In non‐small cell lung cancer (NSCLC), immune checkpoint inhibitors (ICIs) significantly improve overall survival (OS). Tumor mutational burden (TMB) has emerged as a predictive biomarker for patients treated with ICIs. Here, we evaluated the predictive power of TMB measured by the Oncomine™ Tumor Mutational Load targeted sequencing assay in 76 NSCLC patients treated with ICIs. TMB was assessed retrospectively in 76 NSCLC patients receiving ICI therapy. Clinical data (RECIST 1.1) were collected and patients were classified as having either durable clinical benefit (DCB) or no durable benefit (NDB). Additionally, genetic alterations and PD‐L1 expression were assessed and compared with TMB and response rate. TMB was significantly higher in patients with DCB than in patients with NDB (median TMB = 8.5 versus 6.0 mutations/Mb, Mann–Whitney p = 0.0244). 64% of patients with high TMB (cut‐off = third tertile, TMB ≥ 9) were responders (DCB) compared to 33% and 29% of patients with intermediate and low TMB, respectively (cut‐off = second and first tertile, TMB = 5–9 and TMB ≤ 4, respectively). TMB‐high patients showed significantly longer progression‐free survival (PFS) and OS (log‐rank test p = 0.0014 for PFS and 0.0197 for OS). While identifying different subgroups of patients, combining PD‐L1 expression and TMB increased the predictive power (from AUC 0.63 to AUC 0.65). Our results show that the TML panel is an effective tool to stratify patients for ICI treatment. A combination of biomarkers might maximize the predictive precision for patient stratification. Our study supports TMB evaluation through targeted NGS in NSCLC patient samples as a tool to predict response to ICI therapy. We offer recommendations for a reliable and cost‐effective assessment of TMB in a routine diagnostic setting. © 2019 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Tumor mutational burden (TMB) has emerged as a promising predictive biomarker for immune checkpoint inhibitor therapy. While the feasibility of TMB analysis on formalin-fixed paraffin-embedded (FFPE) samples has been thoroughly evaluated, only limited analyses have been performed on cytological samples, and no dedicated study has investigated concordance of TMB between different sample types. Here, we assessed TMB on matched histological and cytological samples from lung cancer patients and evaluated the accuracy of TMB estimation in these sample types. We analyzed mutations and resulting TMB in FFPE samples and matched ethanol-fixed cytological smears (n = 12 matched pairs) by using a targeted next-generation sequencing assay (Oncomine™ Tumor Mutational Load). Two different variant allele frequency (VAF) thresholds were used to estimate TMB (VAF = 5% or 10%). At 5% VAF threshold, 73% (107/147) of mutations were concordantly detected in matched histological and cytological samples. Discordant variants were mainly unique to FFPE samples (34/40 discordant variants) and mostly C:G > T:A transitions with low allelic frequency, likely indicating formalin fixation artifacts. Increasing the VAF threshold to 10% clearly increased the number of concordantly detected mutations in matched histological and cytological samples to 96% (100/106 mutations), and drastically reduced the number of FFPE-only mutations (from 34 to 4 mutations). In contrast, cytological samples showed consistent mutation count and TMB values at both VAF thresholds. Using FFPE samples, 2 out of 12 patients were classified as TMB-high at VAF cutoff of 5% but TMB-low at 10%, whereas cytological specimens allowed consistent patient classification independently from VAF cutoff. Our results show that cytological smears provide more consistent TMB values due to high DNA quality and lack of formalin-fixation induced artifacts. Therefore, cytological samples should be the preferred sample type for robust TMB estimation.

Molecular profiling of solid tumors facilitates personalized, targeted therapeutic interventions. The ability to perform next-generation sequencing (NGS), especially from small tissue samples, in a short turnaround time (TAT) is essential to providing results that enable rapid clinical decisions. This multicenter study evaluated the performance of a CE in vitro diagnostic (IVD) assay, the Oncomine Dx Express Test, on the Ion Torrent Genexus System for detecting DNA and RNA variants in solid tumors. Eighty-two archived formalin-fixed paraffin embedded (FFPE) tissue samples from lung, colorectal, central nervous system, melanoma, breast, gastric, thyroid, and soft tissue cancers were used to assess the presence of single nucleotide variants (SNVs), insertions and deletions (indels), copy number variations (CNVs), gene fusions, and splice variants. These clinical samples were previously characterized at the various academic centers using orthogonal methods. The Oncomine Dx Express Test showed high performance with 100% concordance with previous characterization for SNVs, indels, CNVs, gene fusions, and splice variants. SNVs and indels with allele frequencies as low as 5% were correctly identified. The test detected all the expected ALK, RET, NTRK1, and ROS1 fusion isoforms and MET exon 14-skipping splice variants. The average TAT from extracted nucleic acids to the final variant report was 18.3 h. The Oncomine Dx Express Test in combination with the Ion Torrent Genexus System is a CE-IVD-compliant, performant, and multicenter reproducible method for NGS detection of actionable biomarkers from a range of tumor samples, providing results in a short TAT that could support timely decision- making for targeted therapeutic interventions.

