A pan-cancer metabolic atlas of the tumor microenvironment

RREB1 could act as an immunological and prognostic biomarker: From comprehensive analysis to osteosarcoma validation

BACKGROUND

The Ras-responsive element binding protein 1 (RREB1) is a transcription factor involved in various biological processes. Notably, RREB1 plays a role in tumor immunity by regulating tumor-related gene expression, shaping the tumor microenvironment, and modulating immune checkpoints. Given these functions, RREB1 has emerged as a potential regulatory target in tumor immunotherapy. However, a comprehensive pan-cancer analysis evaluating RREB1's prognostic value and its role in modulating the immune microenvironment remains unexplored, warranting further investigation to better understand its mechanisms across different cancer types and its implications for personalized immunotherapy.

METHODS

We analyzed RREB1 expression across 33 cancer types using RNA sequencing data from the TCGA database. RREB1 alterations were further characterized using the cBioPortal database. Clinical and pathological features, along with prognostic significance, were assessed using TCGA clinical data. The involvement of RREB1 in the tumor microenvironment was evaluated using the CIBERSORT and ESTIMATE algorithms. Relationships between RREB1 expression and tumor mutation burden (TMB), as well as microsatellite instability (MSI), were investigated using Spearman's rank correlation coefficient. GSEA was applied to explore the biological functions of RREB1. Additionally, we assessed the link between RREB1 expression and the efficacy of PD-1/PD-L1 inhibitors. Finally, a series of in vitro experiments were performed to evaluate the impact of RREB1 expression on the malignant behavior of osteosarcoma (OS) and lung cancer cell lines.

RESULTS

RREB1 was overexpressed in several cancer types and correlated with patient prognosis. RREB1 expression was strongly associated with TMB, MSI, and immune cell infiltration, including regulatory T cells, CD8+ T cells, and macrophages. Furthermore, RREB1 expression was linked to immune responses and the efficacy of immunotherapy. In vitro experiments demonstrated that knockdown of RREB1 significantly inhibited the proliferation and migration of OS cells.

CONCLUSIONS

RREB1 shows potential as a prognostic marker for certain cancers and may predict the efficacy of immunotherapy. Additionally, RREB1 expression is related to immune-related markers, suggesting its role in prognosis and predicting responses to immune microenvironment therapies in specific tumors.

Single cell atlas reveals multilayered metabolic heterogeneity across tumour types

BACKGROUND

Metabolic reprogramming plays a pivotal role in cancer progression, contributing to substantial intratumour heterogeneity and influencing tumour behaviour. However, a systematic characterization of metabolic heterogeneity across multiple cancer types at the single-cell level remains limited.

METHODS

We integrated 296 tumour and normal samples spanning six common cancer types to construct a single-cell compendium of metabolic gene expression profiles and identify cell type-specific metabolic properties and reprogramming patterns. A computational approach based on non-negative matrix factorization (NMF) was utilised to identify metabolic meta-programs (MMPs) showing intratumour heterogeneity. In-vitro cell experiments were conducted to confirm the associations between MMPs and chemotherapy resistance, as well as the function of key metabolic regulators. Survival analyses were performed to assess clinical relevance of cellular metabolic properties.

FINDINGS

Our analysis revealed shared glycolysis upregulation and divergent regulation of citric acid cycle across different cell types. In malignant cells, we identified a colorectal cancer-specific MMP associated with resistance to the cuproptosis inducer elesclomol, validated through in-vitro cell experiments. Furthermore, our findings enabled the stratification of patients into distinct prognostic subtypes based on metabolic properties of specific cell types, such as myeloid cells.

INTERPRETATION

This study presents a nuanced understanding of multilayered metabolic heterogeneity, offering valuable insights into potential personalized therapies targeting tumour metabolism.

FUNDING

National Key Research and Development Program of China (2021YFA1300601). National Natural Science Foundation of China (key grants 82030081 and 81874235). The Shenzhen High-level Hospital Construction Fund and Shenzhen Basic Research Key Project (JCYJ20220818102811024). The Lam Chung Nin Foundation for Systems Biomedicine.

