Strength in numbers: predicting response to checkpoint inhibitors from large clinical datasets.

The advent of immune checkpoint blockers for cancer therapy has spawned great interest in identifying molecular features reflecting the complexity of tumor immunity, which can subsequently be leveraged as predictive biomarkers. In a thorough big-data approach analyzing the largest series of homogenized molecular and clinical datasets, Litchfield et al. identified a set of genomic biomarkers that identifies immunotherapy responders across cancer types.

KRAS and TP53 co-mutation predicts benefit of immune checkpoint blockade in lung adenocarcinoma.

BACKGROUND: Predictive biomarkers in use for immunotherapy in advanced non-small cell lung cancer are of limited sensitivity and specificity. We analysed the potential of activating KRAS and pathogenic TP53 mutations to provide additional predictive information. METHODS: The study cohort included 713 consecutive immunotherapy patients with advanced lung adenocarcinomas, negative for actionable genetic alterations. Additionally, two previously published immunotherapy and two surgical patient cohorts were analyzed. Therapy benefit was stratified by KRAS and TP53 mutations. Molecular characteristics underlying KRASmut/TP53mut tumours were revealed by the analysis of TCGA data. RESULTS: An interaction between KRAS and TP53 mutations was observed in univariate and multivariate analyses of overall survival (Hazard ratio [HR] = 0.56, p = 0.0044 and HR = 0.53, p = 0.0021) resulting in a stronger benefit for KRASmut/TP53mut tumours (HR = 0.71, CI 0.55-0.92). This observation was confirmed in immunotherapy cohorts but not observed in surgical cohorts. Tumour mutational burden, proliferation, and PD-L1 mRNA were significantly higher in TP53-mutated tumours, regardless of KRAS status. Genome-wide expression analysis revealed 64 genes, including CX3CL1 (fractalkine), as specific transcriptomic characteristic of KRASmut/TP53mut tumours. CONCLUSIONS: KRAS/TP53 co-mutation predicts ICI benefit in univariate and multivariate survival analyses and is associated with unique molecular tumour features. Mutation testing of the two genes can be easily implemented using small NGS panels.

Therapeutic drug monitoring of osimertinib in non-small cell lung cancer and short bowel syndrome: A case report.

Short bowel syndrome (SBS) following extensive intestinal resection is often characterized by impaired absorption of orally administered drugs, including tyrosine kinase inhibitors (TKI). We report the case of a patient with EGFR-mutated non-small cell lung carcinoma treated with 80 mg/day of the TKI osimertinib who achieved partial response of the tumour, but was subsequently subjected to a double-barrelled jejunostomy due to ileus. Due to the development of SBS after the bypass surgery, plasma concentrations of osimertinib were monitored using mass spectrometry. The therapeutic drug monitoring confirmed a malabsorption of osimertinib in the patient (108 ng/mL, which is below the 5th percentile of the expected plasma concentration) and was useful to guide adjustments of TKI dosing in order to achieve adequate blood levels (161 ng/mL after increase of the dose to 120 mg/day) in order to maintain tumour control.

Real-world data for precision cancer medicine-A European perspective.

Leveraging real-world data (RWD) for drug access is necessary to overcome a key challenge of modern precision oncology: tackling numerous low-prevalence oncogenic mutations across cancers. Withholding a potentially active medication in patients with rare mutations for the sake of control chemotherapy or "best" supportive care is neither practicable nor ethically justifiable anymore, particularly as RWD could meanwhile be used instead, according to scientific principles outlined by the US Food and Drug Administration, European Medicines Agency and other stakeholders. However, practical implementation varies, with occasionally opposite recommendations based on the same evidence in different countries. In the face of growing need for precision drugs, more transparency of evaluation, a priori availability of guidance for the academia and industry, as well as a harmonized framework for health technology assessment across the European Union (EU) are imperative. These could in turn trigger infrastructural changes in national and pan-European registries, cancer management guidelines (e.g., frequency of routine radiologic restaging, inclusion of patient-reported outcomes), and the health data space, to ensure conformity with declared standards and facilitate extraction of RWD sets (including patient-level data) suitable for approval and pricing with minimal effort. For an EU-wide unification of precision cancer medicine, collective negotiation of drug supply contracts and funding solidarity would additionally be required to handle the financial burden. According to experience from pivotal European programs, off-label use could potentially also be harmonized across EU-states to accelerate availability of novel drugs, streamline collection of valuable RWD, and mitigate related costs through wider partnerships with pharmaceutical companies.

