Press Release

Phasing analysis of lung cancer genomes using a long read sequencer

Release:Jun 21, 2022 Update:Jan 11, 2023
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Professor Yutaka Suzuki and Associate Professor Ayako Suzuki of the Department of Computational Biology and Medical Sciences in the Graduate School of Frontier Sciences led the research project.


Chromosomal backgrounds of cancerous mutations still remain elusive. Here, we conduct the phasing analysis of non-small cell lung cancer specimens of 20 Japanese patients. By the combinatory use of short and long read sequencing data, we obtain long phased blocks of 834 kb in N50 length with >99% concordance rate. By analyzing the obtained phasing information, we reveal that several cancer genomes harbor regions in which mutations are unevenly distributed to either of two haplotypes. Large-scale chromosomal rearrangement events, which resemble chromothripsis events but have smaller scales, occur on only one chromosome, and these events account for the observed biased distributions. Interestingly, the events are characteristic of EGFR mutation-positive lung adenocarcinomas. Further integration of long read epigenomic and transcriptomic data reveal that haploid chromosomes are not always at equivalent transcriptomic/epigenomic conditions. Distinct chromosomal backgrounds are responsible for later cancerous aberrations in a haplotype-specific manner.


Publication: Nature Communications (June 16, 2022)
Title: Phasing analysis of lung cancer genomes using a long read sequencer
Authors: Yoshitaka Sakamoto, Shuhei Miyake, Miho Oka, Akinori Kanai, Yosuke Kawai, Satoi Nagasawa, Yuichi Shiraishi, Katsushi Tokunaga, Takashi Kohno, Masahide Seki, Yutaka Suzuki, Ayako Suzuki

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