ResearcherNihon UniversityNo recent work listed
Hiroki Nagase
Matched on ORCID iD 0000-0002-3992-5399; OpenAlex author ID A5017785312. Sources: OpenAlex.
Their work
- Papers
- 12 (first author 0, last author 5)
- Trials
- 0
- Grants
- 0
- Labs led
- 1
- Collaborators
- 27
2012: 1 paper · 2013: 1 paper · 2014: none · 2015: 2 papers · 2016: none · 2017: none · 2018: none · 2019: none · 2020: 4 papers · 2021: 1 paper · 2022: 2 papers · 2023: 1 paper
Papers 12
- Use of DNA-alkylating pyrrole-imidazole polyamides for anti-cancer drug sensitivity screening in pancreatic ductal adenocarcinoma. Last author DOI 10.1002/cam4.5359↗
- Transcriptomic analysis reveals high ITGB1 expression as a predictor for poor prognosis of pancreatic cancer. Last author DOI 10.1371/journal.pone.0268630↗
- Machine learning with imaging features to predict the expression of ITGAV, which is a poor prognostic factor derived from transcriptome analysis in pancreatic … Last author DOI 10.3892/ijo.2022.5350↗
- Obesity reduces the anticancer effect of AdipoRon against orthotopic pancreatic cancer in diet-induced obese mice. Last author DOI 10.1038/s41598-021-82617-2↗
- Radiogenomics for predicting p53 status, PD-L1 expression, and prognosis with machine learning in pancreatic cancer. Co-author DOI 10.1038/s41416-020-0997-1↗
- MIR1246 in body fluids as a biomarker for pancreatic cancer. Co-author DOI 10.1038/s41598-020-65695-6↗
- Cancer cell-derived interleukin-33 decoy receptor sST2 enhances orthotopic tumor growth in a murine pancreatic cancer model. Last author DOI 10.1371/journal.pone.0232230↗
- Prognostic significance of p16 protein in pancreatic ductal adenocarcinoma. Co-author DOI 10.3892/mco.2020.2047↗
- Silencing of RUNX2 enhances gemcitabine sensitivity of p53-deficient human pancreatic cancer AsPC-1 cells through the stimulation of TAp63-mediated cell death. Co-author DOI 10.1038/cddis.2015.242↗
- Silencing of RUNX2 enhances gemcitabine sensitivity of p53-deficient human pancreatic cancer AsPC-1 cells through the stimulation of TAp63-mediated cell death. Co-author DOI 10.1038/cddiscovery.2015.10↗
- Suppressed expression of NDRG2 correlates with poor prognosis in pancreatic cancer. Co-author DOI 10.1016/j.bbrc.2013.10.010↗
- S100A4, frequently overexpressed in various human cancers, accelerates cell motility in pancreatic cancer cells. Co-author DOI 10.1016/j.bbrc.2012.10.048↗
Closest collaborators
The 25 strongest of 27 by collab_strength@1: shared papers, trials and grants, recent and small-team work weighing most.
- Yosuke Iwatate · 5 shared papers, 2020–2022 · strength 0.58
- Paper Transcriptomic analysis reveals high ITGB1 expression as a predictor for poor prognosis of pancreatic cancer. DOI 10.1371/journal.pone.0268630↗
- Paper Machine learning with imaging features to predict the expression of ITGAV, which is a poor prognostic factor derived fr… DOI 10.3892/ijo.2022.5350↗
- Paper MIR1246 in body fluids as a biomarker for pancreatic cancer. DOI 10.1038/s41598-020-65695-6↗
- Fumitaka Ishige · 5 shared papers, 2020–2022 · strength 0.58
- Paper Transcriptomic analysis reveals high ITGB1 expression as a predictor for poor prognosis of pancreatic cancer. DOI 10.1371/journal.pone.0268630↗
- Paper Machine learning with imaging features to predict the expression of ITGAV, which is a poor prognostic factor derived fr… DOI 10.3892/ijo.2022.5350↗
- Paper MIR1246 in body fluids as a biomarker for pancreatic cancer. DOI 10.1038/s41598-020-65695-6↗
- Hidehito Arimitsu · 5 shared papers, 2020–2022 · strength 0.58
- Paper Transcriptomic analysis reveals high ITGB1 expression as a predictor for poor prognosis of pancreatic cancer. DOI 10.1371/journal.pone.0268630↗
- Paper Machine learning with imaging features to predict the expression of ITGAV, which is a poor prognostic factor derived fr… DOI 10.3892/ijo.2022.5350↗
- Paper MIR1246 in body fluids as a biomarker for pancreatic cancer. DOI 10.1038/s41598-020-65695-6↗
- Wataru Takayama · 5 shared papers, 2020–2022 · strength 0.58
- Paper Transcriptomic analysis reveals high ITGB1 expression as a predictor for poor prognosis of pancreatic cancer. DOI 10.1371/journal.pone.0268630↗
- Paper Machine learning with imaging features to predict the expression of ITGAV, which is a poor prognostic factor derived fr… DOI 10.3892/ijo.2022.5350↗