Artificial intelligence and pathology: From principles to practice and future applications in histomorphology and molecular profiling.

The complexity of diagnostic (surgical) pathology has increased substantially over the last decades with respect to histomorphological and molecular profiling. Pathology has steadily expanded its role in tumor diagnostics and beyond from disease entity identification via prognosis estimation to precision therapy prediction. It is therefore not surprising that pathology is among the disciplines in medicine with high expectations in the application of artificial intelligence (AI) or machine learning approaches given their capabilities to analyze complex data in a quantitative and standardized manner to further enhance scope and precision of diagnostics. While an obvious application is the analysis of histological images, recent applications for the analysis of molecular profiling data from different sources and clinical data support the notion that AI will enhance both histopathology and molecular pathology in the future. At the same time, current literature should not be misunderstood in a way that pathologists will likely be replaced by AI applications in the foreseeable future. Although AI will transform pathology in the coming years, recent studies reporting AI algorithms to diagnose cancer or predict certain molecular properties deal with relatively simple diagnostic problems that fall short of the diagnostic complexity pathologists face in clinical routine. Here, we review the pertinent literature of AI methods and their applications to pathology, and put the current achievements and what can be expected in the future in the context of the requirements for research and routine diagnostics.

Fusion-positive non-small cell lung carcinoma: Biological principles, clinical practice, and diagnostic implications.

Based on superior efficacy and tolerability, targeted therapy is currently preferred over chemotherapy and/or immunotherapy for actionable gene fusions that occur in late-stage non-small cell lung carcinoma (NSCLC). Consequently, current clinical practice guidelines mandate testing for ALK, ROS1, NTRK, and RET gene fusions in all patients with newly diagnosed advanced non-squamous NSCLC (NS-NSCLC). Gene fusions can be detected using different approaches, but today RNA next-generation sequencing (NGS) or combined DNA/RNA NGS is the method of choice. The discovery of other gene fusions (involving, eg, NRG1, NUT, FGFR1, FGFR2, MET, BRAF, EGFR, SMARC fusions) and their partners has increased progressively in recent years, leading to the development of new and promising therapies and mandating the development and implementation of comprehensive detection methods. The purpose of this review is to focus on recent data concerning the main gene fusions identified in NSCLC, followed by the discussion of major challenges in this domain.

Assigning evidence to actionability: An introduction to variant interpretation in precision cancer medicine.

Modern concepts in precision cancer medicine are based on increasingly complex genomic analyses and require standardized criteria for the functional evaluation and reporting of detected genomic alterations in order to assess their clinical relevance. In this article, we propose and address the necessary steps in systematic variant evaluation consisting of bioinformatic analysis, functional annotation and clinical interpretation, focusing on the latter two aspects. We discuss the role and clinical application of current variant classification systems and point out their scope and limitations. Finally, we highlight the significance of the molecular tumor board as a platform for clinical decision-making based on genomic analyses.

Precision oncology for intrahepatic cholangiocarcinoma in clinical practice.

BACKGROUND: Advanced cholangiocarcinoma has a poor prognosis. Molecular targeted approaches have been proposed for patients after progression under first-line chemotherapy treatment. Here, molecular profiling of intrahepatic cholangiocarcinoma in combination with a comprehensive umbrella concept was applied in a real-world setting. METHODS: In total, 101 patients received molecular profiling and matched treatment based on interdisciplinary tumour board decisions in a tertiary care setting. Parallel DNA and RNA sequencing of formalin-fixed paraffin-embedded tumour tissue was performed using large panels. RESULTS: Genetic alterations were detected in 77% of patients and included gene fusions in 21 patients. The latter recurrently involved the FGFR2 and the NRG1 gene loci. The most commonly altered genes were BAP1, ARID1A, FGFR2, IDH1, CDKN2A, CDKN2B, PIK3CA, TP53, ATM, IDH2, BRAF, SMARCA4 and FGFR3. Molecular targets were detected in 59% of patients. Of these, 32% received targeted therapy. The most relevant reason for not initiating therapy was the deterioration of performance status. Patients receiving a molecular-matched therapy showed a significantly higher survival probability compared to patients receiving conventional chemotherapy only (HR: 2.059, 95% CI: 0.9817-4.320, P < 0.01). CONCLUSIONS: Molecular profiling can be successfully translated into clinical treatment of intrahepatic cholangiocarcinoma patients and is associated with prolonged survival of patients receiving a molecular-matched treatment.

