Background: Gene fusions represent promising targets for cancer therapy in lung cancer. Reliable detection of multiple gene fusions is therefore essential. Methods: Five commercially available parallel sequencing assays were evaluated for their ability to detect gene fusions in eight cell lines and 18 FFPE tissue samples carrying a variety of known gene fusions. Four RNA-based assays and one DNA-based assay were compared; two were hybrid capture-based, TruSight Tumor 170 Assay (Illumina) and SureSelect XT HS Custom Panel (Agilent), and three were amplicon-based, Archer FusionPlex Lung Panel (ArcherDX), QIAseq RNAscan Custom Panel (Qiagen) and Oncomine Focus Assay (Thermo Fisher Scientific). Results: The Illumina assay detected all tested fusions and showed the smallest number of false positive results. Both, the ArcherDX and Qiagen panels missed only one fusion event. Among the RNA-based assays, the Qiagen panel had the highest number of false positive events. The Oncomine Focus Assay (Thermo Fisher Scientific) was the least adequate assay for our purposes, seven fusions were not covered by the assay and two fusions were classified as uncertain. The DNA-based SureSelect XT HS Custom Panel (Agilent) missed three fusions and nine fusions were only called by one software version. Additionally, many false positive fusions were observed. Conclusions: In summary, especially RNA-based parallel sequencing approaches are potent tools for reliable detection of targetable gene fusions in clinical diagnostics.

Over the last years, massively parallel sequencing has rapidly evolved and has now transitioned into molecular pathology routine laboratories. It is an attractive platform for analysing multiple genes at the same time with very little input material. Therefore, the need for high quality DNA obtained from automated DNA extraction systems has increased, especially to those laboratories which are dealing with formalin-fixed paraffin-embedded (FFPE) material and high sample throughput. This study evaluated five automated FFPE DNA extraction systems as well as five DNA quantification systems using the three most common techniques, UV spectrophotometry, fluorescent dye-based quantification and quantitative PCR, on 26 FFPE tissue samples. Additionally, the effects on downstream applications were analysed to find the most suitable pre-analytical methods for massively parallel sequencing in routine diagnostics. The results revealed that the Maxwell 16 from Promega (Mannheim, Germany) seems to be the superior system for DNA extraction from FFPE material. The extracts had a 1.3–24.6-fold higher DNA concentration in comparison to the other extraction systems, a higher quality and were most suitable for downstream applications. The comparison of the five quantification methods showed intermethod variations but all methods could be used to estimate the right amount for PCR amplification and for massively parallel sequencing. Interestingly, the best results in massively parallel sequencing were obtained with a DNA input of 15 ng determined by the NanoDrop 2000c spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). No difference could be detected in mutation analysis based on the results of the quantification methods. These findings emphasise, that it is particularly important to choose the most reliable and constant DNA extraction system, especially when using small biopsies and low elution volumes, and that all common DNA quantification techniques can be used for downstream applications like massively parallel sequencing.

Outcome of immune checkpoint inhibition in cancer can be predicted by measuring PDL1 expression of tumor cells. Search for additional biomarkers led to tumor mutational burden (TMB) as surrogate marker for neoantigens presented. While TMB was previously determined via whole exome sequencing (WES), there have been approaches with comprehensive gene panels as well. We sequenced samples derived from formalin-fixed tumors, aPOLEmutated cell line and standard DNA by WES and five different panels. If available, normal tissue was also exome sequenced. Sequencing data was analyzed by commercial software solutions and an in-house pipeline. A robust Pearson correlation (R = 0.9801 ± 0.0167; mean ± sd; N = 7) was determined for the different panels in a tumor paired normal setting for WES. Expanded analysis on tumor only exome sequenced samples yielded similar correlation (R = 0.9439 ± 0.0632; mean ± sd; N = 14). Remaining germline variants increased TMB in WES by 5.761 ± 1.953 (mean ± sd.; N = 7) variants per megabase (v/mb) for samples including synonymous variants and 3.883 ± 1.38 v/mb for samples without synonymous variants compared to tumor-normal paired calling results. Due to limited sample numbers in this study, additional replication is suggested for a clinical setting. Remaining germline variants in a tumor-only setting and artifacts caused by different library chemistries construction might affect the results.

Comprehensive molecular genotyping of lung cancers has become a key requirement for guiding therapeutic decisions. As a paradigm model of implementing next-generation comprehensive diagnostics, Network Genomic Medicine (NGM) has established central diagnostic and clinical trial platforms for centralised testing and decentralised personalised treatment in clinical practice. Here, we describe the structures of the NGM network and give a summary of technologies to identify patients with anaplastic lymphoma kinase (ALK) fusion-positive lung adenocarcinomas. As unifying test platforms will become increasingly important for delivering reliable, quick and affordable tests, the NGM diagnostic platform is currently implementing a comprehensive hybrid capture-based parallel sequencing pan-cancer assay.

MET tyrosine kinase receptor pathway activation has become an important actionable target in solid tumors. Aberrations in the MET proto-oncogene, including MET overexpression, the activation of MET mutations, MET mutations that lead to MET exon 14 skipping, MET gene amplifications, and MET fusions, are known to be primary and secondary oncogenic drivers in cancer; these aberrations have evolved as predictive biomarkers in clinical diagnostics. Thus, the detection of all known MET aberrations in daily clinical care is essential. In this review, current molecular technologies for the detection of the different MET aberrations are highlighted, including the benefits and drawbacks. In the future, another focus will be on the standardization of detection technologies for the delivery of reliable, quick, and affordable tests in clinical molecular diagnostics.

Due to limitations in local therapy approaches for sinonasal tumors, improvement in systemic therapies plays a pivotal role for prolongation of the patient’s survival. The aim of this study was to examine potential biomarkers, including deficiency in mismatch repair proteins (dMMR)/microsatellite instability (MSI-H) in sinonasal cancers and their precancerous lesions. A comprehensive analysis of 10 sinonasal cancer cell lines by whole exome sequencing, screening 174 sinonasal tumors by immunohistochemistry (IHC) for mismatch repair deficiency and next generation sequencing (NGS) of 136 tumor samples revealed a dMMR/MSI-H sinonasal squamous cell carcinoma (SNSCC) cell line based on a somatic missense mutation in MLH1 and an overall frequency of dMMR/MSI-H SNSCC of 3.2% (4/125). Targetable EGFR mutations were found in 89.3% (25/28) of inverted sinonasal papilloma (ISP) and in 60% (6/10) of ISP-associated carcinomas. While PIK3CA and EGFR mutations were not mutually exclusive, KRAS mutated tumors were an EGFR-wildtype. The effect of potential driver mutations in FGFR2, FGFR3, BRAF, HRAS, MAP2K1, PTEN, NOTCH1 and CARD11 need further investigation. Our results suggest that biomarker testing, including MMR-IHC and NGS panel analysis, should be integrated into the diagnostics of clinically aggressive ISPs and SNSCC to assess prognosis and facilitate therapeutic decisions.