ReviewTrends in cancer2016
Modeling Tumor Clonal Evolution for Drug Combinations Design.
Review in Trends in cancer, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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
29 citing papers in PubMed.
- Quantitative modeling of tumor dynamics and development of drug resistance in non-small cell lung cancer patients treated with erlotinib.CPT: pharmacometrics & systems pharmacology · 2024Article
- On the possibility of engineering social evolution in microfluidic environments.Biophysical journal · 2024Article
- Anti-cancer treatment schedule optimization based on tumor dynamics modelling incorporating evolving resistance.Scientific reports · 2022Article
- Independent Drug Action in Combination Therapy: Implications for Precision Oncology.Cancer discovery · 2022Review
- Conditional prediction of consecutive tumor evolution using cancer progression models: What genotype comes next?PLoS computational biology · 2021Article
- Reviewing cancer's biology: an eclectic approach.Journal of the Egyptian National Cancer Institute · 2021Review
- Treatment scheduling effects on the evolution of drug resistance in heterogeneous cancer cell populations.NPJ breast cancer · 2021Article
- Review
- Genomic Characterization of Concurrent Alterations in Non-Small Cell Lung Cancer (NSCLC) Harboring Actionable Mutations.Cancers · 2021Article
- Advances in Research of Adult Gliomas.International journal of molecular sciences · 2021Review
- Extreme value theory as a framework for understanding mutation frequency distribution in cancer genomes.PloS one · 2021Article
- Clonal Evolution Dynamics in Primary and Metastatic Lesions of Pancreatic Neuroendocrine Neoplasms.Frontiers in medicine · 2021Article
- Clonal evolution driven by superdriver mutations.BMC evolutionary biology · 2020Article
- Exploiting evolutionary steering to induce collateral drug sensitivity in cancer.Nature communications · 2020Article
- A Review of Mathematical Models for Tumor Dynamics and Treatment Resistance Evolution of Solid Tumors.CPT: pharmacometrics & systems pharmacology · 2019Review
- Anakoinosis: Correcting Aberrant Homeostasis of Cancer Tissue-Going Beyond Apoptosis Induction.Frontiers in oncology · 2019Review
- Gpn3 Is Essential for Cell Proliferation of Breast Cancer Cells Independent of Their Malignancy Degree.Technology in cancer research & treatment · 2019Article
- MicroRNAs as Key Regulators of Ovarian Cancers.Cell medicine · 2019Review
- The Promising Connection Between Data Science and Evolutionary Theory in Oncology.Frontiers in oncology · 2019Article
- Calling Variants in the Clinic: Informed Variant Calling Decisions Based on Biological, Clinical, and Laboratory Variables.Computational and structural biotechnology journal · 2019Review
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
Abstract
Cancer is a clonal evolutionary process. This presents challenges for effective therapeutic intervention, given the constant selective pressure towards drug resistance. Mathematical modeling from population genetics, evolutionary dynamics, and engineering perspectives are being increasingly employed to study tumor progression, intratumoral heterogeneity, drug resistance, and rational drug scheduling and combinations design. In this review, we discuss promising opportunities these inter-disciplinary approaches hold for advances in cancer biology and treatment. We propose that quantitative modeling perspectives can complement emerging experimental technologies to facilitate enhanced understanding of disease progression and improved capabilities for therapeutic drug regimen designs.
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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.