Genomic architecture of FGFR2 fusions in cholangiocarcinoma and its implication for molecular testing.

BACKGROUND: Cholangiocarcinoma (CCA) is a primary malignancy of the biliary tract with a dismal prognosis. Recently, several actionable genetic aberrations were identified with significant enrichment in intrahepatic CCA, including FGFR2 gene fusions with a prevalence of 10-15%. Recent clinical data demonstrate that these fusions are druggable in a second-line setting in advanced/metastatic disease and the efficacy in earlier lines of therapy is being evaluated in ongoing clinical trials. This scenario warrants standardised molecular profiling of these tumours. METHODS: A detailed analysis of the original genetic data from the FIGHT-202 trial, on which the approval of Pemigatinib was based, was conducted. RESULTS: Comparing different detection approaches and displaying representative cases, we described the genetic landscape and architecture of FGFR2 fusions in iCCA and show biological and technical aspects to be considered for their detection. We elaborated parameters, including a suggestion for annotation, that should be stated in a molecular diagnostic FGFR2 report to allow a complete understanding of the analysis performed and the information provided. CONCLUSION: This study provides a detailed presentation and dissection of the technical and biological aspects regarding FGFR2 fusion detection, which aims to support molecular pathologists, pathologists and clinicians in diagnostics, reporting of the results and decision-making.

Deciphering the immunosuppressive tumor microenvironment in ALK- and EGFR-positive lung adenocarcinoma.

INTRODUCTION: The advent of immune checkpoint blockade (ICB) has led to significantly improved disease outcome in lung adenocarcinoma (ADC), but response of ALK/EGFR-positive tumors to immune therapy is limited. The underlying immune biology is incompletely understood. METHODS: We performed comparative mRNA expression profiling of 31 ALK-positive, 40 EGFR-positive and 43 ALK/EGFR-negative lung ADC focused on immune gene expression. The presence and levels of tumor infiltration lymphocytes (TILs) as well as fourteen specific immune cell populations were estimated from the gene expression profiles. RESULTS: While total TILs were not lower in ALK-positive and EGFR-positive tumors compared to ALK/EGFR-negative tumors, specific immunosuppressive characteristics were detected in both subgroups: In ALK-positive tumors, regulatory T cells were significantly higher compared to EGFR-positive (fold change: FC = 1.9, p = 0.0013) and ALK/EGFR-negative tumors (FC = 2.1, p = 0.00047). In EGFR-positive tumors, cytotoxic cells were significantly lower compared to ALK-positive (FC = - 1.7, p = 0.016) and to ALK/EGFR-negative tumors (FC = - 2.1, p = 2.0E-05). A total number of 289 genes, 40 part of cytokine-cytokine receptor signaling, were differentially expressed between the three subgroups. Among the latter, five genes were differently expressed in both ALK-positive and EGFR-positive tumors, while twelve genes showed differential expression solely in ALK-positive tumors and eleven genes solely in EGFR-positive tumors. CONCLUSION: Targeted gene expression profiling is a promising tool to read out tumor microenvironment characteristics from routine diagnostic lung cancer biopsies. Significant immune reactivity including specific immunosuppressive characteristics in ALK- and EGFR-positive lung ADC, but not a total absence of immune infiltration supports further clinical evaluation of immune-modulators as partners of ICB in such tumors.

KRAS/GNAS-testing by highly sensitive deep targeted next generation sequencing improves the endoscopic ultrasound-guided workup of suspected mucinous neoplasms of the pancreas.

