Evidence map›Paper›PMID 22659796›Full record

ArticleCell cycle (Georgetown, Tex.)2012

Differential impact of structurally different anti-diabetic drugs on proliferation and chemosensitivity of acute lymphoblastic leukemia cells.

Jingxuan Pan, Chun Chen, Yanli Jin, Enrique Fuentes-Mattei, Guermarie Velazquez-Tores, Juliana Maria Benito, Marina Konopleva, Michael Andreeff, Mong-Hong Lee, Sai-Ching Jim Yeung

Open access · bronzeAbstract read
In one paragraph

Article in Cell cycle (Georgetown, Tex.), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
2.6field-weighted citation impact, top 10% 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

26 citing papers in PubMed, 51 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Review
  6. Research Progress on the Use of Metformin in Leukemia Treatment.Current treatment options in oncology · 2024
    Review
  7. Metformin: A potential adjunct for treatment of systemic mastocytosis.The journal of allergy and clinical immunology. Global · 2024
    Article
  8. Review
  9. Review
  10. Article
  11. Review
  12. Review
  13. Review
  14. Review
  15. Mechanisms by Which Obesity Impacts Survival from Acute Lymphoblastic Leukemia.Journal of the National Cancer Institute. Monographs · 2019
    Review
  16. Metformin and blood cancers.Clinics (Sao Paulo, Brazil) · 2018
    Review
  17. Review
  18. Article
  19. Review
  20. 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

10 authors at 3 institutions in 2 countries.

Jingxuan PanDepartment of Pathophysiology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China.
Chun Chen
Yanli Jin
Enrique Fuentes-Mattei
Guermarie Velazquez-Tores
Juliana Maria Benito
Marina Konopleva
Michael Andreeff
Mong-Hong Lee
Sai-Ching Jim Yeung
The University of Texas MD Anderson Cancer Center · USSun Yat-sen University · CNZhongshan Hospital · CN

Funding

TRAINING PROGRAM IN MOLECULAR GENETICS OF CANCERT32CA009299 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI LOZANO, GUILLERMINA · 1985 to 2014
$4.7M
Regulation of cyclin-dependent kinase inhibitor p27 in cancerR01CA089266 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI LEE, MONG-HONG · 2002 to 2013
$2.8M
NCI NIH HHS R01 CA089266NCI NIH HHS R01CA089266NCI NIH HHS T32 CA009299NCI NIH HHS T32CA009299
6 · The paper itself

Abstract

Hyperglycemia during hyper-CVAD chemotherapy is associated with poor outcomes of acute lymphoblastic leukemia (ALL) (Cancer 2004; 100: 1179-85). The optimal clinical strategy to manage hyperglycemia during hyper-CVAD is unclear. To examine whether anti-diabetic pharmacotherapy can influence chemosensitivity of ALL cells, we examined the impacts of different anti-diabetic agents on ALL cell lines and patient samples. Pharmacologically achievable concentrations of insulin, aspart and glargine significantly increased the number of ALL cells, and aspart and glargine did so at lower concentrations than human insulin. In contrast, metformin and rosiglitazone significantly decreased the cell number. Human insulin and analogs activated AKT/mTOR signaling and stimulated ALL cell proliferation (as measured by flow cytometric methods), but metformin and rosiglitazone blocked AKT/mTOR signaling and inhibited proliferation. Metformin 500 μM and rosiglitazone 10 μM were found to sensitize Reh cells to daunorubicin, while aspart, glargine and human insulin (all at 1.25 mIU/L) enhanced chemoresistance. Metformin and rosiglitazone enhanced daunorubicin-induced apoptosis, while insulin, aspart and glargine antagonized daunorubicin-induced apoptosis. In addition, metformin increased etoposide-induced and L-asparaginase-induced apoptosis; rosiglitazone increased etoposide-induced and vincristine-induced apoptosis. In conclusion, our results suggest that use of insulins to control hyperglycemia in ALL patients may contribute to anthracycline chemoresistance, while metformin and thiazolidinediones may improve chemosensitivity to anthracycline as well as other chemotherapy drugs through their different impacts on AKT/mTOR signaling in leukemic cells. Our data suggest that the choice of anti-diabetic pharmacotherapy during chemotherapy may influence clinical outcomes in ALL.

Indexed as

AdolescentApoptosisCell Line, TumorCell ProliferationChildChild, PreschoolDaunorubicinFemaleHumansHypoglycemic AgentsInsulinInsulin AspartInsulin GlargineInsulin, Long-ActingMaleMetforminDaunorubicinHypoglycemic AgentsInsulinInsulin AspartInsulin GlargineInsulin, Long-ActingMetforminMTOR protein, humanProto-Oncogene Proteins c-aktRosiglitazoneThiazolidinedionesTOR Serine-Threonine Kinases

Identifiers

PMID22659796
PMCPMC3383592
OpenAlexW2036634412

What OpenQuestion holds

Textmetadata
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.