Lung cancer is a highly heterogeneous disease. Cancer cells and cells within the tumor microenvironment together determine disease progression, as well as response to or escape from treatment. To map the cell type-specific transcriptome landscape of cancer cells and their tumor microenvironment in advanced non-small cell lung cancer (NSCLC), we analyze 42 tissue biopsy samples from stage III/IV NSCLC patients by single cell RNA sequencing and present the large scale, single cell resolution profiles of advanced NSCLCs. In addition to cell types described in previous single cell studies of early stage lung cancer, we are able to identify rare cell types in tumors such as follicular dendritic cells and T helper 17 cells. Tumors from different patients display large heterogeneity in cellular composition, chromosomal structure, developmental trajectory, intercellular signaling network and phenotype dominance. Our study also reveals a correlation of tumor heterogeneity with tumor associated neutrophils, which might help to shed light on their function in NSCLC.

Sarcomas are malignant soft tissue and bone tumours affecting adults, adolescents and children. They represent a morphologically heterogeneous class of tumours and some entities lack defining histopathological features. Therefore, the diagnosis of sarcomas is burdened with a high inter-observer variability and misclassification rate. Here, we demonstrate classification of soft tissue and bone tumours using a machine learning classifier algorithm based on array-generated DNA methylation data. This sarcoma classifier is trained using a dataset of 1077 methylation profiles from comprehensively pre-characterized cases comprising 62 tumour methylation classes constituting a broad range of soft tissue and bone sarcoma subtypes across the entire age spectrum. The performance is validated in a cohort of 428 sarcomatous tumours, of which 322 cases were classified by the sarcoma classifier. Our results demonstrate the potential of the DNA methylation-based sarcoma classification for research and future diagnostic applications.

The approval of vemurafenib in the US 2011 and in Europe 2012 improved the therapy of not resectable or metastatic melanoma. Patients carrying a substitution of valine to glutamic acid at codon 600 (p.V600E) or a substitution of valine to leucine (p.V600K) in BRAF show complete or partial response. Therefore, the precise identification of the underlying somatic mutations is essential. Herein, we evaluate the sensitivity, specificity and feasibility of six different methods for the detection of BRAF mutations.

Purpose: To identify novel mechanisms of resistance to third-generation EGFR inhibitors in patients with lung adenocarcinoma that progressed under therapy with either AZD9291 or rociletinib (CO-1686). Experimental Design: We analyzed tumor biopsies from seven patients obtained before, during, and/or after treatment with AZD9291 or rociletinib (CO-1686). Targeted sequencing and FISH analyses were performed, and the relevance of candidate genes was functionally assessed in in vitro models. Results: We found recurrent amplification of either MET or ERBB2 in tumors that were resistant or developed resistance to third-generation EGFR inhibitors and show that ERBB2 and MET activation can confer resistance to these compounds. Furthermore, we identified a KRAS^G12S mutation in a patient with acquired resistance to AZD9291 as a potential driver of acquired resistance. Finally, we show that dual inhibition of EGFR/MEK might be a viable strategy to overcome resistance in EGFR-mutant cells expressing mutant KRAS. Conclusions: Our data suggest that heterogeneous mechanisms of resistance can drive primary and acquired resistance to third-generation EGFR inhibitors and provide a rationale for potential combination strategies. Clin Cancer Res; 22(19); 4837–47. ©2016 AACR.

The discovery of oncogenic driver mutations rendering non-small cell lung cancer (NSCLC) targetable by small-molecule inhibitors, and the development of immunotherapies, have revolutionised NSCLC treatment. Today, instead of non-selective chemotherapies, all patients with advanced NSCLC eligible for treatment (and increasing numbers with earlier, less extensive disease) require fast and comprehensive screening of biomarkers for first-line patient selection for targeted therapy, chemotherapy, or immunotherapy (with or without chemotherapy). To avoid unnecessary re-biopsies, biomarker screening before first-line treatment should also include markers that are actionable from second-line onwards; PD-L1 expression testing is also mandatory before initiating treatment. Population differences exist in the frequency of oncogenic driver mutations: EGFR mutations are more frequent in Asia than Europe, whereas the converse is true for KRAS mutations. In addition to approved first-line therapies, a number of emerging therapies are being investigated in clinical trials. Guidelines for biomarker testing vary by country, with the number of actionable targets and the requirement for extensive molecular screening strategies expected to increase. To meet diagnostic demands, rapid screening technologies for single-driver mutations have been implemented. Improvements in DNA- and RNA-based next-generation sequencing technologies enable analysis of a group of genes in one assay; however, turnaround times remain relatively long. Consequently, rapid screening technologies are being implemented alongside next-generation sequencing. Further challenges in the evolving landscape of biomarker testing in NSCLC are actionable primary and secondary resistance mechanisms to targeted therapies. Therefore, comprehensive testing on re-biopsies, collected at the time of disease progression, in combination with testing of circulating tumour DNA may provide important information to guide second- or third-line therapies. Furthermore, longitudinal biomarker testing can provide insights into tumour evolution and heterogeneity during the course of the disease. We summarise best practice strategies for Europe in the changing landscape of biomarker testing at diagnosis and during treatment.