ReviewBMC cancer2025
The complex journey of targeting RAS in oncology.
Review in BMC cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- The Role of KRAS in Non-Small Cell Lung Cancer: From Molecular Background to Precision Medicine.International journal of molecular sciences · 2026Review
- From pancreatic ductal adenocarcinoma to non-small cell lung cancer: daraxonrasib in the RASolute 302 trial - a pan-RAS(ON) breakthrough or the next evolution in targeting diverse oncogenic RAS variants?Annals of medicine and surgery (2012) · 2026Article
- Broad-Spectrum RAS Inhibition in Pancreatic Ductal Adenocarcinoma: Mechanistic Advances and Therapeutic Promise.Pharmaceuticals (Basel, Switzerland) · 2025Review
- Long-Term Disease Control With Lenvatinib in Metastatic Malignant Struma Ovarii: A Case Report.Cureus · 2025Article
- Research progress on the mechanisms of CSF3R mutations in leukemogenesis and treatment strategies.Cancer cell international · 2025Review
- Effect of antihypertensive drugs on survival in patients with non-small cell lung cancer on epidermal growth factor receptor inhibitors.American journal of cancer research · 2025Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Given the prevalence of RAS mutations in various cancers, personalized therapeutic approaches, guided by molecular markers, are essential. Farnesyltransferase inhibitors (FTIs) have emerged as potential therapeutic options; however, they also face obstacles such as toxicity and limited efficacy. Alternative strategies, such as direct inhibitors combined with pathway modulators, RNA interference, and gene-editing technologies, are under clinical investigation. The targeting of RAS, complicated by its structural nuances, particularly in the G domain, has advanced with the identification of druggable pockets such as the SW-II pocket. This breakthrough has led to the development of targeted therapeutics, such as sotorasib and adagrasib, for KRAS G12C-mutated non-small cell lung cancer (NSCLC). However, these advancements face challenges, including adaptive resistance and the necessity for isoform selectivity. New inhibitors, such as LY3537982 or GDC-6036, are promising, but achieving effective and selective RAS inhibition remains a significant challenge. Additionally, clinical trials have highlighted variability in patient responses, attributing limited treatment efficacy to resistance mechanisms, including on-target mutations and off-target pathway activations. Finally, the RAS oncogene, traditionally viewed as predominantly pro-cancerous, plays a complex role in oncogenesis, with recent evidence suggesting context-dependent effects, such as inducing senescence in certain cells. This shift in understanding underscores the therapeutic potential of manipulating the interplay between RAS and TP53 mutations in cancer. In conclusion, the complexity of effectively targeting the RAS-RAF-ERK pathway is exacerbated by the diverse resistance mechanisms. Challenges such as off-target effects and delivery issues remain significant barriers in the introduction of effective therapies based on RAS inhibitors. This overview highlights the evolving nature of targeting RAS in cancer therapy.
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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 OpenQuestion graph.