ReviewMolecular cell2015
The cancer cell map initiative: defining the hallmark networks of cancer.
Review in Molecular cell, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers, 1 of them a synthesis that pooled it.
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
62 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systems-level effects of ectopic galectin-7 reconstitution in cervical cancer and its microenvironment.BMC cancer · 2016Pooled it
- Revisiting the role of mesenchymal stromal cells in cancer initiation, metastasis and immunosuppression.Experimental hematology & oncology · 2024Review
- Predicting anti-cancer drug combination responses with a temporal cell state network model.PLoS computational biology · 2023Article
- Article
- Combinatorial Inactivation of Tumor Suppressors Efficiently Initiates Lung Adenocarcinoma with Therapeutic Vulnerabilities.Cancer research · 2022Article
- Discovery of novelFrontiers in pharmacology · 2022Article
- Artificial intelligence, molecular subtyping, biomarkers, and precision oncology.Emerging topics in life sciences · 2021Review
- A protein network map of head and neck cancer reveals PIK3CA mutant drug sensitivity.Science (New York, N.Y.) · 2021Article
- Interpretation of cancer mutations using a multiscale map of protein systems.Science (New York, N.Y.) · 2021Article
- A protein interaction landscape of breast cancer.Science (New York, N.Y.) · 2021Article
- Predicting anticancer hyperfoods with graph convolutional networks.Human genomics · 2021Article
- Network-guided search for genetic heterogeneity between gene pairs.Bioinformatics (Oxford, England) · 2021Article
- Oncoprotein-specific molecular interaction maps (SigMaps) for cancer network analyses.Nature biotechnology · 2021Article
- Mass spectrometry-based protein-protein interaction networks for the study of human diseases.Molecular systems biology · 2021Review
- Review
- Argonaut: A Web Platform for Collaborative Multi-omic Data Visualization and Exploration.Patterns (New York, N.Y.) · 2020Article
- Crippling life support for SARS-CoV-2 and other viruses through synthetic lethality.The Journal of cell biology · 2020Article
- Precision medicine - networks to the rescue.Current opinion in biotechnology · 2020Review
- HaloTag-based conjugation of proteins to barcoding-oligonucleotides.Nucleic acids research · 2020Article
- Article
2 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
5 authors.
Funding
Abstract
Progress in DNA sequencing has revealed the startling complexity of cancer genomes, which typically carry thousands of somatic mutations. However, it remains unclear which are the key driver mutations or dependencies in a given cancer and how these influence pathogenesis and response to therapy. Although tumors of similar types and clinical outcomes can have patterns of mutations that are strikingly different, it is becoming apparent that these mutations recurrently hijack the same hallmark molecular pathways and networks. For this reason, it is likely that successful interpretation of cancer genomes will require comprehensive knowledge of the molecular networks under selective pressure in oncogenesis. Here we announce the creation of a new effort, The Cancer Cell Map Initiative (CCMI), aimed at systematically detailing these complex interactions among cancer genes and how they differ between diseased and healthy states. We discuss recent progress that enables creation of these cancer cell maps across a range of tumor types and how they can be used to target networks disrupted in individual patients, significantly accelerating the development of precision medicine.
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What 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.