Literature DB >> 28276747

Proteogenomic studies on cancer drug resistance: towards biomarker discovery and target identification.

Shuyue Fu1, Xiang Liu2, Maochao Luo3, Ke Xie4, Edouard C Nice5, Haiyuan Zhang6, Canhua Huang1.   

Abstract

INTRODUCTION: Chemoresistance is a major obstacle for current cancer treatment. Proteogenomics is a powerful multi-omics research field that uses customized protein sequence databases generated by genomic and transcriptomic information to identify novel genes (e.g. noncoding, mutation and fusion genes) from mass spectrometry-based proteomic data. By identifying aberrations that are differentially expressed between tumor and normal pairs, this approach can also be applied to validate protein variants in cancer, which may reveal the response to drug treatment. Areas covered: In this review, we will present recent advances in proteogenomic investigations of cancer drug resistance with an emphasis on integrative proteogenomic pipelines and the biomarker discovery which contributes to achieving the goal of using precision/personalized medicine for cancer treatment. Expert commentary: The discovery and comprehensive understanding of potential biomarkers help identify the cohort of patients who may benefit from particular treatments, and will assist real-time clinical decision-making to maximize therapeutic efficacy and minimize adverse effects. With the development of MS-based proteomics and NGS-based sequencing, a growing number of proteogenomic tools are being developed specifically to investigate cancer drug resistance.

Entities:  

Keywords:  Biomarker Discovery; Cancer drug resistance; Precision/personalized Medicine; Proteogenomics

Mesh:

Substances:

Year:  2017        PMID: 28276747     DOI: 10.1080/14789450.2017.1299006

Source DB:  PubMed          Journal:  Expert Rev Proteomics        ISSN: 1478-9450            Impact factor:   3.940


  3 in total

1.  Optimizing miRNA-module diagnostic biomarkers of gastric carcinoma via integrated network analysis.

Authors:  Fengbin Zhang; Wenjuan Xu; Jun Liu; Xiaoyan Liu; Bingjie Huo; Bing Li; Zhong Wang
Journal:  PLoS One       Date:  2018-06-07       Impact factor: 3.240

Review 2.  A Review of ULK1-Mediated Autophagy in Drug Resistance of Cancer.

Authors:  Li Liu; Lu Yan; Ning Liao; Wan-Qin Wu; Jun-Ling Shi
Journal:  Cancers (Basel)       Date:  2020-02-04       Impact factor: 6.639

3.  Whole-exome sequencing reveals potential mechanisms of drug resistance to FGFR3-TACC3 targeted therapy and subsequent drug selection: towards a personalized medicine.

Authors:  Zhou Tong; Cong Yan; Yu-An Dong; Ming Yao; Hangyu Zhang; Lulu Liu; Yi Zheng; Peng Zhao; Yimin Wang; Weijia Fang; Feifei Zhang; Weiqin Jiang
Journal:  BMC Med Genomics       Date:  2020-09-21       Impact factor: 3.063

  3 in total

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