In one paragraphArticle in bioRxiv : the preprint server for biology, 2025. 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
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 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
5 · Who and what moneyAuthors and funding
11 authors.
Chen ChenDepartment of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA.ORCID 0000-0002-8042-7201 Enakshi SahaDepartment of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA.ORCID 0000-0003-2938-539X Jonas FischerDepartment of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA.
Marouen Ben GuebilaDepartment of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA.ORCID 0000-0001-5934-966X Viola FanfaniDepartment of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA.ORCID 0000-0003-3852-6908 Katherine H ShuttaDepartment of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA.ORCID 0000-0003-0402-3771 Megha PadiDepartment of Molecular and Cellular Biology, University of Arizona, Tucson, AZ 85719, USA.ORCID 0000-0002-3446-4562 Kimberly GlassDepartment of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA.ORCID 0000-0003-4394-5779 Dawn L DeMeoChanning Division of Network Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA.ORCID 0000-0001-9653-0636 Camila M Lopes-RamosDepartment of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA.ORCID 0000-0003-0284-7371 John QuackenbushDepartment of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA.ORCID 0000-0002-2702-5879 Funding
Tissue and Pathology ResourcesP50CA127003 · NCI · DANA-FARBER CANCER INST · PI SHIVDASANI, RAMESH A · 2007 to 2023
$33.2MRespiratory Computational Discovery CoreP01HL114501 · NHLBI · WEILL MEDICAL COLL OF CORNELL UNIV · PI SILVERMAN, EDWIN K · 2013 to 2025
$24.9MSYSTEMS APPROACHES TO THE EPIDEMIOLOGY, GENETICS AND GENOMICS OF LUNG DISEASEST32HL007427 · NHLBI · HARVARD UNIVERSITY (MEDICAL SCHOOL) · PI DAWN L DEMEO, Edwin K Silverman · 1985 to 2026
$13.6MUnraveling the Complexities of Risk and Mechanism in CancerR35CA220523 · NCI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI QUACKENBUSH, JOHN · 2018 to 2024
$6.0MLeveraging Variant-perturbed Gene Regulation to Support Precision Medicine in COPDR01HL155749 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI Kimberly Renee Glass · 2022 to 2026
$4.2MWebMeV: A Robust Platform for Intuitive Genomic Data AnalysisU24CA231846 · NCI · HARVARD SCHOOL OF PUBLIC HEALTH · PI QUACKENBUSH, JOHN · 2019 to 2023
$3.2MNetworks Tools to Understand Sex- and Gender-Specific Drivers of DiseaseR01HG011393 · NHGRI · BRIGHAM AND WOMEN'S HOSPITAL · PI DEMEO, DAWN L, QUACKENBUSH, JOHN · 2021 to 2024
$2.1MUnraveling the regulatory circuits that drive Merkel cell carcinomaR01CA251729 · NCI · UNIVERSITY OF ARIZONA · PI PADI, MEGHA · 2021 to 2025
$1.7MMentoring in Patient Oriented Research in Lung Disease through the Lens of Sex as a Biological VariableK24HL171900 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI DAWN L DEMEO · 2024 to 2026
$386kSex chromosome gene regulatory networks and COPDK01HL166376 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI LOPES-RAMOS, CAMILA · 2023 to 2024
$324kNCI NIH HHS P50 CA127003NCI NIH HHS R01 CA251729NCI NIH HHS R35 CA220523NCI NIH HHS U24 CA231846NHGRI NIH HHS R01 HG011393NHLBI NIH HHS K01 HL166376NHLBI NIH HHS K24 HL171900NHLBI NIH HHS P01 HL114501NHLBI NIH HHS R01 HL155749NHLBI NIH HHS T32 HL007427
6 · The paper itselfAbstract
Lung adenocarcinoma (LUAD) exhibits differences between the sexes in incidence, prognosis, and therapy, suggesting underexplored molecular mechanisms. We conducted an integrative multi-omics analysis using the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and The Cancer Genome Atlas (TCGA) datasets to contrast transcriptomes and proteomes between sexes. We used TIGER to analyze TCGA-LUAD expression data and found sex-biased activity of transcription factors (TFs); we used PTM-SEA with CPTAC-LUAD proteomics data and found sex-biased kinase activity. We combined these to construct a kinase-TF signaling network and discovered druggable pathways linked to cancer-related processes. We also found significant sex biases in clinically relevant TFs and kinases, including NR3C1, AR, and AURKA. Using the PRISM drug screening database, we identified potential sex-specific drugs, such as glucocorticoid receptor agonists and aurora kinase inhibitors. Our findings emphasize the importance of considering sex and using multi-omics network methods to discover personalized cancer therapies.
Indexed as
APOLLOCPTACdrug repurposingLung adenocarcinomamulti-omicspost-translational modificationsPRISMprotein signaling networksex differencesTCGA
Identifiers
PMID39975108
PMCPMC11838606
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