Faculty Bibliography

The 2011 International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society international multidisciplinary classification of lung adenocarcinoma introduced the new categories of adenocarcinoma in situ, minimally invasive adenocarcinoma, and invasive mucinous adenocarcinoma, and replaced the category of mixed subtype adenocarcinoma with lepidic, acinar, papillary, micropapillary, and solid predominant adenocarcinoma. The aim of this manuscript is to evaluate whether the new classification can be applied successfully in determining prognosis of surgically resected patients. Six consecutive clinicopathologic studies using the new classification that were published between spring 2011 and fall 2012 were reviewed. Overall, they demonstrated excellent outcome for adenocarcinoma in situ and minimally invasive adenocarcinoma; intermediate outcome for lepidic, acinar, and papillary predominant adenocarcinoma; and poor outcome for solid and micropapillary predominant adenocarcinoma and invasive mucinous adenocarcinoma. As the new classification remains a proposal at this time, it is hoped that thoracic surgeons will play a leading role in its worldwide dissemination for clinical care and research.

Purpose: To assess whether automated texture analysis of CT images enables discrimination among pathologic classes of lung adenocarcinomas, and thus serves as an in vivo biomarker of lung cancer prognosis. Materials and Methods: Chest CTs of 30 nodules in 30 patients with resected adenocarcinomas were evaluated by a pulmonary pathologist who classified each resected cancer according to the International Association for the Study of Lung Cancer (IASLC) system. The categories included adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), lepidic-predominant adenocarcinoma (LPA), and other invasive adenocarcinomas (INV). 3D volumes of interest (VOIs) and 2D regions of interest (ROIs) were then constructed for each nodule. A comprehensive set of N=279 texture parameters were computed for both 3D and 2D regions. Clustering and classification of these parameters were performed with linear discriminant analysis (LDA) using features determined by optimal subsets. Results: Of the 30 adenocarcinomas, there were 13 INV, 11 LPA, 3 MIA, and 3 AIS. AIS and MIA groups were analyzed together. With all 3 classes, LDA classified 17 of 30 nodules correctly using the nearest neighbor (k=1) method. When only the two largest classes (INV and LPA) were used, 21 of 24 nodules were classified correctly. With 3 classes and 2D texture analysis, and when using only the two largest groups, LDA was able to correctly classify all nodules. Conclusion: CT texture parameters determined by optimal subsets allows for effective clustering of adenocarcinoma classes. These results suggest the potential use of automated (or computer-assisted) CT image analysis to predict the invasive pathologic character of lung nodules. Our approach overcomes the limitations of current radiologic interpretation, such as subjectivity, interand intra-observer variability, and the effect of reader experience

Lung adenocarcinoma, the most common subtype of non-small cell lung cancer, is responsible for more than 500,000 deaths per year worldwide. Here, we report exome and genome sequences of 183 lung adenocarcinoma tumor/normal DNA pairs. These analyses revealed a mean exonic somatic mutation rate of 12.0 events/megabase and identified the majority of genes previously reported as significantly mutated in lung adenocarcinoma. In addition, we identified statistically recurrent somatic mutations in the splicing factor gene U2AF1 and truncating mutations affecting RBM10 and ARID1A. Analysis of nucleotide context-specific mutation signatures grouped the sample set into distinct clusters that correlated with smoking history and alterations of reported lung adenocarcinoma genes. Whole-genome sequence analysis revealed frequent structural rearrangements, including in-frame exonic alterations within EGFR and SIK2 kinases. The candidate genes identified in this study are attractive targets for biological characterization and therapeutic targeting of lung adenocarcinoma.

CONTEXT: In March 2009, a novel swine-origin influenza A/H1N1 virus was identified. After global spread, the World Health Organization in June declared the first influenza pandemic in 41 years. OBJECTIVE: To describe the clinicopathologic characteristics of 34 people who died following confirmed A/H1N1 infection with emphasis on the pulmonary pathology findings. DESIGN: We reviewed medical records, autopsy reports, microbiologic studies, and microscopic slides of 34 people who died between May 15 and July 9, 2009, and were investigated either by the New York City Office of Chief Medical Examiner (32 deaths) or through the consultation service of a coauthor (2 deaths). RESULTS: Most of the 34 decedents (62%) were between 25 and 49 years old (median, 41.5 years). Tracheitis, bronchiolitis, and diffuse alveolar damage were noted in most cases. Influenza viral antigen was observed most commonly in the epithelium of the tracheobronchial tree but also in alveolar epithelial cells and macrophages. Most cases were reverse transcription-polymerase chain reaction positive for influenza. Histologic and microbiologic autopsy evidence of bacterial pneumonia was detected in 55% of cases. Underlying medical conditions including cardiorespiratory diseases and immunosuppression were present in 91% of cases. Obesity (body mass index, >30) was noted in 72% of adult and adolescent cases. CONCLUSIONS: The pulmonary pathologic findings in fatal disease caused by the novel pandemic influenza virus are similar to findings identified in past pandemics. Superimposed bacterial infections of the respiratory tract were common. Preexisting obesity, cardiorespiratory diseases, and other comorbidities also were prominent findings among the decedents