ReviewAdvances in experimental medicine and biology2026
Targeting Lung Cancer Metabolism: Therapeutic Opportunities and Challenges.
Review in Advances in experimental medicine and biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Authors and funding
2 authors.
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Abstract
Lung cancer remains the leading cause of cancer-related deaths worldwide in both men and women. Although conventional chemotherapy has been the backbone of treatment, it often fails to provide long-term survival benefits for most patients. In recent years, advances in the understanding of molecular and genetic alterations in lung cancer have led to the identification of distinct subtypes and the development of targeted therapies. However, these therapies benefit only a limited group of patients with specific driver mutations. Similarly, immunotherapy has brought new hope, yet access and efficacy remain variable across the patient population. As the field evolves, there is growing recognition that cancer metabolism plays a crucial role in tumor progression, immune evasion, and resistance to therapy. This chapter will examine the metabolic reprogramming that occurs in lung cancer cells, including alterations in glycolysis, glutaminolysis, and lipid metabolism, within the context of the tumor microenvironment. It will also examine how these changes impact current treatments and highlight emerging therapeutic strategies targeting cancer metabolism.
Indexed as
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42435178What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.