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Transcriptome profiling research in urothelial cell carcinoma
  • +12
  • Umar Ahmad,
  • Buhari Ibrahim,
  • Mustapha Mohammed,
  • Ahmed Faris Aldoghachi,
  • Mahmood Usman,
  • Abdulbasit Haliru Yakubu,
  • Abubakar Sadiq Tanko,
  • Khadijat Abubakar Bobbo,
  • Usman Adamu Garkuwa,
  • Abdullahi Adamu Faggo,
  • Sagir Mustapha,
  • Mahmoud Al-Masaeed,
  • Syahril Abdullah,
  • Yong Yoke Keong,
  • Abhi Veerakumarasivam
Umar Ahmad
Universiti Putra Malaysia Medical Genetics Laboratory

Corresponding Author:umarahmad@basug.edu.ng

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Buhari Ibrahim
Bauchi State University Gadau
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Mustapha Mohammed
Universiti Sains Malaysia Pusat Pengajian Sains Farmasi
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Ahmed Faris Aldoghachi
Universiti Putra Malaysia Medical Genetics Laboratory
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Mahmood Usman
Ahmadu Bello University Faculty of Agriculture
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Abdulbasit Haliru Yakubu
University of Maiduguri Faculty of Pharmacy
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Abubakar Sadiq Tanko
Bauchi State University Gadau
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Khadijat Abubakar Bobbo
University Putra Malaysia Institut Biosains
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Usman Adamu Garkuwa
Bauchi State University Gadau
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Abdullahi Adamu Faggo
Bauchi State University Gadau
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Sagir Mustapha
Universiti Sains Malaysia School of Medical Sciences
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Mahmoud Al-Masaeed
The University of Newcastle College of Health Medicine and Wellbeing
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Syahril Abdullah
Universiti Putra Malaysia Medical Genetics Laboratory
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Yong Yoke Keong
Universiti Putra Malaysia Jabatan Anatomi Manusia
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Abhi Veerakumarasivam
Sunway University Department of Medical Sciences
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Abstract

Urothelial cell carcinoma (UCC) is the ninth most common cancer that accounts for 4.7% of all the new cancer cases globally. UCC development and progression are due to complex and stochastic genetic programmes. To study the cascades molecular events underlying the poor prognosis that are due to limited treatment options for advance disease and resistance to conventional therapies in UCC, transcriptomics technology (RNA-Seq), a method of analysing the RNA content of a sample using the modern high-throughput sequencing platforms has been employed to address these limitations. Here we review the principles of RNA-Seq technology and summarize the recent studies on human bladder cancer that employed this technique to unravel the pathogenesis of the disease, identify biomarkers, discover pathways and classify the disease state. We list the commonly used computational platforms and software that are publicly available for RNA-Seq analysis. Moreover, we discussed the future perspective for RNA-Seq studies on bladder cancer and recommend the application of new technology called single cell sequencing (scRNA-Seq) to further understand bladder cancer.
16 Jan 2023Submitted to Applied Research
18 Jan 2023Submission Checks Completed
18 Jan 2023Assigned to Editor
22 Jan 2023Reviewer(s) Assigned
05 Mar 2023Review(s) Completed, Editorial Evaluation Pending
05 Mar 2023Editorial Decision: Revise Major
31 May 20231st Revision Received
31 May 2023Submission Checks Completed
31 May 2023Assigned to Editor
31 May 2023Reviewer(s) Assigned
31 May 2023Review(s) Completed, Editorial Evaluation Pending
07 Jun 2023Editorial Decision: Accept