Despite the success of tyrosine kinase-based cancer therapeutics, for most solid tumors the tyrosine kinases that drive disease remain unknown, limiting our ability to identify drug targets and predict response. Here we present the first large-scale survey of tyrosine kinase activity in lung cancer. Using a phosphoproteomic approach, we characterize tyrosine kinase signaling across 41 non-small cell lung cancer (NSCLC) cell lines and over 150 NSCLC tumors. Profiles of phosphotyrosine signaling are generated and analyzed to identify known oncogenic kinases such as EGFR and c-Met as well as novel ALK and ROS fusion proteins. Other activated tyrosine kinases such as PDGFRalpha and DDR1 not previously implicated in the genesis of NSCLC are also identified. By focusing on activated cell circuitry, the approach outlined here provides insight into cancer biology not available at the chromosomal and transcriptional levels and can be applied broadly across all human cancers.

Purpose: To deepen our understanding of mutant ROS1 expression, localization, and frequency in nonsmall cell lung cancer (NSCLC), we developed a highly specific and sensitive immunohistochemistry (IHC)-based assay that is useful for the detection of wild-type and mutant ROS1.Experimental Design: We analyzed 556 tumors with the ROS1 D4D6 rabbit monoclonal antibody IHC assay to assess ROS1 expression levels and localization. A subset of tumors was analyzed by FISH to determine the percentage of these tumors harboring ROS1 translocations. Using specific and sensitive IHC assays, we analyzed the expression of anaplastic lymphoma kinase (ALK), EGFR L858R, and EGFR E746-A750del mutations in a subset of lung tumors, including those expressing ROS1.Results: In our NSCLC cohort of Chinese patients, we identified 9 (1.6%) tumors expressing ROS1 and 22 (4.0%) tumors expressing ALK. FISH identified tumors with ALK or ROS1 rearrangements, and IHC alone was capable of detecting all cases with ALK and ROS1 rearrangements. ROS1 fusion partners were determined by reverse transcriptase PCR identifying CD74-ROS1, SLC34A2-ROS1, and FIG-ROS1 fusions. Some of the ALK and ROS1 rearranged tumors may also harbor coexisting EGFR mutations.Conclusions: NSCLC tumors with ROS1 rearrangements are uncommon in the Chinese population and represent a distinct entity of carcinomas. The ROS1 IHC assay described here is a valuable tool for identifying patients expressing mutant ROS1 and could be routinely applied in clinical practice to detect lung cancers that may be responsive to targeted therapies.

Purpose: Activating mutations within the tyrosine kinase domain of epidermal growth factor receptor (EGFR) are found in approximately 10% to 20% of non^small-cell lung cancer (NSCLC) patients and are associated with response to EGFR inhibitors. The most common NSCLCassociated EGFR mutations are deletions in exon 19 and L858R mutation in exon 21, together accounting for 90% of EGFR mutations. To develop a simple, sensitive, and reliable clinical assay for the identification of EGFR mutations in NSCLC patients, we generated mutation-specific rabbit monoclonal antibodies against each of these two most common EGFR mutations and aimed to evaluate the detection of EGFR mutations in NSCLC patients by immunohistochemistry. Experimental Design:We tested mutation-specific antibodies byWestern blot, immunofluorescence, and immunohistochemistry. In addition, we stained 40 EGFR genotyped NSCLC tumor samples by immunohistochemistry with these antibodies. Finally, with a panel of four antibodies, we screened a large set of NSCLC patient samples with unknown genotype and confirmed the immunohistochemistry results by DNA sequencing. Results: These two antibodies specifically detect the corresponding mutant form of EGFR by Western blotting, immunofluorescence, and immunohistochemistry. Screening a panel of 340 paraffin-embedded NSCLC tumor samples with these antibodies showed that the sensitivity of the immunohistochemistry assay is 92%, with a specificity of 99% as compared with direct and mass spectrometry^based DNA sequencing. Conclusions: This simple assay for detection of EGFR mutations in diagnostic human tissues provides a rapid, sensitive, specific, and cost-effective method to identify lung cancer patients responsive to EGFR-based therapies.Lung cancer is a major cause of cancer-related mortality worldwide and is expected to remain a major health problem for the foreseeable future. Lung cancer is broadly divided into small-cell lung cancer (20% of lung cancers) and non -smallcell lung cancer (NSCLC; 80% of lung cancers). Somatic mutations in the epidermal growth factor receptor (EGFR) gene are found in a subset of NSCLC adenocarcinomas and are associated with sensitivity to the small-molecule EGFR tyrosine kinase inhibitors gefitinib (1, 2) and erlotinib (3). Different EGFR mutations have been reported, but the most common NSCLC-associated EGFR mutations are in-frame deletions in exon 19 (E746_A750del) and the point mutation replacing leucine with arginine at codon 858 in exon 21 (L858R; refs. 3 -5). These two mutations represent 85% to 90% of EGFR mutations in NSCLC patients. Data from clinical research have confirmed that patients with these mutations are highly responsive to EGFR inhibitors including gefitinib and erlotinib (5 -8).Based on these clinical findings, EGFR mutational analysis in lung adenocarcinoma may now be used to guide treatment decisions and to enroll patients in specific arms of clinical trials. Direct DNA sequencing of PCR-amplified genomic DNA has been developed to detect EGFR mutations i...

