Transcript-targeted analysis reveals isoform alterations and double-hop fusions in breast cancer

Shinichi Namba,Katsushige Kawase,Yosuke Tanaka,Fumishi Kishigami,Kenya Kobayashi,Yosuke Togashi,Shusuke Kawashima,Shinya Kojima,Masahito Kawazu,Shoichi Hazama,Satoshi Inoue,Hiroyuki Mano,Noriko Maeda,Toshihide Ueno,Mizuo Ando,Tomoko Ogawa,Yuichi Shiraishi

doi:10.1038/s42003-021-02833-4

Abstract

Although transcriptome alteration is an essential driver of carcinogenesis, the effects of chromosomal structural alterations on the cancer transcriptome are not yet fully understood. Short-read transcript sequencing has prevented researchers from directly exploring full-length transcripts, forcing them to focus on individual splice sites. Here, we develop a pipeline for Multi-Sample long-read Transcriptome Assembly (MuSTA), which enables construction of a transcriptome from long-read sequence data. Using the constructed transcriptome as a reference, we analyze RNA extracted from 22 clinical breast cancer specimens. We identify a comprehensive set of subtype-specific and differentially used isoforms, which extended our knowledge of isoform regulation to unannotated isoforms including a short form TNS3. We also find that the exon–intron structure of fusion transcripts depends on their genomic context, and we identify double-hop fusion transcripts that are transcribed from complex structural rearrangements. For example, a double-hop fusion results in aberrant expression of an endogenous retroviral gene, ERVFRD-1, which is normally expressed exclusively in placenta and is thought to protect fetus from maternal rejection; expression is elevated in several TCGA samples with ERVFRD-1 fusions. Our analyses provide direct evidence that full-length transcript sequencing of clinical samples can add to our understanding of cancer biology and genomics in general.

Highlights

Transcriptome alteration is an essential driver of carcinogenesis, the effects of chromosomal structural alterations on the cancer transcriptome are not yet fully understood
The transcriptome subsequently went through SQANTI27 filtering, and potential artifact transcripts were removed by a random forest algorithm
We obtained a number of uniquely associated full-length non-chimeric (FLNC) reads in each sample; PBcount serves as a complementary measure of isoform expression

Summary

Introduction

Transcriptome alteration is an essential driver of carcinogenesis, the effects of chromosomal structural alterations on the cancer transcriptome are not yet fully understood. Several groups recently conducted comprehensive studies of cancer-specific alternative splicing[2,8,9,10] and showed that RNA alteration affects cancer genes in a manner that complements DNA alteration[2] All of these studies depended on RNAseq technology, which produces relatively short reads and requires imputation to generate full-length transcripts. These analyses were limited to individual splice site abnormalities and could neither directly nor efficiently target consequent transcripts. We constructed a cohort-wide breast cancer transcriptome from directly sequenced transcripts and characterized its complexity and subtype-specific regulation; hundreds of thousands of the isoforms we identified were previously unannotated. Our findings show that transcript-targeted analyses can directly capture a catalog of cancer isoforms originating from complex structural alterations

Methods

Results

Conclusion