Mitochondrial metabolism: A moving target in hepatocellular carcinoma therapy

Mitochondria are pivotal contributors to cancer mechanisms due to their homeostatic and pathological roles in cellular bioenergetics, biosynthesis, metabolism, signaling, and survival. During transformation and tumor initiation, mitochondrial function is often disrupted by oncogenic mutations, leading to a metabolic profile distinct from precursor cells. In this review, we focus on hepatocellular carcinoma, a cancer arising from metabolically robust and nutrient rich hepatocytes, and discuss the mechanistic impact of altered metabolism in this setting. We provide distinctions between normal mitochondrial activity versus disease-related function which yielded therapeutic opportunities, along with highlighting recent preclinical and clinical efforts focused on targeting mitochondrial metabolism. Finally, several novel strategies for exploiting mitochondrial programs to eliminate hepatocellular carcinoma cells in metabolism-specific contexts are presented to integrate these concepts and gain foresight into the future of mitochondria-focused therapeutics.

Targeting amino acid-metabolizing enzymes for cancer immunotherapy

Despite the immune system's role in the detection and eradication of abnormal cells, cancer cells often evade elimination by exploitation of various immune escape mechanisms. Among these mechanisms is the ability of cancer cells to upregulate amino acid-metabolizing enzymes, or to induce these enzymes in tumor-infiltrating immunosuppressive cells. Amino acids are fundamental cellular nutrients required for a variety of physiological processes, and their inadequacy can severely impact immune cell function. Amino acid-derived metabolites can additionally dampen the anti-tumor immune response by means of their immunosuppressive activities, whilst some can also promote tumor growth directly. Based on their evident role in tumor immune escape, the amino acid-metabolizing enzymes glutaminase 1 (GLS1), arginase 1 (ARG1), inducible nitric oxide synthase (iNOS), indoleamine 2,3-dioxygenase 1 (IDO1), tryptophan 2,3-dioxygenase (TDO) and interleukin 4 induced 1 (IL4I1) each serve as a promising target for immunotherapeutic intervention. This review summarizes and discusses the involvement of these enzymes in cancer, their effect on the anti-tumor immune response and the recent progress made in the preclinical and clinical evaluation of inhibitors targeting these enzymes.

Transcriptome Deconvolution Reveals Absence of Cancer Cell Expression Signature in Immune Checkpoint Blockade Response

Immune checkpoint therapy (ICB) has conferred significant and durable clinical benefit to some patients with cancer. However, most patients do not respond to ICB, and reliable biomarkers of ICB response are needed to improve patient stratification. Here, we performed a transcriptome-wide meta-analysis across 1,486 tumors from ICB-treated patients and tumors with expected ICB outcomes based on microsatellite status. Using a robust transcriptome deconvolution approach, we inferred cancer- and stroma-specific gene expression differences and identified cell-type specific features of ICB response across cancer types. Consistent with current knowledge, stromal expression of CXCL9, CXCL13, and IFNG were the top determinants of favorable ICB response. In addition, we identified a group of potential immune-suppressive genes, including FCER1A, associated with poor response to ICB. Strikingly, PD-L1 expression in stromal cells, but not cancer cells, is correlated with ICB response across cancer types. Furthermore, the unbiased transcriptome-wide analysis failed to identify cancer-cell intrinsic expression signatures of ICB response conserved across tumor types, suggesting that cancer cells lack tissue-agnostic transcriptomic features of ICB response.

SIGNIFICANCE

Our results challenge the prevailing dogma that cancer cells present tissue-agnostic molecular markers that modulate immune activity and ICB response, which has implications on the development of improved ICB diagnostics and treatments.