Pulmonary abnormalities, dysfunction or hyper-reactivity occurs in association with inflammatory bowel disease (IBD) more frequently than previously recognized. Emerging evidence suggests that subtle inflammation exists in the airways among IBD patients even in the absence of any bronchopulmonary symptoms, and with normal pulmonary functions. The pulmonary impairment is more pronounced in IBD patients with active disease than in those in remission. A growing number of case reports show that the IBD patients develop rapidly progressive respiratory symptoms after colectomy, with failure to isolate bacterial pathogens on repeated sputum culture, and often request oral corticosteroid therapy. All the above evidence indicates that the inflammatory changes in both the intestine and lung during IBD. Clinical or subclinical pulmonary inflammation accompanies the main inflammation of the bowel. Although there are clinical and epidemiological reports of chronic inflammation of the pulmonary and intestinal mucosa in IBD, the detailed mechanisms of pulmonary-intestinal crosstalk remain unknown. The lung has no anatomical connection with the main inflammatory site of the bowel. Why does the inflammatory process shift from the gastrointestinal tract to the airways? The clinical and subclinical pulmonary abnormalities, dysfunction, or hyper-reactivity among IBD patients need further evaluation. Here, we give an overview of the concordance between chronic inflammatory reactions in the airways and the gastrointestinal tract. A better understanding of the possible mechanism of the crosstalk among the distant organs will be beneficial in identifying therapeutic strategies for mucosal inflammatory diseases such as IBD and allergy.

We evaluated whether the optimal selection of CT reconstruction settings enables the construction of a radiomics model to predict epidermal growth factor receptor (EGFR) mutation status in primary lung adenocarcinoma (LAC) using standard of care CT images. Fifty-one patients (EGFR:wildtype = 23:28) with LACs of clinical stage I/II/IIIA were included in the analysis. The LACs were segmented in four conditions, two slice thicknesses (Thin: 1 mm; Thick: 5 mm) and two convolution kernels (Sharp: B70f/B70s; Smooth: B30f/B31f/B31s), which constituted four groups: (1) Thin-Sharp, (2) Thin-Smooth, (3) Thick-Sharp, and (4) Thick-Smooth. Machine learning algorithms selected and combined 1,695 quantitative image features to build prediction models. The performance of prediction models was assessed by calculating the area under the curve (AUC). The best prediction model yielded AUC (95%CI) = 0.83 (0.68, 0.92) using the Thin-Smooth reconstruction setting. The AUC of models using thick slices was significantly lower than that of thin slices (P < 10−3), whereas the impact of reconstruction kernel was not significant. Our study showed that the optimal prediction of EGFR mutational status in early stage LACs was achieved by using thin CT-scan slices, independently of convolution kernels. Results from the prediction model suggest that tumor heterogeneity is associated with EGFR mutation.

Accurate segmentation of lung cancer in pathology slides is a critical step in improving patient care. We proposed the ACDC@LungHP (Automatic Cancer Detection and Classification in Whole-slide Lung Histopathology) challenge for evaluating different computer-aided diagnosis (CADs) methods on the automatic diagnosis of lung cancer. The ACDC@LungHP 2019 focused on segmentation (pixel-wise detection) of cancer tissue in whole slide imaging (WSI), using an annotated dataset of 150 training images and 50 test images from 200 patients. This paper reviews this challenge and summarizes the top 10 submitted methods for lung cancer segmentation. All methods were evaluated us

Aberrant DNA methylation plays a critical role in the development and progression of many types of cancer. To investigate whether DNA methylation is abnormal in thymic epithelial tumors (TETs), we analyzed global methylation levels and the methylation status of 9 tumor suppressor gene (TSG) promoters in 65 TET samples. We found evidence of TSG promoter hypermethylation and decreased TSG expression in severe TETs. Furthermore, relative to early-stage TETs, global DNA methylation levels were reduced and DNA methyltransferase expression was increased in advanced-stage TETs. Our results suggest that aberrant DNA methylation is associated with TET development.

GPC3 and KRT19 overexpression are associated with carcinogenesis, progression, and poor prognosis in patients with PDAC and a valuable biomarker for diagnosis of PDAC.