Evidence map›Paper›PMID 30515357›Full record

ArticlePeerJ2018

Model-based in silico analysis of the PI3K/Akt pathway: the elucidation of cross-talk between diabetes and breast cancer.

Sammia Rehman, Ayesha Obaid, Anam Naz, Amjad Ali, Shahzina Kanwal, Jamil Ahmad

Open access · goldAbstract read
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Article in PeerJ, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.3field-weighted citation impact, top 42% 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

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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

7 citing papers in PubMed, 11 citations in OpenAlex.

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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

6 authors at 2 institutions in 2 countries.

Sammia RehmanAtta-ur-Rahman School of Applied Biosciences (ASAB), National University of Science and Technology, Islamabad, Pakistan.
Ayesha ObaidAtta-ur-Rahman School of Applied Biosciences (ASAB), National University of Science and Technology, Islamabad, Pakistan.
Anam NazAtta-ur-Rahman School of Applied Biosciences (ASAB), National University of Science and Technology, Islamabad, Pakistan.ORCID 0000-0002-6514-5417
Amjad AliAtta-ur-Rahman School of Applied Biosciences (ASAB), National University of Science and Technology, Islamabad, Pakistan.
Shahzina KanwalGuangzhou Institutes of Biomedicine and Health, Guangzhou, China.
Jamil AhmadResearch Center for Modeling & Simulation (RCMS), National University of Sciences and Technology, Islamabad, Pakistan.
Guangzhou Institutes of Biomedicine and Health · CNNational University of Sciences and Technology · PK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA positive association between diabetes and breast cancer has been identified by various epidemiological and clinical studies. However, the possible molecular interactions between the two heterogeneous diseases have not been fully determined yet. There are several underlying mechanisms which may increase the risk of breast cancer in diabetic patients.

introductionIn this study, we focused on the role of O-GlcNAc transferase (OGT) enzyme in the regulation of phosphatidylinositol-3 kinase (PI3K) pathway through activation/deactivation of Akt protein. The efficiency of insulin signaling in adipocytes is reduced as a result of OGT overexpression which further attenuates Akt signaling; as a result, the efficiency of insulin signaling is reduced by downregulation of insulin-responsive genes. On the other hand, increased expression of OGT results in Akt activation in breast cancer cells, leading to enhanced cell proliferation and inhibition of the apoptosis. However, the interplay amongst these signaling pathways is still under investigation.

methodsIn this study, we used Petri nets (PNs) to model and investigate the role of PI3K and OGT pathways, acting as key players in crosstalk between diabetes and breast cancer, resulting in progression of these chronic diseases. Moreover, in silico perturbation experiments were applied on the model to analyze the effects of anti-cancer agents (shRNA and BZX) and anti-diabetic drug (Metformin) on the system.

resultsOur PN model reflects the alterations in protein expression and behavior and the correlation between breast cancer and diabetes. The analysis proposed two combination therapies to combat breast cancer progression in diabetic patients including combination of OGTmRNA silencing and OGT inhibitor (BZX) as first combination and BZX and Metformin as the second.

conclusionThe PN model verified that alterations in O-GlcNAc signaling affect both insulin resistance and breast cancer. Moreover, the combination therapy for breast cancer patients consisting of anti-diabetic drugs such as Metformin along with OGT inhibitors, for example BZX, can produce better treatment regimens.

Indexed as

Breast cancerInsulin resistanceOGTPetri netPI3K/Akt pathway

Identifiers

PMID30515357
PMCPMC6265603
OpenAlexW2900033301

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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.