A prismatic view of the epigenetic-metabolic regulatory axis in breast cancer therapy resistance

Epigenetic regulation established during development to maintain patterns of transcriptional expression and silencing for metabolism and other fundamental cell processes can be reprogrammed in cancer, providing a molecular mechanism for persistent alterations in phenotype. Metabolic deregulation and reprogramming are thus an emerging hallmark of cancer with opportunities for molecular classification as a critical preliminary step for precision therapeutic intervention. Yet, acquisition of therapy resistance against most conventional treatment regimens coupled with tumor relapse, continue to pose unsolved problems for precision healthcare, as exemplified in breast cancer where existing data informs both cancer genotype and phenotype. Furthermore, epigenetic reprograming of the metabolic milieu of cancer cells is among the most crucial determinants of therapeutic resistance and cancer relapse. Importantly, subtype-specific epigenetic-metabolic interplay profoundly affects malignant transformation, resistance to chemotherapy, and response to targeted therapies. In this review, we therefore prismatically dissect interconnected epigenetic and metabolic regulatory pathways and then integrate them into an observable cancer metabolism-therapy-resistance axis that may inform clinical intervention. Optimally coupling genome-wide analysis with an understanding of metabolic elements, epigenetic reprogramming, and their integration by metabolic profiling may decode missing molecular mechanisms at the level of individual tumors. The proposed approach of linking metabolic biochemistry back to genotype, epigenetics, and phenotype for specific tumors and their microenvironment may thus enable successful mechanistic targeting of epigenetic modifiers and oncometabolites despite tumor metabolic heterogeneity.

Bioinformatics in urology - molecular characterization of pathophysiology and response to treatment

The application of bioinformatics has revolutionized the practice of medicine in the past 20 years. From early studies that uncovered subtypes of cancer to broad efforts spearheaded by the Cancer Genome Atlas initiative, the use of bioinformatics strategies to analyse high-dimensional data has provided unprecedented insights into the molecular basis of disease. In addition to the identification of disease subtypes - which enables risk stratification - informatics analysis has facilitated the identification of novel risk factors and drivers of disease, biomarkers of progression and treatment response, as well as possibilities for drug repurposing or repositioning; moreover, bioinformatics has guided research towards precision and personalized medicine. Implementation of specific computational approaches such as artificial intelligence, machine learning and molecular subtyping has yet to become widespread in urology clinical practice for reasons of cost, disruption of clinical workflow and need for prospective validation of informatics approaches in independent patient cohorts. Solving these challenges might accelerate routine integration of bioinformatics into clinical settings.

Metabolic heterogeneity in cancer

Cancer cells rewire their metabolism to survive during cancer progression. In this context, tumour metabolic heterogeneity arises and develops in response to diverse environmental factors. This metabolic heterogeneity contributes to cancer aggressiveness and impacts therapeutic opportunities. In recent years, technical advances allowed direct characterisation of metabolic heterogeneity in tumours. In addition to the metabolic heterogeneity observed in primary tumours, metabolic heterogeneity temporally evolves along with tumour progression. In this Review, we summarize the mechanisms of environment-induced metabolic heterogeneity. In addition, we discuss how cancer metabolism and the key metabolites and enzymes temporally and functionally evolve during the metastatic cascade and treatment.

Propionate reinforces epithelial identity and reduces aggressiveness of lung carcinoma

The epithelial-to-mesenchymal transition (EMT) plays a central role in the development of cancer metastasis and resistance to chemotherapy. However, its pharmacological treatment remains challenging. Here, we used an EMT-focused integrative functional genomic approach and identified an inverse association between short-chain fatty acids (propionate and butanoate) and EMT in non-small cell lung cancer (NSCLC) patients. Remarkably, treatment with propionate in vitro reinforced the epithelial transcriptional program promoting cell-to-cell contact and cell adhesion, while reducing the aggressive and chemo-resistant EMT phenotype in lung cancer cell lines. Propionate treatment also decreased the metastatic potential and limited lymph node spread in both nude mice and a genetic NSCLC mouse model. Further analysis revealed that chromatin remodeling through H3K27 acetylation (mediated by p300) is the mechanism underlying the shift toward an epithelial state upon propionate treatment. The results suggest that propionate administration has therapeutic potential in reducing NSCLC aggressiveness and warrants further clinical testing.

