Numerous cancer-specific alterations in metabolism have been identified but have not yet resulted in an effective anti cancer therapeutic. In a Review, Faubert et al. discuss how metabolism changes as cancer develops from a small, premalignant lesion to an aggressive primary tumor and then metastasizes. Metabolic vulnerabilities likely change with cancer progression, making the identification of general cancer-associated metabolic features difficult. The authors propose that a more targeted approach to tissues and vulnerabilities identified in patients may be more effective.
Science, this issue p. eaaw5473
Metabolic reprogramming is a hallmark of malignancy first recognized a century ago. In some cases, reprogrammed metabolic activities can be exploited to diagnose, monitor, and treat cancer. Stereotyped metabolic activities in cultured cancer cells—notably, aerobic glycolysis, glutamine catabolism, macromolecular synthesis, and redox homeostasis—support the requirements of exponential growth and proliferation. These pathways are under cell-autonomous control by oncogenic signaling and transcriptional networks. This has produced the widespread perception that a core set of fixed metabolic dependencies will prove to be excellent therapeutic targets across diverse cancer types. Several metabolic inhibitors designed to target these pathways have advanced into clinical trials.
The past decade has brought numerous advances in our understanding of why tumors develop metabolic phenotypes that differ from adjacent, nonmalignant tissues and when these phenotypes represent actionable therapeutic vulnerabilities. Mechanistic insights into how the oncogenotype dictates metabolic patterns have exploded, aided by the ever-increasing use of advanced analytical techniques to characterize tumor metabolism in detail. This has led to the remarkable discovery of a few metabolic properties that can directly promote tumor initiation, including the accumulation of D-2-hydroxyglutarate in tumors with mutations in isocitrate dehydrogenase-1 and -2. Other advances have demonstrated the extraordinary amount of metabolic heterogeneity among human tumors and, in some cases, even within distinct regions of the same tumor. This heterogeneity results from a complex set of factors, including processes intrinsic and extrinsic to the cancer cell. Many of these studies have identified promising subtype-selective metabolic vulnerabilities in experimental models. However, they have cast doubt on the classical paradigm of convergent, oncogene-driven liabilities among histologically and genetically diverse tumors. Even more fundamentally, it has become increasingly clear that metabolic phenotypes and vulnerabilities evolve as tumors progress from premalignant lesions to locally invasive tumors to metastatic cancer. Microenvironmental and genetic factors appear to induce selective pressures that drive clonal evolution within tumors, and this can create or eliminate metabolic liabilities while facilitating cancer progression. During metastasis, for example, several studies demonstrate that cancer cells need to activate mechanisms to resist oxidative stress, or else these cells are culled by the oxidizing environment of the bloodstream. A major theme arising from recent research is that pathways that stimulate the growth of localized, treatment-naïve tumors are distinct from and in some cases irrelevant to the activities that drive mortality by supporting metastasis and therapy resistance.
The emerging view of cancer metabolism is that it is flexible and context-specific, with few fixed, broadly applicable liabilities. Understanding how reprogrammed metabolism supports tumor growth—and identifying which reprogrammed activities are most relevant to therapeutic liabilities—requires a more sophisticated view of how metabolic phenotypes evolve as cancer progresses. Advanced animal models that recapitulate the landmark events in human cancer progression will be instrumental in discovering the most important metabolic vulnerabilities. These animal studies will need to be complemented by increasing efforts to assess metabolism directly in human tumors through metabolomics, metabolic isotope tracers, and advanced techniques in metabolic imaging. Crucially, cooperative, multidisciplinary research is needed to translate findings from animal models into patients and from human cancer into mouse models for mechanistic studies and hypothesis testing. Ideally, work along these lines will generate efficient ways to detect predictive aspects of metabolic behavior in human tumors to aid in clinical trial design and to stratify patients to receive the most effective therapies. These efforts over the next decade should produce a more nuanced but ultimately more relevant and therapeutically actionable view of cancer metabolism.
Metabolic needs and vulnerabilities evolve throughout cancer progression. Early stages of tumor growth require nutrient uptake and biosynthesis, with additional subtype-selective metabolic needs emerging in locally invasive cancers. Tumors acquire dependence on new pathways during later stages of cancer progression, particularly metastasis and therapy resistance. These include potentially targetable liabilities such as dependence on mechanisms to resist oxidative stress and increased reliance on oxidative phosphorylation.
CREDIT: N. CARY/SCIENCE
Metabolic reprogramming is a hallmark of malignancy. As our understanding of the complexity of tumor biology increases, so does our appreciation of the complexity of tumor metabolism. Metabolic heterogeneity among human tumors poses a challenge to developing therapies that exploit metabolic vulnerabilities. Recent work also demonstrates that the metabolic properties and preferences of a tumor change during cancer progression. This produces distinct sets of vulnerabilities between primary tumors and metastatic cancer, even in the same patient or experimental model. We review emerging concepts about metabolic reprogramming in cancer, with particular attention on why metabolic properties evolve during cancer progression and how this information might be used to develop better therapeutic strategies.
This is an article distributed under the terms of the Science Journals Default License.
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