Premium
Single‐cell profiling approaches to probing tumor heterogeneity
Author(s) -
Khoo Bee Luan,
Chaudhuri Parthiv Kant,
Ramalingam Naveen,
Tan Daniel Shao Weng,
Lim Chwee Teck,
Warkiani Majid Ebrahimi
Publication year - 2016
Publication title -
international journal of cancer
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.475
H-Index - 234
eISSN - 1097-0215
pISSN - 0020-7136
DOI - 10.1002/ijc.30006
Subject(s) - computational biology , tumor heterogeneity , profiling (computer programming) , biology , genetic heterogeneity , cancer , bioinformatics , computer science , genetics , phenotype , gene , operating system
Tumor heterogeneity is a major hindrance in cancer classification, diagnosis and treatment. Recent technological advances have begun to reveal the true extent of its heterogeneity. Single‐cell analysis (SCA) is emerging as an important approach to detect variations in morphology, genetic or proteomic expression. In this review, we revisit the issue of inter‐ and intra‐tumor heterogeneity, and list various modes of SCA techniques (cell‐based, nucleic acid‐based, protein‐based, metabolite‐based and lipid‐based) presently used for cancer characterization. We further discuss the advantages of SCA over pooled cell analysis, as well as the limitations of conventional techniques. Emerging trends, such as high‐throughput sequencing, are also mentioned as improved means for cancer profiling. Collectively, these applications have the potential for breakthroughs in cancer treatment.