Factors Impacting Clinically Relevant RNA Fusion Assays Using Next-Generation Sequencing

Abstract

Context.— RNA-based next-generation sequencing (NGS) assays are being used with increasing frequency for comprehensive molecular profiling of solid tumors. Objective.— To evaluate factors that might impact clinical assay performance. Design.— A 4-month retrospective review of cases analyzed by a targeted RNA-based NGS assay to detect fusions was performed. RNA extraction was performed from formalin-fixed, paraffin-embedded tissue sections and/or cytology smears of 767 cases, including 493 in-house and 274 outside referral cases. The types of samples included 422 core needle biopsy specimens (55%), 268 resection specimens (35%), and 77 cytology samples (10%). Results.— Successful NGS fusion testing was achieved in 697 specimens (90.9%) and correlated positively with RNA yield (P < .001) and negatively with specimen necrosis (P = .002), decalcification (P < .001), and paraffin block age of more than 2 years (P = .001). Of the 697 cases that were successfully sequenced, 50 (7.2%) had clinically relevant fusions. The testing success rates and fusion detection rates were similar between core needle biopsy and cytology samples. In contrast, RNA fusion testing was often less successful using resection specimens (P = .007). Testing success was independent of the tumor percentage in the specimen, given that at least 20% tumor cellularity was present. Conclusions.— The success of RNA-based NGS testing is multifactorial and is influenced by RNA quality and quantity. Identification of preanalytical factors affecting RNA quality and yield can improve NGS testing success rates.

Metastatic hepatocellular carcinoma to the bone diagnosed by fine needle aspiration in a veteran population

“…Many patients are not able to undergo an invasive tissue biopsy because of comorbidities or the sample procured being not insufficient for molecular analysis or degeneration due to decalcification methods. 33,34 In such cases, a minimally invasive technique like FNA plays a vital role for obtaining the tissue diagnosis, as well as for molecular testing. In this era of targeted diagnostics, various cytological substrates are increasingly being used for molecular analysis of solid organ malignancies.…”

“…Currently, molecular testing is becoming more and more important to direct the oncologic care of patients. Many patients are not able to undergo an invasive tissue biopsy because of comorbidities or the sample procured being not insufficient for molecular analysis or degeneration due to decalcification methods 33,34 . In such cases, a minimally invasive technique like FNA plays a vital role for obtaining the tissue diagnosis, as well as for molecular testing.…”

Technical aspects of the use of cytopathological specimens for diagnosis and predictive testing in malignant epithelial neoplasms of the lung

“…The literature on RNA fusion analysis by NGS is limited, at least where cytological preparations are concerned 140‐144 . The pre‐analytical factors were examined in one study 144 which analysed 767 cases, consisting of 55% core biopsies, 10% cytology cases (CBs and smears), and the remainder resection specimens. Roughly half were lung carcinomas.…”

“…The literature on RNA fusion analysis by NGS is limited, at least where cytological preparations are concerned. [140][141][142][143][144] The preanalytical factors were examined in one study 144 There was no relation with tumour fraction, provided it was >20%.…”

Targeted RNA-sequencing analysis for fusion transcripts detection in tumor diagnostics: assessment of bioinformatic tools reliability in FFPE samples

“…Several pre-analytical variables can in fact negatively affect the library quality, including the handling of the surgical specimens and RNA fragmentation related to formalin-fixation (as it happens, moreover, for RT-PCR). Both issues negatively impact nucleic acids quality, introducing unpredictable biases that ultimately lead to low-coverage and/or low-quality reads [8]. Beyond nucleic acids quality, bioinformatic analysis of fusion transcripts is also challenging since all existing methods suffer, at least in part, from poor prediction accuracy.…”