respectively differentiate to become cancer associated fibroblasts (CAFs) and cancer associated adipocytes (CAAs), and infiltrated immune cells, that collaborate with the stromal cells to provide the tumor a pro-tumorigenic niche. Here we discuss the association between the reprogramming of glucose metabolism in the TME and oncogenic signaling and its reflection in the non-canonical functions of metabolic enzymes. We also discuss the non-canonical actions of oncometabolites and the contribution to oncogenesis of external metabolites that accumulate in the TME as result of crosstalk between the tumor and the TME. Special emphasis is given in this regard to lysophosphatidic acid (LPA) and adenosine, two powerful metabolites, the concentrations of which rise in the TME due to altered metabolism of the tumor and its surrounding cells, allowing their action as external signals.

Large-Scale Differential Gene Expression Transcriptomic Analysis Identifies a Metabolic Signature Shared by All Cancer Cells

Cancer-dependent metabolic rewiring is often manifested by selective expression of enzymes essential for the transformed cells’ viability. However, the metabolic variations between normal and transformed cells are not fully characterized, and therefore, a systematic analysis will result in the identification of unknown cellular mechanisms crucial for tumorigenesis. Here, we applied differential gene expression transcriptome analysis to examine the changes in metabolic gene profiles between a wide range of normal tissues and cancer samples. We found that, in contrast to normal tissues which exhibit a tissue-specific expression profile, cancer samples are more homogenous despite their diverse origins. This similarity is due to a “proliferation metabolic signature” (PMS), composed of 158 genes (87 upregulated and 71 downregulated gene sets), where 143 are common to all proliferative cells but 15 are cancer specific. Intriguingly, the PMS gene set is enriched for genes encoding rate-limiting enzymes, and its upregulated set with genes associated with poor patient outcome and essential genes. Among these essential genes is ribulose-5-phosphate-3-epimerase (RPE), which encodes a pentose phosphate pathway enzyme and whose role in cancer is still unclear. Collectively, we identified a set of metabolic genes that can serve as novel cancer biomarkers and potential targets for drug development.

Metabolism and cancer: the future is now

In the last decade, the field of cancer metabolism transformed itself from being a description of the metabolic features of cancer cells to become a key component of cellular transformation. Now, the potential role of this field in cancer biology is ready to be unravelled.