Dataset Information

Pan-tumor survey of ROS1 fusions detected by next-generation RNA and whole transcriptome sequencing.

ABSTRACT:

Background

Two ROS1 tyrosine kinase inhibitors have been approved for ROS1 fusion positive (ROS1+) non-small cell lung cancer (NSCLC) tumors. We performed a pan-tumor analysis of the incidence of ROS1 fusions to assess if more ROS1+ patients who could benefit from ROS1 TKIs could be identified.

Methods

A retrospective analysis of ROS1 positive solid malignancies identified by targeted RNA sequencing and whole transcriptome sequencing of clinical tumor samples performed at Caris Life Science (Phoenix, AZ).

Results

A total of 259 ROS1+ solid malignancies were identified from approximately 175,350 tumors that underwent next-generation sequencing (12% from targeted RNA sequencing [Archer]; 88% from whole transcriptome sequencing). ROS1+ NSCLC constituted 78.8% of the ROS1+ solid malignancies, follow by glioblastoma (GBM) (6.9%), and breast cancer (2.7%). The frequency of ROS1 fusion was approximately 0.47% among NSCLC, 0.29% for GBM, 0.04% of breast cancer. The mean tumor mutation burden for all ROS1+ tumors was 4.8 mutations/megabase. The distribution of PD-L1 (22C3) expression among all ROS1+ malignancies were 0% (18.6%), 1%-49% (29.4%), and ≥ 50% (60.3%) [for NSCLC: 0% (17.8%); 1-49% (27.7%); ≥ 50% (53.9%). The most common genetic co-alterations of ROS1+ NSCLC were TP53 (29.1%), SETD2 (7.3%), ARIAD1A (6.3%), and U2AF1 (5.6%).

Conclusions

ROS1+ NSCLC tumors constituted the majority of ROS1+ solid malignancies with four major fusion partners. Given that > 20% of ROS1+ solid tumors may benefit from ROS1 TKIs treatment, comprehensive genomic profiling should be performed on all solid tumors.

SUBMITTER: Nagasaka M

PROVIDER: S-EPMC10585918 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature

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Publications

Pan-tumor survey of ROS1 fusions detected by next-generation RNA and whole transcriptome sequencing.

Nagasaka Misako M Zhang Shannon S SS Baca Yasmine Y Xiu Joanne J Nieva Jorge J Vanderwalde Ari A Swensen Jeffrey J JJ Spetzler David D Korn Wolfgang Michael WM Raez Luis E LE Liu Stephen V SV Ou Sai-Hong Ignatius SI

BMC cancer 20231018 1

<h4>Background</h4>Two ROS1 tyrosine kinase inhibitors have been approved for ROS1 fusion positive (ROS1+) non-small cell lung cancer (NSCLC) tumors. We performed a pan-tumor analysis of the incidence of ROS1 fusions to assess if more ROS1+ patients who could benefit from ROS1 TKIs could be identified.<h4>Methods</h4>A retrospective analysis of ROS1 positive solid malignancies identified by targeted RNA sequencing and whole transcriptome sequencing of clinical tumor samples performed at Caris Li ...[more]

PMID: 37853341

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Project description:BACKGROUND:Next-Generation Sequencing (NGS) technology has exceptionally increased the ability to sequence DNA in a massively parallel and cost-effective manner. Nevertheless, NGS data analysis requires bioinformatics skills and computational resources well beyond the possibilities of many "wet biology" laboratories. Moreover, most of projects only require few sequencing cycles and standard tools or workflows to carry out suitable analyses for the identification and annotation of genes, transcripts and splice variants found in the biological samples under investigation. These projects can take benefits from the availability of easy to use systems to automatically analyse sequences and to mine data without the preventive need of strong bioinformatics background and hardware infrastructure. RESULTS:To address this issue we developed an automatic system targeted to the analysis of NGS data obtained from large-scale transcriptome studies. This system, we named NGS-Trex (NGS Transcriptome profile explorer) is available through a simple web interface http://www.ngs-trex.org and allows the user to upload raw sequences and easily obtain an accurate characterization of the transcriptome profile after the setting of few parameters required to tune the analysis procedure. The system is also able to assess differential expression at both gene and transcript level (i.e. splicing isoforms) by comparing the expression profile of different samples.By using simple query forms the user can obtain list of genes, transcripts, splice sites ranked and filtered according to several criteria. Data can be viewed as tables, text files or through a simple genome browser which helps the visual inspection of the data. CONCLUSIONS:NGS-Trex is a simple tool for RNA-Seq data analysis mainly targeted to "wet biology" researchers with limited bioinformatics skills. It offers simple data mining tools to explore transcriptome profiles of samples investigated taking advantage of NGS technologies.

Dataset Information

Pan-tumor survey of ROS1 fusions detected by next-generation RNA and whole transcriptome sequencing.

Background

Methods

Results

Conclusions

Publications

Pan-tumor survey of ROS1 fusions detected by next-generation RNA and whole transcriptome sequencing.

Similar Datasets

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