ArticleGenome medicine2016
Looking beyond the cancer cell for effective drug combinations.
Article in Genome medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 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.
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Who cites it
21 citing papers in PubMed.
- Taking Charge Against the Silent Pandemic-Electrochemical Characterization of Drug Resistance.Molecules (Basel, Switzerland) · 2026Review
- Targeting Microbiome-Derived Exosomes to Overcome Cancer Therapy Resistance: Mechanisms, Implications, and Opportunities.Mini reviews in medicinal chemistry · 2026Review
- Network-driven cancer cell avatars for combination discovery and biomarker identification for DNA damage response inhibitors.NPJ systems biology and applications · 2024Article
- Combination Treatment with EGFR Inhibitor and Doxorubicin Synergistically Inhibits Proliferation of MCF-7 Cells and MDA-MB-231 Triple-Negative Breast Cancer Cells In Vitro.International journal of molecular sciences · 2024Article
- Designing patient-oriented combination therapies for acute myeloid leukemia based on efficacy/toxicity integration and bipartite network modeling.Oncogenesis · 2024Article
- A functionalized graphene oxide with improved cytocompatibility for stimuli-responsive co-delivery of curcumin and doxorubicin in cancer treatment.Scientific reports · 2022Article
- Deep learning-based multi-drug synergy prediction model for individually tailored anti-cancer therapies.Frontiers in pharmacology · 2022Article
- XDeathDB: a visualization platform for cell death molecular interactions.Cell death & disease · 2021Article
- Ferroptosis inducer erastin sensitizes NSCLC cells to celastrol through activation of the ROS-mitochondrial fission-mitophagy axis.Molecular oncology · 2021Article
- Article
- QSAR-derived affinity fingerprints (part 2): modeling performance for potency prediction.Journal of cheminformatics · 2020Article
- Charting the Fragmented Landscape of Drug Synergy.Trends in pharmacological sciences · 2020Review
- Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen.Nature communications · 2019Article
- Drug combination sensitivity scoring facilitates the discovery of synergistic and efficacious drug combinations in cancer.PLoS computational biology · 2019Article
- Chemogenomic model identifies synergistic drug combinations robust to the pathogen microenvironment.PLoS computational biology · 2018Article
- How to find the right drug for each patient? Advances and challenges in pharmacogenomics.Current opinion in systems biology · 2018Review
- Targeting the tumour stroma to improve cancer therapy.Nature reviews. Clinical oncology · 2018Review
- Integrating Transcriptomic Data with Mechanistic Systems Pharmacology Models for Virtual Drug Combination Trials.ACS chemical neuroscience · 2018Article
- Single-Cell Tracking of A549 Lung Cancer Cells Exposed to a Marine Toxin Reveals Correlations in Pedigree Tree Profiles.Frontiers in oncology · 2018Article
- Comprehensive Analysis of Cancer-Proteogenome to Identify Biomarkers for the Early Diagnosis and Prognosis of Cancer.Proteomes · 2017Review
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Combinations of therapies are being actively pursued to expand therapeutic options and deal with cancer's pervasive resistance to treatment. Research efforts to discover effective combination treatments have focused on drugs targeting intracellular processes of the cancer cells and in particular on small molecules that target aberrant kinases. Accordingly, most of the computational methods used to study, predict, and develop drug combinations concentrate on these modes of action and signaling processes within the cancer cell. This focus on the cancer cell overlooks significant opportunities to tackle other components of tumor biology that may offer greater potential for improving patient survival. Many alternative strategies have been developed to combat cancer; for example, targeting different cancer cellular processes such as epigenetic control; modulating stromal cells that interact with the tumor; strengthening physical barriers that confine tumor growth; boosting the immune system to attack tumor cells; and even regulating the microbiome to support antitumor responses. We suggest that to fully exploit these treatment modalities using effective drug combinations it is necessary to develop multiscale computational approaches that take into account the full complexity underlying the biology of a tumor, its microenvironment, and a patient's response to the drugs. In this Opinion article, we discuss preliminary work in this area and the needs-in terms of both computational and data requirements-that will truly empower such combinations.
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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.