Assessment of ALK Fusions in Uncommon Inflammatory Myofibroblastic Tumors With ALK IHC Positivity but FISH-Equivocal Findings by Targeted RNA Sequencing

Context: Fluorescence in situ hybridization (FISH) and immunohistochemistry (IHC) are common methods to detect ALK status in inflammatory myofibroblastic tumors (IMTs). However, equivocal ALK FISH signals and inconsistency between FISH and IHC are occasionally observed. Objective: To study the inconsistency between FISH and IHC, and clarify ALK status in IMT by targeted RNA sequencing (RNAseq). Conclusions: These findings indicated that RNAseq can simultaneously detect multiple gene fusions and provide fusion forms and breakpoints, which is of great value for differential diagnosis, especially for those uncommon IMTs with equivocal FISH findings, or inconsistency between IHC and FISH. READ ARTICLE

Archives of Pathology & Laboratory Medicine DOI:10.5858/arpa.2021-0230-OA

Authors: Qianlan Yao, Qianming Bai, Xin Zhang, Gang Ji, Heng Chang, Xu Cai, Lin Yu, Jian Wang, Xiaoli Zhu, Xiaoyan Zhou

Case StudyKirk SmithJanuary 18, 2022ALK Fusions, Inflammatory Myofibroblastic Tumors (IMT), ALK IHC Positivity, FISH-Equivocal Findings, Targeted RNA Sequencing

Detection of Multiple Types of Cancer Driver Mutations Using Targeted RNA Sequencing in NSCLC

Currently, DNA and RNA are used separately to capture different types of gene mutations. DNA is commonly used for the detection of SNVs, indels and CNVs; RNA is used for analysis of gene fusion and gene expression. To perform both DNA sequencing (DNA-seq) and RNA-seq, material is divided into two copies, and two different procedures are required for sequencing. Due to overconsumption of samples and experimental process complexity, it is necessary to create an experimental method capable of analyzing SNVs, indels, fusions and expression.We developed an RNA-based hybridization capture panel targeting actionable driver oncogenes in solid tumors and corresponding sample preparation and bioinformatics workflows. Analytical validation with an RNA standard reference containing 16 known fusion mutations and 6 SNV mutations demonstrated a detection specificity of 100.0% [95% CI 88.7%~100.0%] for SNVs and 100.0% [95% CI 95.4%~100.0%] for fusions. The targeted RNA panel achieved a 0.73-2.63 cop..... READ ARTICLEBioRxiv DOI:10.1101/2021.08.25.457723Authors: Sheng Ju, Zihan Cui, Yuayuan Hong, Xiaoqing Wang, Weina Mu, Zhuolin Xie, Xuexia Zeng, Lin Su, Qi Zhang, Xiaofeng Song, Songxia You, Ruixin Chen, Weizhi Chen, Xuchun, Jun Zhao

Review Paper, group3Kirk SmithAugust 26, 2021Cancer Driver Mutations, Targeted RNA Sequencing, NSCLC