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.

Background: Tumor mutational burden (TMB) is an emerging biomarker used to identify patients who are more likely to benefit from immuno-oncology therapy. Aside from various unsettled technical aspects, biological variables such as tumor cell content and intratumor heterogeneity may play an important role in determining TMB. Methods: TMB estimates were determined applying the TruSight Oncology 500 targeted sequencing panel. Spatial and temporal heterogeneity was analyzed by multiregion sequencing (two to six samples) of 24 pulmonary adenocarcinomas and by sequencing a set of matched primary tumors, locoregional lymph node metastases, and distant metastases in five patients. Results: On average, a coding region of 1.28 Mbp was covered with a mean read depth of 609x. Manual validation of the mutation-calls confirmed a good performance, but revealed noticeable misclassification during germline filtering. Different regions within a tumor showed considerable spatial TMB variance in 30% (7 of 24) of the cases (maximum difference, 14.13 mut/Mbp). Lymph node-derived TMB was significantly lower (p ¼ 0.016). In 13 cases, distinct mutational profiles were exclusive to different regions of a tumor, leading to higher values for simulated aggregated TMB. Combined, intratumor heterogeneity and the aggregated TMB could result in divergent TMB designation in 17% of the analyzed patients. TMB variation between primary tumor and distant metastases existed but was not profound. Conclusions: Our data show that, in addition to technical aspects such as germline filtering, the tumor content and spatially divergent mutational profiles within a tumor are relevant factors influencing TMB estimation, revealing limitations of singlesample-based TMB estimations in a clinical context.

Oncogenic gene fusions are important drivers in many cancer types, including carcinomas, with diagnostic and therapeutic implications. Hence, sensitive and rapid methods for parallel profiling in formalin-fixed and paraffin-embedded (FFPE) specimens are needed. In this study we analyzed gene fusions in a cohort of 517 cases where standard treatment options were exhausted. To this end the Archer® DX Solid tumor panel (AMP; 285 cases) and the Oncomine Comprehensive Assay v3 (OCA; 232 cases) were employed. Findings were validated by Sanger sequencing, fluorescence in situ hybridization (FISH) or immunohistochemistry. Both assays demonstrated minimal dropout rates (AMP: 2.4%; n = 7/292, OCA: 2.1%; n = 5/237) with turnaround times of 6–9 working days (median, OCA and AMP, respectively). Hands-on-time for library preparation was 6 h (AMP) and 2 h (OCA). We detected n = 40 fusion-positive cases (7.7%) with TMPRSS2::ERG in prostate cancer being most prevalent (n = 9/40; 22.5%), followed by other gene fusions identified in cancers of unknown primary (n = 6/40; 15.0%), adenoid cystic carcinoma (n = 7/40; 17.5%), and pancreatic cancer (n = 7/40; 17.5%). Our results demonstrate that targeted RNA-sequencing of FFPE samples is feasible, and a well-suited approach for the detection of gene fusions in a routine clinical setting.

Pygo2 acts as a co-activator of Wnt signaling in a nuclear complex with ß-catenin/BCL9/BCL9-2 to increase target gene transcription. Previous studies showed that Pygo2 is upregulated in murine intestinal tumors and human colon cancer, but is apparently dispensable for normal intestinal homeostasis. Here, we have evaluated the in vivo role of Pygo2 during intestinal tumorigenesis using Pygo2 deficient mice. We analyzed chemically induced colon tumor development and conditional intestine specific mouse models harboring either Apc loss-of-function (LOF) or Ctnnb1 gain-of-function (ß-catenin GOF). Remarkably, the number and size of chemically induced tumors was significantly reduced in Pygo2 deficient mice, suggesting that Pygo2 has a tumor promoting function. Furthermore, loss of Pygo2 rescued early tumorigenesis of Ctnnb1 GOF mutants. In contrast, Pygo2 ablation was not sufficient to prevent tumor development of Apc LOF mice. The effect on tumor formation by Pygo2 knockout was linked to the repression of specific deregulated Wnt target genes, in particular of c-Myc. Moreover, the role of Pygo2 appears to be associated with the signaling output of deregulated Wnt signaling in the different tumor models. Thus, targeting Pygo2 might provide a novel strategy to suppress tumor formation in a context dependent manner.

Inflammatory gene signatures are currently being explored as predictive biomarkers for immune checkpoint blockade, and particularly for the treatment of renal cell cancers. From a diagnostic point of view, the nCounter analysis platform and targeted RNA sequencing are emerging alternatives to microarrays and comprehensive transcriptome sequencing in assessing formalin-fixed and paraffin-embedded (FFPE) cancer samples. So far, no systematic study has analyzed and compared the technical performance metrics of these two approaches. Filling this gap, we performed a headto-head comparison of two commercially available immune gene expression assays, using clear cell renal cell cancer FFPE specimens. We compared the nCounter system that utilizes a direct hybridization technology without amplification with an NGS assay that is based on targeted RNA-sequencing with preamplification. We found that both platforms displayed high technical reproducibility and accuracy (Pearson coefficient: ≥0.96, concordance correlation coefficient [CCC]: ≥0.93). A density plot for normalized expression of shared genes on both platforms showed a comparable bi-modal distribution and dynamic range. RNA-Seq demonstrated relatively larger Suranand B. Talla and Eugen Rempel share first authorship. Albrecht Stenzinger and Martina Kirchner share last authorship.

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