Pancreatic cysts or dilated pancreatic ducts are often found by cross-sectional imaging, but only mucinous lesions can become malignant. Therefore, distinction between mucinous and non-mucinous lesions is crucial for adequate patient management. We performed a prospective study including targeted next generation sequencing (NGS) of cell-free DNA in the diagnostic endoscopic ultrasound (EUS)-guided workup. Pancreatic cyst(s) or main duct fluid obtained by EUS-guided FNA was analysed by carcinoembryonic antigen (CEA), cytology and deep targeted NGS of 14 known gastrointestinal cancer genes (AKT1, BRAF, CTNNB1, EGFR, ERBB2, FBXW7, GNAS, KRAS, MAP2K1, NRAS, PIK3CA, SMAD4, TP53, APC) with a limit of detection down to variant allele frequency of 0.01%. Results were correlated to histopathology and clinical follow-up. One hundred and thirteen patients with pancreatic cyst(s) and/or a dilated pancreatic main duct (≥5 mm) were screened. Sixty-six patients had to be excluded, mainly due to inoperability or small cyst size (≤10 mm). Forty-seven patients were enrolled for further analysis. A final diagnosis was available in 27 cases including 8 negative controls. In 43/47 (91.5%) of patients a KRAS- and/or GNAS-mutation was diagnosed by NGS. 27.0% of the KRAS-mutated and 10.0% of the GNAS-mutated lesions harbored multiple mutations. KRAS/GNAS-testing by NGS, cytology, and CEA had a sensitivity and specificity of 94.7/100%, 38.1/100%, and 42.1/75.0%, respectively. KRAS/GNAS-testing was significantly superior to CEA (P = .0209) and cytology (P = .0016). In conclusion, KRAS/GNAS-testing by deep targeted NGS is a suitable method to distinguish mucinous from non-mucinous pancreatic lesions, suggesting its usage as a single diagnostic test. Results must be confirmed in a larger cohort.

Automated sample preparation with SP3 for low-input clinical proteomics.

High-throughput and streamlined workflows are essential in clinical proteomics for standardized processing of samples from a variety of sources, including fresh-frozen tissue, FFPE tissue, or blood. To reach this goal, we have implemented single-pot solid-phase-enhanced sample preparation (SP3) on a liquid handling robot for automated processing (autoSP3) of tissue lysates in a 96-well format. AutoSP3 performs unbiased protein purification and digestion, and delivers peptides that can be directly analyzed by LCMS, thereby significantly reducing hands-on time, reducing variability in protein quantification, and improving longitudinal reproducibility. We demonstrate the distinguishing ability of autoSP3 to process low-input samples, reproducibly quantifying 500-1,000 proteins from 100 to 1,000 cells. Furthermore, we applied this approach to a cohort of clinical FFPE pulmonary adenocarcinoma (ADC) samples and recapitulated their separation into known histological growth patterns. Finally, we integrated autoSP3 with AFA ultrasonication for the automated end-to-end sample preparation and LCMS analysis of 96 intact tissue samples. Collectively, this constitutes a generic, scalable, and cost-effective workflow with minimal manual intervention, enabling reproducible tissue proteomics in a broad range of clinical and non-clinical applications.

[Variant interpretation in molecular pathology and oncology : An introduction]. / Varianteninterpretation in der molekularen Pathologie und Onkologie : Eine Einführung.

Increasingly extensive genomic diagnostics in cancer precision medicine require uniform evaluation criteria for the classification of variants with regard to their functional and therapeutic implications. In this review we present the most important guidelines and classification systems currently used in daily clinical practice, explain their advantages and disadvantages as well as differences and similarities, and present the step-by-step, systematic process that enables successful variant interpretation.

NTRK testing: First results of the QuiP-EQA scheme and a comprehensive map of NTRK fusion variants and their diagnostic coverage by targeted RNA-based NGS assays.

Gene fusions involving the three neurotrophic tyrosine receptor kinase genes NTRK1, NTRK2, or NTRK3 were identified as oncogenic drivers in many cancer types. Two small molecule inhibitors have been tested in clinical trials recently and require the detection of a NTRK fusion gene prior to therapeutic application. Fluorescence in situ hybridization (FISH) and targeted next-generation sequencing (tNGS) assays are commonly used for diagnostic profiling of gene fusions. In the presented study we applied an external quality assessment (EQA) scheme in order to investigate the suitability of FISH and RNA-/DNA-based tNGS for detection of NTRK fusions in a multinational and multicentric ring trial. In total 27 participants registered for this study. Nine institutions took part in the FISH-based and 18 in the NGS-based round robin test, the latter additionally subdivided into low-input and high-input NGS methods (regarding nucleic acid input). Regardless of the testing method applied, all participants received tumor sections of 10 formalin-fixed and paraffin-embedded (FFPE) tissue blocks for in situ hybridization or RNA/DNA extraction, and the results were submitted via an online questionnaire. For FISH testing, eight of nine (88.8%) participants, and for NGS-based testing 15 of 18 (83.3%) participants accomplished the round robin test successfully. The overall high success rate demonstrates that FISH- and tNGS-based NTRK testing can be well established in a routine diagnostic setting. Complementing this dataset, we provide an updated in silico analysis on the coverage of more than 150 NTRK fusion variants by several commercially available RNA-based tNGS panels.