Introduction: Colorectal carcinoma (CRC) is among the most common carcinomas in women and men. In the advanced stage, patients are treated based on the RAS status. Recent studies indicate that in the future, in addition to KRAS and NRAS, alterations in other genes, such as PIK3CA or TP53, will be considered for therapy. Therefore, it is important to know the mutational landscape of routinely diagnosed CRC. Method: We report the molecular profile of 512 Swiss CRC patients analyzed by targeted next-generation sequencing as part of routine diagnostics at our institute. Results: Pathogenic and likely pathogenic variants were found in 462 (90%) CRC patients. Variants were detected in TP53 (54.3%), KRAS (48.2%), PIK3CA (15.6%), BRAF (13.5%), SMAD4 (10.5%), FBXW7 (7.8%), NRAS (3.5%), PTEN (2.7%), ERBB2 (1.6%), AKT1 (1.5%), and CTNNB1 (0.9%). The remaining pathogenic alterations were found in the genes ATM(n= 1), MAP2K1(n= 1), and IDH2(n= 1). Discussion/Conclusions: Our analysis revealed the prevalence of potential predictive markers in a large cohort of CRC patients obtained during routine diagnostic analysis. Furthermore, our study is the first of this size to uncover the molecular landscape of CRC in Switzerland.

Personalized treatment of metastatic non-squamous non-small cell lung cancer (NSCLC) requires detailed molecular characterization of the tumour including detection of predictive driver mutations and programmed death ligand 1 (PD-L1) expression. Complete detection is influenced by the amount of tumour cells sampled as well as their quality. Different sampling techniques may be necessary to provide sufficient tumour material for comprehensive molecular characterization. Missing the detection of targetable molecular genetic aberrations would have a serious impact on the quality of life and prognosis of a patient. This case report highlights the importance of biopsy technique in a patient with NSCLC. Several procedures—pleural puncture, transthoracic lung biopsy and endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA)—could not provide sufficient tumour material for precise tumour characterization. Only the addition of EBUS-guided transbronchial lymph node cryobiopsy (EBUS-TBLNC) enabled complete immunohistochemical and genetic tumour characterization, demonstrating PD-L1 expression in 100% of the tumour cells in the absence of actionable genetic alterations. Based on these results, immunotherapy was initiated.

Immune checkpoint inhibitors (ICI) significantly improve clinical outcome of advanced non-small cell lung cancer (NSCLC) patients. However, as only a subset of patients responds to treatment, there is an urgent need for predictive biomarkers. Here we investigated the association of TCR-beta (TCRB) clonal expansion and convergence with treatment response. We assessed these features within the tumor microenvironment of treatment naïve patients and compared their predictive value with other biomarkers such as tumor mutational burden (TMB) and PD-L1 status. Total RNA was extracted from NSCLC FFPE pretreatment tissue biopsies of patients receiving ICI therapy (n = 45). TCRB repertoire NGS libraries were prepared with the Oncomine TCRB-SR assay and sequenced on the Ion Torrent instrument. TCR convergence (=frequency of clonotypes identical in amino acid but different in nucleotide space) and clonal evenness (=measurement of the similarity of clone sizes) were evaluated independently using Fisher’s test. TMB values from the same biopsies were assessed from extracted genomic DNA via the Oncomine Tumor Mutation Load Assay. PD-L1 status was determined by immunohistochemical staining. Durable clinical benefit from ICI therapy was associated with increased TCR convergence (p = 0.12) and decreased clonal evenness (p = 0.01) independently. The TCR-based patient classification was able to identify responders who otherwise had low to intermediate (<9 Mutations per Mb) TMB or negative (<1%) PD-L1 status. Adding TCR evenness to TMB and PD-L1-based stratification allowed for the identification of 82% of responders, compared to 47% for TMB alone and to the identification of 94% of responders, compared to 59% for PD-L1 alone. Our results show that evaluation of the TCR-beta repertoire in NSCLC specimens is an effective tool to stratify patients according to their response to ICI therapy. In particular, TCR assessment identifies subpopulations of responding patients that would otherwise be misclassified by either TMB or PD-L1 status. Thus, combinatorial use of several biomarkers may yield the highest clinical accuracy for ICI therapy selection. Philip Jermann. Thermo Fisher Scientific. P. Jermann: Honoraria (self), Research grant / Funding (institution), Travel / Accommodation / Expenses: Thermo Fisher Scientific; Research grant / Funding (institution): BMS. K. Leonards: Research grant / Funding (institution): Thermo Fisher Scientific; Research grant / Funding (institution): Bristol-Myers Squibb. T. Looney: Full / Part-time employment: Thermo Fisher Scientific. I. Alborelli: Research grant / Funding (institution), Travel / Accommodation / Expenses: Thermo Fisher Scientific; Research grant / Funding (institution): Bristol-Myers Squibb. S.I. Rothschild: Honoraria (self), Research grant / Funding (institution): AstraZeneca; Honoraria (self), Research grant / Funding (institution): BMS; Research grant / Funding (institution): Merck Serono; Honoraria (self): MSD; Honoraria (self): Roche; Honoraria (self): Novartis. S. Savic Prince: Honoraria (self), Advisory / Consultancy: MSD; Advisory / Consultancy: AstraZeneca; Honoraria (self): Roche. A. Zippelius: Advisory / Consultancy: BMS; Advisory / Consultancy, Research grant / Funding (institution): Roche; Advisory / Consultancy: MSD; Advisory / Consultancy: NBE Therapeutics; Research grant / Funding (institution): Secarna; Research grant / Funding (institution): Beyondsprings; Research grant / Funding (institution): Crescendo; Research grant / Funding (institution): Hookipa. L. Bubendorf: Honoraria (self), Research grant / Funding (institution): Roche; Honoraria (self), Research grant / Funding (institution): MSD; Honoraria (self): BMS; Honoraria (self): AstraZeneca. All other authors have declared no conflicts of interest.