Article in Cancer research communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.
2 · The registry
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.
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what money
Authors and funding
23 authors.
Yasuhiro ArakawaDevelopmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.ORCID 0000-0003-1582-0282
Fathi ElloumiDevelopmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.ORCID 0009-0007-7116-508X
Sudhir VarmaDevelopmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.ORCID 0000-0002-4096-4782
Prashant KhandagaleDevelopmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.ORCID 0000-0002-9751-2189
Ukhyun JoDevelopmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.ORCID 0000-0002-2826-1355
Suresh KumarDevelopmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.ORCID 0000-0001-7404-8259
Nitin RoperDevelopmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.ORCID 0000-0002-6514-5468
William C ReinholdDevelopmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.ORCID 0000-0001-5513-9323
Robert W RobeyLaboratory of Cell Biology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.ORCID 0000-0002-0857-3650
Naoko TakebeDevelopmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.ORCID 0000-0002-5790-4954
Michael M GottesmanLaboratory of Cell Biology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.ORCID 0000-0001-8908-2097
Valentina BoevaDepartment of Computer Science, Institute for Machine Learning, ETH Zurich, Zurich, Switzerland.ORCID 0000-0002-4382-7185
Alfredo BerrutiDepartment of Medical and Surgical Specialties, Radiological Sciences, and Public Health, Medical Oncology Unit, University of Brescia, Azienda Socio Sanitaria Territoriale (ASST) Spedali Civili, Brescia, Italy.ORCID 0000-0002-3956-0043
Andrea AbateSection of Pharmacology, Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy.ORCID 0000-0002-0835-0916
Mariangela TamburelloSection of Pharmacology, Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy.ORCID 0000-0001-7827-0025
Sandra SigalaSection of Pharmacology, Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy.ORCID 0000-0003-3294-4121
Constanze HantelDepartment of Endocrinology, Diabetology and Clinical Nutrition, University Hospital Zurich, and University of Zurich, Zürich, Switzerland.ORCID 0009-0000-8906-2563
Isabel WeigandDivision of Endocrinology and Diabetology, Department of Internal Medicine I, University Hospital, University of Würzburg, Würzburg, Germany.ORCID 0000-0001-5873-8567
Margaret E WiermanDepartment of Medicine-Endocrinology/Metabolism/Diabetes, University of Colorado, Anschutz Medical Campus, Aurora, Colorado.ORCID 0000-0002-7634-1093
Katja Kiseljak-VassiliadesDepartment of Medicine-Endocrinology/Metabolism/Diabetes, University of Colorado, Anschutz Medical Campus, Aurora, Colorado.ORCID 0000-0003-3341-582X
Jaydira Del RiveroDevelopmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.ORCID 0000-0001-9710-4030
Yves PommierDevelopmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.ORCID 0000-0002-3108-0758
Funding
PROTEIN-ASSOCIATED DNA BREAKS AS INDICATOR OF TOPOISOMERASE INHIBITIONZ01BC006150 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI POMMIER, YVES · 1996 to 2008
$1.5M
Intramural NIH HHS Z01 BC006150
6 · The paper itself
Abstract
Adrenocortical carcinoma (ACC) is a rare and highly heterogeneous disease with a notably poor prognosis due to significant challenges in diagnosis and treatment. Emphasizing on the importance of precision medicine, there is an increasing need for comprehensive genomic resources alongside well-developed experimental models to devise personalized therapeutic strategies. We present ACC_CellMinerCDB, a substantive genomic and drug sensitivity database (available at https://discover.nci.nih.gov/acc_cellminercdb) comprising ACC cell lines, patient-derived xenografts, surgical samples, and responses to more than 2,400 drugs examined by the NCI and National Center for Advancing Translational Sciences. This database exposes shared genomic pathways among ACC cell lines and surgical samples, thus authenticating the cell lines as research models. It also allows exploration of pertinent treatment markers such as MDR-1, SOAT1, MGMT, MMR, and SLFN11 and introduces the potential to repurpose agents like temozolomide for ACC therapy. ACC_CellMinerCDB provides the foundation for exploring larger preclinical ACC models. SIGNIFICANCE: ACC_CellMinerCDB, a comprehensive database of cell lines, patient-derived xenografts, surgical samples, and drug responses, reveals shared genomic pathways and treatment-relevant markers in ACC. This resource offers insights into potential therapeutic targets and the opportunity to repurpose existing drugs for ACC therapy.
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 Socratic graph.
A Database Tool Integrating Genomic and Pharmacologic Data from Adrenocortical Carcinoma Cell Lines, PDX, and Patient Samples. · full record | Socratic