Deletion of Forkhead Box M1 Transcription Factor from Respiratory Epithelial Cells Inhibits Pulmonary Tumorigenesis is a research paper published in PLoS ONE (2009). On theSindex it has a DataRank of 2.0. It has been cited 67 times, with 39 citing works in its 1-hop citation network.
The Forkhead Box m1 (Foxm1) protein is induced in a majority of human non-small cell lung cancers and its expression is associated with poor prognosis. However, specific requirements for the Foxm1 in each cell type of the cancer lesion remain unknown. The present study provides the first genetic evidence that the Foxm1 expression in respiratory epithelial cells is essential for lung tumorigenesis. Using transgenic mice, we demonstrated that conditional deletion of Foxm1 from lung epithelial cells (epFoxm1(-/-) mice) prior to tumor initiation caused a striking reduction in the number and size of lung tumors, induced by either urethane or 3-methylcholanthrene (MCA)/butylated hydroxytoluene (BHT). Decreased lung tumorigenesis in epFoxm1(-/-) mice was associated with diminished proliferation of tumor cells and reduced expression of Topoisomerase-2alpha (TOPO-2alpha), a critical regulator of tumor cell proliferation. Depletion of Foxm1 mRNA in cultured lung adenocarcinoma cells significantly decreased TOPO-2alpha mRNA and protein levels. Moreover, Foxm1 directly bound to and induced transcription of the mouse TOPO-2alpha promoter region, indicating that TOPO-2alpha is a direct target of Foxm1 in lung tumor cells. Finally, we demonstrated that a conditional deletion of Foxm1 in pre-existing lung tumors dramatically reduced tumor growth in the lung. Expression of Foxm1 in respiratory epithelial cells is critical for lung cancer formation and TOPO-2alpha expression in vivo, suggesting that Foxm1 is a promising target for anti-tumor therapy.
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Base Score Contribution
0.633
From this paper's citation signal
Citation Network Contribution
1.4
From 33 citing papers with measurable signal
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 32% comes from its base citations and 68% from the citation network (33 citing papers contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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