ArticleScientific reports2018
E2F signature is predictive for the pancreatic adenocarcinoma clinical outcome and sensitivity to E2F inhibitors, but not for the response to cytotoxic-based treatments.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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.
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.
Who cites it
21 citing papers in PubMed.
- An epithelial cell fate-driven predictive model for liver metastasis risk in primary colorectal cancer through single-cell and multi-omics integration.Journal of translational medicine · 2026Article
- E2F3 activates NF-κB signaling through TRIM26 mediated TAB1 ubiquitination in pancreatic cancer.International journal of biological sciences · 2026Article
- Identification of an E2Fs-based gene signature for predicting prognosis and therapeutic response in colorectal cancer.Discover oncology · 2025Article
- The role of miR-150-5p/E2F3/survivin axis in the pathogenesis of plasmablastic lymphoma and its therapeutic potential.Blood advances · 2025Article
- The E2F family: a ray of dawn in cardiomyopathy.Molecular and cellular biochemistry · 2025Review
- Multi-modal domain adaptation for revealing spatial functional landscape from spatially resolved transcriptomics.Briefings in bioinformatics · 2024Article
- E2F transcription factors promote tumorigenicity in pancreatic ductal adenocarcinoma.Cancer medicine · 2024Article
- Genome-wide ATAC-see screening identifies TFDP1 as a modulator of global chromatin accessibility.Nature genetics · 2024Article
- Expression patterns of E2Fs identify tumor microenvironment features in human gastric cancer.PeerJ · 2024Article
- Article
- Vacuolar protein sorting 35 (VPS35) acts as a tumor promoter via facilitating cell cycle progression in pancreatic ductal adenocarcinoma.Functional & integrative genomics · 2023Article
- Review
- Molecular profiling and specific targeting of gemcitabine-resistant subclones in heterogeneous pancreatic cancer cell populations.Frontiers in oncology · 2023Article
- Targeting E2F Sensitizes Prostate Cancer Cells to Drug-Induced Replication Stress by Promoting Unscheduled CDK1 Activity.Cancers · 2022Article
- Early 2 factor (E2F) transcription factors contribute to malignant progression and have clinical prognostic value in lower-grade glioma.Bioengineered · 2021Article
- Polo-Like Kinase 4's Critical Role in Cancer Development and Strategies for Plk4-Targeted Therapy.Frontiers in oncology · 2021Review
- Transcription Factors in Cancer Development and Therapy.Cancers · 2020Review
- Expression and prognostic role of E2F transcription factors in high-grade glioma.CNS neuroscience & therapeutics · 2020Article
- Integrated analysis of the E2F transcription factors across cancer types.Oncology reports · 2020Article
- Next-generation RNA sequencing of FFPE subsections reveals highly conserved stromal reprogramming between canine and human mammary carcinoma.Disease models & mechanisms · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The main goal of this study was to find out strategies of clinical relevance to classify patients with a pancreatic ductal adenocarcinoma (PDAC) for individualized treatments. In the present study a set of 55 patient-derived xenografts (PDX) were obtained and their transcriptome were analyzed by using an Affymetrix approach. A supervised bioinformatics-based analysis let us to classify these PDX in two main groups named E2F-highly dependent and E2F-lowly dependent. Afterwards their characterization by using a Kaplan-Meier analysis demonstrated that E2F high patients survived significantly less than E2F low patients (9.5 months vs. 16.8 months; p = 0.0066). Then we tried to establish if E2F transcriptional target levels were associated to the response to cytotoxic treatments by comparing the IC50 values of E2F high and E2F low cells after gemcitabine, 5-fluorouracil, oxaliplatin, docetaxel or irinotecan treatment, and no association was found. Then we identified an E2F inhibitor compound, named ly101-4B, and we observed that E2F-higly dependent cells were more sensitive to its treatment (IC50 of 19.4 ± 1.8 µM vs. 44.1 ± 4.4 µM; p = 0.0061). In conclusion, in this work we describe an E2F target expression-based classification that could be predictive for patient outcome, but more important, for the sensitivity of tumors to the E2F inhibitors as a treatment. Finally, we can assume that phenotypic characterization, essentially by an RNA expression analysis of the PDAC, can help to predict their clinical outcome and their response to some treatments when are rationally selected.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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 OpenQuestion graph.