PHLI-seq: Constructing and Visualizing Cancer Genomic Maps in 3D by Phenotype-based High-throughput Laser-aided Isolation and Sequencing

Overview

Journal Genome Biol

Specialties Biology
Genetics

Date 2018 Oct 10

PMID 30296938

Citations 9

Authors

Sungsik Kim

Amos Chungwon Lee

Han-Byoel Lee

Jinhyun Kim

Yushin Jung

Han Suk Ryu

Yongju Lee

Sangwook Bae

Minju Lee

Kyungmin Lee

Ryong Nam Kim

Woong-Yang Park

Wonshik Han

Sunghoon Kwon

Affiliations

Soon will be listed here.

Abstract

Spatial mapping of genomic data to tissue context in a high-throughput and high-resolution manner has been challenging due to technical limitations. Here, we describe PHLI-seq, a novel approach that enables high-throughput isolation and genome-wide sequence analysis of single cells or small numbers of cells to construct genomic maps within cancer tissue in relation to the images or phenotypes of the cells. By applying PHLI-seq, we reveal the heterogeneity of breast cancer tissues at a high resolution and map the genomic landscape of the cells to their corresponding spatial locations and phenotypes in the 3D tumor mass.

Citing Articles

Spatial transcriptomic profiling of isolated microregions in tissue sections utilizing laser-induced forward transfer.

Ye K, Chang W, Xu J, Guo Y, Qin Q, Dang K PLoS One. 2024; 19(7):e0305977.

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Mapping cancer biology in space: applications and perspectives on spatial omics for oncology.

Lee S, Kim G, Lee J, Lee A, Kwon S Mol Cancer. 2024; 23(1):26.

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Hema-seq reveals genomic aberrations in a rare simultaneous occurrence of hematological malignancies.

Jeong D, Lee A, Shin K, Kim J, Ham M, Lee C Cell Rep Methods. 2023; 3(10):100617.

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Barcoded multiple displacement amplification for high coverage sequencing in spatial genomics.

Kim J, Kim S, Yeom H, Song S, Shin K, Bae S Nat Commun. 2023; 14(1):5261.

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Spatial epitranscriptomics reveals A-to-I editome specific to cancer stem cell microniches.

Lee A, Lee Y, Choi A, Lee H, Shin K, Lee H Nat Commun. 2022; 13(1):2540.

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