Nucleotide metabolism in the regulation of tumor microenvironment and immune cell function

Nucleotide metabolism plays a crucial role in the regulation of the tumor microenvironment (TME) and immune cell function. In the TME, limited availability of nucleotide precursors due to increased consumption by tumor cells and T cells affects both tumor development and immune function. Metabolic reprogramming in tumor cells favors pathways supporting growth and proliferation, including nucleotide synthesis. Additionally, extracellular nucleotides, such as ATP and adenosine, exhibit dual roles in modulating immune function and tumor cell survival. ATP stimulates antitumor immunity by activating purinergic receptors, while adenosine acts as a potent immunosuppressor. Targeting nucleotide metabolism in the TME holds immense promise for cancer therapy. Understanding the intricate relationship between nucleotide metabolism, the TME, and immune responses will pave the way for innovative therapeutic interventions.

The kynurenine pathway presents multi-faceted metabolic vulnerabilities in cancer

The kynurenine pathway (KP) and associated catabolites play key roles in promoting tumor progression and modulating the host anti-tumor immune response. To date, considerable focus has been on the role of indoleamine 2,3-dioxygenase 1 (IDO1) and its catabolite, kynurenine (Kyn). However, increasing evidence has demonstrated that downstream KP enzymes and their associated metabolite products can also elicit tumor-microenvironment immune suppression. These advancements in our understanding of the tumor promotive role of the KP have led to the conception of novel therapeutic strategies to target the KP pathway for anti-cancer effects and reversal of immune escape. This review aims to 1) highlight the known biological functions of key enzymes in the KP, and 2) provide a comprehensive overview of existing and emerging therapies aimed at targeting discrete enzymes in the KP for anti-cancer treatment.

Pan-cancer analysis of post-translational modifications reveals shared patterns of protein regulation

Post-translational modifications (PTMs) play key roles in regulating cell signaling and physiology in both normal and cancer cells. Advances in mass spectrometry enable high-throughput, accurate, and sensitive measurement of PTM levels to better understand their role, prevalence, and crosstalk. Here, we analyze the largest collection of proteogenomics data from 1,110 patients with PTM profiles across 11 cancer types (10 from the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium [CPTAC]). Our study reveals pan-cancer patterns of changes in protein acetylation and phosphorylation involved in hallmark cancer processes. These patterns revealed subsets of tumors, from different cancer types, including those with dysregulated DNA repair driven by phosphorylation, altered metabolic regulation associated with immune response driven by acetylation, affected kinase specificity by crosstalk between acetylation and phosphorylation, and modified histone regulation. Overall, this resource highlights the rich biology governed by PTMs and exposes potential new therapeutic avenues.

Clinical Network Systems Biology: Traversing the Cancer Multiverse

In recent decades, cancer biology and medicine have ushered in a new age of precision medicine through high-throughput approaches that led to the development of novel targeted therapies and immunotherapies for different cancers. The availability of multifaceted high-throughput omics data has revealed that cancer, beyond its genomic heterogeneity, is a complex system of microenvironments, sub-clonal tumor populations, and a variety of other cell types that impinge on the genetic and non-genetic mechanisms underlying the disease. Thus, a systems approach to cancer biology has become instrumental in identifying the key components of tumor initiation, progression, and the eventual emergence of drug resistance. Through the union of clinical medicine and basic sciences, there has been a revolution in the development and approval of cancer therapeutic drug options including tyrosine kinase inhibitors, antibody-drug conjugates, and immunotherapy. This 'Team Medicine' approach within the cancer systems biology framework can be further improved upon through the development of high-throughput clinical trial models that utilize machine learning models, rapid sample processing to grow patient tumor cell cultures, test multiple therapeutic options and assign appropriate therapy to individual patients quickly and efficiently. The integration of systems biology into the clinical network would allow for rapid advances in personalized medicine that are often hindered by a lack of drug development and drug testing.

