Zuo Q, Kang Y. Metabolic Reprogramming and Adaption in Breast Cancer Progression and Metastasis. Adv Exp Med Biol. 2025;1464:347-370. doi: 10.1007/978-3-031-70875-6_17. PMID: 39821033.

Recent evidence has revealed that cancer is not solely driven by genetic abnormalities but also by significant metabolic dysregulation. Cancer cells exhibit altered metabolic demands and rewiring of cellular metabolism to sustain their malignant characteristics. Metabolic reprogramming has emerged as a hallmark of cancer, playing a complex role in breast cancer initiation, progression, and metastasis. The different molecular subtypes of breast cancer exhibit distinct metabolic genotypes and phenotypes, offering opportunities for subtype-specific therapeutic approaches. Cancer-associated metabolic phenotypes encompass dysregulated nutrient uptake, opportunistic nutrient acquisition strategies, altered utilization of glycolysis and TCA cycle intermediates, increased nitrogen demand, metabolite-driven gene regulation, and metabolic interactions with the microenvironment. The tumor microenvironment, consisting of stromal cells, immune cells, blood vessels, and extracellular matrix components, influences metabolic adaptations through modulating nutrient availability, oxygen levels, and signaling pathways. Metastasis, the process of cancer spread, involves intricate steps that present unique metabolic challenges at each stage. Successful metastasis requires cancer cells to navigate varying nutrient and oxygen availability, endure oxidative stress, and adapt their metabolic processes accordingly. The metabolic reprogramming observed in breast cancer is regulated by oncogenes, tumor suppressor genes, and signaling pathways that integrate cellular signaling with metabolic processes. Understanding the metabolic adaptations associated with metastasis holds promise for identifying therapeutic targets to disrupt the metastatic process and improve patient outcomes. This chapter explores the metabolic alterations linked to breast cancer metastasis and highlights the potential for targeted interventions in this context.

SMARCA4 Inhibits Breast Cancer Progression and Metastasis through RHOA Suppression. Sun Z, Li Z, Wei Y, Xu L, Hang X, Kang Y. Cancer Res. 2025 May 15. doi: 10.1158/0008-5472.CAN-24-2801. PMID: 39992701

Triple-negative breast cancer (TNBC) is the most challenging subtype of the disease due to its aggressive nature and lack of targeted therapy options. To identify regulators of TNBC, we conducted a genome-wide CRISPR knockout screen in both three-dimensional (3D) tumor spheroid and two-dimensional cell culture models. The 3D spheroid model displayed unique potential in identifying putative tumor suppressors because of its closer mimicry of in vivo tumor growth conditions. Notably, the chromatin remodeling SWI/SNF complex emerged as a potent suppressor of tumor spheroid growth. Specifically, loss of the SWI/SNF ATPase subunit SMARCA4 promoted tumor spheroid growth with reduced compactness and enhanced primary tumor growth and metastasis across multiple TNBC models. SMARCA4 was required for the transcription of the Rho GTPase-activating factor ARHGAP29 by enhancing DNA accessibility through direct binding to its promoter. SMARCA4 loss resulted in reduced ARHGAP29 levels and hyperactive RHOA signaling, subsequently disrupting cell adhesion, facilitating the formation of a loose spheroid structure in vitro, and enhancing breast cancer growth and metastasis in vivo. These results establish SMARCA4 and SWI/SNF as tumor suppressors of TNBC through suppression of RHOA activity. Significance: CRISPR-knockout screen in 3D tumor spheroid revealed that SMARCA4, a SWI/SNF ATPase subunit, suppresses triple-negative breast cancer growth and metastasis by increasing ARHGAP29 transcription and inhibiting the RHOA signaling pathway.

Douglas A, Stevens B, Rendas M, Kane H, Lynch E, Kunkemoeller B, Wessendorf-Rodriguez K, Day EA, Sutton C, Brennan M, O'Brien K, Kohlgruber AC, Prendeville H, Garza AE, O'Neill LAJ, Mills KHG, Metallo CM, Veiga-Fernandes H, Lynch L. Rhythmic IL-17 production by γδ T cells maintains adipose de novo lipogenesis. Nature. 2024 Dec;636(8041):206-214. doi: 10.1038/s41586-024-08131-3. Epub 2024 Oct 30. PMID: 39478228; PMCID: PMC11618085.