- Paper MIR1246 in body fluids as a biomarker for pancreatic cancer. DOI 10.1038/s41598-020-65695-6↗
- Yasukuni Mori · 3 shared papers, 2020–2022 · strength 0.36
- Paper Transcriptomic analysis reveals high ITGB1 expression as a predictor for poor prognosis of pancreatic cancer. DOI 10.1371/journal.pone.0268630↗
- Paper Machine learning with imaging features to predict the expression of ITGAV, which is a poor prognostic factor derived fr… DOI 10.3892/ijo.2022.5350↗
- Paper Radiogenomics for predicting p53 status, PD-L1 expression, and prognosis with machine learning in pancreatic cancer. DOI 10.1038/s41416-020-0997-1↗
- Miho Akimoto · 2 shared papers, 2020–2021 · strength 0.35
- Paper Obesity reduces the anticancer effect of AdipoRon against orthotopic pancreatic cancer in diet-induced obese mice. DOI 10.1038/s41598-021-82617-2↗
- Paper Cancer cell-derived interleukin-33 decoy receptor sST2 enhances orthotopic tumor growth in a murine pancreatic cancer m… DOI 10.1371/journal.pone.0232230↗
- Osamu Shimozato · 4 shared papers, 2015–2022 · strength 0.35
- Paper Transcriptomic analysis reveals high ITGB1 expression as a predictor for poor prognosis of pancreatic cancer. DOI 10.1371/journal.pone.0268630↗
- Paper Machine learning with imaging features to predict the expression of ITGAV, which is a poor prognostic factor derived fr… DOI 10.3892/ijo.2022.5350↗
- Paper Silencing of RUNX2 enhances gemcitabine sensitivity of p53-deficient human pancreatic cancer AsPC-1 cells through the s… DOI 10.1038/cddis.2015.242↗
- Naoki Kuwayama · 2 shared papers, 2022 · strength 0.25
- Paper Transcriptomic analysis reveals high ITGB1 expression as a predictor for poor prognosis of pancreatic cancer. DOI 10.1371/journal.pone.0268630↗
- Paper Machine learning with imaging features to predict the expression of ITGAV, which is a poor prognostic factor derived fr… DOI 10.3892/ijo.2022.5350↗
- Takashi Uno · 2 shared papers, 2022 · strength 0.25
- Paper Transcriptomic analysis reveals high ITGB1 expression as a predictor for poor prognosis of pancreatic cancer. DOI 10.1371/journal.pone.0268630↗
- Paper Machine learning with imaging features to predict the expression of ITGAV, which is a poor prognostic factor derived fr… DOI 10.3892/ijo.2022.5350↗
- Keizo Takenaga · 1 shared paper, 2021 · strength 0.19
- Akiko Tsujimoto · 1 shared paper, 2023 · strength 0.17
- Keizo Takenaga · 1 shared paper, 2020 · strength 0.16
- Hirokazu Sugimoto · 2 shared papers, 2015 · strength 0.10
- Paper Silencing of RUNX2 enhances gemcitabine sensitivity of p53-deficient human pancreatic cancer AsPC-1 cells through the s… DOI 10.1038/cddis.2015.242↗
- Paper Silencing of RUNX2 enhances gemcitabine sensitivity of p53-deficient human pancreatic cancer AsPC-1 cells through the s… DOI 10.1038/cddiscovery.2015.10↗
- Mizuyo Nakamura · 2 shared papers, 2015 · strength 0.10
- Paper Silencing of RUNX2 enhances gemcitabine sensitivity of p53-deficient human pancreatic cancer AsPC-1 cells through the s… DOI 10.1038/cddis.2015.242↗
- Paper Silencing of RUNX2 enhances gemcitabine sensitivity of p53-deficient human pancreatic cancer AsPC-1 cells through the s… DOI 10.1038/cddiscovery.2015.10↗
- Toshinori Ozaki · 2 shared papers, 2015 · strength 0.10
- Paper Silencing of RUNX2 enhances gemcitabine sensitivity of p53-deficient human pancreatic cancer AsPC-1 cells through the s… DOI 10.1038/cddis.2015.242↗
- Paper Silencing of RUNX2 enhances gemcitabine sensitivity of p53-deficient human pancreatic cancer AsPC-1 cells through the s… DOI 10.1038/cddiscovery.2015.10↗
- Makoto Sunamura · 2 shared papers, 2012–2013 · strength 0.06
- Yuriko Saiki · 2 shared papers, 2012–2013 · strength 0.06
- Shinichi Fukushige · 2 shared papers, 2012–2013 · strength 0.06
- Akira Horii · 2 shared papers, 2012–2013 · strength 0.06
- Meijie Sang · 1 shared paper, 2015 · strength 0.05
- Meixiang Sang · 1 shared paper, 2015 · strength 0.05
- Shinichi Egawa · 1 shared paper, 2013 · strength 0.03
- Akihiro Yamamura · 1 shared paper, 2013 · strength 0.03
- Kazuhiro Morishita · 1 shared paper, 2013 · strength 0.03
- Michiaki Unno · 1 shared paper, 2013 · strength 0.03
How to reach this person
A chain of introductions through people who have published, run trials or held grants together (warm_path@1: fewest links first, then the strongest). Built from public records only; no contact details are kept.