ArticlePloS one2015
Identification of Biomarker and Co-Regulatory Motifs in Lung Adenocarcinoma Based on Differential Interactions.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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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.
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Who cites it
2 citing papers in PubMed.
- Regulatory Effect of let-7f Transfection in Non-Small Cell Lung Cancer on its Candidate Target Genes.Iranian biomedical journal · 2022Article
- The Functional Effects of Key Driver KRAS Mutations on Gene Expression in Lung Cancer.Frontiers in genetics · 2020Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Changes in intermolecular interactions (differential interactions) may influence the progression of cancer. Specific genes and their regulatory networks may be more closely associated with cancer when taking their transcriptional and post-transcriptional levels and dynamic and static interactions into account simultaneously. In this paper, a differential interaction analysis was performed to detect lung adenocarcinoma-related genes. Furthermore, a miRNA-TF (transcription factor) synergistic regulation network was constructed to identify three kinds of co-regulated motifs, namely, triplet, crosstalk and joint. Not only were the known cancer-related miRNAs and TFs (let-7, miR-15a, miR-17, TP53, ETS1, and so on) were detected in the motifs, but also the miR-15, let-7 and miR-17 families showed a tendency to regulate the triplet, crosstalk and joint motifs, respectively. Moreover, several biological functions (i.e., cell cycle, signaling pathways and hemopoiesis) associated with the three motifs were found to be frequently targeted by the drugs for lung adenocarcinoma. Specifically, the two 4-node motifs (crosstalk and joint) based on co-expression and interaction had a closer relationship to lung adenocarcinoma, and so further research was performed on them. A 10-gene biomarker (UBC, SRC, SP1, MYC, STAT3, JUN, NR3C1, RB1, GRB2 and MAPK1) was selected from the joint motif, and a survival analysis indicated its significant association with survival. Among the ten genes, JUN, NR3C1 and GRB2 are our newly detected candidate lung adenocarcinoma-related genes. The genes, regulators and regulatory motifs detected in this work will provide potential drug targets and new strategies for individual therapy.
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