The circadian rhythm of the immune system helps to protect against pathogens^1-3; however, the role of circadian rhythms in immune homeostasis is less well understood. Innate T cells are tissue-resident lymphocytes with key roles in tissue homeostasis^4-7. Here we use single-cell RNA sequencing, a molecular-clock reporter and genetic manipulations to show that innate IL-17-producing T cells-including γδ T cells, invariant natural killer T cells and mucosal-associated invariant T cells-are enriched for molecular-clock genes compared with their IFNγ-producing counterparts. We reveal that IL-17-producing γδ (γδ17) T cells, in particular, rely on the molecular clock to maintain adipose tissue homeostasis, and exhibit a robust circadian rhythm for RORγt and IL-17A across adipose depots, which peaks at night. In mice, loss of the molecular clock in the CD45 compartment (Bmal1^∆Vav1) affects the production of IL-17 by adipose γδ17 T cells, but not cytokine production by αβ or IFNγ-producing γδ (γδ^IFNγ) T cells. Circadian IL-17 is essential for de novo lipogenesis in adipose tissue, and mice with an adipocyte-specific deficiency in IL-17 receptor C (IL-17RC) have defects in de novo lipogenesis. Whole-body metabolic analysis in vivo shows that Il17a^-/-Il17f^-/- mice (which lack expression of IL-17A and IL-17F) have defects in their circadian rhythm for de novo lipogenesis, which results in disruptions to their whole-body metabolic rhythm and core-body-temperature rhythm. This study identifies a crucial role for IL-17 in whole-body metabolic homeostasis and shows that de novo lipogenesis is a major target of IL-17.

Varghese A, Gusarov I, Gamallo-Lana B, Dolgonos D, Mankan Y, Shamovsky I, Phan M, Jones R, Gomez-Jenkins M, White E, Wang R, Jones D, Papagiannakopoulos T, Pacold ME, Mar AC, Littman DR, Nudler E. Unraveling cysteine deficiency-associated rapid weight loss. bioRxiv [Preprint]. 2024 Jul 31:2024.07.30.605703. doi: 10.1101/2024.07.30.605703. PMID: 39131293; PMCID: PMC11312522.

Forty percent of the US population and 1 in 6 individuals worldwide are obese, and the incidence of this disease is surging globally^1,2. Various dietary interventions, including carbohydrate and fat restriction, and more recently amino acid restriction, have been explored to combat this epidemic^3-6. We sought to investigate the impact of removing individual amino acids on the weight profiles of mice. Compared to essential amino acid restriction, induction of conditional cysteine restriction resulted in the most dramatic weight loss, amounting to 20% within 3 days and 30% within one week, which was readily reversed. This weight loss occurred despite the presence of substantial cysteine reserves stored in glutathione (GSH) across various tissues⁷. Further analysis demonstrated that the weight reduction primarily stemmed from an increase in the utilization of fat mass, while locomotion, circadian rhythm and histological appearance of multiple other tissues remained largely unaffected. Cysteine deficiency activated the integrated stress response (ISR) and NRF2-mediated oxidative stress response (OSR), which amplify each other, leading to the induction of GDF15 and FGF21, hormones associated with increased lipolysis, energy homeostasis and food aversion^8-10. We additionally observed rapid tissue coenzyme A (CoA) depletion, resulting in energetically inefficient anaerobic glycolysis and TCA cycle, with sustained urinary excretion of pyruvate, orotate, citrate, α-ketoglutarate, nitrogen rich compounds and amino acids. In summary, our investigation highlights that cysteine restriction, by depleting GSH and CoA, exerts a maximal impact on weight loss, metabolism, and stress signaling compared to other amino acid restrictions. These findings may pave the way for innovative strategies for addressing a range of metabolic diseases and the growing obesity crisis.

Guo JY, White E. Role of Tumor Cell Intrinsic and Host Autophagy in Cancer. Cold Spring Harb Perspect Med. 2024 Jul 1;14(7):a041539. doi: 10.1101/cshperspect.a041539. PMID: 38253423; PMCID: PMC11216174.
 

Macroautophagy (autophagy hereafter) is an intracellular nutrient scavenging pathway induced by starvation and other stressors whereby cellular components such as organelles are captured in double-membrane vesicles (autophagosomes), whereupon their contents are degraded through fusion with lysosomes. Two main purposes of autophagy are to recycle the intracellular breakdown products to sustain metabolism and survival during starvation and to eliminate damaged or excess cellular components to suppress inflammation and maintain homeostasis. In contrast to most normal cells and tissues in the fed state, tumor cells up-regulate autophagy to promote their growth, survival, and malignancy. This tumor-cell-autonomous autophagy supports elevated metabolic demand and suppresses tumoricidal activation of the innate and adaptive immune responses. Tumor-cell-nonautonomous (e.g., host) autophagy also supports tumor growth by maintaining essential tumor nutrients in the circulation and tumor microenvironment and by suppressing an antitumor immune response. In the setting of cancer therapy, autophagy is a resistance mechanism to chemotherapy, targeted therapy, and immunotherapy. Thus, tumor and host autophagy are protumorigenic and autophagy inhibition is being examined as a novel therapeutic approach to treat cancer.
 