Immuno-oncology gene expression profiling of formalin-fixed and paraffin-embedded clear cell renal cell carcinoma: Performance comparison of the NanoString nCounter technology with targeted RNA sequencing.

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 head-to-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 signaling intensity whereas the nCounter system displayed higher inter-sample variability. Estimated fold changes for all shared genes showed high correlation (Spearman coefficient: 0.73). This agreement is even better when only significantly differentially expressed genes were compared. Composite gene expression profiles, such as an interferon gamma (IFNg) signature, can be reliably inferred by both assays. In summary, our study demonstrates that focused transcript read-outs can reliably be achieved by both technologies and that both approaches achieve comparable results despite their intrinsic technical differences.

Testing NTRK testing: Wet-lab and in silico comparison of RNA-based targeted sequencing assays.

NTRK fusions involving three neurotrophic tyrosine receptor kinase genes NTRK1, NTRK2, and NTRK3 and a variety of fusion partners were identified as oncogenic drivers across many cancer types. Drugs that target the chimeric protein product require the identification of the underlying gene fusion. This advocates the diagnostic use of molecular assays ranging from fluorescence in situ hybridization (FISH) and reverse transcription polymerase chain reaction (RT-PCR)/Sanger approaches to targeted next-generation sequencing (NGS). Immunohistochemistry may be used as a screening tool and adjunct diagnostic assay in this context. Although FISH and RT-PCR/Sanger approaches are widely adopted in routine diagnostics, current experience with targeted RNA-based NGS is limited. Here, we report on the analysis of major assays (TruSight TST170 and TruSight RNA Fusion [Illumina]; Archer FusionPlex Solid Tumor, Archer FusionPlex Lung, and Archer FusionPlex Oncology [Archer]; Oncomine Comprehensive Assay v3 RNA and Oncomine Focus RNA [Thermo Fisher Scientific]) that are commercially available. The data set includes performance results of a multicentric comparative wet-lab study as well as an in silico analysis on the ability to detect the broad range of NTRK fusions reported until now. A test algorithm that reflects assay methodology is provided. This data will support implementation of targeted RNA sequencing in routine diagnostics and inform screening and testing strategies that have been brought forward.

Integrated clinicomolecular characterization identifies RAS activation and CDKN2A deletion as independent adverse prognostic factors in cancer of unknown primary.

Cancer of unknown primary (CUP) denotes a malignancy with histologically confirmed metastatic spread while the primary tumor remains elusive. Here, we address prognostic and therapeutic implications of mutations and copy number variations (CNVs) detected in tumor tissue in the context of a comprehensive clinical risk assessment. Targeted panel sequencing was performed in 252 CUP patients. 71.8% of patients had unfavorable CUP according to ESMO guidelines. 74.7% were adeno- and 13.7% squamous cell carcinomas. DNA was extracted from microdissected formalin-fixed, paraffin-embedded tissues. For library preparation, mostly multiplex PCR-based Ion Torrent AmpliSeq™ technology with Oncomine comprehensive assays was used. Most frequent genetic alterations were mutations/deletions of TP53 (49.6%), CDKN2A (19.0%) and NOTCH1 (14.1%) as well as oncogenic activation of KRAS (23.4%), FGFR4 (14.9%) and PIK3CA (10.7%). KRAS activation was predominantly found in adenocarcinomas (p = 0.01), PIK3CA activation in squamous cell carcinomas (p = 0.03). Male sex, high ECOG score, unfavorable CUP, higher number of involved organs and RAS activation predicted decreased event-free and overall survival in multivariate analysis. Deletions of CDKN2A were prognostically adverse regarding overall survival. TP53 mutations did not significantly influence prognosis in the overall cohort, but worsened prognosis in otherwise favorable CUP subtypes. Although not standard in CUP, for 17/198 (8.6%) patients molecularly targeted treatment was recommended and 10 patients (5.1%) were treated accordingly. In conclusion, besides the identification of drug targets, panel sequencing in CUP is prognostically relevant, with RAS activation and CDKN2A deletion emerging as novel independent risk factors in a comprehensive assessment with clinicopathological data.

