Combined targeted DNA and RNA sequencing of advanced NSCLC in routine molecular diagnostics: Analysis of the first 3,000 Heidelberg cases.
Anna-Lena VolckmarJonas LeichsenringMartina KirchnerPetros ChristopoulosOlaf NeumannJan BudcziesCristiano Manuel Morais de OliveiraEugen RempelIvo BuchhalterRegine BrandtMichael AllgäuerSuranand Babu TallaMoritz von WinterfeldEsther HerpelBenjamin GoeppertAmelie LierHauke WinterTilman BrummerStefan FröhlingMartin FaehlingJürgen R FischerClaus Peter HeußelFelix HerthFelix LasitschkaPeter SchirmacherMichael ThomasVolker EndrisRoland PenzelAlbrecht StenzingerPublished in: International journal of cancer (2019)
Tyrosine kinase inhibitors currently confer the greatest survival gain for nonsmall cell lung cancer (NSCLC) patients with actionable genetic alterations. Simultaneously, the increasing number of targets and compounds poses the challenge of reliable, broad and timely molecular assays for the identification of patients likely to benefit from novel treatments. Here, we demonstrate the feasibility and clinical utility of comprehensive, NGS-based genetic profiling for routine workup of advanced NSCLC based on the first 3,000 patients analyzed in our department. Following automated extraction of DNA and RNA from formalin-fixed, paraffin-embedded tissue samples, parallel sequencing of DNA and RNA for detection of mutations and gene fusions, respectively, was performed using PCR-based enrichment with an ion semiconductor sequencing platform. Overall, 807 patients (27%) were eligible for currently approved, EGFR-/BRAF-/ALK- and ROS1-directed therapies, while 218 additional cases (7%) with MET, ERBB2 (HER2) and RET alterations could potentially benefit from experimental targeted compounds. In addition, routine capturing of comutations, e.g. TP53 (55%), KEAP1 (11%) and STK11 (11%), as well as the precise typing of fusion partners and involved exons in case of actionable translocations including ALK and ROS1, are prognostic and predictive tools currently gaining importance for further refinement of therapeutic and surveillance strategies. The reliability, low dropout rates (<5%), minimal tissue requirements, fast turnaround times (6 days on average) and lower costs of the diagnostic approach presented here compared to sequential single-gene testing, highlight its practicability in order to support individualized decisions in routine patient care, enrollment in molecularly stratified clinical trials, as well as translational research.
Keyphrases
- end stage renal disease
- small cell lung cancer
- ejection fraction
- single cell
- newly diagnosed
- clinical trial
- chronic kidney disease
- advanced non small cell lung cancer
- genome wide
- prognostic factors
- high throughput
- single molecule
- tyrosine kinase
- cell death
- epidermal growth factor receptor
- drug delivery
- deep learning
- dna damage
- gene expression
- circulating tumor
- oxidative stress
- mesenchymal stem cells
- machine learning
- room temperature
- cancer therapy
- cell therapy
- phase ii
- hiv infected
- patient reported
- study protocol
- open label
- chronic myeloid leukemia
- sensitive detection