Literature DB >> 36224382

Identification and analysis of dysregulated fatty acid metabolism genes in breast cancer subtypes.

Umar Yousuf1, Shazia Sofi1, Aanisa Makhdoomi1, Manzoor Ahmad Mir2.   

Abstract

Breast cancer is one of the most aggressive and lethal types of transformation among women. An anomaly of normal fatty acid metabolism is acknowledged as a critical trigger for malignant transformations including breast cancer, but the prospect of targeting fatty acid metabolism for the treatment of malignancy has remained unrecognized so far. It has been observed that specific fatty acid metabolism genes are involved in the commencement and development of breast cancer. These specific genes have also been observed to be related to different isotypes/molecular subtypes of breast cancer. The main purpose of this study was to scrutinize the prognostic significance, functional role, and expression pattern of fatty acid metabolism genes. In-Silico tools like TCGA BrCA, Gepia2, Ualcan Analysis, UCSC Xena, Kaplan-Meier plotter, Bc-gene EXminer, String, gene ontology, and KEGG databases, were used to assess the expression pattern of the fatty acid metabolism genes in breast cancer patients and also among the different molecular sub-types of breast cancer. Differential gene expression analysis revealed dysregulation of FABP4, FABP5, PLIN1, PLIN2, PLIN4, PLIN5, LPIN1, MGLL, PNPLA2, PNPLA7, ACSL1, and ACOX2 showing a fold change >  ± 1.5. Also, most of these genes show downregulation in Ualcan analysis of different isotypes/molecular subtypes of breast cancer. The study reveals that the screened genes i.e., FABP4, FABP5, PLIN1, PLIN2, PLIN4, PLIN5, LPIN1, MGLL, PNPLA2, PNPLA7, ACSL1, and ACOX2 can be used as biomarkers that reveal poor prognosis and may serve as therapeutic targets for the treatment of breast cancer.
© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Bioinformatics; Breast cancer; Dysregulated genes; Expression pattern; Fatty acid metabolism; Gene ontology; Prognosis; Survival probability

Mesh:

Substances:

Year:  2022        PMID: 36224382     DOI: 10.1007/s12032-022-01861-2

Source DB:  PubMed          Journal:  Med Oncol        ISSN: 1357-0560            Impact factor:   3.738


  5 in total

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Journal:  Clin Breast Cancer       Date:  2022-04-25       Impact factor: 3.078

2.  Prevalence, morphologic features and proliferation indices of breast carcinoma molecular classes using immunohistochemical surrogate markers.

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Review 3.  Chemokines in triple-negative breast cancer heterogeneity: New challenges for clinical implications.

Authors:  Umar Mehraj; Umar Mushtaq; Manzoor A Mir; Afnan Saleem; Muzafar A Macha; Mohammad Nadeem Lone; Abid Hamid; Mohammed A Zargar; Syed Mudasir Ahmad; Nissar Ahmad Wani
Journal:  Semin Cancer Biol       Date:  2022-03-09       Impact factor: 17.012

4.  Adapalene inhibits the growth of triple-negative breast cancer cells by S-phase arrest and potentiates the antitumor efficacy of GDC-0941.

Authors:  Umar Mehraj; Nissar Ahmad Wani; Abid Hamid; Mustfa Alkhanani; Abdullah Almilaibary; Manzoor Ahmad Mir
Journal:  Front Pharmacol       Date:  2022-08-08       Impact factor: 5.988

5.  bc-GenExMiner 3.0: new mining module computes breast cancer gene expression correlation analyses.

Authors:  Pascal Jézéquel; Jean-Sébastien Frénel; Loïc Campion; Catherine Guérin-Charbonnel; Wilfried Gouraud; Gabriel Ricolleau; Mario Campone
Journal:  Database (Oxford)       Date:  2013-01-15       Impact factor: 3.451

  5 in total

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