Evidence map›Paper›PMID 25601862›Full record

ArticleFrontiers in immunology2014

Systems Biology Strategy Reveals PKCδ is Key for Sensitizing TRAIL-Resistant Human Fibrosarcoma.

Kentaro Hayashi, Sho Tabata, Vincent Piras, Masaru Tomita, Kumar Selvarajoo

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
0.9field-weighted citation impact, top 26% of its field
1 · What the graph read from it

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 registry

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.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 17 citations in OpenAlex.

  1. Article
  2. Article
  3. Towards multi-omics synthetic data integration.Briefings in bioinformatics · 2024
    Review
  4. Article
  5. Review
  6. Article
  7. Article
  8. Review
  9. Defining rules for cancer cell proliferation in TRAIL stimulation.NPJ systems biology and applications · 2019
    Article
  10. Article
  11. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Kentaro HayashiInstitute for Advanced Biosciences, Keio University , Tsuruoka , Japan ; Systems Biology Program, Graduate School of Media and Governance, Keio University , Fujisawa , Japan.
Sho TabataInstitute for Advanced Biosciences, Keio University , Tsuruoka , Japan ; Systems Biology Program, Graduate School of Media and Governance, Keio University , Fujisawa , Japan.
Vincent PirasInstitute for Advanced Biosciences, Keio University , Tsuruoka , Japan ; Systems Biology Program, Graduate School of Media and Governance, Keio University , Fujisawa , Japan.
Masaru TomitaInstitute for Advanced Biosciences, Keio University , Tsuruoka , Japan ; Systems Biology Program, Graduate School of Media and Governance, Keio University , Fujisawa , Japan.
Kumar SelvarajooInstitute for Advanced Biosciences, Keio University , Tsuruoka , Japan ; Systems Biology Program, Graduate School of Media and Governance, Keio University , Fujisawa , Japan.
Keio University Shonan Fujisawa · JPKeio University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer cells are highly variable and largely resistant to therapeutic intervention. Recently, the use of the tumor necrosis factor related apoptosis-inducing ligand (TRAIL) induced treatment is gaining momentum due to TRAIL's ability to specifically target cancers with limited effect on normal cells. Nevertheless, several malignant cancer types still remain non-sensitive to TRAIL. Previously, we developed a dynamic computational model, based on perturbation-response differential equations approach, and predicted protein kinase C (PKC) as the most effective target, with over 95% capacity to kill human fibrosarcoma (HT1080) in TRAIL stimulation (1). Here, to validate the model prediction, which has significant implications for cancer treatment, we conducted experiments on two TRAIL-resistant cancer cell lines (HT1080 and HT29). Using PKC inhibitor bisindolylmaleimide I, we demonstrated that cell viability is significantly impaired with over 95% death of both cancer types, in consistency with our previous model. Next, we measured caspase-3, Poly (ADP-ribose) polymerase (PARP), p38, and JNK activations in HT1080, and confirmed cell death occurs through apoptosis with significant increment in caspase-3 and PARP activations. Finally, to identify a crucial PKC isoform, from 10 known members, we analyzed each isoform mRNA expressions in HT1080 cells and shortlisted the highest 4 for further siRNA knock-down (KD) experiments. From these KDs, PKCδ produced the most cancer cell death in conjunction with TRAIL. Overall, our approach combining model predictions with experimental validation holds promise for systems biology based cancer therapy.

Indexed as

apoptosiscancercell dynamicscomputational modelprotein kinase Csignaling pathwayTRAIL

Identifiers

PMID25601862
PMCPMC4283611
OpenAlexW1974465142

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.