In one paragraphArticle in Nature genetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from itWhat 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.
2 · The registryThe 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.
3 · Its place in the literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
7 authors.
Somnath Tagore *Department of Systems Biology, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York City, NY, USA.
Samuel Tsang *Division of Oncologic Science, Knight Cancer Institute, Oregon Health Sciences University School of Medicine, Portland, OR, USA.
Carla TangermannDivision of Cancer Research, Department of Thoracic Surgery, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.ORCID 0000-0002-4715-4985 Lucas ZhongMing HuDepartment of Systems Biology, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York City, NY, USA.
Sven DiederichsDivision of Cancer Research, Department of Thoracic Surgery, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany. s.diederichs@dkfz.de.ORCID 0000-0001-7901-4752 Gordon B MillsDivision of Oncologic Science, Knight Cancer Institute, Oregon Health Sciences University School of Medicine, Portland, OR, USA. millsg@ohsu.edu.ORCID 0000-0002-0144-9614 Andrea CalifanoDepartment of Systems Biology, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York City, NY, USA. ac2248@cumc.columbia.edu.ORCID 0000-0003-4742-3679 Funding
Systematic Identification and Pharmacological Targeting of Tumor Dependencies for Precision Cancer MedicineU01CA217858 · NCI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI CALIFANO, ANDREA · 2017 to 2021
$6.1MElucidating and Targeting tumor dependencies and drug resistance determinants at the single cell levelU01CA272610 · NCI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI ANDREA CALIFANO · 2022 to 2026
$4.8MThe Cancer Proteome Atlas: an Integrated Bioinformatics Resource for Functional Cancer Proteomic DataU24CA264128 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Rehan Akbani, Han Liang · 2022 to 2026
$3.9MIntegrative bioinformatics and functional characterization of oncogenic driver aberrations in cancerU01CA217842 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI DENEEN, BENJAMIN, MILLS, GORDON B. · 2017 to 2021
$3.6MSystematic Characterization and Targeting of Neomorphic Drivers in CancerU01CA281902 · NCI · OREGON HEALTH & SCIENCE UNIVERSITY · PI Benjamin Deneen, Han Liang · 2023 to 2026
$3.5MMechanistic maps of adaptive responses to therapeutic stress to optimize combination therapies.U01CA253472 · NCI · OREGON HEALTH & SCIENCE UNIVERSITY · PI KORKUT, ANIL, LIANG, HAN · 2021 to 2025
$2.6MHigh-performance compute cluster for biomedical computingS10OD012351 · OD · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI CALIFANO, ANDREA · 2012 to 2012
$2.0MStorage System for High Performance ComputingS10OD021764 · OD · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI CALIFANO, ANDREA · 2016 to 2016
$600kNCI NIH HHS U01 CA217842NCI NIH HHS U01 CA217858NCI NIH HHS U01 CA253472NCI NIH HHS U01 CA272610NCI NIH HHS U01 CA281902NCI NIH HHS U24 CA264128NIH HHS S10 OD012351NIH HHS S10 OD021764
6 · The paper itselfAbstract
Although the functional effects of many recurrent cancer mutations have been characterized, The Cancer Genome Atlas contains more than 10 million functionally uncharacterized, nonrecurrent events. It is proposed that the context-specific activity of transcription factors assessed through the expression of their transcriptional targets serves as a sensitive and accurate reporter assay for evaluating the functional roles of oncogene mutations. Analysis of transcription factor activity in samples with mutations of unknown significance, compared to established gain-of-function (hypermorph) or loss-of-function (hypomorph) mutations in the same gene, enabled functional characterization of 583,089 individual mutational events across TCGA. This approach facilitated the identification of neomorphic mutations (gain of new function) or mutations that phenocopy mutations in other genes (mutational mimicry). Validation using exogenous mutation expression assays confirmed the majority of predicted loss-of-function, gain-of-function, neomorphic and neutral (no predicted functional effect) mutations in PIK3CA and FGFR2. These findings may inform targeted therapy decisions for patients with mutations of unknown significance in established oncogenes.
Indexed as
MutationNeoplasmsClass I Phosphatidylinositol 3-KinasesGain of Function MutationGene Expression Regulation, NeoplasticHumansOncogenesPhosphatidylinositol 3-KinasesReceptor, Fibroblast Growth Factor, Type 2Class I Phosphatidylinositol 3-KinasesFGFR2 protein, humanPhosphatidylinositol 3-KinasesPIK3CA protein, humanReceptor, Fibroblast Growth Factor, Type 2
Identifiers
PMID41673304
PMCPMC12900636
What OpenQuestion holds
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