Molecular subtyping of cancer: Current status and moving toward clinical applications

Lan Zhao*, Victor H.F. Lee, Kwok Po NG, Hong Yan, Maarten F. Bijlsma

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

Abstract

Cancer is a collection of genetic diseases, with large phenotypic differences and genetic heterogeneity between different types of cancers and even within the same cancer type. Recent advances in genome-wide profiling provide an opportunity to investigate global molecular changes during the development and progression of cancer. Meanwhile, numerous statistical and machine learning algorithms have been designed for the processing and interpretation of high-throughput molecular data. Molecular subtyping studies have allowed the allocation of cancer into homogeneous groups that are considered to harbor similar molecular and clinical characteristics. Furthermore, this has helped researchers to identify both actionable targets for drug design as well as biomarkers for response prediction. In this review, we introduce five frequently applied techniques for generating molecular data, which are microarray, RNA sequencing, quantitative polymerase chain reaction, NanoString and tissue microarray. Commonly used molecular data for cancer subtyping and clinical applications are discussed. Next, we summarize a workflow for molecular subtyping of cancer, including data preprocessing, cluster analysis, supervised classification and subtype characterizations. Finally, we identify and describe four major challenges in the molecular subtyping of cancer that may preclude clinical implementation. We suggest that standardized methods should be established to help identify intrinsic subgroup signatures and build robust classifiers that pave the way toward stratified treatment of cancer patients.

Original languageEnglish
Pages (from-to)572-584
Number of pages13
JournalBriefings in Bioinformatics
Volume20
Issue number2
DOIs
Publication statusPublished - 22 Mar 2019

Scopus Subject Areas

  • Information Systems
  • Molecular Biology

User-Defined Keywords

  • cancer
  • challenges
  • heterogeneity
  • subtypes
  • subtyping

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