Global DNA methylation reflects spatial heterogeneity and molecular evolution of lung adenocarcinomas.

Lung adenocarcinoma (ADC) is the most prevalent subtype of lung cancer and characterized by considerable morphological and mutational heterogeneity. However, little is known about the epigenomic intratumor variability between spatially separated histological growth patterns of ADC. In order to reconstruct the clonal evolution of histomorphological patterns, we performed global DNA methylation profiling of 27 primary tumor regions, seven matched normal tissues and six lymph node metastases from seven ADC cases. Additionally, we investigated the methylation data from 369 samples of the TCGA ADC cohort. All regions showed varying degrees of methylation changes between segments of different, but also of the same growth patterns. Similarly, copy number variations were seen between spatially distinct segments of each patient. Hierarchical clustering of promoter methylation revealed extensive heterogeneity within and between the cases. Intratumor DNA methylation heterogeneity demonstrated a branched clonal evolution of ADC regions driven by genomic instability with subclonal copy number changes. Notably, methylation profiles within tumors were not more similar to each other than to those from other individuals. In two cases, different tumor regions of the same individuals were represented in distant clusters of the TCGA cohort, illustrating the extensive epigenomic intratumor heterogeneity of ADCs. We found no evidence for the lymph node metastases to be derived from a common growth pattern. Instead, they had evolved early and separately from a particular pattern in each primary tumor. Our results suggest that extensive variation of epigenomic features contributes to the molecular and phenotypic heterogeneity of primary ADCs and lymph node metastases.

Variant classification in precision oncology.

Next-generation sequencing has become a cornerstone of therapy guidance in cancer precision medicine and an indispensable research tool in translational oncology. Its rapidly increasing use during the last decade has expanded the options for targeted tumor therapies, and molecular tumor boards have grown accordingly. However, with increasing detection of genetic alterations, their interpretation has become more complex and error-prone, potentially introducing biases and reducing benefits in clinical practice. To facilitate interdisciplinary discussions of genetic alterations for treatment stratification between pathologists, oncologists, bioinformaticians, genetic counselors and medical scientists in specialized molecular tumor boards, several systems for the classification of variants detected by large-scale sequencing have been proposed. We review three recent and commonly applied classifications and discuss their individual strengths and weaknesses. Comparison of the classifications underlines the need for a clinically useful and universally applicable variant reporting system, which will be instrumental for efficient decision making based on sequencing analysis in oncology. Integrating these data, we propose a generalizable classification concept featuring a conservative and a more progressive scheme, which can be readily applied in a clinical setting.

Targeted deep sequencing of effusion cytology samples is feasible, informs spatiotemporal tumor evolution, and has clinical and diagnostic utility.

During the course of disease, many cancer patients eventually present with metastatic disease including peritoneal or pleural spread. In this context, cytology specimens derived from ascites or pleural effusion may help to differentiate malignant from benign conditions and sometimes yield diagnosis of a malignancy. However, even when supported by immunohistochemistry, cytological interpretation can be challenging, especially if tumor cellularity is low. Here, we investigated whether targeted deep sequencing of formalin-fixed and paraffin embedded (FFPE) cytology specimens of cancer patients is feasible, and has diagnostic and clinical impact. To this end, a cohort of 20 matched pairs was compiled, each comprising a cytology sample (FFPE cell block) and at least one biopsy/surgical resection specimen serving as benchmark. In addition, 5 non-malignant effusions were sequenced serving as negative-controls. All samples yielded sufficient libraries and were successfully subjected to targeted sequencing employing a semiconductor based next-generation sequencing platform. Using gene panels of different size and composition, including the Oncomine Comprehensive Assay, for targeted sequencing, somatic mutations were detected in the tissue of all 20 cases. Of these, 15 (75%) harbored mutations that were also detected in the corresponding cytology samples. In four of these cases (20%), additional private mutations were detected in either cytology or tissue samples, reflecting spatiotemporal tumor evolution. Of the five remaining cases, three (15%) showed wild type alleles in cytology material whereas tumor tissue had mutations in interrogated genes. Two cases were discordant, showing different private mutations in the cytology and in the tissue sample, respectively. In summary, sequencing of cytology specimens (FFPE cell block) reflecting spatiotemporal tumor evolution is feasible and yields adjunct genetic information that may be exploitable for diagnostics and therapy.