Ten quick tips for avoiding pitfalls in multi-omics data integration analyses

Data are the most important elements of bioinformatics: Computational analysis of bioinformatics data, in fact, can help researchers infer new knowledge about biology, chemistry, biophysics, and sometimes even medicine, influencing treatments and therapies for patients. Bioinformatics and high-throughput biological data coming from different sources can even be more helpful, because each of these different data chunks can provide alternative, complementary information about a specific biological phenomenon, similar to multiple photos of the same subject taken from different angles. In this context, the integration of bioinformatics and high-throughput biological data gets a pivotal role in running a successful bioinformatics study. In the last decades, data originating from proteomics, metabolomics, metagenomics, phenomics, transcriptomics, and epigenomics have been labelled -omics data, as a unique name to refer to them, and the integration of these omics data has gained importance in all biological areas. Even if this omics data integration is useful and relevant, due to its heterogeneity, it is not uncommon to make mistakes during the integration phases. We therefore decided to present these ten quick tips to perform an omics data integration correctly, avoiding common mistakes we experienced or noticed in published studies in the past. Even if we designed our ten guidelines for beginners, by using a simple language that (we hope) can be understood by anyone, we believe our ten recommendations should be taken into account by all the bioinformaticians performing omics data integration, including experts.

Ribonucleotide reductase regulatory subunit M2 drives glioblastoma TMZ resistance through modulation of dNTP production

During therapy, adaptations driven by cellular plasticity are partly responsible for driving the inevitable recurrence of glioblastoma (GBM). To investigate plasticity-induced adaptation during standard-of-care chemotherapy temozolomide (TMZ), we performed in vivo single-cell RNA sequencing in patient-derived xenograft (PDX) tumors of GBM before, during, and after therapy. Comparing single-cell transcriptomic patterns identified distinct cellular populations present during TMZ therapy. Of interest was the increased expression of ribonucleotide reductase regulatory subunit M2 (RRM2), which we found to regulate dGTP and dCTP production vital for DNA damage response during TMZ therapy. Furthermore, multidimensional modeling of spatially resolved transcriptomic and metabolomic analysis in patients' tissues revealed strong correlations between RRM2 and dGTP. This supports our data that RRM2 regulates the demand for specific dNTPs during therapy. In addition, treatment with the RRM2 inhibitor 3-AP (Triapine) enhances the efficacy of TMZ therapy in PDX models. We present a previously unidentified understanding of chemoresistance through critical RRM2-mediated nucleotide production.

PUREE: accurate pan-cancer tumor purity estimation from gene expression data

Tumors are complex masses composed of malignant and non-malignant cells. Variation in tumor purity (proportion of cancer cells in a sample) can both confound integrative analysis and enable studies of tumor heterogeneity. Here we developed PUREE, which uses a weakly supervised learning approach to infer tumor purity from a tumor gene expression profile. PUREE was trained on gene expression data and genomic consensus purity estimates from 7864 solid tumor samples. PUREE predicted purity with high accuracy across distinct solid tumor types and generalized to tumor samples from unseen tumor types and cohorts. Gene features of PUREE were further validated using single-cell RNA-seq data from distinct tumor types. In a comprehensive benchmark, PUREE outperformed existing transcriptome-based purity estimation approaches. Overall, PUREE is a highly accurate and versatile method for estimating tumor purity and interrogating tumor heterogeneity from bulk tumor gene expression data, which can complement genomics-based approaches or be used in settings where genomic data is unavailable.

Indoleamine 2,3-dioxygenase 1 in circumventing checkpoint inhibitor responses: Updated

Metabolic alterations occur commonly in tumor cells as a way to adapt available energetic sources for their proliferation, survival and resistance. Indoleamine 2,3-dioxygenase 1 (IDO1) is an intracellular enzyme catalyzing tryptophan degradation into kynurenine. IDO1 expression shows a rise in the stroma of many types of human cancers, and it provides a negative feedback mechanism for cancer evasion from immunosurveillance. Upregulation of IDO1 correlates with cancer aggression, poor prognosis and shortened patient survival. The increased activity of this endogenous checkpoint impairs effector T cell function, increases regulatory T cell (Treg) population and induces immune tolerance, so its inhibition potentiates anti-tumor immune responses and reshapes immunogenic state of tumor microenvironment (TME) presumably through normalizing effector T cell activity. A point is that the expression of this immunoregulatory marker is upregulated after immune checkpoint inhibitor (ICI) therapy, and that it has inducible effect on expression of other checkpoints. These are indicative of the importance of IDO1 as an attractive immunotherapeutic target and rationalizing combination of IDO1 inhibitors with ICI drugs in patients with advanced solid cancers. In this review, we aimed to discuss about the impact of IDO1 on tumor immune ecosystem, and the IDO1-mediated bypass of ICI therapy. The efficacy of IDO1 inhibitor therapy in combination with ICIs in advanced/metastatic solid tumors is also a focus of this paper.