Lan T, Arastu S, Lam J, Kim H, Wang W, Wang S, Bhatt V, Lopes EC, Hu Z, Sun M, Luo X, Ghergurovich JM, Su X, Rabinowitz JD, White E, Guo JY. Glucose-6-phosphate dehydrogenase maintains redox homeostasis and biosynthesis in LKB1-deficient KRAS-driven lung cancer. Nat Commun. 2024 (1):5857. doi: 10.1038/s41467-024-50157-8. PMID: 38997257; PMCID: PMC11245543.

Cancer cells depend on nicotinamide adenine dinucleotide phosphate (NADPH) to combat oxidative stress and support reductive biosynthesis. One major NADPH production route is the oxidative pentose phosphate pathway (committed step: glucose-6-phosphate dehydrogenase, G6PD). Alternatives exist and can compensate in some tumors. Here, using genetically-engineered lung cancer mouse models, we show that G6PD ablation significantly suppresses Kras^G12D/+;Lkb1^-/- (KL) but not Kras^G12D/+;P53^-/- (KP) lung tumorigenesis. In vivo isotope tracing and metabolomics reveal that G6PD ablation significantly impairs NADPH generation, redox balance, and de novo lipogenesis in KL but not KP lung tumors. Mechanistically, in KL tumors, G6PD ablation activates p53, suppressing tumor growth. As tumors progress, G6PD-deficient KL tumors increase an alternative NADPH source from serine-driven one carbon metabolism, rendering associated tumor-derived cell lines sensitive to serine/glycine depletion. Thus, oncogenic driver mutations determine lung cancer dependence on G6PD, whose targeting is a potential therapeutic strategy for tumors harboring KRAS and LKB1 co-mutations.

Qiang H, Wang F, Lu W, Xing X, Kim H, Merette SAM, Ayres LB, Oler E, AbuSalim JE, Roichman A, Neinast M, Cordova RA, Lee WD, Herbst E, Gupta V, Neff S, Hiebert-Giesbrecht M, Young A, Gautam V, Tian S, Wang B, Röst H, Greiner R, Chen L, Johnston CW, Foster LJ, Shapiro AM, Wishart DS, Rabinowitz JD, Skinnider MA. Language model-guided anticipation and discovery of unknown metabolites. bioRxiv [Preprint]. 2024 Nov 15:2024.11.13.623458. doi: 10.1101/2024.11.13.623458. PMID: 39605668; PMCID: PMC11601323

Despite decades of study, large parts of the mammalian metabolome remain unexplored. Mass spectrometry-based metabolomics routinely detects thousands of small molecule-associated peaks within human tissues and biofluids, but typically only a small fraction of these can be identified, and structure elucidation of novel metabolites remains a low-throughput endeavor. Biochemical large language models have transformed the interpretation of DNA, RNA, and protein sequences, but have not yet had a comparable impact on understanding small molecule metabolism. Here, we present an approach that leverages chemical language models to discover previously uncharacterized metabolites. We introduce DeepMet, a chemical language model that learns the latent biosynthetic logic embedded within the structures of known metabolites and exploits this understanding to anticipate the existence of as-of-yet undiscovered metabolites. Prospective chemical synthesis of metabolites predicted to exist by DeepMet directs their targeted discovery. Integrating DeepMet with tandem mass spectrometry (MS/MS) data enables automated metabolite discovery within complex tissues. We harness DeepMet to discover several dozen structurally diverse mammalian metabolites. Our work demonstrates the potential for language models to accelerate the mapping of the metabolome.

Geraghty S, Boyer JA, Fazel-Zarandi M, Arzouni N, Ryseck RP, McBride MJ, Parsons LR, Rabinowitz JD, Singh M. Integrative Computational Framework, Dyscovr, Links Mutated Driver Genes to Expression Dysregulation Across 19 Cancer Types. bioRxiv [Preprint]. 2024 Nov 21:2024.11.20.624509. doi: 10.1101/2024.11.20.624509. PMID: 39605479; PMCID: PMC11601522.

Though somatic mutations play a critical role in driving cancer initiation and progression, the systems-level functional impacts of these mutations-particularly, how they alter expression across the genome and give rise to cancer hallmarks-are not yet well-understood, even for well-studied cancer driver genes. To address this, we designed an integrative machine learning model, Dyscovr, that leverages mutation, gene expression, copy number alteration (CNA), methylation, and clinical data to uncover putative relationships between nonsynonymous mutations in key cancer driver genes and transcriptional changes across the genome. We applied Dyscovr pan-cancer and within 19 individual cancer types, finding both broadly relevant and cancer type-specific links between driver genes and putative targets, including a subset we further identify as exhibiting negative genetic relationships. Our work newly implicates-and validates in cell lines-KBTBD2 and mutant PIK3CA as putative synthetic lethals in breast cancer, suggesting a novel combinatorial treatment approach.