ReviewAdvances in experimental medicine and biology2026
Dissecting Cancer Metabolism and Therapeutic Resistance Using In Vitro Platforms.
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.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Understanding cancer metabolism and its adaptations is critical for developing novel therapeutic strategies. In vitro models remain indispensable tools for dissecting tumor biology and testing metabolism-based therapies. Traditional 2D monolayer cultures provide controlled, cost-effective, and reproducible platforms for mechanistic studies, genetic manipulation, and high-throughput drug screening. Advances in 3D models, such as spheroids, organoids, and microfluidic tumor-on-a-chip systems, try to come closer to a natural tumor in order to recapitulate cellular heterogeneity, nutrient and oxygen gradients, and tumor-stroma interactions. These systems provide a model that allows the study of tumor metabolic plasticity, stem-like populations, and therapy resistance mechanisms, offering improved translational relevance. Comparative studies between 2D and 3D cultures reveal significant differences in metabolic flux, drug response, and adaptation to nutrient stress, underscoring the need for integrated approaches. While 2D models remain essential for scalability and early-phase drug discovery, 3D platforms can be valuable for validating metabolic vulnerabilities and therapeutic responses under (patho)physiologically relevant conditions. Together, these complementary systems pave the way for precision oncology, enabling the identification of novel targets, optimization of drug screening, and development of personalized treatment strategies.
Indexed as
Identifiers
42435172What 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.