The Relationship between Histological Composition and Metabolic Profile in Breast Tumors and Peritumoral Tissue Determined with 1H HR-MAS NMR Spectroscopy

Breast tumors constitute the complex entities composed of cancer cells and stromal components. The compositional heterogeneity should be taken into account in bulk tissue metabolomics studies. The aim of this work was to find the relation between the histological content and ¹H HR-MAS (high-resolution magic angle spinning nuclear magnetic resonance) metabolic profiles of the tissue samples excised from the breast tumors and the peritumoral areas in 39 patients diagnosed with invasive breast carcinoma. The total number of the histologically verified specimens was 140. The classification accuracy of the OPLS-DA (Orthogonal Partial Least Squares Discriminant Analysis) model differentiating the cancerous from non-involved samples was 87% (sensitivity of 72.2%, specificity of 92.3%). The metabolic contents of the epithelial and stromal compartments were determined from a linear regression analysis of the levels of the evaluated compounds against the cancer cell fraction in 39 samples composed mainly of cancer cells and intratumoral fibrosis. The correlation coefficients between the levels of several metabolites and a tumor purity were found to be dependent on the tumor grade (I vs II/III). The comparison of the levels of the metabolites in the intratumoral fibrosis (obtained from the extrapolation of the regression lines to 0% cancer content) to those levels in the fibrous connective tissue beyond the tumors revealed a profound metabolic reprogramming in the former tissue. The joint analysis of the metabolic profiles of the stromal and epithelial compartments in the breast tumors contributes to the increased understanding of breast cancer biology.

IDO1 and inflammatory neovascularization: bringing new blood to tumor-promoting inflammation

In parallel with the genetic and epigenetic changes that accumulate in tumor cells, chronic tumor-promoting inflammation establishes a local microenvironment that fosters the development of malignancy. While knowledge of the specific factors that distinguish tumor-promoting from non-tumor-promoting inflammation remains inchoate, nevertheless, as highlighted in this series on the 'Hallmarks of Cancer', it is clear that tumor-promoting inflammation is essential to neoplasia and metastatic progression making identification of specific factors critical. Studies of immunometabolism and inflamometabolism have revealed a role for the tryptophan catabolizing enzyme IDO1 as a core element in tumor-promoting inflammation. At one level, IDO1 expression promotes immune tolerance to tumor antigens, thereby helping tumors evade adaptive immune control. Additionally, recent findings indicate that IDO1 also promotes tumor neovascularization by subverting local innate immunity. This newly recognized function for IDO1 is mediated by a unique myeloid cell population termed IDVCs (IDO1-dependent vascularizing cells). Initially identified in metastatic lesions, IDVCs may exert broader effects on pathologic neovascularization in various disease settings. Mechanistically, induction of IDO1 expression in IDVCs by the inflammatory cytokine IFNγ blocks the antagonistic effect of IFNγ on neovascularization by stimulating the expression of IL6, a powerful pro-angiogenic cytokine. By contributing to vascular access, this newly ascribed function for IDO1 aligns with its involvement in other cancer hallmark functionalities, (tumor-promoting inflammation, immune escape, altered cellular metabolism, metastasis), which may stem from an underlying role in normal physiological functions such as wound healing and pregnancy. Understanding the nuances of how IDO1 involvement in these cancer hallmark functionalities varies between different tumor settings will be crucial to the future development of successful IDO1-directed therapies.