ReviewOncogene2015
Cancer systems biology: embracing complexity to develop better anticancer therapeutic strategies.
Review in Oncogene, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 84 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
84 citing papers in PubMed.
- Molecular origin, discovery, validation and application of neoantigens.Asian journal of pharmaceutical sciences · 2026Review
- STAT1 accelerates cutaneous melanoma progression through TUBB4A expression regulation.Molecular medicine reports · 2026Article
- Predicting and interpreting protein and phosphoprotein abundance from pan-cancer and single-cell transcriptomes.iScience · 2026Article
- EGFR-targeted tyrosine kinase inhibitors: advancements in cancer therapy.Naunyn-Schmiedeberg's archives of pharmacology · 2026Review
- Evaluating deconvolution methods using real bulk RNA-expression data for robust prognostic insights across cancer types.Genome biology · 2026Article
- Review
- SBMLtoOdin and Menelmacar: interactive visualisation of systems biology models for expert and non-expert audiences.Bioinformatics (Oxford, England) · 2025Article
- Systems biology successes and areas for opportunity in prostate cancer.Endocrine-related cancer · 2025Review
- Patient-specific gene co-expression networks reveal novel subtypes and predictive biomarkers in lung adenocarcinoma.NPJ systems biology and applications · 2025Article
- Tumor microenvironment: recent advances in understanding and its role in modulating cancer therapies.Medical oncology (Northwood, London, England) · 2025Review
- Multi-omics analysis reveals the impact of YAP/TEAD4-mediated EIF5A1 expression on mitochondrial apoptosis and bladder cancer progression.BMC cancer · 2025Article
- A Review on Medicinal Approaches of Novel Imatinib Derivatives.Current topics in medicinal chemistry · 2025Review
- Metal grafted graphene-based nanomaterials towards cancer theranostic efficacy.Exploration of targeted anti-tumor therapy · 2025Review
- Risk factors for metabolic syndrome in the premetabolic state assessed using hierarchical clustering study in a health screening group.Scientific reports · 2024Article
- Tumor suppressor ACER1 correlates with prognosis and Immune Infiltration in head and neck squamous cell carcinoma.Scientific reports · 2024Article
- Identification of proteins' expression pathway and the effective miRNAs for the treatment of human papillomavirus-induced cervical cancer: in-silico analyses-experimental research.Annals of medicine and surgery (2012) · 2024Article
- Bridging systems biology and tissue engineering: Unleashing the full potential of complex 3DBiophysics reviews · 2024Review
- hsa-miR-181a-5p inhibits glioblastoma development via the MAPK pathway:Oncology research · 2024Article
- Overexpression of FERM Domain Containing Kindlin 2 (FERMT2) in Fibroblasts Correlates with EMT and Immunosuppression in Gastric Cancer.International journal of genomics · 2024Article
- Artificial Intelligence in the Screening, Diagnosis, and Management of Aortic Stenosis.Reviews in cardiovascular medicine · 2024Review
24 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The transformation of normal cells into cancer cells and maintenance of the malignant state and phenotypes are associated with genetic and epigenetic deregulations, altered cellular signaling responses and aberrant interactions with the microenvironment. These alterations are constantly evolving as tumor cells face changing selective pressures induced by the cells themselves, the microenvironment and drug treatments. Tumors are also complex ecosystems where different, sometime heterogeneous, subclonal tumor populations and a variety of nontumor cells coexist in a constantly evolving manner. The interactions between molecules and between cells that arise as a result of these alterations and ecosystems are even more complex. The cancer research community is increasingly embracing this complexity and adopting a combination of systems biology methods and integrated analyses to understand and predictively model the activity of cancer cells. Systems biology approaches are helping to understand the mechanisms of tumor progression and design more effective cancer therapies. These approaches work in tandem with rapid technological advancements that enable data acquisition on a broader scale, with finer accuracy, higher dimensionality and higher throughput than ever. Using such data, computational and mathematical models help identify key deregulated functions and processes, establish predictive biomarkers and optimize therapeutic strategies. Moving forward, implementing patient-specific computational and mathematical models of cancer will significantly improve the specificity and efficacy of targeted therapy, and will accelerate the adoption of personalized and precision cancer medicine.
Indexed as
Identifiers
25220419What OpenQuestion 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 OpenQuestion graph.